RU2779946C2 - Individualized anti-tumor vaccines - Google Patents

Abstract

FIELD: pharmaceutics; medicine.

SUBSTANCE: object 1 is a method for the production of an individualized vaccine for use in the treatment or prevention of cancer, including the effective amount of recombinant polyepitope polypeptide containing mutation-based neoepitopes, which are the result of cancer-specific somatic mutations in a cancer sample of a patient with cancer, or nucleic acid encoding the specified polyepitope polypeptide, where mutation-based neoepitopes are cross-linked together by means of peptide bonds or linkers. The method includes stages of identification of cancer-specific somatic mutations in the cancer sample of the patient with cancer to obtain a signature of patient’s cancer mutations and to obtain a vaccine, a characteristic feature of which is the obtained cancer mutation signature. Objects 2 and 3 are an individualized vaccine for use in the treatment or prevention of cancer. Object 4 is a method for the treatment of a patient with cancer, including the administration of a vaccine to the patient.

EFFECT: creation of an individualized antitumor vaccine due to obtaining an active vaccine start based on cancer-specific somatic mutations in a cancer sample of a patient with cancer.

30 cl, 21 dwg, 8 tbl, 9 ex

Description

Technical field

The present invention relates to the production of vaccines that are specific to patient tumors and are potentially useful in primary tumor immunotherapy as well as tumor metastases.

State of the art

Malignancies are the leading cause of death, causing 1 out of every 4 deaths. Treatment of malignant neoplasms has traditionally been based on the law of averages, that is, use what works best for the largest number of patients. However, due to molecular heterogeneity in cancers, often less than 25% of treated individuals benefit from approved therapies. Personalized medicine, based on tailored patient care, is seen as a potential solution to low-efficiency, high-cost innovations in drug development.

Antigen-specific immunotherapy, which aims to increase or induce an immune response in patients, has been successfully used in cancer control. T cells play a central role in cell-mediated immunity in humans and animals. Recognition and binding of a particular antigen is mediated by T cell receptors (TCR) expressed on the surface of T cells. The T cell receptor (TCR) of T cells is capable of interacting with immunogenic peptides (epitopes) associated with major histocompatibility complex (MHC) molecules and presented on the surface of target cells. Specific binding of the TCR transmits a signaling cascade into the T cell, leading to proliferation and differentiation into the mature effector T cell.

The identification of a growing number of pathogen and tumor specific antigens (TAA) is leading to a large collection of suitable immunotherapy targets. Cells presenting immunogenic peptides (epitopes) isolated from these antigens can be specifically targeted using an active or passive immunization strategy. Active immunization can lead to the induction and expansion of antigen-specific T cells in patients that are able to specifically recognize and destroy diseased cells. Various antigenic formats can be used for anti-tumor vaccination, including whole cancer cells, proteins, peptides, or immunizing vectors such as RNA, DNA or viral vectors, which can be applied directly in vivo or in vitro by DC stimulation followed by transfer to the patient.

Malignant neoplasms can result from the accumulation of genomic mutations and epigenetic changes, some of which may be the cause of the disease. In addition to tumor-specific antigens, human cancers carry an average of 100-120 non-synonymous mutations, of which many can be targets for vaccines. More than 95% of mutations in a tumor are unique and specific to the patient (Weide et al. 2008: J. Immunother. 31, 180-188). The number of somatic protein-altering mutations that can result in tumor-specific T cell epitopes ranges from 30 to 400. It has been predicted in silico that there are 40-60 HLA class I restricted epitopes isolated from tumor-specific cells per patient per patient. somatic mutations (Azuma et al. 1993: Nature 366, 76-79). In addition, also as a result of tumor-specific mutations, de novo HLA class II-restricted epitopes are likely to arise, but their number is still unknown.

It should be noted that some non-synonymous mutations are randomly involved in neoplastic transformation, which is critical for maintaining the oncogenic phenotype (driver mutations) and may represent a potential “Achilles heel” of cancer cells. As such, non-synonymous mutations are not subject to central immune system tolerance, and they may be ideal candidates for the development of individual cancer vaccines. Mutations found in the primary tumor may also be present in metastases. However, some studies have shown that, during tumor evolution, a patient's metastatic tumors acquire additional genetic mutations that are often clinically important (Suzuki et al. 2007: Mol. Oncol. 1 (2), 172-180; Campbell et al. 2010: Nature 467 (7319), 1109-1113). In addition, also the molecular characteristics of many metastases have significant deviations from those of primary tumors.

The technical problem underlying the present invention is to obtain a highly effective individualized antitumor vaccine.

The present invention is based on the identification of patient-specific tumor mutations and the targeted impact on the patient-specific "signature" of tumor mutations. Specifically, the present invention, which involves sequencing a genome, preferably an exome or a transcriptome, is based on an individualized immunotherapy approach and aims to target a plurality of individual tumor mutations immunotherapeutically. Sequencing using Next Generation Sequencing (NGS) technologies allows rapid and cost effective identification of patient-specific tumor mutations.

The identification of non-synonymous point mutations resulting in amino acid substitutions that would be present in the patient's major histocompatibility complex (MHC) molecules provides new epitopes (neoepitopes) that are specific to the patient's malignancy but are not found in healthy patient cells. Harvesting this set of mutations from cancer cells, such as circulating tumor cells (CTCs), allows the preparation of a vaccine that induces an immune response with the potential to target the primary tumor, even if it contains genetically distinct subpopulations, as well as tumor metastases. For vaccination, such neoepitopes identified according to the present invention are provided to the patient in the form of a polypeptide comprising said neoepitopes, after appropriate processing and presentation by MHC molecules, the neoepitopes are presented to the patient's immune system to stimulate the appropriate T cells.

Preferably, such a polypeptide is provided to a patient by administration of an RNA encoding the polypeptide. A strategy in which in vitro transcribed RNA (IVT-RNA) is directly injected into a patient by various immunization methods has been successfully tested in several mammalian models. RNA can be translated in transfected cells, and the expressed protein, after processing, is presented on MHC molecules on the cell surface to elicit an immune response.

Advantages of using RNA as a reversible gene therapy option include transient expression and non-transforming nature. RNA does not need to enter the nucleus for expression and, moreover, cannot integrate into the host genome, thus eliminating the risk of carcinogenesis. The degree of transfection achieved with RNA is quite high. In addition, the amount of protein obtained corresponds to the amount of physiological expression.

The rationale for immunotherapeutic targeting of multiple individual mutations is that (i) these mutations are exclusively expressed, (ii) the mutated epitopes are expected to be ideal for T-cell immunotherapy because the T cells that recognize them are not subjected to thymic selection, (iii) tumor escape from the immune response can be reduced, for example, by targeting "master mutations" that are highly significant for the tumor phenotype, and (iv) a multi-epitope immune response is more likely to result in improved clinical outcome.

The essence of the invention

The present invention relates to effective methods for obtaining individual recombinant antitumor vaccines that induce an effective and specific immune response in cancer patients and have a potential targeted effect on the primary tumor, as well as tumor metastases. The antitumor vaccines prepared according to the invention, when administered to a patient, provide a group of MHC-presented epitopes specific to the patient's tumor and suitable for stimulating, initiating and/or expanding T cells directed against cells expressing antigens from which the MHC-presented epitopes are isolated. Thus, the vaccines described herein are preferably capable of inducing or stimulating a cellular response, preferably cytotoxic T cell activity, against a cancer characterized by the presentation of one or more antigens expressed by the tumor cells by MHC class I molecules. Since the vaccine produced according to the present invention will target tumor-specific mutations, it will be specific to the patient's tumor.

In one aspect, the present invention relates to a method for obtaining an individualized antitumor vaccine, including the steps:

(a) identifying tumor-specific somatic mutations in a tumor sample of the oncology patient to obtain a signature of the patient's tumor mutations; and

(b) obtaining a vaccine, the characteristic feature of which is the signature of tumor mutations obtained in stage (a).

In one embodiment, the method of the invention includes the following steps:

- obtaining a tumor sample from the cancer patient and obtaining a non-tumor sample, which is preferably isolated from the cancer patient;

- identifying sequence differences between the genome, exome and/or transcriptome of the tumor sample and the genome, exome and/or transcriptome of the non-tumor sample;

- the design of the polypeptide, including epitopes, including differences in the sequences defined in stage (ii);

- obtaining a polypeptide designed in stage (iii), or a nucleic acid, preferably RNA, encoding the specified polypeptide; and

- obtaining a vaccine comprising a polypeptide or nucleic acid obtained in step (iv).

According to the invention, a tumor sample refers to any sample, such as a sample taken from the body, isolated from the tissues of a patient, containing or expected to contain tumor or cancer cells. The sample taken from the body may be any tissue sample, such as blood, a tissue sample obtained from a primary tumor or from tumor metastases, or any other sample containing tumor or cancer cells. Preferably, the body sample is blood and tumor-specific somatic mutations or sequence differences are detected in one or more circulating tumor cells (CTCs) contained in the blood. In another embodiment, the tumor sample refers to one or more isolated tumor or cancer cells, such as circulating tumor cells (CTC), or a sample containing one or more isolated tumor or cancer cells, such as circulating tumor cells (CTC).

A non-tumor sample refers to any sample, such as a sample from an organism, that is isolated from the tissues of a patient or other individual, which is preferably of the same species as the patient, preferably from a healthy individual free of or expected to be free of tumor or cancer cells. The body sample can be any tissue sample, such as blood, or a non-tumorogenic tissue sample.

According to the invention, the term "cancer mutation signature" may refer to cancer mutations present in one or more of the patient's cancer cells, or may refer to only a subset of the cancer mutations present in one or more of the patient's cancer cells. Accordingly, the present invention may include identifying all of the tumor-specific mutations present in one or more of the patient's cancer cells, or may include identifying only a portion of the tumor-specific mutations present in one or more of the patient's cancer cells. Typically, the method of the invention will identify a number of mutations that provide a sufficient number of neoepitopes to be included in a vaccine. "Cancer mutation" refers to a difference in sequence between a nucleic acid contained in a cancer cell and a nucleic acid contained in a healthy cell.

Preferably, the mutations identified in the methods of the present invention are non-synonymous mutations, preferably non-synonymous mutations of proteins expressed in tumor or cancer cells.

In one embodiment, tumor-specific somatic mutations or sequence differences are determined in the genome, preferably in the entire genome of the tumor sample. Thus, the method of the invention may include identifying the signature of tumor mutations in the genome, preferably the entire genome of one or more cancer cells. In one embodiment, the step of identifying tumor-specific somatic mutations in a cancer patient's tumor sample comprises identifying a complete genomic profile of the tumor mutations.

In one embodiment, tumor-specific somatic mutations or sequence differences are detected in the exome, preferably in the entire exome of the tumor sample. The exome is part of the genome of an organism, and is formed by exons, which are the coding regions for expressed genes. Exome provides the genetic blueprint used for the synthesis of proteins and other functional gene products. It is the most functionally relevant part of the genome and thus most likely to contribute to the phenotype of an organism. The exome of the human genome is estimated to represent 1.5% of the total genome (Ng, PC et al., PLoS Gen., 4(8): 1-15, 2008). Thus, the method of the invention may include identifying a characteristic tumor mutation of the exome, preferably the entire exome of one or more cancer cells. In one embodiment, the step of identifying tumor-specific somatic mutations in a tumor sample from a cancer patient comprises identifying a complete exome profile of the tumor mutations.

In one embodiment, tumor-specific somatic mutations or sequence differences are detected in the transcriptome, preferably in the entire transcriptome of the tumor sample. A transcriptome is a set of all RNA molecules, including mRNA, rRNA, tRNA, and other non-coding RNA, produced in a single cell or population of cells. In the context of the present invention, a transcriptome refers to the set of all RNA molecules produced in one cell, in a population of cells, preferably in a population of cancer cells, or in all cells of a given individual at a given time. Thus, the method of the invention may include identifying the signature of tumor mutations in the transcriptome, preferably the entire transcriptome of one or more cancer cells. In one embodiment, the step of identifying tumor-specific somatic mutations in a tumor sample of a cancer patient comprises identifying a complete transcriptome profile of the tumor mutations.

In one embodiment, the step of identifying tumor-specific somatic mutations or identifying sequence differences comprises single cell sequencing of the genome for one or more cancer cells, preferably 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more. Thus, the method of the invention may include identifying a characteristic tumor-specific mutation of said one or more cancer cells. In one embodiment, the cancer cells are circulating tumor cells. Cancer cells, such as circulating tumor cells, can be isolated prior to genome sequencing from a single cell.

In one embodiment, the step of identifying tumor-specific somatic mutations or identifying sequence differences includes the use of next generation sequencing (NGS).

In one embodiment, the step of identifying tumor-specific somatic mutations or identifying sequence differences comprises sequencing the genomic DNA and/or RNA of the tumor sample.

To detect tumor-specific somatic mutations or sequence differences, sequence information obtained from a tumor sample is preferably compared with a reference, such as sequence information obtained from DNA or RNA sequencing of healthy non-malignant cells, such as germline cells, which may be obtained either from the patient or from other individuals. In one embodiment, normal genomic germline DNA is obtained from peripheral blood mononuclear cells (PBMCs).

A vaccine according to the methods of the present invention refers to a vaccine which, when administered to a patient, preferably provides a group of MHC-presented epitopes, e.g., 2 or more, 5 or more, 10 or more, 15 or more, 20 or more, 25 or more, 30 or more, and preferably up to 60, up to 55, up to 50, up to 45, up to 40, up to 35 or up to 30 MHC-presented epitopes, including sequence changes based on identified mutations or sequence differences. Such MHC-presented epitopes, including sequence changes based on identified mutations or sequence differences, are also referred to herein as "neoepitopes". The presentation of such epitopes by the patient's cells, in particular antigen-presenting cells, preferably results in the targeting of T cells to MHC-bound epitopes and thus to the patient's tumor, preferably the primary tumor, as well as tumor metastases expressing antigens from which isolated MHC-presented epitopes that present the same epitopes as on the surface of tumor cells.

To obtain a vaccine, the method of the invention may include the optional inclusion in the vaccine of a sufficient number of neoepitopes (preferably in the form of an encoding nucleic acid) or may include the additional step of determining the applicability of identified mutations in epitopes for antitumor vaccination. Thus, additional steps may include one or more of the following: (i) evaluating whether changes are located in the sequence of known or predicted MHC-presented epitopes, (ii) in vitro and/or in silico testing whether changes in sequence are located in MHC-presented epitopes, for example, testing whether the sequence changes are part of the peptide sequences that are processed and/or presented as MHC-presented epitopes, and (iii) in vitro testing whether the mutated epitopes in question, specifically present in in their natural sequence, for example, when flanked by amino acid sequences that also flank said epitopes in the natural protein, when expressed in antigen-presenting cells, stimulate the patient's T cells with the desired specificity. Each of these flanking sequences may include 3 or more amino acids, 5 or more, 10 or more, 15 or more, 20 or more, and preferably up to 50, up to 45, up to 40, up to 35, or up to 30 amino acids, and may flank sequences epitope from the N-terminus and/or from the C-terminus.

Mutations or sequence differences determined according to the invention can be ranked by their suitability as epitopes for tumor vaccination. Thus, in one aspect, the method of the invention includes a manual or computer-assisted analytical process that analyzes identified mutations and selects them for their suitability for use in respective proposed vaccines. In a preferred embodiment, said analytical process is a computer algorithm based process. Preferably, said analytical process includes one or more, and preferably all, of the following steps:

- identification of expressed, protein-modifying mutations, for example, by analyzing transcripts;

- identification of mutations that are potentially immunogenic, e.g. by comparing data obtained using available databases of confirmed immunogenic epitopes, e.g. http://www.immunepitope.org

The step of identifying mutations that are potentially immunogenic may include identifying and/or sequencing epitopes according to their predictive MHC-binding capacity, preferably binding to MHC class-I.

In another embodiment of the invention, epitopes can be selected and/or ordered using additional parameters such as protein exposure, associated gene expression, sequence uniqueness, predicted probability of presentation, and association with oncogenes.

Multiple CTC assays also allow selection and prioritization of mutations. For example, the priority of a mutation that is found in a large number of CTCs may be higher than that of a mutation found in a smaller number of CTCs.

The collection of neoepitope-based mutations identified according to the invention and provided by the vaccine of the invention is preferably present in the form of a polypeptide comprising said neoepitopes (polyepitope polypeptide) or in the form of a nucleic acid, specifically RNA, encoding said polypeptide. In addition, neoepitopes may be present in the polypeptide in the form of a vaccine sequence, i. be present in their natural sequence, for example, being flanked by amino acid sequences which also flank said epitopes in naturally occurring proteins. Each of such flanking sequences may include 5 or more amino acids, 10 or more, 15 or more, 20 or more, and preferably up to 50, up to 45, up to 40, up to 35, or up to 30 amino acids, and may flank epitope sequences with N- end and/or C-terminus. Thus, the vaccine sequence may include 20 or more amino acids, 25 or more, 30 or more, 35 or more, 40 or more, and preferably up to 50, up to 45, up to 40, up to 35 or up to 30 amino acids. In one embodiment, neoepitopes and/or vaccine sequences are arranged head-to-tail in the polypeptide.

In one embodiment, the neoepitopes and/or vaccine sequences are separated by linkers, specifically neutral linkers. The term "linker" according to the invention refers to peptides added between two peptide domains, such as epitopes or vaccine sequences to link said peptide domains. There is no particular limitation regarding the linker sequence. However, it is preferred that the linker sequence reduces steric hindrance between the two peptide domains, is well translated, and maintains or enables epitope processing. In addition, the linker should not have sequences of immunogenic elements, or have them in small quantities. Linkers should preferably not create non-endogenous neoepitopes such as those that form in close contact between adjacent neoepitopes, which may elicit unwanted immune responses. Thus, the polyepitope vaccine preferably contains linker sequences that are capable of reducing unwanted MHC-binding epitopes from junction sites. Hoyt et al. (EMBO J. 25(8), 1720-9, 2006) and Zhang et al. (J. Biol. Chem., 279(10), 8635-41, 2004) demonstrated that glycine-rich sequences facilitate proteasome processing and thus the use of glycine-rich linker sequences minimizes the amount of linker-containing peptides that can be processed. proteasome. In addition, glycine has been observed to inhibit strong binding to MHC binding grooves (Abastado et al., J. Immunol. 151(7), 3569-75, 1993). Schlessinger et al. (Proteins, 61(1), 115-26, 2005) found that the amino acids glycine and serine included in the amino acid sequence result in a more flexible protein that is more efficiently translated and processed by the proteasome, allowing better access to encoded neoepitopes. Each of the linkers may include 3 or more amino acids, 6 or more, 10 or more, 15 or more, 20 or more, and preferably up to 50, up to 45, up to 40, up to 35, or up to 30 amino acids. Preferably, the linker is enriched in the amino acids glycine and/or serine. Preferably at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at least 95% of the amino acids of the linker are glycine and/or serine. In one embodiment, the linker essentially consists of the amino acids glycine and/or serine. In one embodiment, the linker comprises the amino acid sequence (GGS) _a (GSS) _b (GGG) _c (SSG) _d (GSG) _e where a, b, c, d and e are independently a number selected from 0, 1, 2 , 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 and where a + b + c + d + e differ from 0 and preferably 2 or more, 3 or more, 4 or more, or 5 or more. In one embodiment, the linker includes the sequence described herein, including the linker sequences described in the examples, such as the sequence GGSGGGGSG.

In another embodiment of the present invention, the group of mutations based on the neoepitopes identified according to the invention and presented using the vaccine according to the invention is preferably present in the form of a group of polypeptides comprising said neoepitopes, which may also overlap, or in the form of a group of nucleic acids, in particular RNAs encoding said polypeptides.

In one particular preferred embodiment, the polyepitopic polypeptide of the present invention is administered to a patient in the form of a nucleic acid, preferably RNA, such as in vitro transcribed or synthetic RNA, which can be expressed in the patient's cells, such as antigen-presenting cells to produce a polypeptide. The present invention also provides for the introduction of one or more multi-epitope polypeptides, which for the purposes of the present invention are included using the term "polyepitope polypeptide", preferably in the form of RNA, such as in vitro transcribed or synthetic RNA, which can be expressed in cells of the patient, such as antigen-presenting cells , to obtain one or more polypeptides. In the case of introducing more than one multi-epitope polypeptide, the neo-epitopes that are represented by different multi-epitope polypeptides may be different or partially overlap. After the polypeptide of the invention appears in the patient's cells, such as antigen presenting cells, the polypeptide of the invention is processed to produce the neoepitopes identified according to the invention. Administration of the vaccine of the invention can produce class II MHC-presented epitopes that are capable of eliciting a CD4+ T helper cell response against cells expressing antigens from which the MHC-presented epitopes have been isolated. Alternatively or additionally, administration of the vaccine of the invention may provide MHC class I presented epitopes that are capable of eliciting a CD8+ T cell response against cells expressing antigens from which the MHC presented epitopes are isolated. In addition, the administration of the vaccine of the invention may provide one or more neoepitopes (including known neoepitopes and neoepitopes identified by the invention), as well as one or more epitopes that do not contain tumor-specific somatic mutations, but are expressed by tumor cells and preferably induce an immune response. against tumor cells, preferably a tumor-specific immune response. In one embodiment, administration of a vaccine of the invention provides neoepitopes that are epitopes presented by MHC class II and/or are capable of eliciting a CD4+ helper T cell response against cells expressing antigens from which the MHC-presented epitopes are isolated, as well as epitopes that do not contain tumor-specific somatic mutations, which are MHC class I presented epitopes and/or are capable of inducing a CD8+ T cell response against cells expressing antigens from which MHC-presented epitopes are isolated. In one embodiment, epitopes free of tumor-specific somatic mutations are isolated from a tumor antigen. In one embodiment, neoepitopes and epitopes that do not contain tumor-specific somatic mutations have a synergistic effect in the treatment of malignancy. Preferably, the vaccine of the invention is used to polyepitope stimulate a cytotoxic and/or helper T cell response.

In a further aspect, the present invention provides a vaccine which is produced by the method of the invention. Accordingly, the present invention relates to a vaccine comprising a recombinant polypeptide comprising mutation-based neoepitopes, said neoepitopes derived from tumor-specific somatic mutations in a tumor sample of a cancer patient, or comprising a nucleic acid encoding said polypeptide. Such a recombinant polypeptide may also include epitopes that do not include the tumor-specific somatic mutations discussed above. Preferred embodiments of such a vaccine are described above in the context of the method of the invention.

The vaccine provided according to the invention may include a pharmaceutically acceptable carrier and may optionally include one or more adjuvants, stabilizers, etc. The vaccine may be presented in the form of a therapeutic or prophylactic vaccine.

Another aspect of the present invention relates to a method for inducing an immune response in a patient, comprising administering to the patient the vaccine provided according to the invention.

Another aspect relates to a method for treating a cancer patient, comprising the steps of:

(a) obtaining an individual antitumor vaccine using the method according to the invention; and

(b) administering said vaccine to a patient.

Another aspect relates to a method of treating a cancer patient, comprising administering to the patient a vaccine of the invention.

In the following aspects, the invention provides the vaccines described herein for use in the methods of treatment described herein, specifically for use in the treatment or prevention of cancer.

The cancer treatment described herein may be combined with surgical removal and/or conventional chemotherapy.

Another aspect of the invention relates to a method for determining a false positive rate based on next generation sequencing data, said method comprising:

taking the first sample of genetic material from an animal or human;

taking a second sample of genetic material from an animal or human;

taking the first sample of genetic material from tumor cells;

taking a second sample of genetic material from said tumor cells;

determination of total coverage when compared to a tumor by counting all reference genome bases that are included in both the tumor and at least one of said first animal or human genetic material sample and said second animal or human genetic material sample ;

determining overall coverage in a self-versus-self comparison by counting all bases of the reference genome that are covered by both of said first animal or human genetic material sample and said second animal or human genetic material sample;

dividing said total coverage when compared to a tumor by said total coverage when comparing self-versus-self to obtain a normalization;

determining the false positive rate by dividing 1) the number of single nucleotide variations with a quality score greater than Q when comparing said first sample of animal or human genetic material and said second sample of animal or human genetic material by 2) the number of single nucleotide variations with a quality score greater than than Q when comparing said first sample of genetic material from said tumor cells and said second sample of genetic material from said tumor cells and 3) multiplying the result by said normalization.

In one embodiment, said genetic material is DNA.

In one embodiment, Q is determined using:

establishing a number of qualitative features S=(s ₁ ,…,s _n ), where S is preferable to T=(t ₁ ,…,t _n ), which is denoted by S>T, where s _i > t _i for all i=1, …,n;

determining the false positive rate by dividing 1) the number of single nucleotide variations with a quality score greater than Q when comparing said first sample of animal or human genetic material and said second sample of animal or human genetic material by 2) the number of single nucleotide variations with a quality score higher than Q when comparing said first sample of genetic material from said tumor cells and said second sample of genetic material from said tumor cells and by 3) multiplying the result obtained by said normalization:

determining a range of values for each property for m mutations with n all qualitative features for each;

selective selection of up to p values from the specified range of values;

creating all possible combinations of the selected quality values, resulting in p ⁿ experimental points;

applying a random sample of said experimental points as a predictive parameter for training the "random forest";

applying the appropriate intermediate false positive rate as the answer for the specified random forest training,

where the resulting regression score of the specified "random forest" training is Q.

In one embodiment, said second animal or human DNA sample is allogeneic to said first animal or human DNA sample. In one embodiment, said second animal or human DNA sample is autologous to said first animal or human DNA sample. In one embodiment, said second animal or human DNA sample is xenogeneic to said first animal or human DNA sample.

In one embodiment, said genetic material is RNA.

In one embodiment, Q is determined using:

establishing a number of qualitative features S=(s ₁ ,…,s _n ), where S is preferable to T=(t ₁ ,…,t _n ), which is denoted by S>T, where s _i > t _i for all i=1, …,n;

determining an intermediate false positive rate by dividing 1) the number of single nucleotide variations with quality score S>T when comparing said first animal or human RNA sample and said second animal or human RNA sample by 2) the number of single nucleotide variations with quality score S>T comparing said first RNA sample from said tumor cells and said second RNA sample from said tumor cells and 3) multiplying the result by said normalization;

determining a range of values for each property for m mutations with n all qualitative features;

selective selection of up to p values from the specified range of values;

creation of all possible combinations from the selected qualitative values, which results in obtaining p ⁿ experimental points;

applying a random sample of said experimental points as a predictive parameter for training the "random forest";

applying the appropriate intermediate false positive rate as a response to the specified random forest training,

where the resulting regression score of the specified random forest training is Q.

In one embodiment, said second animal or human RNA sample is allogeneic to said first animal or human RNA sample. In one embodiment, said second animal or human RNA sample is autologous to said first animal or human RNA sample. In one embodiment, said second animal or human RNA sample is xenogeneic to said first animal or human RNA sample.

In one embodiment, the specified false positive rate is used to obtain a vaccine formulation. In one embodiment, the vaccine is delivered intravenously. In one embodiment, the vaccine is delivered intradermally. In one embodiment, the vaccine is delivered intramuscularly. In one embodiment, the vaccine is delivered subcutaneously. In one embodiment, said vaccine is specifically designed for a particular patient.

In one embodiment, one of said first animal or human genetic material sample and said second animal or human genetic material sample is from said particular patient.

In one embodiment, in said step of determining overall coverage when compared to a tumor by counting all bases of a reference genome that is included both in the tumor and in at least one of said first sample of animal or human genetic material and said second sample genetic material from an animal or human, an automated all-base scoring system is used;

In one embodiment, in said step of determining overall coverage in a self-versus-self comparison by counting all the reference genome bases that overlap in both of said first animal or human genetic material sample and said second animal or human genetic material sample, specified automated system.

In one embodiment, in said step of dividing said total coverage compared with a tumor by said total coverage in a self-versus-self comparison to obtain a normalization, said automated system is applied.

In one embodiment, said step of determining a false positive rate by dividing 1) the number of single nucleotide variations with a quality score greater than Q when comparing said first sample of animal or human genetic material and said second sample of animal or human genetic material by 2) the number of single nucleotide variations variations with a quality score higher than Q by comparing said first sample of genetic material from said tumor cells and said second sample of genetic material from said tumor cells and 3) multiplying the result obtained by said normalization.

Another aspect of the invention relates to a method for determining a calculated true/false detection ratio (ROC) curve, said method comprising:

obtaining a mutation data set, each mutation being associated with a false positive rate (FDR); and

for each mutation:

determining a true positive rate (TPR) by subtracting said FDR from one; and

determining a false positive rate (FPR) by setting said FPR equal to said FDR; and

obtaining an estimated ROC by plotting, for each mutation, a point at the sum of the TPR and FPR values prior to the specified mutation, divided by the sum of all TPR and FPR values.

Other features and advantages of the present invention will appear from the following detailed description and from the appended claims.

Detailed description of the invention

Although the present invention will be described in detail below, it should be noted that this invention is not limited to the specific methodology, protocols, and reagents described here, as they may change. It should also be appreciated that the terminology used here is only for the purposes of describing specific embodiments, and is not intended to limit the scope of the present invention, which will be limited only by the appended claims. Unless otherwise indicated, all technical and scientific terms used herein have the same meanings as those of ordinary skill in the art.

Next, the elements of the present invention will be described. These elements are listed with specific embodiments, however, it should be understood that they can be combined in any manner and in any number to create additional embodiments. The variously described examples and preferred embodiments should not be construed as limitations of the present invention, but are intended solely to clearly describe the embodiments. It should be understood that the description supports and covers embodiments that combine the clearly described embodiments with any number of disclosed and/or preferred embodiments. In addition, any permutations and combinations of all described elements in this application should be considered as disclosed by the description of this application until the context indicates otherwise. For example, if in a preferred embodiment the RNA comprises a 120 nucleotide poly(A) tail and in another preferred embodiment the RNA molecule comprises a 5' cap analogue, then in a preferred embodiment the RNA comprises a 120 nucleotide poly(A) tail. nucleotides and a 5'-cap analog.

Eds., (1995) Helvetica Chimica Acta, CH-4010 Basel, Switzerland.Preferably, the terms used herein are defined as described in "A multilingual glossary of biotechnological terms: (IUPAC Recommendations)", HGW Leuenberger, B. Nagel, and H.

Eds., (1995) Helvetica Chimica Acta, CH-4010 Basel, Switzerland.

In carrying out the present invention will be used, unless otherwise indicated, conventional methods of biochemistry, cell biology, immunology and recombinant DNA technology, which are explained in publications belonging to the technical field (see, for example, Molecular Cloning: A Laboratory Manual, 2 ^nd Edition, J. Sambrook et al.eds., Cold Spring Harbor Laboratory Press, Cold Spring Harbor 1989).

Throughout this description and in the claims below, unless the context otherwise requires, the word "comprises" and variations such as "comprises" or "comprising" will be intended to include the stated stated components, numbers, or steps, or a group of components, numbers, or steps. , but not the exclusion of any other components, numbers, or steps, or a group of components, numbers, or steps, although in some embodiments, such other components, numbers, or steps may be excluded, i.e. the object of the invention consist of the inclusion of specified components, numbers or steps, or a group of components, numbers or steps. Terms in the singular in the context of the description of the invention (and especially in the context of the claims) are intended to cover both the singular and the plural, unless otherwise specified herein or unless there is an obvious conflict with the context. The range enumeration in this document is only intended to serve as a method of shortening the individual notation for each individual value that falls within the range. Until otherwise specified in this document, each individual value is included in the description as if it were individually listed in this document.

All of the methods described herein may be performed in any suitable order, unless otherwise indicated herein or unless the context clearly dictates otherwise. The use of any of the examples and all examples, or exemplary expression (eg, "such as") provided herein, is only intended to better illustrate the invention and does not limit the scope of the invention otherwise claimed. No wording in the specification is to be construed as denoting any unclaimed element essential to the practice of the invention.

Several documents are cited throughout this specification. Each of the documents cited in this document (including all patents, patent applications, scientific publications, manufacturer's descriptions, instructions, etc.) cited either above or below is hereby incorporated by reference in its entirety. Nothing in this document should be construed as an admission that the invention is not entitled to change the date to an earlier date in relation to the opposed document due to the earlier creation of the present invention (antedate).

The vaccine according to the invention is a recombinant vaccine.

The term "recombinant" in the context of the present invention means "made using genetic engineering". Preferably, a "recombinant component" such as a recombinant polypeptide in the context of the present invention is not naturally occurring and preferably results from a combination of components such as amino acid sequences and nucleic acid sequences that are not naturally combined. For example, a recombinant polypeptide in the context of the present invention may contain several amino acid sequences, such as neoepitopes or vaccine sequences, isolated from different proteins or different parts of the same protein, linked together, for example, via peptide bonds or suitable linkers.

The term "natural" when used in this document refers to the fact that the object can be found in the natural environment. For example, a peptide or nucleic acid that is present in the body (including viruses) and can be isolated from a source in the natural environment and that has not been specially modified by humans in a laboratory is natural.

According to the invention, the term "vaccine" refers to a pharmaceutical preparation (pharmaceutical composition) or product that, when administered, induces an immune response, specifically a cellular immune response that recognizes and attacks a pathogen or a diseased cell, such as a cancer cell. The vaccine may be used to prevent or treat a disease. The term "individual cancer vaccine" refers to a specific cancer patient and means that the cancer vaccine is tailored to the needs or special circumstances of the individual cancer patient.

The term "immune response" refers to the body's integrated response to an antigen, and preferably refers to a cellular immune response or a cellular as well as a humoral immune response. The immune response may be protective/preventive/prophylactic and/or therapeutic.

"Induction of an immune response" can mean that there was no immune response against a particular antigen before induction, but it can also mean that there was a certain level of immune response against a particular antigen before induction, and after the induction of said immune response, it increased. Thus, "induction of an immune response" also includes "enhancement of an immune response". Preferably, after inducing an immune response in an object, said object is protected from the development of a disease, such as malignancy, or the pathological condition is improved by inducing an immune response. For example, an immune response against an antigen expressed by a tumor can be induced in a patient having cancer or in a subject at risk of developing cancer. The induction of an immune response in this case may mean that the pathological state of the subject is improving, that the subject will not develop metastases, or that the subject at risk of developing malignancy will not develop malignant neoplasm.

"cellular immune response", "cellular response", "cellular response against antigen" or a similar term is meant to include a cellular response directed at cells differing in antigen presentation by MHC class I and class II. The cellular response refers to cells called T-cells or T-lymphocytes, which act as either "helpers" or "killers". Helper T cells (also called CD4 ⁺ T cells) play a central role by regulating the immune response, and killer cells (also called cytotoxic T cells, cytolytic T cells, CD8 ⁺ T cells, or CTLs) kill diseased cells such as like tumor cells, preventing the production of more diseased cells. In preferred embodiments, the present invention includes stimulating an anti-tumor CTL response against tumor cells expressing one or more tumor-expressed antigens, and preferably presenting such tumor-expressed antigens, with MHC class I.

"Antigen" according to the invention encompasses any substance that will elicit an immune response. Specifically, "antigen" refers to any substance, preferably a peptide or protein, that specifically reacts with antibodies or T-lymphocytes (T-cells). According to the present invention, the term "antigen" includes any molecule that includes at least one epitope. Preferably, an antigen in the context of the present invention is a molecule that optionally, after processing, induces an immune response that is preferably specific for the antigen (including cells expressing the antigen). Any suitable antigen that is a candidate for an immune response can be used according to the present invention, where the immune response is preferably a cellular immune response. In the context of embodiments of the present invention, the antigen is preferably presented by a cell, preferably an antigen presenting cell, which includes a diseased cell, specifically a tumor cell, in the context of MHC molecules, resulting in an immune response against the antigen. The antigen is preferably a product that matches or is derived from a naturally occurring antigen. Such natural antigens include tumor antigens.

In a preferred embodiment, the antigen is a tumor antigen, i. part of the tumor cell, such as a protein or peptide expressed in the tumor cell, which can be isolated from the cytoplasm, from the cell surface or from the nucleus of the cell, in particular, which is initially present in the intracellular space or as surface antigens of the tumor cells. For example, tumor antigens include carcinoembryonic antigen, α1-fetoprotein, isoferritin and fetal sulfoglycoprotein, α2-H-ferroprotein and γ-fetoprotein. According to the present invention, the tumor antigen preferably includes any antigen that is expressed in a certain type of tumor and is optionally characteristic in relation to the type and/or level of expression for tumors or malignancies, as well as for tumor or cancer cells. In one embodiment, the term "tumor antigen" or "tumor-specific antigen" refers to proteins that under normal conditions are specifically expressed in a limited number of tissues and/or organs or at certain stages of development, for example, a tumor antigen may under normal conditions be specifically expressed in gastric tissue. , preferably in the gastric mucosa, in the reproductive organs, for example, in the testicles, in trophoblastic tissue, for example, in the placenta, or in germ cell lines, and they are expressed or aberrantly expressed in one or more tumor or cancer tissues. In this context, "limited number" preferably means no more than 3, more preferably no more than 2. Tumor antigens in the context of the present invention include, for example, differentiation antigens, preferably cell type-specific differentiation antigens, i. proteins that under normal conditions are specifically expressed in a certain cell type at a certain stage of differentiation, cancer/testis antigens, i.e., proteins that under normal conditions are specifically expressed in the testis and sometimes in the placenta, and germ cell specific antigens lines. Preferably, the tumor antigen or aberrant expression of the tumor antigen identifies cancer cells. In the context of the present invention, a tumor antigen that is expressed by a cancer cell of a subject, for example a cancer patient, is preferably a self-protein of said subject. In preferred embodiments, the tumor antigen in the context of the present invention is specifically expressed under normal conditions in a tissue or organ that is not essential, i. tissue or organs that, when destroyed by the immune system, do not result in the death of the subject, or in organs or structures of the body that are not accessible or difficult to access by the immune system.

According to the invention, the terms "tumor antigen", "tumor expressed antigen", "cancer antigen" and "antigen expressed by cancer cells" are equivalent and are used interchangeably herein.

The term "immunogenicity" refers to the relative effectiveness of an antigen in inducing an immune response.

An "antigenic peptide" according to the invention preferably refers to a portion or fragment of an antigen which is capable of stimulating an immune response, preferably a cellular response against the antigen or cells expressing the antigen, preferably by antigen presentation, such as diseased cells, in particular cancer cells. . Preferably, the antigenic peptide is capable of stimulating cellular immunity against a cell characterized by antigen presentation by MHC class I, and preferably is capable of stimulating antigen-responsive cytotoxic T lymphocytes (CTL). Preferably, the antigenic peptides of the invention are peptides that are presented by MHC class I and/or class II, or which can be processed to produce peptides presented by MHC class I and/or class II. Preferably, the antigenic peptides comprise an amino acid sequence substantially corresponding to the amino acid sequence of the antigen fragment. Preferably, said antigen fragment is a peptide presented by MHC class I and/or class II. Preferably, the antigenic peptide of the invention comprises an amino acid sequence substantially corresponding to the amino acid sequence of such a fragment, and is processed to obtain such a fragment, i.e. a peptide presented by MHC class I and/or class II, which is isolated from the antigen.

If the peptide will be presented directly, i.e. without processing, in particular without cleavage, then it will have a length that is suitable for binding to an MHC molecule, in particular an MHC class I molecule, and preferably its length is 7-20 amino acids, more preferably 7-12 amino acids, more preferably , 8-11 amino acids, specifically 9 or 10 amino acids.

If the peptide is part of a larger component containing additional sequences, such as a vaccine sequence or a polypeptide, and is presented after processing, specifically after cleavage, then the peptide obtained by processing is of a length that is suitable for binding to an MHC molecule, specifically to the molecule MHC class I, and preferably, its length is 7-20 amino acids, more preferably 7-12 amino acids, more preferably 8-11 amino acids, in particular 9 or 10 amino acids. Preferably, the sequence of the peptide to be presented after processing is derived from the amino acid sequence of the antigen, i.e., its sequence substantially corresponds to, and preferably is completely identical to, the antigen fragment. Thus, an antigenic peptide or vaccine sequence according to the invention in one embodiment comprises a sequence of 7-20 amino acids, more preferably 7-12 amino acids, more preferably 8-11 amino acids, in particular 9 or 10 amino acids, which substantially correspond to and preferably completely identical to the antigen fragment, and after processing the antigenic peptide or vaccine sequence, they are the presented peptide. According to the invention, such a peptide obtained by processing includes an identified sequence change.

According to the invention, an antigenic peptide or epitope may be present in a vaccine as part of a larger component, such as a vaccine sequence and/or a polypeptide comprising more than one antigenic peptide or epitope. The antigenic peptide or epitope present is obtained after appropriate processing.

Peptides having amino acid sequences substantially corresponding to the sequence of the peptide that is presented by the MHC class I molecule may differ in one or more residues that are not essential for TCR recognition of the peptide as being presented by the MHC class I molecule, or may differ in the binding of the peptide to MHC. Such substantially corresponding peptides are also capable of stimulating antigen-responsive CTLs and may be considered immunologically equivalent. Peptides having amino acid sequences different from the presented peptides in a residue that does not affect TCR recognition but improves MHC binding stability can improve the immunogenicity of the antigenic peptide and may be referred to herein as "optimized peptides". With current knowledge as to which of these residues is most likely to influence binding to either the MHC or the TCR, a rational way to design essentially suitable peptides can be applied. The resulting functional peptides are considered antigenic peptides.

The antigenic peptide, when presented to the MHC, must be recognized by the T-cell receptor. Preferably, the antigenic peptide, if recognized by the T cell receptor, is capable of inducing, in the presence of appropriate costimulatory signals, clonal expansion of the T cell carrying the T cell receptor specifically recognizing the antigenic peptide. Preferably, the antigenic peptides, in particular when presented in the context of MHC molecules, are capable of stimulating an immune response, preferably a cellular response, against the antigen from which they are derived or against cells expressing the antigen, and preferably presenting the antigen. Preferably, the antigenic peptide is capable of stimulating cellular immunity against a cell characterized by MHC class I antigen presentation and preferably capable of stimulating antigen-responsive CTLs. Such a cell is preferably a target cell.

"Antigen processing" or "processing" refers to the degradation of a polypeptide or antigen into processing products that are fragments of said polypeptide or antigen (e.g., degradation of the polypeptide into peptides) and the association of one or more of such fragments (e.g., via binding) with MHC molecules for presentation by cells, preferably antigen-presenting cells, to specific T cells.

"Antigen presenting cells" (APCs) are cells that present peptide fragments of protein antigens in association with MHC molecules on their cell surface. Some APCs can activate antigen-specific T cells.

Specialized antigen-presenting cells are very efficient in internalizing an antigen, either through phagocytosis or receptor-mediated endocytosis, and subsequently presenting an antigen fragment bound to an MHC class II molecule on their membrane. The T cell recognizes and interacts with the MHC class II antigen-molecule complex on the membrane of the antigen-presenting cell. An additional co-stimulatory signal is then produced by the antigen-presenting cell, leading to the activation of the T cell. The expression of co-stimulatory molecules is a characteristic feature of specialized antigen-presenting cells.

The main types of specialized antigen presenting cells are dendritic cells, which have a wide spectrum of antigen presentation, and are probably the most important antigen presenting cells, macrophages, B cells and certain activated epithelial cells.

Dendritic cells (DC) are a population of leukocytes that present antigens captured in peripheral tissues to T cells via both antigen-presenting pathways, using MHC class II and I molecules. It is well known that dendritic cells are powerful inducers of the immune response. , and the activation of these cells is a critical step in the induction of antitumor immunity.

Dendritic cells are conventionally classified as "immature" and "mature" cells, which can be used as a simple way to distinguish between two well-characterized phenotypes. However, this nomenclature should not imply the exclusion of all possible intermediate stages of differentiation.

Immature dendritic cells are characterized as antigen-presenting cells with high antigen uptake and processing capacity, which correlates with high Fcγ receptor and mannose receptor expression. The mature phenotype is typically characterized by lower expression of these markers, but high expression of cell surface molecules responsible for T cell activation, such as MHC class I and II molecules, adhesion molecules (eg, CD54 and CD11), and co- stimulatory molecules (eg, CD40, CD80, CD86 and 4-1 BB).

Dendritic cell maturation is referred to as the state of dendritic cell activation in which such antigen-presenting dendritic cells result in stimulation of T cells, while presentation by immature dendritic cells results in resistance. The maturation of dendritic cells is primarily driven by biomolecules with microbial properties, detected by innate immune receptors (bacterial DNA, viral RNA, endotoxin, etc.), pro-inflammatory cytokines (TNF, IL-1, IFN), CD40 ligation on the surface dendritic cells with CD40L, and substances released from cells in a state of cell death under stress. Dendritic cells can be obtained by culturing bone marrow cells in vitro using cytokines such as granulocyte-macrophage colony stimulating factor (GM-CSF) and tumor necrosis factor alpha.

Non-specialized antigen-presenting cells do not constitutively express MHC class II proteins required to interact with native T cells; they are only expressed when non-specialized antigen-presenting cells are stimulated with cytokines such as IFNγ.

"Antigen-presenting cells" can be loaded with peptides presented by MHC class I molecules by transducing cells using a nucleic acid, preferably an RNA encoding a peptide or a polypeptide comprising the presenting peptide, for example, a nucleic acid encoding an antigen.

In some embodiments, a pharmaceutical composition of the invention, comprising a gene delivery vehicle targeting dendritic or other antigen presenting cells, may be administered to a patient, resulting in transfection that occurs in vivo. In vivo transfection of dendritic cells can generally be carried out using techniques well known in the art. such as those described in WO 97/24447, or using the gene gun method described in Mahvi et al., Immunology and cell Biology 75: 456-460, 1997.

According to the invention, the term "antigen-presenting cell" also includes target cells.

"Target cell" will mean a cell that is the target of an immune response, such as a cellular immune response. Target cells include cells that present an antigen or antigenic epitope, ie. a peptide fragment isolated from an antigen and include any unwanted cell such as a cancer cell. In preferred embodiments, the target cell is a cell expressing an antigen as described herein, and preferably presenting said antigen with an MHC class I molecule.

The term "epitope" refers to an antigenic determinant in a molecule, such as an antigen, i.e., a portion or fragment of a molecule that is recognized by the immune system, for example, that is recognized by a T cell, specifically when presented in the context of MHC molecules. An epitope of a protein such as a tumor antigen preferably comprises a continuous or discontinuous stretch of said protein and is preferably 5-100 amino acids in length, preferably 5-50, more preferably 8-30, most preferably 10-25 amino acids, e.g. the epitope may preferably be 9 amino acids in length , 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, or 25 amino acids. Particularly preferably, if the epitope in the context of the present invention is a T-cell epitope.

According to the invention, an epitope can bind to MHC molecules, such as MHC molecules on the cell surface, and thus can be a "MHC binding peptide" or "antigenic peptide". The term "MHC binding peptide" refers to a peptide that binds to an MHC class I molecule and/or to an MHC class II molecule. In the case of MHC class I/peptide complexes, binding peptides are typically 8-10 amino acids in length, although longer or shorter peptides may be effective. In the case of MHC class II/peptide complexes, binding peptides are typically 10-25 amino acids in length, and more specifically 13-18 amino acids in length, although longer or shorter peptides may be effective.

The terms "epitope", "antigenic peptide", "antigenic epitope", "immunogenic peptide" and "MHC binding peptide" are used interchangeably herein and preferably refer to a partial presentation of an antigen, which is preferably capable of eliciting an immune response against an antigen or cell, expressing or preferably including the presented antigen. Preferably, the terms refer to the immunogenic site of the antigen. Preferably, this is an antigen site that is recognized (ie, specifically bound) by a T-cell receptor, specifically if it is presented in the context of MHC molecules. Such preferred immunogenic sites bind to an MHC class I or class II molecule. As used herein, an immunogenic site is said to "bind to" a class I or class II MHC molecule if such binding is detected using an assay known in the art.

As used herein, the term "neoepitope" refers to an epitope that is not present in a reference, such as a normal non-tumor or germline cell, but which is found in cancer cells. In particular, this includes situations where a corresponding epitope is found in a normal non-tumor or germ cell, but due to one or more mutations in the tumor cell, the sequence of the epitope is changed, resulting in the appearance of a neo-epitope.

The term "plot" refers to a part. With respect to a particular structure, such as an amino acid sequence or a protein, the term "region" thereof may mean a continuous or discrete portion of said structure. Preferably, the amino acid sequence portion comprises at least 1%, at least 5%, at least 10%, at least 20%, at least 30%, preferably at least 40%, preferably at least 50%, more preferably at least 60%, more preferably at least 70%, even more preferably at least 80%, and most preferably at least 90% of the amino acids of said amino acid sequence. Preferably, if the section is a discrete part, then said discrete part consists of 2, 3, 4, 5, 6, 7, 8, or more parts of the structure, each part being a continuous element of the structure. For example, a discrete portion of an amino acid sequence may consist of 2, 3, 4, 5, 6, 7, 8, or more, preferably no more than 4 portions of said amino acid sequence, where each portion preferably includes at least 5 contiguous contiguous amino acids, at least 10 contiguous amino acids, preferably at least 20 contiguous amino acids, preferably at least 5 contiguous amino acids from the amino acid sequence.

The terms "part" and "fragment" are used interchangeably herein and refer to a continuous element. For example, a part of a structure, such as an amino acid sequence or a protein, refers to a contiguous element of said structure. The site, part or fragment of the structure preferably includes one or more functional properties of the specified structure. For example, a region, portion, or fragment of an epitope, peptide, or protein is preferably immunologically equivalent to the epitope, peptide, or protein from which it is derived. In the context of the present invention, a "part" of a structure, such as an amino acid sequence, preferably comprises, preferably consists of at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 85%, at least 90%, at least 92%, at least at least 94%, at least 96%, at least 98%, at least 99% of the whole structure of the amino acid sequence.

The term "immunoreactive cell" in the context of the present invention refers to a cell that has effector functions in the immune response. An "immunoreactive cell" is preferably capable of binding to an antigen or a cell presenting an antigen or an antigenic peptide derived from an antigen and mediates an immune response. For example, such cells secrete cytokines and/or chemokines, secrete antibodies, recognize tumor cells, and optionally kill such cells. For example, immunoreactive cells include T cells (cytotoxic T cells, helper T cells, tumor-invading T cells), B cells, natural killer cells, neutrophils, macrophages, and dendritic cells. Preferably, in the context of the present invention, "immunoreactive cells" are T cells, preferably CD4 ⁺ and/or CD8 ⁺ T cells.

Preferably, the "immunoreactive cell" recognizes an antigen or antigenic peptide isolated from an antigen with some degree of specificity, specifically if it is presented in the context of MHC molecules, such as on the surface of antigen presenting cells or diseased cells such as tumor cells. Preferably, said recognition enables a cell that recognizes an antigen or antigenic peptide derived from said antigen to be responsive or reactive. If the cell is a helper T cell (CD4 ⁺ T cell) bearing receptors that recognize an antigen or antigenic peptide derived from an antigen in the context of MHC class II molecules, such responsiveness or reactivity may include cytokine release and/or CD8 ⁺ activation. lymphocytes (CTL) and/or B cells. If the cell is a CTL, then such responsiveness or reactivity may include the killing of cells presented in the context of MHC class I molecules, i.e., cells that differ in antigen presentation using MHC class I molecules, for example, through apoptosis or perforin-mediated cellular lysis. According to the invention, CTL responsiveness may include sustained calcium release, cell division, production of cytokines such as IFN-γ and TNF-α, upregulation of marker activation such as CD44 and CD69, and specific cytolytic killing of antigen-expressing target cells. CTL responsiveness can also be determined using an artificial reporter that accurately detects CTL responsiveness. Those CTLs that recognize an antigen or antigenic peptide derived from an antigen and are responsive or reactive are also referred to herein as "antigen-responsive CTLs". If the cell is a B cell, then such responsiveness may include the release of immunoglobulins.

The terms "T cell" and "T lymphocyte" are used interchangeably herein and include T helper cells (CD4+ T cells) and cytotoxic T cells (CTL, CD8+ T cells), which include cytolytic T cells.

T cells belong to a group of white blood cells known as lymphocytes and play a central role in cell-mediated immunity. They may differ from other types of lymphocytes such as B cells and natural killer cells by the presence of a special receptor on their cell surface called the T cell receptor (TCR). The thymus is the principal organ responsible for the maturation of T cells. Several different subsets of T cells have been found, each with a different function.

Helper T cells assist other white blood cells in immunological processes, including the maturation of B cells into plasma cells and the activation of cytotoxic T cells and macrophages. These cells are also known as CD4+ T cells because they express the CD4 protein on their surface. Helper T cells become activated when they are presented with peptide antigens by class II MHC molecules that are expressed on the surface of antigen presenting cells (APCs). Once activated, they rapidly divide and secrete small proteins called cytokines that regulate or promote an active immune response.

Cytotoxic T cells destroy virus-infected cells and tumor cells and are also involved in transplant rejection. These cells are also known as CD8+ T cells since they express the CD8 glycoprotein on their surface. These cells recognize their targets by binding to an antigen associated with the MHC class I molecule, which is present on the surface of almost every cell in the body.

Most T cells have a T cell receptor (TCR) present in a complex of several proteins. In fact, the T-cell receptor consists of two separate peptide chains, which are formed from independent T-cell receptor alpha and beta genes (TCRα and TCRβ) and are called α- and β-TCR chains. γδ T cells (gamma delta T cells) characterize a small subset of T cells that have distinct T cell receptors (TCRs) on their surface. At the same time, in γδ T-cells, TCR is formed from one γ-chain and one δ-chain. This group of T cells is usually much smaller (2% of total T cells) than αβ T cells.

The first signal in T cell activation is provided by binding of the T cell receptor to a short peptide presented by the major histocompatibility complex (MHC) on another cell. This binding ensures that only the T cell with the TCR specific to that peptide is activated. The partner cell is usually a specialized antigen presenting cell (APC), typically a dendritic cell in case of a naive response, although B cells and macrophages can be important APCs. Peptides presented to CD8+ T cells by MHC class I molecules are typically 8-10 amino acids in length; peptides presented to CD4+ T cells by MHC class II molecules tend to be longer because the ends of the binding groove of the MHC class II molecule are open.

According to the present invention, a T cell receptor is capable of binding to a specific target if it has sufficient affinity for said specific target and binds to said specific target in standard assays. "Affinity" or "binding affinity" is often measured using the equilibrium dissociation constant (K _D ). A T cell receptor is not (substantially) capable of binding to a target if it does not have sufficient affinity for said target and does not bind substantially to said target in standard assays.

The T cell receptor is preferably capable of specific binding to a specific target. A T-cell receptor is specific for a particular target if it is able to bind to said particular target while it is (substantially) unable to bind to other targets, ie. does not have sufficient affinity for other targets and does not bind significantly to other targets in standard assays.

The formation of cytotoxic T-lymphocytes can be caused in vivo by incorporation of an antigen or antigenic peptide into antigen-presenting cells in vivo. The antigen or antigenic peptide can be present either as a protein or as DNA (eg within a vector) or as RNA. The antigen can be processed into a partner peptide for the MHC molecule while its fragment can be presented without the need for further processing. The latter occurs, in particular, if they bind to MHC molecules. In general, it is possible to administer to a patient by intradermal injection. However, injection can also be via an intranodal route to a lymph node (Maloy et al. (2001), Proc Natl Acad Sci USA 98:3299-303). The resulting cells present the complex of interest and are recognized by autologous cytotoxic T-lymphocytes, which then proliferate.

Specific activation of CD4+ or CD8+ T cells can be detected in various ways. Methods for detecting specific T cell activation include detection of T cell proliferation, production of cytokines (eg, lymphokines), or generation of cytotoxic activity. For CD4+ T cells, the preferred method for detecting specific T cell activation is to detect T cell proliferation. For CD8+ T cells, the preferred method for detecting specific T cell activation is to detect the generation of cytotoxic activity.

The term "major histocompatibility complex" and the abbreviation "MHC" includes MHC class I and MHC class II molecules and refers to a complex of genes that are present in all vertebrates. MHC proteins or molecules are important for signaling between lymphocytes and antigen presenting cells or diseased cells in immune responses where proteins and MHC molecules bind to peptides and present them for recognition by T cell receptors. MHC-encoded proteins are expressed on the surface of cells and present both their own antigens (peptide fragments from the cell itself) and foreign antigens (eg, fragments of invading microorganisms) to T cells.

The MHC area is divided into three subgroups, class I, class II, and class III. Class I MHC proteins contain the α-chain and β2-microglobulin (not part of the MHC encoded by chromosome 15). They present antigenic fragments to cytotoxic T cells. On most cells of the immune system, especially antigen-presenting cells, MHC class II proteins contain α- and β-chains, and they present antigenic fragments to T-helper cells. The MHC class III region encodes for other immune components such as complement components and some components that encode for cytokines.

In humans, genes in the MHC region that encode antigen-presenting proteins on the cell surface are referred to as human leukocyte antigen (HLA) genes. However, the abbreviation MHC is often used to refer to HLA gene products. HLA genes include nine so-called classic MHC genes: HLA-A, HLA-B, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DRA, and HLA-DRB1.

In one preferred embodiment of all aspects of the invention, the MHC molecule is an HLA molecule.

By "antigen presenting cell" or "antigen presenting cell" or similar expressions is meant a cell, such as a diseased cell, such as a cancer cell, or an antigen presenting cell presenting an antigen or a fragment isolated from said antigen, for example, by processing antigen in the context of MHC molecules, specifically MHC class I molecules. Similarly, the term "disease characterized by antigen presentation" means a disease in which cells characterized by antigen presentation, in particular by MHC class I molecules, are involved. transfecting the cell with a nucleic acid, such as RNA, encoding an antigen.

By "presentable antigen fragment" or similar expressions is meant that the fragment can be presented with MHC class I or class II molecules, preferably MHC class I, for example when added directly to antigen presenting cells. In one embodiment, the fragment is a fragment that is naturally presented by cells expressing the antigen.

The term "immunologically equivalent" means that immunologically equivalent molecules, such as immunologically equivalent amino acid sequences, exhibit the same or substantially the same immunological properties and/or have the same or substantially the same immunological effects, for example, in terms of the type of immunological effect, such as inducing a humoral and/or cellular immune response, the strength and/or duration of the induced immune response, or the specificity of the induced immune response. In the context of the present invention, the term "immunologically equivalent" is preferably used in relation to the immunological effects or properties of the peptide used for immunization. For example, an amino acid sequence is immunologically equivalent to a reference amino acid sequence if said amino acid sequence, when exposed to the subject's immune system, induces an immune response having reaction specificity with the reference amino acid sequence.

The term "immune effector functions" in the context of the present invention includes any functions mediated by components of the immune system that result, for example, in the destruction of tumor cells or inhibition of tumor growth and/or inhibition of tumor development, including inhibition of tumor spread and metastasis. Preferably, immune effector functions in the context of the present invention are T cell mediated effector functions. Such functions include, in the case of a helper T cell (CD4 ⁺ T cell), recognition of an antigen or an antigenic peptide derived from an antigen in the context of class II MHC molecules via T cell receptors, release of cytokines, and/or activation of CD8 ⁺ lymphocytes (CTL ) and/or B cells, and in the case of CTL, recognition of an antigen or an antigenic peptide derived from an antigen in the context of MHC class I molecules by T cell receptors, killing cells presented in the context of MHC class I molecules, i.e. , cells characterized by antigen presentation by an MHC class I molecule, for example, via apoptosis or perforin-mediated cell lysis, production of cytokines such as IFN-γ and TNF-α, and specific cytolytic killing of antigen-expressing target cells.

The term "genome" refers to the total amount of genetic information in the chromosomes of an organism or cell. The term "exome" refers to coding regions of the genome. The term "transcriptome" refers to the set of all RNA molecules.

The "Nucleic acid" according to the invention is preferably deoxyribonucleic acid (DNA) or ribonucleic acid (RNA), more preferably RNA, most preferably in vitro transcribed RNA (IVT RNA) or synthetic RNA. Nucleic acids include, according to the invention, genomic DNA, cDNA, mRNA, recombinantly produced and chemically synthesized molecules. According to the invention, the nucleic acid may be present as a single or double stranded and linearly or covalently cyclic molecule. According to the invention, the nucleic acid may be isolated. The term "isolated nucleic acid" means according to the invention that the nucleic acid (i) has been amplified in vitro, for example by polymerase chain reaction (PCR), (ii) has been obtained recombinantly by cloning, (iii) has been purified, for example by digestion and separation using gel electrophoresis, or (iv) was synthesized, for example, using chemical synthesis. The nucleic acid can be used for oral administration, ie. for transfection of cells, specifically in the form of RNA, which can be obtained by in vitro transcription from a DNA template. In addition, RNA can be modified prior to use by stabilizing sequences, capping, and polyadenylation.

The term "genetic material" refers to an isolated nucleic acid, either DNA or RNA, a portion of a double helix, a portion of a chromosome, or the entire genome of an organism or cell, specifically an exome or transcriptome.

The term "mutation" refers to a change or difference in a nucleic acid sequence (nucleotide substitution, insertion or deletion) compared to a reference. "Somatic mutation" can occur in any of the body's cells with the exception of germ cells (sperm and egg) and thus does not pass to the offspring. These changes can (but not always) cause cancer or other diseases. Preferably, the mutation is a non-synonymous mutation. The term "non-synonymous mutation" refers to a mutation, preferably a nucleotide change, that results in an amino acid change, such as an amino acid change in a translation product.

According to the invention, the term "mutation" includes point mutations, insertion-deletions, cross-links, chromothripsis and RNA-editing mutations.

According to the invention, the term "insert-deletion" describes a specific class of mutations, defined as a mutation that results in colocalized insertion and deletion and in the gain or loss of nucleotides. In the coding regions of the genome, if the length of the insertion-deletion is not a multiple of 3, they lead to a frameshift mutation. Insertion-deletion may be opposed to point mutation; in the case where insertion-deletion inserts and removes nucleotides from a sequence, a point mutation is a form of substitution that replaces one nucleotide with another.

Crosslinks can lead to the formation of hybrid genes formed from two previously separate genes. They can occur as a result of translocation, interstitial deletion, or inversion of a chromosome segment. Cross-linked genes are often oncogenes. Oncogenic crosslinked genes can result in a gene product with a new or different function from that of the two crosslinking partners. Otherwise, the proto-oncogene is linked to a strong promoter and thereby the oncogenic function is turned on by upregulation caused by the strong promoter from the 5' region of the crosslinking partner. The production of oncogenic cross-linked transcripts can also be caused by trans-splicing or misread events.

According to the invention, the term "chromothripsis" refers to a genetic event in which specific regions of the genome are cleaved and then sewn back together in a single destructive event.

According to the invention, the terms "RNA editing" or "RNA editing" refer to molecular processes in which the information content in an RNA molecule is changed through a chemical change in the composition of the bases. RNA editing includes nucleoside modifications such as deaminations of cytidine (C) to uridine (U) and adenosine (A) to inosine (I), as well as non-template nucleotide additions and insertions. RNA editing in mRNA changes the amino acid sequence of the encoded protein so that it differs from that predicted by the genomic DNA sequence.

The term "cancer mutation signature" refers to mutations that are present in cancer cells compared to non-tumor reference cells.

According to the invention, a "reference" can be used to correlate and compare the results obtained in the methods of the invention from tumor samples. Typically, a "reference" may be derived from one or more normal samples that are not susceptible to neoplastic disease, or obtained from a patient or from one or more individuals, preferably healthy, in particular from individuals of the same species. A "reference" can be determined empirically by testing a sufficiently large number of normal samples.

Any suitable sequencing method can be used according to the invention, with Next Generation Sequencing (NGS) technologies being preferred. Third Generation Sequencing methods may replace NGS technology in the future to increase the speed of the method's sequencing step. For the sake of clarity, the terms "Next Generation Sequencing" or "NGS" in the context of the present invention means all new high-throughput sequencing technologies that, in contrast to the "standard" sequencing methodology known as the Sanger method, read nucleic acid arrays randomly in parallel throughout the genome by breaking the entire genome into short sections. Such NGS technologies (also known as massively parallel sequencing technologies) can provide whole genome, exome, transcriptome (all transcribed genome sequences), or methylome (all methylated genome sequences) nucleic acid sequence information in a very short time, for example, within 1-2 weeks, preferably within 1-7 days, or most preferably within less than 24 hours, and in principle allow single cell sequencing methods. Many NGS platforms that are commercially available or that are mentioned in the scientific literature can be used in the context of the present invention, such as those described in Zhang et al. 2011: The impact of next-generation sequencing on genomics. J Genet Genomics 38(3), 95-109; or in Voelkerding et al. 2009: Next generation sequencing: From basic research to diagnostics. Clinical chemistry 55, 641-658. Particular examples of such NGS technologies/platforms are

1. Sequencing-by-synthesis technology, known as pyrosequencing, performed, for example, in the "GS-FLX 454 Genome Sequencer ^TM " of a company associated with Roche, "454 Life Sciences" (Brenford, Connecticut), first described in Ronaghi et al. 1998: A sequencing method based on real-time pyrophosphate. Science 281 (5375), 363-365. This technology uses emulsion PCR, in which single-stranded DNA-binding beads are encapsulated by vigorous shaking into aqueous micelles containing PCR reagents surrounded by emulsion PCR amplification oil. In the pyrosequencing process, the light emitted from the phosphate molecules during the incorporation of nucleotides is recorded as the polymerase synthesizes the DNA strand.

2. Sequence-by-synthesis methods developed by Solexa (now part of Illumina Inc., San Diego, CA) based on reversible terminator dyes and run in, for example, the Illumina/Solexa Genome Analyzer™ and in the Illumina HiSeq 2000 Genome Analyzer™. In this technology, all four nucleotides are added simultaneously to cluster fragments with hybridized nucleotide primers in channels with flow cells containing DNA polymerase. Bridge amplification expands the cluster strands with all four fluorescently labeled nucleotides for sequencing.

3. Sequencing-by-ligation methods, such as those performed on the SOLid™ platform of Applied Biosystems (now Life Technologies Corporation, Carlsbad, CA). In this technology, a pool of all possible fixed length oligonucleotides is labeled according to the sequenced position. Oligonucleotides are annealed and ligated; preferential ligation with DNA ligase for paired sequences results in a signal that is informative of the nucleotide at that position. Prior to sequencing, the DNA is amplified by emulsion PCR. The resulting beads, each containing only copies of a single DNA molecule, are placed on a glass slide. As a second example, the Polonator™ G.007 platform from Dover Systems (Salem, New Hampshire) also employs a sequencing-by-ligation method using random bead-based emulsion PCR to amplify DNA fragments for parallel sequencing.

4. Single molecule sequencing technologies such as, for example, those used in the PacBio RS system from Pacific Biosciences (Menlo Park, Calif.) or the HeliScope™ platform of Helicos Biosciences (Cambridge, Massachusetts). The excellent characteristics of this technology lie in its ability to sequence single molecules of DNA or RNA without amplification, defined as real-time single molecule DNA sequencing (SMRT). For example, HeliScope uses a highly sensitive fluorescence detection system to directly detect each nucleotide as it is synthesized. A similar fluorescence resonance energy transfer (FRET) method has been developed at Visigen Biotechnology (Houston, Texas). Other fluorescence-based single molecule sequencing technologies are "U.S. Genomics (GeneEngine™) and Genovoxx (AnyGene™).

5. Nanotechnologies for single molecule sequencing, which use various nanostructures, for example, located on a chip to track the movement of a polymerase molecule along a single strand during replication. Particular examples of nanotechnology-based methods are the "GridON™" platform from Oxford Nanopore Technologies (Oxford, UK), assisted hybridization nano-pore sequencing ("HANS™") platforms from Nabsys (Providence, Rhode Island) , and a proprietary ligase-based DNA sequencing platform using DNA nanoball (DNB) technology called combinatorial probe-anchor ligation (“cPAL™”).

6. Single molecule sequencing technologies based on electron microscopy, such as those developed by LightSpeed Genomics (Sunnyvale, CA) and Halcyon Molecular (Redwood City, CA).

7. Ion semiconductor sequencing, which is based on the detection of hydrogen ions that are released during DNA polymerization. For example, Ion Torrent Systems (San Francisco, CA) uses a high-density chip of micro-machined wells to carry out this biochemical process in a massively parallel fashion. Each well contains a different DNA template. The bottom of the wells is an ion sensitive layer, which is a patented ion sensor.

Preferably, DNA and RNA preferably serve as starting material for NGS. Such nucleic acids can easily be obtained from samples such as biological material, for example, from fresh, quick-frozen or paraffin-embedded formalin-fixed tumor tissues (FFPE) or from freshly isolated cells or from CTCs that are present in the peripheral blood of patients. Normal unmutated genomic DNA or RNA can be isolated from normal somatic tissue, however, germline cells are preferred in the context of the present invention. Germ DNA or RNA is isolated from peripheral blood mononuclear cells (PBMC) of patients with non-hematologic malignancies. Although nucleic acids isolated from FFPE tissues or from freshly isolated single cells are highly fragmented, they are suitable for NGS applications.

Several targeted NGS methods for exome sequencing are described in the scientific literature (for a review, see, for example, Teer and Mullikin 2010: Human Mol Genet 19 (2), R145-51), each of which can be used in conjunction with the present invention. Many of these methods (described, for example, as genome capture, genome separation, genome enrichment, etc.) use hybridization methods and include chip-based methods (for example, Hodges et al. 2007: Nat. Genet. 39, 1522 -1527) and solution hybridization methods (e.g., Choi et al. 2009: Proc. Natl. Acad. Sci USA 106, 19096-19101). Commercial kits for DNA sample preparation and subsequent exome capture are also available: for example, "Illumina Inc." (San Diego, CA) offers "TruSeq™ DNA Sample Preparation Kit" and "Exome Enrichment Kit TruSeq™ Exome Enrichment Kit".

In order to reduce the number of false positives when detecting tumor-specific somatic mutations or sequence differences when comparing, for example, the sequence of a tumor sample with the sequence of a reference sample, such as the sequence of a germline sample, it is preferable to determine the sequence in duplicates of one or both of these types of samples. Thus, it is preferable that the sequence of the reference sample, such as the sequence of the germline sample, is determined two times, three times or more. Otherwise, or additionally, the sequence of the tumor sample is determined two times, three times or more. It is also possible to determine the sequence of a reference sample, such as the sequence of a germline sample and/or the sequence of a tumor sample more than once by determining at least once the sequence of genomic DNA and determining at least once the RNA sequence of said reference sample and/or specified tumor sample. For example, by determining the variation between replicates of a reference sample, such as a germline sample, the false positive (FDR) somatic mutation rate can be determined as a statistic. Technical replicates of a sample should produce identical results, and any detectable mutation in a given self-versus-self comparison is a false positive. Specifically, to determine the false positive rate for detecting somatic mutations in a tumor sample relative to a reference sample, the technical replica of the reference sample can be used as a benchmark for estimating the number of false positives. In addition, various quality-related metrics (eg, overlap or SNP quality) can be combined into a single quality score using a machine learning method. For a given somatic variation, all other variations can be scored in excess of the quality score, making it possible to order all variations in the dataset.

According to the invention, a high throughput single cell genome wide genotyping method can be used.

In one embodiment of high throughput single cell genome wide genotyping, the "Fluidigm" platform can be used. Such a method may include the following steps:

1. Collection of tumor tissue/cells and healthy tissue from a given patient.

2. Genetic material is isolated from tumor and healthy cells and then its exome (DNA) is sequenced using standard next generation sequencing (NGS) protocols. The overlap of NGS is such that heterozygous alleles can be detected with at least 5% frequency. The transcriptome (RNA) is also isolated from tumor cells, converted to cDNA, and sequenced to determine which genes are expressed by tumor cells.

3. Non-synonymous expressed single nucleotide variations (English single nucleotide variation, SNV) are identified as described in this document. Filter out sites that are SNPs in healthy tissue.

4. N=96 mutations from (3) are selected by overlapping different frequencies. SNP genotyping assays based on fluorescence detection are designed and synthesized for these mutations (examples of such assays include: TaqMano based SNP assay from Life Technologies or SNPtype assays from Fluidigm). The tests will include specific target amplification (STA) primers to amplify amplicons containing this SNV (this is the standard in the TaqMan and SNPtype tests).

5. Individual cells will be isolated from tumor and healthy tissue either by laser microdissection (LMD) or by disaggregation to single cell suspensions followed by sorting as previously described (Dalerba P. et al. (2011) Nature Biotechnology 29: 1120- 1127). Cells can be selected either without pre-selection (ie all), or, alternatively, tumor cells can be enriched. Enrichment methods include: specific staining, cell size sorting, histological analysis during LMD, and so on.

6. Individual cells will be isolated in PCR tubes containing the master mix along with STA primers and the SNV containing amplicons will be amplified. Otherwise, the single cell genome will be amplified by whole genome amplification (WGA) as previously described (Frumkin D. et al. (2008) Cancer Research 68: 5924). Cell lysis will be carried out either in a heating step at 95°C or with a special lysis buffer.

7. STA-amplified samples are diluted and loaded onto the Fluidigm genotyping chip.

8. Healthy tissue samples will be used as positive controls to identify clusters of homozygous alleles (no mutation). Since NGS data reveals that homozygous mutations are exceptionally rare, typically only two clusters are expected: XX and XY, with X=healthy.

9. The number of chips that can be made is not limited, with the possibility of practical implementation of the analysis up to ~1000 single cells (~10 chips). If carried out in 384-well plates, sample preparation will be reduced to several days.

10. Then determine the SNV for each cell.

In another embodiment of high throughput single cell genome wide genotyping, the NGS platform may be used. Such a method may include the following steps:

1. Steps 1-6 above are identical except that N (the number of SNVs analyzed) can be much larger than 96. In the case of WGA, several STA cycles will be performed after. The STA primers will contain two universal tag sequences on each primer.

2. After STA, the barcoded primers will be amplified by PCR into amplicons. Barcoded primers contain unique "barcode" sequences and the above generic label sequences. Each cell will thus contain a unique barcode.

3. Amplicons from all cells will be mixed and sequenced by NGS. A practical limitation on the number of cells that can be multiplexed is the number of plates that can be prepared. Since samples can be prepared in 384-well plates, the practical limit would be ~5000 cells.

4. Based on sequence data, SNV (or other structural abnormalities) of individual cells are detected.

According to the invention, tumor genetic reconstruction based on single cell genotyping ("phylogenetic antigen prioritization") can be used to prioritize antigens. In addition to an antigenic priority system based on criteria such as expression, mutation type (non-synonymous vs. other), MHC-binding characteristics, and so on, an additional prioritization avenue designed to deal with intratumoral and intertumoral heterogeneity and bias can be used. biopsy, can be used as described, for example, below.

1. Identification of most common antigens

The frequency of each SNV can be accurately estimated based on the single cell assay described above, in conjunction with the high throughput whole genome genotyping method, and most of the widespread SNVs present can be selected for individualized cancer vaccines (IVACs).

2. Identification of primary basal antigens based on root tree analysis.

NGS data from tumors suggest that homozygous mutations (hot spots in both alleles) are rare events. Thus, there is no need for haplotyping, and a phylogenetic tree of tumor somatic mutations can be generated from single cell SNV data. The germ sequence will be used for the root of the tree. Using an algorithm to reproduce hereditary sequences, sequences of nodes near the root of the tree will be reproduced. These sequences contain the earliest mutations predicted to exist in the primary tumor (defined herein as primary basal mutations/antigens). Due to the low probability that two mutations will occur on the same alleles at the same position in the genome, mutations in ancestral sequences are predicted to be fixed in the tumor.

Prioritizing primary basal antigens is not equivalent to prioritizing the most common mutations in a biopsy (although primary basal mutations are expected to be among the most common in biopsies). The reason is: let's say two SNVs are present in all biopsy cells (and thus have the same frequency of 100%), but one mutation is basal and the other is not, so the basal mutation must be selected for IVAC. This is because the basal mutation is likely to be present in all areas of the tumor, while the later mutation may be a more recent mutation that was accidentally fixed in the area where the biopsy was taken. In addition, basal antigens probably exist in metastatic tumors derived from the primary tumor. Thus, by prioritizing basal antigens for IVAC, the skilled artisan can greatly increase the chance that IVAC will be able to eradicate the entire tumor rather than just part of the tumor.

If secondary tumors exist and they have also been selected, then the evolutionary tree of all tumors can be estimated. This approach can improve the robustness of the tree and allow the detection of mutations that are basal to all tumors.

3. Identification of antigens that maximally cover the tumor(s)

Another way to obtain antigens, which maximally covers all tumor sites, is to take several biopsies from the tumor. One strategy would be to select antigens identified by NGS analysis present in all biopsies. To improve the chances of identifying basal mutations, phylogenetic analysis can be performed based on single cell mutations from all biopsies.

In the case of metastasis, biopsies can be obtained from all tumors and mutations identified by NGS that are common to all tumors can be selected.

4. Use of CTC to prioritize antigens that inhibit metastasis

It is believed that metastatic tumors are obtained from single cells. Thus, by genotyping individual cells isolated from a given patient's various tumors, in conjunction with genotyping the patient's circulating tumor cells (CTCs), one can reconstruct the evolutionary history of the cancer. The expectation is to observe metastatic tumors evolving from the original tumor through the phylogenetic branch of the CTC isolated from the primary tumor.

Below (an unbiased method for CTC identification, enumeration and genetic probing), we describe an extension of the above high-throughput single cell genome-wide genotyping method for unbiased isolation and genomic analysis of CTC. Using the analysis described above, the specialist can subsequently reconstruct the phylogenetic tree of the primary tumor, CTC, and secondary tumors developed from metastases (if any). Based on this tree, the specialist can identify mutations (slave and lead) that appear at or shortly after CTCs first detach from the primary tumor. The expectation is that the genomes of CTCs derived from the primary tumor are evolutionarily more similar to the genomes of the primary tumor than the genomes of the secondary tumor. In addition, the genomes of CTCs derived from a primary tumor are expected to contain unique mutations that are fixed in secondary tumors, or that are likely to be fixed if secondary tumors form in the future. These unique mutations can be prioritized for IVAC to target (or prevent) metastasis.

The advantage of CTC priority mutations versus primary basal mutations is that CTC-derived antigens can mobilize T cells specifically to target metastases, and thus they will be an independent wing of T cell targeting of the primary tumor (using different antigens). In addition, if there are few or no secondary tumors, then the chance of immune escape from CTC-derived antigens is expected to be lower, since the likelihood for a tumor to escape immunity will correlate with the number of tumor cells bearing a given antigen.

5. Identification of antigens present in the same cell (“cocktail” IVAC)

It is believed that the tumor evolves by suppressing mutations as a result of the selective pressure of the immune system and therapy. Cancer vaccines that target multiple antigens that coexist on the same cell and that are also not uncommon in the tumor have a greater chance of overcoming the tumor's immune escape mechanism, and thus reduce the chance of recurrence. Such "vaccine cocktails" would be similar to antiretroviral combination therapy for HIV+ patients. Coexisting mutations can be identified by phylogenetic analysis or by checking the SNV alignment of all cells.

In addition, according to the invention, an unbiased method for identifying, enumerating and genetically probing CTCs can be used. Such a method may include the following steps:

1. Obtaining a biopsy of the tumor(s) and determining the atlas of somatic mutations.

2. Step 1: Selection of N≥96 mutations for further study based on the previously developed prioritization scheme.

Step 2: Perform a single cell analysis (see the high throughput single cell genome wide genotyping method described above) followed by phylogenetic analysis to select for N≥96 primary basal mutations and possibly more recent mutations for maximum diversity. The former mutations are applicable for CTC identification (see below), and the latter for phylogenetic analysis (see section “identification of antigens coexisting on the same cell (“IVAC cocktail”)).

3. Obtaining whole blood from a cancer patient

4. Lysis of erythrocytes

5. Removal of leukocytes by depletion of CD45+ cells (eg, by sorting, magnetic microspheres conjugated with an anti-CD45 antibody, etc.) to enrich CTC.

6. Removal of free DNA by DNase hydrolysis. The source of free DNA can be DNA present in the blood or DNA from dead cells.

7. Sorting the remaining cells into PCR tubes, performing STA (based on selected mutations) and screening for "Fluidigm" (high throughput single cell genome wide genotyping method described above). CTCs should generally be positive across multiple SNVs.

8. Cells identified as tumor (=CTC) can then be further analyzed phylogenetically based on a panel of screened SNVs (see Identification of Antigens Coexisting on the Same Cell (“IVAC Cocktail”)).

It is also possible to combine this method with previously created methods for dedicated CTCs. For example, one skilled in the art can sort EpCAM+ cells, or cells positive for cytokeratins (Rao CG. et al. (2005) International journal of oncology 27:49; Allard WJ. et al. (2004) Clinical Cancer Research 10: 6897-6904) . These putative CTCs can then be confirmed/probed with Fluidigm/NGS to isolate their mutations.

This method can be used to calculate CTC. Since the method is not based on a specific marker that may or may not be expressed by tumor cells, but rather is based on the mutation profile of tumor somatic mutations unique to the patient, it is an unbiased method for detecting and enumerating CTC.

According to the invention, a method can be used that includes tumor phylogenetic reconstruction based on single cell genotyping to enrich leading mutations ("phylogenetic filter").

In one embodiment of this method, a pan-tumor phylogenetic analysis is performed to extract leading mutations.

For example, leading mutations from n=1 tumors can be detected.

In the above section "Identification of primary basal antigens based on the analysis" tree with a root ", we described a method for identifying the original sequences and/or identifying cells that have sequences close to the" tree root ". It is expected that the number of mutations in these sequences will be significantly less than the number of mutations in the total tumor sample, since by definition they are sequences close to the "root of the tree". Thus, by selecting sequences close to the "root of the tree", it is expected that many driven mutations will be "phylogenetically filtered out". This procedure has the potential to significantly enrich leading mutations. The lead mutations can then be used to identify/select a patient's treatment, or can be used as keys for new therapies.

In another example, lead mutations can be detected from n>1 tumors of a given type.

By reconstructing primary basal mutations from a variety of tumors of a particular type, one can significantly increase the chance of detecting leading mutations. Since basal sequences close to the "root of the tree" filter out many lead mutations, the signal-to-background ratio for detecting lead mutations is expected to increase significantly. Thus, this method has the potential to detect (1) a less frequent lead mutation (2) a frequent lead mutation from fewer samples.

In another embodiment of the method, including tumor phylogenetic reconstruction based on single cell genotyping to enrich for lead mutations ("phylogenetic filter"), a phylogenetic analysis is performed to extract lead mutations that cause metastasis.

In the above section "Using CTC to prioritize antigens that inhibit metastasis" we described a method for detecting CTC-associated mutations. This method can also be used to enrich for leading mutations leading to metastasis. For example, by mapping the combined phylogenetics of the primary tumor, secondary tumor, and CTC, CTCs isolated from the primary tumor should be linked between the phylogenetic branches of the primary and secondary tumors. Such phylogenetic analysis can help pinpoint mutations that are unique in a given transitional state between primary and secondary tumors. A fraction of these mutations may represent lead mutations. In addition, by comparing unique CTC mutations from different cases of the same tumor (i.e., n>1 tumors), one can further enrich for unique metastasis-causing lead mutations.

According to the invention, phylogenetic analysis can be used to identify primary versus secondary tumors.

In the case of metastasis, if all tumors are sampled, the rooted tree can be used to predict the temporal order in which tumors appear: which tumor is primary (nodes closest to the tree root) and which tumors are the most recent. This may be useful in cases where it is difficult to determine which tumor is the primary.

In the context of the present invention, the term "RNA" refers to a molecule that includes at least one ribonucleotide residue and preferably consists entirely or partially of ribonucleotide residues. "Ribonucleotide" refers to a nucleotide containing a hydroxyl group at the 2' position of the β-D-ribofuranosyl group. The term "RNA" includes double-stranded RNA, single-stranded RNA, isolated RNA such as partially or completely purified RNA, virtually pure RNA, synthetic RNA, and recombinantly produced RNA such as modified RNA that differs from natural RNA by insertion, deletion, substitution and/ or a change in one or more nucleotides. Such changes may include the insertion of non-nucleotide material, such as at the end(s) of the RNA or internally, for example, to one or more nucleotides of the RNA. Nucleotides of RNA molecules may also include non-standard nucleotides such as synthetic nucleotides or chemically synthesized nucleotides or deoxynucleotides. These altered RNAs may be referred to as natural RNA analogs or analogs.

According to the present invention, the term "RNA" includes and preferably refers to "mRNA". The term "mRNA" means "messenger RNA" and refers to a "transcript" that is generated using a DNA template and encodes a peptide or polypeptide. Typically, an mRNA includes a 5'-UTR, a protein-coding region, and a 3'-UTR. mRNA has only a limited half-life in cells and in vitro. In the context of the present invention, mRNA can be obtained in vitro by transcription of a DNA template. The methodology for in vitro transcription is known to those skilled in the art. For example, there are many commercially available kits for in vitro transcription.

According to the invention, the stability and efficiency of RNA translation can, if necessary, be modified. For example, the RNA can be stabilized and its translation increased by one or more modifications that have a stabilizing effect and/or increase the efficiency of RNA translation. Such modifications are described, for example, in PCT/EP2006/009448, incorporated herein by reference. In order to increase the expression of the RNA used according to the present invention, it can be modified within the coding region, i.e. sequence encoding the expressed peptide or protein, preferably without changing the sequence of the expressed peptide or protein, so as to increase the GC content to increase mRNA stability and to effect codon optimization and thus enhance translation in cells.

The term "modification" in the context of the RNA used in the present invention, includes the modification of RNA, which is not normally present in the specified RNA.

In one embodiment of the invention, the RNA used according to the invention does not contain uncapped 5'-triphosphates. Removal of such uncapped 5'-triphosphates can be achieved by treating the RNA with phosphatase.

RNA according to the invention may contain modified ribonucleotides in order to increase its stability and/or reduce cytotoxicity. For example, in one embodiment, in the RNA used according to the invention, 5-methylcytidine is partially or completely replaced, preferably completely, by cytidine. Alternatively or additionally, in one embodiment, in the RNA used according to the invention, pseudouridine is partially or completely replaced, preferably completely, by uridine.

In one embodiment, the term "modification" refers to providing the RNA with a 5'-cap or 5'-cap analogue. The term "5'-cap" refers to the capping structure found at the 5' end of the mRNA molecule and typically consists of a guanosine nucleotide linked to the mRNA via an unusual 5'-5' triphosphate bond. In one embodiment, this guanosine is methylated at the 7-position. The term "standard 5'-cap" refers to the naturally occurring RNA 5'-cap group, preferably the 7-methylguanosine (m ⁷ G) cap group. In the context of the present invention, the term "5'-cap" includes a 5'-cap analog that resembles the structure of an RNA cap and that is modified so that it has the ability to stabilize RNA and/or enhance translation of RNA when attached to it, preferably in vivo and/ or in a cage.

Preferably, the 5' end of the RNA includes a cap structure having the following general formula:

where R_oneand R₂are independently hydroxy or methoxy, and W^-, X^- and Y^- are independently oxygen, sulfur, selenium, or BH₃. In a preferred embodiment R_oneand R₂are hydroxy, and W^-, X^- and Y^- are oxygen. In a further preferred embodiment, one of R_oneand R₂, preferably R_oneis hydroxy and the other is methoxy, and W^-, X^- and Y^- are oxygen. In a further preferred embodiment, R_oneand R₂are hydroxy, and one of the W^-, X^- and Y^-, preferably X^-represents sulfur, selenium, or BH₃, preferably sulfur while the other is oxygen. In a further preferred embodiment, one of R_oneand R₂, preferably R₂are hydroxy and the other is methoxy, and one is W^-, X^- and Y^-, preferably X^-represents sulfur, selenium, or BH₃, preferably sulfur while the other is oxygen.

In the above formula, the nucleotide on the right side is linked to the RNA chain through its 3' group.

Those Cap structures where at least one of W ^- , X ^- and Y ^- is sulfur, i. e. which has a phosphorothioate component exist in various diastereomeric forms, each of which is covered in this document. In addition, the present invention covers all tautomers and stereoisomers of the above formula.

For example, the cap structure having the structure described above, where R ₁ is methoxy _, R ₂ is hydroxy, X ^- is sulfur, and W ^- and Y ^- are oxygen, exists in two diastereomeric forms (Rp and Sp). They can be resolved on reverse phase HPLC and are named D1 and D2 according to the order in which they were eluted from the reverse phase HPLC column. According to the invention, the D1 m ₂ ^7,2'-O Gpp _S pG isomer is particularly preferred.

The production of RNAs containing a 5'-cap or 5'-cap analog can be achieved by in vitro transcription of a DNA template in the presence of said 5'-cap or 5'-cap analog, where said 5'-cap is cotranscriptionally incorporated into the formed the RNA strand or RNA can be generated, for example, by in vitro transcription, and the 5'-cap can be attached to the RNA post-transcriptionally using capping enzymes, for example, capping enzymes of the vaccinia virus.

The RNA may include additional modifications. For example, additional modification of the RNA used in the present invention may be an extension or shortening of the natural poly(A) tail or a change in the 5' or 3' untranslated regions (UTRs), such as introducing a UTR that is not associated with a coding region. said RNA, e.g. insertion or replacement of an existing 3'-UTR with one or more, preferably two, copies of a 3'-UTR derived from a globin gene such as alpha2-globin, alpha1-globin, beta-globin, preferably beta-globin more preferably human beta globin.

RNA containing an open poly-A sequence is translated more efficiently than RNA containing a hidden poly-A sequence. The term "poly(A) tail" or "poly-A sequence" refers to a sequence of adenyl(A) residues that are typically located at the 3' end of an RNA molecule, and "open poly-A sequence" means that a poly -A sequence at the 3' end of the RNA molecule containing A poly-A sequences not followed by nucleotides other than A located at the 3' end, i.e. below the poly-A sequence. In addition, a long poly-A sequence of about 120 base pairs results in optimal transcript stability and RNA translation efficiency.

Thus, in order to increase the stability and/or expression of the RNA used according to the invention, it can be modified so as to be present together with a poly-A sequence, preferably having a length of 10-500 adenosine residues, more preferably 30-300, even more preferably 65-200 and especially 100-150 adenosine residues. In a particularly preferred embodiment, the poly-A sequence is approximately 120 adenosine residues in length. To further increase the stability and/or expression of the RNA used according to the invention, the poly-A sequence may be open.

In addition, the inclusion of the 3'-untranslated region (UTR) in the 3'-untranslated region of the RNA molecule can lead to an increase in the efficiency of translation. A synergistic effect can be achieved by including two or more of these 3' untranslated regions. The 3'-untranslated regions may be autologous or heterologous to the RNA into which they are introduced. In one specific embodiment, the 3'-untranslated region is isolated from the human β-globin gene.

A combination of the above modifications, i.e. the incorporation of a poly-A sequence, the opening of a poly-A sequence, and the incorporation of one or more 3'-untranslated regions has a synergistic effect on RNA stability and enhances translation efficiency.

The term "stability" of RNA refers to the "half-life" of RNA. "Half-life" refers to the period of time that is required for the loss of half the activity, amount or number of molecules. In the context of the present invention, the half-life of an RNA is indicative of the stability of said RNA. The half-life of RNA can influence the "length of expression" of the RNA. An RNA having a long half-life can be expected to be expressed over an extended period of time.

Of course, if according to the invention it is desirable to reduce the stability and/or efficiency of RNA translation, then modification of the RNA is possible, which interferes with the function of elements that, as described above, increase the stability and/or efficiency of RNA translation.

The term "expression" is used according to the invention in its broadest sense, and includes the production of RNA and/or peptides or proteins, for example, using transcription and/or translation. In relation to RNA, the term "expression" or "translation" refers specifically to the production of peptides or polypeptides. It also includes partial expression of nucleic acids. In addition, expression may be transient or stable.

According to the invention, the term expression also includes "aberrant expression" or "abnormal expression". "Aberrant expression" or "abnormal expression" means according to the invention that the expression is changed, preferably increased, compared to a reference, for example, the state of an object that does not have a disease associated with aberrant or abnormal expression of a certain protein, for example, a tumor antigen. An increase in expression refers to an increase of at least 10%, specifically at least 20%, at least 50% or at least 100% or more. In one embodiment, expression is found only in diseased tissue while expression in healthy tissue is repressed.

The term "specifically expressed" means that the protein is expressed essentially only in a specific tissue or organ. For example, the fact that a tumor antigen is specifically expressed in the gastric mucosa means that said protein is predominantly expressed in the gastric mucosa and is not expressed in other tissues, or is not expressed to a significant extent in other tissues or organ types. Thus, a protein that is exclusively expressed in gastric mucosal cells and to a much lesser extent in any other tissue, such as the testes, is specifically expressed in gastric mucosal cells. In some embodiments, the tumor antigen can also be specifically expressed under normal conditions in more than one tissue type, such as 2 or 3 tissue or organ types, but preferably no more than 3 different tissue or organ types. In this case, the tumor antigen is specifically expressed in these organs. For example, if a tumor antigen is expressed under normal conditions, preferably in approximately equal proportions in the lung and in the stomach, then said tumor antigen is specifically expressed in the lung and in the stomach.

In the context of the present invention, the term "transcription" refers to the process in which the genetic code of a DNA sequence is transcribed into RNA. The RNA can then be translated into protein. According to the present invention, the term "transcription" includes "in vitro transcription", where the term "in vitro transcription" refers to a process in which RNA, specifically mRNA, is synthesized in vitro in a cell-free system, preferably using appropriate cell extracts. Preferably, cloning vectors are used to generate transcripts. These cloning vectors are generally designed as transcription vectors and are encompassed by the term "vector" according to the invention. According to the present invention, the RNA used in the present invention is preferably an in vitro transcribed RNA (IVT-RNA) and can be obtained by in vitro transcription of an appropriate DNA template. The transcription control promoter can be any promoter for any RNA polymerase. Specific examples of RNA polymerases are T7, T3, and SP6 RNA polymerases. Preferably, in vitro transcription according to the invention is controlled by a T7 or SP6 promoter. A DNA template for in vitro transcription can be obtained by cloning a nucleic acid, specifically a cDNA, and inserting it into an appropriate in vitro transcription vector. cDNA can be obtained by reverse transcription of RNA.

The term "translation" according to the invention refers to the process in the ribosome of a cell by which a messenger RNA chain directs the assembly of an amino acid sequence to produce a peptide or polypeptide.

The expression control sequences or regulatory sequences that may be operably linked to a nucleic acid according to the invention may be homologous or heterologous to the nucleic acid. A coding sequence and a regulatory sequence are "operably" linked together if they are covalently linked together such that transcription or translation of the coding sequence is under the control or influence of the regulatory sequence. If the coding sequence is translated into a functional protein with the regulatory sequence operably linked to the coding sequence, then induction of the regulatory sequence results in transcription of the coding sequence without causing a frameshift in the coding sequence or failure to translate into the target protein or peptide.

The term "expression control sequence" or "regulatory sequence" includes, according to the invention, promoters, ribosome binding sequences, and other control elements that control the transcription of a nucleic acid or translation of the resulting RNA. In one embodiment of the invention, regulatory sequences can be controlled. The exact structure of the regulatory sequences may vary by species or by cell type, but generally includes 5'-untranslated and 5'- and 3'-untranslated sequences that are involved in initiating transcription or translation, such as TATA- boxing, capping sequences, CAAT sequence, and so on. Specifically, 5'-non-translated regulatory sequences include a promoter region that includes a transcriptional control sequence for an operably linked gene. The regulatory sequences may also include enhancer sequences or 5' activator sequences.

Preferably, according to the invention, if the RNA expressed in the cell can be introduced into said cell. In one embodiment of the methods of the invention, the RNA that is introduced into the cell is obtained by in vitro transcription of the appropriate DNA template.

According to the invention, terms such as "RNA capable of being expressed" and "coding RNA" are used interchangeably herein and, in relation to a particular peptide or polypeptide, mean that RNA, if present in an appropriate environment, preferably within a cell, can be expressed to obtain said peptide or polypeptide. Preferably, the RNA which, according to the invention, is capable of interacting with the cellular translation apparatus to produce a peptide or polypeptide, is capable of being expressed.

Terms such as "transfer", "introduction" or "transfection" are used interchangeably herein and refer to the introduction of nucleic acids, specifically exogenous or heterologous nucleic acids, in particular RNA, into a cell. According to the present invention, a cell may form part of an organ, tissue and/or organism. According to the present invention, the introduction of a nucleic acid is achieved both using a "naked" nucleic acid, and in combination with an introduction reagent. Preferably, the introduction of nucleic acids occurs in the form of "naked" nucleic acids. Preferably, the RNA is administered in combination with stabilizing agents such as RNase inhibitors. The present invention also contemplates the re-introduction of nucleic acids into cells to allow expression over extended periods of time.

Cells can be transfected with any carrier that can associate with RNA, for example by complexing with RNA or by forming vesicles that embed or encapsulate the RNA, resulting in increased stability of the RNA compared to naked RNA. Carriers useful according to the invention include, for example, lipid-containing carriers such as cationic lipids, liposomes, in particular cationic liposomes, and micelles and nanoparticles. Cationic lipids can form complexes with negatively charged nucleic acids. Any cationic lipid can be used according to the invention.

Preferably, the introduction of an RNA that encodes a peptide or polypeptide into a cell, specifically a cell present in vivo, results in the expression of said peptide or polypeptide in the cell. In specific embodiments, targeting nucleic acids to specific cells is preferred. In such embodiments, the carrier that is used to introduce the nucleic acid into the cell (eg, a retrovirus or liposome) displays a targeting molecule. For example, a molecule, such as an antibody that is specific for a surface membrane protein on the target cell, or a ligand for a receptor on the target cell, may be included in or linked to the nucleic acid carrier. In the case where the nucleic acid is administered via a liposome, proteins that bind to a surface membrane protein that is associated with endocytosis can be included in the liposome formulation to allow targeting and/or uptake. Such proteins include capsid proteins or fragments thereof that are specific to a particular cell type, antibodies to proteins that are internalized, proteins that are intracellularly localized, and so on.

According to the present invention, the term "peptide" refers to substances comprising two or more, preferably 3 or more, preferably 4 or more, preferably 6 or more, preferably 8 or more, preferably 10 or more, preferably 13 or more, preferably 16 or more , preferably 21 or more and preferably up to 8, 10, 20, 30, 40 or 50, specifically up to 100 amino acids connected by covalent peptide bonds. The term "polypeptide" or "protein" refers to large peptides, preferably peptides containing more than 100 amino acid residues, but, in general, the terms "peptide", "polypeptide" and "protein" are synonymous and are used interchangeably herein.

According to the invention, the term "sequence change" in relation to peptides or proteins refers to amino acid insertion variants, amino acid addition variants, amino acid deletion variants and amino acid substitution variants, preferably amino acid substitution variants. All of these sequence changes according to the invention can potentially create new epitopes.

Inserted amino acid variants include insertions of one or two or more amino acids into a particular amino acid sequence.

Amino acid addition variants include amino and/or carboxy-terminal crosslinks of one or more amino acids, such as 1, 2, 3, 4 or 5 or more amino acids.

Deletion amino acid variants are characterized by the removal of one or more amino acids from a sequence, such as the removal of 1, 2, 3, 4, or 5 or more amino acids.

Substitutional amino acid variants are characterized in that at least one residue in the sequence is removed and another residue is inserted in its place.

The term "isolated" according to the invention means that a specific component, specifically, a specific sequence, is present in the subject from which it is isolated, specifically an organism or molecule. In the case of amino acid sequences, especially specific regions of the sequences, "isolated" specifically means that the corresponding amino acid sequence is isolated from the amino acid sequence in which it is present.

The term "cell" or "host cell" preferably represents an intact cell, ie. with an intact membrane that has not released its usual intracellular components such as enzymes, organelles, or genetic material. The intact cell is preferably a viable cell, ie. a living cell capable of carrying out its normal metabolic functions. Preferably, said term refers according to the invention to any cell that can be transformed or transfected using exogenous nucleic acid. The term "cell" includes, according to the invention, prokaryotic cells (e.g., E. coli) or eukaryotic cells (e.g., dendritic cells, B cells, CHO cells, COS cells, K562 cells, HEK293 cells, HELA cells, yeast cells, and insect cells ). The exogenous nucleic acid can be found within the cell (i) in a freely dispersed state, as such, (ii) incorporated into a recombinant vector, or (iii) integrated into the host cell's genome or mitochondrial DNA. Particularly preferred are mammalian cells such as human, mouse, hamster, pig, goat and primate cells. Cells can be isolated from a wide variety of tissue types and include primary cells and cell lines. Specific examples include keratinocytes, peripheral blood leukocytes, bone marrow stem cells, and embryonic stem cells. In further embodiments, the cell is an antigen presenting cell, in particular a dendritic cell, a monocyte, or a macrophage.

A cell that includes a nucleic acid molecule preferably expresses the peptide or polypeptide encoded by the nucleic acid.

The term "clonal expansion" refers to a process in which the amount of the respective component is multiplied. In the context of the present invention, the term is preferably used in the context of an immunological response in which lymphocytes are stimulated by an antigen, proliferate, and a specific lymphocyte recognizing said antigen multiplies. Preferably, clonal expansion leads to lymphocyte differentiation.

Terms such as "reduction" or "inhibition" refer to the ability to cause an overall decrease in the level, preferably 5% or more, 10% or more, 20% or more, more preferably 50% or more, and most preferably 75% or more. The term "inhibits" or similar expressions includes complete or substantially complete inhibition, i.e. reduction to zero or substantially to zero.

Terms such as "increase", "enhancement", "stimulation" or "prolongation" preferably refer to an increase, enhancement, stimulation or prolongation of at least about 10%, preferably at least 20%, preferably at least 30%, preferably at least 40%, preferably at least 50%, preferably at least 80%, preferably at least 100%, preferably by at least 200%, and specifically by at least 300%. These terms may also refer to an increase, enhancement, stimulation, or prolongation from zero, or an unmeasured or undetectable level, to a level greater than zero, or to a level that is measurable or detectable.

The agents, compositions, and methods described herein can be used to treat a subject having a disease, for example, a disease characterized by the presence of diseased cells expressing an antigen and presenting an antigenic peptide. Particularly preferred diseases include malignancies. The agents, compositions, and methods described herein may also be used for immunization or vaccination to prevent the disease described herein.

According to the invention, the term "disease" refers to any pathological condition, including malignant neoplasms, specifically those forms of malignant neoplasms that are described in this document.

The term "normal" refers to a healthy state or conditions in a healthy object or tissue, ie. to non-pathological conditions, where "healthy" preferably means non-cancerous.

A "disease involving cells expressing an antigen" according to the invention means that the expression of an antigen is detected in cells of a diseased tissue or organ. Expression in cells of a diseased tissue or organ may be increased relative to healthy tissue or organ. Increase refers to an increase of at least 10%, specifically at least 20%, at least 50%, at least 100%, at least 200%, at least , by 500%, at least 1000%, at least 10000% or even more. In one embodiment, expression is found only in diseased tissue while expression in healthy tissue is repressed. According to the invention, diseases involving or associated with cells expressing an antigen include malignant neoplasms.

A malignant tumor (medical term: malignant neoplasm) is a class of diseases in which a group of cells exhibits uncontrolled growth (dividing outside of normal boundaries), invasion (invading and destroying adjacent tissues), and sometimes metastasis (spread to other locations in the body through lymph or blood). These three malignant properties of malignancies distinguish them from benign tumors, which are self-limiting and do not invasive or metastasize. Most cancers form a tumor, but some, like leukemia, do not.

A malignant tumor is essentially synonymous with a malignant neoplasm. Neoplasia, malignancy, and malignancy are essentially synonymous.

According to the invention, the term "tumor" or "tumor disease" refers to the abnormal growth of cells (called neoplastic cells, tumor cells or tumor cells), preferably forming a tumor or lesion. The term "tumor cell" refers to an abnormal cell that grows by rapid uncontrolled cell proliferation and continues to grow after stimuli that initiated the cessation of new growth. Tumors show partial or complete loss of structural organization and functional coordination with normal tissue, and usually form a discrete mass of tissue that may be benign, premalignant, or malignant.

A benign tumor is a tumor that lacks all three of the malignant properties of a malignancy. Thus, by definition, a benign tumor does not grow indefinitely, in an aggressive manner, does not penetrate into surrounding tissues, and does not spread to non-adjacent tissues (does not metastasize).

Neoplasm is an abnormal mass of tissue as a result of neoplasia. Neoplasia (new growth in Greek) is an abnormal proliferation of cells. Cell growth is exceeded and not coordinated with the growth of normal tissues around them. Growth continues in the same exuberant manner even after the stimulus is removed. It usually causes a nodule or tumor to appear. Neoplasms can be benign, premalignant, or malignant.

"Tumor growth" or "tumor growth" according to the invention refers to the tendency of a tumor to increase in size and/or to the tendency of tumor cells to proliferate.

For the purposes of the present invention, the terms "cancer" and "disease associated with malignancy" are used interchangeably with the terms "tumor" and "neoplastic disease".

Malignant diseases are classified according to the type of cells that resemble the tumor, and thus the tissue is assumed to be the origin of the tumor. These are, respectively, histology and localization.

The terms "malignancy" or "cancer" according to the invention includes leukemias, seminomas, melanomas, teratomas, lymphomas, neuroblastomas, gliomas, rectal cancer, endometrial cancer, kidney cancer, adrenal cancer, thyroid cancer, blood cancer, skin cancer, cancer brain, cervical cancer, bowel cancer, liver cancer, colon cancer, stomach cancer, colon cancer, head and neck cancer, gastrointestinal cancer, lymph node cancer, esophageal cancer, colorectal cancer, pancreatic cancer, ear cancer, throat cancer and nose (ENT), breast cancer, prostate cancer, uterine cancer, ovarian cancer, lung cancer and their metastases. Examples include lung carcinoma, breast carcinoma, colon carcinoma, renal cell carcinoma, cervical carcinoma, or metastases of the types of cancer or tumor described above. The term cancer according to the invention also includes cancer metastases and cancer recurrence.

The main types of lung cancer are small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). There are three main types of non-small cell lung cancer: squamous cell lung cancer, adenocarcinoma, and large cell lung cancer. Adenocarcinomas account for approximately 10% of all lung cancers. This malignancy usually occurs in the peripheral regions of the lung in contrast to small cell lung cancer and squamous cell lung cancer, which both tend to be more centrally located.

Skin cancer is a malignant growth on the skin. The most common skin cancers are basal cell carcinoma, squamous cell carcinoma, and melanoma. Malignant melanoma is a serious type of skin cancer. It occurs due to the uncontrolled growth of pigment cells called melanocytes.

According to the invention, a "carcinoma" is a malignant tumor arising from epithelial cells. This group characterizes the most common malignant neoplasms, including common forms of breast, prostate, lung and colon cancer.

"Bronchiolar carcinoma" is a carcinoma of the lung believed to be derived from the epithelium of terminal bronchioles, in which neoplastic tissue extends along the alveolar walls and grows into small masses within the alveoli. Mucin can be found in some of these cells and in the material of the alveoli, which also includes denuded cells.

"Adenocarcinoma" is a malignant neoplasm that originates from the tissue of the glands. This tissue is also part of a larger category of tissue known as epithelial tissue. Epithelial tissue includes the skin, glands, and many other tissues that line the body's cavities and organs. The epithelium is embryologically derived from the ectoderm, endoderm and mesoderm. Cells do not need to be part of a gland to be classified as adenocarcinoma, provided they have secretory properties. This form of carcinoma can occur in some higher mammals, including humans. Well-differentiated adenocarcinomas tend to resemble the tissues of the gland from which they originate, while poorly differentiated ones may not. By staining the cells from the biopsy, the pathologist will determine if the tumor is an adenocarcinoma or some other type of cancer. Adenocarcinomas can occur in a variety of body tissues due to the nature of the ubiquitous presence of glands within the body. Although each of the glands may not secrete the same substances, if the cell has exocrine function, then it is considered glandular, and its malignant form is thus called adenocarcinoma. Malignant adenocarcinomas invade other tissues and often metastasize, given sufficient time to do so. Adenocarcinoma of the ovary is the most common type of ovarian carcinoma. It includes serum and mucosal adenocarcinoma, clear cell adenocarcinoma, and endometrioid adenocarcinoma.

Renal cell carcinoma, also known as renal cell carcinoma, or renal cell adenocarcinoma, is a cancer of the kidney that originates from the tissue lining the proximal convoluted tubule, very small channels in the kidney that filter the blood and remove waste products. Renal cell carcinoma is the much more common type of kidney cancer in adults and the most lethal of all genitourinary tumors. The various subtypes of renal cell carcinomas are clear cell renal cell carcinoma and papillary renal cell carcinoma. Clear cell renal cell carcinoma is the most common form of renal cell carcinoma. Under a microscope, the cells that make up clear cell renal cell carcinoma appear very light or transparent. Papillary renal cell carcinoma is the second most common subtype. These cancers form finger-like growths (called papillae) in some, if not most, tumors.

Lymphoma and leukemia are neoplasias derived from hematopoietic (blood-forming) cells.

A blast tumor or blastoma is a tumor (usually malignant) that resembles immature embryonic tissue. Many of these tumors are most common in children.

By "metastasis" is meant the spread of tumor cells from their place of origin to another part of the body. The formation of metastases is a very complex process and depends on the separation of malignant tumor cells from the primary tumor, invasion through the extracellular matrix, penetration through the endothelial basement membrane to enter the abdominal cavity and into the vessels, and then after the implementation of transport by the bloodstream, from infiltration of target organs. Finally, the growth of a new tumor, i.e. secondary tumor or metastatic tumor at the target site depends on angiogenesis. Tumor metastasis often occurs even after removal of the primary tumor, as tumor cells or components may remain and develop metastatic potential. In one embodiment, the term "metastasis" according to the invention refers to "distant metastasis", which refers to metastasis that is distant from the primary tumor and the regional lymph node system.

The cells of a secondary metastatic tumor are similar to the cells of the original tumor. This means that if ovarian cancer metastasizes to the liver, then the secondary tumor will be made up of abnormal ovarian cells and not abnormal liver cells. Therefore, a tumor in the liver is called metastatic ovarian cancer and not liver cancer.

In ovarian cancer, metastasis can occur in the following ways: through direct contact or spread, it can spread to nearby tissue or organs located close to or near the ovaries, such as the fallopian tubes, uterus, bladder, rectum, etc.; by settling or falling out in an abnormal cavity, which is the most common way for ovarian cancer to spread. Tumor cells rupture the surface of the ovarian mass and drip onto other structures in the abdomen, such as the liver, stomach, colon, or diaphragm; by breaking away from the mass of the ovary, penetrating the lymphatics and then traveling to other areas of the body or to distant organs such as the lung or liver; by detachment from the mass of the ovary, penetration into the circulatory system and then by movement to other areas of the body or to distant organs.

According to the invention, metastatic ovarian cancer includes a malignant tumor in the fallopian tubes, a malignant tumor in the abdominal organs such as the intestines, a malignant tumor in the uterus, a malignant tumor in the bladder, a malignant tumor in the rectum, a malignant tumor in the liver, a malignant tumor in the stomach, a cancer in the colon, a cancer in the diaphragm, a cancer in the lungs, a cancer in the area that lines the abdominal or pelvic cavity (peritoneum), and a cancer in the brain. Similarly, metastatic lung cancer refers to cancer that spreads from the lungs to distant and/or multiple sites in the body and includes liver cancer, adrenal cancer, bone cancer, and brain cancer.

The term "circulating tumor cells" or "CTC" refers to cells that detach from the primary tumor or from tumor metastases and circulate in the bloodstream. CTCs can form seed material for the subsequent growth of additional tumors (metastases) in various tissues. Circulating tumor cells are detected at a rate of 1-10 CTC/mL of whole blood from patients with metastatic disease. Research methods have been developed to isolate CTC. Several research methods for isolating CTC are described in the art, for example, methods that exploit the fact that epithelial cells normally express the cell adhesion protein EpCAM, which is not present in normal blood cells. Immunomagnetic bead capture involves treating blood samples with an anti-EpCAM antibody that is conjugated to magnetic particles, followed by separating the bound cells in a magnetic field. The isolated cells were then stained with antibody to another epithelial marker, cytokeratin, as well as to the common leukocyte marker CD45, so as to distinguish rare CTCs from contaminating leukocytes. This laborious and semi-automated method identifies CTCs with an average yield of approximately 1 CTC/ml and a purity of 0.1% (Allard et al., 2004: Clin Cancer Res 10, 6897-6904). The second method of CTC isolation uses a microfluidic CTC capture device that involves flowing whole blood through a chamber with 80,000 built-in microbeads that become functional due to coating with EpCAM antibody. CTCs are then stained with secondary antibodies either against cytokeratin or tissue-specific markers such as PSA in prostate cancer or HER2 in breast cancer and visualized by automated microbar scanning on multiple panels along 3D coordinates. CTC chips are able to identify cytokeratin-positive circulating tumor cells in patients with an average yield of 50 cells/ml and a purity in the range of 1-80% (Nagrath et al., 2007: Nature 450, 1235-1239). Another option for isolating CTC is to use the CellSearch™ Circulating Tumor Cell (CTC) test from Veridex, LLC (Raritan, NJ), which captures, identifies, and counts CTC in a blood tube. The CellSearch™ system is a US Food and Drug Administration (FDA) approved methodology for the enumeration of CTC in whole blood, which is based on a combination of immunomagnetic labeling and automated digital microscopy. There are other methods for isolating CTC described in the scientific literature, each of which can be used in conjunction with the present invention.

A relapse or relapse occurs when a person is again exposed to a condition that they were exposed to in the past. For example, if a patient suffered from a neoplastic disease, received successful treatment for said disease, and developed said disease again, then said newly developed disease may be considered a relapse or relapse. However, according to the invention, the return or recurrence of the neoplastic disease may optionally occur at the site of the original neoplastic disease. Thus, for example, if a patient has been suffering from an ovarian tumor and has been successfully treated, then recurrence or recurrence may be the occurrence of a tumor at a site other than the ovaries. The return or recurrence of the tumor also includes situations where the tumor appears in a place other than the site of the original tumor, as well as in the site of the original tumor. Preferably, the original tumor for which the patient has been treated is a primary tumor, and a tumor at a site other than the original tumor is a secondary or metastatic tumor.

The term "treat" means to administer a compound or composition as described herein to a subject for the purpose of preventing or eliminating a disease, including reducing the size of a tumor or the number of tumors in the subject; stopping or slowing down the disease in the subject; inhibiting or slowing the development of a new disease in the subject; reducing the frequency or severity of symptoms and/or relapses in a subject who currently has or previously had the disease; and/or renewal, i.e. increasing the lifespan of an object. Specifically, the term "treating a disease" includes curing, shortening, ameliorating, preventing, slowing or inhibiting the progression or worsening of, or preventing or delaying the onset of a disease or its symptoms.

The term "at risk" means an entity, i.e. a patient who is identified as having a higher than normal chance of developing a disease, specifically cancer, compared to the general population. In addition, an object that has or currently has a disease, specifically cancer, is an object that has an increased risk of developing the disease, such as the object may continue to develop the disease. Subjects that currently have or have had cancer also have an increased risk of cancer metastasis.

The term "immunotherapy" refers to treatment, including the activation of a specific immune response. In the context of the present invention, terms such as "protects", "prevents", "prophylactic", "preventive", or "protective" refer to preventing or treating or both in relation to the onset and/or continuation of a disease in a subject and specifically to minimize the chance that the subject will develop a disease, or to delay the development of a disease. For example, a person at risk of developing a tumor as described above would be a candidate for therapy to prevent a tumor.

Prophylactic administration of immunotherapy, for example, prophylactic administration of a composition of the invention, preferably protects the recipient from the development of the disease. The therapeutic administration of immunotherapy, for example, the therapeutic administration of a composition of the invention may result in inhibition of the progress/growth of the disease. Inhibition includes slowing down the progress/growth of a disease, specifically disrupting the progression of a disease, which preferably results in elimination of the disease.

Immunotherapy can be carried out using any and a variety of methods in which the agents provided herein act to remove diseased cells from a patient. Such removal may take place as a result of amplification or induction in the patient of an immune response specific to an antigen or a cell expressing the antigen.

In some embodiments, immunotherapy may be active immunotherapy, in which treatment is based on in vivo stimulation of the host's endogenous immune system to respond against diseased cells, with the administration of immune response modifying agents (such as the polypeptides and nucleic acids provided herein).

The agents and compositions provided herein may be used alone or in combination with standard therapeutic regimens such as surgery, radiation, chemotherapy, and/or bone marrow transplantation (autologous, synergistic, allogeneic, or foreign).

The term "immunization" or "vaccination" describes the process of treating an object to induce an immune response for therapeutic or prophylactic purposes.

The term "in vivo" refers to the situation in the subject.

The terms "object", "individual", "organism" or "patient" are used interchangeably and refer to vertebrate animals, preferably mammals. For example, mammals in the context of the present invention are humans, non-human primates, domestic animals such as dogs, cats, sheep, cattle, goats, pigs, horses, etc., laboratory animals such as mice, rats, rabbits, guinea pigs, etc., as well as captive animals such as zoo animals. The term "animal" as used herein includes a human. The term "object" may also include a patient, i. an animal, preferably a human, having a disease, preferably as described herein.

The term "autologous" is used to describe something that is extracted from the same object. For example, "autologous transplant" refers to a transplant of tissue or organs originating from the same entity. Such treatments are preferred because they overcome the immunological barrier that would otherwise lead to rejection.

The term "heterologous" is used to describe something that is made up of many different elements. For example, bone marrow transferred from one individual to another individual is a heterologous transplant. A heterologous gene is a gene isolated from a source other than the subject.

As part of an immunization or vaccination composition, it is preferred that one or more of the agents described herein be administered together with one or more adjuvants to induce an immune response or to enhance an immune response. The term "adjuvant" refers to compounds that prolong or enhance or accelerate the immune response. The composition of the present invention preferably exhibits its effect without the addition of adjuvants. In addition, the composition of the present invention may contain any known adjuvant. Adjuvants include a heterologous group of compounds such as emulsions (eg Freund's adjuvants), mineral compounds (such as alum), bacterial products (such as Bordetella pertussis toxin), liposomes, and immunostimulatory complexes. Examples of adjuvants are monophosphoryl lipid-A (MPL, SmithKline Beecham). Saponins such as QS21 ("SmithKline Beecham"), DQS21 ("SmithKline Beecham"; WO 96/33739), QS7, QS17, QS18, and QS-L1 (So et al., 1997, Mol. Cells 7: 178- 186), incomplete Freund's adjuvants, complete Freund's adjuvants, vitamin E, montanide, alum, CpG olignucleotides (Krieg et al., 1995, Nature 374:546-549), and various water-in-oil emulsions that are prepared from biologically degradable oils such as squalene and/or tocopherol.

Other substances that stimulate the patient's immune response may also be administered. For example, it is possible to use cytokines in vaccination, due to their regulatory properties in relation to lymphocytes. Such cytokines include, for example, interleukin-12 (IL-12) which has been shown to increase the protective effect of vaccines (see Science 268:1432-1434, 1995), GM-CSF and IL-18.

There are a number of compounds which enhance the immune response and which can thus be used in vaccination. These compounds include co-stimulatory molecules presented in the form of proteins or nucleic acids, such as B7-1 and B7-2 (CD80 and CD86, respectively).

According to the invention, a "tumor sample" is a sample, such as a physical sample containing tumor or cancer cells, such as circulating tumor cells (CTC), specifically a tissue sample, including biological fluids and/or a cellular sample. According to the invention, a "non-oncogenic sample" is such a sample as a physical sample that does not contain tumor or cancer cells, such as circulating tumor cells (CTC), specifically, a tissue sample, including biological fluids and/or a cellular sample. Such physical samples can be obtained in a standard manner, such as by tissue biopsy, including needle biopsy, and by collection of blood, bronchial aspirate, sputum, urine, feces, and other body fluids. According to the invention, the term "sample" also includes a processed sample, such as fractions or isolates of biological samples, for example, nucleic acids or cell isolates.

The therapeutically active agents, vaccines, and compositions described herein may be administered by any suitable route, including injection or infusion. Administration may be, for example, orally, intravenously, intraperitoneally, intramuscularly, subcutaneously or transdermally. In one embodiment, the administration is intranodal, such as by injection into a lymph node. Other forms of administration involve the in vitro transfection of antigen-presenting cells, such as dendritic cells, with the nucleic acids described herein, followed by the introduction of antigen-presenting cells.

The agents described herein are administered in effective amounts. "Effective amount" refers to the amount that achieves the desired response or effect, alone or in conjunction with other doses. In the case of treating a specific disease or a specific condition, the target response preferably refers to the inhibition of the course of the disease. Inhibition includes slowing down the progress of a disease, and in particular stopping or reversing the progress of a disease. The target response in the treatment of a disease or condition may also be to delay the onset or prevent the onset of said disease or said condition.

The effective amount of an agent described herein will depend on the condition being treated, the severity of the disease, individual patient parameters including age, physiology, size and weight, duration of treatment, type of concomitant therapy (if any), specific route of administration, and similar factors. Accordingly, the administered doses of the agents described herein may depend on a variety of such parameters. In the event that the patient's response is insufficient at the initial dose, higher doses may be used (or effectively higher doses given by another more precisely localized route of administration).

Pharmaceutical compositions according to the invention are preferably sterile and contain an effective amount of a therapeutically active substance to obtain the desired response or effect.

Pharmaceutical compositions of the invention are generally administered in pharmaceutically compatible amounts and in a pharmaceutically compatible formulation. The term "pharmaceutically compatible" refers to a non-toxic material that does not interact with the action of the active ingredient of the pharmaceutical composition. Formulations of this type may generally contain salts, buffers, preservatives, carriers, immune enhancing excipients such as adjuvants, for example CpG oligonucleotides, cytokines, saponin, GM-CSF and/or RNA, and where appropriate, therapeutically active compounds. . When used in medicine, the salts must be pharmaceutically compatible. However, salts that are not pharmaceutically compatible can be used to prepare pharmaceutically compatible salts and are included in the invention. Pharmacologically and pharmaceutically compatible salts of this type include in particular salts prepared from the following acids: hydrochloric, hydrobromic, sulfuric, nitric, phosphoric, maleic, acetic, salicylic, citric, formic, malonic, succinic acid and so on. Pharmaceutically compatible salts may also be prepared as alkali metal salts or alkaline earth metal salts such as sodium salts, potassium salts or calcium salts.

The pharmaceutical composition may include a pharmaceutically compatible carrier. The term "carrier" refers to an organic or inorganic component, natural or synthetic origin, where the active component is combined for the purpose of ease of use. According to the invention, the term "pharmaceutically compatible carrier" includes compatible solid or liquid filters, diluents or encapsulating substances that are suitable for administration to a patient. The components of the pharmaceutical composition according to the invention are usually such that there is no interaction that significantly impairs pharmaceutical efficacy.

The pharmaceutical compositions of the invention may contain suitable buffer substances such as acetic acid in salt, boric acid in salt and phosphoric acid in salt.

The pharmaceutical compositions, where necessary, may also contain suitable preservatives such as benzalkonium chloride, chlorobutanol, paraben and thimerosal.

Pharmaceutical compositions are usually presented in unit dosage form and may be prepared in a manner known per se. The pharmaceutical compositions of the invention may be in the form of capsules, tablets, lozenges, solutions, suspensions, syrups, elixirs or, for example, emulsions.

Compositions suitable for parenteral administration generally comprise a sterile aqueous or non-aqueous preparation of the active compound, which is preferably isotonic with the recipient's blood. Examples of compatible vehicles and diluents are Ringer's solution and isotonic sodium chloride solution. In addition, sterile fixed oils are commonly used as a solution or suspension medium.

The present invention is described in detail using the drawings and examples below, which are used for illustrative purposes only and are not intended to be limiting. Through the description and examples, the following embodiments, which are likely to be included in the invention, are available to a person skilled in the art.

Blueprints

Figure 1

Top: A method for detecting and prioritizing likely immunogenic somatic mutations in total tumor samples. Bottom: Method applied to the B16 and Black6 system.

Figure 2: Example of a Confirmed Mutation in Kif18b

A mutation identified in the Kif18b gene by NGS exome sequencing, which was confirmed by Sanger sequencing. In wild-type cells, the sequence is T/T. In tumor cells, the sequence is a mixture of T/G.

Figure 3: Immunological reactivity against mutated sequences

Mice (n=5) were immunized twice (d0, d7) with mutated peptide sequences (100 μg + 50 μg PolyI:C; subcutaneously). On day 12, mice were sacrificed and spleen cells were harvested. An "IFNγ ELISpot" assay was performed using 5x10 ⁵ spleen cells/well as effectors and 5x10 ⁴ bone marrow dendritic cells loaded with peptides (2 μg/ml for 2h at 37°C and 5% CO ₂ ) in as target cells. Spleen effector cells were tested against the mutated peptide, the wild-type peptide and the control peptide (vesicular stomatitis virus nucleoprotein, VSV-NP, ak 52-59). Shown is the mean value measuring the number of spots from which background anti-VSV-NP spots were subtracted for each mouse (open circles: mice immunized with wild-type peptide; solid boxes: mice immunized with mutated peptides). Data are presented for each mouse and the mean ± standard error of the mean is shown.

Figure 4: Survival advantage for mice vaccinated with newly identified mutated peptide sequences.

B16F10 cells (7.5 x 10 ⁴ ) were inoculated subcutaneously in d0. Mice were vaccinated with peptide 30 (Jerini Peptide Technologies (Berlin); 100 μg peptide + 50 μg poly I:C sc (Invivogen)) on day - 4, day + 2 and day + 9. The control group received Poly I:C only (50 µg sc). Tumor growth was monitored to day + 16*, p < 0.05 in log-rank test (Mantel-Cox).

Figure 5

(A) Examples of increased protein expression (left eGFP, right Luciferase) with RNA optimized for stable and efficient translation (B) Example of polyepitope expansion of antigen-specific CD8 ⁺ and CD4 ⁺ T cells with RNA optimized for efficient antigen targeting (see Reference Kreiter, Konrad, Sester et al, Cancer Immunol Immunother 56:1577-1587, 2007). T (C) An example of pre-clinical evidence of antitumor efficacy in the B16 melanoma model using an RNA vaccine that encodes a single epitope (OVA-SIINFEKL). Survival data were obtained from mice treated with the vaccine alone or with the vaccine in combination with an adjuvant. (D) Design of individual polyneoepitope vaccines. The vaccine carrier combines functional elements for increased expression and optimized immunogenicity. Up to 30 mutated epitopes that are separated by linkers can be integrated into a molecule in the context of their natural sequences.

Figure 6: Construct Design

(A) Schematic diagram of a polyepitope RNA construct. Cap: cap analogue; 5´UTR : 5´untranslated region; L : Linker; Seq. 1: RNA sequence encoding a peptide containing a mutated aa; 3´UTR : 3´untranslated region; poly-A: poly-A tail. (B) Sequence of RNA constructs encoding 2 aa sequences including a mutated aa from B16F10. The start and stop codon, as well as the signal peptide and the MITD sequence, are not part of the schematic drawing, which is indicated by "....".

Figure 7: Functionality of RNA polyepitope

(AC) Data for "IFNγ ELISpot" using 5 x 10 ⁵ spleen cells per well as effectors and 5 x 10 ⁴ BMDC as target cells. BMDC were loaded with peptide (2 μg/ml for 2h at 37°C and 5% CO ₂ ) or transfected with RNA (20 μg) by electroporation. Control RNA was eGFP (left panel) or an RNA construct encoding 2 unlinked peptides containing mutated aa separated by a linker. Data are presented as mean ± std. osh. average. (A) Shown are data for mutated peptide 30, wild-type peptide 30, and RNA encoding mutation 30 and 31. (B) Shown are data for mutated peptide 12, wild-type peptide 12, and RNA encoding mutation 12 and 39. (C) Depicted representative ELISpot scan for reading data from a single mouse shown in (B).

Figure 8: Two embodiments of polyneoepitope RNA vaccines showing bridging epitopes

An RNA vaccine can be designed with or without linkers (top) between mutant-encoding peptides. Good epitopes include those that include a somatic mutation (“*”) and bind to MHC molecules. Bad epitopes include epitopes that bind to MHC molecules but contain either parts of two peptides (bottom) or parts of a peptide and a linker sequence (top).

Figure 9: Identification and characterization of "T-cell drug-responsive mutanome"

(A) The flowchart gives an idea of the experimental procedure from samples B16F10 and C57BL/6 to the output of "ELISPOT" data. (B) Shown are the number of hits for each evaluation step and the mutation selection process for DNA confirmation and immunogenic testing. Mutations selected for confirmation and testing of immunogenicity are those predicted to be immunogenic and are found in genes expressed at RPKM > 10. (C) T-cell drug-responsive "mutanome" mapped to the B16F10 genome. Cycles from outer to inner position for the following subgroups: (1) present in each of the three repetitions, (2) FDR < 0.05, (3) localized in protein-coding regions, (4) cause non-synonymous changes, (5) localized in expressed genes, and (6) are presented in a confirmed form. Mouse chromosomes (outer circle), gene density (green), gene expression (green(low)/yellow/red(high)), and somatic mutations (orange).

Figure 10: Immune response elicited in vivo by vaccination of mice with long synthetic peptides representing the mutation

(A,B) "IFN-γ ELISPOT" analysis of T-cell effectors from mice vaccinated with peptides encoding the mutation. Columns represent the mean (±St. O. Mean) of 5 mice per group. Asterisks indicate statistically significant differences in reactivity against the mutation and against the wild-type peptide (Student's t-test; p-value < 0.05). (A) Splenocytes from vaccinated mice were restimulated with BMDCs transfected with the peptide encoding the mutation used for vaccination, the corresponding wild-type peptide, and a foreign control peptide (VSV-NP). (B) To analyze T cell reactivity against endogenously processed mutations, splenocytes from vaccinated mice were restimulated with BMDC, transfected control RNA (eGFP) or RNA encoding the indicated mutation. (C) Mutation 30 (Kif18B gene, Q6PFD6 protein, p.K739N mutation). Sanger sequencing and mutation sequence (top). Localization of protein domains and mutations (bottom).

Figure 11: Antitumor effects of mutated peptide vaccines in mice with aggressively growing B16F10 tumors

(A) C57BL/6 mice (n = 7) were inoculated with 7.5 x 10 ⁴ B16F10 cells sc. to the side of the mouse. On days 3 and 10 after tumor inoculation, mice were vaccinated with 100 μg MUT30 or MUT44 peptide + 50 μg poly(I:C) or adjuvant alone. (B) C57BL/6 mice (n=5) received one immunization with 100 μg MUT30 peptide + 50 μg poly(I:C) on day -4. On day 0, s.c. were inoculated. 7.5 x 10 ⁴ B16F10 cells in the flank of the mouse. Booster immunization with the MUT30 peptide (+poly(I:C)) was performed on days 2 and 9.

Kaplan-Meier survival curve (left). Kinetics of tumor growth (right).

Figure 12: Vaccination with RNA encoding mutations leads to CD4 ⁺ and CD8 ⁺ T-cell response

Data from analysis of intracellular cytokine staining for IFN-γ in CD4 ⁺ and CD8 ⁺ T-cell effectors derived from mice vaccinated with RNA encoding the mutation. RNA coded for 1 (Monoepitope, top row), 2 (Biepitope, middle row), or 16 (Polyepitope, bottom row) different mutations. Spots represent average values for 3 mice per group. Asterisks indicate statistically significant differences in reactivity against the mutation and against the control peptide (VSV-NP) (Student's t-test; p-value < 0.05). FACS plots show the effectors from the animal with the highest secretion of IFN-γ for each mutation and reveal the phenotype of the T-cell response.

Figure 13: Vaccination with Polyepitope RNA Encoding Mutations Leads to T Cell Responses Against Multiple Mutations

"IFN-γ ELISPOT" analysis of T-cell effectors from mice vaccinated with a mutation-encoding polyepitope peptide that carries 16 different mutations. Bars represent means (±SEM) for 3 mice per group. The photographs show three copies of wells with cells from one typical animal restimulated with the indicated peptides.

Figure 14: Vaccination with 5 different model epitopes encoded by a single RNA results in an immune response against all encoded epitopes

A) "IFN-γ ELISPOT" analysis of T-cell effectors from mice vaccinated with a model polyepitope peptide encoding mutations that carries 5 different model epitopes (SIINFEKL, Trp2, VSV-NP, Inf-NP, OVA class II). Splenocytes were re-stimulated with the indicated peptides. Spots characterize the average of three copies of wells from 5 mice per group. B) Pentamer staining of blood lymphocytes from one control mouse and one mouse immunized with the model polyepitope peptide. Inf-NP pentamer-stained CD8 ⁺ cells are specific for the Inf-NP peptide.

Figure 15: A Mutation-inducing CD4 ⁺ T cells can induce a potent antitumor effect against B16F10 melanoma in synergy with a weak CD8 ⁺ T cell epitope

C57BL/6 mice (n = 8) were inoculated with 1 x 10 ⁵ B16F10 cells sc. to the side. On days 3, 10 and 17 after tumor inoculation, mice were vaccinated with 100 µg MUT30, Trp2, or both peptides + 50 µg poly(I:C). A) shows the average value of the kinetics of tumor growth for each group. At day 28, the mean values between the single treatment groups and the untreated animals and the combined treatment group were statistically different (Mann-Whitney test, p-value < 0.05). B) Kaplan-Meier survival plot for different groups. The survival curves of mice vaccinated with MUT30 and MUT30 + Trp2 are statistically different (log-rank test, p-value = 0.0029).

Figure 16: Overview of the method for detecting somatic mutations in B16

The number of individual stages is given as an example for one B16 sample, compared to one black6 sample. "Exons" refers to the coordinates of the exons defined by all RefSeq protein-coding transcripts.

Figure 17: Venn diagram showing the number of somatic variations in protein-coding exons detected by one or two or all three software tools, respectively.

Amounts were calculated after filtration and represent the consensus of all three samples.

Figure 18: A Examples of single nucleotide variations detected: Somatic mutation found in all three B16 samples (left), non-somatic mutation found in all B16 and black6 samples (middle) and mutation found in only one black6 sample (right). B Computed FDR distribution for the dataset whose tested mutations were selected; the distribution is visualized as the mean calculated ROC curve with gray bars indicating the 95% confidence interval for the mean in both coordinates at uniformly sampled locations. The average is obtained from the distribution of the calculated ROC curves for FDR of all possible 18 combinations (see text).

Figure 19: A ROC Evaluation Curves for comparing three different software tools (duplicates, 38x coverage). B Estimated ROC curves for comparison of different average sequencing depths (samtools, no replicas). 38x is used to denote the coverage obtained by experiment, while other coverages have been downsampled starting from this data. C The calculated ROC curves visualize the effect of reproducing the experiment (38x coverage, "samtools"). D Estimated ROC curves for various sequencing protocols ("samtools", no replicas). Curves were evaluated using the results of the 2x100 nt library.

Figure 20: A Ten tested mutations with the lowest FDR values, selected using the optimal set of parameters from a finite set of 2396 variations. None of these mutations are present in dbSNP (version 128; mm9 genome assembly). B Relative amount of variation found in the same database as A for a given FDR limit, plotted separately for all database variants and mutations tested. For visual clarity, only values from 0 to 10% FDR are shown.

Figure 21: Antitumor activity of the mutation-encoding polyepitope RNA vaccine C57BL/6 mice (n=10) were inoculated with 1 x 10 ⁵ B16F10 cells sc. to the side of the mouse. On days 3, 6, 10, 17 and 21 after tumor inoculation, mice were vaccinated with polyepitope RNA, along with a liposomal RNA transfection reagent. The control group received liposomes without RNA. The figure shows a Kaplan-Meier survival plot for various groups. Survival curves are statistically different (log-rank test, p-value = 0.0008).

Examples

Methods and methods used herein are described or practiced as per se known and as described, for example, in Sambrook et al., Molecular Cloning: A Laboratory Manual, 2nd ^Edition (1989) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY All methods, including use of kits and reagents, are performed according to manufacturer's information unless specifically noted otherwise.

Example 1 Mutation Detection and Prioritization

We first demonstrated objective profiling of tumor and normal specimens, which is based on sequencing results, to identify somatic mutations. We have demonstrated this not only for bulk tumor samples, but also, for the first time, we have demonstrated the ability to identify mutations from individual circulating tumor cells. We then prioritized mutations for inclusion in the polyneoepitope vaccine based on the predicted immunogenicity of the mutations and demonstrated that the identified mutations are indeed immunogenic.

Mutation detection

Rationale for the use of CTC: The detection of circulating tumor cells (CTC) from the peripheral blood of cancer patients is a recognized independent prognostic marker of the clinical course of a tumor disease (Pantel et al, Trends Mol Med 2010; 16(9):398-406). For many years, the clinical significance of CTC has been the subject of intense scientific and clinical research in oncology. The detection of CTC in the blood of patients with metastatic breast, prostate, and colorectal cancer has been shown to be of prognostic value, providing additional information for traditional imaging methods and other prognostic tumor biomarkers. Sequentially taken blood samples taken from the patient before, at an early stage, and after treatment with a therapeutic agent (systemic or targeted) contain information about the response to treatment/treatment failure. Molecular analysis of drug-resistant CTCs may provide further insight into the mechanisms of resistance (eg, mutations in certain signaling pathways or loss of target expression) in individual patients. An additional opportunity for profiling and genetic characterization of CTC lies in the identification of new targets of malignant tumors for the development of new targeted therapies. This new diagnostic strategy is referred to as "Liquid Tumor Biopsy". Since profiling can be performed quickly and periodically, with the need to obtain only the patient's blood without surgery, this approach can provide a "real time" overview of the tumor status.

Tumor Cell Mutations We demonstrated our ability to identify mutations using B16 melanoma cells, exome capture to extract protein-coding regions, next-generation sequencing with our HiSeq 2000, followed by bioinformatic analysis with our iCAM software pipeline (Fig. one). We identified 2448 non-synonymous mutations and selected 50 for confirmation. We were able to confirm all 50 somatic mutations.

The following is an example of the effect on a protein of a detected somatic mutation in B16 melanoma cells:

Kifl8b, NM_197959, exon 3

Mutation (+15 ak) SPSKPSFQEFVDWENVSPELNSTDQPFLPS

Wild type (+15 ak) SPSKPSFQEFVDWEKVSPELNSTDQPFLPS

Individual circulating tumor cell (CTC) mutations: We were then able to identify tumor-specific somatic mutations by NGS RNA profiling from single CTCs. Labeled B16 melanoma cells were intravenously injected into mouse tails, mice were sacrificed, blood was collected from hearts, cells were sorted to extract labeled circulating B16 cells (CTC), RNA was extracted, "SMART" cDNA synthesis and non-specific amplification were performed, and then NGS analysis of RNA -Seq and subsequent data analysis (below).

We profiled eight individual CTCs and identified somatic mutations. Moreover, in eight of the eight cells, previously identified mutations were identified. In many cases, the data demonstrate heterogeneity at the level of individual cells. For example, at position 144078227 on chromosome 2 (mm9 assembly) in the Snx15 gene, two cells had a reference nucleotide (C) while two other cells had a mutated nucleotide (T).

This suggests that we are able to profile individual CTCs to identify somatic mutations, a fundamental route to iVAC (individualized vaccine) "real time" in which patients are profiled appropriately and the results reflect the patient's current status rather than status at an earlier time. point. Moreover, this suggests that we are able to identify heterogeneous somatic mutations that are present in a subset of tumor cells, which allows us to estimate the frequency of mutations, for example, to identify major mutations and rare mutations.

Ways

Samples: For the profiling experiment, samples include 5-10 mm tail samples from C57BL/6 mice ("Black6") and highly aggressive mouse melanoma cells ("B16"), which were originally derived from Black6 mice.

Circulating tumor cells (CTCs) were generated using fluorescently labeled B16 melanoma cells. B16 cells were resuspended in PBS and an equal volume of freshly prepared CFSE solution (5 µM in PBS) was added to them. The sample was gently mixed with a vibrating mixer, followed by incubation for 10 minutes at room temperature. To stop the labeling reaction, an equal amount of PBS containing 20% FSC was added to the sample and gently mixed with a vibrating mixer. After 20 minutes of incubation at room temperature, the cells were washed twice with PBS. Finally, cells were resuspended in PBS and injected intravenously (iv) into mice. Mice were sacrificed after 3 minutes and blood was collected.

Erythrocytes from blood samples were lysed by adding 1.5 ml of freshly prepared PharmLyse solution (Beckton Dickinson) per 100 μl of blood. After one wash step, 7-AAD was added to the sample and incubated for 5 minutes at room temperature. The incubation was followed by two wash steps and the sample was resuspended in 500 µl PBS.

CFSE-labeled circulating B16 cells were sorted using an "Aria I" ("BD") cell sorter. Single cells were sorted into 96-well v-bottom plates supplemented with RLT buffer (Qiagen) at a volume of 50 μl/well. After sorting was complete, the plates were stored at -80°C until nucleic acid extraction and sample preparation began.

Nucleic acid extraction and sample preparation: Nucleic acids from B16 cells (DNA and RNA) and Black6 tail tissue (DNA) were extracted using the Qiagen DNeasy Blood and Tissue kit (for DNA) and the Qiagen RNeasy Micro kit (for RNA).

RNA was extracted from individual sorted CTCs and SMART cDNA synthesis and non-specific amplification were performed. RNA from sorted CTC cells was extracted using the RNeasy Micro Kit (Qiagen, Hilden, Germany) according to the supplier's instructions. The modified BD SMART protocol was used for cDNA synthesis: Mint reverse transcriptase (Evrogen, Moscow, Russia) was combined with oligo(dT)-T-primer long to prime the first-strand synthesis reaction and TS-short (Eurogentec S.A. ", Seraing, Belgium), introducing an oligo(riboG) sequence to allow the creation of an extended template through the activity of the terminal transferase at the reverse transcriptase and to switch the template [Chenchik, A., Y. et al. 1998. Generation and use of high quality cDNA from small amounts of total RNA by SMART PCR. In Gene Cloning and Analysis by RT-PCR. P. L. J. Siebert, ed. BioTechniques Books, MA, Natick. 305-319]. 35 cycles with 5 U PfuUltra Hotstart High-Fidelity DNA Polymerase (Stratagene, La Jolla, CA) and 0.48 µM TS-PCR primer in the presence of 200 µM dNTP (amplification conditions: 2 min at 95 °C during , 30 s at 94°C, 30 s at 65°C, 1 min. at 72°C for, final elongation for 6 min. at 72°C). Successful amplification of the CTC genes was monitored using specific primers to track actin and GAPDH.

Next generation sequencing, DNA sequencing: Exome capture for DNA resequencing was performed using the Agilent Sure-Select solution capture assay [Gnirke A et al: Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing. Nat Biotechnol 2009, 27:182-189], in this case designed to capture all mouse protein-coding regions.

Briefly, 3 μg of purified genomic DNA was fragmented to 150-200 bp. using the ultrasonic device "Covaris S2". The ends of the gDNA fragments were completed with T4 DNA polymerase, Klenow fragment and phosphorylated at 5' with T4 polynucleotide kinase. Blunt-ended gDNA fragments were 3'-adenylated using a Klenow fragment (3' to 5' exo minus). Illumina 3' single T-overlapped paired end adapters were ligated to the gDNA fragments with T4 DNA ligase in a 10:1 molar ratio of adapter to genomic DNA insert. The gDNA fragments ligated with adapters were enriched, sequences specific for pre-capture and flow cell were added using Illumina PE PCR 1.0 and 2.0 primers and Herculase II polymerase (Agilent) during 4 PCR cycles.

500 ng of the adapter-ligated PCR-enriched gDNA fragments were hybridized with Agilent's SureSelect whole mouse exome biotinylated bait RNA library for 24 hours at 65°C. The hybridized gDNA/bait RNA complexes were removed using streptavidin-coated magnetic microspheres. The gDNA/bait RNA complexes were washed out and the bait RNAs were cleaved during elution in SureSelect elution buffer, leaving the captured PCR-enriched gDNA fragments with ligated adapters. The gDNA fragments were amplified by PCR after capture with Herculase II DNA polymerase (Agilent) and SureSelect GA primers for 10 cycles.

All purifications were performed in 1.8x the volume of AMPure XP magnetic microspheres (Agencourt). All quality controls were performed using the Qubit HS test from Invitrogen and the fragment size was determined using the HS DNA test on a Bioanalyzer 2100 from Agilent.

Exome-enriched gDNA libraries were clustered on cBot using the Truseq SR cluster kit v2.5 using 7 pM, and 50 bp. sequenced on Illumina HiSeq2000 using Truseq SBS kit-HS 50 bp.

Next Generation Sequencing, RNA Sequencing (RNA-Seq): mRNA-seq Barcoded cDNA libraries were generated from 5 µg of total RNA using a modified version of the Illumina mRNA-seq protocol. mRNA was isolated using Seramag Oligo(dT) magnetic microspheres (Thermo Scientific). The isolated mRNA was fragmented using divalent cations and heating, resulting in fragments in the range of 160-220 nucleotides. Fragmented mRNA was converted into cDNA using random primers and SuperScriptII (Invitrogen), followed by second strand synthesis using polymerase I and RNase H. The cDNA ends were completed with T4 DNA polymerase, Klenow fragment and phosphorylated 5' with T4 polynucleotide kinase. Blunt-ended cDNA fragments were 3'-adenylated using a Klenow fragment (3' to 5' exo minus). 3' single T-overlapping "Illumina multiplex" specific adapters were ligated with T4 DNA ligase in a molar ratio of adapter to cDNA insert of 10:1.

cDNA libraries were purified and selected for size 200-220 bp. using E-Gel 2% SizeSelect gel (Invitrogen). Enrichment, addition of Illumina six-base indexing sequences and flow cell sequences were performed by PCR using Phusion DNA polymerase (Finnzymes). All purifications were performed with 1.8x the volume of AgencourtAMPure XP magnetic beads. All quality controls were performed using the Qubit HS test from Invitrogen and the size of the fragments was determined using the HS DNA test on a Bioanalyzer 2100 from Agilent.

Barcoded RNA-Seq libraries were clustered on cBot with a Truseq SR cluster kit v2.5 using 7 pM and sequenced at 50 bp. on the Illumina HiSeq2000 using the Truseq SBS kit-HS 50 bp.

CTC: For RNA-Seq profiling of CTC, a modified version of this protocol was used that used 500-700 ng of SMART-amplified cDNA, double-ended adapters were ligated, and PCR enrichment was performed with Illumina PE PCR primers 1.0 and 2.0.

Analysis of NGS Data, Gene Expression: To determine expression values, Illumina HiSeq 2000 RNA sample output sequences were pre-processed according to standard Illumina protocol. The analysis includes filtering out low-quality reads and decompressing. For transcriptome analysis of RNA-Seq, sequence reads were aligned with a reference genomic sequence [Mouse Genome Sequencing Consortium. Initial sequencing and comparative analysis of the mouse genome. Nature, 420, 520-562 (2002)] using "bowtie" (version 0.12.5) [Langmead B. et al. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10:R25] using "-v2 --best" options for genome alignments and default options for transcript alignments. Alignment coordinates were compared with exon coordinates of RefSeq transcripts [Pruitt KD. et al. NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2005 Jan 1;33(Database issue):D501-4] and for each transcript the number of overlapping alignments was recorded. Sequence reads that did not align with the genomic sequence were aligned against a database of all possible exon-exon bridging sequences of the RefSeq transcripts. The number of reads aligned with the splicing boundaries were combined with the amounts of the corresponding transcript obtained in the previous step and normalized to RPKM (number of reads, per exon model kilobase per million reads mapped) (Mortazavi A et al., Nat Methods 2008;5:621- eight). (2008). Mapping and quantifying mammalian transcriptomes by rna-seq. Nat Methods, 5(7):621-628]) for each transcript. Both gene expression values and exon expression values were calculated based on the normalized number of reads overlapping each gene or exon, respectively.

Mutation detection, tumor-based part: 50 nt Illumina HiSeq 2000 single-ended reads were aligned with bwa (version 0.5.8c) [Li H. and Durbin R. (2009) Fast and accurate short read alignment with Burrows-Wheeler Transform . Bioinformatics, 25:1754-60] using the default settings with the mm9 mouse genome reference assembly. Indeterminate reads - these are those of the reads that map to many places in the genome - were deleted, the remaining alignments were sorted, indexed and converted to binary and compressed format (BAM), and the quality scores of the reads were converted from the Illumina standard "phred + 64" to scores the quality of the Sanger standard using shell scripts.

For each of the sequenced tracks, mutations were identified using three computer programs: "samtools" (version 0.1.8) [Li H. Improving SNP discovery by base alignment quality. bioinformatics. 2011 Apr 15;27(8):1157-8. Epub 2011 Feb 13], GATK (version 1.0.4418) [McKenna A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010 Sep;20(9):1297-303. Epub 2010 Jul 19], and "SomaticSniper" (http://genome.wustl.edu/software/somaticsniper). For samtools, we used the settings and filter criteria recommended by the authors, including first round filtering, maximum coverage 200. For the second round of samtools filtering, the minimum insertion-deletion quality score was 50, the minimum point mutation quality was 30. For mutation prediction " GATK", we followed the guidelines developed by the authors with best practices presented in the GATK user guide (http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit). The variant quality score recalibration step was omitted and replaced with hard filtering. For assignment of mutations using "SomaticSniper" used the default parameters, and only predicted mutations with a "somatic score" equal to 30 or more were considered further.

Mutation detection, CTC: According to the iCAM method for the main part of the tumor, 50 nt single-ended "Illumina HiSeq 2000" reads were aligned with "bwa" (version 0.5.8c) [5]) using the default settings of the reference assembly of the mouse genome mm9 . Since the CTC NGS reads were generated from the RNA-Seq assay, the reads were also aligned for transcriptome sequences, including exon-exon junctions, using the "bowtie" (above). Using all nucleotide sequences from the reads, we compared both the reference genome and mutations derived from the main part of the B16 tumor. To display the results, the identified mutations were evaluated both using Perl scripts and manually using the "samtools" and "IGV" (Integrated Genome Viewer) software.

The output of "mutation detection" is the identification of somatic mutations in tumor cells, from the sample - NGS data - a list of mutations. In B16 samples, we identified 2448 somatic mutations using exome resequencing.

Mutation prioritization

We then demonstrated the possibility of pipelined prioritization of mutations for inclusion in a vaccine. This method, called the "individual cancer mutation detection pipeline" (iCAM), identifies and prioritizes somatic mutations through a series of steps incorporating a variety of advanced algorithms and bioinformatics techniques. The output of this method is a list of somatic mutations prioritized based on likely immunogenicity.

Identification of Somatic Mutations: Mutations were identified using three different algorithms for both sample B16 and sample Black6 (Mutation Detection, above). The first step of iCAM is to combine the output lists of each algorithm to obtain a highly reliable list of somatic mutations. Variants issued by "GATK" and "samtools" in the same sample relative to the reference genome. To select highly significant mutations with few false positives for a given sample (ie, tumors or normals), mutations were selected such that they were identified in all replicas. Then selected options that are present in the tumor sample, but not present in the normal sample. SomaticSniper automatically reports potential somatic variations from paired tumor and normal data. We additionally filtered the results by the intersection of the results obtained from the replicas. To remove as many false positives as possible, we crossed the mutation lists obtained by applying all algorithms to all replicas. The final step for each somatic mutation is to assign a confidence value (p-value) for each mutation based on coverage depth, SNP quality, consensus quality, and mapping quality.

Mutation Impact: The impact of filtered, consensus, somatic mutations is scripted within the iCaM mutation detection pipeline. First, mutations that occur in genetic regions that are not unique in the genome, such as those that occur in protein paralogs and pseudogenes, are excluded from the analysis because sequence reads that align in multiple places are removed. Second, it is determined whether a mutation occurs in the transcript. Third, it is determined whether the mutation occurs in the protein-coding region. Fourth, the transcript sequence is translated with or without mutation to determine if there is a change in the amino acid sequence.

Mutation Expression: The iCAM pipeline selects somatic mutations that are found in genes and exons that are expressed in tumor cells. Expression levels are determined from the NGS data of RNA-Seq of tumor cells (above). The number of reads that overlap the gene and exon indicates levels of expression. These numbers are normalized to RPKM (number of reads, per exon model kilobase per million mapped reads) [Mortazavi A. et al. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008 Jul;5(7):621-8. Epub 2008 May 30]) and those expressed above 10 RPKM are selected.

MHC Binding: To determine the likelihood that an epitope containing a mutated peptide binds to an MHC molecule, the iCAM pipeline is run in a modified version of the MHC prediction software from the Immune Epitope Database (http://www.iedb.org/) . The local installation includes modifications to optimize the flow of data through the algorithm. For B16 and Black6 data, prediction was run with all available MHC class I black6 alleles and all epitopes for the respective peptide lengths. Mutations are chosen to be in an epitope that is in the 95% percentile distribution of the IEDB training data prediction score (http://mhcbindingpredictions.immuneepitope.org/dataset.html), considering all MHC alleles and all potential mutation-overlapping epitopes .

Mutation Selection Criteria: Somatic mutations are selected according to the following criteria: a) having unique sequence content, b) identified by all three programs, c) high mutation certainty, d) non-synonymous protein change, e) high level of transcript expression, f) and prediction of binding to suitable MHC class I.

The output of this method is a list of somatic mutations prioritized based on likely immunogenicity. There are 2448 somatic mutations in B16 melanoma cells. 1247 of these mutations were found in gene transcripts. Of these, 734 cause non-synonymous changes in proteins. Of these, 149 are found in genes expressed in tumor cells. Of these expressing non-synonymous mutations, 102 are predicted to be present on MHC molecules. These 102 probable immunogenic mutations then go through a mutation confirmation step (below).

Mutation confirmation

Somatic mutations from the resequenced DNA exome were confirmed by either of two methods, resequencing of the mutated region and RNA-Seq analysis.

To confirm the mutations by resequencing, the genomic region containing the mutation was amplified by standard PCR from 50 ng of both tumor DNA and normal control DNA. The size of the amplified products was in the range of 150-400 nt. The specificity of the reaction was controlled by loading the PCR product onto a Qiaxel device (Qiagen). PCR products were purified using a minElute PCR purification kit (Qiagen). Specific PCR products were sequenced using the standard Sanger sequencing method (Eurofins), followed by electrophoregram analysis.

Mutation confirmation was also performed by testing for tumor RNA. Tumor gene and exon expression values were obtained from RNA-Seq (NGS RNA sequencing), by mapping nucleotide sequences on transcripts and counting them. We tested the sequence data itself to identify mutations in the tumor sample [Berger MF. et al. Integrative analysis of the melanoma transcriptome. Genome Res. 2010 Apr;20(4):413-27. Epub 2010 Feb 23], thereby providing independent confirmation of identified somatic mutations derived from DNA.

Table 1. List of genes containing 50 verified mutations

Genes containing 50 identified and confirmed somatic mutations, annotated with gene symbol, gene name, and predicted location and function.

Example 2 IVAC Selection Algorithm Allows Detection of Immunogenic Mutations

To investigate whether specific T cell responses could be induced against confirmed B16F10 melanoma cell mutations, untreated C57BL/6 mice (n=5/peptide) were immunized twice (d0, d7) subcutaneously with 100 µg of peptide (+50 µg polyI:C as an adjuvant) containing either a mutated a sequence or a wild type a sequence (see Table 2). All peptides are 27 aa long with a wild-type mutated aa/a in the central position. On day 12, mice were sacrificed and spleen cells were harvested. Data were read using the IFNγ ELISpot method with 5x10 ⁵ spleen cells/well as effectors and 5x10 ⁴ bone marrow dendritic cells loaded with peptides (2 μg/ml) as target cells. Spleen effector cells were tested against the mutated peptide, wild-type peptide and control peptide (vesicular stomatitis virus nucleoprotein, VSV-NP).

On the 44 sequences tested, we observed that 6 of them induce T-cell immunity directed only against the mutated sequence but not against the wild-type peptide (FIG. 3).

The data prove that the identified and prioritized mutations can be used to induce tumor-specific T-cell immunity after application as a peptide vaccine in untreated mice.

Example 3 Identified Mutations Can Confer Therapeutic Antitumor Immunity

To test for the ability of the identified mutations to confer anti-tumor immunity after vaccination of intact mice, we investigated this issue with peptide no. 30, which has been shown to induce mutation-selective T-cell reactivity. B16F10 cells (7.5 x 10 ⁴ ) were inoculated subcutaneously in d0. Mice were vaccinated with peptide 30 (see Table 1; 100 µg peptide + 50 µg Poly I:C sc) on day - 4, day + 2 and day + 9. The control group received only Poly I:C (50 µg s.p.). to.). Tumor growth was monitored every other day. On day +16 we found that only 1 out of 5 mice in the peptide vaccine group developed a tumor, while in the control group 4 out of 5 mice showed tumor growth.

The data prove that a peptide sequence comprising a B16F10-specific mutation can confer anti-tumor immunity that is effectively capable of destroying tumor cells (see FIG. 4). Because B16F10 is a highly aggressive tumor cell line, the discovery that the methodology used to identify and prioritize mutations ultimately leads to the selection of a mutation that is already effective as a vaccine on its own is an important proof of concept for this entire process.

Example 4 Data supporting polyepitope antigen presentation

Tested mutations from the patient's protein coding regions constitute a pool from which candidates can be selected to assemble a polyneoepitope vaccine template for use as a precursor for GMP RNA vaccine fabrication. Suitable vector cassettes as a vaccine scaffold have already been described (Holtkamp, S. et al., Blood, 108: 4009-4017, 2006; Kreiter, S. et al., Cancer Immunol. Immunother., 56: 1577-1587, 2007 ; Kreiter, S. et al., J. Immunol., 180: 309-318, 2008). Preferred vector cassettes are modified in their coding and untranslated regions (UTRs) and maximize translation of the encoded protein over long periods of time (Holtkamp, S. et al., Blood, 108: 4009-4017, 2006; Kuhn, A. N. et al., Gene Ther., 17: 961-971, 2010). In addition, the vector scaffold contains antigen targeting modules for the simultaneous expansion of both cytotoxic and helper T cells (Kreiter, S. et al., Cancer Immunol. Immunother., 56: 1577-1587, 2007; Kreiter, S. et al., J. Immunol., 180: 309-318, 2008; Kreiter, S. et al., Cancer Research, 70 (22), 9031-9040, 2010 (Fig. 5) Importantly, we have shown that that such an RNA vaccine can be used to present multiple MHC class I and II epitopes simultaneously.

The IVAC sequences of the polyneoepitope RNA vaccine are constructed from a stretch of up to 30 amino acids, which include mutations in the center. These sequences are connected head-to-tail via short linkers to form a polyneoepitope vaccine encoding up to 30 or more selected mutations and their flanking regions. These patient-specific individually optimized inserts are codon-optimized and cloned into the RNA scaffold described above. Quality control of such constructs includes in vitro transcription and expression in cells to test for functional transcription and translation. Translation analysis will be performed with antibodies against the c-terminal targeting domain.

Example 5 Scientific proof of concept for an RNA construct with a poly-neo epitope

The concept of poly-neo epitope RNA is based on a long mRNA transcribed in vitro, which consists of contiguous sequences encoding mutated peptides connected by linker sequences (see Fig. 6). Coding sequences are selected from non-synonymous mutations and always have a codon inserted for the mutated amino acid flanked by regions of 30 to 75 base pairs from the context of the original sequence. The linker sequence encodes amino acids that are preferably not processed by the cellular antigen processing machinery.

The in vitro transcribed constructs are based on the pST1-A120 vector containing the T7 promoter, a tandem beta-globulin 3' UTR sequence, and a 120 bp poly(A) tail, which have been shown to increase the stability and translational efficiency of RNA, the ability of the encoded antigen to stimulate T cells (Holtkamp S. et al., Blood 2006; PMID: 16940422). In addition, a fragment of the MHC class I signal peptide and transmembrane and cytosolic domains were inserted, including a stop codon (MHC class I or MITD directed migration signal), flanked by a polylinker sequence for epitope cloning (Kreiter S. et al., J. Immunol. , 180: 309-318, 2008). The latter have been shown to increase antigen presentation, thereby enhancing the expansion of antigen-specific CD8+ and CD4+ T cells and improving effector functions.

For the first proof of concept, bi-epitope vectors were used, i.e. encoding one polypeptide containing two mutated epitopes. Codon-optimized sequences encoding (i) a mutated epitope of 20-50 amino acids, (ii) a glycine/serine-rich linker, (iii) a second mutated epitope of 20-50 amino acids, and (iv) an additional glycine/serine-rich linker , flanked by appropriate restriction endonuclease recognition sites for cloning into the pST1 construct described above, were designed and synthesized by a commercial vendor (Geneart, Regensburg, Germany). After sequence verification, they were cloned into a pST1-based vector framework to obtain constructs as shown in FIG. 6.

The pST1-A120 based plasmids described above were linearized with class IIs restriction endonuclease. The DNA of the linearized plasmids was purified by phenol/chloroform extraction and ethanol precipitation. The amount of linearized vector DNA was assessed spectrophotometrically and subjected to in vitro transcription in virtually the same way as described by Pokrovskaya and Gurevich (1994, Anal. Biochem. 220: 420-423). To obtain RNA with appropriately modified 5'-capping structures, a capping analog was added to the transcription reaction. In the reactions, GTP was present at a concentration of 1.5 mM, while the capping analog was present at a concentration of 6.0 mM. All other NTPs were present at 7.5 mM. At the end of the transcription reaction, the linearized vector DNA was digested with 0.1 U/μl of TURBO DNase (Ambion, Austin/Texas, USA) for 15 minutes at 37°C. RNA was purified from these reactions using the MEGAclear Kit (Ambion, Austin/Texas, USA) according to the manufacturer's protocol. The concentration and amount of RNA was estimated spectrophotometrically and analyzed on a Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA).

We used T from mice vaccinated with the peptide as effector cells. In the IFNγ ELISpot, we tested the ability of T cells induced by peptide vaccination as described above to recognize target cells (bone marrow dendritic cells, BMDC) activated with either the peptide (2 μg/mL, for 2 hours at 37°C and 5% CO ₂ ) or transfected RNA (20 µg, prepared as described above) by electroporation. As illustrated by the example in FIG. 7, for mutations 12 and 30 (see Table 2), we can observe that the RNA construct is able to give rise to an epitope recognized by mutation-specific T cells.

With the data presented, we could demonstrate that an RNA encoding a polyneoepitope including a glycine/serine rich linker can be translated and processed in antigen-presenting cells, resulting in the presentation of the correct epitope that is recognized by antigen-specific T cells.

Example 6 Polyneoepitope Vaccine Design - Need for a Linker

The polyneoepitope RNA construct contains a scaffold construct containing a plurality of peptides encoded by somatic mutations linked to a linker peptide sequence. In addition to optimizing codons and improving RNA stability and translational efficiency of the scaffold, one embodiment of the polyneoepitope RNA vaccine includes linkers designed to increase the presentation of MHC class I and II antigenic peptides and reduce the presentation of detrimental epitopes.

Linker: The linker sequence has been designed to connect multiple mutated peptides. The linker should allow the formation and presentation of the mutated epitope while interfering with the formation of detrimental epitopes such as those formed by the junction between adjacent peptides or between the linker sequence and endogenous peptides. These "junction" epitopes may not only compete with the target epitopes for cell surface presentation, reducing vaccine efficacy, but may also lead to an unwanted autoimmune reaction. Thus, we designed the linker sequence in order to a) avoid the formation of "junction" peptides that bind to MHC molecules, b) avoid the formation of "junction" peptides by proteasomal processing, c) achieve efficient translation and processing by the proteasome.

In order to avoid the formation of "connector" peptides that bind to MHC molecules, we compared different linker sequences. Glycine, for example, inhibits strong binding in the binding groove of the MHC [Abastado JP. et al., J Immunol. 1993 Oct 1;151(7): 3569-75]. We tested many linker sequences and many linker lengths and calculated the number of "connector" peptides that bind MHC molecules. We used the Immune Epitope Database (IEDB, http://www.immuneepitope.org/) software tools to calculate the probability that a given peptide sequence contains a ligand that will bind MHC class I molecules.

In model B16, we identified 102 expressed non-synonymous somatic mutations that were predicted to be presented on the MHC class I molecule. Using 50 confirmed mutations, we calculated various vaccine products using either no linkers or different linker lengths. , and calculated the number of detrimental "junction" peptides using the IEDB algorithm (Fig. 8).

Table 5 shows the results of several different linkers, various linker lengths, and results with no linker and with five linkers. The number of MHC binding bridging peptides ranges from 2 to 91 for predicted data for 9 aa and 10 aa epitopes (top and bottom). Linker size affects the number of linking peptides (bottom). For this sequence, the smallest 9 aa epitopes were predicted for the 7 aa linker sequence GGSGGGG.

Linker 1 and Linker 2 used in the experimentally tested polyneoepitope RNA vaccine constructs (see below) also have advantageously low predicted linking neoepitopes. This is true for 9-measure and 10-measure predictions.

This suggests that the linker sequence is critical for the formation of poor MHC-binding epitopes. Moreover, the length of the linker sequence affects the number of bad MHC-binding epitopes. We found that sequences that are G-rich prevent the formation of MHC-binding ligands.

Table 3. Linker effect (10 aa epitopes)

The predicted number of bad epitopes, defined as class I MHC-binding epitopes that contain bridging sequences, for each peptide linker. 10 amino acid epitopes are considered here. Glycine-rich linkers contain the fewest "connecting" epitopes.

Table 4. Effect of the Linker part (9 aa epitopes)

The predicted number of bad epitopes, defined as MHC class I binding epitopes that contain junction sequences, for each peptide linker. 9 amino acid epitopes are considered here. Glycine-rich linkers contain the fewest "connecting" epitopes.

Table 5. Influence of the Linker Part

The predicted number of bad epitopes, defined as MHC class I binding epitopes that contain junction sequences, for each peptide linker. 9 amino acid epitopes are considered here. Top: number of 9 aa junction epitopes without a linker and with 5 different linkers. Middle: number of 100 aa junction epitopes without linker and with 5 different linkers. Bottom: Number of 99 aa junction epitopes for similar linkers of various lengths. Glycine-rich linkers contain the fewest connecting epitopes.

In order to avoid proteosomal processing, which may result in the formation of "junction" peptides, we investigated the use of different amino acids in the linker. Glycine-rich sequences impair proteosomal processing [Hoyt MA et al. (2006). EMBO J 25(8): 1720–9; Zhang M. and Coffino P. (2004) J Biol Chem 279 (10): 8635–41]. Thus, the action of glycine-rich linker sequences is based on minimizing the amount of linker-containing peptides that can be processed by the proteasome.

The linker must allow the mutated peptides to be efficiently translated and processed by the proteasome. The amino acids glycine and serine are flexible [Schlessinger A and Rost B., Proteins. 2005 Oct 1;61(1):115-26]; their incorporation into linkers results in a more flexible protein. We included glycine and serine in the linker to increase the flexibility of the protein, which should allow for more efficient translation and processing by the proteasome, which in turn allows better access to encoded antigenic peptides.

Thus, the linker must be glycine rich in order to prevent bad epitopes from binding to the MHC; should interfere with the ability of the proteasome to process linker peptides, which can be done by incorporating glycine; and should be flexible to increase access to peptides containing mutations, which can be done through a combination of the amino acids glycine and serine. Therefore, in one embodiment of the vaccine construct of the invention, the sequences GGSGGGGSGG and GGSGGGSGGS are preferably included as linker sequences.

Example 7 Polyneoepitope RNA Vaccine

The polyneoepitope RNA constructs are based on the pST1-A120 vector containing the T7 promoter, the 3'UTR tandem beta-globin sequence, and 120 bp. tail poly(A), which have been shown to increase the stability and translational efficiency of RNA, thereby enhancing the ability of the encoded antigen to stimulate T cells ((Holtkamp S. et al., Blood 2006; PMID: 16940422). In addition, there have been inserted a fragment of the MHC class I signal peptide and transmembrane and cytosolic domains including a stop codon (MHC class I signal migration or MITD) flanked by a polylinker sequence for epitope cloning (Kreiter S. et al., J. Immunol., 180: 309-318 , 2008) The latter has been shown to increase antigen presentation, thereby enhancing the expansion of antigen-specific CD8+ and CD4+ T cells and improving effector functions.

To obtain RNA constructs with a polyneoepitope for 50 identified and tested B16F10 mutations, 3 RNA constructs were generated. The constructs consist of codon-optimized sequences encoding (i) a mutated 25 amino acid epitope, (ii) a glycine/serine rich linker, (iii) repeats of the mutated epitope sequence followed by a glycine/serine rich linker. The chain of sequences containing the mutated epitope and the linkers are flanked by suitable restriction endonuclease recognition sites for cloning into a pST1-based construct as described above. The vaccine constructs were designed and synthesized by GENEART. After sequence verification, they were cloned into a pST1-based vector scaffold to obtain vaccine constructs with an RNA polyneoepitope.

Description of the clinical method

Clinical application will cover the following stages:

- Eligible patients must consent to DNA analysis by next generation sequencing.

- A tumor sample obtained during routine diagnostic procedures (paraffin-embedded, formalin-fixed tissue) and peripheral blood cells will be obtained and used for mutation analysis as described.

- Detected mutations will be confirmed

- Based on this, a prioritized vaccine will be designed. For RNA vaccines, a reference plasmid template will be obtained by gene synthesis and cloning.

- Plasmids will be used to obtain clinical grade RNA, quality control and RNA vaccine.

- The vaccine drug product will be sent to the appropriate testing center for clinical use.

- The RNA vaccine can be used as a bulk vaccine in a buffer mixture or can be encapsulated in nanoparticles or liposomes for direct injection, for example, into the lymph nodes, s.c., i.v., im. Alternatively, an RNA vaccine can be used to transfect in vitro, for example, dendritic cells for adoptive transfer.

The entire clinical process will take less than 6 weeks. The "lag phase" between patient informed consent and drug availability will be carefully regulated by the clinical trial protocol, including permission to continue the standard treatment regimen until the investigational product is available.

Example 8. Identification of tumor mutations and their use for tumor vaccination

We used exome NGS resequencing to detect mutations in the B16F10 mouse melanoma cell line and identified 962 non-synonymous somatic point mutations, 563 in expressed genes. Potential lead mutations occur in classical tumor suppressor genes (Pten, Trp53, Tp63, Pml) and genes involved in proto-oncogenic signaling pathways that control cell proliferation (eg, Mdm1, Pdgfra), cell adhesion and migration (e.g. Fdz7, Fat1) or apoptosis (Casp9). Moreover, B16F10 accumulates mutations in Aim1 and Trrap that have previously been described as frequently altered in human melanoma.

The immunogenicity and specificity of the 50 tested mutations were tested using C57BL/6 mice immunized with long peptides encoding the mutated epitopes. One third (16/50) of them were shown to be immunogenic. Of these, 60% exhibit immune responses preferentially directed against the mutated sequence over the wild-type sequence.

We tested the hypothesis in tumor transplant models. Immunization with peptides confers in vivo tumor control under protective and therapeutic conditions, qualifying mutated epitopes containing single amino acid substitutions as effective vaccines.

Animals

C57BL/6 mice (Jackson Laboratories) were maintained in accordance with federal and state animal research policies at the University of Mainz.

Cells

The B16F10 melanoma cell line was purchased in 2010 from the American Type Culture Collection (Product Number: ATCC CRL-6475, Lot Number: 58078645). Early (3rd, 4th) cell passages were used in tumor experiments. Cells were tested in a standard manner for Mycoplasma. Cells were not re-authenticated after receipt.

Next generation sequencing

Nucleic acid extraction and sample preparation: DNA and RNA from a large number of B16F10 cells and C57BL/6 tail DNA and tissue were extracted three times using the Qiagen DNeasy Blood and Tissue kit (for DNA) and the Qiagen RNeasy Micro kit (for RNA).

Exome DNA sequencing: Exome capture for DNA resequencing was performed three times with an Agilent Sure-Select mouse solution capture assay (Gnirke A et al., Nat Biotechnol 2009;27:182-9) designed to capture all mouse coding region proteins. 3 μg of purified genomic DNA (gDNA) was fragmented to 150-200 bp. using the ultrasonic device "Covaris S2". The ends of the fragments were completed, phosphorylated at 5' and adenylated at 3' according to the manufacturer's instructions. Paired Illumina end adapters were ligated to the gDNA fragments using a molar ratio of adapters to gDNA of 10:1. Enriched sequences for pre-capture and flow cell were added with primers "Illumina PE PCR 1.0" and "2.0" during 4 cycles of PCR. 500 ng of adapter-ligated PCR-enriched gDNA fragments were hybridized with Agilent's SureSelect RNA library of biotinylated whole mouse exome baits for 24 hours at 65°C. The hybridized gDNA/bait RNA complexes were removed with streptavidin-coated magnetic beads, and the bait RNA was cleaved during elution in SureSelect elution buffer. These eluted gDNA fragments were PCR amplified after capture for 10 cycles. Exome-enriched gDNA libraries were clustered on cBot using the Truseq SR cluster kit v2.5 using 7 pM, and 50 bp. sequenced on Illumina HiSeq2000 using Truseq SBS kit-HS 50 bp.

RNA-based Gene Expression, "Transcriptome" Profiling (RNA-Seq): Barcoded "mRNA-seq cDNA" libraries were prepared in triplicate, from 5 μg of total RNA (modified Illumina mRNA-seq protocol). mRNA was isolated using "Seramag Oligo(dT)" (Thermo Scientific) magnetic microspheres and fragmented using divalent cations and heating. The resulting fragments (160–220 nt) were converted into cDNA using random primers and SuperScriptII (Invitrogen), followed by the synthesis of the second strand using DNA polymerase I and RNase H. The cDNA ends were repaired in, and then they were phosphorylated at 5' and adenylated at 3' according to the manufacturer's instructions. 3' single T-overlapping "Illumina multiplex" specific adapters were ligated with T4 DNA ligase in a molar ratio of adapter to cDNA insert of 10:1. cDNA libraries were purified and selected by size 200-220 bp. (gel "E-Gel 2% SizeSelect", "Invitrogen"). Enrichment, addition of six base Illumina indexing sequences and flow cell sequences was performed by PCR using Phusion DNA polymerase (Finnzymes). All purifications up to this stage were carried out in 1.8x the volume of magnetic microspheres "AgencourtAMPure XP". All quality controls were performed using the Qubit HS test from Invitrogen and the size of the fragments was determined using the HS DNA test on a Bioanalyzer 2100 from Agilent. Barcoded RNA-Seq libraries were clustered and sequenced as described above.

NGS Data Analysis, Gene Expression: The readouts of the RNA sample sequences were preprocessed according to the standard Illumina protocol, including filtering for low quality readouts. Read sequence data were aligned to the mm9 reference genomic sequence (Waterston RH et al., Nature 2002;420:520-62) with a bowtie (version 0.12.5) (Langmead B et al., Genome Biol 2009;10:R25 ). For genome alignment, two mismatches were resolved and only the best alignment (“-v2 –best” was recorded); default parameters were used for transcriptome alignments. Readouts, not genomic sequence aligned, were aligned with the sequence database of all possible exon-exon junctions of RefSeq transcripts (Pruitt KD et al., Nucleic Acids Res 2007;35:D61-D65). Expression values were determined by the intersection of the read coordinates with those of the RefSeq transcripts that accounted for the overlapped exon and junction read data and normalized to RPKM expression units (number of reads, per exon model kilobase per million mapped reads) (Mortazavi A et al., Nat Methods 2008;5:621-8).

Analysis of NGS data, detection of somatic mutations: Somatic mutations were identified as described in Example 9. 50 bp one-sided reads were aligned to the reference mouse mm9 genome using "bwa" (default parameters, version 0.5.8c) (Li H and Durbin R, Bioinformatics 2009;25:1754-60). Ambiguous reads mapped at many locations in the genome were removed. Mutations were identified using three programs: "samtools" (version 0.1.8) (Li H, Bioinformatics 2011;27:1157-8), "GATK" (version 1.0.4418) (McKenna A et al, Genome Res 2010;20 :1297-303), and "SomaticSniper" (http://genome.wustl.edu/software/somaticsniper) (Ding L et al., Hum Mol Genet 2010;19:R188-R196). Potential variations identified in all three B16F10 repeats were assigned a false positive rate (FDR) value (see also example 9).

Selection, validation and function of mutations

Selection: For selection, mutations must meet the following criteria: (i) present in all three B16F10 repeats and absent in all three C57BL/6 repeats, (ii) FDR ≤0.05, (iii) homogeneity in C57BL/6, (iv) occur in the RefSeq transcript, and (v) cause non-synonymous changes that can be counted as a significant mutation. Selection for screening and testing for immunogenicity requires the mutations to be expressed genes (median replicate RPKM >10).

Verification: DNA mutations were classified as verified if they were confirmed by Sanger sequencing or B16F10 RNA-Seq reads. All selected variants were amplified from 50 ng of B16F10 cell DNA or C57BL/6 tail tissue using flanking primers, the products were visualized (QIAxcel system, Qiagen) and purified (QIAquick PCR Purification Kit, Qiagen) . An amplicon of the expected size was excised from the gel, purified (QIAquick Gel Extraction Kit, Qiagen) and Sanger sequenced (Eurofins MWG Operon, Ebersberg, Germany), with a forward primer used for PCR amplification.

Functional Impact: SIFT (Kumar P et al., Nat Protoc 2009;4:1073-81) and POLYPHEN-2 (Adzhubei IA et al., Nat Methods 2010;7:248-9) programs that predict the functional significance of the amino acid in protein function, based on the arrangement of protein domains and interspecies sequence conservatism, was used to assess the impact of selected mutations. Ingenuity IPA tools were used to infer the function of the gene.

Synthetic peptides and adjuvants

All peptides, including class I ovalbumin (OVA _258-265 ), class II (OVA class II _330-338 ), influenza nucleoprotein (Inf-NP _366-374 ), vesicular stomatitis virus nucleoprotein (VSV-NP _52-59 ) and related tyrosinase protein 2 (Trp2 _180-188 ) was purchased from Jerini Peptide Technologies (Berlin, Germany). Synthetic peptides were 27 amino acids long with a mutated amino acid (MUT) or wild-type amino acid (WT) at position 14. Polyinosinic:polycytidylic acid (poly(I:C), InvivoGen) was used as the subcutaneously injectable adjuvant. MHC-Pentamer specific for Inf-NP _{366-374 peptide} was purchased from ProImmune Ltd..

Immunization of mice

Female C57BL/6 mice of the same age were injected subcutaneously with 100 μg of the peptide and 50 μg of poly(I:C) prepared in PBS (200 μl total volume) in the flank between the last rib and pelvis (5 mice per group). Each group was immunized on day 0 and day 7 with peptides encoding two different peptides, one peptide in each side. Twelve days after the initial injection, mice were sacrificed and splenocytes were isolated for immunological testing.

Otherwise, age-matched female C57BL/6 mice were intravenously injected with 20 µg of in vitro transcribed RNA prepared with 20 µl of 2Lipofectamine™ RNAiMAX (Invitrogen) in PBS in a total injection volume of 200 µl (3 mice per group). Each group was immunized on days 0, 3, 7, 14 and 18. Twenty-three days after the first injection, mice were sacrificed and splenocytes were isolated for immunological testing. DNA sequences representing one (monoepitope), two (biepitope), or 16 mutations (polyepitope) were constructed using 50 amino acids (aa) with a mutation at position 25 aa (biepitope) or using 27 aa with a mutation at position 14 (mono- and polyepitope), separated by a 9-aa glycine/serine linker and cloned into the pST1-2BgUTR-A120 framework (Holtkamp et al., Blood 2006;108:4009-17). In vitro transcription from this template and purification have previously been described (Kreiter et al., Cancer Immunol Immunother 2007;56:1577-87).

Immunoassay spot analysis

Enzyme-linked immunosorbent assay (ELISPOT) (Kreiter S et al., Cancer Res 2010;70:9031-40) and bone marrow-derived syngeneic dendritic cells (BMDC) generation as stimulants have previously been described (Lutz MB et al., J Immunol Methods 1999;223:77-92). BMDCs were either activated with the peptide (2 μg/ml) or transfected with in vitro transcribed (IVT) RNA encoding the indicated mutation or control RNA (eGFP-RNA). Sequences representing two mutations, each containing 50 amino acids with a mutation at position 25 and separated by a 9 aa glycine/serine linker, were cloned into the pST1-2BgUTR-A120 framework (Holtkamp S et al., Blood 2006;108:4009-17). In vitro transcription from this template and purification have previously been described (Kreiter S et al., Cancer Immunol Immunother 2007;56:1577-87). For analysis, 5 x 10 ⁴ BMDCs modeled with peptide or RNA were co-incubated with 5 x 10 ⁵ freshly isolated splenocytes in a microtiter plate coated with anti-IFN-γ antibody (10 μg/ml, clone AN18; Mabtech). After 18 hours at 37° C., cytokine secretion was detected with an anti-IFN-γ antibody (clone R4-6A2; Mabtech). The number of spots was counted and analyzed using ImmunoSpot® S5 Versa ELISPOT Analyzer, IImmunoCapture™ Image Acquisition software and ImmunoSpot® Analysis software version 5. ). Responses were considered significant if either the test gave a p-value of <0.05 or the mean number of spots was >30 spots/5x10 ⁵ effector cells. Reactivity was assessed by the average number of spots (-: <30; +: >30; ++: >50; +++ >200 spots/well).

Analysis of intracellular cytokines

Aliquots of splenocytes obtained for the "ELISPOT" assay were subjected to cytokine production analysis by intracellular flow cytometry. To this end, 2 x 10 ⁶ splenocytes per sample were placed in a 96-well plate in culture medium (RPMI + 10% FCS) enriched with the Golgi apparatus inhibitor Brefeldin A (10 µg/ml). Cells from each animal were re-stimulated for 5 hours at 37° C. with 2 x 10 ⁵ BMDC activated with the peptide. After incubation, cells were washed with PBS, resuspended in 50 μl PBS, and extracellularly stained with the following anti-mouse antibodies for 20 minutes at 4°C: anti-CD4 FITC, anti-CD8 APC-Cy7 (BD Pharmingen). After incubation, cells were washed with PBS and then resuspended in 100 µl of Cytofix/Cytoperm solution (BD Bioscience) for 20 min. at 4°C to permeabilize the outer membrane. After permeabilization, cells were washed with Perm/Wash-Buffer (BD Bioscience), resuspended in 50 µl/sample in Perm/Wash-Buffer (BD Bioscience), and stained intracellularly with the following anti-mouse antibodies in for 30 minutes at 4°C: anti-IFN-γ PE, anti-TNF-α PE-Cy7, anti-IL2 APC (BD Pharmingen). After washing with Perm/Wash-Buffer, cells were resuspended in PBS containing 1% paraformaldehyde for flow cytometry analysis. Samples were analyzed using a BD FACSCanto™ II cytometer and FlowJo (version 7.6.3).

B16 melanoma tumor model

For tumor vaccination experiments, 7.5×10 ⁴ B16F10 melanoma cells were inoculated sc. in the flanks of C57BL/6 mice. In a prophylactic regimen, immunization with the mutation-specific peptide was performed 4 days before and 2 and 9 days after tumor inoculation. In a therapeutic experiment, the peptide vaccine was administered 3 and 10 days after tumor injection. Tumor sizes were measured every three days and mice were sacrificed when the tumors reached a diameter of 15 mm.

Otherwise, for tumor vaccination experiments, the flanks of coeval female C57BL/6 mice were inoculated sc. 1 x 10 ⁵ B16F10 melanoma cells. Peptide vaccination was performed on days 3, 10 and 17 after tumor inoculation with 100 μg of peptide and 50 μg of poly(I:C) prepared in PBS (total volume 200 μl) injected subcutaneously in the flank between the last rib and pelvis. RNA immunizations were performed with 20 μg of in vitro transcribed mutation-encoding RNA prepared with 20 μl of Lipofectamine™ RNAiMAX (Invitrogen) in PBS for a total injection volume of 200 μl. As a control, one group of animals were injected with RNAiMAX (Invitrogen) in PBS. Animals were immunized 3, 6, 10, 17 and 21 days after tumor inoculation. Tumor sizes were measured every three days with a caliper and mice were sacrificed when the tumor diameter reached 15 mm.

Identification of nonsynonymous mutations in B16F10 murine melanoma.

Our goal was to identify potentially immunogenic somatic point mutations in B16F10 murine melanoma by NGS, and to test them for in vivo immunogenicity by peptide vaccination of mice and measurement of induced T cell responses using the "ELISPOT" assay (Fig. 9A). We sequenced wild type C57BL/6 background genome and B16F10 cell exomes, each isolated and captured in triplicate. For each sample, more than 100 million single-sided reads of 50 nucleotides were obtained. Of these, 80% aligned uniquely on the mm9 mouse genome and 49% aligned on the target, demonstrating successful target enrichment and resulting in over 20-fold overlap of 70% of the target nucleotides in each of the three samples. RNA-Seq of B16F10 cells, also profiled in triplicate, generated 30 million 50-bp one-sided reads, of which 80% aligned on the mouse transcriptome.

DNA reads (exome capture) from B16F10 and C57BL/6 were analyzed to identify somatic mutations. Copy number variation analysis (Sathirapongsasuti JF et al., Bioinformatics 2011;27:2648-54) demonstrated DNA amplifications and deletions in B16F10, including a homozygous deletion of the tumor suppressor Cdkn2a (cyclin-dependent kinase 2A inhibitor, p16Ink4A). Focusing on point mutations to identify possible immunogenic mutations, we identified 3570 somatic point mutations at FDR ≤ 0.05 (Fig. 9B). The most common class of mutations were C>T / G>A transitions, usually resulting from exposure to ultraviolet radiation (Pfeifer GP et al., Mutat Res 2005;571:19-31). Of these somatic mutations, 1392 occurred in transcripts, with 126 mutations in untranslated regions. Of the 1266 mutations in coding regions, 962 caused non-synonymous changes in proteins, and 563 of these occurred in expressed genes (Fig. 9B).

Assignment of identified mutations to carrier genes and verification

It is noteworthy that many of the mutated genes (962 genes containing non-synonymous somatic point mutations) were previously associated with malignant tumor phenotypes. Mutations have been found in known tumor suppressor genes, including Pten, Trp53 (also called p53), and Tp63. In Trp53, the best known tumor suppressor (Zilfou JT et al., Cold Spring Harb Perspect Biol 2009;1:a001883), the asparagine to aspartic acid mutation at position 127 (p.N127D) is located in the DNA-binding domain and predicted by "SIFT » changes the function. Pten contains two mutations (p.A39V, p.T131P), both of which are predicted to have deleterious effects on protein function. Mutation p.T131P adjacent to mutation (p.R130M) has been shown to reduce phosphatase activity (Dey N et al., Cancer Res 2008;68:1862-71). Moreover, mutations have been found in genes associated with DNA repair signaling pathways such as Brca2 (breast cancer protein 2, early onset), Atm (telangiectatic ataxia mutant protein), Ddb1 (damage-specific DNA-binding protein 1) and Rad9b (RAD9 homologue B). Moreover, mutations occur in other tumor-associated genes, including Aim1 (tumor suppressor "Absent in melanoma 1"), Flt1 (Vegr1 oncogene, fms-related tyrosine kinase 1), Pml (tumor suppressor "promyelocytic leukemia"), Fat1 (" tumor suppressor FAT, homologue 1"), Mdm1 (TP53 nuclear binding protein), Mta3 (metastasis-associated family 1, member 3), and Alk (anaplastic lymphoma receptor tyrosine kinase). We found a p.S144F mutation in Pdgfra (platelet growth factor receptor, alpha polypeptide) associated with the cell membrane receptor tyrosine kinase MAPK/ERK signaling pathway previously identified in tumors (Verhaak RG et al., Cancer Cell 2010;17:98-110 ). A mutation occurred in p.L222V in Casp9 (casapase 9, apoptosis-associated cysteine peptidase). CASP9 proteolytically cleaves poly(ADP-ribose) polymerase (PARP), regulates apoptosis, and has been associated with several malignancies (Hajra KM et al., Apoptosis 2004;9:691-704). The mutations we found could potentially contribute to PARP signaling and apoptotic signaling. Most interestingly, no mutations were found in Braf, c-Kit, Kras or Nras. However, mutations have been identified in Rassf7 (RAS-associated protein) (p.S90R), Ksr1 (ras 1 suppressor kinase) (p.L301V), and Atm (PI3K signaling pathway) (p.K91T), which are all predicted to have a significant effect on protein function. Trrap (transformation/transcription domain associated protein) was identified earlier this year in human melanoma samples as a new potential target in melanomas (Wei X et al., Nat Genet 2011;43:442-6). In B16F10, a mutation in Trrap occurs in p.K2783R and is predicted to disrupt the FAT domain overlap of the phosphatidylinositokinase-related kinase (PIK).

Of the 962 non-synonymous mutations identified by NGS, we selected 50 mutations, including 41 with FDR < 0.05, for PCR-based validation and immunogenicity testing. Selection criteria were location in the expressed gene (RPKM > 10) and predicted immunogenicity. Remarkably, we were able to test all 50 mutations (Table 6, Fig. 9B).

In FIG. 9C shows B16F10 chromosome arrangement, gene density, gene expression, mutations, and filtered mutations (inner rings).

In vivo immunogenicity testing with mutation-representing long peptides

To provide antigens for testing the immunogenicity of these mutations, we used long peptides that have many different advantages over other immunization peptides (Melief CJ and van der Burg SH, Nat Rev Cancer 2008;8:351-60). Long peptides are able to induce antigen-specific CD8+ as well as CD4+ T cells (Zwaveling S et al., Cancer Res 2002;62:6187-93; Bijker MS et al., J Immunol 2007;179:5033-40). Moreover, long peptides require processing in order to be presented on MHC molecules. Such uptake is most efficiently carried out by dendritic cells, which are optimal for priming a potent T cell response. Prepared peptides, in contrast, do not require clipping and are exogenously loaded onto all cells expressing MHC molecules, including non-activated B and T cells, resulting in the induction of tolerance and fratricide (Toes RE et al., J Immunol 1996;156:3911- 8; Su MW et al., J Immunol 1993;151:658-67). For each of the 50 mutations tested, we designed peptides that are 27 amino acids long and have the mutant or wild-type amino acid at the center. Thus, any potential MHC class I and II epitope, 8-14 amino acids long, carrying a mutation can be processed from this precursor peptide. As an adjuvant for peptide vaccination, we used poly(I:C), which is known to stimulate cross-presentation and increase vaccine efficacy (Datta SK et al., J Immunol 2003;170:4102-10; Schulz O et al., Nature 2005 ;433:887-92). 50 mutations were tested in vivo in mice to induce T cells. Interestingly, 16 out of 50 mutation-encoding peptides were found to elicit immune responses in immunized mice. Induced T cells showed different reactivity patterns (Table 7).

Table 7. Summary of T cell reactivities determined after vaccination with the peptide encoding the mutation. Statistical analysis was performed using Student's t-test and Mann-Whitney test (non-parametric test). Responses were considered significant if either the test gave a p-value of <0.05 or the mean number of spots was >30 spots/5x10 ⁵ effector cells. Reactivity was assessed by the average number of spots -: <30; +: >30; ++: >50; +++ >200 spots/well).

Twelve immune response inducing peptides are predominantly mutant epitopes. This was confirmed in mice immunized with mutations 30 (MUT30, Kif18b) and 36 (MUT36, Plod2) (FIG. 10A). The "ELISPOT" assay revealed strong mutation-dependent immune responses with no cross-reactivity against wild-type peptide or unbound control peptide (VSV-NP). With five peptides including mutations 05 (MUT05, Eef2) and 25 (MUT25, Plod2) (FIG. 10A), immune responses were generated with comparable recognition of both the mutant peptide and the wild-type peptide. Most of the mutant peptides were unable to induce significant T cell responses, as evidenced by the example of mutations 01 (MUT01, Fzd7), 02 (MUT02, Xpot), and 07 (MUT07, Trp53). The immune responses induced by some of the mutations found were in the range of immunogenicity (500 spots/5x10 ⁵ cells) obtained in mice immunized as a positive control with the described class I MHC epitope from the mouse melanoma tumor antigen tyrosinase-related protein 2 (Trp2180-188 , Fig. 10A) (Bloom MB et al., Exp Med 1997;185:453-9; Schreurs MW et al. Cancer Res 2000;60:6995-7001). For selected peptides that induce a strong mutation-dependent T cell response, we validated immune recognition by an independent approach. Instead of long peptides, in vitro transcribed RNA (IVT RNA) encoding fragments of the mutant peptides MUT17, MUT30, and MUT44 was used to read immunological data. BMDCs transfected with the mutated RNA or irrelevant RNA acted as antigen-presenting cells (APC) in the ELISPOT assay, with immunized mouse splenocytes acting as the effector cell population. BMDCs transfected with mRNAs encoding MUT17, MUT30 and MUT44 were specifically and strongly recognized by mouse splenocytes immunized with the respective long peptides (FIG. 10B). Significantly lower reactivity against control RNA-transfected BMDCs was documented, likely due to non-specific BMDC activation of single-stranded RNA (Student's t-test; MUT17: p = 0.0024, MUT30: p = 0.0122, MUT44: p = 0.0075). These data confirm that induced mutation-specific T cells effectively recognize endogenously processed epitopes. Two mutations that induce preferential recognition of mutant epitopes are in the Actn4 and Kif18b genes. The somatic mutation in ACTN4 (actinin, alpha 4) p.F835V is located in the calcium-binding protein domain "EF-hand". Although both SIFT and POLYPHEN predict a significant impact of this mutation on protein function, the gene is not a known oncogene. However, anti-ACTN4 mutation-specific T cells have recently been associated with a positive patient outcome (Echchakir H et al., Cancer Res 2001;61:4078-83). KIF18B (a member of the kinesin family, 18B) is a kinesin with microtubule migration and ATP and nucleotide binding that is involved in the regulation of cell division (Lee YM et al., Gene 2010;466:16-25) (Fig. 10C). The DNA sequence at the position encoded by p.K739 is homogeneous in reference C57BL/6, while DNA reads from B16F10 revealed a heterozygous somatic mutation. Both nucleotides were detected in 16F10 RNA-Seq reads and were confirmed by Sanger sequencing. KIF18B has not previously been associated with a malignant tumor phenotype. The p.K739N mutation is not located in a known functional or conserved protein domain (FIG. 10C, bottom) and is thus more likely to be a guide rather than a master mutation. These examples confirm the loss of correlation between the ability to induce a mutation-recognized immune response and functional or immunological relevance.

In vivo evaluation of antitumor activity of vaccine candidates

To assess whether immune responses elicited in vivo would be translated into antitumor effects in tumor-bearing mice, we selected MUT30 (a mutation in Kif18b) and MUT44 as examples. These mutations have been shown to induce a strong immune response, preferably against the mutated peptide, and can be endogenously processed (FIGS. 10A, B). The therapeutic potential of vaccination with mutant peptides was investigated by immunizing mice with either MUT30 or MUT44 and adjuvant 3 and 10 days after inoculation with 7.5x10 ⁵ B16F10. Tumor growth was inhibited by vaccinations with both peptides compared to the control group (FIG. 11A). Because B16F10 is a very aggressive tumor, we also tested protective immune responses. Mice were immunized with the MUT30 peptide and inoculated sc. 7.5x10 ⁵ B16F10 cells 4 days later and re-stimulated with MUT30 2 and 9 days after tumor challenge. Complete tumor protection and survival of 40% of mice treated with MUT30 was observed, with all mice in the control group dying within 44 days (FIG. 11B, left). In those mice that developed tumors despite MUT30 immunization, tumor growth was slower due to a median survival of 6 days longer than the control group (FIG. 11B, right). These data suggest that vaccination against just one mutation can confer antitumor effects.

Immunization of RNA encoding mutations.

The 50 tested mutations from the B16F10 melanoma cell line were used to construct various RNA vaccines. DNA sequences representing one (monoepitope), two (biepitope), or 16 different mutations (polyepitope) were constructed using 50 amino acids (aa) with a mutation at position 25 (biepitope) or using 27 aa with a mutation at position 14 (mono - and polyepitope) and separated using a glycine/serine linker 9 aa long. These constructs were cloned into the pST1-2BgUTR-A120 framework for in vitro mRNA transcription (Holtkamp et al., Blood 2006;108:4009-17).

To test in vivo ability to induce T-cell responses against various RNA vaccines, groups of three C57BL/6 mice were immunized with RNAi formulation with RNAiMAX lipofectamine followed by intravenous injection. After 5 immunizations, mice were sacrificed and splenocytes were analyzed for mutation-specific T-cell responses by intracellular cytokine staining and "IFN-γ ELISPOT" analysis after re-stimulation with the appropriate mutation-encoding peptide or control peptide (VSV-NP).

In FIG. 12 shows one example for each vaccine design. In the top row, mice were vaccinated with an RNA with a monoepitope encoding MUT30 (mutation in Kif18b) that induces MUT30-specific CD4⁺ T cells (see sample FACS plot). In the middle row, the FACS diagram and graph demonstrate the induction of MUT08-specific (mutation in Ddx23) CD4⁺ T cells after immunization with a biepitope encoding MUT33 and MUT08. Bottom line, mice were immunized with a polyepitope encoding 16 different mutations including MUT08, MUT33 and MUT27 (see Table 8). FACS chart and plot illustrate that MUT27 reactive T cells have CD8 phenotype.

Table 8. Overview of mutations and gene names encoded by mono-, bi-, and polyepitope RNA vaccines

The same polyepitope was used to obtain the data presented in FIG. 13. The diagram shows ELISPOT data after re-stimulation of splenocytes with control (VSV-NP), MUT08, MUT27 and MUT33 peptides, proving that the polyepitope vaccine can induce specific T cell responses against several different mutations.

Taken together, the data demonstrate the ability to induce mutation-specific T cells with mono-, bi-, and polyepitopes. Moreover, the data demonstrate the induction of CD4 ⁺ and CD8 ⁺ T cells and the induction of some different specificities from a single construct.

Immunization with model epitopes

To further describe the design of the polyepitope RNA vaccine, DNA sequences were constructed that included five different known model epitopes, including one MHC class II epitope (class I ovalbumin (SIINFEKL), class II (OVA class II), influenza nucleoprotein (Inf- NP), vesicular stomatitis virus nucleoprotein (VSV-NP), and tyrosinase-related protein 2 (Trp2)). The epitopes were separated by the same 9 aa glycine/serine linker used for the mutant polyepitope. These constructs were cloned into the pST1-2BgUTR-A120 framework for in vitro mRNA transcription.

In vitro transcribed RNAs were used to vaccinate five C57BL/6 mice with intranodal immunization (four immunizations of 20 μg RNA in the inguinal lymph nodes). Five days after immunization, blood and splenocyte samples were collected from mice for analysis. Fig. 14A shows an "IFN-γ ELISPOT" analysis of splenocytes restimulated with the indicated peptides. It is clearly seen that all three MHC class I epitopes (SIINFEKL, Trp2 and VSV-NP) induce very large numbers of antigen-specific CD8 ⁺ T cells. Also, an OVA class II epitope (MHC class II epitope) induces a strong CD4 ⁺ T cell response. The fourth MHC class I epitope was analyzed by staining Inf-NP-specific CD8 ⁺ T cells with a fluorescently labeled pentameric MHC-peptide complex (Pentamer) (FIG. 14B).

These data prove that a polyepitope design using a glycine/serine linker to separate different MHC class I and class II immunogenic epitopes is able to induce specific T cells against each encoded epitope, regardless of immunodominance.

Antitumor response after coding mutation therapy with a polyepitope RNA vaccine

The same polyepitope whose immunogenicity was analyzed in FIG. 13 was used to investigate the antitumor activity of mutation-encoding RNAs against B16F10 tumor cells. Specifically, groups of C57BL/6 mice (n=10) were subcutaneously inoculated with 1 x 10 ⁵ B16F10 melanoma cells in the flank. On days 3, 6, 10, 17 and 21, mice were immunized with polyepitope RNA using a liposomal transfection reagent. The control group was injected with liposomes only.

Fig. 21 shows group survival curves, revealing significantly improved median survival at 27 days, with 1 in 10 mice surviving without tumor, compared to 18.5 days of median survival in the control group.

Antitumor response after therapy with a combination of mutant and normal peptide

The antitumor activity of the tested mutations was evaluated in an in vivo therapeutic tumor experiment using MUT30 as a peptide vaccine. Specifically, groups of C57BL/6 mice (n=8) were subcutaneously inoculated with 1 x 10 ⁵ B16F10 melanoma cells in the flank. On days 3, 10 and 17, mice were immunized with MUT30 peptides, tyrosinase-related protein 2 (Trp2 _180-188 ) using polyI:C as an adjuvant, or a combination of both peptides. Trp2 is a known CD8 ⁺ epitope expressed by B16F10 melanoma cells.

Fig. 15A shows the average growth of tumors in groups. It can be clearly seen that up to day 28, tumor growth was almost completely inhibited in the group that was immunized with the combination of the known CD8 ⁺ T cell epitope and the CD4 ⁺ T cell inducing MUT30. The known Trp2 epitope alone is not sufficient to provide a good antitumor effect under these conditions, but at the start of the experiment, both single therapy groups (MUT30 and Trp2) still provide tumor growth inhibition compared to the untreated group up to day 25. These data are supported by the survival curves shown in Fig. 15V. It is clearly seen that the median survival is increased in mice injected with single peptides, with 1/8 of the mice surviving in the Trp2 vaccinated group. In addition, the group treated with both peptides showed an even better median survival with 2/8 mice surviving.

Together, both epitopes act synergistically to provide a strong antitumor effect.

Example 9 Medium for Reliable Detection of Somatic Mutations and Application to B16-F10 Melanoma Cells

NGS is objective because it allows high-throughput detection of variations in the whole genome or target regions such as protein-coding exons.

However, despite being revolutionary, the NGS platform is still prone to errors leading to misprediction of variations. Moreover, the quality of the results depends on the experimental design parameters and analysis methodologies. Although predictions of variation typically include scores designed to distinguish between true variation and error, the practicality of these scores is not fully understood, nor is their interpretation in relation to the optimization of experiments. This is especially true when comparing the state of tissues, for example when comparing tumor and normal tissue, for somatic mutations. As a consequence, researchers are forced to rely on personal experience to determine experimental parameters and arbitrary filtering thresholds for selecting mutations.

Our study is aimed at a) creating an environment for comparing parameters and methods for identifying somatic mutations and b) assigning a confidence value to the identified mutations. We sequenced samples three times from C57BL/6 mice and the B16-F10 melanoma cell line. From this data, we derived the false positive rate for somatic mutations, a measure that we then used to evaluate existing mutation detection software and to evaluate laboratory protocols.

Various experimental and algorithmic factors contribute to the false positive rate for variations detected by NGS [Nothnagel, M. et al., Hum. Genet. 2011 Feb 23 [Epub ahead of print]]. Sources of errors include PCR artifacts, primer errors [Hansen, K.D., et al., Nucleic. Acids. Res. 38, e131 (2010); Taub, M.A. et al., Genome Med. 2, 87 (2010)] and targeted enrichment [Bainbridge, M.N. et al., Genome Biol. 11, R62 (2010)], sequence effects [Nakamura, K. et al., Acids Res.(2011) first published online May 16, 2011 doi:10.1093/nar/gkr344], base predictions causing sequence errors [Kircher, M. et al., Genome Biol. 10, R83 (2009). Epub 2009 Aug 14] and read alignment [Lassmann, T. et al., Bioinformatics 27, 130–131 (2011)], causing variability in coverage and sequencing errors that affect further analysis, such as prediction of variants around insert-deletions [Li, H., Bioinformatics 27, 1157-1158 (2011)].

To indicate the contribution of various error sources to the prediction of somatic mutations, a general statistical model has not been described; only individual aspects are covered without removing all systematic errors. Recent computational methods for measuring the expected number of false positive mutation predictions include using the variation set transition/transversion ratio [Zhang, Z., Gerstein, M., Nucleic Acids Res 31, 5338-5348 (2003); DePristo, M.A. et al., Nature Genetics 43, 491–498 (2011)], machine learning [DePristo, M.A. et al., Nature Genetics 43, 491–498 (2011)] and inheritance errors when working with familial genomes [Ewen, K.R. et al., Am. J. Hum. Genet. 67, 727-736 (2000)] or pooled samples [Druley, T.E. et al., Nature Methods 6, 263-265 (2009); Bansal, V., Bioinformatics 26, 318-324 (2010)]. For optimization purposes, Druley et al. [Druley, T.E. et al., Nature Methods 6, 263 - 265 (2009)] relied on short fragments of the plasmid sequence, which, however, may not be representative of the sample. For a set of single nucleotide variations (SNVs) and selected experiments, comparison with SNVs identified by other methods is feasible [Van Tassell, C.P. et al., Nature Methods 5, 247 - 252 (2008)] but difficult to assess in terms of new somatic mutations.

Using the exome sequencing project as an example, we propose to calculate the false positive rate (FDR) from NGS data alone. The method is not only applicable to the selection and prioritization of diagnostic and therapeutic targets, but also supports the development of algorithms and methods, allowing us to determine valid recommendations for similar experiments.

To detect mutations, DNA from the tail tissue of three C57BL/6 (black6) mice (from the same litter) and DNA from B16-F10 (B16) melanoma cells, in triplicate, were individually enriched for protein-coding exons (Agilent Sure Select Whole Mouse Exome"), resulting in a total of 6 samples. RNA was extracted from B16 cells three times. Single-ended 50 nt (1 x 50 nt) and double-ended 100 nt (2 x 100 nt) reads were prepared on an Illumina HiSeq 2000. Each sample was loaded into an individual lane, resulting in an average of 104 million reads per lane. DNA-reads were aligned to the reference mouse genome using "bwa" [Li, H. Durbin, R., Bioinformatics 25, 1754-1760 (2009)], and RNA-reads were aligned using "bowtie" [Langmead, B. et al., Genome Biol. 10, R25 (2009)]. The average coverage for 97% of the target areas in the 1x50 nt libraries was 38, and the 2x100 nt experiments gave an average coverage for 98% of the target areas of 165.

Somatic variations were independently identified using software packages "SAMtools" [Li, H. et al., Bioinformatics 25, 2078-2079 (2009)], "GATK" [DePristo, M.A. et al., Nature Genetics 43, 491–498 (2011)] and "SomaticSNiPer" [Ding, L. et al., Hum. Mol. Genet (2010) first published online September 15, 2010] (Fig. 16) comparing single nucleotide variations found in B16 samples with corresponding loci in black6 samples (B16 cells were originally derived from black6 mice). Potential mutations were filtered according to the recommendations of the authors of the respective software ("SAMtools" and "GATK") or by selecting the appropriate lower threshold for the somatic score "SomaticSNiPer", respectively.

To obtain the false positive rate (FDR) for mutation detection, we first crossed mutation sites and obtained 1355 high quality somatic mutations as a consensus among all three programs (Fig. 17). However, the observed differences in the results of the applied software tools are significant. In order to avoid erroneous conclusions, we have developed a way to assign FDR to each mutation using replicas. Technical replicates of a sample should produce identical results, and any detectable mutation in a given self-versus-self comparison is a false positive. Thus, in order to determine the false positive rate of detecting somatic mutations in a tumor sample relative to a normal sample (“tumor comparison”), we can use the technical replicate of a normal sample as a benchmark for estimating the number of false positives.

In FIG. 18A shows examples of variation found in black6/B16 data, including somatic mutation (left), non-somatic variation relative to reference (middle), and possible false positives (right). Each somatic mutation can be associated with a Q quality score. The number of false positives compared with a tumor indicates several false positives when compared self-versus-self. Thus, for a given mutation with a Q quality score detected when compared to the tumor, we estimate the false positive rate by calculating the ratio of mutations found in the self-versus-self comparison with a Q score or better to the total number of mutations found in the comparison with the tumor. , with a Q score or better.

Difficulties arise in determining Q, since most mutation detection environments calculate several quality scores. Here we use the random forest classifier [Breiman, L., Statist. sci. 16, 199-231 (2001)] to combine multiple scores into a single Q quality score. We refer to the methods section for details on the details of the quality score and FDR calculations.

A potential estimation bias in method comparisons is due to different coverage; we thus normalize the false positive rate to cover:

We calculate total coverage by counting all bases of the reference genome that are covered by both the tumor and normal samples, or both self-versus-self samples, respectively.

By estimating the number of false positives and positives at each FDR false positive rate (see methods), we generated true/false detection ratio (ROC) curves and calculated the AUC (area under the curve) for each mutation detection method, thus allowed comparison of mutation detection strategies (FIG. 18B).

Moreover, the selection of reference data may affect the FDR calculation. With the available black6/B16 data it is possible to create 18 triplets (black6 vs. black6 and black6 vs. b16 combinations). When comparing the resulting FDR distributions for sets of somatic mutations, the results are consistent (Fig. 18B).

Using this definition of the false positive rate, we have obtained a standard environment for assessing the influence of a variety of experimental and algorithmic parameters on the resulting set of somatic mutations. We then applied this environment to study the effect of software tools, coverage, double-ended sequencing, and the number of technical cues on the identification of somatic mutations.

First, the choice of software tool has a clear impact on the identified somatic mutations (FIG. 19A). In the data tested, "SAMtools" gave the strongest enrichment in true positives in the FDR-ranked set of somatic mutations. However, it should be noted that all tools offer many parameters and quality scores for individual mutations. Here, we have used the default settings specified by the developers of the algorithm; we expect that the parameters can be optimized and emphasize that the FDR environment defined here is designed to perform and evaluate such optimization.

For the described B16 sequencing experiment, we sequenced each sample in an individual flow cell and achieved a 38-fold average base coverage of the target region for the individual samples. However, this coverage is not needed to obtain an equally good set of somatic mutations, which can reduce costs. In addition, the effect of coverage depth on genome-wide detection of SNV has recently been discussed [Ajay, S.S. et al., Genome Res. 21, 1498-1505 (2011)]. To study the effect of coverage on exon capture data, we reduced the number of sequence-aligned reads for each library by 1/50 nt to obtain an approximate coverage of 5, 10, and 20 times, respectively, and then reapplied the mutation prediction algorithms. As expected, higher coverage results in a better (ie, fewer false positives) set of somatic mutations, although the improvement from 20-fold coverage to maximum coverage is not significant (FIG. 19B).

It is easy to model and evaluate various experimental parameters with the available data and environment. When comparing duplicates with triplicates, triplicates were found to be of no benefit over duplicates (FIG. 19C), although duplicates showed a clear improvement over a study with no replicas at all. In terms of the ratio of somatic mutations in these sets, we see an enrichment at FDR 5% from 24.2% for the no-replica run to 71.2% for duplicates and 85.8% for triplicates. Despite enrichment, the use of triplicate overlap removed more low FDR mutations than high FDR mutations, as indicated by a lower ROC AUC and a curve shift to the left (FIG. 19C): specificity is slightly improved by lower sensitivity.

An additional 2 x 100 nt sequenced library was used to simulate 1 x 100, two 2 x 50, and two 1 x 50 nt libraries, respectively, by in silicio removal of the second read and/or the 3' and 5' ends of the reads, giving a total of 5 simulated libraries. These libraries were compared using calculated FDR predicted mutations (FIG. 19D). Despite a much higher mean coverage (greater than 77 vs 38), somatic mutations detected with 2x50 5' and 1x100 nt libraries have lower ROC AUCs and thus worse FDR distribution than the 1x50 nt library. This is due to the accumulation of high FDR mutations in areas of low coverage since the sets of low FDR mutations are very similar. The implication is that the optimal sequencing length should either be small so that sequenced bases concentrate around the capture probe sequences (which nevertheless potentially leads to loss of information about the somatic status of mutations in uncovered regions), or should be close to the fragment length. (2x100 nt = 200 nt total length for ~250 nt fragments in our case), effectively filling gaps in the coating. This conclusion is also supported by the ROC AUC of the 2x50 nt 3' library (modeled with only the 3' ends of the 2x100 nt library), which is higher than the ROC AUC of the 2x50 nt 5' library (modeled with only the 5' ends of the 2x100 nt library), despite to lower base quality at the 3' ends of the reads.

These observations allow us to determine the best practice procedures for the detection of somatic mutations. Among all the parameters evaluated, 20x coverage in both samples, and the use of a technical duplicate, achieve near-optimal results in these relatively homogeneous samples, and this is cost-adjusted. A 1x50 nt library, with approximately 100 million reads, appears to be the most pragmatic choice for achieving this coverage. This is true for all possible pairs of datasets. We applied these parameter settings retrospectively, without using additional filtering to predict crude variants, and calculated the FDR for 50 selected mutations from the intersection of all three methods, as shown in FIG. 17. All mutations were confirmed by a combination of Sanger resequencing and B16-RNA-Seq sequence reads. 44 of these mutations could be detected using a 5% FDR threshold (FIG. 20). As a negative control, we resequenced the loci of 44 predicted mutations with high FDR values (>50%) and checked the corresponding sequences in the RNA-Seq data. We found that 37 of these mutations were not confirmed, in addition to the fact that the remaining seven potential mutation loci were not covered by RNA-Seq reads and were not generated in the sequencing reaction.

Although we have shown the application of the environment in four specific questions, it is by no means limited to these parameters, and can be applied to study the influence of all experimental or algorithmic parameters, for example, the influence of software for alignment, the choice of scoring system for mutations, or the choice of exome selection equipment. .

We performed all experiments on a set of experiments with B16 melanoma cells; however, the method is not limited to these data. The only requirement is that a self-versus-self reference dataset be available, which means that at least one technical replicate of a non-tumor sample must be obtained for each new protocol. Although our experiments indicate that the method is reliable with respect to the choice of technical repetition within certain limits, which means that repetition is not necessarily necessary in every single experiment. However, the method requires that the various quality measures be comparable between the reference dataset and the remaining datasets.

As part of this contribution, we initiated the use of a statistical environment for the detection of somatic mutations, taking into account the frequency of false positive results. This environment is not only applicable for the selection of diagnostic or therapeutic targets, but also allows a general comparison of the experimental and calculated steps of the protocol on the generated quasi-valid data. Here, we have applied this idea in order to implement protocol decisions regarding software tools, coverage, replicas, as well as paired-end sequencing.

Ways

Library capture and sequencing

Next generation sequencing, DNA sequencing: Exome capture for DNA resequencing was performed using an Agilent Sure-Select solution-based capture assay [Gnirke, A., et al., Nat. Biotechnol. 27, 182-189 (2009)], in this case configured to capture all known mouse exons.

3 μg of purified genomic DNA was fragmented to 150-200 bp. using the ultrasonic device "Covaris S2". The ends of the gDNA fragments were completed with T4 DNA polymerase, a Klenow fragment, and phosphorylated at 5' with T4 polynucleotide kinase. Blunt-ended gDNA fragments were 3'-adenylated using a Klenow fragment (3' to 5', exo minus). Using T4 DNA ligase, Illumina 3' single T-overlapping paired end adapters were ligated to gDNA fragments at a molar ratio of adapter to genomic DNA insert of 10:1. The gDNA fragments ligated with adapters were enriched, sequences specific for pre-capture and flow cell were added using Illumina PE PCR 1.0 and 2.0 primers and Herculase II polymerase (Agilent) during 4 PCR cycles.

500 ng of adapter-ligated enriched PCR gDNA fragments were hybridized with Agilent's SureSelect Biotinylated Whole Mouse Exome Biotinylated Bait RNA Library for 24 hours at 65°C. Hybridized gDNA/bait RNA complexes were removed using streptavidin-coated magnetic microspheres. The gDNA/bait RNA complexes were washed out and the bait RNAs were cleaved during elution in SureSelect elution buffer, leaving the captured PCR-enriched gDNA fragments with ligated adapters. The gDNA fragments were amplified by PCR after capture with Herculase II DNA polymerase (Agilent) and SureSelect GA primers for 10 cycles.

Purifications were performed in 1.8x the volume of AMPure XP magnetic microspheres (Agencourt). For quality controls, we used the Qubit HS test from Invitrogen, and the fragment size was determined using the HS DNA test on a Bioanalyzer 2100 from Agilent.

Exome-enriched gDNA libraries were clustered on cBot using the Truseq SR cluster kit v2.5 using 7 pM and sequenced on Illumina HiSeq200 using the Truseq SBS kit.

Exome data analysis

Sequence reads were aligned with "bwa" (version 0.5.8c) [Li, H. Durbin, R., Bioinformatics 25, 1754-1760 (2009)] using the default settings on the mouse genome mm9 reference assembly [Mouse Genome Sequencing Consortium , Nature 420, 520-562 (2002)]. Ambiguous reads - reads that map to many places in the genome according to the "bwa" output - have been removed. The remaining alignments were sorted, indexed, and converted to binary and compressed format (BAM), and the read quality scores were converted from the standard Illumina "phred+64" quality scores to the standard Sanger quality scores using shell scripts.

Mutations were identified for each of the sequenced lanes using three computer programs: "SAMtools pileup" (version 0.1.8) [Li, H. et al., Bioinformatics 25, 2078-2079 (2009)], "GATK" (version 1.0. 4418) [DePristo, M.A. et al., Nature Genetics 43, 491–498 (2011)], and "SomaticSniper" [Ding, L. et al., Hum. Mol. Genet (2010) first published online September 15, 2010]. For "SAMtools" we used the settings and filter criteria recommended by the authors (http://sourceforge.net/apps/mediawiki/SAMtools/index.php?title=SAM_FAQ; accessed September 2011), including filtering the first round, the maximum coverage is 200. For In the second round of SAMtools filtering, the minimum insertion-deletion quality score was 50, and the minimum point mutation quality was 30. To assign mutations using GATK, we followed the best practices developed by the authors and presented in the GATK User Guide (http: //www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit; accessed October 2010). For each sample, a local realignment around insertion-deletion sites was performed followed by recalibration of base quality. The "UnifiedGenotyper" module was applied to the resulting alignment data files. Known dbSNP polymorphisms [Sherry, S.T. et al., Nucleic Acids Res. 29, 308-311 (2009)] (version 128 for mm9) complemented the individual stages. The variant score recalibration step was omitted and replaced with hard filtering. SomaticSniper used default parameters to assign mutations, and then only predicted mutations with a "somatic score" of 30 or greater were considered. In addition, for each potentially mutated locus, we required non-null coverage in normal tissue and removed all mutations located in repeat sequences as determined by the "RepeatMasker" of the "UCSC Genome Browser" for the assembly of the mouse mm9 genome [Fujita, P.A. et al., Nucleic Acids Res. 39, 876-882 (2011)].

RNA-Seq

Barcoded mRNA-seqcDNA libraries were generated from 5 µg of total RNA using a modified version of the Illumina mRNA-seq protocol. mRNA was isolated using SeramagOligo(dT) magnetic microspheres (Thermo Scientific). The isolated mRNA was fragmented using divalent cations and heating, resulting in fragments in the range of 160-200 nucleotides. Fragmented mRNA was converted into cDNA using random primers and SuperScriptII (Invitrogen), followed by second strand synthesis using polymerase I and RNase H. The cDNA ends were completed using T4 DNA polymerase, Klenow fragment and phosphorylated at the 5' ends using T4 polynucleotide kinase. Blunt-ended cDNA fragments were 3'-adenylated using a Klenow fragment (3' to 5' exo minus). Using T4 DNA ligase, 3'-terminal single T-overlapping Illumina multiplex-specific adapters were ligated to cDNA fragments. cDNA libraries were purified and sized to 300 bp. using E-Gel 2% SizeSelect gel (Invitrogen). Enrichment, addition of six base Illumina indexing sequences and flow cell sequences was performed by PCR using Phusion DNA polymerase (Finnzymes). Purifications were performed in 1.8 x the volume of AMPure XP magnetic microspheres.

Barcoded RNA-seq libraries were clustered on cBot using the Truseq SR cluster kit v2.5 using 7 pM and sequenced on Illumina HiSeq200 using the Truseq SBS kit.

Raw HiSeq output was processed according to standard Illumina protocol, including low quality read removal and decompression. The sequence reads were then aligned to the reference genomic sequence [Mouse Genome Sequencing Consortium, Nature 420, 520-562 (2002)] with a bowtie [Langmead, B. et al., Genome Biol. 10, R25 (2009)]. Alignment coordinates were compared with exon coordinates of RefSeq transcripts [Pruitt, K.D. et al., Nucleic Acids Res. 33, 501-504 (2005)] and the number of overlapping alignments was recorded for each transcript. Sequence reads that did not align with the genomic sequence were aligned against a database of all possible exon-exon bridging sequences of RefSeq transcripts [Pruitt, K.D. et al., Nucleic Acids Res. 33, 501-504 (2005)]. Alignment coordinates were compared with RefSeq exon coordinates and junction coordinates, reads were counted, and normalized to RPKM (number of reads that map per kilobase of transcript nucleotides per million reads mapped) [Mortazavi, A. et al., Nat. Methods 5, 621-628 (2008)]) for each transcript.

SNV check

We selected SNV for Sanger and RNA resequencing. SNVs were identified that were predicted by all three programs that were non-synonymous and that were found in transcripts having a minimum of 10 RPKM. Among them, we selected 50 with the highest SNP quality scores provided by the programs. As a negative control, 44 SNVs were selected that had an FDR of 50% or greater, that were present in only one cell line sample, and that were predicted by only one mutation assignment program. Using DNA, the selected variants were verified by PCR amplification of the regions using 50 ng of DNA, followed by Sanger sequencing (Eurofins MWG Operon, Ebersberg, Germany). Reactions were successful for 50 and 32 loci of positive and negative controls, respectively. Validation was also carried out by examining RNA-Seq tumor reads.

FDR Calculation and Machine Learning

"Random Forest" Quality Score Calculations: Commonly Used Mutation Designation Algorithms (DePristo, M.A. et al., Nature Genetics 43, 491–498 (2011), Li, H. et al., Bioinformatics 25, 2078-2079 (2009), Ding, L. et al., Hum. Mol. Genet (2010) first published online September 15, 2010) provide multiple scores that all potentially affect the quality of mutation prediction. These include, but are not limited to, the quality of the base of interest assigned by the instrument, the quality of the alignment at that position, the number of reads spanning that position, or the difference score between two genomes compared at that position. To calculate the false positive rate, we need ordering of mutations, however this is not directly feasible for all mutations because we may have conflicting information from different quality scores.

We use the following strategy to achieve full ordering. In the first step, we apply a very strict definition of superiority, assuming that a mutation is of better quality than another if and only if it is superior in all categories. So the set of qualitative features S=(s ₁ ,…,s _n ) is preferable to T = (t ₁ , ..., t _n ), which is denoted as S>T, if s _i > t _i for all i=1, …,n. We have defined an intermediate FDR (IFDR) as follows

However, we consider IFDR only as an intermediate step because in many closely related cases comparison is not possible and we thus do not benefit from the vast amount of data available. Thus, we have taken advantage of the good generalizing property of the random forest regression [Breiman, L., Statist. sci. 16, 199-231 (2001)] and trained a "random forest" implemented in R (R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2010, Liaw, A ., Wiener, M., R News 2, 18-22 (2002)).

For m input mutations with n quality properties each, a range of values for each property was determined and up to p values were sampled at even intervals from that range; if the quality property value set is less than p, then that set was used instead of the selected set. All possible combinations of selected or sorted quality values are then created, resulting in a maximum of p ⁿ data points in an n-dimensional quality space. A random sample including 1% of these points and the corresponding IFDR values were used as predictor and response, respectively, for random forest training.

The resulting regression score is our generalized quality score Q; it can be thought of as being locally weighted by a combination of individual quality scores. It allows you to make a direct comparison on a single value of any two mutations and calculate the current false positive rate:

To train the random forest model used to generate the results in this study, we calculated the IFDR of a sample from the somatic mutations of all samples before selecting a random 1% subset. This allows the total available quality space to be mapped to FDR values. We used the quality properties "SNP quality", "coverage depth", "consensus quality", and "RMS mapping quality" ("SAMtools", P = 20); 'SNP quality', 'coverage depth', 'variant confidence/unfiltered depth' and 'RMS mapping quality' ('GATK', P = 20); or "SNP quality", "coverage depth", "consensus quality", "RMS mapping quality", and "somatic score" ("SomaticSNiPer", P = 12), respectively. Different values of p provide a set size of comparable magnitude.

Total Coverage Calculation: The number of possible mutation predictions can introduce a major bias in determining the false positive rate. Only if we have the same number of possible mutation sites occurring in our tumor comparison and our self-versus-self comparison is the number of predicted mutations comparable and can serve as the basis for calculating the false positive rate. To correct for this potential bias, we applied the total coverage ratio. As a total coverage, we determined the number of coated bases in at least one of the two samples that are used to assign mutations. We calculated total coverage individually for tumor comparisons as well as for self-versus-self comparisons.

ROC score

The curves of the ratios of correct and false detection of signals (Receiver operating characteristic, ROC) and the corresponding area under the curve (area under curve, AUC) are suitable for organizing classifiers and visualizing their effectiveness [Fawcett, T., Pattern Recogn. Lett. 27, 861–874 (2006)]. We have extended this concept to evaluate the effectiveness of experimental and computational procedures. However, ROC plotting requires knowledge of all true positive and false positive (TP and FP) examples in the data set, information that is typically not represented and is difficult to obtain for high-throughput data (such as NGS data). Thus, we use the calculated FDRs to estimate the respective TP and FP levels and to plot the ROC and calculate the AUC. The central idea is that the FDR of a single mutation in a data set gives a fraction of how much that mutation contributes to the sum of TP/FP mutations, respectively. Also for a list of random TP and FP assignments, the resulting ROC AUC values will be 0.5 in our method, indicating a completely random prediction. We started with two conditions:

[1]

[one]

and

[2]

[2]

with FPR and TPR representing the necessary false positive and true positive ratios, respectively, for a given mutation, defining the appropriate point in ROC space. [1] and [2] can be rearranged into

[3]

[3]

and

[4]

[four]

To obtain the estimated ROC curve, the mutations in the dataset were sorted by FDR and for each mutation a point was plotted in the total values within that mutation divided by the sum of all TPR and TPR values, respectively. AUC is calculated by summing the areas of all consecutive trapezoids between the curve and the x-axis.

--->

SEQUENCE LIST

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<---

Claims (47)

1. A method of obtaining an individualized vaccine for use in the treatment or prevention of cancer, comprising an effective amount of a recombinant polyepitope polypeptide containing mutation-based neoepitopes that result from cancer-specific somatic mutations in a cancer sample of a patient having cancer, or a nucleic acid encoding said polyepitope a polypeptide wherein mutation-based neoepitopes are linked together via peptide bonds or linkers, comprising the steps of: (A) identifying cancer-specific somatic mutations in a cancer sample of a patient having cancer to obtain a signature of the patient's cancer mutations, comprising the steps (i) obtaining nucleic acid sequence information by sequencing the genomic DNA and/or RNA of a cancer sample of a patient having cancer, (ii) obtaining information about the reference nucleic acid sequence by sequencing the genomic DNA and/or RNA of normal non-cancerous cells, and (iii) comparing the nucleic acid sequence information from the cancer sample obtained in step ((A)(i)) with the reference nucleic acid sequence information obtained in step ((A)(ii)); (iv) identifying differences in sequence according to step ((A)(iii)) and identifying cancer-specific somatic mutations in a cancer sample from a patient having cancer; and (B) obtaining a vaccine, the characteristic feature of which is the signature of cancer mutations obtained in stage (A), including the stages (i) obtaining a recombinant polyepitope polypeptide or a nucleic acid encoding said polyepitope polypeptide, wherein the recombinant polyepitope polypeptide comprises mutation-based neoepitopes containing the mutations identified in step ((A)(iv)), wherein the mutation-based neoepitopes are fused together by peptide bonds or linkers; (ii) obtaining a vaccine containing an effective amount of the recombinant polyepitope polypeptide or nucleic acid obtained in step ((B)(i)). 2. The method of claim 1, wherein step (A) of identifying cancer-specific somatic mutations comprises identifying a signature of cancer mutations in the exome of one or more cancer cells. 3. The method of claim 1 or 2, wherein step (A) of identifying cancer-specific somatic mutations comprises sequencing a single cell genome from one or more cancer cells. 4. The method of claim 3 wherein the cancer cells are circulating cancer cells. 5. The method according to any one of paragraphs. 1-4, wherein step (A) of identifying cancer-specific somatic mutations involves the use of next generation sequencing (NGS). 6. The method according to any one of paragraphs. 1-5 wherein normal non-cancerous cells are obtained from said patient having cancer. 7. The method according to any one of paragraphs. 1-6, where the reference nucleic acid sequence information is derived from germline cells. 8. The method according to any one of paragraphs. 1-6, where reference nucleic acid sequence information is derived from germline genomic DNA derived from peripheral blood mononuclear cells (PBMCs). 9. The method of claim 7 or 8, wherein said cancer pattern originates from a primary tumor, and wherein step (A) of identifying cancer-specific somatic mutations further comprises the steps of: ((iii)(a)) providing a phylogenetic tree of cancer-specific somatic mutations, where information about the sequence of the reference nucleic acid obtained in step (ii) is used to create the basis of the tree, ((iii)(b)) reproducing ancestral sequences, where the ancestral sequences are the sequences of nodes near the root of the phylogenetic tree containing the primary basal mutations, the primary basal mutations being the earliest mutations predicted to exist in the primary cancer, and ((iii)(c)) selecting primary basal mutations from the inherited sequences identified in step ((iii)(b)). 10. The method according to any one of paragraphs. 1-9, where step (A) of identifying cancer-specific somatic mutations is repeated at least twice. 11. The method according to any one of paragraphs. 1-10, containing the additional step of determining the suitability of identified mutations in epitopes for cancer vaccination, where subsequent steps include one or more of the following: (i) assessing whether the identified mutations are located in known or predicted MHC-presented epitopes, (ii) testing in vitro and/or in silico whether the identified mutations are on the epitopes presented on the MHC, and (iii) in vitro testing whether the mutated epitopes in question, by themselves or when expressed by antigen presenting cells, would be capable of stimulating the patient's T cells having the desired specificity. 12. The method of claim 11, wherein in step (ii) testing in vitro and/or in silico whether the identified mutations are on the epitopes presented on the MHC involves testing whether the mutations are part of the peptide sequences that are processed into and/or presented as MHC presented epitopes. 13. The method of claim 11 or 12, wherein in step (iii) the mutated epitopes are in the context of their natural sequences and are flanked by amino acid sequences that also flank said epitopes in the natural protein. 14. The method according to any one of paragraphs. 1-13, where the polyepitope polypeptide preferably contains up to 30 neoepitopes based on mutations. 15. The method according to any one of paragraphs. 1-14, wherein the polyepitope polypeptide further comprises epitopes not containing cancer-specific somatic mutations that are expressed by cancer cells. 16. The method according to any one of paragraphs. 1-15, where the epitopes in the formation of the vaccine sequence are presented in the context of their natural sequence. 17. The method of claim 16 wherein the vaccine sequence is 30 amino acids long. 18. The method according to any one of paragraphs. 1-17, where neoepitopes, epitopes and/or vaccine sequences are arranged head to tail. 19. The method according to any one of paragraphs. 1-13, wherein said nucleic acid encoding said polyepitopic polypeptide is RNA and said vaccine is an RNA vaccine. 20. The method of claim 19, wherein the polyepitope polypeptide encoded by the nucleic acid preferably contains up to 30 mutation-based neoepitopes. 21. The method of claim 20, wherein the nucleic acid-encoded polyepitopic polypeptide also contains epitopes that do not contain tumor-specific somatic mutations that are expressed by cancer cells. 22. The method according to any one of paragraphs. 20 and 21, where the epitopes are in the context of their natural sequence so as to form the sequence encoded by the vaccine RNA sequence. 23. The method of claim 22, wherein the length of the polyepitopic polypeptide sequence encoded by the RNA vaccine sequence is 30 amino acids. 24. The method according to any one of paragraphs. 1-13 or 19-23, where neoepitopes, epitopes in a polyepitope polypeptide and/or a polyepitope polypeptide sequence encoded by an RNA vaccine sequence, are linked head to tail. 25. The method according to any one of paragraphs. 1-18, where the vaccine is a prophylactic and/or therapeutic vaccine. 26. The method of claim 1, wherein the MHC-presented epitopes are class II MHC-presented epitopes that are capable of eliciting a CD4+ helper T cell response against cells expressing the antigens from which the MHC-presented epitopes originate, and optionally MHC class I presented epitopes that are capable of eliciting a CD8+ T cell response against cells expressing antigens from which the MHC presented epitopes are derived. 27. Individualized vaccine for use in the treatment or prevention of cancer, which is obtained by the method according to any one of paragraphs. 1-26. 28. A personalized vaccine for use in the treatment or prevention of cancer, comprising an effective amount of a recombinant polyepitope polypeptide comprising mutation-based neoepitopes, said neoepitopes being the result of cancer-specific somatic mutations in a cancer sample of a patient having cancer, the mutation-based neoepitopes being cross-linked together via peptide bonds or linkers, or comprising a nucleic acid encoding said polyepitopic polypeptide. 29. The vaccine of claim 28, wherein said polyepitopic polypeptide further comprises epitopes that do not contain cancer-specific somatic mutations that are expressed by cancer cells. 30. A method for treating a patient with cancer, comprising the steps of: (a) carrying out the method according to any one of paragraphs. 1-26 to obtain an individualized cancer vaccine according to claim 27, or to obtain an individualized cancer vaccine according to any one of paragraphs. 28, 29, and (b) administering said vaccine to a patient.

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