EP3652338A1

EP3652338A1 - Method for predicting responsiveness to immunotherapy

Info

Publication number: EP3652338A1
Application number: EP18745848.4A
Authority: EP
Inventors: François FUKS; Jana JESCHKE; Luis Teixeira; Christos Sotiriou
Original assignee: Universite Libre de Bruxelles ULB
Current assignee: Universite Libre de Bruxelles ULB
Priority date: 2017-07-14
Filing date: 2018-07-13
Publication date: 2020-05-20
Also published as: WO2019012105A1

Abstract

This invention relates to the field of cancer diagnostics and therapeutics. In particular, the invention relates to a method for predicting responsiveness to immunotherapy in a subject having a neoplastic disease, the method comprising: (A) determining the methylation level of a gene or a fragment thereof selected from the group consisting of internexin neuronal intermediate filament protein alpha (ΓΝΑ), protein tyrosine phosphatase, receptor type C-associated protein (PTPRCAP), semaphorin 3B (SEMA3B), kelch-like family member 6 (KLHL6), and Ras association domain family member 1 (RASSF1) in a sample from the subject, wherein: hypomethylation of the gene or fragment thereof in the sample indicates that the subject will be responsive to immunotherapy; or hypermethylation of the gene or fragment thereof in the sample indicates that the subject will be unresponsive to immunotherapy; or (B) (i) determining a methylation profile of two or more genes or fragments thereof selected from the group consisting of IN A, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in the sample from the subject; (ii) comparing the methylation profile as determined in (i) with a reference methylation profile, said reference methylation profile representing a known responsiveness to immunotherapy; (iii) finding a deviation or no deviation of the methylation profile as determined in (i) from said reference methylation profile; and (iv) attributing said finding of deviation or no deviation to a particular prediction of responsiveness of the subject to immunotherapy.

Description

METHOD FOR PREDICTING RESPONSIVENESS TO IMMUNOTHERAPY FIELD OF THE INVENTION

This invention applies to the area of cancer diagnostics and therapeutics. In particular, the present invention relates to methods for determining responsiveness to immunotherapy, such as treatment with an immune checkpoint inhibitor, in a subject having a neoplastic disease.

BACKGROUND OF THE INVENTION

Immuno-oncology is a recent and growing field on the frontier of cancer therapy. Contrary to cancer therapies that directly target malignant cells, immuno-oncology therapies stimulate the body's immune system to target and attack the tumor, which is otherwise invisible to, or inhibiting the immune response. To this end, several methods have been developed. First, passive therapies facilitate the body's existing immune response and do not require direct participation of the immune cells, typically through binding and modifying the intracellular signaling of surface receptors. Immune checkpoint inhibitors, perhaps the most well-known of immuno-oncology therapies, are an example of passive therapies. Immune checkpoint inhibitors include monoclonal antibodies that block binding of the tumor cell at receptors that inactivate the T-cell. Second, active therapies direct immune cells to attack tumor-associated antigens, stimulating them to recognize, and destroy the cancer.

The immune response is highly complex, and many factors can influence the outcome of immunotherapies. In addition, response patterns to immunotherapy such as treatment with immune checkpoint inhibitors (e.g., PD-L1/PD1 inhibitors) are strikingly different from those of chemotherapy or targeted therapies. Targeted therapies cause fast tumor remissions but with prompt acquisition of resistance. In contrast, patients who respond to immune checkpoint inhibitors show significant and durable responses, although a delay of even months can be observed. From a clinical point of view there is a strong need to identify biomarkers that can predict the outcome of immunotherapy, such as PD-L1/PD1 inhibitors. Since therapies with immune checkpoint inhibitors are very expensive, there is a great need in the art to identify biomarkers which are predictive of patient responsiveness to such therapies in order to appropriately determine an efficacious and cost- effective course of therapeutic intervention.

In view thereof, there remains a need in the art for further and/or improved companion diagnostics to immunotherapy, such as further and/or improved companion diagnostics to treatment with immunotherapy agents such as immune checkpoint inhibitors. SUMMARY OF THE INVENTION

Through extensive research, the present inventors have found that determining the methylation level of one or more genes or a fragment thereof selected from the group consisting of internexin neuronal intermediate filament protein alpha (ΓΝΑ), protein tyrosine phosphatase, receptor type C- associated protein (PTPRCAP), semaphorin 3B (SEMA3B), kelch-like family member 6 (KLHL6), and Ras association domain family member 1 (RASSF1), can be used: 1) as a marker for predicting responsiveness to immunotherapy in a subject having a neoplastic disease; and/or 2) as a marker for predicting survival or for prognosis in a subject having a neoplastic disease.

As corroborated by the experimental section, which illustrates certain representative embodiments of the invention, the present inventors demonstrated that hypomethylation of the ΓΝΑ gene or fragment thereof in a neoplastic tissue sample from a human subject having a neoplastic disease, allows to predict responsiveness of the subject to immunotherapy, and thereby the need of treatment of the subject with immunotherapy.

Accordingly, a first aspect of the invention relates to a method for predicting responsiveness to immunotherapy in a subject having a neoplastic disease, the method comprising determining the methylation level of a gene or a fragment thereof selected from the group consisting of internexin neuronal intermediate filament protein alpha (ΓΝΑ), protein tyrosine phosphatase, receptor type C- associated protein (PTPRCAP), semaphorin 3B (SEMA3B), kelch-like family member 6 (KLHL6), and Ras association domain family member 1 (RASSFl) in a sample from the subject, wherein: - hypomethylation of the gene or fragment thereof in the sample indicates that the subject will be responsive to immunotherapy; or

hypermethylation of the gene or fragment thereof in the sample indicates that the subject will be unresponsive to immunotherapy.

Another aspect of the invention relates to a method for predicting responsiveness to immunotherapy in a subject having a neoplastic disease, the method comprising:

(i) determining a methylation profile of two or more genes or fragments thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl in the sample from the subject;

(ii) comparing the methylation profile as determined in (i) with a reference methylation profile, said reference methylation profile representing a known responsiveness to immunotherapy;

(iii) finding a deviation or no deviation of the methylation profile as determined in (i) from said reference methylation profile; and (iv) attributing said finding of deviation or no deviation to a particular prediction of responsiveness of the subject to immunotherapy.

Preferably, an aspect provides a method for predicting responsiveness to immunotherapy in a subject having a neoplastic disease, the method comprising determining the methylation level of ΓΝΑ gene or a fragment thereof in a sample from the subject, wherein:

hypomethylation of the INA gene or fragment thereof in the sample indicates that the subject will be responsive to immunotherapy; or

hypermethylation of the INA gene or fragment thereof in the sample indicates that the subject will be unresponsive to immunotherapy.

The methods illustrating the principles of the present invention advantageously allow determining the responsiveness to immunotherapy of a subject having a neoplastic disease, and to identify those subjects to be treated with an immunotherapy agent, such as an immune checkpoint inhibitor. The present methods advantageously allow determining responsiveness to immunotherapy of a subject having a neoplastic disease in formalin- fixed paraffin-embedded (FFPE) or fresh-frozen samples, which are routinely prepared in the clinic.

As illustrated in the examples, the present inventors have further found that determining a methylation profile of two or more genes selected form the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 allows predicting survival in a human subject having a neoplastic disease, such as in particular skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, or breast cancer such as in particular HER2 -positive breast cancer, luminal breast cancer , or triple- negative (TN) breast cancer.

Hence, a further aspect relates to a method for predicting survival or for prognosis in a subject having a neoplastic disease, the method comprising determining the methylation level of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from the subject, wherein:

hypomethylation of the gene or fragment thereof in the sample indicates an increased chance of survival of the subject or indicates a favourable prognosis; or

hypermethylation of the gene or fragment thereof in the sample indicates a reduced chance of survival of the subject or indicates an unfavourable prognosis.

Another aspect relates to a method for predicting survival or for prognosis in a subject having a neoplastic disease, the method comprising: (ί') determining a methylation profile of two or more genes or fragments thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in a sample from the subject;

(ϋ') comparing the methylation profile as determined in (i') with a reference methylation profile, said reference methylation profile representing a known chance of survival or a known prognosis;

(iii') finding a deviation or no deviation of the methylation profile as determined in (i') from said reference methylation profile; and

(iv') attributing said finding of deviation or no deviation to a particular prediction of chance of survival or prognosis.

The present methods advantageously allow to predict survival in a subject having a neoplastic disease, such as in particular in a subject having skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, or breast cancer. The present methods advantageously allow predicting survival in a subject in FFPE or fresh-frozen samples, which are routinely prepared in the clinic.

A further aspect relates to an immunotherapy agent for use in a method of treating a neoplastic disease in a subject, wherein the subject has been selected as having a neoplastic disease characterised by hypomethylation of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

A further aspect relates to an immunotherapy agent for use in a method of treating a neoplastic disease in a subject, wherein the subject has been selected as responsive to immunotherapy by a method as taught herein.

The present medical uses and methods of treatment advantageously allow, for instance a medical practitioner such as an oncologist, to treat only those subjects with an immunotherapy agent that are likely to clinically benefit from such treatment.

Those skilled in the art will recognize the many other effects and advantages of the present methods, uses or products, and the numerous possibilities for end uses of the present invention from the detailed description and examples provided below.

DESCRIPTION OF THE DRAWINGS FIG. 1 represents a forest plot showing the log2 value of the hazard ratios (HR) and confidence intervals (CI) for prediction of survival outcome in univariate Cox models for the MeTIL score (grey) or pathological tumor-infiltrating lymphocyte counts (PaTIL, black) in different TCGA cancer types. Stars indicate statistical significance (p < 0.05). BLCA, bladder urothelial carcinoma; BRCA, breast invasive carcinoma; CESC, cervical squamous cell carcinoma and endocervical adenocarcinoma; COREAD, colon and rectum adenocarcinoma; ESCA, esophageal carcinoma; HNSC, head and neck squamous cell carcinoma; KIRP, kidney renal papillary cell carcinoma; LIHC, liver hepatocellular carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; OV, ovarian serous cystadenocarcinoma; PAAD, pancreatic adenocarcinoma; PCPG, pheochromocytoma and paraganglioma; PRAD, prostate adenocarcinoma; SARC, sarcoma; SKCM, skin cutaneous melanoma; STAD, stomach adenocarcinoma; TGCT, testicular germ cell tumors; THCA, thyroid carcinoma; THYM, thymoma; UCEC, uterine corpus endometrial carcinoma.

FIG. 2 represents a forest plot showing the log2 value of the hazard ratios (HR) and confidence intervals (CI) for prediction of survival outcome in multivariate Cox models for the MeTIL score (grey) or pathological tumor-infiltrating lymphocyte counts (PaTIL, black) in different TCGA cancer types. Stars indicate statistical significance (p < 0.05). Abbreviations as in FIG. 1.

FIG. 3 represents a heat map displaying the results of an unsupervised hierarchical clustering analysis of TCGA skin cutaneous melanomas based on Beta-values of the MeTIL markers. A hypomethylated, an intermediate methylated and a hypermethylated cluster appeared, which are associated with differences in subtypes, PaTIL, and methylation profiles (MeTIL scores). Differences between methylation clusters were assessed with a one-way ANOVA or Chi2 test. P values are shown in the upper right corner of the heat map.

FIG. 4 represents Kaplan Meier survival curves for the three methylation clusters defined in the heat map of FIG. 3.

FIG. 5 represents MeTIL scores grouped by three melanoma subtypes: immune, keratin and microphthalmia-associated transcription factor-low (MITF-low). Differences in MeTIL scores between melanoma subtypes were assessed with a one-way ANOVA test and the P value is shown in the upper right corner of the plot.

FIG. 6 represents a graph illustrating receiver operating curves (ROC) and area under the curve (AUC) values of the MeTIL score (grey) and tumor-infiltrating lymphocytes quantified with pathology (PaTIL, black) in 84 melanoma patients from the TCGA that underwent treatment with immunotherapy.

FIG. 7 represents a forest plot showing the log2 value of the odds ratios (OR) and CI of the MeTIL score (grey), pathological tumor-infiltrating lymphocyte counts (PaTIL, black) and the individual markers of the methylation signature comprising INA, SEMA3B, PTPRCAP, KLHL6, and RASSF1 for prediction of response to immunotherapy in 84 melanoma patients from the TCGA. Asterisk indicates statistical significance (p < 0.05).

DETAILED DESCRIPTION OF THE INVENTION

As used herein, the singular forms "a", "an", and "the" include both singular and plural referents unless the context clearly dictates otherwise.

The terms "comprising", "comprises" and "comprised of as used herein are synonymous with "including", "includes" or "containing", "contains", and are inclusive or open-ended and do not exclude additional, non-recited members, elements or method steps. The terms also encompass "consisting of and "consisting essentially of, which enjoy well-established meanings in patent terminology.

The recitation of numerical ranges by endpoints includes all numbers and fractions subsumed within the respective ranges, as well as the recited endpoints.

The terms "about" or "approximately" as used herein when referring to a measurable value such as a parameter, an amount, a temporal duration, and the like, are meant to encompass variations of and from the specified value, such as variations of ± 10% or less, preferably ± 5% or less, more preferably ± 1% or less, and still more preferably ± 0.1% or less of and from the specified value, insofar such variations are appropriate to perform in the disclosed invention. It is to be understood that the value to which the modifier "about" refers is itself also specifically, and preferably, disclosed.

Whereas the terms "one or more" or "at least one", such as one or more members or at least one member of a group of members, is clear per se, by means of further exemplification, the term encompasses inter alia a reference to any one of said members, or to any two or more of said members, such as, e.g., any >3, >4, >5, >6 or >7 etc. of said members, and up to all said members. In another example, "one or more" or "at least one" may refer to 1, 2, 3, 4, 5, 6, 7 or more.

The discussion of the background to the invention herein is included to explain the context of the invention. This is not to be taken as an admission that any of the material referred to was published, known, or part of the common general knowledge in any country as of the priority date of any of the claims.

Throughout this disclosure, various publications, patents and published patent specifications are referenced by an identifying citation. All documents cited in the present specification are hereby incorporated by reference in their entirety. In particular, the teachings or sections of such documents herein specifically referred to are incorporated by reference. Unless otherwise defined, all terms used in disclosing the invention, including technical and scientific terms, have the meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. By means of further guidance, term definitions are included to better appreciate the teaching of the invention. When specific terms are defined in connection with a particular aspect of the invention or a particular embodiment of the invention, such connotation is meant to apply throughout this specification, i.e., also in the context of other aspects or embodiments of the invention, unless otherwise defined.

In the following passages, different aspects or embodiments of the invention are defined in more detail. Each aspect or embodiment so defined may be combined with any other aspect(s) or embodiment(s) unless clearly indicated to the contrary. In particular, any feature indicated as being preferred or advantageous may be combined with any other feature or features indicated as being preferred or advantageous.

Reference throughout this specification to "one embodiment", "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment, but may. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner, as would be apparent to a person skilled in the art from this disclosure, in one or more embodiments. Furthermore, while some embodiments described herein include some but not other features included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention, and form different embodiments, as would be understood by those in the art. For example, in the appended claims, any of the claimed embodiments can be used in any combination.

As corroborated by the experimental section, which illustrates certain representative embodiments of the invention, the inventors identified that the methylation level of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl, for instance the methylation level of ΓΝΑ or a fragment thereof, or the methylation profile of two or more genes or fragments thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl, such as the methylation profile of INA or a fragment thereof, PTPRCAP or a fragment thereof, SEMA3B or a fragment thereof, KLHL6 or a fragment thereof, and RASSFl or a fragment thereof, could be useful as a clinical marker for predicting responsiveness to immunotherapy in a subject having a neoplastic disease.

Accordingly, an aspect relates to a method for predicting responsiveness (or sensitivity or susceptibility) to immunotherapy in a subject having a neoplastic disease, the method comprising determining the methylation level of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from the subject, wherein hypomethylation of the gene or fragment thereof in the sample indicates that the subject will be responsive (or sensitive or susceptible) to immunotherapy. In certain embodiments, hypermethylation of the gene or fragment thereof in the sample indicates that the subject will be unresponsive (or insensitive or unsusceptible) to immunotherapy.

Also provided is thus the use of the methylation level of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl as a biomarker useful for determining responsiveness (or sensitivity or susceptibility) to immunotherapy in a subject having a neoplastic disease, wherein:

hypomethylation of the gene or fragment thereof in the sample indicates that the subject will be responsive (or sensitive or susceptible) to immunotherapy; or

hypermethylation of the gene or fragment thereof in the sample indicates that the subject will be unresponsive (or insensitive or unsusceptible) to immunotherapy.

Certain embodiments provide a method as taught herein for indicating immunotherapy as a suitable treatment for a neoplastic disease in a subject, the method comprising determining the methylation level of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from the subject, wherein:

hypomethylation of the gene or fragment thereof in the sample indicates immunotherapy as a suitable treatment; or

hypermethylation of the gene or fragment thereof in the sample indicates immunotherapy as an unsuitable treatment.

In certain embodiments, if hypomethylation of the gene or fragment thereof in the sample is determined, immunotherapy is indicated as a suitable treatment, as the subject will clinically benefit from the treatment. In certain embodiments, if hypermethylation of the gene or fragment thereof in the sample is determined, immunotherapy is not indicated as a suitable treatment, as the subject will have no clinical benefit from the treatment.

Certain embodiments provide a method as taught herein for predicting an immunotherapy outcome in a subject having a neoplastic disease, the method comprising determining the methylation level of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from the subject, wherein:

hypomethylation of the gene or fragment thereof in the sample indicates a favourable prognosis; or hy ermethylation of the gene or fragment thereof in the sample indicates an unfavourable prognosis.

Certain embodiments relate to a method for the stratification of subjects having a neoplastic disease, the method comprising determining the methylation level of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in a sample from the subject, wherein:

hypomethylation of the gene or fragment thereof in the sample indicates that the subject will be responsive to immunotherapy; or

The present methods may thus allow to predict an immunotherapy outcome or stratify patients having a neoplastic disease for immunotherapy based on their methylation level. Based on the prediction or classification, the treatment of the neoplastic disease can be adapted.

In certain embodiments of the methods as taught herein, the method may comprise, consist essentially of, or consist of determining the methylation level of the ΓΝΑ gene or fragment thereof. In certain embodiments, the method may comprise, consist essentially of, or consist of determining the methylation level of the ΓΝΑ gene or fragment thereof in the sample from the subject, wherein: hypomethylation of the INA gene or fragment thereof in the sample indicates that the subject will be responsive to immunotherapy; or

- hypermethylation of the INA gene or fragment thereof in the sample indicates that the subject will be unresponsive to immunotherapy.

Accordingly, an aspect relates to a method for predicting or determining responsiveness (or sensitivity or susceptibility) to immunotherapy in a subject having a neoplastic disease, the method comprising, consisting essentially of, or consisting of determining the methylation level of INA gene or a fragment thereof in a sample from the subject, wherein hypomethylation of the INA gene or fragment thereof in the sample indicates that the subject will be responsive (or sensitive or susceptible) to immunotherapy. In certain embodiments, hypermethylation of the INA gene or fragment thereof in the sample indicates that the subject will be unresponsive (or insensitive or unsusceptible) to immunotherapy.

Also provided is the use of the methylation level of INA gene or a fragment thereof as a biomarker useful for determining responsiveness (or sensitivity or susceptibility) to immunotherapy in a subject having a neoplastic disease, wherein: hy omethylation of the INA gene or fragment thereof in the sample indicates that the subject will be responsive (or sensitive or susceptible) to immunotherapy; or

hypermethylation of the INA gene or fragment thereof in the sample indicates that the subject will be unresponsive (or insensitive or unsusceptible) to immunotherapy.

Certain embodiments provide a method as taught herein for indicating immunotherapy as a suitable treatment for a neoplastic disease in a subject, the method comprising determining the methylation level of INA gene or a fragment thereof in a sample from the subject, wherein:

hypomethylation of the INA gene or fragment thereof in the sample indicates immunotherapy as a suitable treatment; or

hypermethylation of the INA gene or fragment thereof in the sample indicates immunotherapy as an unsuitable treatment.

In certain embodiments, if hypomethylation of the INA gene or fragment thereof in the sample is determined, immunotherapy is indicated as a suitable treatment. In certain embodiments, if hypermethylation of the INA gene or fragment thereof in the sample is determined, immunotherapy is not indicated as a suitable treatment, as the subject will have no clinical benefit from the treatment.

Certain embodiments provide a method as taught herein for predicting an immunotherapy outcome in a subject having a neoplastic disease, the method comprising determining the methylation level of INA gene or a fragment thereof in a sample from the subject, wherein:

hypomethylation of the INA gene or fragment thereof in the sample indicates a favourable prognosis; or

hypermethylation of the INA gene or fragment thereof in the sample indicates an unfavourable prognosis.

Certain embodiments relate to a method for the stratification of subjects having a neoplastic disease, the method comprising determining the methylation level of INA gene or a fragment thereof in a sample from the subject, wherein:

An aspect relates to a method for predicting responsiveness to immunotherapy in a subject having a neoplastic disease, the method comprising: (i) determining a methylation profile of two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl in the sample from the subject;

(iii) finding a deviation or no deviation of the methylation profile as determined in (i) from said reference methylation profile; and

(iv) attributing said finding of deviation or no deviation to a particular prediction of responsiveness of the subject to immunotherapy.

Further provided is the use of the methylation profile of two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl as a biomarker useful for determining responsiveness to immunotherapy in a subject having a neoplastic disease.

In certain embodiments of the methods as taught herein, the methods may comprise, consist essentially of, or consist of determining the methylation profile of the ΓΝΑ gene or fragment thereof, the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSFl gene or fragment thereof.

Accordingly, a preferred aspect relates to a method for predicting or determining responsiveness (or sensitivity or susceptibility) to immunotherapy in a subject having a neoplastic disease, the method comprising:

(i) determining a methylation profile of the INA gene or fragment thereof, the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSFl gene or fragment thereof in the sample from the subject;

Further provided is the use of the methylation profile of the ΓΝΑ gene or fragment thereof, the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSF1 gene or fragment thereof as a biomarker useful for determining responsiveness to immunotherapy in a subject having a neoplastic disease.

The phrases "determining responsiveness" and "predicting responsiveness" may be used interchangeably herein.

The terms "predicting", "prediction" or "predictive" as used herein refers to an advance declaration, indication or foretelling of a response or reaction to a therapy in a subject not (yet) having been treated with the therapy. For example, a prediction of responsiveness (or sensitivity or susceptibility) to immunotherapy in a subject may indicate that the subject will respond or react to the immunotherapy, for example within a certain time period, e.g., so that the subject will have a clinical benefit from the immunotherapy. A prediction of unresponsiveness (or insensitivity or insusceptibility) to immunotherapy in a subject may indicate that the subject will minimally or not respond or react to the immunotherapy, for example within a certain time period, e.g., so that the subject will have no clinical benefit from the immunotherapy.

The terms "responsiveness", "sensitivity" or "susceptibility" may be used interchangeably herein and refer to the quality that predisposes a subject having a neoplastic disease to be responsive or reactive to an immunotherapy. A subject is "responsive", "sensitive", or "susceptible" (which terms are used interchangeably) to immunotherapy (i.e., treatment with an immunotherapy agent) if the subject will have a clinical benefit from the treatment. A neoplastic tissue, including a tumor, is "responsive", "sensitive", or "susceptible" to an immunotherapy if the proliferation rate of the neoplastic tissue is inhibited as a result of contact with the immunotherapy, compared to the proliferation rate of the neoplastic tissue in the absence of contact with the immunotherapy, e.g. treatment with an immune checkpoint inhibitor.

The terms "unresponsiveness", "insensitivity", "insusceptibility" or "resistance" may be used interchangeably herein and refer to the quality that predisposes a subject having a neoplastic disease to a minimal (e.g. insignificant) or no response to an immunotherapy. A subject is "unresponsive", "insensitive", "unsusceptible" or "resistant" (which terms are used interchangeably) to an immunotherapy (i.e., treatment with an immunotherapy agent) if the subject will have no clinical benefit from the treatment. A neoplastic tissue, including a tumor, is "unresponsive", "insensitive", "unsusceptible" or "resistant" to an immunotherapy if the proliferation rate of the neoplastic tissue is not inhibited, or inhibited to a very low (e.g. therapeutically insignificant) degree, as a result of contact with the immunotherapy, compared to the proliferation rate of the neoplastic tissue in the absence of contact with the immunotherapy, e.g. an immune checkpoint inhibitor. The methods as disclosed herein may allow to make a prediction that a subject having a neoplastic disease will be responsive to immunotherapy or will be unresponsive to immunotherapy. This may in certain embodiments include predicting that a subject having a neoplastic disease will have a comparatively low probability (e.g., less than 50%, less than 40%, less than 30%, less than 20% or less than 10%>) of being responsive to immunotherapy; or that a subject having a neoplastic disease will have a comparatively high probability (e.g., at least 50%, at least 60%, at least 70%, at least 80%) or at least 90%) of being responsive to immunotherapy.

The term "outcome" generally refers to the evaluation undertaken to assess the results or consequences of management and procedures (i.e., the interventions) used in combatting a disease in order to determine the efficacy, effectiveness, safety, practicability, etc., of these interventions, e.g. in individual cases or series. The term "outcome" as used herein refers to a process of assessing the consequences of treating an individual afflicted with a neoplastic disease with immunotherapy, i.e. predicting whether said individual is likely to respond or not to the immunotherapy. The methods as taught herein provide a prediction of how a patient's neoplastic disease will progress when treated with immunotherapy and whether there is chance of recovery.

As demonstrated by the examples, which illustrate certain representative embodiments of the invention, the inventors further identified the methylation profile, such as in particular the MeTIL score, of the ΓΝΑ gene or a fragment thereof, the PTPRCAP gene or a fragment thereof, the SEMA3B gene or a fragment thereof, the KLHL6 gene or a fragment thereof, and the RASSF1 gene or a fragment thereof as a clinical marker for predicting survival or for prognosis in a subject having a neoplastic disease, such as in particular skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, or breast cancer, such as HER2 -positive breast cancer, luminal breast cancer, and TN breast cancer.

Accordingly, an aspect provides a method for predicting survival or for prognosis in a subject having a neoplastic disease, the method comprising:

(Α') determining the methylation level of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in a sample from the subject, wherein:

- hypomethylation of the gene or fragment thereof in the sample indicates an increased chance of survival of the subject or indicates a favourable prognosis; or

hypermethylation of the gene or fragment thereof in the sample indicates a reduced chance of survival of the subject or indicates an unfavourable prognosis; or (Β')

(ί') determining a methylation profile of two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from the subject;

Further provided is the use of the methylation profile of two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl as a biomarker useful for predicting survival or for prognosis in a subject having a neoplastic disease.

Preferably, an aspect provides a method for predicting survival or for prognosis in a subject having a neoplastic disease, the method comprising:

(i') determining a methylation profile of the INA gene or a fragment thereof, the PTPRCAP gene or a fragment thereof, the SEMA3B gene or a fragment thereof, the KLHL6 gene or a fragment thereof, and the RASSFl gene or a fragment thereof in a sample from the subject;

Also provided is thus the use of the methylation profile of INA gene or a fragment thereof, PTPRCAP gene or a fragment thereof, SEMA3B gene or a fragment thereof, KLHL6 gene or a fragment thereof, and RASSFl gene or a fragment thereof as a biomarker useful for predicting survival or for prognosis in a subject having a neoplastic disease, such as in particular skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, or breast cancer.

In certain embodiments, the survival may comprise overall survival (OS), disease-free survival (DFS), or disease-specific survival (DSS).

Overall survival or survival rate measures death due to any cause (a disease in question and any other reason), but is not specific for the disease in question. The terms "overall survival" or "survival rate" refers to the percentage of subjects in a study or treatment group who have survived for a defined period of time. This percentage is usually reported together with the period of time since the date of diagnosis or treatment.

Disease- free survival (DFS) denotes the chances of staying free of a disease after a particular treatment of a group of individuals suffering from the disease. The term "disease-free survival" refers to the percentage of subjects in a study or treatment group who are likely to be free of disease after a defined period of time. The time period usually begins at the time of diagnosis, at the start of treatment, or from the day of surgery, and ends at the time of local or distant relapse. Disease- free survival rates are an indication of how effective a particular treatment is. Very often, two treatment strategies are compared on the basis of the disease-free survival that is achieved in similar groups of patients. Disease-free survival is often used with the term overall survival when cancer survival is described.

The term "disease-specific survival" (DSS) refers to the percentage of subjects in a study or treatment group who have not died from a specific disease in a defined period of time. The time period usually begins at the time of diagnosis or at the start of treatment and may end at the time of death. Patients who died from causes other than the disease being studied are not counted in this measurement.

The term "prognosis" generally refer to an anticipation on the progression of a disease or condition and the prospect (e.g., the probability, duration, and/or extent) of recovery. A good prognosis of the diseases or conditions taught herein may generally encompass anticipation of a satisfactory partial or complete recovery from the diseases or conditions, preferably within an acceptable time period. A good prognosis of such may more commonly encompass anticipation of not further worsening or aggravating of such, preferably within a given time period. A poor prognosis of the diseases or conditions as taught herein may generally encompass anticipation of a substandard recovery and/or unsatisfactorily slow recovery, or to substantially no recovery or even further worsening of such.

The term "neoplastic disease" generally refers to any disease or disorder characterized by neoplastic cell growth and proliferation, whether benign (not invading surrounding normal tissues, not forming metastases), pre-malignant (pre-cancerous), or malignant (invading adjacent tissues and capable of producing metastases). The term neoplastic disease generally includes all transformed cells and tissues and all cancerous cells and tissues. Neoplastic diseases or disorders include, but are not limited to abnormal cell growth, benign tumors, premalignant or precancerous lesions, malignant tumors, and cancer. Examples of neoplastic diseases or disorders are benign, pre-malignant, or malignant neoplasms located in any tissue or organ, such as in the prostate, colon, abdomen, bone, breast, digestive system, liver, pancreas, peritoneum, endocrine glands (adrenal, parathyroid, pituitary, testicles, ovary, thymus, thyroid), eye, head and neck, nervous (central and peripheral), lymphatic system, pelvic, skin, soft tissue, spleen, thoracic, or urogenital tract.

In certain embodiments of the methods or uses as taught herein, the neoplastic disease may be a tumor or may be characterized by the presence of a tumor.

As used herein, the terms "tumor" or "tumor tissue" refer to an abnormal mass of tissue that results from excessive cell division. A tumor or tumor tissue comprises tumor cells which are neoplastic cells with abnormal growth properties and no useful bodily function. Tumors, tumor tissue and tumor cells may be benign, pre-malignant or malignant, or may represent a lesion without any cancerous potential. A tumor or tumor tissue may also comprise tumor-associated non-tumor cells, e.g., vascular cells which form blood vessels to supply the tumor or tumor tissue. Non-tumor cells may be induced to replicate and develop by tumor cells, for example, the induction of angiogenesis in a tumor or tumor tissue.

In certain embodiments of the methods or uses as taught herein, the neoplastic disease may be cancer.

As used herein, the term "cancer" refers to a malignant neoplasm characterized by deregulated or unregulated cell growth. The term "cancer" includes primary malignant cells or tumors (e.g., those whose cells have not migrated to sites in the subject's body other than the site of the original malignancy or tumor) and secondary malignant cells or tumors (e.g., those arising from metastasis, the migration of malignant cells or tumor cells to secondary sites that are different from the site of the original tumor). The term "metastatic" or "metastasis" generally refers to the spread of a cancer from one organ or tissue to another non-adjacent organ or tissue. The occurrence of the neoplastic disease in the other non-adjacent organ or tissue is referred to as metastasis.

Examples of cancer include but are not limited to carcinoma, lymphoma, blastoma, sarcoma, and leukemia or lymphoid malignancies. More particular examples of such cancers include without limitation: squamous cell cancer (e.g., epithelial squamous cell cancer), lung cancer including small-cell lung cancer, non-small cell lung cancer, adenocarcinoma of the lung, squamous carcinoma of the lung and large cell carcinoma of the lung, cancer of the peritoneum, hepatocellular cancer, gastric or stomach cancer including gastrointestinal cancer, pancreatic cancer, glioma, glioblastoma, cervical cancer, ovarian cancer, liver cancer, bladder cancer, hepatoma, breast cancer, colon cancer, rectal cancer, colorectal cancer, endometrial cancer or uterine carcinoma, salivary gland carcinoma, kidney or renal cancer, prostate cancer, vulvar cancer, thyroid cancer, hepatic carcinoma, anal carcinoma, penile carcinoma, as well as CNS cancer, melanoma, head and neck cancer, bone cancer, bone marrow cancer, duodenum cancer, esophageal cancer, thyroid cancer, or hematological cancer.

Other examples of cancers or malignancies include, but are not limited to: Acute Childhood Lymphoblastic Leukemia, Acute Lymphoblastic Leukemia, Acute Lymphocytic Leukemia, Acute Myeloid Leukemia, Adrenocortical Carcinoma, Adult (Primary) Hepatocellular Cancer, Adult (Primary) Liver Cancer, Adult Acute Lymphocytic Leukemia, Adult Acute Myeloid Leukemia, Adult Hodgkin's Disease, Adult Hodgkin's Lymphoma, Adult Lymphocytic Leukemia, Adult Non- Hodgkin's Lymphoma, Adult Primary Liver Cancer, Adult Soft Tissue Sarcoma, AIDS-Related Lymphoma, AIDS-Related Malignancies, Anal Cancer, Astrocytoma, Bile Duct Cancer, Bladder Cancer, Bone Cancer, Brain Stem Glioma, Brain Tumors, Breast Cancer, Cancer of the Renal Pelvis and Urethra, Central Nervous System (Primary) Lymphoma, Central Nervous System Lymphoma, Cerebellar Astrocytoma, Cerebral Astrocytoma, Cervical Cancer, Childhood (Primary) Hepatocellular Cancer, Childhood (Primary) Liver Cancer, Childhood Acute Lymphoblastic Leukemia, Childhood Acute Myeloid Leukemia, Childhood Brain Stem Glioma, Glioblastoma, Childhood Cerebellar Astrocytoma, Childhood Cerebral Astrocytoma, Childhood Extracranial Germ Cell Tumors, Childhood Hodgkin's Disease, Childhood Hodgkin's Lymphoma, Childhood Hypothalamic and Visual Pathway Glioma, Childhood Lymphoblastic Leukemia, Childhood Medulloblastoma, Childhood Non-Hodgkin's Lymphoma, Childhood Pineal and Supratentorial Primitive Neuroectodermal Tumors, Childhood Primary Liver Cancer, Childhood Rhabdomyosarcoma, Childhood Soft Tissue Sarcoma, Childhood Visual Pathway and Hypothalamic Glioma, Chronic Lymphocytic Leukemia, Chronic Myelogenous Leukemia, Colon Cancer, Cutaneous T-Cell Lymphoma, Endocrine Pancreas Islet Cell Carcinoma, Endometrial Cancer, Ependymoma, Epithelial Cancer, Esophageal Cancer, Ewing's Sarcoma and Related Tumors, Exocrine Pancreatic Cancer, Extracranial Germ Cell Tumor, Extragonadal Germ Cell Tumor, Extrahepatic Bile Duct Cancer, Eye Cancer, Female Breast Cancer, Gallbladder Cancer, Gastric Cancer, Gastrointestinal Carcinoid Tumor, Gastrointestinal Tumors, Germ Cell Tumors, Gestational Trophoblastic Tumor, Hairy Cell Leukemia, Head and Neck Cancer, Hepatocellular Cancer, Hodgkin's Disease, Hodgkin's Lymphoma, Hypergammaglobulinemia, Hypopharyngeal Cancer, Intestinal Cancers, Intraocular Melanoma, Islet Cell Carcinoma, Islet Cell Pancreatic Cancer, Kaposi's Sarcoma, Kidney Cancer, Laryngeal Cancer, Lip and Oral Cavity Cancer, Liver Cancer, Lung Cancer, Lymphoproliferative Disorders, Macroglobulinemia, Male Breast Cancer, Malignant Mesothelioma, Malignant Thymoma, Medulloblastoma, Melanoma, Mesothelioma, Metastatic Occult Primary Squamous Neck Cancer, Metastatic Primary Squamous Neck Cancer, Metastatic Squamous Neck Cancer, Multiple Myeloma, Multiple Myeloma/Plasma Cell Neoplasm, Myelodysplasia Syndrome, Myelogenous Leukemia, Myeloid Leukemia, Myeloproliferative Disorders, Nasal Cavity and Paranasal Sinus Cancer, Nasopharyngeal Cancer, Neuroblastoma, Non-Hodgkin's Lymphoma During Pregnancy, Non-melanoma Skin Cancer, Non-Small Cell Lung Cancer, Occult Primary Metastatic Squamous Neck Cancer, Oropharyngeal Cancer, Osteo- /Malignant Fibrous Sarcoma, Osteosarcoma/Malignant Fibrous Histiocytoma, Osteosarcoma/Malignant Fibrous Histiocytoma of Bone, Ovarian Epithelial Cancer, Ovarian Germ Cell Tumour, Ovarian Low Malignant Potential Tumor, Pancreatic Cancer, Paraganglioma, Paraproteinemias, Purpura, Parathyroid Cancer, Penile Cancer, Pheochromocytoma, Pituitary Tumor, Plasma Cell Neoplasm/Multiple Myeloma, Primary Central Nervous System Lymphoma, Primary Liver Cancer, Prostate Cancer, Rectal Cancer, Renal Cell Cancer, Renal Pelvis and Urethra Cancer, Retinoblastoma, Rhabdomyosarcoma, Salivary Gland Cancer, Sarcoidosis Sarcomas, Sezary Syndrome, Skin Cancer, Small Cell Lung Cancer, Small Intestine Cancer, Soft Tissue Sarcoma, Squamous Neck Cancer, Stomach Cancer, Supratentorial Primitive Neuroectodermal and Pineal Tumors, T-Cell Lymphoma, Testicular Cancer, Thymoma, Thyroid Cancer, Transitional Cell Cancer of the Renal Pelvis and Urethra, Transitional Renal Pelvis and Urethra Cancer, Trophoblastic Tumours, Urethra and Renal Pelvis Cell Cancer, Urethral Cancer, Uterine Cancer, Uterine Sarcoma, Vaginal Cancer, Visual Pathway and Hypothalamic Glioma, Vulvar Cancer, Waldenstrom's Macroglobulinemia, or Wilms' Tumour.

In certain embodiments, the tumor, including any metastases of the tumor, may be of epithelial or melanocyte origin. In certain embodiments, the tumor, including any metastases of the tumor, may originate from chromaffin cells, ganglia of the sympathetic nervous system, follicular thyroid cells or parafollicular thyroid cells.

Tumors of epithelial origin include any tumors originated from epithelial tissue in any of several sites, such as without limitation skin, lung, intestine, colon, breast, bladder, head and neck (including lips, oral cavity, salivary glands, nasal cavity, nasopharynx, paranasal sinuses, pharynx, throat, larynx, and associated structures), esophagus, thyroid, kidney, liver, pancreas, bladder, penis, testes, prostate, vagina, cervix, or anus.

In certain embodiments, the tumor may be a carcinoma, including any malignant neoplasm originated from epithelial tissue in any of several sites, such as without limitation skin, lung, intestine, colon, breast, bladder, head and neck (including lips, oral cavity, salivary glands, nasal cavity, nasopharynx, paranasal sinuses, pharynx, throat, larynx, and associated structures), esophagus, thyroid, kidney, liver, pancreas, bladder, penis, testes, prostate, vagina, cervix, or anus. In certain embodiments, the tumor may be thyroid carcinoma.

In certain embodiments, the tumor may be a squamous cell carcinoma (SCC). SCC may include without limitation SCC originated from skin, head and neck (including lips, oral cavity, salivary glands, nasal cavity, nasopharynx, paranasal sinuses, pharynx, throat, larynx, and associated structures), thyroid, esophagus, lung, penis, prostate, vagina, cervix, anus, or bladder. In certain embodiments, the tumor may be lung squamous cell carcinoma, or head and neck squamous cell carcinoma.

Tumors of melanocyte origin include any tumors originated from melanocytes in any of several sites, such as without limitation skin, mouth, eyes, or small intestine.

In certain embodiments, the tumor may be a melanoma, including any malignant neoplasm originated from melanocytes in any of several sites, such as without limitation skin, mouth, eyes, or small intestine. In certain embodiments, the tumor may be skin cutaneous melanoma.

Tumors originating from chromaffin cells include pheochromocytoma. Tumors originating from ganglia of the sympathetic nervous system include paraganglioma. Tumors originating from follicular or parafollicular thyroid cells include thymoma.

In certain embodiments, the tumor may be pheochromocytoma, paraganglioma, or thymoma.

In certain embodiments of the methods or uses as taught herein, the neoplastic disease may be selected from the group consisting of skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, and breast cancer. In certain embodiments of the methods or uses as taught herein, the neoplastic disease is HER2 -positive breast cancer, luminal breast cancer, or TN breast cancer. In certain embodiments of the methods or uses as taught herein, the neoplastic disease may be selected from the group consisting of skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, HER2 -positive breast cancer, luminal breast cancer, and TN breast cancer. In certain embodiments of the methods or uses as taught herein, the neoplastic disease may be selected from the group consisting of skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, and thymoma. As illustrated in the example section, the methods as taught herein advantageously allow predicting responsiveness to immunotherapy or predicting survival in subjects having skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, or breast cancer, such as in particular HER2 -positive breast cancer, luminal breast cancer, and TN breast cancer. In certain embodiments of the methods or uses as taught herein, the neoplastic disease is not breast cancer.

In certain embodiments of the methods or uses as taught herein, the neoplastic disease may be pheochromocytoma, paraganglioma, thyroid carcinoma, or thymoma. Advantageously, the present method allows for the first time to predict survival or to determine a prognostic value related to tumor infiltrating lymphocytes (TILs) in a subject having pheochromocytoma, paraganglioma, thyroid carcinoma, and thymoma.

In certain preferred embodiments of the methods or uses as taught herein, the neoplastic disease may be melanoma, such as skin cutaneous melanoma.

Accordingly, certain embodiments provide a method for predicting responsiveness to immunotherapy in a subject having a melanoma, such as skin cutaneous melanoma, the method comprising determining the methylation level of ΓΝΑ gene or a fragment thereof in a melanoma tissue sample from the subject, wherein:

As illustrated in the examples, which illustrate certain representative embodiments of the invention, the inventors further identified that the methylation profile of the INA gene or a fragment thereof, the PTPRCAP gene or a fragment thereof, the SEMA3B gene or a fragment thereof, the KLHL6 gene or a fragment thereof, and the RASSFl gene or a fragment thereof allow to distinguish melanoma subtypes, namely immune subtype melanoma versus keratin subtype or microphthalmia- associated transcription factor-low (MITF-low) subtype melanoma.

Hence, an aspect provides a method for distinguishing melanoma subtypes in a subject having a melanoma, such as skin cutaneous melanoma, the method comprising determining the MeTIL score as taught herein of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a melanoma tissue sample from the subject, wherein:

a high MeTIL score as taught herein of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP,

SEMA3B, KLHL6, and RASSFl in the sample indicates that the subject has an immune subtype melanoma; or a low MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in the sample indicates that the subject has a keratin subtype melanoma or a MITF-low subtype melanoma.

Advantageously, the methods as taught herein thus allow to distinguish melanoma subtypes and to treat only patients with an immune subtype melanoma, which will be sensitive to and clinically benefit from treatment with an immunotherapy agent.

The wording "immune subtype melanoma" refers to a subtype of melanoma characterised by a significant number of overexpressed genes associated with immune cell subsets (T cells, B cells, and NK cells), immune signaling molecules, co-stimulatory and co-inhibitory immune checkpoint proteins, cytokines, chemokines, and corresponding receptors. Patients with regionally metastatic tumors in this subclass show more favourable post-accession survival than those in the "keratin" and "MITF-low" clusters (TCGA Network, 2015. Cell 161, 1681-1696).

The term "post-accession survival" refers to survival calculated from date of sample accession (collection) to date of last follow-up or death.

The wording "keratin subtype melanoma" refers to a subtype of melanoma characterised by high expression of genes associated with keratins, pigmentation, and epithelium, as well as genes associated with neuronal development or other organ- specific embryologic development. Patients with regionally metastatic tumors within this subtype exhibit worse outcome when compared with stage-matched patients assigned to the "immune" or "MITF-low" cluster, supporting the view that the keratin cluster represents, at least in part, a previously unappreciated but biologically distinct melanoma subtype with adverse prognosis (TCGA Network, 2015. Cell 161, 1681-1696).

The wording "microphthalmia-associated transcription factor-low subtype melanoma" or "MITF- low subtype melanoma" refers to a subtype of melanoma characterised by low expression of genes associated with pigmentation and epithelial expression, including several MITF target genes and genes involved in immunomodulation, adhesion, migration, and extracellular matrix. This group is resistant to targeted therapy (TCGA Network, 2015. Cell. 161, 1681-1696; Jonsson et al., 2010, Clin Cancer Res, 16, 3356-33672015; Jonsson et al., 2015, Oncotarget, 6, 12297-12309).

The term "tumor cell" as used throughout this specification broadly encompasses any neoplastic cell, whether benign, pre- malignant (p re-cancerous) or malignant. The term encompasses inter alia cancer cells, including primary and secondary malignant cells, circulating tumor cells (CTCs), disseminated tumor cells (DTCs), and metastatic tumor cells. The terms "sample" or "biological sample" as used throughout this specification include any biological specimen obtained (isolated, removed) from a subject. Samples may include without limitation organ tissue (e.g., primary or metastatic tumor tissue), whole blood, plasma, serum, whole blood cells, red blood cells, white blood cells (e.g., peripheral blood mononuclear cells), saliva, urine, stool (feces), tears, sweat, sebum, nipple aspirate, ductal lavage, tumor exudates, synovial fluid, cerebrospinal fluid, lymph, fine needle aspirate, amniotic fluid, any other bodily fluid, exudate or secretory fluid, cell lysates, cellular secretion products, inflammation fluid, semen and vaginal secretions. Preferably, a sample may be readily obtainable by non-invasive or minimally invasive methods, such as blood collection ('liquid biopsy'), urine collection, feces collection, tissue (e.g., tumor tissue) biopsy or fine-needle aspiration, allowing the provision / removal / isolation of the sample from a subject. The term "tissue" as used herein encompasses all types of cells of the body including cells of organs but also including blood and other body fluids recited above. The tissue may be healthy or affected by pathological alterations, e.g., tumor tissue. The tissue may be from a living subject or may be cadaveric tissue.

Particularly useful samples are those known to comprise, or expected or predicted to comprise, or known to potentially comprise, or expected or predicted to potentially comprise tumor cells.

Any suitable weight or volume of a sample may be removed from a subject for analysis. Without limitation, a liquid sample may have a volume between 1 ml and 20 ml, such as 5 ml, 7.5 ml, 10 ml, 15 ml or 20 ml. A solid sample may have a weight of between 1 g and 20 g, such as 5 g, 7.5 g, 10 g, 15 g or 20 g.

The biological sample may be any sample in which the methylation level of the relevant gene(s) can be determined. Preferably, the biological sample is a neoplastic tissue sample, such as a tumor sample, e.g., a primary or metastatic tumor sample. The biological sample may also be derived from a biological fluid or body fluid, for example, whole blood, blood, urine, lymph fluid, serum, plasma, nipple aspirate, ductal fluid, and tumor exudate. It has been shown in the literature that cancer or tumor cells often release genomic DNA in circulating or other bodily fluids. Since said genomic DNA has the same methylation profile of the DNA inside the tumor or cancer cell, said methylation profile can be detected in the circulating or other bodily fluid sample. This has for example been reviewed by Qureshi et al., 2010 (Int. J. Surgery 2010, 8:194-198), hereby incorporated by reference in its entirety. In certain embodiments, the sample is a body fluid comprising neoplastic cells.

In certain embodiments of the methods or uses as taught herein, the sample is a neoplastic tissue sample. In certain embodiments, the neoplastic tissue sample is a neoplastic tissue biopsy or neoplastic tissue fine-needle aspirate. In certain embodiments, the neoplastic tissue sample is resected neoplastic tissue.

In certain embodiments of the methods or uses as taught herein, the sample is tumor biopsy or tumor fine-needle aspirate, for example biopsy or fine -needle aspirate from primary or metastatic tumor tissue. In certain embodiments of the methods or uses as taught herein, the sample is resected tumor tissue, e.g., resected primary or metastatic tumor tissue.

A sample can be obtained from a subject in any way typically used in clinical settings for obtaining a sample comprising the required cells or nucleic acid including RNA, genomic DNA, mitochondrial DNA, and protein-associated nucleic acids. For example, the sample can be obtained from fresh, frozen, or paraffin-embedded surgical samples or biopsies of an organ or tissue comprising the suitable cells or nucleic acid to be tested. If desired, the sample can be mixed with a fluid or purified or amplified or otherwise treated. For examples, samples may be treated in one or more purification steps in order to increase the purity of the desired cells or nucleic acid in the sample, or they may be examined without any purification steps. Any nucleic acid specimen in purified or non-purified form obtained from such sample can be utilized in the methods as taught herein.

In certain embodiments of the methods or uses as taught herein, the sample may be a formalin- fixed and paraffin-embedded (FFPE) sample or fresh-frozen sample. Preferably, the sample is a FFPE sample. The present methods advantageously allow determining the responsiveness to immunotherapy, such as to an immune checkpoint inhibitor, of a subject, preferably a human subject, having a neoplastic disease in FFPE samples which are routinely used in the clinic.

The terms "subject", "individual" or "patient" are used interchangeably throughout this specification, and typically and preferably denote humans, but may also encompass reference to non-human animals, preferably warm-blooded animals, even more preferably mammals, such as, e.g., non-human primates, rodents, canines, felines, equines, ovines, porcines, and the like. The term "non-human animals" includes all vertebrates, e.g., mammals, such as non-human primates, (particularly higher primates), sheep, dog, rodent (e.g. mouse or rat), guinea pig, goat, pig, cat, rabbits, cows, and non-mammals such as chickens, amphibians, reptiles etc. In certain embodiments, the subject is a non-human mammal. In certain preferred embodiments of the methods or uses as taught herein, the subject is a human subject. In other embodiments, the subject is an experimental animal or animal substitute as a disease model. The term does not denote a particular age or sex. Thus, adult and newborn subjects, as well as fetuses, whether male or female, are intended to be covered. Examples of subjects include humans, dogs, cats, cows, goats, and mice. The term subject is further intended to include transgenic species. Suitable subjects may include without limitation subjects presenting to a physician for a screening for a neoplastic disease, subjects presenting to a physician with symptoms and signs indicative of a neoplastic disease, subjects diagnosed with a neoplastic disease, subjects who have received anticancer therapy, subjects undergoing anti-cancer treatment, and subjects having a neoplastic disease is in remission.

A tumor cell as intended herein may be an animal cell, preferably a warm-blooded animal cell, more preferably a vertebrate cell, yet more preferably a mammalian cell, including humans and non-human mammals, and in certain particularly preferred embodiments a human cell.

The terms "marker" or "biomarker" are widespread in the art and commonly broadly denote a biological molecule, more particularly an endogenous biological molecule, and/or a detectable portion thereof, whose qualitative and/or quantitative evaluation in a tested object (e.g., in or on a cell, cell population, tissue, organ, or organism, e.g., in a biological sample of a subject) is predictive or informative with respect to one or more aspects of the tested object's phenotype and/or genotype. The terms "marker" and "biomarker" may be used interchangeably throughout this specification.

The term "nucleic acid" as used throughout this specification typically refers to a polymer (preferably a linear polymer) of any length composed essentially of nucleoside units. A nucleoside unit commonly includes a heterocyclic base and a sugar group. Heterocyclic bases may include inter alia purine and pyrimidine bases such as adenine (A), guanine (G), cytosine (C), thymine (T) and uracil (U) which are widespread in naturally- occurring nucleic acids, other naturally- occurring bases (e.g., xanthine, inosine, hypoxanthine) as well as chemically or biochemically modified (e.g., methylated), non-natural or derivatised bases. Exemplary modified nucleobases include without limitation 5-substituted pyrimidines, 6-azapyrimidines and N-2, N-6 and 0-6 substituted purines, including 2-aminopropyladenine, 5- propynyluracil and 5-propynylcytosine. In particular, 5- methylcytosine substitutions have been shown to increase nucleic acid duplex stability and may be preferred base substitutions in for example antisense agents, even more particularly when combined with 2'-0-methoxyethyl sugar modifications. Sugar groups may include inter alia pentose (pentofuranose) groups such as preferably ribose and/or 2-deoxyribose common in naturally- occurring nucleic acids, or arabinose, 2-deoxyarabinose, threose or hexose sugar groups, as well as modified or substituted sugar groups (such as without limitation 2'-0-alkylated, e.g., 2'-0- methylated or 2'-0-ethylated sugars such as ribose; 2'-0-alkyloxyalkylated, e.g., 2'-0- methoxyethylated sugars such as ribose; or 2'-0,4'-C-alkylene-linked, e.g., 2'-0,4'-C-methylene- linked or 2'-0,4'-C-ethylene-linked sugars such as ribose; 2'-fluoro-arabinose, etc.). Nucleoside units may be linked to one another by any one of numerous known inter-nucleoside linkages, including inter alia phosphodiester linkages common in naturally- occurring nucleic acids, and further modified phosphate- or phosphonate-based linkages such as phosphorothioate, alkyl phosphorothioate such as methyl phosphorothioate, phosphorodithioate, alkylphosphonate such as methylphosphonate, alkylphosphonothioate, phosphotriester such as alkylphosphotriester, phosphoramidate, phosphoropiperazidate, phosphoromorpholidate, bridged phosphoramidate, bridged methylene phosphonate, bridged phosphorothioate; and further siloxane, carbonate, sulfamate, carboalkoxy, acetamidate, carbamate such as 3'-N-carbamate, morpholino, borano, thioether, 3'-thioacetal, and sulfone internucleoside linkages. Preferably, inter-nucleoside linkages may be phosphate-based linkages including modified phosphate-based linkages, such as more preferably phosphodiester, phosphorothioate or phosphorodithioate linkages or combinations thereof. The term "nucleic acid" also encompasses any other nucleobase containing polymers such as nucleic acid mimetics, including, without limitation, peptide nucleic acids (PNA), peptide nucleic acids with phosphate groups (PHONA), locked nucleic acids (LNA), morpholino phosphorodiamidate-backbone nucleic acids (PMO), cyclohexene nucleic acids (CeNA), tricyclo- DNA (tcDNA), and nucleic acids having backbone sections with alkyl linkers or amino linkers (see, e.g., Kurreck 2003 (Eur J Biochem 270: 1628-1644)). "Alkyl" as used herein particularly encompasses lower hydrocarbon moieties, e.g., C1-C4 linear or branched, saturated or unsaturated hydrocarbon, such as methyl, ethyl, ethenyl, propyl, 1 -propenyl, 2-propenyl, and isopropyl. Nucleic acids as intended herein may include naturally occurring nucleosides, modified nucleosides or mixtures thereof. A modified nucleoside may include a modified heterocyclic base, a modified sugar moiety, a modified inter-nucleoside linkage or a combination thereof.

The term "nucleic acid" further preferably encompasses DNA, RNA and DNA/RNA hybrid molecules, specifically including hnRNA, pre-mRNA, mRNA, cDNA, genomic DNA, amplification products, oligonucleotides, and synthetic (e.g., chemically synthesised) DNA, RNA or DNA/RNA hybrids. A nucleic acid can be naturally occurring, e.g., present in or isolated from nature, can be recombinant, i.e., produced by recombinant DNA technology, and/or can be, partly or entirely, chemically or biochemically synthesised. A "nucleic acid" can be double-stranded, partly double stranded, or single-stranded. Where single-stranded, the nucleic acid can be the sense strand or the antisense strand. In addition, nucleic acid can be circular or linear.

The reference to any marker, including any nucleic acid, corresponds to the marker commonly known under the respective designations in the art. The terms encompass such markers of any organism where found, and particularly of animals, preferably warm-blooded animals, more preferably vertebrates, yet more preferably mammals, including humans and non-human mammals, still more preferably of humans.

The terms particularly encompass such markers, including any nucleic acids, with a native sequence, i.e., ones of which the primary sequence is the same as that of the markers found in or derived from nature. A skilled person understands that native sequences may differ between different species due to genetic divergence between such species. Moreover, native sequences may differ between or within different individuals of the same species due to normal genetic diversity (variation) within a given species. Also, native sequences may differ between or even within different individuals of the same species due to somatic mutations, or post-transcriptional or post- translational modifications. Any such variants or isoforms of markers are intended herein. Accordingly, all sequences of markers found in or derived from nature are considered "native". The terms encompass the markers when forming a part of a living organism, organ, tissue or cell, when forming a part of a biological sample, as well as when at least partly isolated from such sources. In certain embodiments, markers, including any nucleic acids, may be human, i.e., their primary sequence may be the same as a corresponding primary sequence of or present in a naturally occurring human markers. Hence, the qualifier "human" in this connection relates to the primary sequence of the respective markers, rather than to their origin or source. For example, such markers may be present in or isolated from samples of human subjects.

Unless otherwise apparent from the context, reference herein to any marker, including any nucleic acid, or fragment thereof may generally also encompass modified forms of said marker, peptide, polypeptide, protein, or nucleic acid, or fragment thereof, such as bearing post-expression modifications including, for example, phosphorylation, glycosylation, lipidation, methylation, cysteinylation, sulphonation, glutathionylation, acetylation, oxidation of methionine to methionine sulphoxide or methionine sulphone, and the like.

As used herein, the reference to any marker, including any nucleic acid, corresponds to the marker commonly known under the respective designations in the art.

The term "gene" is well-known in the art and in general refers to a locatable region of genomic sequence, corresponding to a unit of inheritance, which is associated with regulatory regions, transcribed regions and/or other functional sequence regions. Genes typically comprise a coding sequences encoding a gene product, such as an RNA molecule or a polypeptide.

Table 1 provides the standard nomenclature, as well as the accession numbers for the genomic and mRNA reference sequences of exemplary genes of the present invention, derived all from Homo sapiens. Source: National Center for Biotechnology Information (NCBI). The entries in Table 1 are presented in the form: gene, name, GenelD, Genbank RefSeq for one or more representative mRNA sequences followed by the Genbank sequence version.

Exemplary human genes as taught herein may be as annotated under Swissprot/Uniprot (http://www.uniprot.org/) or NCBI Genbank (http://www.ncbi.nlm.nih.gov/) accession numbers given below. A skilled person will appreciate that although only one or more isoforms may be listed below, all isoforms are intended.

Table 1 : Exemplary human genes

The reference herein to any marker, including any nucleic acid, also encompasses fragments thereof. Hence, the reference herein to measuring (or measuring the quantity of) any one marker may encompass measuring the marker and/or measuring one or more fragments thereof.

For example, any marker and/or one or more fragments thereof may be measured collectively, such that the measured quantity corresponds to the sum amounts of the collectively measured species. In another example, any marker and/or one or more fragments thereof may be measured each individually.

The term "fragment" with reference to a nucleic acid (polynucleotide) generally denotes a 5'- and/or 3 '-truncated form of a nucleic acid. Preferably, a fragment may comprise at least about 30%, e.g., at least about 50% or at least about 70%, preferably at least about 80%, e.g., at least about 85%), more preferably at least about 90%>, and yet more preferably at least about 95% or even about 99% of the nucleic acid sequence length of said nucleic acid. For example, insofar not exceeding the length of the full-length nucleic acid, a fragment may include a sequence of > 5 consecutive nucleotides, or > 10 consecutive nucleotides, or > 20 consecutive nucleotides, or > 30 consecutive nucleotides, e.g., >40 consecutive nucleotides, such as for example > 50 consecutive nucleotides, e.g., > 60, > 70, > 80, > 90, > 100, > 200, > 300, > 400, > 500 or > 600 consecutive nucleotides of the corresponding full-length nucleic acid. The terms encompass fragments arising by any mechanism, in vivo and/or in vitro, such as, without limitation, by alternative transcription or translation, exo- and/or endo-proteolysis, exo- and/or endo-nucleolysis, or degradation of the peptide, polypeptide, protein, or nucleic acid, such as, for example, by physical, chemical and/or enzymatic proteolysis or nucleolysis.

In certain embodiments of the methods or uses as taught herein, the fragment of the ΓΝΑ gene has a sequence as defined by SEQ ID NO: 1, the fragment of the PTPRCAP gene has a sequence as defined by SEQ ID NO: 2, the fragment of the SEMA3B gene has a sequence as defined by SEQ ID NO: 3, the fragment of the KLHL6 gene has a sequence as defined by SEQ ID NO: 4, and/or the fragment of the RASSF1 gene has a sequence as defined by SEQ ID NO: 5.

In certain embodiments, the methods as taught herein comprise determining the methylation level of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from the subject.

The wording "a gene selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl" refers to one gene selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl,

The wording "two or more genes selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl" refers to two, three, four, or all five genes selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl .

For instance, determining the methylation level of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl may comprise determining the methylation level of ΓΝΑ or a fragment thereof, determining the methylation level of PTPRCAP or a fragment thereof, determining the methylation level of SEMA3B or a fragment thereof, determining the methylation level of KLHL6 or a fragment thereof, or determining the methylation level of RASSFl or a fragment thereof.

For instance, determining the methylation profile of two or more genes or fragments thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl may comprise:

determining the methylation level of the ΓΝΑ gene or fragment thereof and the PTPRCAP gene or fragment thereof; determining the methylation level of the ΓΝΑ gene or fragment thereof and the SEMA3B gene or fragment thereof; determining the methylation level of the

ΓΝΑ gene or fragment thereof and the KLHL6 gene or fragment thereof; determining the methylation level of the ΓΝΑ gene or fragment thereof and the RASSFl gene or fragment thereof; determining the methylation level of the PTPRCAP gene or fragment thereof and the SEMA3B gene or fragment thereof; determining the methylation level of the PTPRCAP gene or fragment thereof and the KLHL6 gene or fragment thereof; determining the methylation level of the PTPRCAP gene or fragment thereof and the RASSFl gene or fragment thereof; determining the methylation level of the SEMA3B gene or fragment thereof and the KLHL6 gene or fragment thereof; determining the methylation level of the SEMA3B gene or fragment thereof and the RASSFl gene or fragment thereof; or determining the methylation level of the KLHL6 gene or fragment thereof and the RASSFl gene or fragment thereof,

determining the methylation level of the INA gene or fragment thereof, the PTPRCAP gene or fragment thereof, and the SEMA3B gene or fragment thereof; determining the methylation level of the INA gene or fragment thereof, the PTPRCAP gene or fragment thereof, and the KLHL6 gene or fragment thereof; determining the methylation level of the INA gene or fragment thereof, the PTPRCAP gene or fragment thereof, and the RASSFl gene or fragment thereof; determining the methylation level of the INA gene or fragment thereof, the SEMA3B gene or fragment thereof, and the KLHL6 gene or fragment thereof; determining the methylation level of the INA gene or fragment thereof, the SEMA3B gene or fragment thereof, and the RASSFl gene or fragment thereof; determining the methylation level of the INA gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSFl gene or fragment thereof; determining the methylation level of the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, and the KLHL6 gene or fragment thereof; determining the methylation level of the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, and the RASSFl gene or fragment thereof; determining the methylation level of the PTPRCAP gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSFl gene or fragment thereof; or determining the methylation level of the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSFl gene or fragment thereof,

determining the methylation level of the INA gene or fragment thereof, the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, and the KLHL6 gene or fragment thereof; determining the methylation level of the INA gene or fragment thereof, the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, and the RASSFl gene or fragment thereof; determining the methylation level of the INA gene or fragment thereof, the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSFl gene or fragment thereof; or determining the methylation level of the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSFl gene or fragment thereof, or determining the methylation level of the INA gene or fragment thereof, the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSF1 gene or fragment thereof.

In certain preferred embodiments, determining the methylation level of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 comprises determining the methylation level of INA or a fragment thereof. In certain preferred embodiments, determining the methylation profile of two or more genes or fragments thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl comprises determining the methylation level of the INA gene or fragment thereof, the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSFl gene or fragment thereof.

The phrases "methylation level" or "level of methylation" may be used interchangeably herein and refer to a measure of the quantity (e.g., readout being an absolute or relative quantity) of methylated cytosine nucleotides, in particular methylated cytosine deoxyribonucleotides (i.e., DNA methylation), in a biological sample from a subject.

The methylation level of a gene or fragment thereof may be expressed as a value of methylatable cytosine nucleotides or CpG dinucleotides in the gene or fragment thereof that are methylated. For example, the methylation level can be calculated as a Beta value, e.g. an Infinium beta value:

Beta value = M / (U + M)

with M being Methylated allele intensity and U being Unmethylated allele intensity.

One CpG on one chromosome can only be methylated or unmethylated. Given that there are two copies of each chromosome in one cell, the methylation level of one cell methylated at one CpG can be 0.00 (CpG in both alleles unmethylated), 0.50 (CpG in one allele methylated, CpG in the other allele unmethylated) or 1.00 (CpG in both alleles methylated). When DNA is isolated from a sample, the DNA is a mixture of DNA from many cells from the sample. Depending on how many of the cells from the sample are unmethylated, hemimethylated, or fully methylated, the methylation level of a cytosine nucleotide or CpG dinucleotide at one position can range, e.g., when expressed as beta value from 0.00 (both alleles unmethylated in all cells) to 1.00 (both alleles methylated in all cells). For instance, the methylation level may range from unmethylated (i.e., no cytosine nucleotides or CpG dinucleotides in the gene or fragment thereof are methylated, or a methylation level, e.g., Infinium beta value of 0.00) to fully methylated (i.e., all methylatable cytosine nucleotides or CpG dinucleotides in a gene or fragment thereof are methylated or a methylation level, e.g., Infinium beta value of of 1.00). For instance, when using bisulfite pyrosequencing, the methylation level of a CpG dinucleotide (at one position) in a sequence can be determined as follows. By the bisulfite treatment, a methylated cytosine nucleotide will stay "C" and an unmethylated cytosine nucleotide will have been converted to "T". The number of C's and T's can be counted. The level of methylation of a CpG dinucleotide at one position as measured by bisulfite pyrosequencing can be calculated as:

[number of C's / (number of C's + number of T's)] * 100%

For example, when looking at a CpG dinucleotide at one position, if 1000 out of 1000 nucleotides at this position are "C", then the DNA is fully (100%) methylated at this position or has a methylation level of 100%) (e.g., Infinium beta value of 1.00) at this position, if 300/1000 nucleotides at this position are "C", then the DNA has a methylation level of 30%> (e.g., Infinium beta value of 0.30) at this position (also called "partial methylation"), or if 0 out of 1000 nucleotides at this position are "C", then the DNA is unmethylated (0%>) at this position or has a methylation level of 0%> (e.g., Infinium beta value of 0.00) at this position.

If the methylation of multiple CpGs of one gene is measured, the methylation level may be determined (e.g. calculated) for each CpG and a) each methylation level may be interpreted as an independent event, or b) the average methylation level may be calculated from the individual methylation levels, or a methylation profile may be determined as described herein.

The phrase "methylated nucleotide" or "methylated nucleotide base" refers to a nucleotide (base) comprising a methyl moiety, where the nucleotide (base) typically does not comprise a methyl moiety. For example, cytosine does not contain a methyl moiety on its pyrimidine ring. 5- methylcytosine contains a methyl moiety at position 5 of the pyrimidine ring. In this respect, cytosine is not a methylated nucleotide and 5-methylcytosine is a methylated nucleotide.

The term "methylation" as used herein refers to the presence of a methyl moiety on a nucleotide (base), where the nucleotide (base) typically does not comprise a methyl moiety.

As used herein, a "methylated CpG dinucleotide" refers to a CpG dinucleotide comprising a methyl moiety on the cytosine nucleotide ("C") in position 5, i.e. a CpG dinucleotide comprising 5- methylcytosine.

The term "CpG dinucleotide" refers to a cytosine ("C") followed by guanine ("G") in the linear sequence of bases along its 5' to 3' direction and linked by a phosphate bond ("p"), such as a phosphodiester or a modified phosphorothioate.

The phrase "methylated nucleic acid molecule" refers to a nucleic acid molecule that contains one or more nucleotides that are methylated. A gene or fragment thereof comprising at least one methylated nucleotide, preferably a methylated CpG dinucleotide, can be considered methylated. A gene or fragment thereof that does not comprise any methylated nucleotides can be considered unmethylated.

If the methylation of two or more genes is measured, a methylation profile may be determined, suitably incorporating information on the methylation level of each of the two or more genes. Such methylation profile measured in a sample can be suitably compared with a corresponding reference methylation profile established using the same procedure or formula in reference subject(s). In certain embodiments, the methylation profile may be a multi-parameter value. In certain embodiments, the methylation levels of the two or more genes may be combined, such as added, to yield a single value. For example, the methylation levels of the two or more genes may each be modulated by an appropriate weighing factor (e.g., equal or non-equal) and subsequently combined, such as added, to yield a single value.

In certain embodiments of the methods as taught herein, a methylation profile may be determined by calculating a score from the methylation levels of the two or more genes or fragments thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

In certain embodiments, determining a methylation profile of two or more genes or fragments thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1 may comprise:

determining the methylation level of each of the two or more genes or fragments thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from the subject; and

calculating a score from the methylation levels of the two or more genes or fragments thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl .

In certain embodiments, the score can be calculated by any suitable (statistical) method known in the art such as principal component analysis (PCA), normalized PCA (NPCA), weighted average, Non-Negative Matrix Factorization (NMF) or machine learning.

For instance, a score can be calculated by applying a "normalized PCA" (NPCA) approach to transform the individual methylation values of two or more genes or fragments thereof into a score (such as the MeTIL score discussed below). Advantageously, the calculation of the score by NPCA does not require complex algorithm and can easily be applied by any lab on any methylation dataset.

Beta-values can be computed using the following formula: Beta-value = M/[U+M] where M and U are the raw "methylated" and "unmethylated" signals, respectively. Beta-values can be corrected for type I and type II bias using the peak-based correction (Dedeurwaerder et al., 2011, Epigenomics, 3, 771-784; Dedeurwaerder et al., 2014, Brief Bioinform, 15, 929-941). The Beta- values of each CpG of the one or more genes or fragments thereof are standardized (m=0, s=l) on a discovery dataset. A principal component analysis (PCA) can then be applied and the first component can be used as final score (e.g., MeTIL score) for the samples of the discovery set. The score (e.g., MeTIL score) on any other datasets can be obtained using the NPCA parameters derived from the discovery set with the following formula: ^"^^"(^⁴^¹¹^ ^,r' )^v (beta is the matrix of Beta-values for the methyl the two or more genes or fragments as taught herein thereof on the new dataset, are the data transformed using the scale s and the center c from the discovery cohort and v is the eigenvector from the discovery cohort. This formula allows generating the score (e.g., MeTIL score) from any methylation data, for example using the following command in R language: (scale(beta, center=cl, scale=sl)%*%vl)[,l] (beta is the matrix of Beta- values for the probes from the signature (with samples in rows and probes in column) and cl, si and vl are parameters from the discovery cohort.

Further a score can be calculated by weighted average, Non-Negative Matrix Factorization (NMF), or machine learning. The weighted average summarizes the individual methylation values by attributing equal contribution of each value to the score. The NMF, similar to the NPCA, finds the optimal contribution of each methylation value to the score by assigning weights to each value. A machine learning approach generates the most informative score by using a training/test procedure, which is the least error-prone procedure.

In certain embodiments, the score of the methylation levels of each of the two or more genes or fragments thereof selected from the group consisting of IN A, PTPRCAP, SEMA3B, KLHL6, and RASSF1 may be calculated by NPCA as described herein.

The term "MeTIL score" as used herein refers to the score obtained from the methylation levels of two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl calculated by NPCA, such as by NPCA as described herein.

Due to the nature of the calculation of the MeTIL score by NPCA, such as by NPCA as described herein, the MeTIL score inversely correlates with the methylation level of the two or more genes or fragments thereof selected from the group consisting of IN A, PTPRCAP, SEMA3B, KLHL6, and RASSFl.

Further, the inventors have found by extensive experimentation that the MeTIL score positively correlates with the number, proportion or percentage of tumor infiltrating lymphocytes in a neoplastic tissue sample. The methylation level in a sample from a subject may refer to an absolute quantity of methylated cytosine nucleotides in the sample from the subject.

For instance, the methylation level, e.g., expressed as a beta value, may be about 0.05, 0.10, about 0.20, about 0.30, about 0.40, about 0.50, about 0.60, about 0.70, about 0.80, about 0.90, or about 1.00.

For instance, the methylation level, e.g., as measured by bisulfite pyrosequencing, may be about 0.1%, about 0.2%, about 0.3%, about 0.4%, about 0.5%, about 0.6%, about 0.7%, about 0.8%, about 0.9%), about 1%>, about 2%, about 3%>, about 4%, about 5%, or more, such as about 10%>, about 15%, about 20%, about 25%, about 30%, about 35%, about 40%, about 45%, about 50%, about 55%, about 60%, about 65%, about 70%, about 75%, about 80%, about 85%, about 90%, about 95% or about 100%). The methylation level may be more than 80%> methylated, between 20%> to 80%) methylated, or less than 20%> methylated. The methylation level may be more than 75% methylated, between 25% to 75% methylated, or less than 25% methylated.

In certain embodiments of the methods as taught herein, a MeTIL score may range from -4.5 (low) to 6.5 (high).

In certain embodiments, a MeTIL score of at least 0 may be a high MeTIL score. For instance, a MeTIL score of at least 0.1 , at least 0.2, at least 0.3, at least 0.4, at least 0.5, at least 0.6, at least 0.7, at least 0.8, at least 0.9, at least 1.0, at least 1.1 , at least 1.2, at least 1.3, at least 1.4, at least 1.5, at least 1.6, at least 1.7, at least 1.8, at least 1.9, or more may be a high MeTIL score.

In certain embodiments, a MeTIL score of at least 2.0 may be a high MeTIL score. For instance, a MeTIL score of at least 2.1 , at least 2.2, at least 2.3, at least 2.4, at least 2.5, at least 2.6, at least 2.7, at least 2.8, at least 2.9, at least 3.0, at least 3.5, at least 4.0, at least 4.5, at least 5.0, at least 5.5, or at least 6.0 may be a high MeTIL score.

In certain embodiments of the methods as taught herein, a MeTIL score ranging from 0 to 6.5 may be a high MeTIL score. In certain embodiments, a MeTIL score ranging from 1.0 to 6.5 may be a high MeTIL score. In certain embodiments, a MeTIL score ranging from 2.0 to 6.5 may be a high MeTIL score.

In certain embodiments, a MeTIL score of less than 0 may be a low MeTIL score. For instance, a MeTIL score of at most -0.1 , at most -0.2, at most -0.3, at most -0.4, at most -0.5, at most -0.6, at most -0.7, at most -0.8, at most -0.9, at most -1.0, at most -1.1 , at most -1.2, at most -1.3, at most - 1.4, at most -1.5, at most -1.6, at most -1.7, at most -1.8, at most -1.9, or less may be a low MeTIL score. In certain embodiments, a MeTIL score of at most -2.0 may be a low MeTIL score. For instance, a MeTIL score of at most -2.5, at most -3.0, at most -3.5, or at most -4.0 may be a low MeTIL score.

In certain embodiments of the methods as taught herein, a MeTIL score ranging from -4.5 to 0 may be a low MeTIL score. In certain embodiments, a MeTIL score ranging from -4.5 to -0.1 may be a low MeTIL score. In certain embodiments, a MeTIL score ranging from -4.5 to -1.0 or from -4.5 to -2.0 may be a low MeTIL score.

The methylation level in a sample from a subject may refer to a relative quantity of methylated cytosine nucleotides in the sample from the subject, i.e., the quantity of methylated cytosine nucleotides in the sample from the subject compared with the quantity of methylated cytosine nucleotides in a reference sample, e.g. a reference sample from the same subject or from an unrelated subject.

In certain embodiments, the methods as taught herein may rely on comparing the methylation level of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl measured in samples from patients with reference values, wherein said reference values represent known responsiveness to immunotherapy and/or known prognosis.

In certain embodiments, the methods as taught herein may rely on comparing the methylation profile or score of two or more genes or fragments thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl measured in samples from patients with reference scores, wherein said reference scores represent known responsiveness to immunotherapy and/or known prognosis.

For example, a reference value or reference score may represent the prediction of responsiveness (or sensitivity or susceptibility) of a subject to immunotherapy or the prediction of unresponsiveness (or insensitivity or insusceptibility) of a subject to immunotherapy. In another example, a reference value or reference score may represent responders to immunotherapy or non- responders to immunotherapy. In yet another example, a reference value or reference score may represent a prediction of a certain degree of responsiveness of a subject to immunotherapy.

In a further example, a reference value or reference score can represent a neoplastic tissue sample having high number of tumor-infiltrating lymphocytes (TILs) (e.g., as determined by pathological assessment), or a neoplastic tissue sample having intermediate number of TILs (e.g., as determined by pathological assessment), or a neoplastic tissue sample having low number of tumor-infiltrating lymphocytes (e.g., as determined by pathological assessment).

In a further example, a reference value or reference score may represent a neoplastic tissue sample or a healthy tissue sample, such as from the same subject or a different subject. In another example, a reference value or reference score may represent a good prognosis for a given neoplastic disease as taught herein or a poor prognosis for said neoplastic disease. In a further example, a reference value or reference score may represent varyingly favorable or unfavorable prognoses for such neoplastic disease.

Such comparison may generally include any means to determine the presence or absence of at least one difference or deviation and optionally of the size of such difference or deviation between values or scores being compared. A comparison may include a visual inspection, an arithmetical or statistical comparison of measurements. Such statistical comparisons include, but are not limited to, applying a rule.

Reference values or reference scores may be established according to known procedures. For example, a reference value or reference score may be established in a reference subject or individual or a population of individuals characterized by a particular prediction of responsiveness to immunotherapy and/or a particular prediction of chance of survival or prognosis of said neoplastic disease (i.e., for whom said prediction of responsiveness to immunotherapy and/or prediction of chance of survival or prognosis of the neoplastic disease holds true). Such population may comprise without limitation 2 or more, 10 or more, 100 or more, or even several hundred or more individuals.

A "deviation" of a first value from a second value may generally encompass any direction (e.g., increase: first value > second value; or decrease: first value < second value) and any extent of alteration.

For example, a deviation may encompass a decrease in a first value by, without limitation, at least about 10% (about 0.9-fold or less), or by at least about 20% (about 0.8-fold or less), or by at least about 30%) (about 0.7-fold or less), or by at least about 40% (about 0.6-fold or less), or by at least about 50%) (about 0.5-fold or less), or by at least about 60%> (about 0.4-fold or less), or by at least about 70%) (about 0.3-fold or less), or by at least about 80% (about 0.2-fold or less), or by at least about 90%) (about 0.1 -fold or less), relative to a second value with which a comparison is being made.

For example, a deviation may encompass an increase of a first value by, without limitation, at least about 10%) (about 1.1 -fold or more), or by at least about 20% (about 1.2-fold or more), or by at least about 30% (about 1.3-fold or more), or by at least about 40% (about 1.4-fold or more), or by at least about 50% (about 1.5-fold or more), or by at least about 60% (about 1.6-fold or more), or by at least about 70% (about 1.7-fold or more), or by at least about 80%) (about 1.8-fold or more), or by at least about 90% (about 1.9-fold or more), or by at least about 100%) (about 2-fold or more), or by at least about 150%) (about 2.5-fold or more), or by at least about 200%) (about 3-fold or more), or by at least about 500% (about 6-fold or more), or by at least about 700%> (about 8-fold or more), or like, relative to a second value with which a comparison is being made.

Preferably, a deviation may refer to a statistically significant observed alteration. For example, a deviation may refer to an observed alteration which falls outside of error margins of reference values or reference scores in a given population (as expressed, for example, by standard deviation or standard error, or by a predetermined multiple thereof, e.g., ±lxSD or ±2xSD or ±3xSD, or ±lxSE or ±2xSE or ±3xSE). Deviation may also refer to a value falling outside of a reference range defined by values in a given population (for example, outside of a range which comprises >40%, > 50%, >60%, >70%, >75% or >80% or >85% or >90% or >95% or even >100% of values in said population).

In a further embodiment, a deviation may be concluded if an observed alteration is beyond a given threshold or cut-off. Such threshold or cut-off may be selected as generally known in the art to provide for a chosen sensitivity and/or specificity of the prediction methods, e.g., sensitivity and/or specificity of at least 50%, or at least 60%, or at least 70%, or at least 80%, or at least 85%, or at least 90%, or at least 95%.

For example, receiver-operating characteristic (ROC) curve analysis can be used to select an optimal cut-off value of the quantity of the methylation level of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1, or of a methylation profile or score based on two or more of said genes, for clinical use of the present methods, based on acceptable sensitivity and specificity, or related performance measures which are well-known per se, such as positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), negative likelihood ratio (LR-), Youden index, or similar. By means of an example, a cut-off value may be selected such as to provide for AUC value higher than 50%), or higher than 55%, or higher than 60%, or higher than 65%, or higher than 70%, or higher than 75%, or higher than 80%, or higher than 85%, or higher than 90%, or higher than 95%.

By extensive research, the present inventors have found that responders to immunotherapy show gene hypomethylation, whereas non-responders to immunotherapy or healthy tissue samples show gene hypermethylation.

The term "hypomethylation" generally refers to a decrease in the epigenetic methylation of cytosine in a DNA.

The term "hypermethylation" generally refers to an increase in the epigenetic methylation of cytosine in a DNA. In certain embodiments of the methods as taught herein, the methods for predicting responsiveness to immunotherapy in a subject having a neoplastic disease may comprise:

(i) determining the methylation level of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in the sample from the subject;

(ii) comparing the methylation level as determined in (i) with a reference value, said reference value representing a known responsiveness of a reference subject to immunotherapy;

(iii) finding a deviation or no deviation of the methylation level as determined in (i) from said reference value; and

In certain embodiments of the methods as taught herein, the reference value represents a reference subject that is responsive to immunotherapy, and wherein:

the same or a decreased methylation level of the gene or a fragment thereof as measured in (i) compared with a reference value indicates that the subject will be responsive to immunotherapy, or

an increased methylation level of the gene or a fragment thereof as measured in (i) compared with the reference value indicates that the subject will be unresponsive to immunotherapy.

hypomethylation of the gene or a fragment thereof as measured in (i) compared with a reference value indicates that the subject will be responsive to immunotherapy, or

hypermethylation of the gene or a fragment thereof as measured in (i) compared with the reference value indicates that the subject will be unresponsive to immunotherapy.

In certain embodiments of the methods as taught herein, the reference value represents a reference subject that is unresponsive to immunotherapy, and wherein:

a decreased methylation level of the gene or a fragment thereof as measured in (i) compared with the reference value indicates that the subject will be responsive to immunotherapy, or the same or an increased methylation level of the gene or a fragment thereof as measured in (i) compared with the reference value indicates that the subject will be unresponsive to immunotherapy. In certain embodiments of the methods as taught herein, the reference value represents a reference subject that is unresponsive to immunotherapy, and wherein:

hypomethylation of the gene or a fragment thereof as measured in (i) compared with the reference value indicates that the subject will be responsive to immunotherapy, or

- hypermethylation of the gene or a fragment thereof as measured in (i) compared with the reference value indicates that the subject will be unresponsive to immunotherapy.

In certain embodiments of the methods as taught herein, the methods for predicting survival or for prognosis in a subject having a neoplastic disease may comprise:

(i') determining the methylation level of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in the sample from the subject;

(ϋ') comparing the methylation level as determined in (i') with a reference value, said reference value representing a known chance of survival or a known prognosis of the neoplastic disease in a reference subject;

(iii') finding a deviation or no deviation of the methylation level as determined in (i') from said reference value; and

(iv') attributing said finding of deviation or no deviation to a particular prediction of chance of survival or prognosis of the neoplastic disease in the subject.

In certain embodiments of the methods as taught herein, the reference value represents a reference subject having a favourable prognosis, and wherein:

the same or a decreased methylation level of the gene or a fragment thereof as measured in (i') compared with the reference value indicates a favourable prognosis in the subject, or an increased methylation level of the gene or a fragment thereof as measured in (i') compared with the reference value indicates an unfavourable prognosis in the subject.

hypomethylation of the gene or a fragment thereof as measured in (i') compared with the reference value indicates a favourable prognosis in the subject, or

hypermethylation of the gene or a fragment thereof as measured in (i') compared with the reference value indicates an unfavourable prognosis in the subject. In certain embodiments of the methods as taught herein, the reference value represents a reference subject having an unfavourable prognosis, and wherein:

a decreased methylation level of the gene or a fragment thereof as measured in (i') compared with the reference value indicates a favourable prognosis in the subject, or

- the same methylation or an increased methylation level of the gene or a fragment thereof as measured in (i') compared with the reference value indicates an unfavourable prognosis in the subject.

In certain embodiments of the methods as taught herein, the reference value represents a reference subject having an unfavourable prognosis, and wherein:

- hypomethylation of the gene or a fragment thereof as measured in (i') compared with the reference value indicates a favourable prognosis in the subject, or

hypermethylation of the gene or a fragment thereof as measured in (i') compared with the reference value indicates an unfavourable prognosis in the subject.

In certain embodiments, hypomethylation may correspond to a decreased methylation level of a gene or fragment thereof in a sample, preferably a neoplastic tissue sample, from a subject compared with the methylation level of the gene or fragment thereof in a reference sample. In certain embodiments, the reference sample may be a sample from a non-responder to immunotherapy. In certain embodiments, the reference sample may be a healthy tissue sample, e.g. from the same subject or from an unrelated subject.

In certain embodiments, hypermethylation may correspond to same or an increased methylation level of a gene or fragment thereof in a sample, preferably a neoplastic tissue sample, from a subject compared with the methylation level of the gene or fragment thereof in a reference sample. In certain embodiments, the reference sample may be a sample from a non-responder to immunotherapy. In certain embodiments, the reference sample may be a healthy tissue sample, e.g. from the same subject or from an unrelated subject.

In certain embodiments, a reference sample may be a neoplastic tissue sample or a healthy tissue sample, such as from the same subject or a different subject.

In certain embodiments, the methods as taught herein may comprise:

determining the methylation level of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in a sample, preferably a neoplastic tissue sample, from the subject; and comparing the methylation level of the gene or fragment thereof with the methylation level of the gene or fragment thereof in a reference sample; wherein a decreased methylation level in the sample from the subject compared with the methylation level in the reference sample corresponds to hypomethylation of the gene or fragment thereof, or an increased methylation level in the sample from the subject compared with the methylation level in the reference sample corresponds to hypermethylation of the gene or fragment thereof.

By extensive experimentation, the present inventors have found that responders to immunotherapy show a high MeTIL score as taught herein, whereas non-responders to immunotherapy or healthy tissue samples show a low MeTIL score as taught herein.

In certain embodiments of the methods as taught herein, the methods for predicting responsiveness to immunotherapy in a subject having a neoplastic disease may comprise:

(i) determining a score, e.g., MeTIL score, of two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in the sample from the subject;

(ii) comparing the score, e.g., MeTIL score, as determined in (i) with a reference score, said reference score representing a known responsiveness to immunotherapy;

(iii) finding a deviation or no deviation of the score, e.g., MeTIL score, as determined in (i) from said reference score; and

In certain embodiments of the methods as taught herein, the reference score represents a reference subject that is responsive to immunotherapy, and wherein:

a decreased score, e.g., MeTIL score, as measured in (i) compared with a reference score indicates that the subject will be unresponsive to immunotherapy, or

- the same or an increased score, e.g., MeTIL score, as measured in (i) compared with the reference score indicates that the subject will be responsive to immunotherapy.

a low score, e.g., MeTIL score, as measured in (i) compared with a reference score indicates that the subject will be unresponsive to immunotherapy, or

a high score, e.g., MeTIL score, as measured in (i) compared with the reference score indicates that the subject will be responsive to immunotherapy. In certain embodiments of the methods as taught herein, the reference score represents a reference subject that is unresponsive to immunotherapy, and wherein:

the same or a decreased score, e.g., MeTIL score, as measured in (i) compared with the reference score indicates that the subject will be unresponsive to immunotherapy, or

- an increased score, e.g., MeTIL score, as measured in (i) compared with the reference score indicates that the subject will be responsive to immunotherapy.

In certain embodiments of the methods as taught herein, the reference score represents a reference subject that is unresponsive to immunotherapy, and wherein:

a low score, e.g., MeTIL score, as measured in (i) compared with the reference score indicates that the subject will be unresponsive to immunotherapy, or

a high score, e.g., MeTIL score, as measured in (i) compared with the reference score indicates that the subject will be responsive to immunotherapy.

(i') determining a score, e.g., MeTIL score, of two or more genes or fragments thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in a sample from the subject;

(ϋ') comparing the score, e.g., MeTIL score, as determined in (i') with a reference score, said reference score representing a known chance of survival or a known prognosis;

(iii') finding a deviation or no deviation of the score, e.g., MeTIL score, as determined in (i') from said reference score; and

In certain embodiments of the methods as taught herein, the reference score represents a reference subject having a favourable prognosis, and wherein:

a decreased score, e.g., MeTIL score, as measured in (i') compared with the reference score indicates an unfavourable prognosis in the subject, or

the same or an increased score, e.g., MeTIL score, as measured in (i') compared with the reference score indicates a favourable prognosis in the subject.

In certain embodiments of the methods as taught herein, the reference score represents a reference subject having a favourable prognosis, and wherein: a low score, e.g., MeTIL score, as measured in (ί') compared with the reference score indicates an unfavourable prognosis in the subject, or

a high score, e.g., MeTIL score, as measured in (i') compared with the reference score indicates a favourable prognosis in the subject.

In certain embodiments of the methods as taught herein, the reference score represents a reference subject having an unfavourable prognosis, and wherein:

the same or a decreased score, e.g., MeTIL score, as measured in (i') compared with the reference score indicates an unfavourable prognosis in the subject, or

an increased score, e.g., MeTIL score, as measured in (i') compared with the reference score indicates a favourable prognosis in the subject.

a low score, e.g., MeTIL score, as measured in (i') compared with the reference score indicates an unfavourable prognosis in the subject, or

In certain embodiments, a high score, e.g., MeTIL score, may correspond to an increased score, e.g., MeTIL score, of two or more genes or fragments thereof in a sample, preferably a neoplastic tissue sample, from a subject compared with the score, e.g., MeTIL score, of the two or more genes or fragments thereof in a reference sample. In certain embodiments, the reference sample may be a sample from a non-responder to immunotherapy. In certain embodiments, the reference sample may be a healthy (i.e., non-diseased) tissue sample, e.g. from the same subject or from an unrelated subject.

In certain embodiments, a low score, e.g., MeTIL score, may correspond to a decreased score, e.g., MeTIL score, of two or more genes or fragments thereof in a sample, preferably a neoplastic tissue sample, from a subject compared with the score, e.g., MeTIL score, of the two or more genes or fragments thereof in a reference sample. In certain embodiments, the reference sample may be a sample from a non-responder to immunotherapy. In certain embodiments, the reference sample may be a healthy (i.e., non-diseased) tissue sample, e.g. from the same subject or from an unrelated subject.

In certain embodiments, the methods as taught herein may comprise: determining the score, e.g., MeTIL score, of two or more genes or fragments thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in a sample, preferably a neoplastic tissue sample, from the subject; and

comparing the score, e.g., MeTIL score, of the two or more genes or fragments thereof with the score, e.g., MeTIL score, of the of two or more genes or fragments thereof in a reference sample; wherein an increased score, e.g., MeTIL score, in the sample from the subject compared with the score, e.g., MeTIL score, in the reference sample corresponds to a high score, e.g., MeTIL score, of the two or more genes or fragments thereof, or an decreased score, e.g., MeTIL score, in the sample from the subject compared with the score, e.g., MeTIL score, in the reference sample corresponds to a low score, e.g., MeTIL score, of the two or more genes or fragments thereof.

Further disclosed herein is a method for establishing a reference methylation level comprising: determining the methylation level of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a reference sample (e.g., from a non-responder to immunotherapy), thereby producing a reference methylation level of a reference sample (e.g., from a non-responder to immunotherapy). Also disclosed herein is a method for establishing a reference score comprising: determining the methylation level of each of the two or more genes or fragments thereof, preferably the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from a reference sample (e.g., from a non-responder to immunotherapy), and calculating a score as described herein, thereby establishing a reference score of a reference sample (e.g., from a non- responder to immunotherapy).

Also disclosed herein are reference methylation levels or scores obtainable or obtained by the methods described herein. Further disclosed herein is the use of reference methylation levels or scores as described herein for predicting responsiveness to immunotherapy in a subject having a neoplastic disease.

Further aspects relate to the use of a set of reference methylation levels or scores as described herein for indicating immunotherapy as a suitable treatment for a neoplastic disease in a subject; for predicting an immunotherapy outcome in a subject having a neoplastic disease; for the stratification of subjects having a neoplastic disease; or for predicting survival or for prognosis in a subject having a neoplastic disease.

In certain embodiments of the methods as taught herein, determining the methylation level of a gene or fragment thereof may comprise determining the methylation level of one or more CpG dinucleotides in the gene or fragment thereof. In certain embodiments, the methods as taught herein may further comprise determining the methylation level of one or more CpG dinucleotides in the ΓΝΑ gene or fragment thereof, the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and/or the RASSFl gene or fragment thereof.

In certain embodiments of the methods as taught herein, determining the methylation level of a gene or fragment thereof may comprise determining the methylation level of a CpG dinucleotide located in a fragment of the gene having a sequence as defined by SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, and/or SEQ ID NO: 5.

Preferred target CpG dinucleotides are listed in Table 3 by the chromosomal position of the cytosine residue.

In certain embodiments of the methods as taught herein, determining the methylation level of a gene or fragment thereof may comprise determining the methylation level of a CpG dinucleotide located in a fragment of the gene having a chromosomal position of the cytosine residue as defined in Table 3.

In certain embodiments, a CpG dinucleotide may be located in a coding region, such as the 5' and 3' untranslated regions, or an ex on, as well as in a non-coding region, including a regulatory region, such as the promoter region, of a gene. In certain embodiments, a methylated CpG dinucleotide may be located inside or outside a CpG island.

The term "regulatory region" or "regulatory sequence" in respect of a specific gene, refers to a region of the non-coding nucleotide sequences within the gene that is necessary or sufficient to provide for the regulated expression of the coding region of the gene. Thus, the term "regulatory region" includes promoter sequences, regulatory protein binding sites, and upstream activator sequences. Specific nucleotides within a regulatory region may serve multiple functions. For example, a specific nucleotide may be part of a promoter and participate in the binding of a transcriptional activator protein.

"Promoter" or "promoter region" refers to a nucleotide sequence capable of controlling the expression of a coding sequence or functional RNA. In general, a promoter sequence is located 5' to a coding sequence. The promoter sequence consists of proximal and more distal upstream elements, the latter elements often referred to as enhancers. Accordingly, an "enhancer" is a nucleotide sequence which can stimulate promoter activity and may be an innate element of the promoter or a heterologous element inserted to enhance the level or tissue-specificity of a promoter. It is understood by those skilled in the art that different promoters may direct the expression of a gene in different tissues or cell types, or at different stages of development, or in response to different environmental conditions. Typically, a promoter region extends between approximately 1 kb, 500 bp, or 150 to 300 bp upstream from the transcription start site.

The term "CpG island" is a G:C-rich region of genomic DNA containing a greater number of CpG dinucleotides relative to total genomic DNA, as defined in the art. In many genes, the CpG islands begin just upstream of a promoter and extend downstream into the transcribed region. The islands can also surround the 5' region of the coding region of the gene as well as the 3' region of the coding region. CpG islands can be found in multiple regions of a gene like upstream of coding regions in a regulatory region including a promoter region; within the coding regions (e.g., exons); downstream of coding regions in, for example, enhancer regions; or within introns. All of these regions can be assessed to determine their methylation status. It should be noted that hypermethylation of the genes or fragments thereof as taught herein is not limited to CpG islands only, but can be in so-called "shores" or "shelves" or can be lying completely outside a CpG island region.

In certain embodiments of the methods as taught herein, determining the methylation level of a gene or fragment thereof may comprise determining the methylation level of one or more CpG dinucleotides located in the promoter region of the gene or fragment thereof.

The methylation level of a gene or fragment thereof may be determined by any technique for detecting methylated nucleic acid molecules. These techniques are based on any one or more of the classic techniques of hybridization, amplification, sequencing, electrophoresis, chromatography, and mass spectrometry.

In certain embodiments of the methods or uses as taught herein, the methylation level of a gene or fragment thereof in the sample may be determined by one or more techniques selected from the group consisting of nucleic acid amplification, polymerase chain reaction (PCR), methylation specific PCR (MCP), methylated-CpG island recovery assay (MIRA), combined bisulfite- restriction analysis (COBRA), bisulfite pyrosequencing, single-strand conformation polymorphism (SSCP) analysis, restriction analysis, microarray analysis, and bead-chip technology.

Methylation specific PCR (US 5,786,146, US 6,017,704, US 6,200,756) allows the distinction between modified and unmodified DNA by hybridizing oligonucleotide primers which specifically bind to the modified or unmodified DNA. After hybridization, an amplification reaction can be performed and amplification products assayed. The presence of an amplification product indicates that a sample hybridized to the primer. The specificity of the primer indicates whether the DNA had been modified or not, which in turn indicates whether the DNA had been methylated or not. For example, bisulfite ions modify non-methylated cytosine bases, changing them to uracil bases. Uracil bases hybridize to adenine bases under hybridization conditions. Thus an oligonucleotide primer which comprises adenine bases in place of guanine bases would hybridize to the bisulfite- modified DNA, whereas an oligonucleotide primer containing the guanine bases would hybridize to the non-modified (methylated) cytosine residues in the DNA. Amplification using a DNA polymerase and a second primer yield amplification products that can be readily observed. The amplification products can be optionally hybridized to specific oligonucleotide probes which may also be specific for certain products. Alternatively, oligonucleotide probes can be used which will hybridize to amplification products from both modified and non-modified DNA.

Any reference to "modified" bases or sequences, in the appropriate context, alludes to the treatment of these bases or sequences with a suitable reagent, in order to convert non-methylated cytosine into uracil bases.

With real-time methylation specific PCR, the methylation profile of the genes of interest can be assessed by determining the amplification level of said genes based on amplification-mediated displacement or on binding of one or more probes whose binding sites are located within the amplicon. In general, real-time quantitative methylation specific PCR is based on the continuous monitoring of a progressive fluorogenic PCR by an optical system. Such PCR systems usually use two amplification primers and an additional amplicon-specific, fluorogenic hybridization probe that specifically binds to a site within the amplicon. The probe can include one or more fluorescence label moieties. For example, the probe can be labeled with two fluorescent dyes: 1) a 6-carboxy- fluorescein (FAM), located at the 5' end, which serves as reporter, and 2) a 6-carboxy-tetramethyl- rhodamine (TAMRA), located at the 3' end, which serves as a quencher. When amplification occurs, the 5 '-3' exonuclease activity of the Taq DNA polymerase cleaves the reporter from the probe during the extension phase, thus releasing it from the quencher. The resulting increase in fluorescence emission of the reporter dye is monitored during the PCR process and represents the number of DNA fragments generated. This process is known as Taqman. Other systems to monitor real-time PCR involve the use of hairpin primers (Amplifluor), hairpin probes (Molecular Beacons), FRET probe pairs (Lightcycler), primers incorporating a hairpin probe (Scorpion), Plexor™ system, primers incorporating complementary sequences of DNAzymes that cleave a reporter substrate included in the reaction mixture (DzyNA) or fluorescent dyes (such as SYBR Green).

Methylation-dependent sequence variation at CpG dinucleotide motifs offers different approaches to PCR primer design. In one approach, oligonucleotide primers are designed to specifically bind methylated primer-binding sites, and a probe is designed to anneal specifically within the amplicon during extension. Such primers typically comprise CpG dinucleotides which get affected by DNA methylation. In another approach, oligonucleotide primers are designed to bind either methylated or unmethylated primer-binding sites, and the probe is designed to anneal specifically to methylated probe binding sites. In yet another approach, both oligonucleotide primers and probes are designed to specifically bind methylated binding sites. In either approach, when there is a sufficient region of complementarity, e.g., 12, 15, 18, or 20 nucleotides, between the target and the primer, the primer may also contain additional nucleotide residues that do not interfere with hybridization but may be useful for other manipulations. Exemplary of such other residues may be sites for restriction endonuclease cleavage, for ligand binding, or for factor binding or linkers or repeats.

Another way to distinguish between modified and non-modified DNA employs oligonucleotide probes or isolated oligonucleotides which may also be specific for certain products. Such probes can be hybridized directly to modified DNA or to amplification products of modified DNA. Oligonucleotide probes can be labeled using any detection system known in the art. These include but are not limited to fluorescent moieties, radioisotope labeled moieties, bioluminescent moieties, luminescent moieties, chemiluminescent moieties, enzymes, substrates, receptors, or ligands. The oligonucleotide probes may be bound to a support. The support can be any suitable support such as plastic materials, (fluorescent) beads, magnetic beads, synthetic or natural membranes, latex beads, polystyrene, column supports, glass beads or slides, nanotubes, fibres or other organic or inorganic supports. The binding processes are well-known in the art and generally comprise cross-linking, covalently binding or physically adsorbing the oligonucleotide to the support. A support may also contain a plurality of oligonucleotide probes arrayed on the support. Such array may comprise multiple copies of the same oligonucleotide probe so as to capture the same target gene (region) on the array or may comprise a plurality of different oligonucleotide probes targeting different genes (regions) so as to capture a plurality of target genes (regions) on the array. An exemplary method for detecting the methylation status of a nucleic acid based on the use of oligonucleotide probes is the use of Infinium® BeadChip sold by Illumina Inc. San Diego (US), which makes use of a bead chip.

Another approach for determining the methylation level of the one or more genes or fragments thereof uses methylation-sensitive restriction endonucleases to detect methylated CpG dinucleotide motifs. Such endonucleases may either preferentially cleave methylated recognition sites relative to non-methylated recognition sites, or preferentially cleave non-methylated relative to methylated recognition sites. Examples of the former are Acc III, Ban I, BstN I, Msp I, and Xma I. Examples of the latter are Acc II, Ava I, BssH II, BstU I, Hpa II, and Not I. Yet another approach is the combined bisulfite-restriction analysis (COBRA assay) in which PCR products obtained from bisulfite-treated DNA are further analysed by using restriction enzymes that recognize sequences containing 5'CG, such as Taql (5'TCGA) or BstUI (5'CGCG), such that methylated and unmethylated DNA can be distinguished. Following digestion of sample DNA with either methylation-sensitive or methylation-insensitive restriction enzymes (for ex. Mspl and Hpall), the DNA can be analysed by methods such as Southern Blotting and PCR. Southern blot analysis involves electrophoretic separation of the resulting DNA fragments and hybridization with a labeled probe adjacent to the CpG of interest. If the hybridization signal from the methylation-sensitive and methylation-insensitive digested DNA samples results in different size bands, than the site of interest was methylated. In contrast, PCR analysis involves amplification across the CpG of interest. The expected band will only be observed in the methylation-sensitive digested sample if the site of interest is methylated. The PCR assay requires much lower amounts of DNA for each site of interest (for example 1-10 ng), but necessitates the design and testing of specific primer pairs for every site of interest.

Still another way for the identification of methylated CpG dinucleotides utilizes the ability of the MBD domain of the MeCP2 protein to selectively bind to methylated DNA sequences. Restriction endonuclease digested genomic DNA is loaded onto expressed His-tagged methyl-CpG binding domain that is immobilized onto a solid matrix and used for preparative column chromatography to isolate highly methylated DNA sequences.

Alternatively, the HELP assay can be used, which is based on the differential ability of restriction enzymes to recognize and cleave methylated and unmethylated CpG DNA sites.

Furthermore, ChlP-on-chip assays, based on the ability of commercially prepared antibodies to bind to DNA methylation-associated proteins like MCP2, can be used to determine the methylation level. Also restriction landmark genomic scanning, also based upon differential recognition of methylated and unmethylated CpG sites by restriction enzymes can be used. Methylated DNA immunoprecipitation (MeDIP), analogous to chromatin immunoprecipitation, can be used to isolate methylated DNA fragments for input into DNA detection methods such as DNA microarrays (MeDIP-chip) or DNA sequencing (MeDIP-seq). The unmethylated DNA is not precipitated. Alternatively, molecular break light assay for DNA adenine methyltransferase activity can be used. This is an assay that uses the specificity of the restriction enzyme Dpnl for fully methylated (adenine methylation) GATC sites in an oligonucleotide labeled with a fluorophore and quencher. The adenine methyltransferase methylates the oligonucleotide making it a substrate for Dpnl. Cutting of the oligonucleotide by Dpnl gives rise to a fluorescence increase. Further, methylated- CpG island recovery assay (MIRA) can be used.

Typically, for determining the methylation level of the one or more genes or fragments thereof, genomic DNA or a fragment thereof, is treated with a reagent that selectively modifies an unmethylated cytosine residue but that is incapable of modifying a methylated cytosine residue; and the resulting product is detected. Examples of reagents for selective modification of unmethylated cytosine residues include hydrazine and bisulfite ions. Hydrazine-modified DNA, or a portion thereof, can be treated with piperidine to cleave it. Bisulfite ion-treated DNA, or a portion thereof, can be treated with alkali. The resulting products can be detected directly, or after a further reaction that creates products, which are easily distinguishable. For example, the products resulting from the treatment with a reagent that selectively modifies an unmethylated cytosine residue but which is incapable of modifying methylated cytosine residue, may be detected by amplification with at least one primer that hybridizes to a sequence comprising a modified non-methylated CpG dinucleotide motif, i.e. UpG or TpG, but not to a sequence comprising an unmodified methylated CpG dinucleotide motif, thereby forming amplification products. Conversely, the resulting products may be detected by amplification with at least one primer that hybridizes to a sequence comprising an unmodified methylated CpG dinucleotide motif but not to a sequence comprising a modified non-methylated CpG, i.e. UpG or TpG, dinucleotide motif, thereby forming amplification products. In addition, the amplification products under investigation may be detected using (a) a first oligonucleotide probe which hybridizes to a sequence comprising a modified non-methylated CpG dinucleotide motif, i.e. UpG or TpG, but not to a sequence comprising an unmodified methylated CpG dinucleotide motif, (b) a second oligonucleotide probe that hybridizes to a sequence comprising an unmodified methylated CpG dinucleotide motif but not to a sequence comprising a modified non-methylated CpG dinucleotide motif, i.e. UpG or TpG, or (c) both said first and second oligonucleotide probes.

Accordingly, in embodiments of the methods as taught herein, determining the methylation level of a gene or fragment thereof, may comprise:

a) isolating genomic DNA from a sample from the subject;

b) contacting the genomic DNA obtained in step a) with at least one reagent as described herein that selectively modifies an unmethylated cytosine residue but that is incapable of modifying a methylated cytosine residue, thereby obtaining modified DNA; and

c) detecting the modified DNA obtained in step b) with a technique as described herein.

In certain embodiments, the methods as taught herein may further comprise the prior step of providing a sample, preferably a neoplastic tissue sample, from the subject.

In certain embodiments of the methods or uses as taught herein, genomic DNA is isolated from a sample, such as a neoplastic tissue sample, for methylation analysis. Genomic DNA may be isolated by any means standard in the art, including the use of commercially available kits. Briefly, when the DNA is encapsulated by a cellular membrane, the sample must be disrupted and lysed by enzymatic, chemical or mechanical means, thereby obtaining a DNA solution. The DNA solution may then be cleared of proteins and other contaminants, e.g. by digestion with proteinase K. The DNA is then recovered from the solution. This may be carried out by means of a variety of methods including salting out, organic extraction or binding of the DNA to a solid phase support. The choice of method will be affected by several factors including time, expense and required quantity of DNA. Wherein the DNA is not enclosed in a membrane (e.g. circulating DNA from a blood sample) methods standard in the art for the isolation and/or purification of DNA may be employed. Such methods include the use of a protein degenerating reagent, e.g. a chaotropic salt such as guanidine hydrochloride or urea; or a detergent, e.g. sodium dodecyl sulphate (SDS), cyanogen bromide. Alternative methods include but are not limited to ethanol precipitation or propanol precipitation, vacuum concentration amongst others by means of a centrifuge. The person skilled in the art may also make use of devices such as filter devices, e.g. ultrafiltration, silica surfaces or membranes, magnetic particles, polystyrene particles, polystyrene surfaces, positively charged surfaces, and positively charged membranes, charged membranes, charged surfaces, charged switch membranes, charged switched surfaces. Once the nucleic acids have been extracted, the genomic double stranded DNA is used in the methylation analysis.

As used throughout this specification, the terms "therapy" or "treatment" refer to the alleviation or measurable lessening of one or more symptoms or measurable markers of a pathological condition such as a disease or disorder. The terms encompass primary treatments as well as neo-adjuvant treatments, adjuvant treatments and adjunctive therapies. The terms "anti-cancer therapy" or "anticancer treatment" broadly refer to the alleviation or measurable lessening of one or more symptoms or measurable markers of a neoplastic disease. Measurable lessening includes any statistically significant decline in a measurable marker or symptom. Generally, the terms encompass both curative treatments and treatments directed to reduce symptoms and/or slow progression of the disease. The terms encompass both the therapeutic treatment of an already developed pathological condition, as well as prophylactic or preventative measures, wherein the aim is to prevent or lessen the chances of incidence of a pathological condition. In certain embodiments, the terms may relate to therapeutic treatments. In certain other embodiments, the terms may relate to preventative treatments. Treatment of a chronic pathological condition during the period of remission may also be deemed to constitute a therapeutic treatment. The term may encompass ex vivo or in vivo treatments.

The term "immunotherapy" broadly encompasses any treatment that modulates a subject's immune system. In particular, the term comprises any treatment that modulates an immune response, such as a humoral immune response, a cell-mediated immune response, or both. An immune response may typically involve a response by a cell of the immune system, such as a B cell, cytotoxic T cell (CTL), T helper (Th) cell, regulatory T (Treg) cell, antigen-presenting cell (APC), dendritic cell, monocyte, macrophage, natural killer T (NKT) cell, natural killer (NK) cell, basophil, eosinophil, or neutrophil, to a stimulus. In the context of anti-cancer treatments, immunotherapy may preferably elicit, induce or enhance an immune response, such as in particular an immune response specifically against tumor tissues or cells, such as to achieve tumor cell death. Immunotherapy may modulate, such increase or enhance, the abundance, function, and/or activity of any component of the immune system, such as any immune cell, such as without limitation T cells (e.g., CTLs or Th cells), dendritic cells, and/or NK cells.

Immunotherapies can be categorized as active, passive or a combination thereof. Anti-cancer immunotherapy is based on the fact that cancer cells typically have molecules on their surface, known as tumor antigens that can be detected by the immune system. Active immunotherapy directs the immune system to attack tumor cells by targeting tumor antigens. Passive immunotherapies enhance existing anti-tumor responses, typically through binding and modifying the intracellular signalling of surface receptors.

Immunotherapy comprises cell-based immunotherapy in which immune cells, such as T cells and/or dendritic cells, are transferred into the patient. The term also comprises an administration of substances or compositions, such as chemical compounds and/or biomolecules (e.g., antibodies, antigens, interleukins, cytokines, or combinations thereof), that modulate a subject's immune system.

Examples of cancer immunotherapy include without limitation treatments employing monoclonal antibodies, for example immune checkpoint inhibitors, Fc-engineered monoclonal antibodies against proteins expressed by tumor cells, prophylactic or therapeutic cancer vaccines, adoptive cell therapy, and combinations thereof.

In certain embodiments of the methods or uses as taught herein, the immunotherapy may comprise treatment with one or more immunotherapy agents selected from the group consisting of immune checkpoint inhibitors, monoclonal antibodies, vaccines, and adoptive cell therapy.

In certain embodiments of the methods or uses as taught herein, the immunotherapy agent may be an immune checkpoint inhibitor, a monoclonal antibody, a vaccine, an adoptive cell therapy agent, or a combination thereof.

In certain embodiments of the methods or uses as taught herein, the immunotherapy may comprise treatment with one or more immune checkpoint inhibitors (i.e., inhibitors of immune checkpoints). The present methods advantageously allow predicting responsiveness to treatment with one or more immune checkpoint inhibitors in a subject, preferably human subject, having a neoplastic disease, thereby allowing to treat only those subjects which will clinically benefit from such treatment. Immune checkpoints are inhibitory pathways that slow down or stop immune reactions and prevent excessive tissue damage from uncontrolled activity of immune cells. Inhibition of immune checkpoint targets can stimulate immune responses by immune cells, such as CTLs, against tumor cells.

Examples of immune checkpoint targets for inhibition include without limitation PD-1 (examples of PD-1 inhibitors include without limitation pembrolizumab, nivolumab, and combinations thereof), CTLA-4 (examples of CTLA-4 inhibitors include without limitation ipilimumab, tremelimumab, and combinations thereof), PD-L1 (examples of PD-L1 inhibitors include without limitation atezolizumab), LAG3, B7-H3 (CD276), B7-H4, TIM-3, BTLA, A2aR, killer cell immunoglobulin- like receptors (KIRs), IDO, and combinations thereof.

In certain embodiments of the methods or uses as taught herein, the immune checkpoint inhibitor may be a PD-1 inhibitor, a CTLA-4 inhibitor, a PD-L1 inhibitor, a LAG3 inhibitor, a B7-H3 (CD276) inhibitor, a B7-H4 inhibitor, a TIM-3 inhibitor, a BTLA inhibitor, a A2aR inhibitor, a killer cell immunoglobulin-like receptor (KIR) inhibitor, an IDO inhibitor, or a combination thereof. Since therapies with such immune checkpoint inhibitors are significantly toxic and very expensive, the present methods advantageously allow to predict patient responsiveness to such therapies, thereby allowing to determine an efficacious and cost-effective course of therapeutic intervention.

In certain embodiments, the PD-1 inhibitor may be pembrolizumab, nivolumab, or a combination thereof. In certain embodiments, the CTLA-4 inhibitor may be ipilimumab, tremelimumab, or a combination thereof. In certain embodiments, the PD-L1 inhibitor may be atezolizumab.

By means of further guidance, Fc-optimized monoclonal antibodies are configured to specifically bind a protein expressed by tumor cells, such as a tumor antigen, and comprise an engineered Fc portion mediating effector functions, such as antibody-dependent cellular cytotoxicity, complement-dependent cytotoxicity, and/or antibody-dependent cell-mediated phagocytosis.

The term "tumor antigen" as used throughout this specification refers to an antigen that is uniquely or differentially expressed by a tumor cell, whether intracellular or on the tumor cell surface (preferably on the tumor cell surface), compared to a normal or non-neoplastic cell. By means of example, a tumor antigen may be present in or on a tumor cell and not typically in or on normal cells or non-neoplastic cells, or a tumor antigen may be present in or on a tumor cell in greater amounts than in or on normal or non-neoplastic cells, or a tumor antigen may be present in or on tumor cells in a different form than that found in or on normal or non-neoplastic cells. The term thus includes tumor-specific antigens (TSA), including tumor-specific membrane antigens, tumor- associated antigens (TAA), including tumor-associated membrane antigens, embryonic antigens on tumors, growth factor receptors, growth factor ligands, etc. Examples of tumor antigens include, without limitation, β-human chorionic gonadotropin ( HCG), glycoprotein 100 (gplOO/Pmel 17), carcinoembryonic antigen (CEA), tyrosinase, tyrosinase-related protein 1 (gp75/TRPl), tyrosinase- related protein 2 (TRP-2), NY-BR-1, NY-CO-58, NY-ESO-1, MN/gp250, idiotypes, telomerase, synovial sarcoma X breakpoint 2 (SSX2), mucin 1 (MUC-1), antigens of the melanoma-associated antigen (MAGE) family, high molecular weight-melanoma associated antigen (HMW-MAA), melanoma antigen recognized by T cells 1 (MARTI), Wilms' tumor gene 1 (WT1), HER2/neu, mesothelin (MSLN), alphafetoprotein (AFP), cancer antigen 125 (CA-125), and abnormal forms of ras or p53. Further targets in neoplastic diseases include without limitation CD37 (chronic lymphocytic leukemia), CD123 (acute myeloid leukemia), CD30 (Hodgkin/large cell lymphoma), MET (NSCLC, gastroesophageal cancer), IL-6 (NSCLC), and GITR (malignant melanoma).

The term "vaccine" generally refers to a therapeutic or prophylactic pharmaceutical composition for in vivo administration to a subject, comprising a component to which a vaccinated subject is induced to raise an immune response, preferably a protective immune response, or immune tolerance (tolerising vaccines).

Optionally, the vaccine may further comprise one or more adjuvants for enhancing the immune response. Suitable adjuvants include, for example saponin, mineral gels such as aluminium hydroxide, surface active substances such as lysolecithin, pluronic polyols, polyanions, peptides, oil or hydrocarbon emulsions, bacilli Calmette-Guerin (BCG), keyhole limpet hemocyanin (KLH), monophosphoryl lipid A (MPL), Corynebacterium parvum, ohgodeoxynucleotides containing unmethylated CpG motif, and QS-21.

Optionally, the vaccine may further comprise one or more immunostimulatory molecules, or one or more molecules promoting immune tolerance. Examples of such molecules include various cytokines, lymphokines and chemokines. By means of example, examples of molecules with immunostimulatory, immune-potentiating, and pro-inflammatory activities, such as interleukins (e.g., IL-1, IL-2, IL-3, IL-4, IL-12, IL-13); growth factors (e.g., granulocyte-macrophage (GM)- colony stimulating factor (CSF)); and other immunostimulatory molecules, such as macrophage inflammatory factor, Flt3 ligand, B7.1 ; B7.2, etc.

Tumor vaccines include vaccines that either a) prevent infections with cancer-causing viruses, b) treat existing cancer (therapeutic cancer vaccines) or c) prevent the development of cancer, or ameliorate its effects (prophylactic cancer vaccines).

One approach to produce tumor vaccines of type b) or c), also known as therapeutic or immunotherapeutic tumor vaccines, is to isolate tumor cells from a cancer patient, prepare an immunogenic composition from said tumor cells, for example, by rendering said tumor cells non- viable, preparing a lysate of said tumor cells, or isolating proteins from said tumor cells, and immunize a subject (e.g., the same cancer patient or another subject) with a vaccine comprising said immunogenic composition. The immunogenic composition contains tumor antigen(s) expressed by said tumor cells, whereby the vaccination can elicit or stimulate an immune response (e.g., B-cell or CTL response) against the tumor antigen(s) and the tumor cells expressing the tumor antigen(s).

Another approach to therapeutic anti-cancer vaccination is to generate the immune response in situ in a patient. This enhances the anti-tumor immune response to tumor antigens released following lytic virus replication providing an in situ, patient specific anti-tumor vaccine as a result (examples of suitable oncolytic viruses include but are not limited to talimogene laherparepvec). Yet another approach is to immunize a patient with a compound that play a physiological role in cancer genesis, so that the patient's body eliminates said compound. In such case, the compound is a self-antigen or a self-hapten, i.e., it does not provoke a strong immune response when administered to the patient, but can elicit an adequate immune response when conjugated to a carrier.

Another approach to therapeutic anti-cancer vaccination includes dendritic cell vaccines. The term broadly encompasses vaccines comprising dendritic cells which are loaded with antigen(s) against which an immune reaction is desired.

The term "dendritic cell" (DC) may refer to any member of a diverse population of morphologically similar cell types found in lymphoid or non-lymphoid tissues. DC may include, for example, "professional" antigen presenting cells, and have a high capacity for sensitising MHC- restricted T cells. DCs may be recognised, for example, by function, by phenotype and/or by gene expression pattern, particularly by cell surface phenotype. These cells can be characterised by their distinctive morphology, high levels of surface MHC-class II expression and ability to present antigen to CD4+ and/or CD8+ T cells, particularly to naive T cells. Functionally, DCs may be identified by any suitable assay, known to one of skilled in the art, for determination of antigen presentation. Such assays may include, for example, testing the ability to stimulate antigen-primed and/or naive T cells by presentation of a test antigen, followed by determination of T cell proliferation, release of cytokines such as IL-2, and the like. Dendritic cells can be isolated or generated from a biological sample by methods well known in the art. Suitable biological samples for isolation or generation of DC include without limitation a peripheral blood sample, bone marrow sample, umbilical cord blood sample or the like. By means of an example but without limitation, DC present in a biological sample may be isolated by immunofluorescent or immunomagnetic labelling of select surface markers known to be expressed or not expressed by DC, coupled with a corresponding fluorescence activated cell sorting (FACS) gating strategy or immunomagnetic separation, respectively. Alternatively, DC can be generated from CD14+ monocytes by incubating them with suitable cytokines (Zhou & Tedder, Proc Natl Acad Sci USA. 1996, vol. 93, 2588-92).

The term "antigen loading" as used throughout this specification refers to a method or process of delivering one or more antigens to immune cells, such as particularly to antigen-presenting cells, such as more particularly to dendritic cells, such that the antigenic epitopes of the antigen(s) are presented on MHC, whether intracellular or on the immune cell surface. Typically, immune cells may be loaded with antigen(s) by a process comprising contacting or incubating the immune cells in vitro I ex vivo with a composition comprising the antigen(s) or a composition comprising nucleic acid(s) encoding the antigen(s) under conditions that permit the immune cells to contact, express (if needed), process and present the antigen(s) on MHC. The skilled person will know the incubation temperature and time periods sufficient to allow for effective loading of antigens. For example, incubation steps may be typically from between about 1 to about 2 or about 4 hours, at temperatures of between about 25°C to about 37°C and/or may be overnight at about 4°C, and the like. By means of an example, the immune cells may be contacted with a composition comprising an isolated antigen, for example, an antigen isolated from a naturally-occurring source of the antigen, or an antigen produced recombinantly by a suitable host or host cell expression system and isolated therefrom (e.g., a suitable bacterial, yeast, fungal, plant or animal host or host cell expression system), or produced recombinantly by cell-free transcription or translation, or non- biological nucleic acid or peptide synthesis. By means of another example, the immune cells may be contacted with a composition comprising a naturally- occurring source of the antigen, i.e., substantially without isolating the antigen from said naturally- occurring source. For instance, the immune cells may be contacted with a composition comprising cells which naturally express the antigen or cell debris of such cells, e.g., tumor cells expressing tumor antigen(s). Suitably, such cells may be rendered non- viable and preferably lysed, for example, killed and preferably lysed by a mechanical, chemical or physical treatment, such as heat killed, apoptotic, necrotic or otherwise processed. By means of a further example, the immune cells may be contacted with cells of a suitable host or host cell expression system which recombinantly produce the antigen, i.e., substantially without isolating the antigen from said cells. Suitably, such cells may be rendered non-viable and preferably lysed, for example, killed and preferably lysed by a mechanical, chemical or physical treatment, such as heat killed or otherwise processed. Immune cells may also be loaded with an antigen by introducing into the immune cells a nucleic acid, commonly a recombinant nucleic acid, encoding the antigen, whereby the immune cells express the antigen.

Adoptive cell therapy (ACT) can refer to the transfer of cells, most commonly immune-derived cells, such as in particular cytotoxic T cells (CTLs), back into the same patient or into a new recipient host with the goal of transferring the immunologic functionality and characteristics into the new host. If possible, use of autologous cells helps the recipient by minimizing tissue rejection and graft vs. host disease issues.

The adoptive transfer of autologous tumor infiltrating lymphocytes (TILs) or genetically re-directed peripheral blood mononuclear cells has been used to successfully treat patients with advanced solid tumors, including melanoma and colorectal carcinoma, as well as patients with CD19-expressing hematologic malignancies. Adoptive transfer of immune system cells, such as T cells, specific for selected antigens, such as tumor associated antigens is particularly envisaged.

Various strategies may for example be employed to genetically modify T cells by altering the specificity of the T cell receptor (TCR) for example by introducing new TCR a and β chains with selected peptide specificity. Alternatively, chimeric antigen receptors (CARs) may be used in order to generate immunoresponsive cells, such as T cells, specific for selected targets, such as malignant cells, with a wide variety of receptor chimera constructs having been described.

Examples of CAR constructs include without limitation 1) CARs consisting of a single-chain variable fragment of an antibody specific for an antigen, for example comprising a V_L linked to a V_H of a specific antibody, linked by a flexible linker, for example by a CD8a hinge domain and a CD8a transmembrane domain, to the transmembrane and intracellular signaling domains of either CD3ζ or FcRy; and 2) CARs further incorporating the intracellular domains of one or more costimulatory molecules, such as CD28, OX40 (CD134), or 4- IBB (CD137) within the endodomain, or even including combinations of such costimulatory endodomains.

A further aspect relates to an immunotherapy agent, such as an immune checkpoint inhibitor, for use in a method of treating a neoplastic disease in a subject, wherein the subject has been selected as having a neoplastic disease characterised by hypomethylation of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

A further aspect relates to an immunotherapy agent, such as an immune checkpoint inhibitor, for use in a method of treating a neoplastic disease in a subject, wherein the subject has been selected as responsive to immunotherapy by a method as taught herein.

A related aspect provides an immunotherapy agent, such as an immune checkpoint inhibitor, for use in a method of treating a neoplastic disease in a subject, wherein the subject has a neoplastic disease characterised by hypomethylation of a gene or fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

A further aspect provides an immunotherapy agent, such as an immune checkpoint inhibitor, for use in a method of treating a neoplastic disease in a subject, wherein the method comprises: determining the methylation level of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in a sample from the subject; and

identifying whether the methylation level of the gene or fragment thereof corresponds to hypomethylation.

In certain embodiments, the immunotherapy agent may be an immune checkpoint inhibitor, a monoclonal antibody (such as Fc-optimized monoclonal antibodies), a vaccine (such as dendritic cell vaccines), an adoptive cell therapy agent (such as T cells), or a combination of two or more, such as three or four, thereof.

Further particularly preferred embodiments relate to an immunotherapy agent for use as defined herein or to a method as taught herein, wherein:

the neoplastic disease is characterised by hypomethylation of at least the ΓΝΑ gene or fragment thereof;

the neoplastic disease is selected from the group consisting of skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, and breast cancer;

the neoplastic disease is pheochromocytoma, paraganglioma, thyroid carcinoma, or thymoma; the immunotherapy agent is an immune checkpoint inhibitor;

the immune checkpoint inhibitor is a PD-1 inhibitor, a CTLA-4 inhibitor, a PD-Ll inhibitor, a LAG3 inhibitor, a B7-H3 (CD276) inhibitor, a B7-H4 inhibitor, a TIM-3 inhibitor, a BTLA inhibitor, a A2aR inhibitor, a killer cell immunoglobulin- like receptor (KIR) inhibitor, an IDO inhibitor, or a combination thereof;

the subject is a human subject;

the fragment of the ΓΝΑ gene has a sequence as defined by SEQ ID NO: 1, the fragment of the PTPRCAP gene has a sequence as defined by SEQ ID NO: 2, the fragment of the SEMA3B gene has a sequence as defined by SEQ ID NO: 3, the fragment of the KLHL6 gene has a sequence as defined by SEQ ID NO: 4, and/or the fragment of the RASSFlgene has a sequence as defined by SEQ ID NO: 5; and/or

the methylation level of a gene or fragment thereof in the sample is determined by one or more techniques selected from the group consisting of nucleic acid amplification, PCR, MCP,

MIRA, COBRA, bisulfite pyrosequencing, SSCP analysis, restriction analysis, microarray analysis, and bead-chip technology. A further aspect provides a method of treating a neoplastic disease in a subject in need of such a treatment, comprising administering a therapeutically effective amount of an immunotherapy agent, such as an immune checkpoint inhibitor, to the subject, wherein the subject has been selected as having a neoplastic disease characterised by hypomethylation of a gene or fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

A further aspect provides a method of treating a neoplastic disease in a subject in need of such a treatment, comprising administering a therapeutically effective amount of an immunotherapy agent, such as an immune checkpoint inhibitor, to the subject, wherein the subject has a neoplastic disease characterised by hypomethylation of a gene or fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

A related aspect provides a method of treating a neoplastic disease in a subject in need of such a treatment, the method comprising:

determining the methylation level of a gene or fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in a sample from the subject; - identifying whether the methylation level of the gene or fragment thereof corresponds to hypomethylation; and

if the methylation level of the gene or fragment thereof corresponds to hypomethylation, administering a therapeutically effective amount of an immunotherapy agent, such as an immune checkpoint inhibitor, to the subject.

A related aspect provides the use of an immunotherapy agent, such as an immune checkpoint inhibitor, for the manufacture of a medicament for the treatment of a neoplastic disease in a subject, wherein the subject has been selected as having a neoplastic disease characterised by hypomethylation of a gene or fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

A further aspect provides the use of an immunotherapy agent, such as an immune checkpoint inhibitor, for the manufacture of a medicament for the treatment of a neoplastic disease in a subject, wherein the subject has a neoplastic disease characterised by hypomethylation of a gene or fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

A related aspect provides the use of an immunotherapy agent, such as an immune checkpoint inhibitor, for the manufacture of a medicament for the treatment of a neoplastic disease in a subject, wherein the subject has been selected for treatment by a method comprising: determining the methylation level of a gene or fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in a sample from the subject; identifying whether the methylation level of the gene or fragment thereof corresponds to hypomethylation; and

- if the methylation level of the gene or fragment thereof corresponds to hypomethylation, selecting the subject for the treatment.

In certain embodiments, the neoplastic disease is characterised by hypomethylation of the ΓΝΑ gene or fragment thereof.

Hence, a further aspect provides an immunotherapy agent, such as an immune checkpoint inhibitor, for use in a method of treating a neoplastic disease in a subject, wherein the subject has been selected as having a neoplastic disease characterised by hypomethylation of ΓΝΑ gene or a fragment thereof.

A related aspect provides an immunotherapy agent, such as an immune checkpoint inhibitor, for use in a method of treating a neoplastic disease in a subject, wherein the subject has a neoplastic disease characterised by hypomethylation of IN A gene or a fragment thereof.

A further aspect provides an immunotherapy agent, such as an immune checkpoint inhibitor, for use in a method of treating a neoplastic disease in a subject, wherein the method comprises:

determining the methylation level of ΓΝΑ gene or a fragment thereof in a sample from the subject; and

- identifying whether the methylation level of the ΓΝΑ gene or fragment thereof corresponds to hypomethylation.

A further aspect provides a method of treating a neoplastic disease in a subject in need of such a treatment, comprising administering a therapeutically effective amount of an immunotherapy agent, such as an immune checkpoint inhibitor, to the subject, wherein the subject has been selected as having a neoplastic disease characterised by hypomethylation of ΓΝΑ gene or a fragment thereof, or wherein the subject has a neoplastic disease characterised by hypomethylation of ΓΝΑ gene or a fragment thereof.

- determining the methylation level of ΓΝΑ gene or a fragment thereof in a sample from the subject; identifying whether the methylation level of the INA gene or fragment thereof corresponds to hypomethylation; and

if the methylation level of the INA gene or fragment thereof corresponds to hypomethylation, administering a therapeutically effective amount of an immunotherapy agent, such as an immune checkpoint inhibitor, to the subject.

A related aspect provides the use of an immunotherapy agent, such as an immune checkpoint inhibitor, for the manufacture of a medicament for the treatment of a neoplastic disease in a subject, wherein the subject has been selected as having a neoplastic disease characterised by hypomethylation of INA gene or a fragment thereof, or wherein the subject has a neoplastic disease characterised by hypomethylation of INA gene or a fragment thereof.

A related aspect provides the use of an immunotherapy agent, such as an immune checkpoint inhibitor, for the manufacture of a medicament for the treatment of a neoplastic disease in a subject, wherein the subject has been selected for treatment by a method comprising:

determining the methylation level of INA gene or a fragment thereof in a sample from the subject;

identifying whether the methylation level of the INA gene or fragment thereof corresponds to hypomethylation; and

if the methylation level of the INA gene or fragment thereof corresponds to hypomethylation, selecting the subject for the treatment.

In certain embodiments, the neoplastic disease may be characterised by a high MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

Hence, a further aspect provides an immunotherapy agent, such as an immune checkpoint inhibitor, for use in a method of treating a neoplastic disease in a subject, wherein the subject has been selected as having a neoplastic disease characterised by a high MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl, or wherein the subject has a neoplastic disease characterised by a high MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl .

A further aspect provides an immunotherapy agent, such as an immune checkpoint inhibitor, for use in a method of treating a neoplastic disease in a subject, wherein the method comprises: determining the MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from the subject; and

identifying whether the MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA,

PTPRCAP, SEMA3B, KLHL6, and RASSFl corresponds to a high MeTIL score.

A further aspect provides a method of treating a neoplastic disease in a subject in need of such a treatment, comprising administering a therapeutically effective amount of an immunotherapy agent, such as an immune checkpoint inhibitor, to the subject, wherein the subject has been selected as having a neoplastic disease characterised by a high MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl, or wherein the subject has a neoplastic disease characterised by a high MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl .

determining the MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl, in a sample from the subject;

identifying whether the MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl corresponds to a high MeTIL score; and if the MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B,

KLHL6, and RASSFl corresponds to a high MeTIL score, administering a therapeutically effective amount of an immunotherapy agent, such as an immune checkpoint inhibitor, to the subject.

A related aspect provides the use of an immunotherapy agent, such as an immune checkpoint inhibitor, for the manufacture of a medicament for the treatment of a neoplastic disease in a subject, wherein the subject has been selected as having a neoplastic disease characterised by a high MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl, or wherein the subject has a neoplastic disease characterised by a high MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

determining the MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFlin a sample from the subject;

- identifying whether the MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 corresponds to a high MeTIL score; and if the MeTIL score of the two or more genes or fragments thereof, preferably of the five genes or fragments thereof, selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 corresponds to a high MeTIL score, selecting the subject for the treatment.

As used herein, a phrase such as "a subject in need of treatment" includes subjects that would benefit from treatment of a given condition, particularly a neoplastic disease such as skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, or thymoma. Such subjects may include, without limitation, those that have been diagnosed with said condition, those prone to develop said condition and/or those in who said condition is to be prevented.

The terms "treat" or "treatment" encompass both the therapeutic treatment of an already developed disease or condition, such as the therapy of an already developed neoplastic disease, as well as prophylactic or preventive measures, wherein the aim is to prevent or lessen the chances of incidence of an undesired affliction, such as to prevent occurrence, development and progression of a neoplastic disease. Beneficial or desired clinical results may include, without limitation, alleviation of one or more symptoms or one or more biological markers, diminishment of extent of disease, stabilised (i.e., not worsening) state of disease, delay or slowing of disease progression, amelioration or palliation of the disease state, and the like. "Treatment" can also mean prolonging survival as compared to expected survival if not receiving treatment.

The term "prophylactically effective amount" refers to an amount of an active compound or pharmaceutical agent that inhibits or delays in a subject the onset of a disorder as being sought by a researcher, veterinarian, medical doctor or other clinician. The term "therapeutically effective amount" as used herein, refers to an amount of active compound or pharmaceutical agent that elicits the biological or medicinal response in a subject that is being sought by a researcher, veterinarian, medical doctor or other clinician, which may include inter alia alleviation of the symptoms of the disease or condition being treated. Methods are known in the art for determining therapeutically and prophylactically effective doses for the pharmaceutical formulation as taught herein.

The products and methods as taught herein allow to administer a therapeutically effective amount of an immune checkpoint inhibitor as taught herein in subjects having a neoplastic disease which will benefit from such treatment. The term "therapeutically effective amount" as used herein, refers to an amount of active compound or pharmaceutical agent that elicits the biological or medicinal response in a subject that is being sought by a surgeon, researcher, veterinarian, medical doctor or other clinician, which may include inter alia alleviation of the symptoms of the disease or condition being treated. Methods are known in the art for determining therapeutically effective doses of an immune checkpoint inhibitor as taught herein.

The term "therapeutically effective dose" as used herein refers to an amount of an immune checkpoint inhibitor as taught herein, that when administered brings about a positive therapeutic response with respect to treatment of a patient having a neoplastic disease.

Appropriate therapeutically effective doses of an immune checkpoint inhibitor as taught herein may be determined by a qualified physician with due regard to the nature of the immune checkpoint inhibitor, the disease condition and severity, and the age, size and condition of the patient.

Without limitation, a typical dose of an immune checkpoint inhibitor (e.g., Pembrolizumab) to be administered may range from about 2 mg/kg body weight to about 10 mg/kg body weight per administration.

Without limitation, a typical dose of an immune checkpoint inhibitor to be administered may range from about 10 mg to about 2000 mg, or from about 10 mg to about 1000 mg per administration. For example, the dose of an immune checkpoint inhibitor to be administered may range from about 50 mg to about 1500 mg or from about 100 mg to about 500 mg or from about 75 mg to about 200 mg, per administration. Preferably, the dose of an immune checkpoint inhibitor to be administered may be about 125 mg per administration.

For instance, an immune checkpoint inhibitor such as Pembrolizumab (PD-1 inhibitor) may be intravenously (iv) administered at a dose of 10 mg/kg until progression, or at a fixed dose of 200 mg every 3 weeks until progression. Alternatively, an immune checkpoint inhibitor such as Atezolizumab (PD-Ll inhibitor) may be administered by intravenous (iv) administration at a fixed dose of 1200 mg every three weeks. Other available immune checkpoint inhibitors such as PD1 and PD-L1 inhibitors include for instance Nivolumab, Avelumab, and Durvalumab. All these immune checkpoint inhibitors may be delivered as a monotherapy or in combination with CTLA-4 inhibitors, chemotherapy and/or radiotherapy.

Further aspects relate to a set of (isolated) oligonucleotides useful for practicing the uses and methods as described throughout this specification.

An aspect relates to a set of oligonucleotides for determining the methylation level of ΓΝΑ gene or a fragment thereof, PTPRCAP gene or a fragment thereof, SEMA3B gene or a fragment thereof, KLHL6 gene or a fragment thereof, and/or RASSF1 gene or a fragment thereof, or of one or more gene fragments as defined by SEQ ID NO: 1 SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, and SEQ ID NO: 5, or of one or more CpG dinucleotides having a chromosomal position as defined in Table 3, the set of isolated oligonucleotides comprising or consisting of isolated oligonucleotides having a nucleotide sequence complementary to a nucleotide sequence as defined by SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, and/or SEQ ID NO: 5.

Hence, an aspect relates to a set of isolated oligonucleotides comprising or consisting of isolated oligonucleotides having a nucleotide sequence complementary to a nucleotide sequence as defined by SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, and/or SEQ ID NO: 5.

In certain embodiments, the set of isolated oligonucleotides may comprise isolated oligonucleotides having a nucleotide sequence complementary to a nucleotide sequence as defined by SEQ ID NO: 1. In further embodiments, the set of isolated oligonucleotides may further comprise one or more isolated oligonucleotides having a nucleotide sequence complementary to a nucleotide sequence as defined by SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, and SEQ ID NO: 5.

In certain preferred embodiments, the set of isolated oligonucleotides may comprise or consist of isolated oligonucleotides having a nucleotide sequence complementary to a nucleotide sequence as defined by SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, and SEQ ID NO: 5.

A further aspect relates to the use of a set of isolated oligonucleotides as taught herein for predicting responsiveness to immunotherapy in a subject having a neoplastic disease.

Further aspects relate to the use of a set of isolated oligonucleotides as taught herein for indicating immunotherapy as a suitable treatment for a neoplastic disease in a subject; for predicting an immunotherapy outcome in a subject having a neoplastic disease; for the stratification of subjects having a neoplastic disease; or for predicting survival or for prognosis in a subject having a neoplastic disease. Preferably, the subject is a human subject. Also disclosed herein are kits of parts comprising a set of isolated oligonucleotides as taught herein. The kits of parts may further comprise a reagent that selectively modifies an unmethylated cytosine residue but that is incapable of modifying a methylated cytosine residue. The kits of parts may also comprise one or more reference methylation signatures as defined herein, and/or means for determining the methylation level.

The terms "kit of parts" and "kit" as used throughout this specification refer to a product containing components necessary for carrying out the specified methods, packed so as to allow their transport and storage. Materials suitable for packing the components comprised in a kit include crystal, plastic (e.g., polyethylene, polypropylene, polycarbonate), bottles, flasks, vials, ampules, paper, envelopes, or other types of containers, carriers or supports. Where a kit comprises a plurality of components, at least a subset of the components (e.g., two or more of the plurality of components) or all of the components may be physically separated, e.g., comprised in or on separate containers, carriers or supports. The components comprised in a kit may be sufficient or may not be sufficient for carrying out the specified methods, such that external reagents or substances may not be necessary or may be necessary for performing the methods, respectively. Typically, kits are employed in conjunction with standard laboratory equipment, such as liquid handling equipment, environment (e.g., temperature) controlling equipment, analytical instruments, etc. In addition to the recited set of isolated oligonucleotides as taught herein, optionally provided on arrays or microarrays, the present kits may also include some or all of solvents, buffers (such as for example but without limitation histidine-buffers, citrate-buffers, succinate-buffers, acetate-buffers, phosphate-buffers, formate buffers, benzoate buffers, TRIS (Tris(hydroxymethyl)-aminomethan) buffers or maleate buffers, or mixtures thereof), enzymes (such as for example but without limitation thermostable DNA polymerase), detectable labels, detection reagents, and control formulations (positive and/or negative), useful in the specified methods. Typically, the kits may also include instructions for use thereof, such as on a printed insert or on a computer readable medium. The terms may be used interchangeably with the term "article of manufacture", which broadly encompasses any man-made tangible structural product, when used in the present context.

A further aspect relates to the use of a kit of parts as taught herein for predicting responsiveness to immunotherapy in a subject having a neoplastic disease.

Yet further aspects relate to the use of a kit of parts as taught herein for indicating immunotherapy as a suitable treatment for a neoplastic disease in a subject; for predicting an immunotherapy outcome in a subject having a neoplastic disease; for the stratification of subjects having a neoplastic disease; or for predicting survival or for prognosis in a subject having a neoplastic disease. Preferably, the subject is a human subject. The present application also provides aspects and embodiments as set forth in the following Statements:

Statement 1. A method for predicting responsiveness to immunotherapy in a subject having a neoplastic disease, the method comprising:

(A) determining the methylation level of a gene or a fragment thereof selected from the group consisting of internexin neuronal intermediate filament protein alpha (ΓΝΑ), protein tyrosine phosphatase, receptor type C-associated protein (PTPRCAP), semaphorin 3B (SEMA3B), kelch- like family member 6 (KLHL6), and Ras association domain family member 1 (RASSFl) in a sample from the subject, wherein:

- hypomethylation of the gene or fragment thereof in the sample indicates that the subject will be responsive to immunotherapy; or

hypermethylation of the gene or fragment thereof in the sample indicates that the subject will be unresponsive to immunotherapy; or

(B)

(i) determining a methylation profile of two or more genes or fragments thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSFl in the sample from the subject;

Statement 2. The method according to Statement 1, wherein the immunotherapy comprises treatment with one or more immune checkpoint inhibitors.

Statement 3. The method according to Statement 2, wherein the immune checkpoint inhibitor is a PD-1 inhibitor, a CTLA-4 inhibitor, a PD-L1 inhibitor, a LAG3 inhibitor, a B7-H3 (CD276) inhibitor, a B7-H4 inhibitor, a TIM-3 inhibitor, a BTLA inhibitor, a A2aR inhibitor, a killer cell immunoglobulin- like receptor (KIR) inhibitor, an IDO inhibitor, or a combination thereof.

Statement 4. The method according to any one of Statements 1 to 3, wherein the method comprises determining the methylation level of the ΓΝΑ gene or fragment thereof. Statement 5. The method according to any one of Statements 1 to 4, wherein the method comprises determining the methylation profile of the ΓΝΑ gene or fragment thereof, the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSF1 gene or fragment thereof.

Statement 6. A method for predicting survival or for prognosis in a subject having a neoplastic disease, the method comprising:

(Α') determining the methylation level of a gene or a fragment thereof selected from the group consisting of internexin neuronal intermediate filament protein alpha (INA), protein tyrosine phosphatase, receptor type C-associated protein (PTPRCAP), semaphorin 3B (SEMA3B), kelch- like family member 6 (KLHL6), and Ras association domain family member 1 (RASSFl) in a sample from the subject, wherein:

hypermethylation of the gene or fragment thereof in the sample indicates a reduced chance of survival of the subject or indicates an unfavourable prognosis; or

(Β')

(ί') determining a methylation profile of two or more genes or fragments thereof selected from the group consisting of internexin neuronal intermediate filament protein alpha (INA), protein tyrosine phosphatase, receptor type C-associated protein (PTPRCAP), semaphorin 3B (SEMA3B), kelch- like family member 6 (KLHL6), and Ras association domain family member 1 (RASSFl) in a sample from the subject;

Statement 7. The method according to any one of Statements 1 to 6, wherein the neoplastic disease is selected from the group consisting of skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, and breast cancer. Statement 8. The method according to any one of Statements 1 to 7, wherein the neoplastic disease is pheochromocytoma, paraganglioma, thyroid carcinoma, or thymoma.

Statement 9. The method according to any one of Statements 1 to 8, wherein the sample is a neoplastic tissue sample, preferably a tumor biopsy or fine-needle aspirate, or resected tumor tissue; and/or wherein the sample is a formalin-fixed paraffin-embedded (FFPE) sample or fresh- frozen sample, preferably a FFPE sample.

Statement 10. The method according to any one of Statements 1 to 9, wherein the methylation profile is determined by calculating a score from the methylation levels of the two or more genes or fragments thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

Statement 11. The method according to any one of Statements 1 to 10, wherein the subject is a human subject.

Statement 12. The method according to any one of Statements 1 to 11, wherein the fragment of the ΓΝΑ gene has a sequence as defined by SEQ ID NO: 1, the fragment of the PTPRCAP gene has a sequence as defined by SEQ ID NO: 2, the fragment of the SEMA3B gene has a sequence as defined by SEQ ID NO: 3, the fragment of the KLHL6 gene has a sequence as defined by SEQ ID NO: 4, and/or the fragment of the RASSFl gene has a sequence as defined by SEQ ID NO: 5.

Statement 13. The method according to any one of Statements 1 to 12, wherein the methylation level of a gene or fragment thereof in the sample is determined by one or more techniques selected from the group consisting of nucleic acid amplification, polymerase chain reaction (PCR), methylation specific PCR (MCP), methylated-CpG island recovery assay (MIRA), combined bisulfite-restriction analysis (COBRA), bisulfite pyrosequencing, single-strand conformation polymorphism (SSCP) analysis, restriction analysis, microarray analysis, and bead-chip technology.

Statement 14. An immunotherapy agent for use in a method of treating a neoplastic disease in a subject,

(A) wherein the subject has been selected as having a neoplastic disease characterised by hypomethylation of a gene or a fragment thereof selected from the group consisting of internexin neuronal intermediate filament protein alpha (INA), protein tyrosine phosphatase, receptor type C- associated protein (PTPRCAP), semaphorin 3B (SEMA3B), kelch-like family member 6 (KLHL6), and Ras association domain family member 1 (RASSFl); or

(B) wherein the subject has been selected as responsive to immunotherapy by a method as defined in any one of claims 1 to 5, or 7 to 13. Statement 15. The immunotherapy agent for use according to Statement 14, wherein the neoplastic disease is characterised by hypomethylation of at least the ΓΝΑ gene or fragment thereof.

Statement 16. The immunotherapy agent for use according to Statement 14 or 15, wherein the neoplastic disease is selected from the group consisting of skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, and breast cancer.

Statement 17. The immunotherapy agent for use according to any one of Statements 14 to 16, wherein the neoplastic disease is pheochromocytoma, paraganglioma, thyroid carcinoma, or thymoma.

Statement 18. The immunotherapy agent for use according to any one of Statements 14 to 17, wherein the immunotherapy agent is an immune checkpoint inhibitor.

Statement 19. The immunotherapy agent for use according to any one of Statements 14 to 18, wherein the immune checkpoint inhibitor is a PD-1 inhibitor, a CTLA-4 inhibitor, a PD-L1 inhibitor, a LAG3 inhibitor, a B7-H3 (CD276) inhibitor, a B7-H4 inhibitor, a TIM-3 inhibitor, a BTLA inhibitor, a A2aR inhibitor, a killer cell immunoglobulin- like receptor (KIR) inhibitor, an IDO inhibitor, or a combination thereof.

Statement 20. The immunotherapy agent for use according to any one of Statements 14 to 19, wherein the subject is a human subject.

Statement 21. The immunotherapy agent for use according to any one of Statements 14 to 20, wherein the fragment of the INA gene has a sequence as defined by SEQ ID NO: 1, the fragment of the PTPRCAP gene has a sequence as defined by SEQ ID NO: 2, the fragment of the SEMA3B gene has a sequence as defined by SEQ ID NO: 3, the fragment of the KLHL6 gene has a sequence as defined by SEQ ID NO: 4, and/or the fragment of the RASSFlgene has a sequence as defined by SEQ ID NO: 5.

Statement 22. The immunotherapy agent for use according to any one of Statements 14 to 22, wherein the methylation level of a gene or fragment thereof in the sample is determined by one or more techniques selected from the group consisting of nucleic acid amplification, polymerase chain reaction (PCR), methylation specific PCR (MCP), methylated-CpG island recovery assay (MIRA), combined bisulfite-restriction analysis (COBRA), bisulfite pyrosequencing, single-strand conformation polymorphism (SSCP) analysis, restriction analysis, microarray analysis, and bead- chip technology.

While the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications, and variations will be apparent to those skilled in the art in light of the foregoing description. Accordingly, it is intended to embrace all such alternatives, modifications, and variations as follows in the spirit and broad scope of the appended claims.

The herein disclosed aspects and embodiments of the invention are further supported by the following examples.

EXAMPLES

Previously, the present inventors evaluated a methylation profile involving the genes ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1 in a method for predicting susceptibility to anthracycline treatment in patients with breast cancer.

By extensive research, as provided below, the inventors have found that determining methylation of a gene or a fragment thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1, or determining the methylation profile of two or more genes or fragments thereof selected from the group consisting of ΓΝΑ, PTPRCAP, SEMA3B, KLHL6, and RASSF1 can be used: 1) as a marker for predicting survival in a subject having cancer, such as in particular in a human subject having skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, or breast cancer; and/or 2) as a marker for predicting responsiveness to immunotherapy in a subject having cancer, such as in particular in a human subject having skin cutaneous melanoma.

Materials and methods

Histopathological assessment of tumor-infiltrating lymphocytes (TILs) and other cell types of the tumor microenvironment

The histopathological assessment of tumor-infiltrating lymphocytes (PaTIL) was performed on hematoxylin and eosin-stained tumor sections by defining the percentage of mononuclear cells within the epithelium of the invasive tumor cell nests. Tumor-infiltrating lymphocyte frequencies were evaluated independently by two well-trained pathologists and the mean value was used for analyses. PaTIL were available for TCGA tumors.

TCGA data

DNA methylation data and PaTIL for twenty cancer types were downloaded from the TCGA data repository (March 2015) and clinical data and survival information from the 'firehose' website ('Clinical Pick Tierl ' files January 2017, http://gdac.broadinstitute.org/). Histopathological measurements of PaTIL for TCGA tumors were performed on hematoxylin and eosin-stained sections. A minimum of ten specimen fields were assessed to evaluate the percent of nuclei and necrosis. Then the total percent of the different cell types was evaluated (necrotic cells were not part of this calculation) (according to www.nationwidechildrens.org/tss-training-webinar). Melanoma subtype information were obtained from a recent study by the Cancer Genome Atlas Network.

Infinium HumanMethylation450K

Genomic DNA was extracted with the Qiagen-DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany) or QIAamp DNA Mini Kit (Qiagen) as previously described (Dedeurwaerder et al., 2011, EMBO Mol Med, 3, 726-741). DNA methylation was analyzed on Infinium HumanMethylation450K bead-arrays as previously described for Infinium HumanMethylation27K bead-arrays (Dedeurwaerder et al., 2011, EMBO Mol Med, 3, 726-741). Briefly, genomic DNA (300 to 800 ng) was converted with sodium bisulfite using the Zymo EZ DNA Methylation Kit (Zymo Research, Orange, USA) and methylation assays were performed with 4 ml converted DNA at 50 ng/ml according to manufacturer's protocol. Methylumi R package was used to extract raw probe intensity values. The quality of array data was evaluated using the visualization tool from GenomeStudio™ (or in-house R reimplementation of this tool) by assessing the intensity level of the control probes. All samples that showed the expected profiles for the different control probes were utilized for further analyses. Infinium HumanMethylation 450K raw data were submitted to Gene Expression Omnibus database

(http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE72308).

Bioinformatics

Infinium HumanMethylation450K pre-processing: Raw data (uncorrected probe intensity values) from the Infinium Methylation arrays were processed with the following steps: Probes of low quality (detection p-value threshold of 0.05), cross-reactive probes (i.e. targeting several genomic locations) as well as probes containing SNPs based on the extended annotation of Price et al. (2013, Epigenetics Chromatin, 6, 4; Dedeurwaerder et al., 201 1, Epigenomics, 3, 771-784) were removed. Additionally, probes targeting X and Y-chromosomes were removed from the analysis. Beta- values were computed using the following formula: Beta-value = M/[U+M] where M and U are the raw "methylated" and "unmethylated" signals, respectively. Beta-values were corrected for type I and type II bias using the peak-based correction (Dedeurwaerder et al., 2011, Epigenomics, 3, 771 -784; Dedeurwaerder et al., 2014, Brief Bioinform, 15, 929-941).

Selection of markers for MeTIL signature: In a first step, T-lymphocyte-associated cytosines were identified by utilizing previously published genome-wide DNA methylation profiles (Infinium HumanMethylation) from eight normal or cancerous breast epithelial cell lines (MCF10A, MCF-7, T47D, SKBR3, BT20, MDA-MB-231, MDA-MB-361, ZR-75-1) and three T-lymphocyte samples (WEIS3E5, R12C9 and ex-vivo T-cells) (Dedeurwaerder et al., 2011, EMBO Mol Med, 3, 726- 741). We computed the median Beta- value for each probe in the group of T-lymphocytes and in the group of breast epithelial cells and calculated the delta Beta-value for each probe between the median Beta-values of the two groups (Median τ-iymphocytes - Median _Breast epithelial ceils). Probes were selected that were hypomethylated in T-lymphocytes versus breast epithelial cells with a minimum difference in delta Beta of 0.8 (Delta Beta < -0.8). To identify the most discriminative probes, we further selected for probes that showed a low variability within both groups (SD τ-iymphocytes≤ 0.1 & SD Breast epithelial ceils≤ 0.1). This selection approach yielded 29 T-lymphocyte-associated markers.

MeTIL signature optimization (machine learning): A machine learning approach was applied to select for probes from the list of T-lymphocyte-associated cytosines that reflect most accurately the quantity of PaTIL in patient samples. We utilized Infinium HumanMethylation profiles of 105 breast primary tumors (cohort 1) for which H&E staining-based PaTIL (in %) were available. We defined three PaTIL categories based on the pathological intra-tumoral (iTU-Ly) PaTIL readings: 'PaTIL-Absent' (PaTIL < 1%), 'PaTIL-Low' (PaTIL > 1% & PaTIL < 20%) and 'PaTIL-High' (PaTIL > 20% & PaTIL < 100%). The BC cohort was divided into three parts (two 'training' sets and one 'test' set) in order to apply a three-fold cross validation. To establish a small signature with minimal redundancy between probes we applied the mRMR feature selection method to the training set (Peng et al., 2005, IEEE Trans Pattern Anal Mach Intell, 27, 1226-1238). To account for the unequal size between the three TIL categories (PaTIL-High is smaller than PaTIL-Low or PaTIL-Absent), we integrated the 'EasyEnsemble' approach (Liu et al., 2009, IEEE Trans Syst Man Cybern, 39, 539-550) into the model. This approach trained 20 different Random Forest models, each model on a different data set obtained through the inclusion of all samples from the PaTIL High category while randomly selecting the same number of samples from the PaTIL-Low and the PaTIL-Absent category. The performance of the developed 'EasyEnsemble' models was assessed through prediction making in the test set and the computation of the 'Balanced-Error Rate' (BER). For a more robust estimation of the BER, a three-fold cross validation was applied 200 times and for each run randomized data were used as negative control. This entire process was repeated for a signature size ranging from a single cytosine to the entire set of T-lymphocyte- associated cytosines. The signature size, for which no more improvement of the BER was observed (five features signature size), was selected as the final size. This process generated 3x200 output

signatures. The distance between the signatures was defined as

(corspear refers to the spearman correlation, Fl_; to the 1^th feature from signature 1 and F2_; to the i^th feature from signature 2 after sorting the features in order to maximize the sum of the spearman correlation). For each signature, the sum of its pairwise distance to all other output signatures was computed, and the signature with the smallest sum was assumed to be the most representative and chosen as final signature, named "MeTIL signature". Establishment of the MeTIL score: We applied a "normalized PCA" (NPCA) approach to transform the individual methylation values of the probes of the machine learning- derived MeTIL signature into a score ("MeTIL score"), which reflects TIL percentage in a way that does not require complex algorithm and can easily be applied by any lab on any methylation dataset. Therefore, we first standardized (m=0, s=l) the Beta- values of each CpG from the signature on the discovery dataset (cohort 1). A principal component analysis (PCA) was then applied and the first component was used as final MeTIL score for the samples of the discovery set. The MeTIL score on any other datasets was obtained using the NPCA parameters derived from the discovery set with the

S { ht'tH

a: ^' V L I v c IV

following formul ' (beta is the matrix of Beta- values for the MeTIL signature on the new dataset, \ I ' 7 are the data transformed using the scale s and the center c from the discovery cohort and v is the eigenvector from the discovery cohort.

This formula also allows any reader to generate the MeTIL score from any methylation data, for example using the following command in R language: (scale(beta, center=cl, scale=sl)%*%vl)[,l] (beta is the matrix of Beta-values for the probes from the signature (with samples in rows and probes in column) and cl, si and vl are parameters from the discovery cohort that can be found in Table 2.

Table 2: PCA parameters

Simulations: Whole tumor samples were simulated using Infinium methylation profiles from cell lines. Breast epithelial cell line profiles where used to mimic tumor cells while T-lymphocyte profiles represented TILs. A random selection of methylation probes across all cell lines was used to simulate the presence of additional cells types typically represented in a tumor (fibroblasts, endothelial cells, macrophages etc.). These three components and additional noise were combined using the following formula: f $ - f 3^3 ^~*~ ^ where Mc is the combined M-value, fl, f2 and β are the fractions of TILs, tumor cells and other cell-type(s) in the simulated tissue, respectively, and Ml, M2 and M3 are their respective M-values and e a Gaussian noise of mean equal to 0 and standard deviation of ws (s is computed as the standard deviation of the delta between M-values of each possible pair of cell lines from the same type across all Infinium probes and w is a weight used increase/decrease the noise level). M-values were used in this analysis since the heteroscedasticity and the bounded nature of Beta-values are incompatible with a Gaussian noise while M-value are homoscedastic and unbounded (Du et al., 2010, BMC Bioinformatics, 11, 587). The conversion from Beta-values to M-values was achieved using a previously described formula M-value = log2 (b-value/(l - b-value). (Dedeurwaerder et al., 2011, Epigenomics, 3, 771- 784). The combined M-value Mc was converted back into a Beta-value using the appropriate formula (Dedeurwaerder et al., 2011, Epigenomics, 3, 771-784) and the MeTIL score was computed using the NPCA parameters following the formula described in "Establishment of the MeTIL score" (above). To verify the correlation between the MeTIL score and TILs, simulations were performed for increasing values of fl with fixed value of e and f3, and f2 defined as 1- (fl+f3). 50 steps of fl were assessed (i.e. each step corresponding to a 2% increase in TILs if f3=0) and 200 simulations were calculated at each step allowing the spearman correlation to be computed from 10 000 dots.

Statistics

Statistical analyses were conducted with RStudio Version 0.94.110. Differences between more than two groups were assessed with a one-way ANOVA or Chi2 test. Cox proportional hazard regression analyses and Kaplan-Meier survival curves with log-rank tests, recording patients at the time of dead/recurrence or last follow-up visit, were used to compare overall survival or disease free survival rates. Multivariate Cox regression models were established based on the Akaike's information criterion (AIC). Odds ratios (ORs) were used to compare pathologic complete response (pCR) rates. The area under the curve (AUC) was used to assess prediction performance. All P values were two sided and P values < 0.05 were considered statistically significant.

Example 1: Prediction of survival in different cancer types with a method according to an embodiment of the present invention

The methylation signature as provided in Table 3, referred to in the example section as the MeTIL signature, was used to assess prediction of survival differences in different cancer types available in The Cancer Gene Atlas (TCGA). The different cancer types (abbreviation, full name) were BLCA, bladder urothelial carcinoma; BRCA, breast invasive carcinoma; CESC, cervical squamous cell carcinoma and endocervical adenocarcinoma; COREAD, colon and rectum adenocarcinoma; ESCA, esophageal carcinoma; HNSC, head and neck squamous cell carcinoma; KIRP, kidney renal papillary cell carcinoma; LIHC, liver hepatocellular carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; OV, ovarian serous cystadenocarcinoma; PAAD, pancreatic adenocarcinoma; PCPG, pheochromocytoma and paraganglioma; PRAD, prostate adenocarcinoma; SARC, sarcoma; SKCM, skin cutaneous melanoma; STAD, stomach adenocarcinoma; TGCT, testicular germ cell tumors; THCA, thyroid carcinoma; THYM, thymoma; UCEC, uterine corpus endometrial carcinoma.

A normalized PCA approach, as described in the Material and methods section, was applied to transform the individual methylation values of the probes of the MeTIL signature into a score, referred to herein as the MeTIL score.

From the 21 tested cancer types, in head and neck squamous cell carcinoma (HNSC); pheochromocytoma and paraganglioma (PCPG); skin cutaneous melanoma (SKCM); thyroid carcinoma (THCA); and thymoma (THYM), high MeTIL scores associated with better prognosis (FIG. 1, grey and Table 4). On the other hand, pathological assessment of tumor- infiltrating lymphocytes (PaTIL) did not associate with better prognosis (FIG. 1, black and Table 4).

Table 3 : Probe information of the MeTIL signature

Chromosomal position cytosine: Cytosine position hgl9

Table 4: Correlation between MeTIL score or pathological assessment of tumor-infiltrating lymphocytes (PaTIL) and median survival of patients in various cancer cohorts (univariate COX proportional hazards regression)

MeTIL score PaTIL

Cancer Patients HR 95% CI P HR 95% CI P Type (Events)

BLCA 395(157) 0.95 0.85 - 1.05 0.284 1 0.98 - 1.02 0.687

BRCA 1034(128) 0.93 0.84-1.03 0.171 1 0.98 - 1.01 0.567

CESC 304(69) 0.93 0.81 - 1.08 0.359 1.01 1 - 1.02 0.245

COREAD 183(39) 0.79 0.59-1.05 0.108 0.96 0.9-1.03 0.228

ESCA 172(70) 0.98 0.85 - 1.14 0.793 1.01 0.99-1.02 0.217

HNSC 311(113) 0.85 0.74 - 0.98 0.025 0.99 0.97-1.01 0.248

KIRP 188(20) 0.89 0.64 - 1.24 0.486 0.95 0.79-1.13 0.536

LGG 252(33) 1.19 0.95 - 1.49 0.136 0.32 0.02 - 6.74 0.468

LIHC 357(107) 0.93 0.83 - 1.04 0.18 1 0.96-1.04 0.9

LUAD 262(76) 0.91 0.78 - 1.08 0.279 0.99 0.97-1.01 0.374

LUSC 244(93) 0.86 0.74 - 1.01 0.0733 1.01 0.99-1.03 0.248 ov 105(51) 1.13 0.86-1.47 0.386 1 0.99 - 1 0.346

PAAD 143(69) 0.97 0.84 - 1.11 0.628 1 0.99-1.01 0.746

PCPG 179(6) 0.46 0.24 - 0.88 0.0195 1.03 0.99-1.08 0.146

PRAD 415(7) 1.18 0.69-2.03 0.544 0.94 0.8 - 1.11 0.457

SARC 249(83) 0.94 0.84-1.06 0.335 0.86 0.69-1.07 0.181

SKCM 350(181) 0.91 0.85 - 0.98 0.0103 0.96 0.92 - 1.01 0.105

STAD 256(96) 1.05 0.94 - 1.18 0.381 0.98 0.97 - 1 0.103

TGCT 133(4) 1.17 0.63-2.19 0.614 1.02 0.98 - 1.05 0.395

THCA 500(14) 0.6 0.36 - 0.98 0.043 0.47 0.18 - 1.19 0.111 MeTIL score PaTIL

Cancer Patients HR 95% CI P HR 95% CI P Type (Events)

THYM 121(6) 0.66 0.44 - 0.99 0.0425 0.69 0.3 - 1.56 0.372

UCEC 539(69) 0.91 0.76 - 1.1 0.332 1 0.99 - 1.02 0.778

Abbreviations: MeTIL score, individual methylation values of the probes of the MeTIL signature transformed by a normalized PCA approach into a score; PaTIL, pathological assessment of tumor- infiltrating lymphocytes on H&E stained tumor sections; HR, hazard ratio; CI, confidence interval; P, p value

MeTIL scores predicted survival differences independently of other prognostic variables in HNSC, PCPG, SKCM and THYM but also in lung squamous cell carcinoma (LUSC) (FIG. 2, MeTIL: grey, PaTIL: black; and Table 5).

Table 5: Correlation between MeTIL score or pathological assessment of tumor-infiltrating lymphocytes (PaTIL) and median survival of patients in various cancer cohorts (multivariate COX proportional hazards regression; optimal multivariate models for each cancer subtype were determined by applying a forward and backward variable selection based on the Akaike's information criterion)

MeTIL score PaTIL

Cancer Patients HR 95% CI P HR 95% CI P

Type (Events)

BLCA 395(157) 0.92 0.83 - 1.02 0.13 1 0.97 - 1.02 0.68

BRCA 1034(128) 0.99 0.89 - 1.1 0.81 1 0.99 - 1.01 0.914

CESC 304(69) 0.93 0.8 - 1.07 0.322 1.01 1 - 1.02 0.259

COREAD 183(39) 0.85 0.62 - 1.16 0.301 0.97 0.91 - 1.04 0.445

ESCA 172(70) 1.01 0.86 - 1.17 0.942 1.01 0.99 - 1.02 0.285

HNSC 311(113) 0.84 0.73 - 0.97 0.0152 0.99 0.97 - 1.01 0.228

KIRP 188(20) 0.93 0.67 - 1.29 0.67 0.98 0.84 - 1.15 0.835

LGG 252(33) 1.15 0.92 - 1.44 0.207 0.48 0.05 - 4.48 0.517 MeTIL score PaTIL

Cancer Patients HR 95% CI P HR 95% CI P

Type (Events)

LIHC 357(107) 0.93 0.84 - 1.04 0.231 1 0.96 - 10.3 0.865

LUAD 262(76) 0.91 0.78 - 1.07 0.255 0.99 0.97 - 1.02 0.508

LUSC 244(93) 0.85 0.72 - 0.99 0.0416 1.01 0.99 - 1.03 0.262 ov 105(51) 1.12 0.85 - 1.46 0.418 1 0.99 - 1.01 0.377

PAAD 143(69) 0.91 0.79 - 1.06 0.227 1 0.99 - 1.01 0.745

PCPG 179(6) 0.35 0.16 - 0.79 0.0108 1.03 0.99 - 1.08 0.131

PRAD 415(7) 1.35 0.73 - 2.5 0.344 0.95 0.82 - 1.1 0.462

SARC 249(83) 0.94 0.84 - 1.05 0.283 0.87 0.7 - 1.08 0.217

SKCM 350(181) 0.85 0.78 - 0.91 8.71e-06 0.96 0.91 - 1.01 0.152

STAD 256(96) 0.99 0.89 - 1.11 0.93 0.98 0.96 - 1 0.0836

TGCT 133(4) 1.15 0.61 - 2.15 0.662 1.01 0.98 - 1.05 0.459

THCA 500(14) 0.74 0.46 - 1.18 0.207 0.49 0.18 - 1.32 0.157

THYM 121(6) 0.6 0.38 - 0.93 0.0242 0.75 0.33 - 1.7 0.492

UCEC 539(69) 0.89 0.74 - 1.07 0.216 1 0.99 - 1.02 0.761

Furthermore, MeTIL scores were correlated with survival endpoints in breast cancer subtype. Differences in survival were observed in HER2 tumors (HR, 0.37; 95% CI, 0.16 to 0.85; P = 0.02). In luminal tumors (HR, 0.82; 95% CI, 0.67 to 1.02; P = 0.069) and triple-negative (TN) tumors (HR, 0.67; 95% CI, 0.44 to 1.03; P = 0.066), the association between MeTIL scores and survival was borderline significant. PaTIL on the other hand predicted no survival differences in luminal (HR, 0.98; 95% CI, 0.93 to 1.02; P = 0.324), HER2 (HR, 0.56; 95% CI, 0.20 to 1.58; P = 0.273) and TN (HR, 0.99; 95% CI, 0.96 to 1.03; P = 0.733) tumors. Importantly, as in breast cancer, the MeTIL score may have a prognostic value in other cancer types if these are grouped in subtypes. Taken together, these results evidence that the MeTIL score, although originally developed for the evaluation of susceptibility to anthracycline treatment in patients with breast cancer, unexpectedly allows to predict survival in various cancer types, including skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, HER2 -positive breast cancer, luminal breast cancer, and triple-negative breast cancer, and also allows to stratify patients for a better prognosis.

Example 2: Prediction of survival in skin cutaneous melanoma with a method according to an embodiment of the present invention

An unsupervised hierarchical clustering analysis of TCGA skin cutaneous melanomas (SKCM) based on Beta- values of the MeTIL markers was performed. A hypomethylated, an intermediate methylated, and a hypermethylated cluster appeared, which were associated with variable levels of pathological assessment of tumor-infiltrating lymphocytes on H&E stained tumor sections (PaTIL) (P = 0.049), distinct molecular subtypes (P < 0.001), and MeTIL scores (P < 0.001) (FIG. 3) as well as differences in survival (P = 0.018) (FIG. 4). MeTIL score displayed different levels in melanoma subtypes with the immune subtype displaying the highest median MeTIL score (P < 0.001) (FIG. 5).

Together, these data evidence that a method according to an embodiment of the present invention allows to predict survival outcome in various cancer types such as including skin cutaneous melanoma, with good prognosis for immune subtype of melanoma displaying the highest MeTIL score.

Example 3: Prediction of responsiveness to immunotherapy in melanoma with methods according to embodiments of the present invention

In order to assess prediction of responsiveness to immunotherapy in melanoma patients from The Cancer Gene Atlas (TCGA), the methylation level of SEQ ID NO: 1, 2, 3, 4 and 5 (MeTIL signature) and the methylation level of each of SEQ ID NO: 1, 2, 3, 4 and 5 separately were determined.

The MeTIL score displayed potential to predict success of immunotherapy in 84 melanoma patients from TCGA (FIG. 6). The MeTIL score displayed a greater area under the curve (AUC) value (AUC = 62.779%) than tumor-infiltrating lymphocytes quantified by pathology (AUC = 50.67%) (FIG. 6; MeTIL: grey, PaTIL: black). The individual markers of the MeTIL signature (INA, PTPRCAP, SEMA3B, KLHL6, or RASSFl) showed different AUC values for prediction of response to immunotherapy in melanoma (Table 6). Table 6: Prediction of response to immunotherapy in melanoma by determining the methylation level of INA, PTPRCAP, SEMA3B, KLHL6, or RASSF1 independently in 84 melanoma patients that underwent treatment with immunotherapy

The methylation of INA alone displayed greatest AUC values and thus, had highest potential to predict immunotherapy success (Table 6). Indeed, logistic regression modeling confirmed that INA predicted for response to immunotherapy in melanoma (FIG. 7).

Claims

1. A method for predicting responsiveness to immunotherapy in a subject having a neoplastic disease, the method comprising:

(A) determining the methylation level of a gene or a fragment thereof selected from the group consisting of internexin neuronal intermediate filament protein alpha (INA), protein tyrosine phosphatase, receptor type C-associated protein (PTPRCAP), semaphorin 3B (SEMA3B), kelch-like family member 6 (KLHL6), and Ras association domain family member 1 (RASSFl) in a sample from the subject, wherein:

(B)

2. The method according to claim 1, wherein the immunotherapy comprises treatment with one or more immune checkpoint inhibitors.

3. The method according to claim 2, wherein the immune checkpoint inhibitor is a PD-1 inhibitor, a CTLA-4 inhibitor, a PD-L1 inhibitor, a LAG3 inhibitor, a B7-H3 (CD276) inhibitor, a B7-H4 inhibitor, a TIM-3 inhibitor, a BTLA inhibitor, a A2aR inhibitor, a killer cell immunoglobulin- like receptor (KIR) inhibitor, an IDO inhibitor, or a combination thereof. The method according to any one of claims 1 to 3, wherein the method comprises determining the methylation level of the ΓΝΑ gene or fragment thereof.

The method according to any one of claims 1 to 4, wherein the method comprises determining the methylation profile of the ΓΝΑ gene or fragment thereof, the PTPRCAP gene or fragment thereof, the SEMA3B gene or fragment thereof, the KLHL6 gene or fragment thereof, and the RASSFl gene or fragment thereof.

A method for predicting survival or for prognosis in a subject having a neoplastic disease, the method comprising:

(Α') determining the methylation level of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from the subject, wherein:

(Β')

(ί') determining a methylation profile of two or more genes or fragments thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSFl in a sample from the subject;

The method according to any one of claims 1 to 6, wherein the neoplastic disease is selected from the group consisting of skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, and breast cancer.

8. The method according to any one of claims 1 to 7, wherein the neoplastic disease is pheochromocytoma, paraganglioma, thyroid carcinoma, or thymoma.

9. The method according to any one of claims 1 to 8, wherein the sample is a neoplastic tissue sample, preferably a tumor biopsy or fine-needle aspirate, or resected tumor tissue; and/or wherein the sample is a formalin- fixed paraffin-embedded (FFPE) sample or fresh-frozen sample, preferably a FFPE sample.

10. The method according to any one of claims 1 to 9, wherein the methylation profile is determined by calculating a score from the methylation levels of the two or more genes or fragments thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1.

11. The method according to any one of claims 1 to 10, wherein the subject is a human subject.

12. The method according to any one of claims 1 to 11, wherein the fragment of the ΓΝΑ gene has a sequence as defined by SEQ ID NO: 1, the fragment of the PTPRCAP gene has a sequence as defined by SEQ ID NO: 2, the fragment of the SEMA3B gene has a sequence as defined by SEQ ID NO: 3, the fragment of the KLHL6 gene has a sequence as defined by SEQ ID NO: 4, and/or the fragment of the RASSF1 gene has a sequence as defined by SEQ ID NO: 5.

13. The method according to any one of claims 1 to 12, wherein the methylation level of a gene or fragment thereof in the sample is determined by one or more techniques selected from the group consisting of nucleic acid amplification, polymerase chain reaction (PCR), methylation specific PCR (MCP), methylated-CpG island recovery assay (MIRA), combined bisulfite- restriction analysis (COBRA), bisulfite pyrosequencing, single-strand conformation polymorphism (SSCP) analysis, restriction analysis, microarray analysis, and bead-chip technology.

14. An immunotherapy agent for use in a method of treating a neoplastic disease in a subject,

(A) wherein the subject has been selected as having a neoplastic disease characterised by hypomethylation of a gene or a fragment thereof selected from the group consisting of INA, PTPRCAP, SEMA3B, KLHL6, and RASSF1 ; or

(B) wherein the subject has been selected as responsive to immunotherapy by a method as defined in any one of claims 1 to 5, or 7 to 13.

15. The immunotherapy agent for use according to claim 14, wherein: the neoplastic disease is characterised by hypomethylation of at least the ΓΝΑ gene or fragment thereof;

the neoplastic disease is selected from the group consisting of skin cutaneous melanoma, lung squamous cell carcinoma, head and neck squamous cell carcinoma, pheochromocytoma, paraganglioma, thyroid carcinoma, thymoma, and breast cancer; the neoplastic disease is pheochromocytoma, paraganglioma, thyroid carcinoma, or thymoma;

the immunotherapy agent is an immune checkpoint inhibitor;

the immune checkpoint inhibitor is a PD-1 inhibitor, a CTLA-4 inhibitor, a PD-L1 inhibitor, a LAG3 inhibitor, a B7-H3 (CD276) inhibitor, a B7-H4 inhibitor, a TIM-3 inhibitor, a BTLA inhibitor, a A2aR inhibitor, a killer cell immunoglobulin- like receptor (KIR) inhibitor, an IDO inhibitor, or a combination thereof;

the subject is a human subject;

the methylation level of a gene or fragment thereof in the sample is determined by one or more techniques selected from the group consisting of nucleic acid amplification, PCR, MCP, MIRA, COBRA, bisulfite pyrosequencing, SSCP analysis, restriction analysis, microarray analysis, and bead-chip technology.