JP2023551204A - Optimized peptide vaccine compositions and methods - Google Patents

Abstract

The present disclosure provides methods, systems, and compositions for nucleic acid and peptide sequences. The present disclosure provides nucleic acid sequences encoding at least two amino acid sequences selected from the group consisting of SEQ ID NO: 1-6, SEQ ID NO: 8-10, SEQ ID NO: 12-28, and SEQ ID NO: 30-41. The present disclosure also provides immunogenic peptide compositions comprising at least one peptide selected from the group consisting of SEQ ID NOs: 42-65. The present disclosure provides compositions comprising nucleic acid sequences encoding at least two amino acid sequences selected from the group consisting of SEQ ID NOs: 1550-1593. The present disclosure further provides a nucleic acid sequence encoding at least one amino acid sequence selected from the group consisting of SEQ ID NOs: 1595-1661.

Description

This application claims 35 U.S.C. 119(e) benefit and priority to U.S. Patent Application No. 17/336,960, filed June 2, 2021. U.S. Patent Application No. 17/336,960, now U.S. Patent Application No. 11,058,751, filed on July 13, 2021, filed on November 20, 2020 This is a continuation of No. 17/100,630. The contents of each of these documents are incorporated herein by reference in their entirety.

This application also claims the benefit and priority of U.S. Pat. Application No. 17/389,875 is currently U.S. Patent Application No. 11,161,892 filed on November 2, 2021, United States Patent Application No. 17, filed December 7, 2020. This is a continuation of No./114,237. The contents of each of these documents are incorporated herein by reference in their entirety.

This application also claims the benefit of U.S. Patent Application No. 63/249,235, filed September 28, 2021, the contents of which are incorporated herein by reference in their entirety.

All patents, patent applications, and publications cited herein are incorporated by reference in their entirety. The disclosures of such publications are incorporated by reference into this application in their entirety.

This patent disclosure contains material that is subject to copyright protection. The copyright owner has no objection to facsimile reproduction of patent documents or patent disclosures in the United States Patent and Trademark Office patent files or records, but otherwise reserves any and all copyright rights therein.

INCORPORATION BY REFERENCE All documents cited herein are incorporated by reference in their entirety.

SEQUENCE LISTING This application contains a sequence listing submitted electronically in ASCII format, which is incorporated herein by reference in its entirety. This ASCII copy was created on November 15, 2021, and the file name is 2215269_00123WO1_SL. txt and has a size of 23,070,263 bytes.

TECHNICAL FIELD The present invention relates generally to peptide vaccine compositions, systems, and methods. More particularly, the present invention relates to compositions, systems, and methods for designing peptide vaccines to treat or prevent disease that are optimized based on predicted population immunogenicity.

The goal of peptide vaccines is to train the immune system to expand its ability to recognize and engage cells presenting target peptides, improving immune responses against cancerous cells or pathogens. Peptide vaccines can also be administered to those already suffering from the disease to increase the immune response against an implicated cancer, other disease, or pathogen. Alternatively, a peptide vaccine can be administered to induce the immune system to develop therapeutic tolerance to one or more peptides. There is a need for peptide vaccine compositions, systems, and methods based on the prediction of target peptides that will be presented to protect the host from cancer, other diseases, or pathogen infections. We have identified neoantigens introduced by mutations in the RAS gene that occur in numerous cancers, as well as chronic myeloid leukemia (CML), acute lymphoblastic leukemia (ALL), and acute myeloid leukemia (AML). The present invention provides novel prophylactic and therapeutic cancer vaccines based on BCR-ABL gene fusions that occur in cases of breast cancer, invasive ductal carcinoma, and other cancers.

In one aspect, the present invention provides SEQ ID NO. 1, SEQ ID NO. 2, SEQ ID NO. 3, SEQ ID NO. 4, SEQ ID NO. 5, SEQ ID NO. 6, SEQ ID NO. 8, SEQ ID NO. 9, SEQ ID NO. 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37, SEQ ID NO: 38, SEQ ID NO: 39, SEQ ID NO: 40, and SEQ ID NO: 41.

In some embodiments, the nucleic acid sequence is an immunogenic composition. In some embodiments, the nucleic acid sequence is administered in vivo in a construct for expression. In some embodiments, in vivo administration of the nucleic acid sequence is configured to produce at least one peptide presented by an HLA class I molecule. In some embodiments, at least one peptide is a modified or unmodified fragment of a mutant KRAS protein. In some embodiments, the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to prevent cancer. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to treat cancer.

In another aspect, the invention provides SEQ ID NO:1, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO:10, SEQ ID NO:12, Number 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25 , SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37, SEQ ID NO: 38, Sequence An immunogenic peptide composition comprising at least two peptides selected from the group consisting of No. 39, SEQ ID No. 40, and SEQ ID No. 41 is provided.

In some embodiments, at least one peptide of the at least two peptides is presented by an HLA class I molecule in the subject. In some embodiments, at least one peptide of the at least two peptides is a modified or unmodified fragment of a mutant KRAS protein. In some embodiments, the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to prevent cancer. In some embodiments, an immunogenic peptide composition is administered to a subject in an effective amount to treat cancer. In some embodiments, the immunogenic peptide compositions include SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10. , SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, Sequence Number 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37 , SEQ ID NO: 38, SEQ ID NO: 39, SEQ ID NO: 40, and SEQ ID NO: 41.

In another aspect, the invention provides SEQ ID NO:42, SEQ ID NO:43, SEQ ID NO:44, SEQ ID NO:45, SEQ ID NO:46, SEQ ID NO:47, SEQ ID NO:48, SEQ ID NO:49, SEQ ID NO:50, SEQ ID NO:51, Number 52, SEQ ID NO: 53, SEQ ID NO: 54, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 59, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 63, SEQ ID NO: 64 , and SEQ ID NO: 65.

In some embodiments, the nucleic acid sequence is an immunogenic composition. In some embodiments, the nucleic acid sequence is administered in vivo in a construct for expression. In some embodiments, in vivo administration of the nucleic acid sequence is configured to produce at least one peptide presented by an HLA class II molecule. In some embodiments, at least one peptide is a modified fragment of a mutant KRAS protein. In some embodiments, the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to prevent cancer. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to treat cancer.

In another aspect, the invention provides SEQ ID NO:42, SEQ ID NO:43, SEQ ID NO:44, SEQ ID NO:45, SEQ ID NO:46, SEQ ID NO:47, SEQ ID NO:48, SEQ ID NO:49, SEQ ID NO:50, SEQ ID NO:51, Number 52, SEQ ID NO: 53, SEQ ID NO: 54, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 59, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 63, SEQ ID NO: 64 , and SEQ ID NO: 65.

In some embodiments, at least one peptide in the immunogenic peptide composition is presented by an HLA class II molecule. In some embodiments, at least one peptide in the immunogenic peptide composition is a modified or unmodified fragment of a mutant KRAS protein. In some embodiments, the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to prevent cancer. In some embodiments, an immunogenic peptide composition is administered to a subject in an effective amount to treat cancer. In some embodiments, the immunogenic peptide compositions are SEQ ID NO: 42, SEQ ID NO: 43, SEQ ID NO: 44, SEQ ID NO: 45, SEQ ID NO: 46, SEQ ID NO: 47, SEQ ID NO: 48, SEQ ID NO: 49, SEQ ID NO: 50. , SEQ ID NO: 51, SEQ ID NO: 52, SEQ ID NO: 53, SEQ ID NO: 54, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 59, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, Sequence No. 63, SEQ ID No. 64, and SEQ ID No. 65.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; at least one peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen or a self protein; for each peptide sequence in the first peptide set, a plurality of peptide- determining whether each peptide sequence in the first set of peptides has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles; and a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one amino acid of a peptide sequence in the first peptide set. determining whether each modified peptide sequence in the second set of peptides has a peptide-HLA binding score that satisfies a second threshold for at least three HLA alleles. the second threshold being more constrained than the first threshold, and creating a third set of peptides by selecting a subset of the second set of peptides, the selection being more constrained than the first threshold; calculating population coverage, the calculation of population coverage comprising: if the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence does not meet a first threshold with respect to the first HLA allele; performing a step comprising excluding a peptide-HLA binding score for a first HLA allele of the modified peptide sequence, the selected subset having population coverage above a third threshold; an experimental assay; obtaining a peptide-HLA immunogenicity metric for at least one peptide sequence in the third set of peptides; and at least one peptide sequence in the third set of peptides on which the experimental assay was performed. A method is provided comprising forming an immunogenic peptide composition comprising:

In some embodiments, selecting a plurality of unmodified peptide sequences to create a first set of peptides involves sliding a window of size n across amino acid sequences encoding tumor neoantigens or self-proteins. and n is about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences in the first peptide set. In some embodiments, each peptide sequence in the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. In some embodiments, the method further comprises filtering the first set of peptides to exclude peptide sequences that have a predicted binding core that includes the target residue at the anchor position. In some embodiments, the method further comprises substituting at least one amino acid residue of each peptide sequence in the first set of peptides, wherein for at least one peptide sequence in the first set of peptides, At least one amino acid residue is present at the anchor position. In some embodiments, the first threshold is a binding affinity of less than about 1000 nM. In some embodiments, the second threshold is a binding affinity of less than about 500 nM. In some embodiments, population coverage is calculated based on the frequency of HLA haplotypes in the human population. In some embodiments, population coverage is calculated based on the frequencies of at least three HLA alleles in the human population. In some embodiments, the plurality of unmodified peptide sequences are derived from tumor neoantigens or self-proteins present in the subject. In some embodiments, the third threshold is a percentage of the human population of about 0.7 to about 0.8. In some embodiments, the tumor neoantigen or self protein is associated with a cancer consisting of pancreas, colon, rectum, kidney, bronchus, lung, uterus, cervix, bladder, liver, and stomach. selected from the group.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; a plurality of unmodified peptide sequences are associated with tumor neoantigens or self-proteins; a plurality of peptide-HLA immunogenicity metrics for each peptide sequence in the first peptide set; determining whether each peptide sequence in the first set of peptides has a peptide-HLA immunogenicity metric that satisfies a first threshold for at least three HLA alleles; creating a second peptide set comprising a peptide set and a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one amino acid residue of a peptide sequence in the first peptide set; determining whether each modified peptide sequence in the second set of peptides has a peptide-HLA immunogenicity metric that satisfies a second threshold for at least three HLA alleles; wherein the second threshold is more constrained than the first threshold; and creating a third set of peptides by selecting a subset of the second set of peptides, the selection comprising: , calculating a predicted vaccine performance, wherein the calculation of the predicted vaccine performance is such that the peptide-HLA immunogenicity metric of the unmodified peptide sequence associated with the modified peptide sequence exceeds a first threshold with respect to the first HLA allele. If not, the predicted vaccine performance includes excluding the peptide-HLA immunogenicity metric for the first HLA allele of the modified peptide sequence, and predicting the non-excluded peptide-HLA immunogenicity metric for each peptide sequence in the third set of peptides. performing a step that is a function of an HLA immunogenicity metric; performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence in the third peptide set; and A method is provided that includes forming an immunogenic peptide composition that includes at least one peptide sequence in a third set of peptides on which an experimental assay was performed.

In some embodiments, selecting the plurality of unmodified peptide sequences to create the first set of peptides comprises sliding a window of size n across the amino acid sequence encoding the tumor neoantigen or self protein. , n is about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences in the first peptide set. In some embodiments, each peptide sequence in the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. In some embodiments, the method further comprises filtering the first set of peptides to exclude peptide sequences that have a predicted binding core that includes the target residue at the anchor position. In some embodiments, the method further comprises substituting at least one amino acid residue of each peptide sequence in the first set of peptides, wherein for at least one peptide sequence in the first set of peptides, At least one amino acid residue is present at the anchor position. In some embodiments, the first threshold is a binding affinity of less than about 1000 nM.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; each peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen or self protein; determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles; creating a second peptide set comprising a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising a substitution of at least one amino acid residue of a peptide sequence in the first peptide set; determining whether each modified peptide sequence in the second set of peptides has a peptide-HLA binding score that satisfies a second threshold for at least three HLA alleles, the step comprising: a second threshold is more constrained than the first threshold; and creating a third set of peptides by selecting a subset of the second set of peptides, the selection determining the predicted vaccine performance. calculating, the calculation of predicted vaccine performance comprises: calculating the predicted vaccine performance if the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence does not meet a first threshold with respect to the first HLA allele; excluding the peptide-HLA binding score for the first HLA allele of the third peptide set, wherein the predicted vaccine performance is a function of the non-excluded peptide-HLA binding score of each peptide sequence in the third peptide set. performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence in the third set of peptides; and a third peptide on which the experimental assay was performed. A method is provided that includes forming an immunogenic peptide composition that includes at least one peptide sequence in a set.

In some embodiments, the second threshold is based on data obtained from one or more experimental assays. In some embodiments, the predicted vaccine performance further determines that the first peptide sequence in the first peptide set is linked to a second HLA allele of at least three HLA alleles by the first binding core. a function of the peptide-HLA immunogenicity metric of at least one modified peptide sequence of the plurality of modified peptide sequences bound to a second HLA allele of the at least three HLA alleles if predicted to bind to a second HLA allele of the at least three HLA alleles; , the first binding core is a binding core of the first peptide sequence, the first binding core is the same as the second binding core, and the first binding core and the second binding core are of the peptide sequence. comprising an amino acid position within the sequence, the second binding core being a binding core of at least one modified peptide sequence of the plurality of modified peptide sequences bound to a second HLA allele.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; at least one peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen or a self protein; for each peptide sequence in the first peptide set, a plurality of peptide- determining whether each peptide sequence in the first set of peptides has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles; and a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one amino acid of a peptide sequence in the first peptide set. determining whether each modified peptide sequence in the second set of peptides has a peptide-HLA binding score that satisfies a second threshold for at least three HLA alleles. and the second threshold is more constrained than the first threshold, creating a third set of peptides by selecting a subset of the second set of peptides, the selection comprising: calculating predicted vaccine performance based on the HLA type of the first performing a step comprising excluding a peptide-HLA binding score for a first HLA allele of the modified peptide sequence if the threshold is not met; obtaining a peptide-HLA immunogenicity metric for at least one peptide sequence; and forming an immunogenic peptide composition comprising at least one peptide sequence in a third set of peptides on which an experimental assay was performed. Provide a method including.

In some embodiments, each peptide sequence in the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. In some embodiments, the plurality of unmodified peptide sequences are derived from tumor neoantigens or self-proteins present in the subject. In some embodiments, at least three HLA alleles are present in the subject's HLA type. In some embodiments, the plurality of unmodified peptide sequences are derived from tumor neoantigens or self-proteins present in the subject. In some embodiments, the plurality of unmodified peptide sequences are derived from tumor neoantigens or self-proteins present in the subject. In some embodiments, the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of at least one peptide sequence in the third peptide set. In some embodiments, the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of at least one peptide sequence in the third peptide set.

In another aspect, the invention provides a composition comprising a nucleic acid sequence encoding at least two amino acid sequences selected from the group consisting of SEQ ID NOs: 1550-1593.

In some embodiments, the composition is immunogenic. In some embodiments, the nucleic acid sequence is administered in vivo in a construct for expression. In some embodiments, in vivo administration of the nucleic acid sequence is configured to produce at least one peptide presented by an HLA class I molecule. In some embodiments, at least one peptide is a modified or unmodified fragment of a BCL-ABL gene fusion. In some embodiments, the BCR-ABL gene fusion is b3a2 or b2a2. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to prevent cancer. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to treat cancer.

In another aspect, the invention provides a composition comprising at least two aminopeptides selected from the group consisting of SEQ ID NOs: 1550-1593.

In some embodiments, at least one peptide of the at least two peptides is presented by an HLA class I molecule in the subject. In some embodiments, at least one peptide in the immunogenic peptide composition is a modified or unmodified fragment of a BCL-ABL gene fusion. In some embodiments, the BCR-ABL gene fusion is b3a2 or b2a2. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to prevent cancer. In some embodiments, an immunogenic peptide composition is administered to a subject in an effective amount to treat cancer. In another aspect, the invention provides a composition comprising at least two peptides selected from the group consisting of SEQ ID NOs: 1550-1593.

In another aspect, the invention provides a nucleic acid sequence encoding at least one amino acid sequence selected from the group consisting of SEQ ID NOs: 1595-1661.

In some embodiments, the composition is immunogenic. In some embodiments, the nucleic acid sequence is administered in vivo in a construct for expression. In some embodiments, in vivo administration of the nucleic acid sequence is configured to produce at least one peptide presented by an HLA class II molecule. In some embodiments, at least one amino acid sequence is derived from a modified fragment of a BCL-ABL gene fusion. In some embodiments, the BCR-ABL gene fusion is b3a2 or b2a2. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to prevent cancer. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to treat cancer.

In another aspect, the invention provides a nucleic acid sequence encoding at least one amino acid sequence selected from the group consisting of SEQ ID NOs: 1595-1661.

In some embodiments, at least one peptide is presented by an HLA class II molecule in the subject. In some embodiments, at least one peptide in the immunogenic peptide composition is a modified or unmodified fragment of a BCL-ABL gene fusion. In some embodiments, the BCR-ABL gene fusion is b3a2 or b2a2. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to prevent cancer. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to treat cancer. In some embodiments, the immunogenic peptide composition comprises at least two peptides selected from the group consisting of SEQ ID NOs: 1595-1661.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; for each peptide sequence in the first set of peptides, wherein at least one peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen, a pathogen proteome, or a self protein; determining a plurality of peptide-HLA binding scores, determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles; a step of creating a first peptide set and a second peptide set comprising a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences being a peptide sequence in the first peptide set; determining a plurality of peptide-HLA binding scores for each peptide sequence in the second set of peptides, and selecting a subset of the second set of peptides; creating a third set of peptides by selecting, the selection comprising calculating population coverage, the calculation of population coverage determining the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence; , excluding a peptide-HLA binding score for the first HLA allele of the modified peptide sequence if the first threshold is not met for the first HLA allele; performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence in the third peptide set; A method is provided that includes forming an immunogenic peptide composition that includes at least one peptide sequence of the third set of peptides in which the assay was performed.

In some embodiments, selecting a plurality of unmodified peptide sequences to create a first set of peptides of size n over at least a portion of an amino acid sequence encoding a tumor neoantigen, pathogen proteome, or self protein. sliding a window, where n is about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences of the first peptide set. In some embodiments, each peptide sequence of the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. Some embodiments further include filtering the first set of peptides to exclude peptide sequences that have a predicted binding core that includes the target amino acid residue at the anchor position. In some embodiments, the method further comprises substituting at least one amino acid residue of each peptide sequence of the first peptide set, wherein for at least one peptide sequence of the first peptide set, the at least one amino acid residue exists at the anchor position. In some embodiments, the first threshold is a binding affinity of less than about 1000 nM. In some embodiments, population coverage is calculated for at least three HLA alleles. In some embodiments, population coverage is calculated based on the frequency of HLA haplotypes in the human population. In some embodiments, population coverage is calculated based on the frequencies of at least three HLA alleles in the human population. In some embodiments, the plurality of unmodified peptide sequences are derived from tumor neoantigens, pathogen proteomes, or self proteins present in the subject. In some embodiments, the second threshold is a percentage of the human population of about 0.7 to about 0.8. In some embodiments, the tumor neoantigen or self protein is associated with a cancer consisting of pancreas, colon, rectum, kidney, bronchus, lung, uterus, cervix, bladder, liver, and stomach. selected from the group. In some embodiments, the pathogen proteome is associated with a pathogen infection in a human subject. In some embodiments, the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of at least one peptide sequence of the third set of peptides.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; the plurality of unmodified peptide sequences are associated with tumor neoantigens, pathogen proteomes, or self proteins; for each peptide sequence in the first peptide set, the plurality of peptide-HLA immunogenic determining whether each peptide sequence in the first set of peptides has a peptide-HLA immunogenicity metric that satisfies a threshold for at least three HLA alleles; the first set of peptides; and creating a second peptide set comprising a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one amino acid residue of a peptide sequence in the first peptide set. determining a plurality of peptide-HLA immunogenicity metrics for each peptide sequence in the second set of peptides; and selecting a subset of the second set of peptides to obtain a third peptide. creating a set, wherein the selecting includes calculating a predicted vaccine performance, the calculating the predicted vaccine performance including a peptide-HLA immunogenicity metric of an unmodified peptide sequence associated with a modified peptide sequence; including excluding the peptide-HLA immunogenicity metric for the first HLA allele of the modified peptide sequence if the threshold is not met for one HLA allele; performing an experimental assay to determine the peptide-HLA immunogenicity metric for at least one peptide sequence of the third set of peptides; and forming an immunogenic peptide composition comprising at least one peptide sequence of a third set of peptides on which an experimental assay was performed.

In some embodiments, selecting a plurality of unmodified peptide sequences to create a first set of peptides of size n over at least a portion of an amino acid sequence encoding a tumor neoantigen, pathogen proteome, or self protein. sliding a window, where n is about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences of the first peptide set. In some embodiments, each peptide sequence of the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. Some embodiments further include filtering the first set of peptides to exclude peptide sequences that have a predicted binding core that includes the target amino acid residue at the anchor position. Some embodiments further include substituting at least one amino acid residue of each peptide sequence of the first set of peptides. In some embodiments, the threshold is a binding affinity of less than about 1000 nM. In some embodiments, at least three HLA alleles are present in the subject's HLA type. In some embodiments, the plurality of peptide sequences are derived from tumor neoantigens, pathogen proteomes, or self proteins present in the subject. In some embodiments, the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of at least one peptide sequence of the third set of peptides.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; each peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen, pathogen proteome, or self protein; determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a threshold for at least three HLA alleles; the first peptide set; and creating a second peptide set comprising a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one amino acid residue of a peptide sequence in the first peptide set. determining a plurality of peptide-HLA binding scores for each peptide sequence in the second set of peptides; and selecting a subset of the second set of peptides to form a third set of peptides. creating a step in which the selecting includes calculating a predicted vaccine performance, wherein the calculation of the predicted vaccine performance is such that the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence is higher than that of the first HLA allele. including excluding the modified peptide sequence's peptide-HLA binding score for the first HLA allele if the threshold for the gene is not met; performing a step that is a function of an HLA binding score; performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence of the third peptide set; and the experimental assay. forming an immunogenic peptide composition comprising at least one peptide sequence of a third set of peptides in which the method has been performed.

In some embodiments, the second threshold is determined from data obtained from one or more experimental assays. In some embodiments, the performance of the predicted vaccine is further determined if the first peptide sequence of the first peptide set is predicted to bind to the second HLA allele by the first binding core. a function of the peptide-HLA immunogenicity metric of at least one modified peptide sequence of the second set of peptides with respect to an HLA allele of the first the binding core of is the same as the second binding core, the first binding core and the second binding core each include an amino acid position within the peptide sequence, and the second binding core comprises at least one modified peptide sequence. is the combined core of In some embodiments, the plurality of peptide sequences are derived from tumor neoantigens, pathogen proteomes, or self proteins present in the subject.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; for each peptide sequence in the first set of peptides, wherein at least one peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen, a pathogen proteome, or a self protein; determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a threshold for at least three HLA alleles; creating a second peptide set comprising one peptide set and a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one of the peptide sequences in the first peptide set; determining a plurality of peptide-HLA binding scores for each peptide sequence in the second set of peptides; and a third step by selecting a subset of the second set of peptides. creating a set of peptides of the unmodified peptide sequence associated with the modified peptide sequence, the selection comprising calculating predicted vaccine performance based on the HLA type of the subject; performing a step comprising excluding a peptide-HLA binding score for a first HLA allele of the modified peptide sequence if the HLA binding score does not meet a threshold for the first HLA allele; an experimental assay; obtaining a peptide-HLA immunogenicity metric for at least one peptide sequence of the third set of peptides; and at least one peptide sequence of the third set of peptides on which the experimental assay was performed. A method is provided that includes forming an immunogenic peptide composition.

In some embodiments, each peptide sequence in the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. In some embodiments, the plurality of peptide sequences are derived from tumor neoantigens, pathogen proteomes, or self proteins present in the subject.

The following figures illustrate exemplary embodiments of the invention.

FIG. 1 is a flowchart of the vaccine optimization method. FIG. 2 is a flowchart of the vaccine optimization method by seed set compression. FIG. 3 is a graph showing predicted population coverage of MHC class I vaccines by vaccine size for KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D targets. FIG. 4 is a graph showing predicted population coverage of MHC class II vaccines by vaccine size for KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D targets. Figure 5 shows heteroclitic peptides for BCR-ABL b3a2 fusion, at least one peptide-HLA hit (circle), at least three peptide-HLA hits (triangles), and at least five peptide-HLA hits (squares). FIG. 2 is a graph showing predicted population coverage by vaccine size for MHC class I vaccines containing MHC class I vaccines. Dashed lines indicate the predicted population coverage of the BCR-ABL b3a2 fusion vaccine without heteroclitic peptides for at least one (top dashed line) and five (bottom dashed line) peptide-HLA hits per individual. Figure 6 shows heteroclitic peptides for BCR-ABL b3a2 fusion, at least one peptide-HLA hit (circle), at least three peptide-HLA hits (triangles), and at least five peptide-HLA hits (squares). 2 is a graph showing predicted population coverage rates by vaccine size for MHC class II vaccines containing MHC class II vaccines. The dashed line indicates the predicted population coverage of the BCR-ABL b3a2 fusion vaccine without heteroclitic peptides for at least one peptide-HLA hit per individual. Figure 7 shows heteroclitic peptides for BCR-ABL b2a2 fusion, at least one peptide-HLA hit (circle), at least three peptide-HLA hits (triangle), at least five peptide-HLA hits (square). FIG. 2 is a graph showing predicted population coverage by vaccine size for MHC class I vaccines including: FIG. The dashed line indicates the predicted population coverage of the BCR-ABL b3a2 fusion vaccine without heteroclitic peptides for at least one peptide-HLA hit per individual. Figure 8 shows heteroclitic peptides for BCR-ABL b2a2 fusion, at least one peptide-HLA hit (circle), at least three peptide-HLA hits (triangles), and at least five peptide-HLA hits (squares). 2 is a graph showing predicted population coverage rates by vaccine size for MHC class II vaccines containing MHC class II vaccines. Dashed lines indicate the predicted population coverage of the BCR-ABL b3a2 fusion vaccine without heteroclitic peptides for at least one (top dashed line) and five (bottom dashed line) peptide-HLA hits per individual. Figure 9 shows the vaccine size of KRAS G12V vaccine for HLA diplotypes HLA-A02:03, HLA-A11:01, HLA-B55:02, HLA-B58:01, HLA-C03:02, and HLA-C03:03. Another predicted peptide-HLA hit is shown. Figure 10 shows the probabilities of pancreatic, colorectal, and bronchial/pulmonary disease presentation and the corresponding probabilities of target presentation for various mutant protein targets. FIG. 11 is a flowchart of a multi-target (combination) vaccine optimization method. Figure 12 shows predicted population coverage by vaccine size for pancreatic cancer multi-target (combination) MHC class I vaccines for KRAS G12D, KRAS G12V, and KRAS G12R targets. The dashed line shows the predicted population coverage of the pancreatic cancer combination vaccine without MHC class I heteroclitic peptides. Figure 13 shows predicted population coverage by vaccine size for pancreatic cancer multi-target (combination) MHC class II vaccines for KRAS G12D, KRAS G12V, and KRAS G12R targets. The dashed line shows the predicted population coverage of the pancreatic cancer combination vaccine without MHC class II heteroclitic peptides. 1 is a script showing an example Python implementation of the MergeMulti function for a combination vaccine design procedure.

In some embodiments, the present disclosure provides peptide sequences that are presented by major histocompatibility complex (MHC) molecules on cells and that train the immune system to recognize cancer or pathogen-affected cells. An integrated peptide vaccine is provided. In some embodiments, the present disclosure provides a method for inducing therapeutic tolerance in antigen-specific immunotherapy for autoimmune diseases (Alhadj Ali et al., 2017, Gibson, et al. 2015). Peptide vaccines are provided that incorporate peptide sequences that will be presented by histocompatibility complex (MHC) molecules. In some embodiments, a peptide vaccine is a composition consisting of one or more peptides. In some embodiments, a peptide vaccine is an mRNA or DNA construct that is administered in vivo for expression, encoding one or more peptides.

Peptide presentation by MHC molecules is necessary for the peptide to be immunogenic and for the resulting peptide-MHC complex to be recognized by an individual's T cells, inducing T cell activation, expansion, and immune memory. However, it is not enough. In some embodiments, multiplex identification of antigen-specific T cell receptors using ELISPOT (Slota et al., 2011) or a combination of immunoassay and immunoreceptor sequencing (MIRA) assays (Klinger et al., 2015) to score peptide presentation (e.g., peptide immunogenicity requiring peptide binding) by MHC molecules (e.g., HLA alleles) (e.g., measured as peptide-HLA binding score). . In some embodiments, multiplex identification of antigen-specific T cell receptors using ELISPOT (Slota et al., 2011) or a combination of immunoassay and immunoreceptor sequencing (MIRA) assays (Klinger et al. , 2015) can be used to generate peptide-HLA immunogenicity metrics for peptides and HLA alleles in a given experimental situation or individual. In some embodiments, multiplex identification of antigen-specific T cell receptors using ELISPOT (Slota et al., 2011) or a combination of immunoassay and immunoreceptor sequencing (MIRA) assays (Klinger et al. , 2015) to score peptide presentation (e.g., binding affinity) by MHC molecules (e.g., HLA alleles) (e.g., measured as peptide-HLA binding score). , or peptide-can be combined with machine learning-based predictions to determine immunogenicity metrics. In some embodiments, MHCflurry or NetMHCpan (Reynisson et al., 2020) computational methods (known in the art) are used to predict MHC class I presentation of peptides by HLA alleles (see Table 1). ). In some embodiments, the NetMHCIIpan calculation method (Reynisson et al., 2020) is used to predict MHC class II presentation of peptides by HLA alleles (see Table 2).

In some embodiments, MHCflurry (Odonnell et al., 2018, Odonnell et al., 2020, incorporated herein by reference in their entirety), NetMHCpan (Reynisson et al., 2020). This document is incorporated herein by reference in its entirety), and NetMHCIIpan (Reynisson et al., 2020) to determine whether MHC class I (MHCflurry, NetMHCpan) presentation of peptides by HLA allele or class II ( NetMHCIIpan) presentation. In other embodiments, other methods for determining peptide-HLA binding are used, such as those disclosed in WO 2005/042698. This document is incorporated herein by reference in its entirety. In NetMHCpan-4.1 and NetMHCIIpan-4.0, the NNAalign_MA algorithm (Alvarez et al., 2019, incorporated herein by reference in its entirety) was used to predict peptide-HLA binding. Ru. NNAlign_MA is then based on the NNAlign (Nielsen et al., 2009, Nielsen et al., 2017, herein incorporated by reference in its entirety) neural network. In NetMHCpan-4.1 (Reynisson et al., 2020), the NNAalign_MA network is used with at least 180 inputs (9×20=180 inputs) describing peptide sequences. Networks with both 56 and 66 hidden neurons and two outputs are used (Alvarez et al., 2019). Each network architecture (56 or 66 hidden neurons) was trained with 5 different random parameter initializations and 5-fold cross-validation, resulting in a total of 50 individual trained networks (2 architectures x 5 initializations x 5 cross-validations). These 50 trained networks include 25 networks with at least 10,800 parameters (180 inputs x 56 neurons) and 25 networks with at least 11,880 parameters (180 inputs x 66 neurons). Used as an ensemble with a network. Therefore, the ensemble of 50 networks of NetMHCpan-4.1 consists of at least 567,000 parameters that must be evaluated with at least 567,000 arithmetic operations to calculate peptide-MHC binding. In NetMHCpan-4.1 (Reynisson et al., 2020), the NNAalign_MA network is used with at least 180 inputs (9×20=180 inputs) describing peptide sequences. Networks with 2, 10, 20, 40, and 60 hidden neurons and two outputs are used (Alvarez et al., 2019). Each network architecture (2, 10, 20, 40, and 60 hidden neurons) was trained with 10 different random parameter initializations and 5-fold cross-validation, resulting in a total of 250 individual trained networks (5 (architecture x 10 initializations x 5 cross-validations). These 250 trained networks include: 50 networks with at least 360 parameters (180 inputs x 2 neurons); 50 networks with at least 1800 parameters (180 inputs x 10 neurons); 50 networks with at least 1800 parameters (180 inputs x 10 neurons); 50 networks with parameters (180 inputs x 20 neurons), 50 networks with at least 7200 parameters (180 inputs x 40 neurons), at least 10,800 parameters (180 inputs x 60 neurons) used as an ensemble with 50 networks. Therefore, the ensemble of 250 networks in NetMHCpan-4.1 has at least 1,188,000 parameters that must be evaluated with at least 1,188,000 arithmetic operations to calculate peptide-MHC binding. Consisting of

Peptides are presented by MHC molecules upon binding within the groove of the MHC molecule and transported to the cell surface where they can be recognized by T cell receptors. Target peptide refers to a foreign peptide or a self peptide. In some embodiments, a peptide that is part of the normal proteome in a healthy individual is a self peptide, and a peptide that is not part of the normal proteome is a foreign peptide. In some embodiments, the target peptide can be part of the normal proteome that exhibits aberrant expression (eg, a cancer-testis antigen, such as NY-ESO-1). Foreign peptides can be generated by mutation of normal self-proteins within tumor cells, creating epitopes called neoantigens, or by pathogen infection. In some embodiments, a neoantigen is any subsequence of a human protein that includes one or more altered amino acids or protein modifications that do not occur in a healthy individual. Thus, in this disclosure, a foreign peptide refers to an amino acid sequence encoding a fragment of a target protein/peptide (or full-length protein/peptide), and the target protein/peptide is a neoantigen protein, a pathogen proteome, or a non-self and any other undesirable proteins expected to be bound and presented by HLA alleles.

For example, KRAS gene mutations are the most frequently mutated oncogene in cancer, but are extremely difficult to treat with small molecule therapeutics. The KRAS protein is part of a signaling pathway that controls cell proliferation, and point mutations in this protein can cause constitutive pathway activation and uncontrolled cell proliferation. Single amino acid KRAS mutations result in only small changes in protein structure, making it difficult to develop small molecule drugs that recognize mutant-specific binding pockets and inactivate KRAS signaling. KRAS oncogenic mutations include glycine to aspartate (G12D), glycine to valine (G12V), glycine to arginine (G12R), or glycine to cystine (G12C) at position 12. or a glycine to aspartic acid mutation at position 13 (G13D). Corresponding foreign peptides contain such mutations. KRAS is a member of the RAS gene family, which also includes HRAS and NRAS. KRAS, HRAS, and NRAS are identical in sequence from residue 1 to residue 86. Therefore, all vaccines and peptide sequences described herein against mutations in one RAS family member can be used against the same mutation in any other RAS family member (e.g., KRAS G12D vaccine is also a vaccine against HRAS G12D).

The BCR-ABL mutation is the result of an abnormal conjugation between the BCR gene on chromosome 22 and the ABL gene on chromosome 9, resulting in a fusion of the two genes on chromosome 22. Differences in the fusion products formed result in different BCR-ABL transcripts, with b3a2 (also known as e14a2) and b2a2 (also known as e13a2) being the most common. In a study of 200 patients with BCR-ABL, 42% expressed b2a2, 41% expressed b3a2, and 18% expressed both transcripts (Jain et al., 2016). Aberrant b2a2 and b3a2 BCR-ABL fusions create novel protein sequences containing foreign peptides at the junction of BCL and ABL. Disclosed herein are methods of using such foreign peptides and their derivatives as neoantigenic epitopes for vaccine design.

A challenge in the design of peptide vaccines is the diversity of human MHC alleles (HLA alleles), each of which has specific characteristics for the peptide sequence they are to present. Indicates priority. The human leukocyte antigen (HLA) locus located within the MHC encodes HLA class I and class II molecules. There are three classical class I loci (HLA-A, HLA-B, and HLA-C) and three loci encoding class II molecules (HLA-DR, HLA-DQ, and HLA-DP) do. An individual's HLA type describes the alleles the individual has at each of these loci. Peptides from about 8 to about 11 residues in length can bind to HLA class I (or MHC class I) molecules, whereas peptides from about 13 to about 25 residues in length can bind to HLA class II (or MHC class I) molecules. or MHC class II) molecules (Rist et al., 2013; Chicz et al., 1992). Human populations originating from different geographic regions have different frequencies of HLA alleles, and such populations exhibit linkage disequilibrium between HLA loci, resulting in population-specific haplotype frequencies. In some embodiments, an effective vaccine comprising considering HLA allele frequencies in the target population as well as linkage disequilibrium between HLA genes to achieve a set of peptides that are likely to be robustly presented. A method for producing is disclosed.

The present disclosure provides compositions, systems, and methods of vaccine design that generate immunity against single or multiple targets. In some embodiments, the target is a neoantigenic protein sequence, a pathogen proteome, or any non-self that is expected to be bound and presented by HLA molecules (also referred to herein as HLA alleles). Other undesirable protein sequences. If a target is present in an individual, there may be multiple peptide sequences presented by different HLA alleles. In some embodiments, it may be desirable to create a vaccine that includes selected self-peptides, and such selected self-peptides are therefore considered to be target peptides for this purpose.

The term peptide-HLA binding is defined as the binding of a peptide to an HLA allele that can be predicted computationally, observed experimentally, or predicted computationally using experimental observations. Both are possible. Metrics of peptide-HLA binding can be expressed as affinity, percentile ranking, binary at a predetermined threshold, probability, or other metrics known in the art. The term peptide-HLA immunogenicity metric is defined as activation of T cells based on recognition of peptides upon binding of HLA alleles. The term peptide-HLA immunogenicity score is another term for the peptide-HLA immunogenicity metric, and these terms are synonymous. Peptide-HLA immunogenicity metrics can vary between individuals, and metrics of peptide-HLA immunogenicity can be expressed as probability, binary indicators, or other metrics regarding the likelihood that a peptide-HLA combination is immunogenic. It can be expressed as In some embodiments, peptide-HLA immunogenicity is defined as the induction of immune tolerance based on recognition of the peptide upon binding of HLA alleles. Peptide-HLA immunogenicity metrics can be predicted computationally, observed experimentally, or predicted computationally using experimental observations. In some embodiments, peptide-HLA immunogenicity requires peptide-HLA binding, so the peptide-HLA immunogenicity metric is based solely on peptide-HLA binding. In some embodiments, peptide-HLA immunogenicity data or computational predictions of peptide-HLA immunogenicity can be included and combined with scores of peptide presentation in the methods disclosed herein. One way to combine scores is to use immunogenicity data for peptides assayed for immunogenicity in affected or vaccinated individuals, and select the HLA allele predicted by computational methods to have the highest likelihood of presentation. is to assign the peptide to the HLA allele that presented it in the individual. For peptides that have not been assayed experimentally, computational presentation predictions can be used. In some embodiments, different computational methods for predicting peptide-HLA immunogenicity or peptide-HLA binding can be combined (Liu et al., 2020b). For a given set of peptides and a set of HLA alleles, the term peptide-HLA hit is the number of unique combinations of peptides and HLA alleles that exhibit peptide-HLA immunogenicity or binding at a given threshold. . For example, a peptide-HLA hit of 2 means that one peptide is predicted to bind to two different HLA alleles (or induce T cell activation), or two peptides are predicted to bind to two different HLA alleles (or induce T cell activation). predicted to bind to the same HLA allele (or induce T cell activation), or mean that the two peptides are predicted to bind to the same HLA allele (or induce T cell activation) can do. For a given set of peptides and HLA frequencies, HLA haplotype frequencies, or HLA diplotype frequencies, the expected peptide-HLA hit count is the peptide HLA hits in each set of HLAs representing an individual, weighted by their frequency of occurrence. is the average number of

Because immunogenicity can vary between individuals, one way to increase the probability of vaccine efficacy is to use a diverse set of targeting peptides (e.g., at least two peptides), so that some of them is to increase the likelihood that a subset of the group will be immunogenic in a given individual. Previous studies using mouse models have shown that most MHC-presented peptides are immunogenic, but immunogenicity varies between individuals, as described in Croft et al. (2019). different. In some embodiments, experimental peptide-HLA immunogenicity data is used to determine which target peptides and their modifications will be effective immunogens in vaccines.

Peptide vaccine design considerations are discussed in Liu et al., Cell Systems 11, Issue 2, p. 131-146 (Liu et al., 2020) and (Liu et al., 2020b) and U.S. Patent No. 11,058. , 751 and US Pat. No. 11,161,892. These documents are incorporated herein by reference in their entirety.

A particular target peptide may not bind with high affinity to a wide range of HLA molecules. To increase the binding of target peptides to HLA molecules, their amino acid composition can be altered to change one or more anchor residues or other residues. In some embodiments, the amino acid composition of the target peptide can be altered to change one or more residues in order to increase the immunogenicity of the target peptide when presented by an HLA molecule. . Anchor residues are amino acids that interact with HLA molecules and have the greatest effect on the peptide's affinity for HLA molecules. Peptides in which one or more amino acid residues have been changed are called heteroclitic peptides. In some embodiments, heteroclitic peptides include target peptides with residue modifications at anchor positions. In some embodiments, heteroclitic peptides include target peptides with residue modifications at non-anchor positions. In some embodiments, heteroclitic peptides include target peptides with residue modifications that include unnatural amino acids and/or amino acid derivatives. Modifications to create heteroclitic peptides can improve the binding of the peptide to both MHC class I and MHC class II molecules, and the required modifications are both peptide- and MHC class-specific. It can be. Peptide anchor residues face the MHC molecular groove and are therefore less visible to T cell receptors than other peptide residues. Accordingly, heteroclitic peptides with anchor residue modifications have been observed to induce T cell responses in which stimulated T cells also respond to unmodified peptides. It has been observed that the use of heteroclitic peptides in vaccines can improve vaccine efficacy (Zirlik et al., 2006). In some embodiments, the immunogenicity of the heteroclitic peptide is determined experimentally, as is known in the art (Houghton et al., 2007), and the corresponding base (also known as seed) of the heteroclitic peptide is determined experimentally. determine the ability to activate T cells that also recognize peptides (called peptides). In some embodiments, such assays of immunogenicity and cross-reactivity of heteroclitic peptides are performed when the heteroclitic peptide is presented by a particular HLA allele.

Peptide Vaccines Inducing Immunity Against One or More Targets In some embodiments, methods are provided for formulating peptide vaccines using a single vaccine design against one or more targets. In some embodiments, the single target is a foreign protein with a particular mutation (eg, KRAS G12D). In some embodiments, the single target is a self protein (eg, a protein overexpressed in tumor cells, such as a cancer/testis antigen). In some embodiments, the single target is a pathogen protein (eg, a protein included in the viral proteome). In some embodiments, multiple targets can be used (eg, both KRAS G12D and KRAS, or exogenous peptides derived from BCL-ABL transcripts b2a2 and b3a2).

In some embodiments, the method comprises extracting peptides from all target proteome sequences to construct a candidate set, as described in Liu et al. (2020).

FIGS. 1 and 2 show flowcharts of exemplary vaccine design methods that can be used for MHC class I or MHC class II vaccine design. The candidate peptide set (see Figures 1 and 2) consists of target peptides extracted by windowing the input protein sequence. In some embodiments, the extracted target peptide is about 8 to about 10 amino acids long [eg, for MHC class I binding (Rist et al., 2013)]. In some embodiments, the extracted target peptide presented by the MHC class I molecule is longer than 10 amino acid residues, such as 11 residues (Trolle et al., 2016). In some embodiments, the extracted target peptide is about 13 to about 25 in length [eg, for class II binding (Chicz et al., 1992)]. In some embodiments, sliding windows of various size ranges described herein are used throughout the proteome. In some embodiments, other target peptide lengths can be used for MHC class I and class II sliding windows. In some embodiments, computational prediction of proteasomal cleavage is used to filter or select peptides in the candidate set. One computational method for predicting proteasomal cleavage is described in Nielsen et al. (2005). In some embodiments, peptide mutation rate, glycosylation, cleavage site, or other criteria can be used to filter peptides, as described in Liu et al. (2020). In some embodiments, peptides can be filtered based on evolutionary sequence diversity above a predetermined threshold. Evolutionary sequence diversity can be calculated with respect to other species, other pathogens, other pathogen strains, or other related organisms. In some embodiments, the first set of peptides is a candidate set.

In some embodiments, to design a vaccine against a foreign peptide produced by an aberrant gene fusion, a target peptide is extracted from the gene fusion product for inclusion in a candidate peptide set, and the extracted target peptide is Each contains a breakpoint between two genes. For example, in some embodiments to design a BCR-ABL vaccine, BCR-ABL b3a2 (e14a2) and b2a2 (e13a2) chimeric protein sequences were obtained from NCBI (GenBank ID CAA10376.1 and CAA10377.1, respectively). ). For each isoform, sliding windows of length 8-11 (MHC class I) and 13-25 (MHC class II) were extracted around the BCR-ABL breakpoint. The sliding window can be extracted using the procedures described herein in "MHC Class I Vaccine Design Procedure" and "MHC Class II Vaccine Design Procedure", where P _{1. ．． ．． n} contains the chimeric protein sequence, t specifies the location of the breakpoint in the chimeric protein sequence, and s=true. In the case of b3a2, the BCR-ABL junction breaks the triplet codon and a new lysine (“K”) is generated at the breakpoint (Clark et al., 2001). In the case of b2a2, junctional codon disruption causes an Asp to Glu change, but this novel amino acid is also present in the normal a1a2 junction (Clark et al., 2001). Therefore, for b3a2, we retained all obtained windows that spanned the 'K' breakpoint. For b2a2, only windows containing the sequence "KEE" were retained and windows found only in BCR or ABL protein sequences were excluded. This procedure can be applied to identify breakpoints between fusion genes and generate vaccines against other unusual gene fusions by using the window strategy described herein.

As shown in Figures 1-2, in some embodiments, the next step of the method is to remove all It involves scoring the target peptides in the candidate set for peptide-HLA binding to the considered HLA allele. In some embodiments, the first set of peptides is a candidate set after scoring the target peptides. Scoring can be accomplished for human HLA molecules, mouse H-2 molecules, porcine SLA molecules, or MHC molecules of any species for which predictive algorithms can be used or developed. Therefore, vaccines targeting non-human species can be designed using this method. Scoring metrics can include nanomolar affinity of the target peptide for the HLA allele, elution ligand, presentation, and other scores that can be expressed as percentile rankings or other metrics. The candidate set can be further filtered to exclude peptides for which the predicted binding core does not contain the particular pathogenic or neoantigen target residue of interest, or for which the predicted binding core contains the target residue at the anchor position. The candidate set may also be filtered for target peptides of a particular length, eg, MHC class I length 9. In some embodiments, scoring of target peptides is accomplished by experimental data or a combination of experimental data and computational prediction methods. If a computational model is not available to make peptide-HLA binding predictions for a particular (peptide, HLA) pair, the binding value for such a pair is the average of the immunogenicity values obtained for the supported pairs. value, median, minimum, or maximum value, may be defined by a fixed value (such as an indicator of nonbinding), or predict the most similar (peptide, HLA) pair available in a scoring model. Other techniques may be used for inference, including functions.

In some embodiments, foreign peptides created by aberrant gene fusions are not excluded if they contain fusion breakpoints that fall into MHC class I or class II anchor positions of HLA alleles. For example, in the design of an MHC class I BCL-ABL vaccine, if the BCR-ABL breakpoint falls within the peptide anchor position, no window is excluded. For MHC class II, the scoring model requires that the breakpoint be within the predicted 9-mer binding core (at any position) for a given HLA, and scores peptide-HLA pairs that do not meet this criterion. is excluded. In some embodiments, for MHC class I BCR-ABL vaccine design, the window is excluded if the BCR-ABL breakpoint falls within the peptide anchor position. In some embodiments, for MHC class II BCR-ABL vaccine design, if the BCR-ABL breakpoint is within the anchor position of the predicted 9-mer binding core of a given peptide-HLA pair; Peptide-HLA scores are excluded. In some embodiments, for MHC class II vaccine design, gene fusion breakpoints can be located anywhere inside or outside the predicted 9-mer binding core of a given peptide-HLA pair. .

In some embodiments, a base set (also referred to herein as a seed set) is constructed by selecting peptides from a scoring candidate set using individual peptide-HLA binding or immunogenicity criteria. (e.g., the first set of peptides) (Figure 1). In some embodiments, a given peptide has more than one peptide-HLA score, so selection is based on the best affinity or the most immunogenicity (e.g., for a given HLA allele, the most may be based on a peptide-HLA binding score or a peptide-HLA immunogenicity metric that binds strongly or is predicted to most potently activate T cells). The criteria used to score peptide-HLA binding during the scoring procedure can correspond to various goals during the base set selection stage and during the vaccine design stage. For example, a target peptide with a peptide-HLA binding affinity of 500 nM may be presented by an affected individual, but less frequently than a target peptide with a peptide-HLA binding affinity of 50 nM. . During the combinatorial design phase of a vaccine, more constrained affinity criteria, such as 50 nM, can be used to increase the probability that the vaccine peptide will be found and presented by HLA molecules ( For example, in Figures 1 and 2, the third peptide set, when selecting a vaccine against the target). In some embodiments, a relatively unrestrictive threshold for peptide-HLA immunogenicity or peptide-HLA binding (e.g., less than about 1000 nM or less than about 500 nM) for a particular HLA allele score is set for a candidate peptide- used as the first threshold for filtering HLA scores (first peptide scoring and score filtering step in Figures 1 and 2), and a relatively more restrictive second threshold (e.g., less than about 50 nM). , used for filtering the expanded set peptide-HLA scores (second peptide filtering and scoring step in Figures 1 and 2). In some embodiments, the particular peptide-HLA scores of modified peptides of a given HLA are not used in vaccine design if their unmodified counterpart peptides do not meet a first less restrictive threshold. This filtering of peptide-HLA scores allows peptides to be recognized by the vaccine-expanded T-cell clonotype, since peptides that are not sufficiently immunogenic for vaccine inclusion may still be antigenic (meeting the first threshold). Based on the observation that there is a possibility that A peptide is antigenic if it is recognized by a T cell receptor and results in a response such as CD8+ T cell cytotoxicity or CD4+ cell activation. Derivatives of antigenic peptides are strongly immunogenic and are included in vaccines, thus activating and expanding T cells that recognize the antigenic peptide. Expansion of T cells that recognize unmodified antigenic peptides can provide an immune response that contributes to disease control. In some embodiments, peptides are scored for potential inclusion in a third set of peptides (in Figures 1 and 2, vaccines against targets) that have a peptide-HLA binding affinity of less than about 500 nM. In some embodiments, peptides with a peptide-HLA binding affinity of less than about 1000 nM for at least one HLA allele are selected for the base set. Alternatively, predictions of peptide-HLA immunogenicity may be used to qualify target peptides for base set inclusion. In some embodiments, experimental observation of the immunogenicity of peptides in the context of their presentation by HLA alleles, or experimental observation of binding of peptides to HLA alleles, is used to Peptides can be scored for binding or peptide-HLA immunogenicity.

In some embodiments, experimental observations of peptide presentation by particular HLA alleles in tumor cells can be used to score peptides for peptide-HLA binding or peptide-HLA immunogenicity. In some embodiments, experimental observation of peptide tumor cell presentation by a particular HLA allele is used to determine peptide-HLA binding or peptide-HLA immunogenicity for that HLA allele. can be scored. In some embodiments, experimental observations of peptide tumor cell presentation can be used to score peptides for peptide-HLA binding or peptide-HLA immunogenicity, and HLA for a particular observed peptide. Alleles are selected from HLA alleles present in the tumor that meet predicted peptide-HLA binding or immunogenicity thresholds. In some embodiments, peptide presentation by tumor cells is determined experimentally using mass spectrometry, as described in Bear et al. (2021) or Wang et al. (2019), and The data is used to score peptide-HLA binding or peptide-HLA immunogenicity. In some embodiments, presentation of the peptide by tumor cells is determined experimentally using mass spectrometry, and such experimental data is used to base one or more HLA alleles for the vaccine. Qualify the inclusion of set (seed set) peptides. In some embodiments, the presentation of a peptide by tumor cells is determined experimentally using mass spectrometry, and such experimental data is used to indicate that the peptide is presented by an HLA allele. If not observed in the analysis, exclude the peptide's peptide-HLA binding score or peptide-HLA immunogenicity score. In some embodiments, the presentation of a peptide by tumor cells in an individual is determined experimentally using mass spectrometry, and such experimental data is used to determine the presentation of a peptide by tumor cells in that individual for one or more HLA alleles. Qualify the inclusion of a base set (seed set) of peptides. In some embodiments, presentation of the peptide by tumor cells in the individual is determined experimentally using mass spectrometry, and such experimental data is used to indicate that the peptide is presented by HLA alleles. If not observed by mass spectrometry, exclude the peptide-HLA binding score or peptide-HLA immunogenicity score for that peptide. In some embodiments, computational prediction of immunogenicity of a peptide in the context of HLA allele presentation, such as the methods of Ogishi et al. (2019) or Bulik-Sullivan et al. (2019), is scored. It can be used for.

In some embodiments, the peptide-HLA score or peptide-HLA immunogenicity score of the first peptide in a given base set (seed set) of HLA alleles is the same as the wild type corresponding to the first peptide. A peptide (e.g., an unmutated native form of the peptide or a peptide of a corresponding species within a defined sequence edit distance) has a Peptide-HLA score or a Peptide-HLA immunogenicity score of the same HLA allele within a defined threshold. If it has, it will be excluded and will not be considered in vaccine design. The threshold may be based on the difference between the scores of the first peptide and the wild type peptide, the ratio of the scores of the first peptide and the wild type peptide, the score of the wild type peptide, or other metrics. The prescribed threshold value may be either greater than or less than the specified value. In some embodiments, a threshold is defined such that the wild-type peptide is not expected to be presented. In some embodiments, if the peptide-HLA score or peptide-HLA immunogenicity score of the first peptide is eliminated during vaccine design, its derivatives against the same HLA allele (e.g., heteroclitic peptide derivatives) All peptide-HLA scores or peptide-HLA immunogenicity scores are also excluded and are not taken into account in vaccine design.

In some embodiments, the method uses population HLA haplotype frequencies to run the OptiVax-Robust algorithm described in Liu et al. (2020) on the scored candidate set to It further includes constructing a basic set of peptides (also referred to herein as a seed set) (Figure 2). In some embodiments, HLA diplotype frequencies may be provided to OptiVax. OptiVax-Robust includes an algorithm that eliminates peptide redundancy resulting from a sliding window approach using various window sizes, but also uses other redundancy elimination means to determine the minimum edit distance between target peptides in a candidate set. constraints can be enforced. The size of the seed set is determined by the point of diminishing returns of population coverage as a function of the number of target peptides in the seed set. Other criteria can also be used, including minimum number of vaccine target peptides, maximum number of vaccine target peptides, and desired predicted population coverage. In some embodiments, the predetermined population coverage is less than about 0.4, about 0.4-0.5, about 0.5-0.6, or about 0. 6 to 0.7, about 0.7 to 0.8, about 0.8 to 0.9, or greater than about 0.9. Another possible criterion is the minimum expected number of peptide-HLA binding hits in each individual. In an alternative embodiment, the method further includes executing the OptiVax-Unlinked algorithm described in Liu et al. (2020) instead of OptiVax-Robust.

The OptiVax-Robust method uses binary predictions of peptide-HLA immunogenicity, and such binary predictions can be generated as described in Liu et al. (2020b). The OptiVax-Unlinked method uses the probability that a target peptide binds to an HLA allele and can be generated as described in Liu et al. (2020). In some embodiments, OptiVax-Unlinked and EvalVax-Unlinked are used with probability of peptide-HLA immunogenicity. Either method can be used for the purposes described herein, so the term "OptiVax" refers to either the Robust or Unlinked method. In some embodiments, the probability of peptide-HLA immunogenicity observed in experimental assays can be used as the probability of peptide-HLA binding in EvalVax-Unlinked and OptiVax-Unlinked. In some embodiments, the population HLA haplotypes or HLA allele frequencies provided to OptiVax for vaccine design are representative of the global population. In an alternative embodiment, the population HLA haplotypes or HLA allele frequencies provided to OptiVax for vaccine design are specific to a geographic region. In an alternative embodiment, the HLA haplotypes or HLA allele frequencies of the population provided to OptiVax for vaccine design are ancestry-specific. In an alternative embodiment, the population HLA haplotypes or HLA allele frequencies provided to OptiVax for vaccine design are race-specific. In an alternative embodiment, the population HLA haplotypes or HLA allele frequencies provided to OptiVax for vaccine design include genetic indicators of risk, age, chemical exposure, alcohol intake, chronic inflammation, diet, It is specific to individuals with risk factors such as hormones, immunosuppression, infectious agents, obesity, radiation, sunlight, or smoking. In an alternative embodiment, the population HLA haplotypes or HLA allele frequencies provided to OptiVax for vaccine design are specific to individuals with certain HLA alleles. In an alternative embodiment, the HLA diplotype provided to OptiVax for vaccine design represents a single individual and is used in the design of a personalized vaccine.

In some embodiments, the base (or seed) set of target peptides (e.g., the first set of peptides) resulting from the application of OptiVax to the candidate set of target peptides is an unmodified target peptide that is a possible small vaccine design. (seed set in Figure 2). A base peptide is a target peptide included in a base or seed peptide set (eg, a first peptide set). In some embodiments, the seed set (eg, the first peptide set) is based on filtering candidate peptide scores by predicted or observed affinity or immunogenicity for HLA molecules (seed set of FIG. 1). However, some embodiments include modifications of the seed (or base) set to maximize the presentation of the target peptide on a wide range of HLA haplotypes. In some embodiments, experimental assays can be used to ensure that the modified seed (or base) peptide activates T cells that also recognize the base/seed peptide.

For a given target peptide, optimal anchor residue selection may depend on the HLA allele that binds and presents the target peptide and the class of HLA allele (MHC class I or class II). The seed peptide set (eg, the first peptide set) can become an expanded set by including anchor residue modified peptides of either MHC class I or II peptides (FIGS. 1-2). Therefore, one aspect of vaccine design is that heteroclitic peptides derived from the same target peptide for vaccine inclusion, in light of the fact that different heteroclitic peptides will have different and potentially overlapping population coverage. Consider how to select a limited set of critical peptides.

In some embodiments, all possible anchor modifications of each base set of target peptides are considered. Typically, there are two anchor residues in the peptide to which MHC class I molecules bind, typically at positions 2 and 9 for 9-mer peptides. In some embodiments, 8-mer, 10-mer, and 11-mer anchors are found at positions 2 and n, where n is the last position (positions 8, 10, and 11, respectively). ). For MHC class I molecules, the last position n is referred to herein as the carboxyl-terminal "C" position. In some embodiments, 20 possible amino acids at each anchor position are tried to select the best heteroclitic peptide. Thus, for MHC class I binding, 400 (ie 20 amino acids every two positions = 20 ² )-1 heteroclitic peptides are generated for each basic target peptide. Typically, there are four anchor residues in the peptide to which MHC class II molecules bind, typically at positions 1, 4, 6, and 9 of the 9-mer binding core. Thus, for MHC class II binding, 160,000 (ie, 20 amino acids at every 4 positions=20 ⁴ )−1 heteroclitic peptides are generated for each basic target peptide. In some embodiments, more than two (MHC class I) or more than four (MHC class II) locations are considered as anchors. Other methods, including Bayesian optimization, can be used to select optimal anchor residues and generate heteroclitic peptides from each seed (or base) set peptide. Other methods for selecting optimal anchor residues are presented in "Machine learning optimization of peptides for presentation by class II MHCs" by Dai et al. (2020). This document is incorporated herein in its entirety. In some embodiments, the anchor positions are determined by the HLA allele presenting the peptide, and thus the set of heteroclitic peptides includes all possible anchor modifications for each set of HLA-specific anchor positions. .

In some embodiments, for all of the target peptides in the base/seed set, new peptide sequences are created with all possible anchor residue modifications (e.g., MHC class I or class II), and all such modifications are A new heteroclitic basic set (extended set in FIGS. 1-2) is introduced, which includes: In some embodiments, if one or more of the anchor residue positions of the peptide contain a substitution mutation that distinguishes the peptide from its self-peptide, the anchor residue modification of the peptide is added to the heteroclitic base set. is not included. In some embodiments, anchor residue modifications of the base/seed peptide include only those peptide positions in the heteroclitic base set that do not contain substitution mutations that distinguish the base/seed peptide from its self-peptide. In some embodiments, an anchor residue modification of a peptide is not included in the heteroclitic base set if one or more of the mutations of the peptide do not occur between its adjacent pairs of anchor residues. do not have. In some embodiments, for all of the peptides in the base/seed set, a new peptide sequence with an anchor residue modification (e.g., MHC class I or class II) is created, and a new heteroclonal sequence containing the selected modification is created. A basic set of ticks (in FIGS. 1-2, an extended set) is provided. In some embodiments, the anchor residue positions used to modify the peptide are selected from the anchor residue positions determined by the HLA alleles considered during vaccine evaluation. In some embodiments, the heteroclitic base set (in Figures 1-2, the expanded set) also includes the original seed (or base) set (in Figures 1-2, the seed peptide set). In some embodiments, the heteroclitic base set includes amino acid substitutions at non-anchor residues. In some embodiments, modifications of basic peptide residues are accomplished to alter binding to T cell receptors and improve therapy efficacy (Candia et al., 2016). In some embodiments, the heteroclitic base set includes amino acid substitutions for non-natural amino acid analogs. The heteroclitic base set is scored for HLA affinity, peptide-HLA immunogenicity, or other metrics described herein (separate rounds of peptides shown in Figures 1-2). scoring and score filtering). In some embodiments, for pairs of heteroclitic peptides and HLA alleles, the scoring predictions are further updated to ensure that the heteroclitic peptide has a peptide-HLA binding score or a specified peptide-HLA immunogenicity metric. Pairs whose seed (or base) peptides are derived from are not predicted to be presented by HLA alleles can be excluded at a specified threshold. In some embodiments, the peptide-HLA score is also filtered so that the predicted binding core of the heteroclitic peptide presented by a particular HLA allele is determined by the corresponding seed (or base) set of that HLA allele. It can be ensured that the binding core and position of the target peptide are precisely aligned. In some embodiments, the scoring predictions are filtered for HLA alleles such that heteroclitic peptides considered for that HLA allele are modified only at anchor positions determined by that HLA allele. guaranteed. Scoring produces metrics of peptide HLA immunogenicity for peptides and HLA alleles, where the metric can be binary, probability of immunogenicity, or other metrics of immunogenicity such as peptide-HLA affinity or percent rank. may be based on computational predictions, experimental observations, or a combination of both computational predictions and experimental observations. In some embodiments, the probability of peptide-HLA immunogenicity is used by OptiVax-Unlinked. In some embodiments, heteroclitic peptides are tested in experimental assays such as MIRA (Klinger et al., 2015) or ELISPOT to determine their peptide-HLA immunogenicity metrics for specific HLA alleles. include. In some embodiments, MIRA data for heteroclitic peptides can be incorporated into a model of peptide-HLA immunogenicity using the method of Liu et al. (2020b). In some embodiments, the peptide-HLA immunogenicity metrics of a heteroclitic peptide are determined experimentally and the ability to activate T cells that also recognize the corresponding seed (or base) peptide of the heteroclitic peptide. is performed as known in the art to qualify heteroclitic peptides for vaccine inclusion (Houghton et al., 2007). In some embodiments, such assays of immunogenicity and cross-reactivity of heteroclitic peptides are performed when the heteroclitic peptide is presented by a particular HLA allele.

In some embodiments, experimental observations regarding presentation of heteroclitic peptides by specific HLA alleles in cells can be used to score peptides for peptide-HLA binding or peptide-HLA immunogenicity. . In some embodiments, presentation of heteroclitic peptides by cells is determined experimentally using mass spectrometry, as described in Bear et al. (2021) or Wang et al. (2019). , and use such data to score for peptide-HLA binding or peptide-HLA immunogenicity. In some embodiments, the presentation of heteroclitic peptides by cells is determined experimentally using mass spectrometry, and such experimental data is used to guide the inclusion of heteroclitic peptides for inclusion in a vaccine. Certify. In some embodiments, presentation of the peptide by tumor cells is determined experimentally using mass spectrometry, and such experimental data is used to indicate that the peptide is presented by HLA alleles using mass spectrometry. The peptide-HLA binding score or the peptide-HLA immunogenicity score of a peptide is excluded if it is not observed. In some embodiments, the presentation of heteroclitic peptides by cells having HLA alleles found in an individual is determined experimentally using mass spectrometry, and such experimental data are used to Qualifying the inclusion of heteroclitic peptides for inclusion in vaccines for In some embodiments, presentation of the peptide by tumor cells in the individual is determined experimentally using mass spectrometry, and such experimental data is used to indicate that the peptide is presented by HLA alleles. Exclude the peptide-HLA binding score or peptide-HLA immunogenicity score for that peptide if it is not observed by mass spectrometry. In some embodiments, computational prediction of immunogenicity of heteroclitic peptides in the context of HLA allele presentation, such as the methods of Ogishi et al. (2019) or Bulik-Sullivan et al. (2019), , which can be used for scoring.

In some embodiments, a peptide in the heteroclitic base set is one of the base/seed peptides from which it was derived that (1) one of its anchor positions relative to the HLA allele distinguishes the base/seed peptide from the self peptide; (2) if the peptide-HLA binding or peptide-HLA immunogenicity of the self-peptide is stronger than a certain threshold of self-peptide binding or immunogenicity; removed. This eliminates peptides in the heteroclitic base set that may cross-react with the self-peptide as a result of sharing TCR-facing residues with the self-peptide. In some embodiments, the threshold for self-peptide binding is approximately 500 nM to 1000 nM.

In some embodiments, redundant peptides in the heteroclitic base set are removed. In some embodiments, the redundant peptide is a peptide that is less immunogenic than a second heteroclitic peptide in the base heteroclitic set for all scored HLA-HLA immunogenicity scores. or a first heteroclitic peptide with a peptide-HLA binding score, and the first and second heteroclitic peptides are both derived from the same base (or seed) peptide. In some embodiments, peptide redundancy is determined solely by comparing the peptide-HLA immunogenicity scores or peptide-HLA binding scores of the HLA alleles, and the peptide-HLA immunogenicity scores of both peptides for the HLA alleles. The sex score or peptide-HLA binding score is more immunogenic than a predetermined threshold (eg, 50 nM for binding). In some embodiments, the redundant peptide is an average peptide that is less immunogenic than the average peptide-HLA immunogenicity score or peptide-HLA binding score of the second heteroclitic peptide in the base heteroclitic set. a first heteroclitic peptide with an HLA immunogenicity score or a peptide-HLA binding score, where the first and second heteroclitic are both derived from the same base (or seed) peptide and have an HLA allele An average score is calculated where the peptide-HLA immunogenicity score or peptide-HLA binding score of both peptides for the HLA allele is more immunogenic than a predetermined threshold (eg, 50 nM for binding). In some embodiments, the redundant peptide is a weighted peptide that is less immunogenic than the HLA immunogenicity score or peptide-HLA binding score of a second heteroclitic peptide in the base heteroclitic set. a first heteroclitic peptide with an HLA immunogenicity score or a peptide-HLA binding score, the first and second heteroclitic are both derived from the same base (or seed) peptide, and the weights are: A weighted score for the HLA allele is calculated, determined by the frequency of the HLA allele in the human population, and the peptide-HLA immunogenicity score or peptide-HLA binding score of both peptides for the HLA allele is determined by a predetermined threshold (e.g. In the case of binding, it is more immunogenic than 50 nM).

In some embodiments, the next step is to score the heteroclitic base set (second set of peptides) and filter the resulting scores to generating a second set of peptides by comparing the peptide-HLA immunogenicity score or peptide-HLA binding score of the peptide-HLA to a threshold value. In some embodiments, an affinity criterion of about 50 nM is used to increase the probability that the vaccine peptide will be found and presented by HLA molecules. In some embodiments, the affinity criterion is more constrained than 50 nM (ie, <50 nM). In some embodiments, the affinity criterion is more constrained than 500 nM (ie, <500 nM). In some embodiments, an individual peptide-HLA binding score or immunogenicity metric is determined so that peptides can be retained as long as they meet criteria for at least one HLA allele, and peptides that meet the criteria Only the score is considered for vaccine design.

In some embodiments, the next step includes inputting the second set of peptides into OptiVax to select a small set of vaccine peptides that maximize predicted vaccine performance (vaccine performance optimization; Figure 1 ~Figure 2). In some embodiments, predicted vaccine performance is a function of predicted peptide-HLA binding affinity (e.g., across all peptide-HLA combinations of a given peptide set or across HLA alleles in a population or individual). is a function of the distribution of peptide-HLA binding affinities, weighted by occurrence). In some embodiments, the predicted vaccine performance is the predicted population coverage of the vaccine. In some embodiments, the predicted vaccine performance is the expected number of peptide-HLA hits produced by the vaccine in a population or individual. In some embodiments, predicted vaccine performance is the minimum predicted peptide-HLA hit number produced by the vaccine (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more). Requires. In some embodiments, predicted vaccine performance is a function of population coverage and the desired number of predicted peptide-HLA hits generated by the vaccine. In some embodiments, predicted vaccine performance is a metric that describes the overall immunogenicity properties of a vaccine, such that all of the peptides in the vaccine are present on two or more HLA alleles (e.g., three Peptide-HLA immunogenicity against one or more HLA alleles) is scored. In some embodiments, predicted vaccine performance exceeds the maximum number of peptide-HLA hits (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more). Excluding immunogenic contribution by HLA alleles. In some embodiments, predicted vaccine performance is based on individual HLA hits that exceed the maximum number of peptide-HLA hits (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more). Excluding the epidemiogenic contribution of diplotypes. In some embodiments, the predicted vaccine performance is the fraction of alleles covered, which is the predicted peptide produced by the vaccine - the minimum number of peptides with HLA immunogenicity (e.g. 1, 2, 3, 4, 5, 6, 7, 8, or more). In some embodiments, predicted vaccine performance is determined by the predicted peptides produced by the vaccine - the minimum number of peptides with HLA immunogenicity (e.g., 1, 2, 3, 4, 5, 6, 7, 8, or more) is the expected fraction of HLA alleles in a single individual.

In some embodiments, vaccines are derived from a heteroclitic base set (also referred to as an expanded set, as shown in Figures 1-2) with progressively less stringent predicted peptide immunogenicity or presentation. It is designed by iteratively selecting peptides based on the following criteria. In some embodiments, a peptide is retained if at least one of its peptide-HLA scores is not excluded by the threshold used. In some embodiments, OptiVax is first used to determine specific peptide qualification criteria (e.g., the seed HLA-peptide score from the candidate set must bind at least one MHC molecule at 500 nM or more). The peptide-HLA score from the expanded set (must bind at least one MHC molecule at 50 nM or stronger) is used to design a vaccine with the desired vaccine performance. The vaccine resulting from this application of OptiVax is then tested using less stringent criteria (e.g., the seed peptide from the candidate set - HLA score is at least 1000 nM or more potent with at least one MHC molecule). The peptide-HLA score from the expanded set must bind to at least one MHC molecule at 100 nM or more) to be used as the basis for vaccine augmentation to obtain the desired vaccine. further improve performance. Methods for vaccine augmentation are described in Liu et al. (2020b), which is incorporated herein by reference in its entirety. In some embodiments, multiple rounds of vaccine augmentation can be used. In some embodiments, the final augmented vaccine is the selected vaccine.

In some embodiments, selection of peptide sets that meet the desired predicted vaccine performance can be accomplished by computational algorithms other than OptiVax. In some embodiments, integer linear programming or mixed integer linear programming is used instead of OptiVax to select the peptide set. An example of integer programming for peptide set selection is described in Toussaint et al. (2008). This document is incorporated herein by reference in its entirety. An exemplary solution for mixed integer linear programming is Python-MIP, which can be used in conjunction with Toussaint et al. (2008). A second example of a method for vaccine peptide selection is described in “Maximum n-times Coverage for Vaccine Design” by Liu et al. (2021), which is incorporated herein by reference in its entirety. It will be done.

Predicted vaccine performance refers to metrics. Predicted vaccine performance can be expressed as a single number, multiple numbers, any number of non-numbers, and combinations thereof. The value or values may be expressed in any mathematical or symbolic terms and on any scale (eg, nominal, ordinal, interval, or proportional scale).

The seed (or base) peptide and all modified peptides derived from that seed (or base) peptide constitute a single peptide family. In some embodiments, the maximum number of peptides that are from the same peptide family (e.g., 1, 2, 3, 4, 5 , 6, 7, 8, or more) are given a computational immunogenicity credit for that HLA allele. This limitation on the immunogenicity of a peptide family limits the credit generated by multiple modified forms of the same basic peptide. In some embodiments, the methods described herein include performing OptiVax with an EvalVax objective function that corresponds to a desired metric of predicted vaccine performance. In some embodiments, population coverage refers to the proportion of a subject population that presents one or more immunogenic peptides that activate T cells in response to a seed (or base) target peptide. Population coverage metrics are calculated using HLA haplotype frequencies in a given population, such as a representative human population. In some embodiments, population coverage metrics are calculated using marginal HLA frequencies in the population. Maximizing population coverage is based on the proportion of HLA haplotypes in a given population (e.g., a representative human population), with at least a minimum number (e.g., 1, 2, 3, 4, 5, 6, 7, 8 A set of peptides (either a basic peptide set, a modified peptide set, or a combination of basic and modified peptides) that collectively result in the largest fraction of the population exhibiting immunogenic peptide-HLA binding of ; for example, a first set of peptides, a second set of peptides, or a third set of peptides). In some embodiments, this process involves OptiVax selection of heteroclitic peptides (such as those described in this disclosure) that activate T cells responsive to the corresponding seed (or base) peptide and the heteroclitic base peptide. and improving population coverage. In some embodiments, the final vaccine design always includes a seed (or base) target peptide. In some embodiments, a peptide is considered a candidate for vaccine design only if it is observed to be immunogenic in clinical data, animal models, or tissue culture models (e.g., first, second , and/or included in the third peptide set).

Although heteroclitic peptides are used in this disclosure as an exemplary embodiment, any modified peptide can be used in place of a heteroclitic peptide. Modified peptides are peptides that have one or more amino acid substitutions of the target base/seed peptide. Amino acid substitutions may be located at anchor positions or at any other non-anchor position.

In some embodiments, a candidate vaccine peptide (e.g., base peptide or modified peptide) is excluded from vaccine inclusion if it activates T cells that recognize the self-peptide (e.g., this 2). In some embodiments, a candidate vaccine peptide (e.g., a base peptide or a modified peptide) has an outward self-peptide residue whose outward amino acids are presented by the same HLA allele upon binding of the HLA alleles. are computationally excluded from vaccine inclusion if they are similar to a group, in which case similarity may be defined by identity or by similarity, such as the BLOSUM matrix (BLOSUM matrices are known in the art). It may be defined by a metric. Testing of vaccine peptides for their ability to activate T cells that recognize self-peptides can be performed experimentally by vaccinating animal models followed by ELISPOT or other immunogenicity assays, or by using human tissue protocols. can be achieved. In either case, a model with HLA alleles presenting the vaccine peptide is used. In some embodiments, primary human blood mononuclear cells (PBMCs) are stimulated with vaccine peptides to allow T cell proliferation and then T cell activation by self peptides, as described by Tapia-Calle et al. (2019). or by other methods known in the art. In some embodiments, if a T cell is activated by a self-peptide, that vaccine peptide is excluded from vaccine inclusion. In some embodiments, computational prediction of a peptide's ability to activate T cells that also recognize self-peptides can be used. Such predictions may be based on modeling the outward residues of the peptide-HLA complex and their interactions with other peptide residues. In some embodiments, the candidate vaccine peptide (e.g., base peptide or modified peptide) has a structural component of the peptide-MHC complex of the candidate peptide (e.g., base peptide or modified peptide) and the peptide-MHC complex of the self-peptide. If it is predicted to activate T cells that also recognize self-peptides based on similarity, they may be excluded from vaccine inclusion or tested experimentally for cross-reactivity. One method for predicting peptide-MHC structures is described in Park et al. (2013).

In some embodiments, a peptide-HLA binding score or peptide-HLA immunogenicity metric for a candidate heteroclitic vaccine peptide (e.g., a modified peptide) and an HLA allele determines whether the candidate heteroclitic vaccine peptide is In the case of an HLA allele, if it does not activate T cells that recognize its corresponding base/seed target peptide, it is excluded from consideration during vaccine design (second round of peptide scoring and score filtering, Figures 1- Figure 2). In some embodiments, a heteroclitic vaccine peptide (e.g., a modified peptide) is a T that recognizes its corresponding base/seed target peptide for a given HLA allele. If the cells do not activate, they are excluded from vaccine design (second round of peptide scoring and score filtering, Figures 1-2). Testing of a candidate heteroclitic peptide (e.g., a modified peptide) for its ability to activate T cells that recognize its corresponding seed (or base) target peptide with respect to the same HLA allele can be performed by vaccinating an animal model and subsequently This can be accomplished experimentally by performing ELISPOT or other immunogenicity assays or using human tissue protocols. In either case, a model with HLA alleles presenting heteroclitic peptides is used. In some embodiments, human PBMCs are stimulated with a heteroclitic peptide to allow T cell proliferation, followed by T cell activation with a seed (or base) target peptide, as described by Tapia-Calle et al. (2019). or using other methods known in the art. In some embodiments, computational prediction of the ability of a heteroclitic peptide to activate T cells that also recognize the corresponding seed (or base) target peptide can be used. Such predictions may be based on modeling the outward residues of the peptide-HLA complex and their interactions with other peptide residues. In some embodiments, the structural similarity of the peptide-HLA complex of a heteroclitic peptide and the corresponding peptide-HLA complex of a seed (or base) target is used to target heteroclitic peptides for vaccine inclusion. Experimental immunogenicity testing is required prior to qualifying the peptide or including it in a vaccine.

TCR Interface Divergence (TCRID) is the least squares difference between the 3D position of a TCR opposing residue in a first peptide and the corresponding residue position in a second peptide for a particular HLA allele. It is the mean square deviation. In some embodiments, other metrics are used for TCRID instead of least mean square deviation. In some embodiments, other metrics are used for TCRID, including position deviation of non-TCR opposing residues and MHC residues from particular HLA alleles. In some embodiments, TCRID is used to predict whether two peptides will activate the same T cell clonotype when presented by a given HLA allele. In some embodiments, along with the crystal structure of the HLA molecule, the FlexPepDock (London et al., 2011, herein incorporated by reference in its entirety) or DINC (Antunes et al., 2018, (which is incorporated herein by reference in its entirety) can be used to calculate the TCRID metric of a pair of peptides considering a given HLA molecule. In some embodiments, TCRID (1) determines the 3D peptide-HLA structure of two different peptides bound by a particular HLA allele; (2) aligns the HLA alpha helices of the peptide-HLA structure. and (3) by calculating the least mean square deviation of the differences between TCR opposing residues of the two peptides with respect to an aligned alpha-helical reference frame.

In some embodiments, the second peptide scoring and score filtering step in FIGS. 1 and 2 is an HLA-specific step between the heteroclitic peptide and its corresponding base (or seed) peptide from which it was derived If the TCRID is above the first TCRID threshold, it will exclude the peptide-HLA binding or immunogenicity score of the heteroclitic peptide for the particular HLA allele. In some embodiments, the second peptide scoring and score filtering step in FIGS. 1 and 2 is an HLA-specific step between the heteroclitic peptide and its corresponding unmutated self-peptide from which it was derived. If the TCRID is below the second TCRID threshold, it will exclude all peptide-HLA binding or immunogenicity scores for the heteroclitic peptide. In some embodiments, the first peptide scoring and score filtering step in FIGS. 1 and 2 is such that the HLA-specific TCRID between the peptide and its corresponding unmutated self peptide is equal to or less than a third TCRID threshold. , all peptide-HLA binding or immunogenicity scores for the candidate peptide will be excluded. In some embodiments, either the TCRID threshold is determined by experimentally observing or computationally predicting the cross-reactivity of TCR molecules to peptide-HLA complexes.

Figure 3 (MHC class I) and Figure 4 (MHC class II) were selected with OptiVax-Robust with different numbers of peptides designed for KRAS mutations G12D, G12V, G12R, G12C, and G13D. Figure 3 shows the predicted population coverage of single target specific vaccines. Figures 3-4 show that as the number of peptides in a vaccine increases, its predicted population coverage increases. The population coverage shown in Figures 3-4 is for individuals with the specific mutation that the vaccine was designed to cover. As the peptide count increases, the average number of peptide-HLA hits in each individual of the population will also typically increase.

Figure 5 shows predicted population coverage by vaccine size for MHC class I vaccines for BCL-ABL fusions producing b3a2. Figure 6 shows predicted population coverage by vaccine size for MHC class II vaccines for BCL-ABL fusions producing b3a2. Figure 7 shows predicted population coverage by vaccine size for MHC class I vaccines for BCL-ABL fusions producing b2a2. Figure 8 shows predicted population coverage by vaccine size for MHC class II vaccines for BCL-ABL fusions producing b2a2.

Using OptiVax, vaccines can be designed to maximize the fraction/proportion of the population in which HLA molecules are predicted to bind and present at least p peptides of the vaccine. In some embodiments, this prediction (eg, scoring) includes experimental immunogenicity data to directly predict that the at least p peptides are immunogenic. A numerical value p can be entered into OptiVax and OptiVax can be run multiple times with varying values of p to obtain predicted optimal target peptide sets for various peptide counts p. A larger value of p will increase vaccine redundancy at the cost of more peptides to achieve the desired population coverage. In some embodiments, it may not be possible to achieve a given population coverage given a particular heteroclitic base set. In some embodiments, the number p is a function of the desired size of the vaccine.

Using the methods described herein, separate vaccine formulations can be designed for MHC class I and class II-based immunization.

In some embodiments, this procedure is used to create a vaccine for an individual. In some embodiments, the target peptide present in an individual is determined by sequencing the individual's tumor RNA or DNA and identifying mutations that produce the foreign peptide. One embodiment of this method is described in US Pat. No. 10,738,355, which is incorporated herein in its entirety. In some embodiments, peptide sequencing is used to identify target peptides in an individual. One embodiment of this is described in US Patent Application Publication No. 2011/0257890. In some embodiments, the target peptide used in the individual's vaccine is a self peptide, a foreign peptide, a pathogen peptide, or a sample from which the RNA encoding the self peptide, foreign peptide, or pathogen peptide is derived from the individual. is selected if it is observed within and present at a predetermined level. Targeting peptides in individuals are used to construct the vaccines disclosed herein. For vaccine design, OptiVax is provided with a diplotype containing the individual's HLA type. In an alternative embodiment, an individual's HLA type is separated into a plurality of diplotypes with frequencies that sum to 1, and each diplotype is associated with one or more of the individual's HLA alleles, and other alleles. Contains a statement that the gene location should not be evaluated. The use of multiple diplotypes will cause the OptiVax objective function to increase the likelihood that the immunogenic peptide will be presented by all of the constructed diplotypes. This achieves the objective of maximizing the number of distinct HLA alleles in an individual exhibiting peptide-HLA immunogenicity, thus increasing the allelic coverage of the vaccine in the individual.

Figure 9 shows a single MHC class I HLA diplotype with HLA-A02:03, HLA-A11:01, HLA-B55:02, HLA-B58:01, HLA-C03:02, and HLA-C03:03. Figure 3 shows the predicted vaccine performance (predicted peptide-HLA hit number) of 10 G12V MHC class I vaccines for individuals with OptiVax was used to design 10 G12V MHC class I vaccines against this HLA diplotype with peptide counts ranging from 1 to 10. For the results in Figure 9, six synthetic diplotypes are marked, each weighted equally, each having one HLA allele derived from an individual HLA diplotype, and other allele positions not evaluated. OptiVax was run using. The 10 peptide vaccines in Figure 9 are SEQ ID NO: 3 (GAVGVGKSL), SEQ ID NO: 4 (LMVVGAVGV), SEQ ID NO: 7 (VVGAVGVGK), SEQ ID NO: 14 (GPVGVGKSV), SEQ ID NO: 69 (LMVVGAVGI), and SEQ ID NO: 72 (LMVVGAVGL). ), SEQ ID NO: 131 (GAVGVGKSM), SEQ ID NO: 138 (GPVGVGKSA), SEQ ID NO: 142 (VTGAVGVGK), and SEQ ID NO: 198 (VAGAVGVGM). The two peptides SEQ ID NO: 3 (GAVGVGKSL) and SEQ ID NO: 131 (GAVGVGKSM) are predicted to bind to two of the HLA alleles with an affinity of 50 nM or lower.

MHC Class I Vaccine Design Procedure In some embodiments, the MHC Class I vaccine design procedure consists of the following computational steps.

Ｎ：ＥｖａｌＶａｘおよびＯｐｔｉＶａｘ目的関数のパラメーター。個体がカバーされるとみなされるための集団カバー率目標の最小予測個体別ヒット数を指定する。初期設定＝１（Ｐ（ｎ≧１）集団カバー率を計算する）。 In some embodiments, the inputs for the calculation are as follows.
P1 _{. ．． ．． n} : Peptide sequence (length n) containing the neoantigen or pathogenic target of interest (eg, KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, KRAS G13D, BCR-ABL b3a2, BCR-ABL b2a2). P _i represents the amino acid at position i.
t: position of target mutation in P, t∈[1, . ．． ．． n] (for example, t=12 for KRAS G12D).
s: Substitution mutation s∈[true, false] is true if the mutation is a substitution, and true if the mutation is a deletion or insertion or if the peptide does not contain a mutation (such as a pathogen target). It's false. If the mutation is a deletion or insertion, t indicates the position immediately preceding the deletion or insertion.
τ ₁ : Threshold of potential presentation of peptide by MHC for peptide-MHC scoring (e.g. 500 nM binding affinity)
τ ₂ : Threshold for predicted presentation of peptides by MHC for peptide-MHC scoring (e.g. 50 nM binding affinity)

N: Parameters of EvalVax and OptiVax objective functions. Specifies the minimum expected number of per-individual hits for population coverage goals for an individual to be considered covered. Initial setting = 1 (calculate P(n≧1) population coverage).

In some embodiments, the peptide-HLA scoring function used is as follows.

The second condition, j≠{t-(k-1), t-1}, means that the mutation in t is at position P2 or Pk (i.e., the anchor position) of the windowed k-mer peptide and suddenly Exclude peptides whose mutations are substitutions.

したがって、Ｂは、少なくとも１つのＨＬＡにより潜在的に提示されると予測される天然ペプチドを含む。
Ｂ中のペプチドに由来するすべてのヘテロクリティックペプチドのセットＢ’を作出する：

数式中、ＡＮＣＨＯＲ－ＭＯＤＩＦＩＥＤ（ｂ）は、ｂに由来するすべての３９９個のアンカー修飾ペプチド（Ｐ２およびＰ９のアミノ酸に対するすべての考え得る修飾を有する）のセットを返す。

Therefore, B includes a natural peptide predicted to be potentially presented by at least one HLA.
Create a set B' of all heteroclitic peptides derived from peptides in B:

In the formula, ANCHOR-MODIFIED(b) returns the set of all 399 anchor-modified peptides (with all possible modifications to the P2 and P9 amino acids) derived from b.

数式中、各ヘテロクリティックペプチドｂ’∈Ｂ’は、基本ペプチドｂ∈Ｂの突然変異である。この条件は、ｈがｂを潜在的に提示すると予測されなかった場合、ｂに由来するすべてのヘテロクリティックペプチドｂ’は、ｈにより提示されないことになることを強制する（たとえｈがｂ’を提示すると別様に予測された場合であっても）。

In the formula, each heteroclitic peptide b'εB' is a mutation of the basic peptide bεB. This condition forces that if h was not predicted to potentially present b, then all heteroclitic peptides b' derived from b will not be presented by h (even if h is b' even if it would have been predicted otherwise).

In some embodiments, this procedure can be repeated independently for each target of interest, and the resulting independent vaccine sets can be combined into a combination vaccine as described below.

MHC Class II Vaccine Design Procedure In some embodiments, the MHC Class II vaccine design procedure consists of the following computational steps.

Ｎ：ＥｖａｌＶａｘおよびＯｐｔｉＶａｘ目的関数のパラメーター。個体がカバーされるとみなされるための集団カバー率目標のための最小予測個体別ヒット数を指定する。初期設定＝１（Ｐ（ｎ≧１）集団カバー率を計算する）。 In some embodiments, the inputs for the calculation are as follows.
P1 _{. ．． ．． n} : peptide sequence (length n) containing the neoantigen of interest (eg, KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, KRAS G13D, BCR-ABL b3a2, BCR-ABL b2a2). P _i represents the amino acid at position i.
t: position of target mutation in P, t∈[1, . ．． ．． , n] (for example, t=12 for KRAS G12D).
s: Substitution mutation s∈[true, false] is true if the mutation is a substitution, and true if the mutation is a deletion or insertion or if the peptide does not contain a mutation (such as a pathogen target). It's false. If the mutation is a deletion or insertion, t indicates the position immediately preceding the deletion or insertion.
τ ₁ : Threshold of potential presentation of peptide by MHC for peptide-MHC scoring (e.g. 500 nM binding affinity)
τ ₂ : Threshold for predicted presentation of peptides by MHC for peptide-MHC scoring (e.g. 50 nM binding affinity)

N: Parameters of EvalVax and OptiVax objective functions. Specifies the minimum expected number of per-individual hits for the population coverage goal for an individual to be considered covered. Initial setting = 1 (calculate P(n≧1) population coverage).

In some embodiments, the peptide-HLA scoring function used is as follows.

なお、Ｓ_１はバイナリ行列であり、１は、ＨＬＡがペプチドを潜在的に提示すると予測されることを示し、０は、潜在的提示がないことを示すことに留意されたい。

Note that _S1 is a binary matrix, where 1 indicates that the HLA is predicted to potentially present the peptide and 0 indicates no potential presentation.

数式中、Ｐ_ｔは目的の標的残基（例えば、ＫＲＡＳ Ｇ１２Ｄの突然変異部位）である。この条件は、Ｓ_２中の非ゼロスコアを有するすべての（ペプチド，ＨＬＡ対立遺伝子）対について、標的残基が非アンカー位置の結合コア内に入ることを強制し、結合コアが、ペプチド毎に対立遺伝子により異なることを可能にする（特定のペプチドの結合コアは、そのペプチドを提示するＨＬＡ対立遺伝子に基づいて異なる可能性がある）。したがって、各対（ｐ，ｈ）毎に、予測結合コアＣ［ｐ，ｈ］が、標的残基Ｐ_ｔをアンカー位置（９－ｍｅｒコアのＰ１、Ｐ４、Ｐ６、またはＰ９）に特定する場合、またはＰ_ｔが結合コア内に含まれていない場合、Ｓ_２［ｐ，ｈ］＝０である。代替的な実施形態では、Ｐ_ｔは、コアの外側に位置してもよくまたはコア内部の非アンカー位置に位置してもよい。一部の実施形態では、Ｐ_ｔは、コアの内部および／または外部の特定の位置にのみ位置してもよい。一部の実施形態では、Ｃにおける結合コア予測には、予測信頼度が伴う。一部の実施形態では、予測コアＣ［ｐ，ｈ］の信頼度が所望の閾値（例えば、０．５、０．６、０．７、０．８、または０．９）を下回る場合、Ｓ_２［ｐ，ｈ］＝０である。

In the formula, P _t is the target residue of interest (eg, the mutation site of KRAS G12D). This condition forces the target residue to fall within the binding core at the non-anchor position for every (peptide, HLA allele) pair with a non-zero score in _S2 , and the binding core is Allows for allelic variation (the binding core of a particular peptide can vary based on the HLA allele presenting that peptide). Therefore, for each pair (p,h), if the predicted binding core C[p,h] specifies the target residue P _t at the anchor position (P1, P4, P6, or P9 of the 9-mer core) , or if P _t is not contained within the combined core, then S ₂ [p,h]=0. In alternative embodiments, P _t may be located outside the core or at a non-anchored location within the core. In some embodiments, P _t may be located only at certain locations inside and/or outside the core. In some embodiments, the combined core prediction in C is accompanied by a prediction confidence. In some embodiments, if the confidence of the predictive core C[p,h] is below a desired threshold (e.g., 0.5, 0.6, 0.7, 0.8, or 0.9), then S ₂ [p, h]=0.

数式中、ＡＮＣＨＯＲ－ＭＯＤＩＦＩＥＤ（ｂ，ｃ）は、９－ｍｅｒ結合コアｃのＰ１、Ｐ４、Ｐ６、およびＰ９にアミノ酸に対するすべての考え得る修飾を有するｂに由来するすべての２０^４－１個のアンカー修飾ペプチドのセットを返す。したがって、各基本ペプチドｂ毎に、ヘテロクリティックセットＢ’は、スコア付け行列Ｓ_２により示される有効なコア位置を有するｂを潜在的に提示するあらゆるＨＬＡ対立遺伝子について特定されたｂのすべての固有コアに対する修飾を有するすべてのアンカー修飾ペプチドｂ’を含む。 Next, create a set B' of all heteroclitic peptides derived from peptides in B:

In the formula, ANCHOR-MODIFIED(b,c) represents all 20 ⁴ −1 molecules derived from b with all possible modifications to amino acids at P1, P4, P6, and P9 of the 9-mer binding core c. Returns a set of anchor-modified peptides. Therefore, for each basic peptide b, the heteroclitic set B' includes all of b's identified for any HLA allele potentially presenting b with a valid core position as indicated by the scoring matrix _S Includes all anchor-modified peptides b' with modifications to the unique core.

を計算する。
数式中、各ヘテロクリティックペプチドｂ’∈Ｂ’は、基本ペプチドｂ∈Ｂの突然変異である。この条件は、ヘテロクリティックペプチドｂ’の結合コアが、基本ペプチドｂと同じ相対位置にあることを強制し、暗黙的に、標的残基Ｐ_ｔが依然として９－ｍｅｒ結合コア内の非アンカー位置に入ることを強制する（工程３）。 Updated scoring matrix of heteroclitic peptides, conditional on identified binding cores of heteroclitic and basic peptides occurring at the same offset by a specific HLA

Calculate.
In the formula, each heteroclitic peptide b'εB' is a mutation of the basic peptide bεB. This condition forces the binding core of the heteroclitic peptide b' to be in the same relative position as the basic peptide b, implicitly implying that the target residue _Pt remains at a non-anchored position within the 9-mer binding core. (Step 3)

を計算する。
数式中、各ヘテロクリティックペプチドｂ’∈Ｂ’は、基本ペプチドｂ∈Ｂの突然変異である。この条件は、ｈがｂを提示すると予測されなかった場合、ｂに由来するすべてのヘテロクリティックペプチドｂ’は、ｈにより提示されないことになることを強制する（たとえｈがｂ’を提示すると別様に予測された場合であっても）。 Updated score matrix for heteroclitic peptides, conditional on the potential presentation of the corresponding basic peptide by each HLA:

Calculate.
In the formula, each heteroclitic peptide b'εB' is a mutation of the basic peptide bεB. This condition forces that if h was not predicted to present b, then all heteroclitic peptides b' derived from b will not be presented by h (even if h presents b' even if predicted otherwise).

In some embodiments, this procedure can be repeated independently for each single target of interest, and the resulting independent vaccine sets can be combined into a combination vaccine as described below.

MHC Class I or Class II Vaccine Design Methods Prioritizing Peptide Conservation In some embodiments, vaccine inclusion favors peptide sequences that are more conserved across strains, species, or other protein sources of interest. . In some embodiments, vaccine design takes into account sets of related protein sequences called protein variants. Protein variants are one example of a family of protein sequences, and protein variants may be sequences derived from different species, pathogen strains, viral strains, or other variants considered for vaccine design. In some embodiments, each protein variant has an associated probability, called a protein variant probability, and the sum of all protein variant probabilities for a supplied set of protein variants is one. In some embodiments, multiple proteins of interest can be considered in the design of a single vaccine using MHC class I or class II vaccine design methods that prioritize peptide conservation. In such embodiments, all protein variants of the protein of interest are considered collectively to generate candidate peptides. In some embodiments, the sum of protein variant probabilities across all of the multiple proteins considered is one.

A set of candidate peptides is generated from each protein variant using a sliding window method that parses the protein variants into peptide sequences. In some embodiments, for MHC class I, 8-mers, 9-mers, 10-mers, and 11-mers are generated, but this process can be performed with any desired window length. and the resulting peptide sets can be combined. In some embodiments, for MHC class I, only 9-mers are generated. In some embodiments, all windowed peptides of length 13-25 are generated for MHC class II, but this process can use any desired window length (e.g., only 15-mers). It can be implemented by In some embodiments, peptides predicted to be glycosylated in a given protein variant are removed and the variant is not considered, as described in Liu et al. 2020. This document is incorporated herein by reference in its entirety.

In some embodiments, the degree of conservation of each generated peptide sequence (MHC class I or class II) is defined as the fraction of input protein variants in which that peptide sequence occurs. For example, if a given 9-mer peptide sequence is present in peptides generated from 90% of the protein variants provided as input, its degree of conservation is 0.90. In some embodiments, the conservation of each generated peptide sequence (MHC class I or class II) is defined as the sum of the protein variant frequencies in which that peptide sequence occurs. For example, if a given 9-mer peptide sequence occurs in peptides generated from protein variants with protein variant probabilities of 0.10 and 0.20, its degree of conservation is 0.30. In some embodiments, this functionality is implemented by a ComputeConservation function that calculates the sum of frequencies of protein variants that include a peptide sequence. In some embodiments, if there are not enough protein variants to calculate the expected future degree of conservation, the method found in Hie et al., 2021, herein incorporated by reference in its entirety. ComputeConservation can be implemented using methods for predicting conservation, such as those given below.

In some embodiments, vaccine design takes conservation into account by prioritizing more conserved peptides over other peptides for vaccine inclusion in order to meet desired vaccine performance metrics. In some embodiments, this vaccine design method first attempts to design a vaccine with candidate peptides that all meet a first conservation threshold, and if the desired vaccine performance is not met, the stringency increases. Iterative addition of additional peptides with low conservation is attempted to meet the desired vaccinality metric. In some embodiments, vaccine design that prioritizes conservation proceeds by setting vaccine design D to the empty set and then performing the following steps: (1) each peptide creates a set of candidate peptides; (2) selecting vaccine designs with various numbers/combinations of peptides from this candidate set and applying this method to MHC class I or class II vaccine designs; Optimizing vaccine performance metrics using methods disclosed herein to augment the vaccine design contained in D (one implementation of vaccine augmentation is described in (Liu et al., 2021) (3) from step 2, meeting the desired vaccine performance metrics or adding one more peptide to the selected set; (4) selecting any minimal vaccine peptide set design that does not result in the desired minimum improvement in vaccine performance metrics; (4) if a vaccine peptide set is found in step 3, the vaccine of step 3; adding the peptide set design to vaccine design D; and (5) determining whether vaccine design D meets a desired vaccine performance metric goal, and if so, returning vaccine design D as the final vaccine design. . In step 6, if vaccine design D does not meet the desired vaccine performance metric goal, the calculation proceeds to the following steps: (6) Set the updated conservation threshold to be lower (more constrained) than the current conservation threshold. (7) either the desired vaccine performance metric goal is achieved in step 6 or the updated preservation threshold is less than the minimum desired preservation threshold; Repeating the process starting from step 1 while retaining the current vaccine design D and the current candidate set until . In any iteration, if the updated conservation threshold is lower than the minimum desired conservation threshold, then the latest version of vaccine design D will be used as the final vaccine design. When the process is complete, the final vaccine design D contains all of the peptides that can be used in a vaccine.

In some embodiments, the MHC class I or class II vaccine design procedure consists of the following computational steps.

Ｏ_ｊ：タンパク質変異体Ｐ_ｊのタンパク質変異体確率
ｔ_ｊ：標的突然変異のタンパク質変異体Ｐ_ｊにおける位置 ｔ∈［１，．．．ｎ］
Ｄ：空集合φに初期化されたワクチン設計
ｓ：置換突然変異ｓ∈［真，偽］は、突然変異が置換の場合は真であり、突然変異が欠失もしくは挿入である場合またはペプチドが突然変異を含まない場合は偽である。突然変異が欠失または挿入である場合、ｔは、欠失または挿入の直前の位置を示す。
ｃ_１：ペプチドの初期保存度レベル
ｃ_ｃ：現在の保存度閾値
ｃ_２：各繰り返しでの保存度レベルの変化
ｃ_ｍ：最小最終保存度
ν：標的ワクチン性能メトリック
ν_ｄ：ワクチンサイズを増加させためのワクチン性能メトリックの最小変化
Ｎ：ＥｖａｌＶａｘおよびＯｐｔｉＶａｘ目的関数のパラメーター。個体がカバーされるとみなされるための集団カバー率目標のための最小予測個体別ヒット数を特定する。初期設定＝１（Ｐ（ｎ≧１）集団カバー率を計算する）。

In some embodiments, the inputs for the calculation are as follows.

O _j : Protein variant probability of protein variant P _j t _j : Position of target mutation in protein variant P _j t∈[1, . ．． ．． n]
D: Vaccine design initialized to the empty set φ s: Substitution mutation s∈[true, false] is true if the mutation is a substitution, and if the mutation is a deletion or insertion or if the peptide It is false if it does not contain a mutation. If the mutation is a deletion or insertion, t indicates the position immediately preceding the deletion or insertion.
c ₁ : initial conservation level of peptide c _c : current conservation threshold c ₂ : change in conservation level at each iteration _cm : minimum final conservation ν : target vaccine performance metric ν _d : increasing vaccine size Minimum change in vaccine performance metrics for N: Parameters of EvalVax and OptiVax objective functions. Identify the minimum expected number of per-individual hits for the population coverage goal for an individual to be considered covered. Initial setting = 1 (calculate P(n≧1) population coverage).

The protein variant sequence P _j is used to generate a windowed peptide across the protein sequence starting at each position m and having a peptide length of k residues. The result is a set X _j containing all of the peptide sequences of protein variants P j. P _{j,m. ．． ．． m+(k-1)} produces a sequence only if the subscript is within the defined protein P _j . In some embodiments, for MHC class I, k is selected to generate 8-mers, 9-mers, 10-mers, and 11-mers, but this process can be performed using any desired It can be performed with window lengths and the resulting peptide sets can be combined. In some embodiments, for MHC class I, only 9-mers are generated. In some embodiments, for MHC class II, we extract all windowed peptides of length 13-25, but this process can be adapted to any desired window length (e.g. 15-mer only).

In some embodiments, for MHC class I, the second condition m≠{t-(k-1), t-1} means that the mutation in t is the P2 of the windowed k-mer peptide. or in the Pk position (ie, the anchor position) and the mutation is a substitution and is for MHC class I design. The MHC class II design method filters MHC class II anchor positions.

Create a set B of all peptides occurring in any input protein variant.

Next, the current preservation degree threshold is set to the initial preservation degree threshold.

Step 5 determines whether vaccine design D meets the desired vaccine performance metric goals. If vaccine design set D satisfies the final vaccine performance design metric v, return D as the final design.

In step 6, the conservation threshold is updated to be lower (fewer constraints) than the current conservation threshold. If vaccine design set D does not satisfy the final vaccine performance design metric v, reduce c _c .

In step 7, the current vaccine design D is updated until either the desired vaccine performance metric goal in step 5 is achieved or the updated preservation threshold is less than the minimum desired preservation threshold. and repeat the process starting at step 1, keeping the current candidate set. If c _c < _cm , return design set D as the final vaccine. Otherwise, return to step 1 and repeat all subsequent steps.

In some embodiments, this procedure can be repeated independently for each pathogen gene variant or target variant of interest, and the resulting independent vaccine sets can be combined into a combination vaccine.

Methods of Combining Multiple Vaccines The method described above involves generating an optimized set of target peptides (eg, a third set of peptides) for one or more individual targets. In some embodiments, separate vaccines are designed for MHC class I and class II-based immunization against multiple targets (e.g., two or more targets such as KRAS G12D and KRAS G12V). A method is provided.

In some embodiments, disease presentation tables based on empirical data from sources such as the Cancer Genome Atlas (TCGA) are used to produce combinatorial peptide vaccines against multiple targets. A method is disclosed. Figure 10 shows the probability of disease presentation type (e.g., pancreatic cancer, colon Figure 1 illustrates an embodiment for factoring rectal cancer, and skin cancer. A presentation is a unique set of targets presented by one form of disease (eg, different types of cancer or cancer symptoms as shown in FIG. 10). FIG. 10 shows an example of, for each presentation, the probability of that presentation and the probability that a given target will be observed. For a given presentation, there may be one or more targets, each with a probability. In some embodiments, the multi-target vaccine design method involves allocating peptide resources to induce disease immunity based on presentation and respective target probabilities, e.g., as shown in FIG. Become. In some embodiments, the presentation corresponds to the frequency of occurrence of the target in different human populations or different risk groups. The probability of a target in the population is calculated for each possible presentation by summing the product of the probability of that presentation and the probability of the target in that presentation. Figure 10 shows the weights used to combine individual vaccines for each target (rows) into combination vaccines for each disease indication (columns). Values indicate the observed fraction of cases containing each target mutation. Data are from The Cancer Genome Atlas (TCGA). The TCGA data is filtered for each disease symptom into cases where the primary site is the symptom.

In some embodiments, if the basic peptides generated by mutations to different proteins are the same, the same vaccine design will be generated for mutations to different proteins. For example, in some embodiments of base peptide selection, the following mutations share the same set of base peptides and therefore have identical vaccine designs: HRAS Q61K, NRAS Q61K, and KRAS Q61K; HRAS Q61L, NRAS Q61L, and KRAS Q61L; HRAS Q61R, NRAS Q61R, and KRAS Q61R. Referring to FIG. 10, in some embodiments, if two mutations have the same individual vaccine design, when weighting the individual vaccine designs for inclusion in a combination vaccine, as described below. Their presentation-specific probabilities are added (eg, for thyroid cancer NRAS Q61R and HRAS Q61R).

Referring to FIG. 11, in some embodiments, the method includes first designing individual peptide vaccines against each target to create a combinatorial vaccine design against multiple targets. This will initially result in a set of target-specific vaccine designs. In some embodiments, the marginal predicted vaccine performance of each target-specific vaccine of size k is determined by subtracting the predicted vaccine performance of a vaccine of size k-1 from the predicted vaccine performance of size k. stipulated. Because the composition of a vaccine can change as the number of peptides used in a vaccine increases, to calculate the contribution to a combination vaccine, we need to calculate the contribution of each target-specific vaccine instead of a specific set of peptides. Marginal predicted vaccine performance is used.

In some embodiments, for each target-specific vaccine size, the weighted marginal predicted vaccine performance of the target-specific vaccine design is calculated as shown in FIG. 11. For a given target-specific vaccine size, the weighted predicted vaccine performance is calculated by multiplying its predicted vaccine performance by the probability of the target in the population (e.g., by using values as shown in Figure 10). Calculate performance. The marginal weighted predicted vaccine performance of a target-specific vaccine is the weighted coverage at size k minus the coverage at size k-1. The marginal weighted predicted vaccine performance of a size 1 target-specific vaccine is its weighted predicted vaccine performance. As shown in Figure 11, the marginal weighted predicted vaccine performances of all vaccines are combined into a single list, and this combined list is ordered from highest to lowest by the weighted marginal predicted vaccine performances of the target-specific vaccines. Change. The combination vaccine of size n is then determined by the first n elements of this list. The peptides of the combination vaccine are determined by the individual peptide target vaccines whose sizes add up to n and whose weighted predicted vaccine performance sums to the same sum as the first n elements of the permuted list. This maximizes the predicted vaccine performance of a combination vaccine of size n.

In some embodiments, a combinatorial multi-target vaccine is targeted for specific indications based on its overall predicted coverage for the diseases listed according to the presentation table used (e.g., see Figure 10). It can be designed by the predicted coverage and/or by that predicted coverage of a particular target by adjusting the weights used for predicted vaccine performance accordingly. Once the desired coverage level is selected, the peptides of the combination vaccine are determined with the aid of target-specific design. For example, if a combination vaccine comprises a target-specific vaccine of size k, a vaccine peptide directed against this target of size k is used in the combination vaccine.

As an example of one embodiment, FIG. 10 shows mutations (eg, KRAS G12D, G12V, and G12R) and their respective probabilities of occurring in individuals with various cancer indications (eg, pancreatic cancer). Figures 3 (MHC class I) and 4 (MHC class II) show the results of target-specific vaccines against KRAS G12D, G12V, G12R, G12C, and G13D targets using the methods for vaccines described herein. Indicates population coverage. The marginal population coverage of each target-specific vaccine at a given vaccine size is the improvement in coverage at that size and its size-1. If no peptide is present, the coverage is zero. The marginal coverage of each target-specific vaccine is multiplied by the probability of the target in the population as determined by the proportions shown in Figure 10 for the selected indication (eg, pancreatic cancer). These weighted marginal coverages of all target-specific vaccines are sorted to determine the best target-specific composition. The resulting list describes the composition of each size k combination vaccine for the selected indication by taking the first k elements of the list. As an example of one embodiment, FIG. 12 (MHC class I) and FIG. 13 (MHC class II) show the target-specific contributions at each vaccine size of the combination KRAS vaccine for three mutant KRAS G12D, G12V, and G12R. show. In Figures 12 and 13, these examples were calculated using the methods of combinatorial vaccine protocols described herein. In each combination vaccine size, target-specific vaccines of different components are used for the indicated indications. Table 1 (below) includes peptides present in independent (single target) and combinatorial (multitarget) MHC class I vaccine designs against KRAS G12D, G12V, G12R, G12C, and G13D targets. Table 2 (below) includes peptides present in independent (single target) MHC class II vaccine designs against KRAS G12D, G12V, G12R, G12C, and G13D targets and includes individual/single target vaccines. Any subset of can be combined to create an MHC class II vaccine against two or more multiple targets. In an alternative embodiment, the sequence listing provides heteroclitic peptides useful in MHC class I vaccines against KRAS G12D, G12V, G12R, G12C, and G13D targets.

Combination Vaccine Design Procedures In some embodiments, the procedures described herein are used to combine individual mini-vaccines optimized against different targets into a single optimized combination vaccine. .

In some embodiments, the calculation inputs are as follows.
τ: set of neoantigens or pathogenic targets of interest (e.g., KRAS G12D, KRAS G12V, KRAS G12R, BCR-ABL b3a2, BCR-ABL b2a2)
ν: Vaccine set individually optimized for each target. V _t,k denotes the optimal vaccine set of exactly k peptides for target t∈T (eg, calculated by the procedure described above). Note that ν _t,k+1 is not necessarily a superset of ν _t,k .
W: τ→[0,1]: target weights that map each target t∈τ to the probability or weight of t in a particular manifestation of interest (e.g. pancreatic cancer, see Submission A, e.g. Table 1) function.

一部の実施形態では、各標的のｔ、ｃ_ｔ，ｋは、一般に単調増加し、ｋの値が増加すると共に下方へと窪む（各追加ペプチドは、カバー率を増加させるが、リターンは減少する）。 In step 1, for each target t (individually), we calculate the optimized vaccines of size 1 to m as a set ν _t,k (k indicates the vaccine size), and then calculate their vaccine performance at each vaccine size. Calculate. For each target t (individually) and vaccine size (peptide count) k, calculate the unweighted population coverage c _t,k .

In some embodiments, t,c _t,k for each target is generally monotonically increasing and dips downward with increasing value of k (each additional peptide increases the coverage, but the return is Decrease).

一部の実施形態では、各標的ｔのｍ_ｔ，ｋは、ｋ（上記の工程１による）の単調減少関数であるはずである。 In step 2, the vaccine marginal performance is calculated and weighted by the probability weighting of each target. For each target t (individually), calculate the marginal coverage m _t,k of the kth peptide added to the vaccine set.

In some embodiments, m _t,k for each target t should be a monotonically decreasing function of k (according to step 1 above).

加重限界集団カバー率は、提示における標的の出現率により加重されたワクチンのｋ番目のペプチドの有効限界カバー率をもたらす（提示における標的の確率／加重を乗算することにより）。

The weighted marginal population coverage yields the effective marginal coverage of the kth peptide of the vaccine weighted by the probability of occurrence of the target in the presentation (by multiplying by the probability/weight of the target in the presentation).

In step 4, a vaccine with desired performance is selected. The final vaccine size k may vary based on the specific population coverage goal of the vaccine. The marginal weighted coverage values M _k of the combination vaccine are cumulatively summed over k to give the overall effective (target-weighted) population coverage of the combination vaccine containing k peptides, as Σ _j≦K M _k (considering both the probability/weighting of the target in presentation and the expected population coverage of the peptide based on HLA presentation).

Therefore, a combination vaccine with k peptides is a combination of the optimal individual (C _t,k ) peptide vaccines.

MHC Class I Peptide Sequence of RAS Vaccine In some embodiments, the peptide vaccine (single target vaccine or combination multi-target vaccine) comprises about 5, 10, or Contains 20 MHC class I peptides. In some embodiments, the MHC class I peptide vaccine is intended to be directed against one or more of the KRAS G12D, G12V, and G12R targets. In some embodiments, the amino acid sequence of the first peptide in the five-peptide combination vaccine is SEQ ID NO: 1. GADGVGKSM (SEQ ID NO: 1). In some embodiments, the amino acid sequence of the second peptide in the five-peptide combination vaccine is SEQ ID NO: 2. Contains LMVVGADGV (SEQ ID NO: 2). In some embodiments, the amino acid sequence of the third peptide in the five-peptide combination vaccine is SEQ ID NO: 3. GAVGVGKSL (SEQ ID NO: 3). In some embodiments, the amino acid sequence of the fourth peptide in the five-peptide combination vaccine is SEQ ID NO: 4. Contains LMVVGAVGV (SEQ ID NO: 4). In some embodiments, the amino acid sequence of the fifth peptide in the five-peptide combination vaccine is SEQ ID NO: 5. VTGARGVGK (SEQ ID NO: 5). An exemplary combination vaccine with five peptides (SEQ ID NO: 1-SEQ ID NO: 5) against KRAS G12D, G12V, and G12R targets is predicted to have a weighted population coverage of 0.3620.

In some embodiments, any one of the peptides (peptides 1-5) in the five-peptide vaccine is SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, or SEQ ID NO: 5 and 80. , 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

In some embodiments, the amino acid sequences of peptides 1-5 in the 10-peptide combination vaccine include SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, and SEQ ID NO: 5. In some embodiments, the amino acid sequence of the sixth peptide in the 10-peptide combination vaccine is SEQ ID NO: 6. VMGAVGVGK (SEQ ID NO: 6). In some embodiments, the amino acid sequence of the seventh peptide in the 10-peptide combination vaccine is SEQ ID NO: 7. VVGAVGVGK (SEQ ID NO: 7). In some embodiments, the amino acid sequence of the eighth peptide in the 10-peptide combination vaccine is SEQ ID NO: 8. GARGVGKSY (SEQ ID NO: 8). In some embodiments, the amino acid sequence of the ninth peptide in the 10-peptide combination vaccine is SEQ ID NO: 9. GPRGVGKSA (SEQ ID NO: 9). In some embodiments, the amino acid sequence of the tenth peptide in the ten-peptide combination vaccine is SEQ ID NO: 10. LMVVGARGV (SEQ ID NO: 10). An exemplary combination vaccine with 10 peptides (SEQ ID NO: 1-SEQ ID NO: 10) against KRAS G12D, G12V, and G12R targets is predicted to have a weighted population coverage of 0.4374.

In some embodiments, any one of the peptides (peptides 1-10) in the 10-peptide vaccine is SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, or SEQ ID NO: 10 and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95 , 96, 97, 98, or 99% identical.

In some embodiments, the amino acid sequences of peptides 1-10 in the 20-peptide combination vaccine are SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, and SEQ ID NO: 10. In some embodiments, the amino acid sequence of the eleventh peptide in the 20-peptide combination vaccine is SEQ ID NO: 11. GADGVGKSL (SEQ ID NO: 11). In some embodiments, the amino acid sequence of the twelfth peptide in the 20-peptide combination vaccine is SEQ ID NO: 12. GADGVGKSY (SEQ ID NO: 12). In some embodiments, the amino acid sequence of the thirteenth peptide in the 20-peptide combination vaccine is SEQ ID NO: 13. GYDGVGKSM (SEQ ID NO: 13). In some embodiments, the amino acid sequence of the fourteenth peptide in the 20-peptide combination vaccine is SEQ ID NO: 14. GPVGVGKSV (SEQ ID NO: 14). In some embodiments, the amino acid sequence of the 15th peptide in the 20-peptide combination vaccine is SEQ ID NO: 15. LTVVGAVGV (SEQ ID NO: 15). In some embodiments, the amino acid sequence of the 16th peptide in the 20-peptide combination vaccine is SEQ ID NO: 16. VVGAVGVGR (SEQ ID NO: 16). In some embodiments, the amino acid sequence of the 17th peptide in the 20-peptide combination vaccine is SEQ ID NO: 17. GARGVGKSM (SEQ ID NO: 17). In some embodiments, the amino acid sequence of the 18th peptide in the 20-peptide combination vaccine is SEQ ID NO: 18. GPRGVGKSV (SEQ ID NO: 18). In some embodiments, the amino acid sequence of the 19th peptide in the 20-peptide combination vaccine is SEQ ID NO: 19. LLVVGARGV (SEQ ID NO: 19). In some embodiments, the amino acid sequence of the 20th peptide in the 20-peptide combination vaccine is SEQ ID NO: 20. VAGARGVGM (SEQ ID NO: 20). An exemplary combination vaccine with 20 peptides (SEQ ID NO: 1 to SEQ ID NO: 20) against KRAS G12D, G12V, and G12R targets is predicted to have a weighted population coverage of 0.4604.

In some embodiments, any one of the peptides (peptides 1-20) in the 20-peptide vaccine is SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, and SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18 , SEQ ID NO: 19, or SEQ ID NO: 20 and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99 % identical amino acid sequences.

Table 1 lists each SEQ ID NO, the amino acid sequence corresponding to the SEQ ID NO, the KRAS protein target (with a specific mutation), the seed amino acid sequence (i.e., the amino acid sequence of the wild-type KRAS fragment), and the amino acid sequence at positions 2 and 9. The MHC class I peptide sequences described herein, including the amino acid substitutions (if any) of the heteroclitic peptide, and the peptides included in the 5, 10, or 20 combinatorial peptide vaccines described herein. Notes detailing embodiments that may be used. Table 1 also includes additional peptide sequences including SEQ ID NOS: 21-41. In some embodiments, any combination of the peptides listed in Table 1 (SEQ ID NOs: 1-41) can be used to create a combination peptide vaccine having from about 2 to about 40 peptides. . In some embodiments, any one of the peptides (peptides 1-41; SEQ ID NOs: 1-41) in the combination vaccine includes any one of SEQ ID NOs: 1-41 and 80, 81, 82, 83, 84, 85 , 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

Additional amino acid sequences of MHC class I heteroclitic peptides are provided in the sequence listing (SEQ ID NOs: 67-1522). In some embodiments, any combination of MHC class I peptides disclosed herein (SEQ ID NOs: 1-41, 67-1522, 1524-1536, and 1547-1549) is used to A combinatorial peptide vaccine with 40 peptides can be created. In some embodiments, any one of the peptides (peptides 1-41, 67-1522, 1524-1536, and 1547-1549) in the combination vaccine is SEQ ID NO: 1-41, 67-1522, 1524- 1536, or any of 1547 to 1549 and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% Contains identical amino acid sequences.

MHC Class II Peptide Sequences of RAS Vaccines In some embodiments, peptide vaccines (single target vaccines or combination multi-target vaccines) contain between about 2 and 40 MHC Class II peptides, each peptide consisting of about 20 amino acids. including. In some embodiments, the MHC class II peptide vaccine is intended to be directed against one or more of the KRAS G12D, G12V, G12R, G12C, and G13D targets.

Table 2 includes each SEQ ID number, the amino acid sequence corresponding to the SEQ ID number, the amino acid sequence corresponding to the binding core of the peptide, the KRAS protein target (with a specific mutation), the seed amino acid sequence (i.e., wild-type KRAS fragment The MHC class II peptide sequences described herein include the seed amino acid sequence of the binding core, and the amino acid substitutions (if any) of the heteroclitic peptide at positions 1, 4, 6, and 9. It is summarized. Table 2 shows SEQ ID NOS: 42-66. encoding recombinant peptides. Contains peptide sequences comprising SEQ ID NOs: 42-65 (Table 2). In some embodiments, any combination of the peptides listed in Table 2 (SEQ ID NOS: 42-66) may be used to create a single target (individual) peptide vaccine or from about 2 to about 40 peptides. Combination peptide vaccines can be created with In some embodiments, any one of the peptides (peptides 42-66; SEQ ID NOs: 42-66) in the combination vaccine is any one of SEQ ID NOs: 42-66 and 80, 81, 82, 83, 84, 85 , 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

In some embodiments, any combination of MHC class I and/or MHC class II peptides disclosed herein (SEQ ID NOs: 1-1522 and 1524-1549) may be used to target a single target (individual) Peptide vaccines or combination peptide vaccines having about 2 to about 40 peptides can be created. In some embodiments, any one of the peptides (peptides 1-1522 and 1524-1549; SEQ ID NOs: 1-1522 and 1524-1549) in the combination vaccine is and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

RAS mRNA and DNA Vaccines In some embodiments, vaccine peptides are encoded as mRNA or DNA molecules and administered in vivo for expression, as is known in the art. An example of vaccine delivery by mRNA is found in Kranz et al. (2016) and US Pat. No. 8,637,006, which are incorporated herein by reference. In one embodiment, a 5-peptide MHC class I combinatorial pancreatic cancer vaccine (targets: KRAS G12D, G12V, G12R) and a 5-peptide MHC class II combinatorial pancreatic cancer vaccine optimized by the procedures described herein. The construct containing the cancer vaccine (target: KRAS G12D, G12V, G12R) contains 10 peptides. The peptide has a secretion signal sequence added to the N-terminus, followed by an MHC class I transport signal (MITD) (Kreiter et al., 2008; Sahin et al., 2017; US Pat. No. 8,637,006). has been done. MITD has been shown to direct antigens into the pathway for HLA class I and class II presentation (Kreiter et al., 2008). Here, we use the non-immunogenic glycine/serine linkers of Sahin et al. (2017) to combine all peptides of each MHC class into a single construct, whereas Kreiter et al. (2008), it is also conceivable to construct individual constructs containing a single peptide with the same secretion and MITD signals.

In some embodiments, the amino acid sequence encoded by the mRNA vaccine comprises SEQ ID NO: 1523. Underlined amino acids correspond to the signal peptide (or leader) sequence. Amino acids in bold correspond to MHC class I (9 amino acids long; 5 peptides) and MHC class II (13-25 amino acids long; 5 peptides) peptide sequences. Italicized amino acids correspond to transport signals.

In some embodiments, the vaccine is an mRNA vaccine comprising a nucleic acid sequence encoding the amino acid sequence consisting of SEQ ID NO: 1523. In some embodiments, the nucleic acid sequences of the mRNA vaccines are SEQ ID NO: 1523 and Encode amino acid sequences that are 96, 97, 98, or 99% identical.

In some embodiments, the vaccine is a DNA vaccine comprising a nucleic acid sequence encoding the amino acid sequence consisting of SEQ ID NO: 1523. In some embodiments, the DNA vaccine nucleic acid sequences are SEQ ID NOs: 1523 and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, Encode amino acid sequences that are 96, 97, 98, or 99% identical.

In some embodiments, mRNA-encoded vaccine peptides are used as the payload of self-amplifying RNA vaccines. In one embodiment, one or more structural proteins of the infectious alphavirus particle are replaced by an mRNA sequence encoding a vaccine peptide, as described in Geall et al. (2012). This document is incorporated herein by reference. As described in Geall et al. (2012), self-amplifying RNA vaccines can increase the efficiency of antigen production in vivo.

In some embodiments, one or more MHC class I and/or MHC class II peptides disclosed herein (SEQ ID NOs: 1-1522 and 1524-1549) are added to one or more mRNA molecules or DNA The molecules can be encoded and administered in vivo for expression. In some embodiments, about 2 to about 40 peptide sequences are encoded in one or more mRNA constructs. In some embodiments, about 2 to about 40 peptide sequences are present in one or more DNA constructs (i.e., nucleic acids encoding amino acid sequences comprising one or more of SEQ ID NOs: 1-1522 and 1524-1549). ) is coded. In some embodiments, the mRNA vaccine amino acid sequence or the DNA vaccine nucleic acid sequence is any of SEQ ID NOs: 1-1522 or 1524-1549 and 80, 81, 82, 83, 84, 85, 86, 87, 88, Encoding amino acid sequences that are 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

MHC Class I Peptide Sequence of BCR-ABL Vaccine In some embodiments, the peptide vaccine (single target vaccine or combination multi-target vaccine) comprises about 1 Contains ~40 MHC class I peptides. In some embodiments, the MHC class I peptide vaccine is intended for a BCR-ABL gene fusion. In some embodiments, the BCR-ABL gene fusion is selected from the group consisting of b3a2 and b2a2. In some embodiments, the MHC class I peptide vaccine is intended for preventing cancer. In some embodiments, the MHC class I peptide vaccine is intended to treat cancer. In some embodiments, the MHC class I peptide vaccine is used to prevent chronic myeloid leukemia (CML), acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), or invasive ductal carcinoma. is intended to be. In some embodiments, the MHC class I peptide vaccine is for treating chronic myeloid leukemia (CML), acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), or invasive ductal carcinoma. is intended to be.

In some embodiments, the MHC class I peptide vaccine amino acid sequence vaccine against BCR-ABL comprises one or more of SEQ ID NOs: 1550-1594. In some embodiments, any one of the peptides in the BCR-ABL vaccine is SEQ ID NO: 1550-1594 and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91 , 92, 93, 94, 95, 96, 97, 98, or 99% identical.

In some embodiments, the amino acid sequence vaccine of the MHC class I peptide vaccine against BCR-ABL comprises two or more of SEQ ID NOs: 1550-1594. In some embodiments, any one of the peptides in the BCR-ABL vaccine is SEQ ID NO: 1550-1594 and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91 , 92, 93, 94, 95, 96, 97, 98, or 99% identical.

Table 3 lists each SEQ ID NO, the amino acid sequence corresponding to the SEQ ID NO, the seed amino acid sequence (i.e., the amino acid sequence of the wild-type BCR-ABL protein fusion fragment), and the heteroclitic sequence at position 2 and C (carboxyl terminus). Notes detailing the MHC class I peptide sequences described herein, including amino acid substitutions of the peptides (if any), as well as embodiments in which the peptides may be included in the combination peptide vaccines described herein. shows. SEQ ID NOs: 1550-1582 and 1594 are derived from BCR-ABL b3a2, and SEQ ID NOs: 1583-1593 are derived from BCR-ABL b2a2. In some embodiments, any combination of the peptides listed in Table 3 (SEQ ID NOs: 1550-1594) can be used to create a combination peptide vaccine having about 1 to about 40 peptides. In some embodiments, any one of the peptides (peptides 1550-1594; and 1550-1594) in the combination vaccine is any one of SEQ ID NOs: 1550-1594 and Amino acid sequences that are 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

In some embodiments, any combination of the peptides listed in the "b3a2 vaccine" column of Table 3 (SEQ ID NO: 1550-1582 and SEQ ID NO: 1594) is used to administer about 1 to about 40 peptides. Combination peptide vaccines can be created with In some embodiments, any one of such peptides in the combination vaccine includes the peptides listed in the "b3a2 vaccine" column of Table 3 (SEQ ID NO: 1550-1582 and SEQ ID NO: 1594) and 80, 81, Amino acid sequences that are 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

In some embodiments, a combination peptide vaccine having from about 1 to about 40 peptides using any combination of the peptides listed in the "b2a2 vaccine" column of Table 3 (SEQ ID NOs: 1583-1593) can be created. In some embodiments, any one of such peptides in the combination vaccine includes the peptides listed in the "b2a2 vaccine" column of Table 3 (SEQ ID NOs: 1583-1593) and 80, 81, 82, 83, Amino acid sequences that are 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

Additional amino acid sequences for MHC class I vaccine peptides are provided in the sequence listing (SEQ ID NOs: 1662-2249). In some embodiments, any combination of MHC class I peptides disclosed herein (SEQ ID NOs: 1550-1594 and SEQ ID NOs: 1662-2249) is used to create combinations having from about 1 to about 40 peptides. Peptide vaccines can be created. In some embodiments, any one of the peptides (SEQ ID NO: 1550-1594 and SEQ ID NO: 1662-2249) in the combination vaccine is 80, 81, Amino acid sequences that are 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

MHC Class II Peptide Sequences of BCR-ABL Vaccines In some embodiments, peptide vaccines (single-target vaccines or combinatorial multi-target vaccines) contain approximately 1-40 MHC classes, each peptide consisting of about 20 amino acids. Contains II peptide. In some embodiments, the MHC class II peptide vaccine is intended for a BCR-ABL gene fusion. In some embodiments, the BCR-ABL gene fusion is selected from the group consisting of b3a2 and b2a2. In some embodiments, the MHC class II peptide vaccine is intended for preventing cancer. In some embodiments, the MHC class II peptide vaccine is intended for treating cancer. In some embodiments, the MHC class I peptide vaccine is used to prevent chronic myeloid leukemia (CML), acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), or invasive ductal carcinoma. is intended to be. In some embodiments, the MHC class I peptide vaccine is for treating chronic myeloid leukemia (CML), acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), or invasive ductal carcinoma. is intended to be.

In some embodiments, the MHC class II peptide vaccine amino acid sequence vaccine against BCR-ABL comprises one or more of SEQ ID NOs: 1595-1661. In some embodiments, any one of the peptides in the BCR-ABL vaccine is SEQ ID NO: 1595-1661 and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91 , 92, 93, 94, 95, 96, 97, 98, or 99% identical.

In some embodiments, the amino acid sequence vaccine of the MHC class II peptide vaccine against BCR-ABL comprises two or more of SEQ ID NOs: 1595-1661. In some embodiments, any one of the peptides in the BCR-ABL vaccine is SEQ ID NO: 1595-1661 and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91 , 92, 93, 94, 95, 96, 97, 98, or 99% identical.

Table 4 lists each SEQ ID NO, the amino acid sequence corresponding to the SEQ ID NO, the amino acid sequence corresponding to the binding core of the peptide, the seed amino acid sequence (i.e., the amino acid sequence of the wild-type BCR-ABL protein fusion fragment), the binding core The MHC class II peptide sequences described herein are summarized, including the seed amino acid sequence of and the heteroclitic peptide amino acid substitutions at positions 1, 4, 6, and 9, if any. Table 4 contains peptide sequences comprising SEQ ID NOs: 1595-1661. SEQ ID NOs: 1595-1661 (Table 4) encode recombinant peptides. SEQ ID NOs: 1595-1627 are derived from BCR-ABL b3a2, and SEQ ID NOs: 1628-1661 are derived from BCR-ABL b2a2. In some embodiments, any combination of the peptides listed in Table 4 (SEQ ID NOS: 1595-1661) is used to have a single target (individual) peptide vaccine or from about 1 to about 40 peptides. Combination peptide vaccines can be created. In some embodiments, any one of the peptides (peptides 1595-1661; SEQ ID NOs: 1595-1661) in the combination vaccine is one of SEQ ID NOs: 1595-1661 and 80, 81, 82, 83, 84, 85 , 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

In some embodiments, a combination peptide vaccine having from about 1 to about 40 peptides using any combination of the peptides listed in the "b3a2 vaccine" column of Table 4 (SEQ ID NOs: 1595-1627) can be created. In some embodiments, any one of such peptides in the combination vaccine includes the peptides listed in the "b3a2 vaccine" column of Table 4 (SEQ ID NOs: 1595-1627) and 80, 81, 82, 83, Amino acid sequences that are 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

In some embodiments, a combination peptide vaccine having from about 1 to about 40 peptides using any combination of the peptides listed in the "b2a2 vaccine" column of Table 4 (SEQ ID NOs: 1628-1661) can be created. In some embodiments, any one of such peptides in the combination vaccine includes the peptides listed in the "b2a2 vaccine" column of Table 4 (SEQ ID NOs: 1628-1661) and 80, 81, 82, 83, Amino acid sequences that are 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

Additional amino acid sequences of MHC class II vaccine peptides are provided in the sequence listing (SEQ ID NOs: 2250-63661). In some embodiments, any combination of MHC class II peptides disclosed herein (SEQ ID NOs: 1595-1661 and SEQ ID NOs: 2250-63661) is used to create combinations having from about 1 to about 40 peptides. Peptide vaccines can be created. In some embodiments, any one of the peptides (SEQ ID NO: 1595-1661 and SEQ ID NO: 2250-63661) in the combination vaccine is 80, 81, Amino acid sequences that are 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

In some embodiments, any combination of MHC class I and/or MHC class II peptides (SEQ ID NOS: 1550-63662) disclosed herein may be used to create a single target (individual) peptide vaccine or Combination peptide vaccines can be created having from 2 to about 40 peptides. In some embodiments, any one of the peptides (peptides 1550-63662; SEQ ID NOs: 1550-63662) in the combination vaccine is any one of SEQ ID NOs: 1550-63662 and 80, 81, 82, 83, 84, 85 , 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

BCR-ABL mRNA and DNA Vaccines In one embodiment, a 10-peptide MHC class I BCR-ABL b3a2 vaccine and a 10-peptide MHC class II BCR-ABL b3a2 vaccine optimized by the procedures described herein. The construct containing 20 peptides. The peptide contains a secretion signal sequence at the N-terminus followed by an MHC class I transport signal (MITD) (Kreiter et al., 2008; Sahin et al., 2017; US Pat. No. 8,637,006; (Incorporated herein by reference in their entirety) are appended. MITD has been shown to direct antigens into the pathway for HLA class I and class II presentation (Kreiter et al., 2008). Here, we combine all peptides of each MHC class into a single construct using the non-immunogenic glycine/serine linkers of Sahin et al. (2017), but Kreiter et al. (2008), it is also conceivable to construct individual constructs containing a single peptide with the same secretion and MITD signals.

In some embodiments, the amino acid sequence encoded by the mRNA vaccine comprises SEQ ID NO: 63662. Underlined amino acids correspond to the signal peptide (or leader) sequence. Amino acids in bold correspond to MHC class I (8-11 amino acids long; 10 peptides) and MHC class II (13-25 amino acids long; 10 peptides) peptide sequences. Italicized amino acids correspond to transport signals. In an alternative embodiment, any number and variant of the peptide sequences disclosed herein can be included in an mRNA vaccine comprising the signal peptide sequence and transport signal shown in SEQ ID NO: 63662 below.

In some embodiments, the vaccine is an mRNA vaccine comprising a nucleic acid sequence encoding the amino acid sequence consisting of SEQ ID NO: 63662. In some embodiments, the nucleic acid sequences of the mRNA vaccines are SEQ ID NO: 63662 and Encode amino acid sequences that are 96, 97, 98, or 99% identical.

In some embodiments, the vaccine is a DNA vaccine comprising a nucleic acid sequence encoding the amino acid sequence consisting of SEQ ID NO: 63662. In some embodiments, the DNA vaccine nucleic acid sequences are SEQ ID NO: 63662 and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, Encode amino acid sequences that are 96, 97, 98, or 99% identical.

In some embodiments, one or more MHC class I and/or MHC class II peptides disclosed herein (SEQ ID NOs: 1550-63662) are encoded in one or more mRNA or DNA molecules; Can be administered in vivo for expression. In some embodiments, about 2 to about 40 peptide sequences are encoded in one or more mRNA constructs. In some embodiments, about 2 to about 40 peptide sequences are encoded by one or more DNA constructs (i.e., nucleic acids encoding amino acid sequences comprising one or more of SEQ ID NOs: 1550-63662). Ru. In some embodiments, the mRNA vaccine amino acid sequence or the DNA vaccine nucleic acid sequence is any of SEQ ID NOs: 1550-63662 and 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, Encoding amino acid sequences that are 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical.

In one non-limiting embodiment aspect of the subject matter , the present invention provides SEQ ID NO. 1, SEQ ID NO. 2, SEQ ID NO. 3, SEQ ID NO. 4, SEQ ID NO. 5, SEQ ID NO. No. 10, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23 , SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, Sequence Nucleic acid sequences encoding at least two amino acid sequences selected from the group consisting of No. 37, SEQ ID No. 38, SEQ ID No. 39, SEQ ID No. 40, and SEQ ID No. 41 are provided.

In some embodiments, the nucleic acid sequence is an immunogenic composition. In some embodiments, the nucleic acid sequence is administered in vivo in a construct for expression. In some embodiments, in vivo administration of the nucleic acid sequence is configured to produce at least one peptide presented by an HLA class I molecule. In some embodiments, at least one peptide is a modified or unmodified fragment of a mutant KRAS protein. In some embodiments, the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to prevent cancer. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to treat cancer.

In another aspect, the invention provides SEQ ID NO:1, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO:10, SEQ ID NO:12, Number 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25 , SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37, SEQ ID NO: 38, Sequence An immunogenic peptide composition comprising at least two peptides selected from the group consisting of No. 39, SEQ ID No. 40, and SEQ ID No. 41 is provided.

In some embodiments, at least one peptide of the at least two peptides is presented by an HLA class I molecule in the subject. In some embodiments, at least one peptide of the at least two peptides is a modified or unmodified fragment of a mutant KRAS protein. In some embodiments, the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to prevent cancer. In some embodiments, an immunogenic peptide composition is administered to a subject in an effective amount to treat cancer. In some embodiments, the immunogenic peptide compositions include SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10. , SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, Sequence Number 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37 , SEQ ID NO: 38, SEQ ID NO: 39, SEQ ID NO: 40, and SEQ ID NO: 41.

In another aspect, the invention provides SEQ ID NO:42, SEQ ID NO:43, SEQ ID NO:44, SEQ ID NO:45, SEQ ID NO:46, SEQ ID NO:47, SEQ ID NO:48, SEQ ID NO:49, SEQ ID NO:50, SEQ ID NO:51, Number 52, SEQ ID NO: 53, SEQ ID NO: 54, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 59, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 63, SEQ ID NO: 64 , and SEQ ID NO: 65.

In some embodiments, the nucleic acid sequence is an immunogenic composition. In some embodiments, the nucleic acid sequence is administered in vivo in a construct for expression. In some embodiments, in vivo administration of the nucleic acid sequence is configured to produce at least one peptide presented by an HLA class II molecule. In some embodiments, at least one peptide is a modified fragment of a mutant KRAS protein. In some embodiments, the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to prevent cancer. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to treat cancer.

In another aspect, the invention provides SEQ ID NO:42, SEQ ID NO:43, SEQ ID NO:44, SEQ ID NO:45, SEQ ID NO:46, SEQ ID NO:47, SEQ ID NO:48, SEQ ID NO:49, SEQ ID NO:50, SEQ ID NO:51, Number 52, SEQ ID NO: 53, SEQ ID NO: 54, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 59, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 63, SEQ ID NO: 64 , and SEQ ID NO: 65.

In some embodiments, at least one peptide in the immunogenic peptide composition is presented by an HLA class II molecule. In some embodiments, at least one peptide in the immunogenic peptide composition is a modified or unmodified fragment of a mutant KRAS protein. In some embodiments, the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to prevent cancer. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to treat cancer. In some embodiments, the immunogenic peptide compositions are SEQ ID NO: 42, SEQ ID NO: 43, SEQ ID NO: 44, SEQ ID NO: 45, SEQ ID NO: 46, SEQ ID NO: 47, SEQ ID NO: 48, SEQ ID NO: 49, SEQ ID NO: 50. , SEQ ID NO:51, SEQ ID NO:52, SEQ ID NO:53, SEQ ID NO:54, SEQ ID NO:55, SEQ ID NO:56, SEQ ID NO:57, SEQ ID NO:58, SEQ ID NO:59, SEQ ID NO:60, SEQ ID NO:61, SEQ ID NO:62, Sequence No. 63, SEQ ID No. 64, and SEQ ID No. 65.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; at least one peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen or a self protein; for each peptide sequence in the first peptide set, a plurality of peptide- determining whether each peptide sequence in the first set of peptides has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles; and a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one amino acid of a peptide sequence in the first peptide set. determining whether each modified peptide sequence in the second set of peptides has a peptide-HLA binding score that satisfies a second threshold for at least three HLA alleles. the second threshold being more constrained than the first threshold, and creating a third set of peptides by selecting a subset of the second set of peptides, the selection being more constrained than the first threshold; calculating population coverage, the calculation of population coverage comprising: if the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence does not meet a first threshold with respect to the first HLA allele; performing a step comprising excluding a peptide-HLA binding score for a first HLA allele of the modified peptide sequence, the selected subset having population coverage above a third threshold; an experimental assay; obtaining a peptide-HLA immunogenicity metric for at least one peptide sequence in the third set of peptides; and at least one peptide sequence in the third set of peptides on which the experimental assay was performed. A method is provided comprising forming an immunogenic peptide composition comprising:

In some embodiments, selecting a plurality of unmodified peptide sequences to create a first set of peptides involves sliding a window of size n across amino acid sequences encoding tumor neoantigens or self-proteins. and n is about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences in the first peptide set. In some embodiments, each peptide sequence in the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. In some embodiments, the method further comprises filtering the first set of peptides to exclude peptide sequences that have a predicted binding core that includes the target residue at the anchor position. In some embodiments, the method further comprises substituting at least one amino acid residue of each peptide sequence in the first set of peptides, wherein for at least one peptide sequence in the first set of peptides, At least one amino acid residue is present at the anchor position. In some embodiments, the first threshold is a binding affinity of less than about 1000 nM. In some embodiments, the second threshold is a binding affinity of less than about 500 nM. In some embodiments, population coverage is calculated based on the frequency of HLA haplotypes in the human population. In some embodiments, population coverage is calculated based on the frequencies of at least three HLA alleles in the human population. In some embodiments, the plurality of unmodified peptide sequences are derived from tumor neoantigens or self-proteins present in the subject. In some embodiments, the third threshold is a percentage of the human population of about 0.7 to about 0.8. In some embodiments, the tumor neoantigen or self protein is associated with a cancer consisting of pancreas, colon, rectum, kidney, bronchus, lung, uterus, cervix, bladder, liver, and stomach. selected from the group.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; determining a plurality of peptide-HLA immunogenicity metrics for each peptide sequence in the first peptide set, the plurality of unmodified peptide sequences being associated with tumor neoantigens or self-proteins; determining whether each peptide sequence in the first set of peptides has a peptide-HLA immunogenicity metric that satisfies a first threshold for at least three HLA alleles; creating a second peptide set comprising a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising a substitution of at least one amino acid residue of a peptide sequence in the first peptide set; determining whether each modified peptide sequence in the second set of peptides has a peptide-HLA immunogenicity metric that satisfies a second threshold for at least three HLA alleles, , the second threshold is more constrained than the first threshold, and creating a third set of peptides by selecting a subset of the second set of peptides, the selection comprising: calculating predicted vaccine performance, where the peptide-HLA immunogenicity metric of the unmodified peptide sequence associated with the modified peptide sequence does not meet a first threshold with respect to the first HLA allele; , excluding the peptide-HLA immunogenicity metric for the first HLA allele of the modified peptide sequence, and predicting vaccine performance for each peptide sequence in the third set of peptide-HLA immunogenicity performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence in the third set of peptides; forming an immunogenic peptide composition comprising at least one peptide sequence in a third set of peptides in which the method has been performed.

In some embodiments, selecting the plurality of unmodified peptide sequences to create the first set of peptides comprises sliding a window of size n across the amino acid sequence encoding the tumor neoantigen or self protein. , n is about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences in the first peptide set. In some embodiments, each peptide sequence in the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. In some embodiments, the method further comprises filtering the first set of peptides to exclude peptide sequences that have a predicted binding core that includes the target residue at the anchor position. In some embodiments, the method further comprises substituting at least one amino acid residue of each peptide sequence in the first set of peptides, wherein for at least one peptide sequence in the first set of peptides, At least one amino acid residue is present at the anchor position. In some embodiments, the first threshold is a binding affinity of less than about 1000 nM.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; each peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen or self protein; determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles; creating a second peptide set comprising a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising a substitution of at least one amino acid residue of a peptide sequence in the first peptide set; determining whether each modified peptide sequence in the second set of peptides has a peptide-HLA binding score that satisfies a second threshold for at least three HLA alleles, the step comprising: a second threshold is more constrained than the first threshold; and creating a third set of peptides by selecting a subset of the second set of peptides, the selection determining the predicted vaccine performance. calculating, the calculation of predicted vaccine performance comprises: calculating the predicted vaccine performance if the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence does not meet a first threshold with respect to the first HLA allele; excluding the peptide-HLA binding score for the first HLA allele of the third peptide set, wherein the predicted vaccine performance is a function of the non-excluded peptide-HLA binding score of each peptide sequence in the third peptide set. performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence in the third set of peptides; and a third peptide on which the experimental assay was performed. A method is provided that includes forming an immunogenic peptide composition that includes at least one peptide sequence in a set.

In some embodiments, the second threshold is based on data obtained from one or more experimental assays. In some embodiments, the predicted vaccine performance further determines that the first peptide sequence in the first peptide set is linked to a second HLA allele of at least three HLA alleles by the first binding core. a function of the peptide-HLA immunogenicity metric of at least one modified peptide sequence of the plurality of modified peptide sequences bound to a second HLA allele of the at least three HLA alleles if predicted to bind to a second HLA allele of the at least three HLA alleles; , the first binding core is a binding core of the first peptide sequence, the first binding core is the same as the second binding core, and the first binding core and the second binding core are of the peptide sequence. comprising an amino acid position within the sequence, the second binding core being a binding core of at least one modified peptide sequence of the plurality of modified peptide sequences bound to a second HLA allele.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; at least one peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen or a self protein; for each peptide sequence in the first peptide set, a plurality of peptide- determining whether each peptide sequence in the first set of peptides has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles; and a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one amino acid of a peptide sequence in the first peptide set. determining whether each modified peptide sequence in the second set of peptides has a peptide-HLA binding score that satisfies a second threshold for at least three HLA alleles. and the second threshold is more constrained than the first threshold, creating a third set of peptides by selecting a subset of the second set of peptides, the selection comprising: calculating predicted vaccine performance based on the HLA type of the first performing a step comprising excluding a peptide-HLA binding score for a first HLA allele of the modified peptide sequence if the threshold is not met; obtaining a peptide-HLA immunogenicity metric for at least one peptide sequence; and forming an immunogenic peptide composition comprising at least one peptide sequence in a third set of peptides on which an experimental assay was performed. Provide a method including.

In some embodiments, each peptide sequence in the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. In some embodiments, the plurality of unmodified peptide sequences are derived from tumor neoantigens or self-proteins present in the subject. In some embodiments, at least three HLA alleles are present in the subject's HLA type. In some embodiments, the plurality of unmodified peptide sequences are derived from tumor neoantigens or self-proteins present in the subject. In some embodiments, the plurality of unmodified peptide sequences are derived from tumor neoantigens or self-proteins present in the subject. In some embodiments, the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of at least one peptide sequence in the third peptide set. In some embodiments, the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of at least one peptide sequence in the third peptide set.

In another aspect, the invention provides a composition comprising a nucleic acid sequence encoding at least two amino acid sequences selected from the group consisting of SEQ ID NOs: 1550-1593.

In some embodiments, the composition is immunogenic. In some embodiments, the nucleic acid sequence is administered in vivo in a construct for expression. In some embodiments, in vivo administration of the nucleic acid sequence is configured to produce at least one peptide presented by an HLA class I molecule. In some embodiments, at least one peptide is a modified or unmodified fragment of a BCL-ABL gene fusion. In some embodiments, the BCR-ABL gene fusion is b3a2 or b2a2. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to prevent cancer. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to treat cancer.

In another aspect, the invention provides a composition comprising at least two aminopeptides selected from the group consisting of SEQ ID NOs: 1550-1593.

In some embodiments, at least one peptide of the at least two peptides is presented by an HLA class I molecule in the subject. In some embodiments, at least one peptide in the immunogenic peptide composition is a modified or unmodified fragment of a BCL-ABL gene fusion. In some embodiments, the BCR-ABL gene fusion is b3a2 or b2a2. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to prevent cancer. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to treat cancer. In another aspect, the invention provides a composition comprising at least two peptides selected from the group consisting of SEQ ID NOs: 1550-1593.

In another aspect, the invention provides a nucleic acid sequence encoding at least one amino acid sequence selected from the group consisting of SEQ ID NOs: 1595-1661.

In some embodiments, the composition is immunogenic. In some embodiments, the nucleic acid sequence is administered in vivo in a construct for expression. In some embodiments, in vivo administration of the nucleic acid sequence is configured to produce at least one peptide presented by an HLA class II molecule. In some embodiments, at least one amino acid sequence is derived from a modified fragment of a BCL-ABL gene fusion. In some embodiments, the BCR-ABL gene fusion is b3a2 or b2a2. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to prevent cancer. In some embodiments, the nucleic acid sequence is administered to a subject in an effective amount to treat cancer.

In another aspect, the invention provides a nucleic acid sequence encoding at least one amino acid sequence selected from the group consisting of SEQ ID NOs: 1595-1661.

In some embodiments, at least one peptide is presented by an HLA class II molecule in the subject. In some embodiments, at least one peptide in the immunogenic peptide composition is a modified or unmodified fragment of a BCL-ABL gene fusion. In some embodiments, the BCR-ABL gene fusion is b3a2 or b2a2. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to prevent cancer. In some embodiments, the immunogenic peptide composition is administered to a subject in an effective amount to treat cancer. In some embodiments, the immunogenic peptide composition comprises at least two peptides selected from the group consisting of SEQ ID NOs: 1595-1661.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; for each peptide sequence in the first set of peptides, wherein at least one peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen, a pathogen proteome, or a self protein; determining a plurality of peptide-HLA binding scores, determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles; a step of creating a first peptide set and a second peptide set comprising a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences being a peptide sequence in the first peptide set; determining a plurality of peptide-HLA binding scores for each peptide sequence in the second set of peptides, and selecting a subset of the second set of peptides; creating a third peptide set by selecting, the selection comprising calculating a population coverage, the calculation of the population coverage determining the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence; , excluding a peptide-HLA binding score for the first HLA allele of the modified peptide sequence if the first threshold is not met for the first HLA allele; performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence in the third peptide set; A method is provided that includes forming an immunogenic peptide composition that includes at least one peptide sequence of the third set of peptides in which the assay was performed.

In some embodiments, selecting a plurality of unmodified peptide sequences to create a first set of peptides of size n over at least a portion of an amino acid sequence encoding a tumor neoantigen, pathogen proteome, or self protein. sliding a window, where n is about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences of the first peptide set. In some embodiments, each peptide sequence of the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. Some embodiments further include filtering the first set of peptides to exclude peptide sequences that have a predicted binding core that includes the target amino acid residue at the anchor position. In some embodiments, the method further comprises substituting at least one amino acid residue of each peptide sequence of the first peptide set, wherein for at least one peptide sequence of the first peptide set, the at least one amino acid residue exists at the anchor position. In some embodiments, the first threshold is a binding affinity of less than about 1000 nM. In some embodiments, population coverage is calculated for at least three HLA alleles. In some embodiments, population coverage is calculated based on the frequency of HLA haplotypes in the human population. In some embodiments, population coverage is calculated based on the frequencies of at least three HLA alleles in the human population. In some embodiments, the plurality of unmodified peptide sequences are derived from tumor neoantigens, pathogen proteomes, or self proteins present in the subject. In some embodiments, the second threshold is a percentage of the human population of about 0.7 to about 0.8. In some embodiments, the tumor neoantigen or self protein is associated with a cancer consisting of pancreas, colon, rectum, kidney, bronchus, lung, uterus, cervix, bladder, liver, and stomach. selected from the group. In some embodiments, the pathogen proteome is associated with a pathogen infection in a human subject. In some embodiments, the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of at least one peptide sequence of the third peptide set.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; the plurality of unmodified peptide sequences are associated with tumor neoantigens, pathogen proteomes, or self proteins; for each peptide sequence in the first peptide set, the plurality of peptide-HLA immunogenic determining whether each peptide sequence in the first set of peptides has a peptide-HLA immunogenicity metric that satisfies a threshold for at least three HLA alleles; the first set of peptides; and creating a second peptide set comprising a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one amino acid residue of a peptide sequence in the first peptide set. determining a plurality of peptide-HLA immunogenicity metrics for each peptide sequence in the second set of peptides; and selecting a subset of the second set of peptides to obtain a third peptide. creating a set, wherein the selecting includes calculating a predicted vaccine performance, the calculating the predicted vaccine performance including a peptide-HLA immunogenicity metric of an unmodified peptide sequence associated with a modified peptide sequence; including excluding the peptide-HLA immunogenicity metric for the first HLA allele of the modified peptide sequence if the threshold is not met for one HLA allele; performing an experimental assay to determine the peptide-HLA immunogenicity metric for at least one peptide sequence of the third set of peptides; and forming an immunogenic peptide composition comprising at least one peptide sequence of a third set of peptides on which an experimental assay was performed.

In some embodiments, selecting a plurality of unmodified peptide sequences to create a first set of peptides of size n over at least a portion of an amino acid sequence encoding a tumor neoantigen, pathogen proteome, or self protein. sliding a window, where n is about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences of the first peptide set. In some embodiments, each peptide sequence of the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. Some embodiments further include filtering the first set of peptides to exclude peptide sequences that have a predicted binding core that includes the target amino acid residue at the anchor position. Some embodiments further include substituting at least one amino acid residue of each peptide sequence of the first set of peptides. In some embodiments, the threshold is a binding affinity of less than about 1000 nM. In some embodiments, at least three HLA alleles are present in the subject's HLA type. In some embodiments, the plurality of peptide sequences are derived from tumor neoantigens, pathogen proteomes, or self proteins present in the subject. In some embodiments, the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of at least one peptide sequence of the third peptide set.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; each peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen, pathogen proteome, or self protein; determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a threshold for at least three HLA alleles; the first peptide set; and creating a second peptide set comprising a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one amino acid residue of a peptide sequence in the first peptide set. determining a plurality of peptide-HLA binding scores for each peptide sequence in the second set of peptides; and selecting a subset of the second set of peptides to form a third set of peptides. creating a step in which the selecting includes calculating a predicted vaccine performance, wherein the calculation of the predicted vaccine performance is such that the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence is higher than that of the first HLA allele. including excluding the modified peptide sequence's peptide-HLA binding score for the first HLA allele if the threshold for the gene is not met; performing a step that is a function of an HLA binding score; performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence of the third peptide set; and the experimental assay. forming an immunogenic peptide composition comprising at least one peptide sequence of a third set of peptides in which the method has been performed.

In some embodiments, the second threshold is determined from data obtained from one or more experimental assays. In some embodiments, the performance of the predicted vaccine is further determined if the first peptide sequence of the first peptide set is predicted to bind to the second HLA allele by the first binding core. a function of the peptide-HLA immunogenicity metric of at least one modified peptide sequence of the second set of peptides with respect to an HLA allele of the first the binding core of is the same as the second binding core, the first binding core and the second binding core each include an amino acid position within the peptide sequence, and the second binding core comprises at least one modified peptide sequence. is the combined core of In some embodiments, the plurality of peptide sequences are derived from tumor neoantigens, pathogen proteomes, or self proteins present in the subject.

In another aspect, the invention provides a method for forming an immunogenic peptide composition, the method comprising: using a processor to create a first set of peptides by selecting a plurality of unmodified peptide sequences; for each peptide sequence in the first set of peptides, wherein at least one peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen, a pathogen proteome, or a self protein; determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a threshold for at least three HLA alleles; creating a second peptide set comprising one peptide set and a plurality of modified peptide sequences, each modified peptide sequence of the plurality of modified peptide sequences comprising at least one of the peptide sequences in the first peptide set; determining a plurality of peptide-HLA binding scores for each peptide sequence in the second set of peptides; and a third step by selecting a subset of the second set of peptides. creating a set of peptides of the unmodified peptide sequence associated with the modified peptide sequence, the selection comprising calculating predicted vaccine performance based on the HLA type of the subject; performing a step comprising excluding a peptide-HLA binding score for a first HLA allele of the modified peptide sequence if the HLA binding score does not meet a threshold for the first HLA allele; an experimental assay; obtaining a peptide-HLA immunogenicity metric for at least one peptide sequence of the third peptide set; and at least one peptide sequence of the third peptide set on which the experimental assay was performed. A method is provided that includes forming an immunogenic peptide composition.

In some embodiments, each peptide sequence in the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. In some embodiments, the plurality of peptide sequences are derived from tumor neoantigens, pathogen proteomes, or self proteins present in the subject.

Compositions In some embodiments, a peptide vaccine is administered in a pharmaceutical composition comprising one or more peptides of the present disclosure and comprising a pharmaceutically acceptable carrier. In some embodiments, the peptide vaccine includes a third set of peptides described in this disclosure. In some embodiments, the pharmaceutical composition is in the form of a spray, aerosol, gel, solution, emulsion, lipid nanoparticle, nanoparticle, or suspension. In some embodiments, the pharmaceutical composition is in the form of a cationic nanoemulsion, an example of which is described in Brito et al. (2014). This document is incorporated herein by reference.

The composition is preferably administered to a subject with a pharmaceutically acceptable carrier. Typically, in some embodiments, a suitable amount of a pharmaceutically acceptable salt is used in the formulation to allow the formulation to be isotonic.

In certain embodiments, the peptides are provided as an immunogenic composition comprising any one of the peptides described herein and a pharmaceutically acceptable carrier. In certain embodiments, the immunogenic composition further comprises an adjuvant. In certain embodiments, the peptide is conjugated with other molecules to increase its effectiveness, as is known to those skilled in the art. For example, peptides can be coupled to antibodies that recognize cell surface proteins of antigen-presenting cells to enhance vaccine efficacy. One such method for increasing the effectiveness of peptide delivery is described in Woodham et al. (2018). In certain embodiments for treating autoimmune disorders, peptides are delivered using compositions and protocols designed to induce tolerance, as known in the art. Examples of methods for using peptides for immune tolerization are described in Alhadj Ali, et al. (2017) and Gibson, et al. (2015).

In some embodiments, the pharmaceutically acceptable carrier is selected from the group consisting of saline, Ringer's solution, dextrose solution, and combinations thereof. Other suitable pharmaceutically acceptable carriers known in the art are contemplated. Suitable carriers and their formulation are described in Remington's Pharmaceutical Sciences, 2005, Mack Publishing Co. The pH of the solution is preferably about 5 to about 8, more preferably about 7 to about 7.5. The formulation may also include a lyophilized powder. Additional carriers include sustained release preparations such as semipermeable matrices of solid hydrophobic polymers, which are in the form of shaped articles, eg films, liposomes, or microparticles. It will be apparent to those skilled in the art that certain carriers may be more preferred depending, for example, on the route of administration and concentration of the peptide being administered.

The phrase pharmaceutically acceptable carrier, as used herein, refers to a carrier that is involved in transferring or transporting the subject pharmaceutical agent from one organ or part of the body to another organ or part of the body. , a pharmaceutically acceptable substance, composition, or vehicle, such as a liquid or solid filler, diluent, excipient, solvent, or encapsulating material. Each carrier is acceptable in the sense that it is compatible with the other ingredients of the formulation and not deleterious to the patient. Examples of substances that can serve as pharmaceutically acceptable carriers include: sugars such as lactose, glucose, and sucrose; starches such as corn starch and potato starch; sodium carboxymethyl cellulose. Cellulose and its derivatives such as , ethylcellulose, and cellulose acetate; powdered tragacanth; malt; gelatin; talc; excipients such as cocoa butter and suppository wax; peanut oil, cottonseed oil, safflower oil, sesame oil, olive oil, corn oil, and Oils such as soybean oil; glycols such as butylene glycol; polyols such as glycerin, sorbitol, mannitol, and polyethylene glycol; esters such as ethyl oleate and ethyl laurate; agar; buffers such as magnesium hydroxide and aluminum hydroxide; alginic acid ; pyrogen-free water; isotonic saline; Ringer's solution; ethyl alcohol; phosphate buffered solution; and other non-toxic compatible materials used in pharmaceutical formulations. The term carrier refers to an organic or inorganic ingredient, natural or synthetic, with which the active ingredient is combined to facilitate the application. Additionally, the components of the pharmaceutical composition can be mixed with the compounds of the invention and with each other so that there are no interactions that would substantially impair the desired pharmaceutical efficacy. The compositions may also contain additional agents such as tonicity agents, preservatives, surfactants, and divalent cations, preferably zinc.

The compositions also include excipients or agents to stabilize the peptide composition, such as buffers, reducing agents, bulk proteins, amino acids (such as glycine or praline), or carbohydrates. May contain. Bulk proteins useful in formulating peptide compositions include albumin. Typical carbohydrates useful in formulating peptides include, but are not limited to, sucrose, mannitol, lactose, trehalose, or glucose.

Surfactants can also be used to prevent soluble and insoluble aggregation and/or precipitation of peptides or proteins included in the composition. Suitable surfactants include, but are not limited to, sorbitan trioleate, soy lecithin, and oleic acid. In certain cases, solution aerosols using solvents such as ethanol are preferred. Thus, formulations containing peptides may further include surfactants that can reduce or prevent surface-induced aggregation of the peptides upon atomization of the solution when forming an aerosol. A variety of conventional surfactants can be used, such as polyoxyethylene fatty acid esters and alcohols, and polyoxyethylene sorbitol fatty acid esters. Amounts generally range from 0.001% to 4% by weight of the formulation. In some embodiments, the surfactant used with the present disclosure is polyoxyethylene sorbitan monooleate, polysorbate 80, polysorbate 20. Additional agents known in the art may also be included in the composition.

In some embodiments, the pharmaceutical compositions and dosage forms further include one or more compounds that reduce the rate at which the active ingredient will disintegrate or the properties of the composition will change. So-called stabilizers or preservatives can include, but are not limited to, amino acids, antioxidants, pH buffers, or salt buffers. Non-limiting examples of antioxidants include butylated hydroxyanisole (BHA), ascorbic acid and its derivatives, tocopherol and its derivatives, butylated hydroxyanisole, and cysteine. Non-limiting examples of preservatives include parabens such as methyl or propyl p-hydroxybenzoate and benzalkonium chloride. Further non-limiting examples of amino acids include glycine or proline.

The present invention also stabilizes liquid solutions containing peptides at or below neutral pH by using amino acids containing proline or glycine, with or without divalent cations (inhibitor protein (preventing or minimizing thermally or mechanically induced soluble or insoluble aggregation and/or precipitation of teach things.

In one embodiment, the composition is a single-unit or multi-unit pharmaceutical composition. A single-unit or multi-unit pharmaceutical composition of the invention comprises a prophylactically or therapeutically effective amount of one or more compositions (e.g., a compound of the invention, or other prophylactic or therapeutic agent). ), typically including one or more vehicles, carriers, or excipients, stabilizers, and/or preservatives. Preferably, the vehicle, carrier, excipient, stabilizer, and preservative are pharmaceutically acceptable.

In some embodiments, pharmaceutical compositions and dosage forms include anhydrous pharmaceutical compositions and dosage forms. Anhydrous pharmaceutical compositions and dosage forms of the invention can be prepared using anhydrous or low moisture containing ingredients and low moisture or low humidity conditions. Pharmaceutical compositions and dosage forms containing lactose and at least one active ingredient comprising a primary or secondary amine are free from substantial contact with moisture and/or moisture during manufacturing, packaging, and/or storage. Where expected, it is preferably anhydrous. An anhydrous pharmaceutical composition should be prepared and stored such that its anhydrous nature is maintained. Therefore, anhydrous compositions are preferably packaged using materials known to prevent exposure to water so that they can be included in suitable formulation kits. Examples of suitable packaging include, but are not limited to, hermetically sealed foil, plastic, unit dose containers (eg, vials), blister packs, and strip packs.

Suitable vehicles are well known to those skilled in the pharmaceutical art; non-limiting examples of suitable vehicles include glucose, sucrose, starch, lactose, gelatin, rice, silica gel, glycerol, talc, sodium chloride, dry skim milk. , propylene glycol, water, sodium stearate, ethanol, and similar materials well known in the art. Physiological saline solutions and aqueous dextrose and glycerol solutions can also be used as liquid media. Whether a particular vehicle is suitable for incorporation into a pharmaceutical composition or dosage form depends on, but is not limited to, the manner in which the dosage form is to be administered to a patient and the particular active ingredients in the dosage form. It depends on various factors known in the art, including: Pharmaceutical vehicles can be sterile liquids such as water and oils, including those of petroleum, animal, vegetable, or synthetic origin, such as peanut oil, soybean oil, mineral oil, and sesame oil.

The present invention also provides that the pharmaceutical compositions can be packaged in hermetically sealed containers, such as ampoules or sachets with indicated quantities. In one embodiment, the pharmaceutical composition can be supplied as a sterile lyophilized powder in a delivery device suitable for administration to the patient's lower respiratory tract. Pharmaceutical compositions may optionally be presented in a pack or dispenser device which may contain one or more unit dosage forms containing the active ingredient. The pack may include, for example, metal or plastic foil, such as a blister pack. The pack or dispenser device may be accompanied by instructions for administration.

Methods for preparing such formulations or compositions include the step of bringing into association a compound of the invention with the carrier and, optionally, one or more accessory ingredients. In general, formulations are prepared by uniformly and intimately bringing into association a compound of the invention with liquid carriers or finely divided solid carriers, or both, and then, if necessary, shaping the product.

Formulations of the invention suitable for administration are in the form of powders, granules, or as solutions or suspensions in aqueous or non-aqueous liquids, each containing a predetermined amount of a compound of the invention (e.g. a peptide) as an active ingredient. as a liquid, or as an oil-in-water or water-in-oil liquid emulsion, or as an elixir or syrup, or as a troche (using inert bases such as gelatin and glycerin, or sucrose and acacia), and/or Alternatively, it may be used as a mouthwash.

The liquid compositions herein can be used as is in a delivery device or can be used in the preparation of pharmaceutically acceptable formulations containing peptides, for example prepared by spray drying methods. The method of spray lyophilizing peptides/proteins for pharmaceutical administration disclosed in Maa et al., Curr. Pharm. Biotechnol., 2001, 1, 283-302 is incorporated herein. In another embodiment, the liquid solutions herein are freeze-spray dried and the spray-dried product is collected as a dispersible peptide-containing powder that is therapeutically effective when administered to an individual.

The compounds and pharmaceutical compositions of the invention can be used in combination therapy. That is, the compounds and pharmaceutical compositions can be administered simultaneously with, before, or after one or more other desired therapeutic agents or medical procedures (e.g., peptide vaccines can be administered with chemotherapy, radiation, (can be used in combination therapy with another treatment, such as a drug, and/or another treatment). The particular combination of therapies (therapeutic agents or procedures) for use in a combination regimen will take into account the compatibility of the desired therapeutic agents and/or procedures and the desired therapeutic effect sought to be achieved. It will also be appreciated that the therapies used can achieve the desired effect on the same disorder (e.g. the compounds of the invention can be administered simultaneously with another therapeutic or prophylactic agent). .

The invention also provides a pharmaceutical pack or kit comprising one or more containers filled with one or more of the ingredients of the pharmaceutical compositions of the invention. Such containers may, as appropriate, be accompanied by a notice in the form prescribed by the governmental agency that regulates the manufacture, use, or sale of pharmaceutical or biological products, which notice indicates that the reflects any governmental approval of, use, or sale.

The present invention provides dosage forms containing peptides suitable for the treatment of cancer or other diseases. Dosage forms can be formulated, for example, as sprays, aerosols, nanoparticles, liposomes, or other forms known to those skilled in the art. See, e.g., Remington's Pharmaceutical Sciences; Remington: The Science and Practice of Pharmacy supra; Pharmaceutical Dosage Forms and Drug Delivery Systems by Howard C., Ansel et al., Lippincott Williams &Wilkins; 7th edition (Oct. 1, 1999). sea bream.

Generally, dosage forms used for the acute treatment of a disease may contain greater amounts of one or more of the active ingredients contained therein than dosage forms used for the chronic treatment of the same disease. In addition, prophylactically and therapeutically effective dosage forms may vary for different conditions. For example, if the purpose is to treat cancer or other diseases, therapeutically effective dosage forms may contain peptides with appropriate immunogenic effects. On the other hand, different effective dosages may be useful if the peptide of the invention is intended to be used as a prophylactic agent (e.g. vaccine) against cancer or another disease/condition. May contain. These and other ways in which the particular dosage forms encompassed by this invention may differ from one another will be readily apparent to those skilled in the art. For example, Remington's Pharmaceutical Sciences, 2005, Mack Publishing Co.; Remington: The Science and Practice of Pharmacy by Gennaro, Lippincott Williams &Wilkins; 20th edition (2003); Pharmaceutical Dosage Forms and Drug Delivery Systems by Howard C. Ansel et al. , Lippincott Williams &Wilkins; 7th edition (Oct. 1, 1999); and Encyclopedia of Pharmaceutical Technology, edited by Swarbrick, J. & J.C. Boylan, Marcel Dekker, Inc., New York, 1988. These documents are incorporated herein by reference in their entirety.

Additionally, the pH of a pharmaceutical composition or dosage form can be adjusted to improve the delivery and/or stability of one or more active ingredients. Similarly, the polarity of a solvent carrier, its ionic strength, or tonicity can be adjusted to improve delivery. Compounds such as stearates can also be added to pharmaceutical compositions or dosage forms to advantageously alter the hydrophilicity or lipophilicity of one or more active ingredients to improve delivery. In this regard, stearates can also serve as the lipid vehicle of the formulation, as an emulsifier or surfactant, and as a delivery or penetration enhancer. Different salts, hydrates, or solvates of the active ingredient can be used to further tailor the properties of the resulting composition.

The composition can be formulated with suitable carriers and adjuvants using techniques to obtain compositions suitable for immunization. The composition may include an adjuvant suitable for immunization, such as, but not limited to, alum, poly IC, MF-59, squalene-based adjuvants, or liposome-based adjuvants.

In some embodiments, the compositions and methods include any suitable agent or immunomodulator that can modulate host immune tolerance mechanisms and induced antibody release. In certain embodiments, the immunomodulatory agent transiently modulates a subject's immune response, e.g., to induce an immune response that includes antibodies against tumor neoantigens [i.e., tumor-specific antigens (TSAs)]. Administered at sufficient times and in sufficient amounts.

Expression Systems In certain aspects, the invention provides for culturing a cell line expressing any one of the peptides of the invention in a culture medium containing any of the peptides described herein.

A variety of expression systems for producing recombinant proteins/peptides are known in the art, including prokaryotic (e.g. bacterial) expression systems, plant expression systems, insect expression systems, yeast expression systems, and mammalian expression systems. can be mentioned. Suitable cell lines can be transformed, transduced, or transfected with nucleic acids containing coding sequences for peptides of the invention to produce molecules of interest. Expression vectors containing such a nucleic acid sequence, optionally linked to at least one regulatory sequence to enable expression of the nucleotide sequence in a host cell, can be introduced by methods known in the art. . Those skilled in the art will appreciate that the design of the expression vector may depend on factors such as the choice of host cell to be transfected and/or the type and/or amount of the desired protein to be expressed. do. Enhancer regions are sequences found upstream or downstream of promoter regions in non-coding DNA regions and are known in the art to be important in optimizing expression. If desired, a viral origin of replication can be used, such as when using a prokaryotic host for introducing plasmid DNA. However, in eukaryotes, chromosomal integration is a common mechanism of DNA replication. In stable transfection of mammalian cells, only a small proportion of cells are able to integrate the introduced DNA into their genome. The expression vector and transfection method used may be factors contributing to the success of the integration event. In order to stably amplify and express a desired protein, a vector containing a DNA encoding the protein of interest is stably integrated into the genome of a eukaryotic cell (e.g., a mammalian cell) to produce a transfected gene. results in stable expression of A gene encoding a selectable marker (e.g., resistance to an antibiotic or drug) is introduced into the host cell together with the gene of interest to identify and select clones that stably express the gene encoding the protein of interest. can do. Cells containing the gene of interest can be identified by drug selection, in which case cells that have integrated the selectable marker gene will survive in the presence of the drug. Cells that do not have the selectable marker gene will die. Surviving cells can then be screened for production of the desired protein molecule.

Host cell strains can also be selected that modulate the expression of inserted sequences or modify and process nucleic acids in the particular manner desired. Such modifications (eg, glycosylation and other post-translational modifications) and processing (eg, cleavage) of peptide/protein products may be important for peptide/protein function. Different host cell strains have characteristic and specific mechanisms for post-translational processing and modification of proteins and gene products. Therefore, choosing an appropriate host system or cell line can ensure correct modification and processing of the expressed target protein. Thus, eukaryotic host cells that have the cellular machinery for correct processing of primary transcripts, glycosylation, and phosphorylation of gene products may be used.

With respect to host cells in culture, various culture parameters can be used. Appropriate culture conditions for mammalian cells are well known in the art (Cleveland WL, et al., J lmmunol Methods, 1983, 56(2): 221-234) or can be determined by one skilled in the art. [See, for example, Animal Cell Culture: A Practical Approach 2nd Ed., Rickwood, D. and Hames, B. D., eds. (Oxford University Press: New York, 1992]]. Cell culture conditions may vary depending on the type of host cell chosen. Commercially available media can be used.

Peptides of the invention can be purified from any human or non-human cell that expresses a polypeptide, including cells transfected with an expression construct expressing a peptide of the invention. For protein recovery, isolation, and/or purification, cell culture media or cell lysates are centrifuged to remove particulate cells and cell debris. The desired polypeptide molecule is isolated or purified from contaminant soluble proteins and polypeptides by suitable purification techniques. Non-limiting methods of protein purification include: size exclusion chromatography; affinity chromatography; ion exchange chromatography; ethanol precipitation; reversed phase HPLC; resins such as silica or cation exchange resins, e.g. Chromatography in DEAE; chromatofocusing; SDS-PAGE; ammonium sulfate precipitation; gel filtration using, for example, Sephadex G-75, Sepharose; and Protein A Sepharose chromatography to remove immunoglobulin contaminants. Other additives such as protease inhibitors (eg, PMSF or proteinase K) can be used to inhibit proteolysis during purification. It is also possible to use purification procedures that allow selection of carbohydrates, such as ion-exchange soft gel chromatography or HPLC using cation- or anion-exchange resins, in which more acidic fractions are collected.

Methods of Treatment In some embodiments, the subject matter disclosed herein relates to preventive medical treatment that is initiated after diagnosis of cancer to prevent worsening of the disease or to cure the disease. In some embodiments, the term "prevent" refers to providing medical treatment to a subject (e.g., to prevent the development of a potential disease (e.g., one or more types of cancer)). (by administering the nucleic acids or peptides disclosed herein), but "preventing" does not necessarily mean that the disease will not occur in 100% of subjects receiving medical treatment. In one embodiment, the subject matter disclosed herein relates to the prevention of subjects considered to be at risk for cancer or who have been previously diagnosed with cancer (or another disease). In one embodiment, a subject can be administered a peptide vaccine or pharmaceutical composition thereof as described herein. The present invention contemplates the use of any of the peptides produced by the systems and methods described herein. In one embodiment, the peptide vaccines described herein can be administered subcutaneously by syringe or other suitable method known in the art.

A compound or compound combination or pharmaceutical composition disclosed herein can be administered to a cell, mammal, or human by any suitable means. Non-limiting examples of methods of administration include, among others: (a) administration in capsules, tablets, granules, sprays, syrups, or other such forms; , by the oral route; (b) intraocularly, intranasally, intraauricularly, rectally, vaginally, including administration as an aqueous suspension or oily preparation or as a drop, spray, suppository, salve, or ointment; Administration by parenteral routes such as intraurethral, transmucosal, buccal, or transdermal; (c) subcutaneous, intraperitoneal, intravenous, intramuscular, intradermal, intraorbital, intracapsular, intraspinal, including infusion pump delivery; or by injection, including intrasternally; (d) local administration, such as by direct injection into the renal or cardiac area, e.g., by depot implantation; (e) local administration; a compound or combination of compounds disclosed herein; (f) administration by inhalation, including aerosolized, nebulized, and powdered formulations; and (g) administration by implantation.

As will be readily apparent to those skilled in the art, the effective in vivo dose to be administered and the particular method of administration will depend on the age, body weight, and species being treated and the compound or combination of compounds disclosed herein used. will vary depending on the particular use. Determination of effective dosage levels, ie, the dosage levels necessary to achieve a desired result, can be accomplished by one of ordinary skill in the art using routine pharmacological methods. Typically, human clinical applications of a product are initiated at lower dosage levels and the dosage levels are increased until the desired effect is achieved. Alternatively, acceptable in vitro studies can be used to establish useful doses and routes of administration for compositions identified by the present methods using established pharmacological methods. can. Effective animal doses for in vivo studies can be converted to appropriate human doses using conversion methods known in the art (e.g., Nair AB, Jacob S. A simple practice guide for dose conversion between animals and human. Journal of basic and clinical pharmacy. 2016 Mar;7(2):27).

Methods of Prevention In some embodiments, peptides prepared using the methods of the invention can be used as vaccines to promote immune responses against cancer (eg, against tumor neoantigens). In some embodiments, the invention provides compositions and methods for inducing an immune response, eg, inducing antibodies against tumor neoantigens. In some embodiments, the antibody is a broadly neutralizing antibody. In some embodiments, peptides prepared using the methods of the invention can be used as vaccines to promote immune responses against pathogens. In some embodiments, peptides prepared using the methods of the invention can be used to promote immune tolerance as autoimmune disease therapeutics.

In some embodiments, peptides prepared using the methods of the invention can be combined with additional vaccine components. In some embodiments, such combination vaccines include one or more encoding peptides produced using the methods described herein and additional vaccine components (e.g., peptides or proteins) known in the art. It may be encoded by multiple nucleic acids. In some embodiments, such combination vaccines are created by adding peptides or proteins encoding additional vaccine components to the peptides resulting from the methods described herein for combination formulation and packaging. . An example of a combination of vaccine components is the creation of a RAS vaccine, where one or more nucleic acids encoding the components of the vaccine against KRAS G12D and KRAS G12V are used and such nucleic acids are combined into an mRNA-LNP or DNA formulation. The different components are packaged or formulated separately as mRNA-LNP or DNA and then combined for packaging or just prior to administration to an individual.

The compositions, systems, and methods disclosed herein are not limited in scope to the particular embodiments described herein. Indeed, various modifications of the compositions, systems and methods in addition to those described will become apparent to those skilled in the art from the above description.

Claims (120)

SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37, SEQ ID NO: 38, SEQ ID NO: 39, SEQ ID NO: 40, and SEQ ID NO: A nucleic acid sequence encoding at least two amino acid sequences selected from the group consisting of No. 41. 2. The nucleic acid sequence of claim 1, which is an immunogenic composition. 2. The nucleic acid sequence of claim 1, administered in vivo in a construct for expression. 4. The nucleic acid sequence of claim 3, wherein said in vivo administration of said nucleic acid sequence is configured to produce at least one peptide presented by an HLA class I molecule. 5. The nucleic acid sequence of claim 4, wherein the at least one peptide is a modified or unmodified fragment of a mutant KRAS protein. 6. The nucleic acid sequence of claim 5, wherein the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. 4. The nucleic acid sequence of claim 3, which is administered to a subject in an effective amount to prevent cancer. 4. The nucleic acid sequence of claim 3, which is administered to a subject in an effective amount to treat cancer. SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37, SEQ ID NO: 38, SEQ ID NO: 39, SEQ ID NO: 40, and SEQ ID NO: An immunogenic peptide composition comprising at least two peptides selected from the group consisting of No. 41. 10. The immunogenic peptide composition of claim 9, wherein at least one peptide of the at least two peptides is presented by an HLA class I molecule in the subject. 10. The immunogenic peptide composition of claim 9, wherein at least one peptide of the at least two peptides is a modified or unmodified fragment of a mutant KRAS protein. 12. The immunogenic peptide composition of claim 11, wherein the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. 10. The immunogenic peptide composition of claim 9, which is administered to a subject in an effective amount to prevent cancer. 10. The immunogenic peptide composition of claim 9, which is administered to a subject in an effective amount to treat cancer. SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37, SEQ ID NO: 38, SEQ ID NO: 39, SEQ ID NO: 40, and SEQ ID NO: 10. The immunogenic peptide composition of claim 9, comprising at least three peptides selected from the group consisting of number 41. SEQ ID NO:42, SEQ ID NO:43, SEQ ID NO:44, SEQ ID NO:45, SEQ ID NO:46, SEQ ID NO:47, SEQ ID NO:48, SEQ ID NO:49, SEQ ID NO:50, SEQ ID NO:51, SEQ ID NO:52, SEQ ID NO:53, SEQ ID NO: 54, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 59, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 63, SEQ ID NO: 64, and SEQ ID NO: 65. A nucleic acid sequence encoding at least one selected amino acid sequence. 17. An immunogenic composition comprising a nucleic acid sequence according to claim 16. 17. The nucleic acid sequence of claim 16, administered in vivo in a construct for expression. 19. The nucleic acid sequence of claim 18, wherein said in vivo administration of said nucleic acid sequence is configured to produce at least one peptide presented by an HLA class II molecule. 17. The nucleic acid sequence of claim 16, wherein the at least one peptide is a modified fragment of a mutant KRAS protein. 21. The nucleic acid sequence of claim 20, wherein the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. 17. The nucleic acid sequence of claim 16, which is administered to a subject in an effective amount to prevent cancer. 17. The nucleic acid sequence of claim 16, which is administered to a subject in an effective amount to treat cancer. SEQ ID NO:42, SEQ ID NO:43, SEQ ID NO:44, SEQ ID NO:45, SEQ ID NO:46, SEQ ID NO:47, SEQ ID NO:48, SEQ ID NO:49, SEQ ID NO:50, SEQ ID NO:51, SEQ ID NO:52, SEQ ID NO:53, SEQ ID NO: 54, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 59, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 63, SEQ ID NO: 64, and SEQ ID NO: 65. An immunogenic peptide composition comprising at least one selected peptide. 25. The immunogenic peptide composition of claim 24, wherein at least one peptide in the immunogenic peptide composition is presented by an HLA class II molecule. 25. The immunogenic peptide composition of claim 24, wherein at least one peptide in the immunogenic peptide composition is a modified or unmodified fragment of a mutant KRAS protein. 27. The immunogenic peptide composition of claim 26, wherein the mutant KRAS protein is selected from the group consisting of KRAS G12D, KRAS G12V, KRAS G12R, KRAS G12C, and KRAS G13D. 25. The immunogenic peptide composition of claim 24, which is administered to a subject in an effective amount to prevent cancer. 25. The immunogenic peptide composition of claim 24, which is administered to a subject in an effective amount to treat cancer. SEQ ID NO:42, SEQ ID NO:43, SEQ ID NO:44, SEQ ID NO:45, SEQ ID NO:46, SEQ ID NO:47, SEQ ID NO:48, SEQ ID NO:49, SEQ ID NO:50, SEQ ID NO:51, SEQ ID NO:52, SEQ ID NO:53, SEQ ID NO: 54, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 59, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 63, SEQ ID NO: 64, and SEQ ID NO: 65. 25. The immunogenic peptide composition of claim 24, comprising at least two selected peptides. 1. A method for forming an immunogenic peptide composition comprising:
using the processor
creating a first set of peptides by selecting a plurality of unmodified peptide sequences, wherein at least one peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen or a self protein; , process,
determining a plurality of peptide-HLA binding scores for each peptide sequence in the first peptide set;
determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles;
A step of creating a second peptide set comprising the first peptide set and a plurality of modified peptide sequences, wherein each modified peptide sequence of the plurality of modified peptide sequences is a peptide sequence in the first peptide set. a step comprising the substitution of at least one amino acid residue of
determining whether each modified peptide sequence in the second peptide set has a peptide-HLA binding score that satisfies a second threshold with respect to the at least three HLA alleles, a threshold is more constrained than the first threshold; and creating a third set of peptides by selecting a subset of the second set of peptides, the selection reducing population coverage. calculating, said calculation of population coverage comprising: if a peptide-HLA binding score of an unmodified peptide sequence associated with a modified peptide sequence does not meet said first threshold for a first HLA allele; performing a step comprising excluding a peptide-HLA binding score for the first HLA allele of modified peptide sequences, wherein the selected subset has a population coverage greater than a third threshold;
performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence in the third set of peptides; and in the third set of peptides on which the experimental assay was performed. forming an immunogenic peptide composition comprising said at least one peptide sequence of. Selecting the plurality of unmodified peptide sequences to create the first set of peptides includes sliding a window of size n across the amino acid sequence encoding the tumor neoantigen or the self protein, where n is , about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences in the first peptide set. 32. The method of claim 31, wherein each peptide sequence in the first peptide set binds an HLA class I molecule or an HLA class II molecule. 32. The method of claim 31, further comprising filtering the first set of peptides to exclude peptide sequences having a predicted binding core that includes the target residue at an anchor position. further comprising substituting at least one amino acid residue of each peptide sequence in the first peptide set, and for at least one peptide sequence in the first peptide set, the at least one amino acid residue is 32. The method of claim 31, wherein the method is in an anchor location. 32. The method of claim 31, wherein the first threshold is a binding affinity of less than about 1000 nM. 32. The method of claim 31, wherein the population coverage is calculated for the at least three HLA alleles. 32. The method of claim 31, wherein the second threshold is a binding affinity of less than about 500 nM. 32. The method of claim 31, wherein the population coverage is calculated based on the frequency of HLA haplotypes in the human population. 32. The method of claim 31, wherein the population coverage is calculated based on the frequencies of the at least three HLA alleles in the human population. 32. The method of claim 31, wherein the plurality of unmodified peptide sequences are derived from the tumor neoantigen or the self protein present in the subject. 32. The method of claim 31, wherein the third threshold is a percentage of the human population of about 0.7 to about 0.8. said tumor neoantigen or said self protein is associated with a cancer, said cancer selected from the group consisting of pancreatic, colon, rectal, kidney, bronchus, lung, uterus, cervix, bladder, liver, and stomach. 32. The method of claim 31, wherein: 1. A method for forming an immunogenic peptide composition comprising:
using the processor
creating a first set of peptides by selecting a plurality of unmodified peptide sequences, the plurality of unmodified peptide sequences being associated with tumor neoantigens or self-proteins;
determining a plurality of peptide-HLA immunogenicity metrics for each peptide sequence in said first peptide set, each peptide sequence in said first peptide set having a first determining whether the peptide-HLA immunogenicity metric satisfies a threshold of
A step of creating a second peptide set comprising the first peptide set and a plurality of modified peptide sequences, wherein each modified peptide sequence of the plurality of modified peptide sequences is a peptide sequence in the first peptide set. a step comprising the substitution of at least one amino acid residue of
determining whether each modified peptide sequence in the second set of peptides has a peptide-HLA immunogenicity metric that satisfies a second threshold with respect to the at least three HLA alleles; and creating a third set of peptides by selecting a subset of the second set of peptides, wherein the selection is more constrained than the first threshold; calculating vaccine performance, said calculation of predicted vaccine performance determining whether a peptide-HLA immunogenicity metric of an unmodified peptide sequence associated with a modified peptide sequence exceeds said first threshold for a first HLA allele. if not, excluding the peptide-HLA immunogenicity metric for the first HLA allele of the modified peptide sequence; performing a step that is a function of a non-excluded peptide-HLA immunogenicity metric;
performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence in the third set of peptides; and in the third set of peptides on which the experimental assay was performed. forming an immunogenic peptide composition comprising said at least one peptide sequence of. Selecting the plurality of unmodified peptide sequences to create the first set of peptides includes sliding a window of size n across the amino acid sequence encoding the tumor neoantigen or the self protein, where n is , about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences in the first peptide set. 45. The method of claim 44, wherein each peptide sequence in the first set of peptides binds an HLA class I molecule or an HLA class II molecule. 45. The method of claim 44, further comprising filtering the first set of peptides to exclude peptide sequences having a predicted binding core that includes the target residue at an anchor position. 45. The method of claim 44, further comprising substituting at least one amino acid residue of each peptide sequence in the first set of peptides. 45. The method of claim 44, wherein the first threshold is a binding affinity of less than about 1000 nM. 1. A method for forming an immunogenic peptide composition comprising:
using the processor
creating a first set of peptides by selecting a plurality of unmodified peptide sequences, each peptide sequence of the plurality of unmodified peptide sequences being associated with a tumor neoantigen or a self protein;
determining a plurality of peptide-HLA binding scores for each peptide sequence in the first peptide set, each peptide sequence in the first peptide set meeting a first threshold for at least three HLA alleles; Determining whether the peptide has a peptide-HLA binding score that satisfies
A step of creating a second peptide set comprising the first peptide set and a plurality of modified peptide sequences, wherein each modified peptide sequence of the plurality of modified peptide sequences is a peptide sequence in the first peptide set. a step comprising the substitution of at least one amino acid residue of
determining whether each modified peptide sequence in the second peptide set has a peptide-HLA binding score that satisfies a second threshold with respect to the at least three HLA alleles, a threshold value that is more constrained than the first threshold value; and creating a third set of peptides by selecting a subset of the second set of peptides, the selection determining the predicted vaccine performance. and the calculation of predicted vaccine performance comprises: if the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence does not meet the first threshold with respect to the first HLA allele; excluding the peptide-HLA binding score for the first HLA allele of the modified peptide sequence; performing a process that is a function of the score;
performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence in the third set of peptides; and in the third set of peptides on which the experimental assay was performed. forming an immunogenic peptide composition comprising said at least one peptide sequence of. 51. The method of claim 50, wherein the second threshold is based on data obtained from one or more experimental assays. The predicted vaccine performance further predicts that a first peptide sequence in the first peptide set binds to a second HLA allele of the at least three HLA alleles by a first binding core. peptide-HLA immunogenicity metric of at least one modified peptide sequence of said plurality of modified peptide sequences bound to said second HLA allele of said at least three HLA alleles. and the first binding core is a binding core of the first peptide sequence, the first binding core is the same as the second binding core, and the first binding core and the second binding core are the binding core comprises an amino acid position within a peptide sequence, and the second binding core comprises a binding core of the at least one modified peptide sequence of the plurality of modified peptide sequences bound to the second HLA allele. 51. The method of claim 50. 1. A method for forming an immunogenic peptide composition comprising:
using the processor
creating a first set of peptides by selecting a plurality of unmodified peptide sequences, wherein at least one peptide sequence of the plurality of unmodified peptide sequences is associated with a tumor neoantigen or a self protein; , determining a plurality of peptide-HLA binding scores for each peptide sequence in the first peptide set;
determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles;
A step of creating a second peptide set comprising the first peptide set and a plurality of modified peptide sequences, wherein each modified peptide sequence of the plurality of modified peptide sequences is a peptide sequence in the first peptide set. a step comprising the substitution of at least one amino acid residue of
determining whether each modified peptide sequence in the second peptide set has a peptide-HLA binding score that satisfies a second threshold with respect to the at least three HLA alleles, the threshold is more constrained than the first threshold;
creating a third set of peptides by selecting a subset of the second set of peptides, said selecting comprising calculating a predicted vaccine performance based on the subject's HLA type; calculation of the first HLA binding score of the modified peptide sequence if the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence performing a step comprising excluding a peptide-HLA binding score for an HLA allele;
performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence in the third set of peptides; and in the third set of peptides on which the experimental assay was performed. forming an immunogenic peptide composition comprising said at least one peptide sequence of. 54. The method of claim 53, wherein each peptide sequence in the first peptide set binds an HLA class I molecule or an HLA class II molecule. 55. The method of claim 54, wherein the plurality of unmodified peptide sequences are derived from the tumor neoantigen or the self protein present in the subject. 55. The method of claim 54, wherein the at least three HLA alleles are present in the subject's HLA type. 54. The method of claim 53, wherein the plurality of unmodified peptide sequences are derived from the tumor neoantigen or the self protein present in the subject. 54. The method of claim 53, wherein the plurality of unmodified peptide sequences are derived from the tumor neoantigen or the self protein present in the subject. 54. The method of claim 53, wherein the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of the at least one peptide sequence in the third set of peptides. 54. The method of claim 53, wherein the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of the at least one peptide sequence in the third set of peptides. A composition comprising a nucleic acid sequence encoding at least two amino acid sequences selected from the group consisting of SEQ ID NOs: 1550-1593. 62. The composition of claim 61, which is immunogenic. 62. The composition of claim 61, wherein the nucleic acid sequence is administered in vivo in a construct for expression. 64. The composition of claim 63, wherein said in vivo administration of said nucleic acid sequence is configured to produce at least one peptide presented by an HLA class I molecule. 65. The composition of claim 64, wherein the at least one peptide is a modified or unmodified fragment of a BCL-ABL gene fusion. 66. The composition of claim 65, wherein the BCR-ABL gene fusion is b3a2 or b2a2. 64. The composition of claim 63, wherein the nucleic acid sequence is administered to a subject in an effective amount to prevent cancer. 64. The composition of claim 63, wherein the nucleic acid sequence is administered to a subject in an effective amount to treat cancer. An immunogenic peptide composition comprising at least two peptides selected from the group consisting of SEQ ID NOs: 1550-1593. 70. The immunogenic peptide composition of claim 69, wherein at least one peptide of the at least two peptides is presented by an HLA class I molecule in the subject. 70. The immunogenic peptide composition of claim 69, wherein at least one peptide in the immunogenic peptide composition is a modified or unmodified fragment of a BCL-ABL gene fusion. 72. The immunogenic peptide composition of claim 71, wherein the BCR-ABL gene fusion is b3a2 or b2a2. 70. The immunogenic peptide composition of claim 69, which is administered to a subject in an effective amount to prevent cancer. 70. The immunogenic peptide composition of claim 69, which is administered to a subject in an effective amount to treat cancer. 70. The immunogenic peptide composition of claim 69, comprising at least three peptides selected from the group consisting of SEQ ID NOs: 1550-1593. A nucleic acid sequence encoding at least one amino acid sequence selected from the group consisting of SEQ ID NOs: 1595-1661. 77. An immunogenic composition comprising a nucleic acid sequence according to claim 76. 77. The nucleic acid sequence of claim 76, administered in vivo in a construct for expression. 79. The nucleic acid sequence of claim 78, wherein said in vivo administration of said nucleic acid sequence is configured to produce at least one peptide presented by an HLA class II molecule. 77. The nucleic acid sequence of claim 76, wherein said at least one amino acid sequence is derived from a modified fragment of a BCL-ABL gene fusion. 81. The nucleic acid sequence of claim 80, wherein the BCR-ABL gene fusion is b3a2 or b2a2. 77. The nucleic acid sequence of claim 76, wherein the nucleic acid sequence is administered to a subject in an effective amount to prevent cancer. 77. The nucleic acid sequence of claim 76, wherein the nucleic acid sequence is administered to a subject in an effective amount to treat cancer. An immunogenic peptide composition comprising at least one peptide selected from the group consisting of SEQ ID NOs: 1595-1661. 85. The immunogenic peptide composition of claim 84, wherein the at least one peptide is presented by an HLA class II molecule in the subject. 85. The immunogenic peptide composition of claim 84, wherein the at least one peptide in the immunogenic peptide composition is a modified or unmodified fragment of a BCL-ABL gene fusion. 87. The immunogenic peptide composition of claim 86, wherein the BCR-ABL gene fusion is b3a2 or b2a2. 85. The immunogenic peptide composition of claim 84, which is administered to a subject in an effective amount to prevent cancer. 85. The immunogenic peptide composition of claim 84, wherein the composition is administered to a subject in an effective amount to treat cancer. 85. The immunogenic peptide composition of claim 84, comprising at least two peptides selected from the group consisting of SEQ ID NOs: 1595-1661. 1. A method for forming an immunogenic peptide composition comprising:
using the processor
creating a first peptide set by selecting a plurality of unmodified peptide sequences, wherein at least one peptide sequence of the plurality of unmodified peptide sequences is derived from a tumor neoantigen, a pathogen proteome, or an autologous tumor; a process associated with a protein;
determining a plurality of peptide-HLA binding scores for each peptide sequence in the first peptide set;
determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a first threshold for at least three HLA alleles;
A step of creating a second peptide set comprising the first peptide set and a plurality of modified peptide sequences, wherein each modified peptide sequence of the plurality of modified peptide sequences is a peptide sequence in the first peptide set. a step comprising the substitution of at least one amino acid residue of
determining a plurality of peptide-HLA binding scores for each peptide sequence in the second peptide set; and creating a third peptide set by selecting a subset of the second peptide set. and the selection includes calculating a population coverage, wherein the population coverage calculation includes determining that the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence is greater than or equal to the peptide-HLA binding score for the first HLA allele. excluding a peptide-HLA binding score of the modified peptide sequence for the first HLA allele if a first threshold is not met, the selected subset having population coverage above a second threshold; carrying out a process having a rate;
performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence of said third set of peptides; and 1. A method comprising forming an immunogenic peptide composition comprising a peptide sequence. Selecting the plurality of unmodified peptide sequences to create the first set of peptides creates a window of size n over at least a portion of the amino acid sequence encoding the tumor neoantigen, the pathogen proteome, or the self protein. wherein n is about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences of the first peptide set. 91. 92. The method of claim 91, wherein each peptide sequence of the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. 92. The method of claim 91, further comprising filtering the first set of peptides to exclude peptide sequences having a predicted binding core that includes the target amino acid residue at an anchor position. further comprising substituting at least one amino acid residue of each peptide sequence of the first peptide set, wherein for at least one peptide sequence of the first peptide set, the at least one amino acid residue is at an anchor position. 92. The method of claim 91, wherein the method is present in 92. The method of claim 91, wherein the first threshold is a binding affinity of less than about 1000 nM. 92. The method of claim 91, wherein the population coverage is calculated for the at least three HLA alleles. 92. The method of claim 91, wherein the population coverage is calculated based on the frequency of HLA haplotypes in a human population. 92. The method of claim 91, wherein the population coverage is calculated based on the frequencies of the at least three HLA alleles in a human population. 92. The method of claim 91, wherein the plurality of unmodified peptide sequences are derived from the tumor neoantigen, the pathogen proteome, or the self protein present in the subject. 92. The method of claim 91, wherein the second threshold is a percentage of the human population of about 0.7 to about 0.8. The tumor neoantigen or the self protein is associated with a cancer selected from the group consisting of pancreatic, colon, rectal, kidney, bronchus, lung, uterus, cervix, bladder, liver, and stomach. 92. The method of claim 91. 92. The method of claim 91, wherein the pathogen proteome is associated with a pathogen infection in a human subject. 92. The method of claim 91, wherein the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of the at least one peptide sequence of the third peptide set. 1. A method for forming an immunogenic peptide composition comprising:
using the processor
creating a first set of peptides by selecting a plurality of unmodified peptide sequences, the plurality of unmodified peptide sequences being associated with tumor neoantigens, pathogen proteomes, or self proteins;
determining a plurality of peptide-HLA immunogenicity metrics for each peptide sequence in the first peptide set;
determining whether each peptide sequence in the first peptide set has a peptide-HLA immunogenicity metric that meets a threshold for at least three HLA alleles;
A step of creating a second peptide set comprising the first peptide set and a plurality of modified peptide sequences, wherein each modified peptide sequence of the plurality of modified peptide sequences is a peptide sequence in the first peptide set. a step comprising the substitution of at least one amino acid residue of
determining a plurality of peptide-HLA immunogenicity metrics for each peptide sequence in the second set of peptides; and creating a third set of peptides by selecting a subset of the second set of peptides. the step, said selecting comprising calculating predicted vaccine performance, said calculating predicted vaccine performance determining that a peptide-HLA immunogenicity metric of an unmodified peptide sequence associated with a modified peptide sequence is excluding a peptide-HLA immunogenicity metric for the first HLA allele of the modified peptide sequence if the threshold is not met for the HLA allele; performing a step that is a function of a peptide-HLA immunogenicity metric for each peptide sequence in the set;
performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence of the third set of peptides; and A method comprising forming an immunogenic peptide composition comprising at least one peptide sequence. Selecting the plurality of unmodified peptide sequences to create the first set of peptides includes sliding a window of size n over at least a portion of the amino acid sequence encoding the tumor neoantigen, pathogen proteome, or self protein. 105. wherein n is about 8 amino acids to about 25 amino acids long, and n is the length of each peptide sequence of the plurality of unmodified peptide sequences of the first peptide set. The method described in. 106. The method of claim 105, wherein each peptide sequence of the first set of peptides binds to an HLA class I molecule or an HLA class II molecule. 106. The method of claim 105, further comprising filtering the first set of peptides to exclude peptide sequences having a predicted binding core that includes the target amino acid residue at an anchor position. 106. The method of claim 105, further comprising substituting at least one amino acid residue of each peptide sequence of the first set of peptides. 106. The method of claim 105, wherein the threshold is a binding affinity of less than about 1000 nM. 106. The method of claim 105, wherein the at least three HLA alleles are present in the subject's HLA type. 112. The method of claim 111, wherein the plurality of peptide sequences are derived from the tumor neoantigen, the pathogen proteome, or the self proteins present in the subject. 106. The method of claim 105, wherein the immunogenic peptide composition comprises a nucleic acid sequence encoding the amino acid sequence of at least one peptide sequence of the third peptide set. 1. A method for forming an immunogenic peptide composition comprising:
using the processor
creating a first set of peptides by selecting a plurality of unmodified peptide sequences, each peptide sequence of the plurality of unmodified peptide sequences being associated with a tumor neoantigen, a pathogen proteome, or a self protein; , process,
determining a plurality of peptide-HLA binding scores for each peptide sequence in the first peptide set;
determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a threshold for at least three HLA alleles;
A step of creating a second peptide set comprising the first peptide set and a plurality of modified peptide sequences, wherein each modified peptide sequence of the plurality of modified peptide sequences is a peptide sequence in the first peptide set. a step comprising the substitution of at least one amino acid residue of
determining a plurality of peptide-HLA binding scores for each peptide sequence in the second peptide set; and creating a third peptide set by selecting a subset of the second peptide set. and the selecting includes calculating a predicted vaccine performance, and the calculating the predicted vaccine performance includes calculating a peptide-HLA binding score of an unmodified peptide sequence associated with a modified peptide sequence with respect to a first HLA allele. excluding the peptide-HLA binding score of the modified peptide sequence for the first HLA allele if the threshold is not met; performing a step in which the peptide-HLA binding score is a function of the peptide-HLA binding score of;
performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence of the third set of peptides; and A method comprising forming an immunogenic peptide composition comprising at least one peptide sequence. 115. The method of claim 114, wherein the second threshold is based on data obtained from one or more experimental assays. The predicted vaccine performance further relates to the second HLA allele if a first peptide sequence of the first peptide set is predicted to bind to the second HLA allele by a first binding core. , a function of the peptide-HLA immunogenicity metric of at least one modified peptide sequence of said second peptide set, said first binding core being a binding core of said first peptide sequence; the binding core of is the same as a second binding core, said first binding core and said second binding core each include an amino acid position within a peptide sequence, and said second binding core is identical to said at least one binding core; 115. The method of claim 114, wherein the binding core is two modified peptide sequences. 115. The method of claim 114, wherein the plurality of peptide sequences are derived from the tumor neoantigen, the pathogen proteome, or the self protein present in the subject. 1. A method for forming an immunogenic peptide composition comprising:
using the processor
creating a first peptide set by selecting a plurality of unmodified peptide sequences, wherein at least one peptide sequence of the plurality of unmodified peptide sequences is derived from a tumor neoantigen, a pathogen proteome, or an autologous tumor; a process associated with a protein;
determining a plurality of peptide-HLA binding scores for each peptide sequence in the first peptide set;
determining whether each peptide sequence in the first peptide set has a peptide-HLA binding score that satisfies a threshold for at least three HLA alleles;
A step of creating a second peptide set comprising the first peptide set and a plurality of modified peptide sequences, wherein each modified peptide sequence of the plurality of modified peptide sequences is a peptide sequence in the first peptide set. a step comprising the substitution of at least one amino acid residue of
determining a plurality of peptide-HLA binding scores for each peptide sequence in the second peptide set; and creating a third peptide set by selecting a subset of the second peptide set. and the selection includes calculating predicted vaccine performance based on the HLA type of the subject, and the calculation of predicted vaccine performance includes determining whether the peptide-HLA binding score of the unmodified peptide sequence associated with the modified peptide sequence is performing a step comprising excluding a peptide-HLA binding score of the modified peptide sequence for the first HLA allele if the threshold is not met for the first HLA allele;
performing an experimental assay to obtain a peptide-HLA immunogenicity metric for at least one peptide sequence of the third set of peptides; and A method comprising forming an immunogenic peptide composition comprising at least one peptide sequence. 120. The method of claim 118, wherein each peptide sequence in the first set of peptides binds an HLA class I molecule or an HLA class II molecule. 119. The method of claim 118, wherein the plurality of peptide sequences are derived from the tumor neoantigen, the pathogen proteome, or the self proteins present in the subject.

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