Gene Regulation

Abstract

To provide processes for analyzing chromosomal regions and interactions related to immune responsiveness.SOLUTION: Disclosed is a process for determining the responsiveness in a human individual to an immunotherapy, the process comprising detecting the presence or absence of interactions between a first, second, third, fourth and fifth chromosomes, where the detection comprises the steps of: (a) crosslinking chromosomal regions coming together in chromosomal interaction; (b) cutting out the crosslinked regions; (c) ligating the crosslinked and cleaved DNA terminals to generate a ligated nucleic acid; (d) detecting the presence or absence of the ligated nucleic acid thereby detecting whether the regions came together in chromosomal interaction, where the ligated nucleic acids corresponding to the first, second, third, fourth and fifth chromosomal interactions can be detected with specific probe sequences respectively, thereby the responsiveness can be determined.SELECTED DRAWING: None

Description

[Technical field]

[0001] The present invention relates to detecting chromosomal interactions. [Background technology]

[0002] The disease process is complex and the outcome cannot be predicted using available methods. In particular, it is difficult to predict which patients will respond to a particular treatment. Summary of the Invention

[0003] Specific chromosome conformation signatures (CCSs) of loci are present or absent due to regulatory epigenetic control settings associated with pathology or therapy. CCSs have a moderate off-rate and, if they represent a particular phenotype or pathology, CCSs change only upon pharmacological signaling, into a new phenotype, or as a result of external interference. Furthermore, the measurement of these events is binary, so this readout is in stark contrast to the continuous readouts of various levels of DNA methylation, histone modifications, and most non-coding RNAs. Continuous readouts, which have been used for most molecular biomarkers so far, pose challenges to data analysis, because the magnitude of change in a given biomarker varies widely from patient to patient, making the classification statistics problematic when used to stratify patient cohorts. These classification statistics are amenable to using biomarkers that have no magnitude and provide only a binary score of phenotypic difference - indicating that chromosome conformation (EpiSwitch™) biomarkers are an excellent resource for potential diagnostic, prognostic and predictive biomarkers.

[0004] The inventors have identified regions of the genome that have chromosomal interactions related to immune responsiveness using an approach that allows the identification of subgroups in a population. The regions, genes, and specific chromosomal interactions identified from two separate studies using different therapies to treat two different conditions were found to determine the overall immune response in patients, such as by regulating immune responses and T cell activation that control cell surface signaling pathways. The inventors' research allows changes in immune responsiveness to be tracked, for example, during the course of disease or treatment.

[0005] Thus, the present invention is a process for detecting a chromosomal state representing a subgroup in a population, comprising determining whether chromosomal interactions related to that chromosomal state are present or absent within a defined region of the genome, said subgroup relating to how immune responsive an individual is; and - said chromosomal interactions have optionally been identified by a method for determining which chromosomal interactions are associated with a chromosomal state corresponding to an immunoresponsive interaction subgroup of a population, the method comprising contacting a first set of nucleic acids from subgroups with different chromosomal states with a second set of index nucleic acids and allowing complementary sequences to hybridize, where the nucleic acids in the first and second sets of nucleic acids represent ligation products comprising sequences from both chromosomal regions clustered in the chromosomal interaction, and the pattern of hybridization between the first and second sets of nucleic acids allows the determination of which chromosomal interactions are specific to an immunoresponsive subgroup; and -Chromosomal interactions (i) in any of the regions or genes listed in Table 1; and / or (ii) corresponds to any of the chromosomal interactions represented by any of the probes shown in Table 1; and / or (iii) containing (i) or (ii) or present in a 4,000-base region adjacent to (i) or (ii); Provide a process.

[0006] The present invention also relates to a process for detecting a chromosomal state representing a subgroup in a population, comprising determining whether a chromosomal interaction related to that chromosomal state is present or absent within a defined region of the genome, said subgroup being related to how immune responsive an individual is; and - said chromosomal interactions have optionally been identified by a method for determining which chromosomal interactions are associated with a chromosomal state corresponding to an immunoresponsive interaction subgroup of a population, the method comprising contacting a first set of nucleic acids from subgroups with different chromosomal states with a second set of index nucleic acids and allowing complementary sequences to hybridize, where the nucleic acids in the first and second sets of nucleic acids represent ligation products comprising sequences from both chromosomal regions clustered in the chromosomal interaction, and the pattern of hybridization between the first and second sets of nucleic acids allows the determination of which chromosomal interactions are specific to an immunoresponsive subgroup; and -Chromosomal interactions (a) in any of the regions or genes listed in Table 13; and / or (b) corresponds to any of the chromosomal interactions represented by any of the probes shown in Table 13; and / or (c) containing (a) or (b) or present in a 4,000-base region adjacent to (a) or (b); Provide a process.

[0007] The present invention further provides a process for detecting a chromosomal state representing a subgroup in a population, comprising determining whether a chromosomal interaction related to the chromosomal state is present or absent within a defined region of the genome, said subgroup being related to how immune responsive an individual is; and - said chromosomal interactions have optionally been identified by a method for determining which chromosomal interactions are associated with a chromosomal state corresponding to an immunoresponsive interaction subgroup of a population, the method comprising contacting a first set of nucleic acids from subgroups with different chromosomal states with a second set of index nucleic acids and allowing complementary sequences to hybridize, where the nucleic acids in the first and second sets of nucleic acids represent ligation products comprising sequences from both chromosomal regions clustered in the chromosomal interaction, and the pattern of hybridization between the first and second sets of nucleic acids allows the determination of which chromosomal interactions are specific to an immunoresponsive subgroup; and -Chromosomal interactions (α) present in any of the regions or genes listed in Table 16; and / or (β) corresponds to any of the chromosomal interactions represented by any of the probes shown in Table 16; and / or (γ) contains (α) or (β) or is present in a 4,000-base region adjacent to (α) or (β) Provide a process. [Brief description of the drawings]

[0008] [Figure 1] 1 shows examples of clinical annotations of patients included in the study. [Diagram 2] The names of the best biomarkers and the loci where they are located are given. [Diagram 3] Venn diagrams for the best predictive biomarkers from array analysis (comparing baseline for responders and non-responders) and best response biomarkers (comparing responders at baseline and 12 weeks) are shown. [Figure 4] Example of individual patient binary PCR readout for some final signature biomarkers: 1 CCs present, 0 CCs absent. [Diagram 5]Two groups of patients with lung cancer treated with anti-PD-L1 monoclonal antibodies are shown. [Figure 6] Statistical analysis of the top 13 statistically significant markers distinguishing between groups I and II is shown. [Figure 7A] Principal component analysis (PCA) of the top 13 markers selected from the PD-L1 cohort is shown. [Figure 7B] Principal component analysis (PCA) of the top 13 markers selected from the PD-L1 cohort is shown. [Figure 8] In a third separate study conducted in lung cancer patients using a different anti-PD-L1 monoclonal, we show how baseline samples from 15 patients were provided blinded with annotation of response / non-response to treatment. [Figure 9] We show how a random forest classifier built based on the five listed markers generates predictive calls for each of the 15 samples (prediction column). [Figure 10] The predicted calls for each sample compared to the open-label validation (actual column) are shown. The stratification efficiency is shown in the table. [Figure 11] The standard rOC curve for the classifier is shown. AUC=0.786 [Figure 12] We show the principal components analysis of all samples used in this analysis: 8 from the first test, 24 from the second test, and 15 from the validation. [Figure 13] Showing overlap of 2522 common reads in responders. [Figure 14] The most statistically significant - showing the examination of 276 common significant leads in both studies for responders (study I on the left, study II on the right). [Figure 15] Only 1 is shown for non-responders (Study I on the left, Study II on the right). [Figure 16] FIG. 1 shows how the loci of array reads for responding and non-responding markers (studies I and III) overlap with genes involved in the interferon gamma pathway. [Figure 17]FIG. 1 shows how the loci of array reads for responding and non-responding markers (studies I and III) overlap with genes involved in the interferon gamma pathway. Only statistically significant data are shown. [Figure 18] Figure 2 shows how the loci of array reads for responding and non-responding markers (studies I and III) overlap with genes involved in the interferon gamma pathway. Shown for all studies I-III. [Figure 19] Venn diagrams across four cohorts: gene loci (ORFs) for the INFG pathway, anti-PD-L1 responders and non-responders, and all anti-PD-1. [Figure 20] Venn diagrams across four cohorts: gene loci (ORFs) for the INFG pathway, anti-PD-1 responders and non-responders, and all anti-PD-L1. [Figure 21] All loci of responder markers shared between studies I-III and the INFG gene are shown. [Figure 22A] A list of 95 loci containing some of the significant response EpiSwitch markers shared across all three studies I-III is shown. [Figure 22B] A list of 95 loci containing some of the significant response EpiSwitch markers shared across all three studies I-III is shown. [Figure 23A] A list of loci from Figure 22 showing the number of significant marker reads and the total number of marker reads when these loci were evaluated on the array is shown. [Figure 23B] A list of loci from Figure 22 showing the number of significant marker reads and the total number of marker reads when these loci were evaluated on the array is shown. [Figure 23C] A list of loci from Figure 22 showing the number of significant marker reads and the total number of marker reads when these loci were evaluated on the array is shown. [Figure 23D]A list of loci from Figure 22 showing the number of significant marker reads and the total number of marker reads when these loci were evaluated on the array is shown. [Figure 24] 1 shows the interferon signaling pathway matching ORFs associated with significant EpiSwitch™ CCS of PDF-L1. [Diagram 25] A preferred method for detecting chromosomal interactions is presented. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] EMBODIMENTS OF THE PRESENT DISCLOSURE The present invention relates to a panel of epigenetic markers for the regulation of the immune system, in particular the regulation of the immune system by cell surface signaling pathways and T cell activation.

[0010] The present invention also includes monitoring the state of the immune system to determine its responsiveness to a particular treatment. This means that appropriate therapy can be given to the patient, and it can be determined whether the patient maintains or loses "responder" status. The present invention therefore provides, in one embodiment, a "live" ongoing readout of "responder" status, allowing the patient to be given a personalized therapy that accurately reflects the patient's needs.

[0011] Immune responsiveness The present invention relates to determining immune responsiveness. It is preferably responsiveness to a therapy involving molecules or cells related to the immune system, such as administration of a composition comprising an antibody or immune cells (e.g. T cells or dendritic cells) or administration of any therapeutic substance mentioned herein. It may also be responsiveness to a substance that modulates or stimulates the immune system, such as a vaccine therapy. The immune responsiveness is therefore preferably responsiveness to an immunotherapy. The immunotherapy may modulate, block or stimulate immune checkpoints, thus targeting or modulating PD-L1, PD-L2 or CTLA4 or any other immune checkpoint molecule disclosed herein, thus being an immune checkpoint therapy. Preferably, the immune responsiveness is responsiveness to an antibody therapy, or any specific therapy disclosed herein (see specific drugs in the following section). The therapy may be a combination therapy.

[0012] In one embodiment, immune responsiveness is responsiveness to a PD-1 or PD-L1 inhibitor, such as an antibody specific for PD-1 or PD-L1. PD-1 is the "programmed cell death protein" and PD-L1 is the "programmed death-ligand 1."

[0013] The immune responsiveness is preferably related to a cancer treatment, and thus typically to whether a particular individual responds to the treatment, where the individual may or may not have cancer, or may be at risk for cancer. The cancer is typically any cancer mentioned herein, such as melanoma, lung cancer, non-small cell lung cancer (NSCLC), diffuse large B-cell lymphoma, liver cancer, hepatocellular carcinoma, prostate cancer, breast cancer, leukemia, acute myeloid leukemia, pancreatic cancer, thyroid cancer, nasal cancer, brain tumor, bladder cancer, cervical cancer, non-Hodgkin's lymphoma, ovarian cancer, colon cancer, or kidney cancer.

[0014] The term "antibody" includes all fragments and derivatives of antibodies, such as single chain scFv or Fab, which retain the ability to bind to an antigen target.

[0015] As described below, immune responsiveness can be determined for any of the therapies, cells, or drugs referred to herein. In some embodiments, the cells or drugs referred to herein can be administered to the individual for whom immune responsiveness is being determined.

[0016] The process of the present invention The process of the present invention includes a classification system for detecting chromosomal interactions related to immune responsiveness. This classification can be performed by using the Episwitch™ system described herein, which is based on the bridging regions of chromosomes that converge to chromosomal interactions, by cutting chromosomal DNA, and then ligating the nucleic acid present in the bridging entity, and inducing ligated nucleic acid that has sequences from both regions that form chromosomal interactions. The detection of this ligated nucleic acid allows the detection of the presence or absence of a specific chromosomal interaction.

[0017] Chromosomal interactions can be identified using the methods described above, in which a first and a second population of nucleic acids are used. These nucleic acids can also be generated using Episwitch™ technology.

[0018] Epigenetic interactions relevant to the present invention As used herein, the terms "epigenetic" and "chromosomal" interactions refer to interactions typically between distal regions of loci on chromosomes, which interactions are dynamic and change, form, or break depending on the state of the chromosomal regions.

[0019] In certain processes of the invention, chromosomal interactions are detected by first generating ligated nucleic acids that contain sequences from both regions of the chromosomes that are part of the interaction. In such processes, both regions can be crosslinked by any suitable means. In a preferred embodiment, the interaction is crosslinked using formaldehyde, but may be crosslinked by any aldehyde, or D-biotinyl-e-aminocaproic acid-N-hydroxysuccinimide ester or digoxigenin-3-O-methylcarbonyl-e-aminocaproic acid-N-hydroxysuccinimide ester. Paraformaldehyde can crosslink DNA strands that are 4 angstroms apart. Preferably, the chromosomal interactions are on the same chromosome, optionally 2-10 angstroms apart.

[0020] Chromosomal interactions can reflect the state of a chromosomal region, for example, whether it is transcribed or repressed in response to changes in physiological conditions.The chromosomal interactions that are specific to the subgroups defined herein are found to be stable, and therefore provide a reliable means of measuring the difference between two subgroups.

[0021] In addition, chromosomal interactions specific to a certain feature (such as disease state) are usually believed to occur early in biological processes, compared to other epigenetic markers, such as changes to methylation or histone protein binding. Therefore, the process of the present invention can detect early stages of biological processes. This can result in earlier intervention (e.g., treatment) that can be more effective. Furthermore, there is little variation in relevant chromosomal interactions between individuals in the same subgroup. Detecting chromosomal interactions is highly beneficial, with up to 50 possible different interactions per gene, so the process of the present invention can interrogate 500,000 different interactions.

[0022] Preferred marker set As used herein, the term "marker" or "biomarker" refers to a specific chromosomal interaction that can be detected (classified) in the present invention. Specific markers are disclosed herein. Any of them, any marker can be used in the present invention. A set of additional markers may be used, for example, in the combination or number disclosed herein. The markers disclosed in the table herein are preferred. They can be classified by any suitable method, such as, for example, PCR or probe-based methods disclosed herein, such as qPCR methods. Markers are defined herein by location or by probe and / or primer sequence.

[0023] Location and causes of epigenetic interactions Epigenetic chromosomal interactions may overlap and include regions of chromosomes that are shown to code for related or undescribed genes, but may also be in intergenic regions.It should be noted further that the inventors have found that epigenetic interactions in all regions are equally important in determining the state of chromosomal loci.These interactions are not necessarily in the coding region of a particular gene located at the locus, but may be in intergenic regions.

[0024] The chromosomal interactions detected in the present invention can be caused by changes to the underlying DNA sequence, environmental factors, DNA methylation, non-coding antisense RNA transcripts, non-mutagenic carcinogens, histone modifications, chromatin reorganization, and specific local DNA interactions.Changes that lead to chromosomal interactions can be caused by changes to the underlying nucleic acid sequence that do not directly affect gene products or gene expression patterns themselves.Such changes can be, for example, SNPs inside and / or outside genes, gene fusions, and / or deletions of intergenic DNA, microRNA, and non-coding RNA.For example, it is known that approximately 20% of SNPs are in non-coding regions, and therefore the process described is also useful in non-coding situations.In one embodiment, the regions of chromosomes that form interactions together are less than 5kb, 3kb, 1kb, 500 base pairs, or 200 base pairs apart on the same chromosome.

[0025] The chromosomal interaction to be detected is preferably within any of the genes mentioned in Tables 1 or 5. However, it may also be upstream or downstream of the gene, for example up to 50,000, up to 30,000, up to 20,000, up to 10,000, or up to 5000 bases upstream or downstream from the gene or coding sequence.

[0026] The chromosomal interaction to be detected is preferably within any of the genes mentioned in Tables 1 or 5. However, it may also be upstream or downstream of the gene, for example up to 50,000, up to 30,000, up to 20,000, up to 10,000, or up to 5000 bases upstream or downstream from the gene or coding sequence.

[0027] The chromosomal interaction to be detected is preferably within any of the genes mentioned in Tables 1 or 5. However, it may also be upstream or downstream of the gene, for example up to 50,000, up to 30,000, up to 20,000, up to 10,000, or up to 5000 bases upstream or downstream from the gene or coding sequence.

[0028] Subgroups, diagnosis and individualized treatment The objective of the present invention is to determine the level of immune responsiveness. This can be at one or more defined time points, for example at least 1, 2, 5, 8 or 10 different time points. The period between the at least 1, 2, 5 or 8 time points can be at least 5, 10, 20, 50, 80 or 100 days. Typically, at least 1, 2 or 5 time points are before the start of treatment, and / or at least 1, 2 or 5 time points are after the start of treatment.

[0029] As used herein, "subgroup" preferably refers to a population subgroup (a subgroup within a population), more preferably a subgroup within a population of a particular eukaryotic cell or a particular animal, such as a mammal (e.g., a human, a non-human, a non-human primate, or a rodent, such as a mouse or rat). Most preferably, "subgroup" refers to a subgroup within a human population.

[0030] The present invention includes detecting and treating specific subgroups in a population.The inventors have discovered that chromosome interactions are different between subsets (e.g., at least two subsets) in a given population.By identifying these differences, physicians can classify their patients as part of one subset of the population described in the process.Therefore, the present invention provides physicians with a process of individualizing drug therapy for patients based on epigenetic chromosome interactions.

[0031] In one embodiment, the present invention relates to testing whether an individual is a "responder". Once a person is found to be a "responder", a related therapy may be administered, which is a therapy that targets immune checkpoint molecules such as PD-1, PD-L1 or CTLA4. In one embodiment, if an individual is found to be a non-responder, then the individual may be administered a combination therapy, such as any combination therapy listed herein. Typically, the combination therapy includes an antibody and a small molecule.

[0032] Generate ligated nucleic acids Certain aspects of the invention utilize ligated nucleic acids, particularly ligated DNA, which contain sequences from both regions that converge in a chromosomal interaction and therefore provide information about the interaction. The EpiSwitch™ method described herein uses the generation of such ligated nucleic acids to detect chromosomal interactions.

[0033] Thus, the process of the present invention comprises the steps (including methods comprising these steps): (i) cross-linking epigenetic chromosomal interactions present at chromosomal loci, preferably in vitro; (ii) optionally, isolating the crosslinked DNA from the chromosomal locus; (iii) cleaving the crosslinked DNA, e.g., by restriction digestion with an enzyme that cuts it at least once (particularly an enzyme that cuts at least once within the chromosomal locus); (iv) ligating the cross-linked cleaved DNA ends (particularly to form a DNA loop); and (v) optionally identifying the presence of ligated DNA and / or DNA loops, in particular using techniques such as PCR (polymerase chain reaction), to identify the presence of specific chromosomal interactions; The method includes producing a ligated nucleic acid (e.g., DNA) by

[0034] These steps may be performed to detect chromosomal interactions for any of the embodiments described herein. The steps may also be performed to generate the first and / or second sets of nucleic acids described herein.

[0035] PCR (polymerase chain reaction) can be used to detect or identify the ligated nucleic acid, for example the size of the PCR product produced can indicate that a specific chromosomal interaction exists and can therefore be used to identify the state of the locus. In a preferred embodiment, at least one, two or three primers or primer pairs shown in Table 4 are used in the PCR reaction. In another embodiment, at least one, two or three primers or primer pairs shown in Table 13 are used in the PCR reaction. In another embodiment, at least one, two or three primers or primer pairs shown in Table 17 are used in the PCR reaction. Those skilled in the art will be aware of the myriad of restriction enzymes that can be used to cut DNA within a chromosomal locus of interest. It will be clear that the particular enzyme used will depend on the locus being investigated and the sequence of the DNA located therein. A non-limiting example of a restriction enzyme that can be used to cut DNA as described in the present invention is TaqI.

[0036] EpiSwitch™ Technology and Other Embodiments EpiSwitch™ technology relates to the use of microarray EpiSwitch™ marker data in the detection of phenotype-specific epigenetic chromosomal conformation signatures. EpiSwitch™ and other embodiments utilizing ligated nucleic acids in the manner described herein have several advantages. For example, nucleic acid sequences from a first set of nucleic acids of the invention either hybridize or do not hybridize with a second set of nucleic acids, so that their stochastic noise is at a low level. This provides a binary result that allows a relatively simple way of measuring complex mechanisms at the epigenetic level. EpiSwitch™ technology also has a fast processing time and low cost. In one embodiment, the processing time is 3-6 hours.

[0037] Samples and sample treatment The process of the present invention will usually be carried out on a sample. The sample will usually contain DNA from an individual. It will usually contain cells. In one embodiment, the sample is obtained by minimally invasive means, and can be, for example, a blood sample. DNA can be extracted and cut with standard restriction enzymes. This can predetermine which chromosome conformations are retained and detected with the EpiSwitch™ platform. Due to the synchronization of chromosome interactions between tissues and blood, including horizontal transfer, blood samples can be used to detect chromosome interactions in tissues, such as tissues associated with disease. For certain disease conditions, such as cancer, genetic noise due to mutations can affect chromosome interaction "signals" in associated tissues, and therefore using blood is advantageous.

[0038] Properties of the Nucleic Acids of the Invention The invention relates to certain nucleic acids, such as ligated nucleic acids, described herein as being used or produced in the process of the invention. These may be the same as the first and second nucleic acids described herein, or may have any of the properties of the first and second nucleic acids. The nucleic acids of the invention typically comprise two portions, each of which comprises a sequence from one of the two regions of a chromosome that converge in a chromosomal interaction. Typically, each portion is at least 8, 10, 15, 20, 30, or 40 nucleotides in length, for example 10-40 nucleotides in length. Preferred nucleic acids include sequences from any of the genes, particularly those in which the nucleic acid is described in any of the tables. Typically, preferred nucleic acids include the specific probe sequences described in Table 1, or fragments and / or homologues of such sequences. Other preferred nucleic acids include the specific probe sequences described in Table 13, or fragments and / or homologues of such sequences. Other preferred nucleic acids include the specific probe sequences described in Table 16, or fragments and / or homologues of such sequences.

[0039] Preferably, the nucleic acid is DNA. When a specific sequence is provided, it is understood that the present invention may use a complementary sequence as required in a particular embodiment. Preferably, the nucleic acid is DNA. When a specific sequence is provided, it is understood that the present invention may use a complementary sequence as required in a particular embodiment.

[0040] Primers shown in Table 4 may also be used in the present invention as described herein. In one embodiment, primers are used that contain either a sequence shown in Table 4; or a fragment and / or homolog of any sequence shown in Table 4. Primers shown in Table 13 may also be used in the present invention as described herein. In one embodiment, primers are used that contain either a sequence shown in Table 13; or a fragment and / or homolog of any sequence shown in Table 13. Primers shown in Table 17 may also be used in the present invention as described herein. In one embodiment, primers are used that contain either a sequence shown in Table 17; or a fragment and / or homolog of any sequence shown in Table 17.

[0041] The second set of nucleic acids - "index" sequences The second set of nucleic acids has the function of being a set of index sequences and is essentially a set of nucleic acid sequences suitable for identifying subgroup-specific sequences. They can represent "background" chromosomal interactions and may or may not be selected in some way. They are generally a subset of all possible chromosomal interactions.

[0042] The second set of nucleic acids may be derived by any suitable method. They may be computationally derived or they may be based on chromosomal interactions in an individual. They typically represent a larger population group than the first set of nucleic acids. In one particular embodiment, the second set of nucleic acids represents all possible epigenetic chromosomal interactions in a particular set of genes. In another particular embodiment, the second set of nucleic acids represents a majority of all possible epigenetic chromosomal interactions present in the population described herein. In one particular embodiment, the second set of nucleic acids represents at least 50% or at least 80% of the epigenetic chromosomal interactions in at least 20, 50, 100 or 500 genes, for example, 20-100, or 50-500 genes.

[0043] The second set of nucleic acids typically represents at least 100 possible epigenetic chromosomal interactions that modify, regulate, or in some way mediate disease states / phenotypes in a population. The second set of nucleic acids may represent chromosomal interactions that affect disease states (typically related to diagnosis or prognosis) in a species. The second set of nucleic acids typically includes sequences that represent epigenetic interactions that are both associated and unassociated with immune responsiveness subgroups.

[0044] In one particular embodiment, the second set of nucleic acids is at least partially derived from naturally occurring sequences in the population, and typically obtained by in silico methods. The nucleic acids may further comprise single or multiple mutations compared to the corresponding portion of the nucleic acid present in the naturally occurring nucleic acid. Mutations include deletion, substitution, and / or addition of one or more nucleotide base pairs. In one particular embodiment, the second set of nucleic acids may comprise sequences that represent homologs and / or orthologs with at least 70% sequence identity with the corresponding portion of the nucleic acid present in the naturally occurring species. In another particular embodiment, at least 80% sequence identity or at least 90% sequence identity with the corresponding portion of the nucleic acid present in the naturally occurring species is provided.

[0045] Properties of the second set of nucleic acids In one particular embodiment, there are at least 100 different nucleic acid sequences in the second set of nucleic acids, preferably at least 1000, 2000, or 5000 different nucleic acid sequences, and up to 100,000, 1,000,000, or 10,000,000 different nucleic acid sequences. A typical number would be 100-1,000,000, such as 1,000-100,000 different nucleic acid sequences. All of these or at least 90% or at least 50% would represent different chromosomal interactions.

[0046] In one particular embodiment, the second set of nucleic acids represents chromosomal interactions at at least 20 different loci or genes, preferably at least 40 different loci or genes, and more preferably at least 100, at least 500, at least 1000, or at least 5000 different loci or genes, such as 100 to 10,000 different loci or genes. The length of the second set of nucleic acids is suitable for them to specifically hybridize to the first set of nucleic acids according to Watson-Crick base pairing and allow identification of subgroup-specific chromosomal interactions. Typically, the second set of nucleic acids will include two portions whose sequences correspond to two chromosomal regions that converge in a chromosomal interaction. The second set of nucleic acids typically includes nucleic acid sequences that are at least 10, preferably 20, and more preferably 30 bases (nucleotides) in length. In another embodiment, the nucleic acid sequences can be at most 500, preferably at most 100, and more preferably at most 50 base pairs in length. In a preferred embodiment, the second set of nucleic acids comprises nucleic acid sequences of between 17 and 25 base pairs. In one embodiment, at least 100, 80%, or 50% of the second set of nucleic acid sequences have a length as described above. Preferably, the different nucleic acids do not have any overlapping sequences, e.g., at least 100%, 90%, 80%, or 50% of the nucleic acids do not have the same sequence over at least 5 consecutive nucleotides.

[0047] The same set of second nucleic acids may be used with different sets of first nucleic acids representing different features of a subgroup, with the second set of nucleic acids acting as an "index," i.e., the second set of nucleic acids may represent a "universal" collection of nucleic acids that can be used to identify chromosomal interactions associated with the different features.

[0048] A first set of nucleic acids The first set of nucleic acids is usually from a subgroup associated with immune responsiveness. The first nucleic acid may have any of the characteristics and properties of the second set of nucleic acids mentioned herein. The first set of nucleic acids is usually from a sample from an individual that has undergone the treatment and processing described herein, particularly the cross-linking and cleavage steps of EpiSwitch™. Typically, the first set of nucleic acids represents all or at least 80% or 50% of the chromosomal interactions present in the sample taken from the individual.

[0049] Typically, the first set of nucleic acids represents a smaller population of chromosomal interactions across the loci or genes represented by the second set of nucleic acids compared to the chromosomal interactions represented by the second set of nucleic acids, i.e., the second set of nucleic acids represents a background or index set of interactions at a defined set of loci or genes.

[0050] Nucleic acid library Any of the types of nucleic acid populations referred to herein may be present in the form of a library comprising at least 200, at least 500, at least 1000, at least 5000, or at least 10,000 different nucleic acids of that type, such as a "first" or "second" nucleic acid. Such libraries may be in the form of bound arrays.

[0051] Hybridization The present invention requires a means for allowing fully or partially complementary nucleic acid sequences from a first set of nucleic acids and a second set of nucleic acids to hybridize. In one embodiment, all of the first set of nucleic acids and all of the second set of nucleic acids are contacted in a single assay, i.e., in a single hybridization step. However, any suitable assay can be used.

[0052] Labeled Nucleic Acids and Hybridization Patterns The nucleic acid referred to herein can be preferably labeled with an independent label, such as a fluorophore (fluorescent molecule) or a radioactive label, which can assist in the detection of hybridization that can be achieved.Certain labels can be detected under UV light.For example, the hybridization pattern on the array described herein represents the difference in epigenetic chromosome interactions between two subgroups, thus providing a process of epigenetic chromosome comparison and determining which epigenetic chromosome interactions are specific to the subgroup of the population of the present invention.

[0053] The term "pattern of hybridization" broadly covers the presence or absence of hybridization between a first set and a second set of nucleic acids, i.e., which particular nucleic acids from the first set hybridize to which particular nucleic acids from the second set, and is not limited to any particular assay or technique, but requires a surface or array capable of detecting the "pattern."

[0054] Select subgroups with special characteristics The present invention provides a process comprising detecting the presence or absence of chromosomal interactions, typically 5-20 or 5-500 such interactions, preferably 20-300 or 50-100 interactions, to determine the presence or absence of a trait associated with immune responsiveness in an individual. Preferably, the chromosomal interactions are in any of the genes mentioned herein. In one embodiment, the chromosomal interactions classified are those represented by the nucleic acids in Table 1. In another embodiment, the chromosomal interactions are those represented in Table 13. In another embodiment, the chromosomal interactions are those represented in Table 16. In the table, the column entitled "Loops Detected" indicates which subgroup is detected by each probe (i.e., responders or non-responders).

[0055] Individuals being tested Examples of species from which the individual to be tested are mentioned herein.In addition, the individual to be tested in the process of the present invention may be selected in several ways.The individual may be susceptible to any of the conditions mentioned herein and / or may require any of the treatments mentioned herein.The individual may receive any of the treatments mentioned herein.

[0056] In one embodiment, the individuals being tested show no response to therapy and the purpose of their testing is to discover whether they are "pseudo-progressors" who do not respond at an earlier stage but respond to therapy at a second stage of the disease.

[0057] Favorable gene regions, loci, genes, and chromosomal interactions For all embodiments of the present invention, preferred gene regions, loci, genes, and chromosomal interactions are referred to in tables, e.g., Table 1. Typically, in the process of the present invention, chromosomal interactions are detected from at least 1, 2, 10, 50, 100, 150, 200, or 300 relevant genes listed in Table 1. Preferably, the presence or absence of at least 1, 2, 10, 50, 100, 150, 200, or 300 relevant specific chromosomal interactions represented by the probe sequences in Table 1 are detected. The chromosomal interactions may be upstream or downstream of any of the genes referred to herein, e.g., 50 kb upstream or 20 kb downstream from the coding sequence.

[0058] In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 1a are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 1b are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 1c are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 1d are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 1e are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 1f are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 1g are classified.

[0059] Typically, at least 5, 10, 15, 20, 30, 40 or 70 chromosomal interactions are classified from any of the genes or regions disclosed in the tables or portions of the tables disclosed herein. Typically, the classified chromosomal interactions are present in at least 20, 50, 100, 200, 300 or all of the genes referred to in Table 2. Typically, the classified chromosomal interactions are present in at least 10, 20, 50, 70 or all of the genes referred to in Table 3.

[0060] For all embodiments of the present invention, preferred gene regions, loci, genes and chromosomal interactions are referred to in Table 13. Typically, in the process of the present invention, chromosomal interactions are detected from at least 1, 2, 10, 50, 100, 150, 200 or 300 related genes listed in Table 13. Preferably, the presence or absence of at least 1, 2, 10, 50, 100, 150, 200 or 300 related specific chromosomal interactions represented by the probe sequences in Table 13 are detected. The chromosomal interactions may be upstream or downstream of any of the genes referred to herein, for example, 50 kb upstream or 20 kb downstream from the coding sequence.

[0061] In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 13a are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 13b are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 13c are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 13d are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 13e are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 13f are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 13g are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 13h are classified. In one embodiment, at least 5, 10, 15, 20 or all of the chromosomal interactions of table 13i are classified.

[0062] Typically, at least 5, 10, 15, 20, 30, 40 or 70 chromosomal interactions are classified from any of the genes or regions disclosed in the tables or portions of the tables disclosed herein. Typically, the classified chromosomal interactions are present in at least 20, 50, 100, 200, 300 or all of the genes referred to in Table 13. Typically, the classified chromosomal interactions are present in at least 10, 20, 50, 70 or all of the genes referred to in Table 13.

[0063] For all embodiments of the present invention, preferred gene regions, loci, genes, and chromosomal interactions are referred to in Table 16. Typically, in the process of the present invention, chromosomal interactions are detected from at least 1, 2, 10, 20, 30, or 40 relevant genes listed in Table 16. Preferably, the presence or absence of at least 1, 2, 10, 20, 30, or 40 relevant specific chromosomal interactions represented by the probe sequences in Table 16 are detected. The chromosomal interactions may be upstream or downstream of any of the genes referred to herein, for example, 50 kb upstream or 20 kb downstream from the coding sequence.

[0064] In one embodiment, at least 5, 10 or 15 or all of the chromosomal interactions in Table 18 are classified.

[0065] Typically, at least 5, 10, 15, 20, 30, 40 or 70 chromosomal interactions are classified from any of the genes or regions disclosed in the tables or portions of the tables disclosed herein. Typically, the classified chromosomal interactions are present in at least 20, 50, 100, 200, 300 or all of the genes referred to in Table 13. Typically, the classified chromosomal interactions are present in at least 10, 20, 50, 70 or all of the genes referred to in Table 13.

[0066] In one embodiment, at least 5, 10, 20, 30, 40 or 70 different chromosomal interactions are classified from those defined in any of Tables 1, 13 and 16. In another embodiment, at least 50%, 80% or all of the chromosomal interactions classified are from Tables 1, 13 and 16.

[0067] In one embodiment, the locus (including the gene and / or location where the chromosomal interaction is detected) may contain a CTCF binding site. This is any sequence that can bind to the transcriptional repressor CTCF. The sequence may consist of or include a CCCTC sequence, which may be present in one, two or three copies at the locus. The CTCF binding site sequence may include the CCGCGNGGNGGCAG sequence (in IUPAC notation). The CTCF binding site may be within at least 100, 500, 1000 or 4000 bases of the chromosomal interaction or within any of the chromosomal regions shown in Table 1. The CTCF binding site may be within at least 100, 500, 1000 or 4000 bases of the chromosomal interaction or within any of the chromosomal regions shown in Table 13.

[0068] In one embodiment, the chromosomal interaction detected is in any of the genetic regions shown in Table 13. If ligated nucleic acid is detected in the process, then the sequence shown in any of the probe sequences in Table 13 can be detected.

[0069] Thus, typically sequences from both regions of the probe (i.e., from both sites of chromosomal interaction) can be detected. In preferred embodiments, a probe that contains or consists of the same or complementary sequence as any of the probes shown in the tables is used in the process. In some embodiments, a probe that contains a sequence that is homologous to any of the probe sequences shown in the tables is used.

[0070] Tables provided herein Table 1 shows probe (Episwitch™ marker) data and gene data representing chromosomal interactions associated with immune responsiveness. The probe sequences represent sequences that can be used to detect ligation products produced from both sites of the gene region that converges to the chromosomal interaction. That is, the probes contain sequences that are complementary to the sequences of the ligation products. The first two sets of Start-End locations represent the probe locations and the second two sets of Start-End locations represent the relevant 4kb region. The following information is provided in the table of probe data: - HyperG_States: p-value for the probability of finding that number of significant Episwitch™ markers at a locus based on the parameters of hypergeometric enrichment - Probe_Count Total: The total number of Episwitch™ conformations tested at that locus - Probe_CountSig: the number of Episwitch™ conformations found to be statistically significant at that locus -FDR HyperG: Hypergeometric p-value corrected for multiple testing (false discovery rate) -Sig Proportion: Proportion of significant Episwitch™ markers relative to the number of markers tested at that locus -logFC: logarithm base 2 of epigenetic ratio (FC) -AveExpr: average log2-expression for the probes across all arrays and channels -T: Moderated t-statistics -p-value: Unadjusted p-value -adj.p.Val: adjusted p-value or q-value -B: The B-statistic (lod or B) is the log odds that the gene is differentially expressed. -FC: Non-log Fold Change -FC_1: Non-logarithmic fold change around zero - LS: The binary value relates to the FC_1 value. FC_1 values ​​less than 1.1 are set to -1, FC_1 values ​​greater than 1.1 are set to 1. Between these values ​​the value is 0.

[0071] Table 1 shows the locus table showing genes where relevant chromosomal interactions have been found to occur. The p-values ​​are the same as HyperG_Stats (p-values ​​for the probability of finding that number of significant Episwitch™ markers at the locus based on the parameters of hypergeometric enrichment). The LS column shows the presence or absence of interactions associated with that particular responder status.

[0072] The probe is designed to be 30 bp away from the Taq1 site. In the case of PCR, PCR primers are also designed to detect the ligation product, but at different positions from Taq1.

[0073] Probe Position: Start1 - 30 bases upstream of TaqI on fragment 1 End1 - TaqI restriction site on fragment 1 TaqI restriction site on Sart2-fragment 2 End2 - 30 bases downstream of TaqI on fragment 2

[0074] 4kb sequence location: Start1 - 4000 bases upstream of TaqI on fragment 1 End1 - TaqI restriction site on fragment 1 TaqI restriction site on Sart2-fragment 2 End2 - 4000 bases downstream of TaqI on fragment 2

[0075] GLMNET values ​​associated with the procedure for fitting the full lasso or elastic-net regularization (λ(elastic-net) set to 0.5).

[0076] Tables 1 and 4 relate to immune responsiveness. Table 2 shows the overlap between the two tests performed, and Table 3 shows the overlap with markers related to interferon gamma. The invention can be practiced with the markers disclosed / represented in either table. The other tables, including Tables 13 and 1, can be interpreted in the same manner as shown in Table 1 above.

[0077] Preferred embodiments for sample preparation and chromosomal interaction detection Methods for preparing samples and detecting chromosome conformation are described herein. Optimized (non-conventional) versions of these methods can be used, for example as described in this section.

[0078] Typically, samples are at least 2 × 10 5 Samples will contain up to 5 x 10 cells. 5 In one embodiment, the sample may contain 2×10 cells. 5 ~5.5×10 5 The cell population will contain 100 cells.

[0079] The cross-linking of epigenetic chromosomal interactions present at chromosomal loci is described herein. This can be performed before cell lysis occurs. Cell lysis can be performed for 3-7 minutes, such as 4-6 or about 5 minutes. In some embodiments, cell lysis is performed for at least 5 minutes and less than 10 minutes.

[0080] Digesting DNA with a restriction enzyme is described herein. Typically, DNA restriction is carried out at about 55° C. to about 70° C., such as about 65° C., for a period of about 10 to 30 minutes, such as about 20 minutes.

[0081] Preferably, a frequent-cutter restriction enzyme is used that results in fragments of the ligated DNA having an average fragment size of up to 4000 base pairs. Optionally, the restriction enzyme results in fragments of the ligated DNA having an average fragment size of about 200-300 base pairs, such as about 256 base pairs. In one embodiment, typical fragment sizes are 200 base pairs to 4,000 base pairs, such as 400-2,000 or 500-1,000 base pairs.

[0082] In one embodiment of the EpiSwitch Method, a DNA precipitation step is not performed between the DNA restriction digestion step and the DNA ligation step.

[0083] DNA ligation is described herein. Typically, DNA ligation is carried out for 5 to 30 minutes, such as about 10 minutes.

[0084] Proteins in the sample may be enzymatically digested, for example with a proteinase, optionally proteinase K. Proteins may be enzymatically digested for a period of about 30 minutes to 1 hour, for example about 45 minutes. In one embodiment, digestion of the proteins, for example proteinase K digestion, is not followed by a step of crosslink reversal or phenol DNA extraction.

[0085] In one embodiment, PCR detection preferably provides a binary readout for the presence / absence of the ligated nucleic acid and is capable of detecting single copies of the ligated nucleic acid.

[0086] FIG. 25 shows a preferred method for detecting chromosomal interactions.

[0087] Processes and uses of the present invention The process of the present invention can be described in various ways: it is a method of making a ligated nucleic acid comprising the steps of (i) in vitro cross-linking chromosomal regions that converge at a chromosomal interaction; (ii) excising the cross-linked DNA or subjecting it to restriction digestion cleavage; and (iii) ligating the cross-linked and cleaved DNA ends to form a ligated nucleic acid, detection of which can be used to determine the chromosomal status at a locus, and preferably The locus may be any of the loci, regions or genes mentioned in Table 1, and / or - the chromosomal interaction may be any chromosomal interaction corresponding to any of the probes mentioned herein or disclosed in Table 1, and / or - the ligation product may have or contain (i) a sequence that is the same as or homologous to any of the probe sequences disclosed in Table 1; or (ii) a sequence that is complementary to (ii). It can be described as a method.

[0088] The process of the present invention is a method for detecting chromosomal states representing different subgroups within a population, comprising the steps of determining whether chromosomal interactions are present or absent within defined epigenetically active regions of the genome, preferably comprising: Subgroups are defined by the presence or absence of immune responsiveness and / or - the chromosomal status may be at any locus, region, or gene mentioned in Table 1; and / or - The chromosomal interaction can be any of those mentioned in Table 1 or any of those corresponding to any of the probes disclosed in that table. It can be described as a method.

[0089] The process of the invention is a method of making a ligated nucleic acid comprising the steps of: (i) in vitro cross-linking chromosomal regions that converge at a chromosomal interaction; (ii) excising the cross-linked DNA or subjecting it to restriction digestion cleavage; and (iii) ligating the cross-linked and cleaved DNA ends to form a ligated nucleic acid, wherein detection of the ligated nucleic acid can be used to determine the chromosomal status at a locus, and preferably - the locus may be any of the loci, regions, or genes mentioned in Table 13; and / or the chromosomal interaction may be any chromosomal interaction referred to herein or corresponding to any of the probes disclosed in Table 13; and / or - the ligation product may have or contain (i) a sequence that is the same as or homologous to any of the probe sequences disclosed in Table 13; or (ii) a sequence that is complementary to (ii). It can be described as a method.

[0090] The process of the present invention is a method for detecting chromosomal states representing different subgroups within a population, comprising the steps of determining whether chromosomal interactions are present or absent within defined epigenetically active regions of the genome, preferably comprising: Subgroups are defined by the presence or absence of immune responsiveness and / or - the chromosomal status may be at any locus, region, or gene mentioned in Table 13; and / or - the chromosomal interaction can be any of those mentioned in Table 13 or any of those corresponding to any of the probes disclosed in that table It can be described as a method.

[0091] The process of the invention is a method of making a ligated nucleic acid comprising the steps of: (i) in vitro cross-linking chromosomal regions that converge at a chromosomal interaction; (ii) excising the cross-linked DNA or subjecting it to restriction digestion cleavage; and (iii) ligating the cross-linked and cleaved DNA ends to form a ligated nucleic acid, wherein detection of the ligated nucleic acid can be used to determine the chromosomal status at a locus, and preferably - the locus may be any of the loci, regions, or genes mentioned in Table 16; and / or the chromosomal interaction may be any chromosomal interaction referred to herein or corresponding to any of the probes disclosed in Table 16; and / or - the ligation product may have or contain (i) a sequence that is the same as or homologous to any of the probe sequences disclosed in Table 16; or (ii) a sequence that is complementary to (ii). It can be described as a method.

[0092] The process of the present invention is a method for detecting chromosomal states representing different subgroups within a population, comprising the steps of determining whether chromosomal interactions are present or absent within defined epigenetically active regions of the genome, preferably comprising: Subgroups are defined by the presence or absence of immune responsiveness and / or - the chromosomal status may be at any locus, region, or gene mentioned in Table 16; and / or - The chromosomal interaction can be any of those mentioned in Table 16 or any of those corresponding to any of the probes disclosed in that table. It can be described as a method.

[0093] The invention includes the detection of chromosomal interactions at any locus, gene or region mentioned in Table 1. The invention includes the use of the nucleic acids and probes described herein to detect chromosomal interactions, for example, the use of at least 1, 5, 10, 50, 100, 200, 250, 300 such nucleic acids or probes to detect chromosomal interactions at at least 1, 5, 10, 50, 100, 200, 250, 300 different loci or genes. The invention includes the detection of chromosomal interactions using any of the primers or primer pairs listed in Table 4, or using variants of these primers (sequences comprising the primer sequences or comprising fragments and / or homologs of the primer sequences) described herein.

[0094] The invention includes the detection of chromosomal interactions at any locus, gene or region mentioned in Table 13. The invention includes the use of the nucleic acids and probes described herein to detect chromosomal interactions, for example, the use of at least 1, 5, 10, 50, 100, 200, 250, 300 such nucleic acids or probes to detect chromosomal interactions at at least 1, 5, 10, 50, 100, 200, 250, 300 different loci or genes. The invention includes the detection of chromosomal interactions using any of the primers or primer pairs listed in Table 13, or using variants of these primers (sequences comprising the primer sequences or comprising fragments and / or homologs of the primer sequences) described herein.

[0095] The invention includes the detection of chromosomal interactions at any locus, gene or region mentioned in Table 16. The invention includes the use of the nucleic acids and probes described herein to detect chromosomal interactions, for example, the use of at least 1, 5, 10, 50, 100, 200, 250, 300 such nucleic acids or probes to detect chromosomal interactions at at least 1, 5, 10, 50, 100, 200, 250, 300 different loci or genes. The invention includes the detection of chromosomal interactions using any of the primers or primer pairs listed in Table 17, or using variants of these primers (sequences comprising the primer sequences or comprising fragments and / or homologs of the primer sequences) described herein.

[0096] When analyzing whether a chromosomal interaction occurs "within" a defined gene, region, or location, both parts of the chromosomes that come together in the interaction are within the defined gene, region, or location, or in some embodiments only a portion of the chromosomes is within the defined gene, region, or location.

[0097] Use of the methods of the invention to identify new treatments Knowledge of chromosomal interactions can be used to identify new treatments for disease states. The present invention provides methods and uses of the chromosomes defined herein to identify or design new therapeutic agents for immunotherapy.

[0098] Homolog Homologs of polynucleotide / nucleic acid (e.g., DNA) sequences are referred to herein.Such homologs typically have at least 70% homology, preferably at least 80%, at least 85%, at least 90%, at least 95%, at least 97%, at least 98%, or at least 99% homology, for example, over a region of at least 10, 15, 20, 30, 100 or more consecutive nucleotides, or over a portion of nucleic acid that is derived from a region of chromosome involved in chromosomal interaction.Homology can be calculated based on nucleotide identity (sometimes referred to as "hard homology").

[0099] Thus, in certain embodiments, homologs of polynucleotide / nucleic acid (e.g., DNA) sequences are referred to herein with reference to percent sequence identity.Typically, such homologs have at least 70% sequence identity, preferably at least 80%, at least 85%, at least 90%, at least 95%, at least 97%, at least 98%, or at least 99% sequence identity, for example, over a region of at least 10, 15, 20, 30, 100 or more consecutive nucleotides, or over a portion of the nucleic acid that is derived from a region of a chromosome involved in chromosomal interactions.

[0100] For example, the UWGCG package provides the BESTFIT program (e.g., used with its default settings) that can be used to calculate homology and / or sequence identity percentage (Devereux et al (1984) Nucleic Acids Research 12, p387-395). The PILEUP and BLAST algorithms can be used to calculate homology and / or sequence identity percentage and / or align sequences (e.g., to identify equivalent or corresponding sequences (typically with their default settings)), as described, for example, in Altschul SF (1993) J Mol Evol 36:290-300; Altschul, S, F et al (1990) J Mol Biol 215:403-10.

[0101] Software for performing BLAST analysis is publicly available through the National Center for Biotechnology Information. The algorithm involves first identifying high-scoring sequence pairs (HSPs) by identifying short words of length W in the query sequence that match when aligned with words of the same length in the database sequence or meet a threshold score T with a certain positive value. T is referred to as the neighborhood word score threshold (Altschul et al, supra). These initial neighborhood word hits act as seeds to initiate searches to find HSPs that contain them. The word hits are extended in both directions along each sequence as far as the cumulative alignment score can be increased. The extension of the word hits in each direction is stopped when the cumulative alignment score falls by an amount X from the value at which it reached its maximum; the accumulation of one or more negatively scoring residue alignments causes the cumulative score to go to zero or below; or when the end of either sequence is reached. The BLAST algorithm parameters W5 T and X determine the sensitivity and speed of the alignment. The BLAST program uses as defaults a wordlength (W) of 11, a BLOSUM62 scoring matrix (see Henikoff and Henikoff (1992) Proc. Natl. Acad. Sci. USA 89:10915-10919) of 50, alignment (B) of 10, expectation (E) of 10, M=5, N=4, and a comparison of both strands.

[0102] BLAST algorithm performs statistical analysis of the similarity between two sequences; see, for example, Karlin and Altschul (1993) Proc. Natl. Acad. Sci. USA 90:5873-5787. One measure of similarity provided by BLAST algorithm is the minimum sum probability (P(N)), which provides an indication of the probability that a match between two polynucleotide sequences would occur by chance. For example, a sequence is considered to be similar to another sequence if the minimum sum probability of comparing a first sequence with a second sequence is less than about 1, preferably less than about 0.1, more preferably less than about 0.01, and most preferably less than about 0.001.

[0103] Homologous sequences typically differ by 1, 2, 3, 4 or more bases (which may be nucleotide substitutions, deletions, or insertions), such as less than 10, 15, or 20 bases. These changes may be measured over any of the regions mentioned above for calculating % homology and / or sequence identity.

[0104] The homology of a "primer pair" can, for example, be calculated by considering the two sequences as a single sequence (as if the two sequences were concatenated) and then compared to another primer pair, again considered as a single sequence.

[0105] array A second set of nucleic acids can be bound to the array, and in one embodiment, there are at least 15,000, 45,000, 100,000, or 250,000 different second nucleic acids bound to the array, preferably corresponding to at least 300, 900, 2000, or 5000 loci. In one embodiment, one, or a plurality, or all of the different populations of second nucleic acids are bound to more than one individual region of the array, effectively being repeated in the array, allowing for error detection. The array is based on the Agilent SurePrint G3 Custom CGH microarray platform. Detection of the binding of the first nucleic acid to the array can be performed by a two-color system.

[0106] Therapeutic Agents (for which responsiveness is determined or selected based on testing according to the present invention) Therapeutic agents are referred to herein. The invention provides such agents for use in preventing or treating a disease condition in an individual, such as an individual identified by the process of the invention. This may include administering a therapeutically effective amount of the agent to an individual in need thereof. The invention provides the use of the agent in the manufacture of a medicament for preventing or treating a condition in an individual.

[0107] The formulation of the drug will depend on the nature of the drug.The drug is provided in the form of a pharmaceutical composition containing the drug and a pharmaceutically acceptable carrier or diluent.Suitable carriers and diluents include isotonic saline solutions, such as phosphate buffered saline.Typical oral dosage compositions include tablets, capsules, liquid solutions, and liquid suspensions.The drug can be formulated for parenteral, intravenous, intramuscular, subcutaneous, transdermal, or oral administration.

[0108] The dosage of the drug can be determined according to various parameters, among them the substance used; the age, weight, and medical condition of the individual to be treated; the route of administration; and the required regimen. A physician can determine the required route of administration and dosage for any particular drug. However, a suitable dosage can be, for example, 0.1 to 100 mg / kg body weight (such as 1 to 40 mg / kg body weight), to be taken 1 to 3 times a day.

[0109] In one embodiment, the invention involves detecting responsiveness to a therapeutic agent, such as any of the therapeutic agents mentioned herein, which may be before starting treatment and / or during the course of treatment.

[0110] The therapy may be alone or in combination, for example, a combination therapy with immune checkpoint modulators (inhibitors) of PD-1 and / or its ligand PD-L1. The therapy may be a combination of anti-PD-1 or anti-PD-L1 combined with another drug that targets the checkpoint, such as CTLA4 (ipilimumab / Yervoy) or a small molecule. The PD-1 inhibitor may be pembrolizumab (Keytruda) or nivolumab (Opdivo). The PD-L1 modulator or therapeutic agent can be atezolizumab (Tecentriq), avelumab (Bavencio), durvalumab (Imfinzi), CA-170, ipilimumab, tremelimumab, nivolumab, pembrolizumab, pidilizumab, BMS935559, GVAXMPDL3280A, MEDI4736, MSB0010718C, MDX-1105 / BMS-936559, AMP-224, MEDI0680.

[0111] Treatments may include agents that target and / or modulate interferon gamma or the JAK-START pathway.

[0112] The therapeutic agent may be any such agent disclosed in any table herein (e.g., Tables 9, 10, or 11), or may target any "target" disclosed herein, including any protein disclosed herein in any table, including Tables 1, 13, or 16. It is understood that any agent disclosed in a combination should also be considered to be disclosed for individual administration.

[0113] Forms of matter referred to herein Any of the substances, such as nucleic acids or therapeutic agents, referred to herein may be in purified or isolated form. They may be in a form different from that found in nature, e.g., they may be present in combination with other substances with which they do not occur in nature. Nucleic acids (including portions of the sequences defined herein) may have sequences different from those found in nature, e.g., at least one, two, three, four, or more nucleotide changes in the sequences described in the section on homology. Nucleic acids may have heterologous sequences at the 5' or 3' ends. Nucleic acids may be chemically different from those found in nature, e.g., they may be modified in some way, but preferably still capable of Watson-Crick base pairing. Where appropriate, the nucleic acids are provided in double-stranded or single-stranded form. The invention provides all of the specific nucleic acid sequences referred to herein in single-stranded or double-stranded form, and thus includes the complementary strand to any sequence disclosed.

[0114] The present invention also provides a kit for carrying out any method of the present invention, including the detection of chromosomal interactions associated with specific subgroups.Such a kit can include a specific binding agent that can detect relevant chromosomal interactions, such as an agent that can detect the ligated nucleic acid produced by the method of the present invention.Preferred agents present in the kit include a probe that can hybridize to the ligated nucleic acid or a primer pair that can amplify the ligated nucleic acid in a PCR reaction, for example, as described herein.

[0115] The present invention also provides a device capable of detecting relevant chromosomal interactions. The device preferably comprises any specific binding agent, probe, or primer pair capable of detecting chromosomal interactions, such as any such agent, probe, or primer pair described herein.

[0116] Detection Method In one embodiment, the quantitative detection of the ligated sequence associated with chromosomal interaction is carried out by using a probe that can be detected when activated during PCR reaction, the ligated sequence comprises sequences from two chromosomal regions that are gathered in epigenetic chromosomal interaction, the method comprises contacting the ligated sequence with a probe during PCR reaction, and detecting the degree of activation of the probe, the probe binds to the ligation site.This method typically uses a dual-labeled fluorescent hydrolysis probe to make specific interaction detectable in a MIQE-compliant manner.

[0117] The probe is generally labeled with a detectable label that has an inactive state and an active state, so that it is only detected when activated. The degree of activation will be related to the degree of template (ligation product) present in the PCR reaction. Detection may be performed during the entire PCR or a part of it, for example, at least 50% or 80% of the cycles of PCR.

[0118] The probe may include a fluorophore covalently attached to one end of the oligonucleotide and a quencher attached to the other end of the nucleotide, where the fluorescence of the fluorophore is quenched by the quencher. In one embodiment, the fluorophore is attached to the 5' end of the oligonucleotide and the quencher is covalently attached to the 3' end of the oligonucleotide. Fluorophores that can be used in the methods of the invention include FAM, TET, JOE, Yakima Yellow, HEX, Cyanine 3, ATTO 550, TAMRA, ROX, Texas Red, Cyanine 3.5, LC610, LC 640, ATTO 647N, Cyanine 5, Cyanine 5.5 and ATTP 680. Quenchers that can be used with suitable fluorophores include TAM, BHQ1, DAB, Eclipse, BHQ2 and BBQ650, and optionally, the fluorophore is selected from HEX, Texas Red and FAM. Preferred combinations of fluorophores and quenchers include FAM and BHQ1 and Texas Red and BHQ2.

[0119] Use of probes in qPCR assays The hydrolysis probes of the present invention are typically temperature gradient optimized with concentration-matched negative controls. Preferably, a single-step PCR reaction is optimized. More preferably, a standard curve is calculated. The advantage of using a specific probe that binds to the ligated sequence junction is that the specificity of the ligated sequence can be achieved without using a nested PCR approach. The methods described herein allow accurate and precise quantification of low copy number targets. The ligated sequence of the target can be purified, e.g., gel purified, prior to temperature gradient optimization. The ligated sequence of the target can be sequenced. Preferably, the PCR reaction is performed using about 10 ng, or 5-15 ng, or 10-20 ng, or 10-50 ng, or 10-200 ng of template DNA. The forward and reverse primers are designed, e.g., by being complementary to the sequences, such that one primer binds to one sequence of the chromosomal region represented by the ligated DNA sequence and the other primer binds to the other chromosomal region represented by the ligated DNA sequence.

[0120] Selection of ligated DNA targets The present invention encompasses the selection of primers and probes for use in the PCR methods defined herein, which includes selecting a primer based on its ability to bind and amplify a ligated sequence, and in particular selecting a probe based on the properties of the target sequence to which it binds at the curvature of the target sequence.

[0121] Probes are typically designed / selected to bind to ligated sequences where restriction fragments spanning the restriction sites are juxtaposed. In one embodiment of the present invention, the predicted curvature of the ligated sequences potentially associated with a particular chromosomal interaction is calculated, for example, using certain algorithms referenced herein. The curvature can be expressed in degrees per helical turn, for example 10.5° per helical turn. Ligated sequences are selected for targets with a curvature propensity peak score of at least 5° per helical turn, typically at least 10°, 15° or 20° per helical turn, for example 5°-20° per helical turn. Preferably, the curvature propensity score per helical turn is calculated for at least 20, 50, 100, 200 or 400 bases, for example 20-400 bases, upstream and / or downstream of the ligation site. Thus, in one embodiment, the target sequence of the ligation product has any of these levels of curvature. Target sequences can also be selected based on the lowest thermodynamic structural free energy.

[0122] Specific embodiments In one embodiment, only intrachromosomal interactions are classified / detected and not extrachromosomal interactions (between different chromosomes).

[0123] In particular embodiments, a particular chromosomal interaction, such as any specific interaction referred to herein (e.g., as defined by any probe or primer pair referred to herein), is not classified. In some embodiments, a chromosomal interaction is not classified to any of the genes described herein, e.g., to any gene described in a figure, such as any or all of the genes described in Figures 2 and 4.

[0124] In one embodiment, none of the chromosomal interactions represented by the probes or primers of any or all of Tables 5-7 are classified. In another embodiment, none of the chromosomal interactions present in any of the genes listed in any or all of Tables 5-7 are classified. In a further embodiment, none of the chromosomal interactions present in any of the regions listed in any or all of Tables 5-7 are classified.

[0125] In one embodiment, the immune responsiveness is not related to antibody therapy. In another embodiment, the immune responsiveness is not related to anti-PD-1 therapy, e.g., anti-PD-1 therapy for melanoma. In another embodiment, the immune responsiveness is not related to treatment of one or more of the following cancers: hematological cancer, leukemia, prostate cancer, breast cancer, diffuse large B-cell lymphoma.

[0126] Screening Methods The present invention provides a method for determining which chromosomal interactions are associated with a chromosomal state corresponding to an immune responsive subgroup of a population, comprising contacting a first set of nucleic acids from the subgroup with a second set of index nucleic acids and hybridizing complementary sequences, the nucleic acids in the first and second sets of nucleic acids representing ligation products comprising sequences from both chromosomal regions clustered at the chromosomal interaction, and the pattern of hybridization between the first and second sets of nucleic acids allows the determination of which chromosomal interactions are specific to the immune responsive subgroup. The subgroup may be any of the specific subgroups defined herein, for example with reference to a particular disease state or therapy.

[0127] Publications The contents of all publications mentioned herein are incorporated herein by reference and may be used to further define aspects related to the present invention.

[0128] table Table 1 shows the final set of markers for immunocompetence testing. Table 2 shows the markers shared between anti-PD-1 and anti-PD-L1 trials. Table 3 shows markers that overlap with interferon gamma activating ORFs. Table 4 shows primer pairs that can be used to detect markers for immune responsiveness. Tables 5-7 show markers, genes and regions that are not included in certain embodiments. Table 8 shows immune checkpoint molecules. Table 9 provides examples of cancer therapies. Tables 10 and 11 show combination and monotherapies for certain embodiments of the present invention. In some embodiments, these are the therapies that are tested for responsiveness. In other embodiments, these therapies are administered to patients according to the results of the tests according to the present invention. Table 12 provides a description of the genes relevant to the present invention. Table 13 shows a further set of markers for testing immune responsiveness. Tables 14 and 15 describe genes related to embodiments of the present invention. Tables 16 to 18 show markers for testing immune responsiveness.

[0129] EMBODIMENTS OF THE PRESENT DISCLOSURE Subsection A. A process for detecting a chromosomal state representing a subgroup in a population, comprising detecting the presence or absence of a chromosomal interaction related to the chromosomal state within a defined region of the genome, said subgroup relating to the degree to which individuals are immunocompetent; and - said chromosomal interactions have optionally been identified by a method for determining which chromosomal interactions are associated with a chromosomal state corresponding to an immunoresponsive interaction subgroup of a population, the method comprising contacting a first set of nucleic acids from subgroups with different chromosomal states with a second set of index nucleic acids and allowing complementary sequences to hybridize, where the nucleic acids in the first and second sets of nucleic acids represent ligation products comprising sequences from both chromosomal regions clustered in the chromosomal interaction, and the pattern of hybridization between the first and second sets of nucleic acids allows the determination of which chromosomal interactions are specific to an immunoresponsive subgroup; and -Chromosomal interactions (i) in any of the regions or genes listed in Table 1; and / or (ii) corresponds to any of the chromosomal interactions represented by any of the probes shown in Table 1; and / or (iii) is present in a 4,000-base region that contains (i) or (ii) or is adjacent to (i) or (ii); or (a) in any of the regions or genes listed in Table 13; and / or (b) corresponds to any of the chromosomal interactions represented by any of the probes shown in Table 13; and / or (c) is present in a 4,000-base region that contains (a) or (b) or is adjacent to (a) or (b); or (α) present in any of the regions or genes listed in Table 16; and / or (β) corresponds to any of the chromosomal interactions represented by any of the probes shown in Table 16; and / or (γ) contains (α) or (β) or is present in a 4,000-base region adjacent to (α) or (β) Either process.

[0130] Section B. Specific combinations of chromosomal interactions (i) includes all chromosomal interactions represented by the probes in Table 1; or (ii) comprises at least 10, 50, 100, 150, 200 or 300 chromosomal interactions represented by the probes in Table 1; and / or (iii) are present together in at least 10, 50, 100, 150, or 200 regions or genes listed in Table 1; and / or (iv) comprises a chromosomal interaction represented by a probe in Table 1 or comprises at least 10, 50, 100, 150, 200, or 300 chromosomal interactions present in a 4,000 base region adjacent to a chromosomal interaction represented by a probe in Table 1. A process described in section A that is classified as

[0131] Section C. Specific combinations of chromosomal interactions (i) includes all chromosomal interactions represented by the probes in Table 13; or (ii) comprises at least 10, 50, 100, 150, 200 or 300 chromosomal interactions represented by the probes of Table 13; and / or (iii) are present together in at least 10, 50, 100, 150, or 200 regions or genes listed in Table 13; and / or (iv) comprises a chromosomal interaction represented by a probe in Table 13 or comprises at least 10, 50, 100, 150, 200, or 300 chromosomal interactions present in a 4,000 base region adjacent to a chromosomal interaction represented by a probe in Table 13. A process described in section A that is classified as

[0132] D. Chromosomal interactions in a sample from an individual, and / or by detecting the presence or absence of DNA loops at the site of chromosomal interaction, and / or by detecting the presence or absence of distal regions of chromosomes that are assembled into a chromosomal conformation, and / or - by detecting the presence of ligated nucleic acids generated during said sorting and whose sequences comprise two regions each corresponding to a region of the chromosome that is recruited in the chromosomal interaction, wherein the detection of the ligated nucleic acids preferably comprises: (i) using a probe having at least 70% identity to any of the specific probe sequences set forth in Table 1, and / or (ii) a primer pair having at least 70% identity to any of the primer pairs in Table 4; or (a) using a probe having at least 70% identity to any of the specific probe sequences listed in Table 13, and / or (b) a primer pair having at least 70% identity to any of the primer pairs in Table 13. The process according to any of the above clauses, wherein any of the following is used:

[0133] E. - the second set of nucleic acids is from a larger group of individuals than the first set of nucleic acids; and / or - the first set of nucleic acids is from at least 8 individuals; and / or - the first set of nucleic acids is from at least 4 individuals from a first subgroup and at least 4 individuals from a second subgroup that preferably does not overlap with the first subgroup; and / or - the process is carried out to select individuals for medical treatment; and / or - immune responsiveness to immunotherapy or immune checkpoint therapy; and / or - The immune system is responsive to cancer immunotherapy; and / or - the process is carried out to determine immune responsiveness at one or more defined time points, optionally with at least one time point being during the course of treatment A process according to any of the preceding paragraphs.

[0134] F. - the second set of nucleic acids represents a non-selected group; and / or - a second set of nucleic acids is attached to the array at defined locations; and / or - the second set of nucleic acids represents chromosomal interactions in at least 100 different genes; and / or - the second set of nucleic acids comprises at least 1,000 different nucleic acids representing at least 1,000 different chromosomal interactions; and / or - the first set of nucleic acids and the second set of nucleic acids comprise at least 100 nucleic acids having a length of 10 to 100 nucleotide bases. A process according to any of the preceding paragraphs.

[0135] G. The first set of nucleic acids comprises: (i) A bridging step of chromosomal regions clustered in chromosomal interactions; (ii) cleaving the cross-linked region, optionally by enzymatic restriction digestion; and (iii) ligating the cross-linked and cleaved DNA ends to generate a first set of nucleic acids, specifically comprising ligated DNA. 4. The process according to any of the preceding claims, which is obtained in a process comprising:

[0136] H.- At least 10-200 different chromosomal interactions are classified, preferably in 10-200 different regions or genes; and optionally (a) 50-100 different chromosomal interactions are classified, each in a different gene and / or a different region as defined in Table 1; or (b) 50-100 different chromosomal interactions are classified, each in a different gene and / or a different region as defined in Table 13; and / or -To select whether an individual will undergo immunotherapy, where the immunotherapy preferably comprises small molecule immunotherapy, antibody immunotherapy or cellular immunotherapy A process according to any of the preceding paragraphs.

[0137] I. (i) contains a single nucleotide polymorphism (SNP); and / or (ii) expresses microRNA (miRNA); and / or (iii) expresses non-coding RNA (ncRNA); and / or (iv) expressing a nucleic acid sequence encoding at least 10 contiguous amino acid residues; and / or (v) expressing the regulatory element; and / or (vii) contains a CTCF binding site A process according to any of the preceding paragraphs.

[0138] J. A process according to any of the above clauses carried out to identify or design a therapeutic agent for immunotherapy, - preferably said process is used to detect whether a candidate agent is capable of inducing changes to chromosomal states that are associated with different levels of immune responsiveness; - the chromosomal interaction is represented by any of the probes in Table 1; and / or - the chromosomal interaction is present in any region or gene listed in Table 1; and optionally: - the chromosomal interactions have been identified by a method for determining which chromosomal interactions are associated with a chromosomal status as defined in A, and / or -Changes in chromosomal interactions are monitored using (i) a probe having at least 70% identity to any of the probe sequences listed in Table 1, and / or (ii) a primer pair having at least 70% identity to any of the primer pairs in Table 4. process.

[0139] K. A process according to any of the above clauses carried out to identify or design a therapeutic agent for immunotherapy, - preferably said process is used to detect whether a candidate agent is capable of inducing changes to chromosomal states that are associated with different levels of immune responsiveness; - the chromosomal interaction is represented by any of the probes in Table 13; and / or - the chromosomal interaction is present in any region or gene listed in Table 13; and optionally: - the chromosomal interactions have been identified by a method for determining which chromosomal interactions are associated with a chromosomal status as defined in A, and / or -Changes in chromosomal interactions are monitored using (i) a probe having at least 70% identity to any of the probe sequences listed in Table 13, and / or (ii) a primer pair having at least 70% identity to any of the primer pairs in Table 13. process.

[0140] L. A process as described in paragraphs J or K above, comprising selecting a target based on detection of a chromosomal interaction, and preferably screening modulators of the target to identify therapeutic agents for immunotherapy, wherein the target is optionally a protein.

[0141] A therapeutic agent for use in immunotherapy in an individual who has been identified as in need of the therapeutic agent by the process described in any of Sections MA-I.

[0142] N. The classification or detection comprises specific detection of the ligation products by quantitative PCR (qPCR) using primers capable of amplifying the ligation products and probes that bind to the ligation sites during the PCR reaction, said probes comprising sequences complementary to sequences from each chromosomal region that is clustered in the chromosomal interaction, preferably said probes comprising: an oligonucleotide that specifically binds to the ligation product, and / or a fluorophore covalently attached to the 5' end of the oligonucleotide, and / or a quencher moiety covalently attached to the 3' end of the oligonucleotide, and Optionally, the fluorophore is selected from HEX, Texas Red and FAM; and / or The probe is a nucleic acid sequence having a length of 10 to 40 nucleotide bases, preferably 20 to 30 nucleotide bases. A process according to any one of paragraphs A to K or a therapeutic agent according to paragraph M, comprising:

[0143] Specific Aspects The EpiSwitch™ platform technology detects epigenetic regulatory signatures of regulatory changes between normal and abnormal disease states at gene loci. The EpiSwitch™ platform identifies and monitors the fundamental epigenetic levels of gene regulation associated with the regulatory conformation of human chromosomes, also known as chromosome conformation signatures. Chromosome signatures are distinct primary steps in the cascade of gene deregulation. They are high-order biomarkers that have a unique set of advantages over biomarker platforms that utilize late epigenetic and gene expression biomarkers, such as DNA methylation and RNA profiling.

[0144] EpiSwitch™ Array Assays The custom EpiSwitch™ array screening platform is available in four densities: 15K, 45K, 100K, and 250K unique chromosome conformations, with each chimeric fragment repeated four times in the array, creating effective densities of 60K, 180K, 400K, and 100,000, respectively.

[0145] Custom-designed EpiSwitch™ arrays The 15K EpiSwitch™ array can screen the entire genome, including around 300 loci interrogated with EpiSwitch™ biomarker discovery technology. EpiSwitch™ arrays are built on the Agilent SurePrint G3 Custom CGH microarray platform; this technology provides four densities of probes: 60K, 180K, 400K, and 100,000. Since each EpiSwitch™ probe is presented as a quadruplet, the density per array is reduced to 15K, 45K, 100K, and 250K, thus allowing for statistical evaluation of reproducibility. The average number of potential EpiSwitch™ markers interrogated per locus is 50; thus, the number of loci that can be examined is 300, 900, 2000, and 5000.

[0146] EpiSwitch™ Custom Array Pipeline The EpiSwitch™ array is a two-color system with one set of samples, after EpiSwitch™ library generation, labeled with Cy5 and the other sample to be compared / analyzed (control) labeled with Cy3. The arrays are scanned using an Agilent SureScan scanner and the resulting features are extracted using Agilent Feature Extraction software. The data is then processed using the EpiSwitch™ array processing script in R. The arrays are run using the standard two-color package in Bioconductor in R: Limma * Array normalization is performed using Limma. * This was done using the intra-array normalization feature in and against the on-chip Agilent positive controls and EpiSwitch™ positive controls. Data was filtered based on Agilent Flag calls, Agilent control probes were removed, and technical replicate probes were averaged and then run in Limma. *The probes are compared and then modeled based on their differences between the two scenarios, which are corrected by using the False Discover Rate. Probes with a coefficient of variation (CV) of <30%, <=1.1 or =>1.1, and passing an FDR p-value of p=0.01 are used for further screening. To reduce the probe set, further multifactorial analysis is performed using the FactorMineR package in R.

[0147] * NOTE: LIMMA is a linear model and empirical Bayesian method for assessing differential expression in microarray experiments. Limma is an R package for the analysis of gene expression data generated by microarray or RNA-Seq.

[0148] A pool of probes is initially selected for final selection based on the parameters of adjusted p-value, FC, and <30% CV (arbitrary cutoff point). Further analysis and the final list are derived based only on the first two parameters (adjusted p-value; FC).

[0149] Statistical Pipeline To select high value EpiSwitch™ markers for transfer to the EpiSwitch™ PCR platform, the EpiSwitch™ screening arrays are processed using the EpiSwitch™ analysis package in R.

[0150] Process 1 Probes are selected based on their corrected p-value (false discovery rate, FDR), which is the product of a modified linear regression model. Probes with p-values ​​below ≦0.1 are selected and then further reduced by their epigenetic ratio (ER), probes ER must be ≦-1.1 or ≧1.1 to be selected for further analysis. The final filter is the coefficient of variation (CV), probes must be below ≦0.3.

[0151] Process 2 The top 40 markers of the statistical list are selected based on their ER for selection as markers for PCR conversion. The top 20 markers with the most negative ER load and the top 20 markers with the most positive ER load form the list.

[0152] Process 3 The resulting markers, statistically significant probes from step 1, form the basis of an enrichment analysis using hypergeometric enrichment (HE), which allows marker reduction from the significant probe list and, together with the markers from step 2, forms the list of probes that are transferred to the EpiSwitch™ PCR platform.

[0153] The statistical probes are processed by HE to determine which genetic locations exhibit statistically significant enrichment of probes, indicating which genetic locations are epicenters of epigenetic differences.

[0154] The most significant enriched loci based on corrected p-values ​​are selected for probe list generation. Genetic locations below a p-value of 0.3 or 0.2 are selected. Statistical probes mapping to these genetic locations along with the markers from step 2 form high-value markers for EpiSwitch™ PCR conversion.

[0155] Array Design and Processing Array Design 1. The loci were processed using SII software (currently v3.2) a. Retrieve the genomic sequences at these specific loci (gene sequences with 50 kb upstream and 20 kb downstream). b. Determine the probability that sequences within this region are involved in CCs. c. A specific RE is used to cut the sequence. d. Determine whether the restriction fragments are likely to interact in a particular orientation. e. Rank the likelihood of the various CCs interacting together. 2. Determine the array size, and hence the number of available probe sites (x). 3. Extract x / 4 interactions. 4. For each interaction, define 30bp of sequence from part 1 to the restriction site and 30bp to the restriction site in part 2. Check that those regions are not repeats, exclude them if so, and pick the next interaction down the list. Join both 30bp together to define the probe. 5. Create a list of x / 4 probes, plus a defined control probe, and replicate four times to be created on the array. 6. Upload the probe list to the Agilent Sure design website for custom CGH arrays. 7. Design Agilent custom CGH arrays using the probe sets.

[0156] Array Processing 1. For template production, process samples using the EpiSwitch™ Standard Operating Procedure (SOP). 2. Clean up by ethanol precipitation by the array processing laboratory. 3. Process samples as described in Agilent SureTag complete DNA labeling kit - Agilent Oligonucleotide Array-based CGH for Genomic DNA Analysis Enzymatic labelling for Blood, Cereals or Tissues. 4. Scan using an Agilent C Scanner using Agilent feature extraction software.

[0157] EpiSwitch™ biomarker signatures exhibit high structural stability, sensitivity, and specificity in stratifying complex disease phenotypes. The technology leverages recent breakthroughs in epigenetic chemistry, monitoring and evaluation of chromosome conformation signatures as a highly informative class of epigenetic biomarkers. Current research methodologies deployed in academic settings require 3-7 days of biochemical processing of cellular material to detect CCSs. These procedures limit sensitivity and reproducibility, and furthermore, do not have the benefit of targeted insights offered by the EpiSwitch™ analytical package at the design stage.

[0158] Computational EpiSwitch™ Array Marker Identification CCS sites in the genome are assessed directly by EpiSwitch™ arrays on clinical samples of the study cohort to identify all relevant stratified lead biomarkers. The EpiSwitch™ array platform is used for marker identification due to its high throughput capacity and ability to rapidly screen a large number of loci. The arrays used were Agilent custom CGH arrays that allow markers to be identified by interrogated in silico software.

[0159] EpiSwitch(TM) PCR Potential markers identified by the EpiSwitch™ Array are then validated by EpiSwitch™ PCR or DNA sequencer (i.e., Roche 454, Nanopore MinION, etc.). Top PCR markers that are statistically significant and show the highest reproducibility are selected for further reduction to a final EpiSwitch™ signature set, which is validated in an independent cohort of samples. EpiSwitch™ PCR is performed by trained technicians following established standardized operating procedure protocols. Manufacturing of all protocols and reagents is under ISO 13485 and 9001 certification, ensuring the quality of work and transferability of the protocols. The EpiSwitch™ PCR and EpiSwitch™ Array biomarker platforms are compatible with both whole blood and cell line analysis. The tests are sensitive enough to detect very low copy number abnormalities using small volumes of blood. EXAMPLES

[0160] In the first study, patients with melanoma were treated with anti-PD-1 (pembrolizumab) for 12 weeks. Their epigenetic state, as measured by EpiSwitch, was assessed first at baseline before treatment and then at 12 weeks, along with a clinical readout of response or non-response. We then screened, evaluated, and validated some of the 3D genome structure profiles, chromosome conformation signatures, at baseline to identify profiles that result in response or non-response to treatment at over 332 genetic locations across the genome. These were assessed with EpiSwitch arrays that interrogate local multiple 3C interactions at these genetic locations in technical and biological repeats, comparing samples from responders and non-responders at baseline. Over 14,000 EpiSwitch markers were assessed directly on the array. The best markers were translated to PCR and evaluated in an independent patient cohort.

[0161] Figure 1 shows an example of clinical annotation of patients used in the study. Color-coded indicators: Patients listed in red were used for array screening. Patients in blue were used as part of an independent cohort for validation. They were not used for marker selection, which is important in the development of robust biomarkers. Clinical assessment of response or non-response was defined by standard RESIST1.1 criteria.

[0162] Stage 1 consists of an initial array screening and evaluation of 14000 marker reads (all predicted by pattern recognition). Stage 2 is the translation of statistically significant marker reads from array to PCR. Further evaluation of markers by PCR with regression analysis for reduction of the final number of markers in the final signature. Stage 3 is the validation of the final signature of the 6 best biomarkers (shown in Figure 2). The table in Figure 2 shows the names of the best biomarkers, the loci where they are located, i.e. where they contribute in a specific way to the overall regulation.

[0163] Figure 3 shows a Venn diagram for the best predictive biomarkers from array analysis (comparing baseline for responders and non-responders) and the best response biomarkers (comparing responders at baseline and week 12). The overlap gives good response biomarkers that are not only present at the onset of response, but can also be monitored over the course of 12 weeks.

[0164] Figure 4 is an example of an individual patient binary PCR readout for some final signature biomarkers: 1 CCs present, 0 CCs absent. Visually you can see the difference in responder and non-responder profiles. R is a responder. NR is a non-responder.

[0165] Figure 5 shows two groups of patients with lung cancer treated with anti-PD-L1 monoclonal antibodies. Blood was collected at baseline (BL) before treatment, and two weeks (2W) after the start of treatment. The identity of the two groups for response was established, but blinded to groups I and II in the original study. The top 30 PCR-based marker leads predictive of response from anti-PD-1 from the original study were evaluated for all patients listed.

[0166] Figure 6 shows the statistical analysis of the top 13 statistically significant markers discriminating between groups I and II. PDCD1LG2 and STAT5 are also top discriminating markers in the original anti-PD-1 trial: PDCD1LG2 for non-responders and STAT5B for responders. This helps to correctly identify groups I and II as responder and non-responder groups. The biomarkers monitor the deregulation of the same immunotherapy checkpoint cellular network induced by either PD-1 in the first trial or its ligand PD-L1 in the second trial, and share overlapping features with the same markers - 6 non-responder markers, 7 responder markers, and 7 responder markers from the first trial with PD-1 are still valid in the second trial with PD-L1.

[0167] Figure 7 shows a principal component analysis (PCA) of the top 13 markers selected from the PD-L1 cohort. This is a 3D PCA and shows good separation of responders and non-responders on the first three components of stratification. Notably, non-responders (dark triangles) also separate among the same patients for baseline (A) and 2 weeks (B) of treatment. This is a separate feature related to how tightly regulated the epigenetic profile is in responders and non-responders.

[0168] Figure 8 shows how in another third study performed on lung cancer patients using different anti-PD-L1 monoclonals, baseline samples of 15 patients were provided as blinded with annotation of response / non-response to treatment. Using 8 patients from the first study (PD-1 treatment in melanoma) and 24 patients from the second study (different PD-L1 in lung cancer), the first and second studies were combined to evaluate the pool of markers, and then the top 5 markers in terms of statistical significance (listed in the table) were used to classify the 15 blinded samples.

[0169] Figure 9 shows how a random forest classifier built on the five listed markers generates a predictive call for each of the 15 samples (predicted column). Figure 10 shows the predicted calls for each sample compared to the open-blind validation (actual column). The stratification efficiency is shown in the table: sensitivity 71%, specificity 87.5%, positive predictive value 83% (important in this patient selection context), negative predictive value 77%.

[0170] Figure 11 shows the standard rOC curve for the classifier. AUC=0.786

[0171] Figure 12 shows the principal component analysis of all samples used in this analysis: 8 from the first test, 24 from the second test, and 15 from validation. On the first principal component, the separation of responders and non-responders is already self-evident. The open classifier has only 2 incorrectly called samples out of all 47 samples.

[0172] The third study concerns anti-PD-L1 therapy in lung cancer. During the array stage of screening, 12 responders and 12 non-responders were compared at baseline on the array for a total of 180,000 reads (technical and biological repeats). Then, PCR translation of the top 100 marker reads from the array was performed, followed by validation.

[0173] A comparison of marker reads from arrays for PD-1 (Study I), PD-L1 (Study II), and PD-L1 Study III was performed. Figure 13 shows the overlap of 2522 common reads for responders. Figure 14 shows the same, but now the most statistically significant - looking at 276 common significant reads in both studies for responders (Study I on the left, Study II on the right). Figure 15 shows the same, but only 1 for non-responders (Study I on the left, Study II on the right).

[0174] Figure 16 shows how the loci of array reads for response and non-response markers (studies I and III) overlap with genes involved in the interferon gamma pathway. Interferon gamma treatment can increase PD-L1 expression, which is a clinical observation of predisposition to response to treatment. Figure 17 is the same, but shows only statistically significant data. Figure 18 is the same, but for all studies I-III.

[0175] Figure 19 shows a Venn diagram across the four cohorts: gene loci (ORFs) for the INFG pathway, anti-PD-L1 responders and non-responders, and all anti-PD-1.

[0176] Figure 20 shows a Venn diagram across the four cohorts: gene loci (ORFs) for the INFG pathway, anti-PD-1 responders and non-responders, and all anti-PD-L1.

[0177] Figure 21 shows all loci of responder markers shared between studies I-III and the INFG gene. Figure 22 shows the same, but with a list of 95 loci including some of the significant response EpiSwitch markers shared across all three studies I-III. Figure 23 shows the loci list from Figure 22 showing the number of significant marker reads and the total number of marker reads when these loci are evaluated on the array. Figure 24 shows the interferon signaling pathway that matched ORFs associated with significant EpiSwitch™ CCS of PDF-L1.

[0178] After establishing common epigenetic preferences as markers of responders in PD-1 and PD-L1 treatment, we traced the observed genetic loci under the control of epigenetic preferences to their protein products and investigated the network relationships of those proteins in terms of known protein-protein networks and their functional roles. Overlaying the loci affected by EpiSwitch markers of response onto the String database network, we show that epigenetically regulated proteins in responders are involved in a tight network linked to two functions: immune response-regulating cell surface receptor signaling pathways and regulating T-cell activation.

[0179] Specific conclusions Markers have been identified that have statistically significant penetrating power to identify patients who are set at baseline to have a good response to immunotherapy (including immune checkpoint therapy), i.e., responders, and those who are not, i.e., non-responders or progressors. The markers in Table 1 represent a common universal profile of responders across three independent cohorts with either melanoma or lung cancer (NSCLC). Melanoma patients were treated with PD-1 (pembrolizumab) and NSCLC were treated with two different PD-L1. These are agnostic markers predictive of treatment and are present in different types of cancer. There is also one important agnostic universal predictive marker of non-responders located between the PD-L1 and PD-L2 loci.

[0180] The list of markers in Table 1 reflects common network modulation of responders and can be used as agnostic markers to monitor response / non-response across a range of treatments and conditions, including response to treatments targeting canonical immune checkpoint molecules that control immunological network responses.

[0181] Future research Continuing the goal of identifying epigenetic alterations based on chromosomal structural signatures (CCSs) will allow for the selection of predictive patients who will respond to anti-PD-1 therapy, either alone or in combination, for the treatment of non-small cell lung cancer (NSCLC). The EpiSwitch™ markers discovered from this array screening were then screened and validated using the EpiSwitch™ PCR platform with three immunotherapy cohorts, two anti-PD-L1 therapies, and one anti-PD-1 therapy (pembrolizumab) in baseline patient samples. Two anti-PD-L1 responsive CCSs were developed in NSCLC patients, and a pembrolizumab responsive CCS was developed in melanoma patients and further validated in NSCLC patients. Tables 13, 16, and 18 provide the results of further studies and show additional sets of markers that can be used to determine immune responsiveness.

[0182] Test Design In the metastatic melanoma study, a total of 32 peripheral blood mononuclear cell (PBMC) samples from 16 patients with metastatic melanoma were examined. These patients received anti-PD1 therapy. Patients had tumor assessments at two time points: baseline and 12 weeks. A total of 16 samples were used in the discovery phase using the EpiSwitch array. The top 100 EpiSwitch markers identified from the array screening were validated in baseline and 12-week samples to identify response and pharmacodynamic effects to anti-PD1 therapy. The top EpiSwitch markers were classified into two groups: responders and non-responders to anti-PD-1 therapy.

[0183] The NSCLC study examined a total of 16 baseline PBMCs from non-small cell lung cancer (NSCLC) patients treated with anti-PD-L1 therapy. Thirty EpiSwitch™ predictive markers were evaluated. The objective of this project was to confirm the predictive ability of EpiSwitch markers common to anti-PD-1 and anti-PD-L1 predictive profiles in baseline NSCLC patients treated with anti-PD-L1 therapy.

[0184] [Table 1] TIFF0007631400000002.tif144152 TIFF0007631400000003.tif140152 TIFF0007631400000004.tif27152 TIFF0007631400000005.tif237157 TIFF0007631400000006.tif20157 TIFF0007631400000007.tif144152 TIFF0007631400000008.tif14564 TIFF0007631400000009.tif153157 TIFF0007631400000010.tif89157 TIFF0007631400000011.tif145147 TIFF0007631400000012.tif91147 TIFF0007631400000013.tif142152 TIFF0007631400000014.tif97152 TIFF0007631400000015.tif132152 TIFF0007631400000016.tif230152 TIFF0007631400000017.tif99152 TIFF0007631400000018.tif130147 TIFF0007631400000019.tif109147 TIFF0007631400000020.tif12280 TIFF0007631400000021.tif11980 TIFF0007631400000022.tif112152 TIFF0007631400000023.tif171152 TIFF0007631400000024.tif60152 TIFF0007631400000025.tif224152 TIFF0007631400000026.tif236152 TIFF0007631400000027.tif81152 TIFF0007631400000028.tif150152 TIFF0007631400000029.tif231152 TIFF0007631400000030.tif169152 TIFF0007631400000031.tif63152 TIFF0007631400000032.tif221152 TIFF0007631400000033.tif24285 TIFF0007631400000034.tif4684 TIFF0007631400000035.tif185152 TIFF0007631400000036.tif100152 TIFF0007631400000037.tif133152 TIFF0007631400000038.tif152152 TIFF0007631400000039.tif83157 TIFF0007631400000040.tif202157 TIFF0007631400000041.tif27152 TIFF0007631400000042.tif231152 TIFF0007631400000043.tif231152 TIFF0007631400000044.tif63152 TIFF0007631400000045.tif166152 TIFF0007631400000046.tif118152 TIFF0007631400000047.tif11482 TIFF0007631400000048.tif17583 TIFF0007631400000049.tif59152 TIFF0007631400000050.tif225152 TIFF0007631400000051.tif238152 TIFF0007631400000052.tif47152 TIFF0007631400000053.tif189157 TIFF0007631400000054.tif97157 TIFF0007631400000055.tif132152 TIFF0007631400000056.tif230152 TIFF0007631400000057.tif186152 TIFF0007631400000058.tif41152 TIFF0007631400000059.tif230152 TIFF0007631400000060.tif15152 TIFF0007631400000061.tif21795 TIFF0007631400000062.tif6996 TIFF0007631400000063.tif161152 TIFF0007631400000064.tif122152 TIFF0007631400000065.tif108152 TIFF0007631400000066.tif172152 TIFF0007631400000067.tif60157 TIFF0007631400000068.tif224157 TIFF0007631400000069.tif229152 TIFF0007631400000070.tif230152 TIFF0007631400000071.tif89152 TIFF0007631400000072.tif139152 TIFF0007631400000073.tif145152 TIFF0007631400000074.tif8694 TIFF0007631400000075.tif20194 TIFF0007631400000076.tif33152 TIFF0007631400000077.tif167152 TIFF0007631400000078.tif63152 TIFF0007631400000079.tif131152 TIFF0007631400000080.tif101156 TIFF0007631400000081.tif97156 TIFF0007631400000082.tif133152 TIFF0007631400000083.tif231152 TIFF0007631400000084.tif19152 TIFF0007631400000085.tif198152 TIFF0007631400000086.tif201101

[0185] [Table 2] TIFF0007631400000088.tif166152 TIFF0007631400000089.tif64152 TIFF0007631400000090.tif166152 TIFF0007631400000091.tif69152 TIFF0007631400000092.tif160152 TIFF0007631400000093.tif73152 TIFF0007631400000094.tif156152 TIFF0007631400000095.tif78152 TIFF0007631400000096.tif152152 TIFF0007631400000097.tif82152 TIFF0007631400000098.tif147152 TIFF0007631400000099.tif87152 TIFF0007631400000100.tif143152 TIFF0007631400000101.tif91152 TIFF0007631400000102.tif138152 TIFF0007631400000103.tif95152 TIFF0007631400000104.tif134152 TIFF0007631400000105.tif100152 TIFF0007631400000106.tif84152

[0186] [Table 3] TIFF0007631400000108.tif158152 TIFF0007631400000109.tif157152

[0187]

Table 4

[0188]

Table 5

[0189]

Table 6

[0190]

Table 7

[0191]

Table 8

[0192]

Table 9

[0193]

Table 10

[0194]

Table 11

[0195]

Table 12

[0196]

Table 13

[0197]

Table 14

[0198]

Table 15

[0199]

Table 16

[0200]

Table 17

[0201]

Table 18

[0202] Item 1. A process for detecting a chromosomal state representing a subgroup in a population, the process comprising determining whether chromosomal interactions related to the chromosomal state are present or absent within a defined region of the genome, the subgroup being related to how immune responsive an individual is; and - said chromosomal interactions have optionally been identified by a method for determining which chromosomal interactions are associated with a chromosomal state corresponding to an immunoresponsive interaction subgroup of a population, the method comprising contacting a first set of nucleic acids from subgroups with different chromosomal states with a second set of index nucleic acids and allowing complementary sequences to hybridize, where the nucleic acids in the first and second sets of nucleic acids represent ligation products comprising sequences from both chromosomal regions clustered in the chromosomal interaction, and the pattern of hybridization between the first and second sets of nucleic acids allows the determination of which chromosomal interactions are specific to an immunoresponsive subgroup; and -Chromosomal interactions (i) in any of the regions or genes listed in Table 1; and / or (ii) corresponds to any of the chromosomal interactions represented by any of the probes shown in Table 1; and / or (iii) is present in a 4,000-base region that contains (i) or (ii) or is adjacent to (i) or (ii); or (a) in any of the regions or genes listed in Table 13; and / or (b) corresponds to any of the chromosomal interactions represented by any of the probes shown in Table 13; and / or (c) is present in a 4,000-base region that contains (a) or (b) or is adjacent to (a) or (b); or (α) present in any of the regions or genes listed in Table 16; and / or (β) corresponds to any of the chromosomal interactions represented by any of the probes shown in Table 16; and / or (γ) contains (α) or (β) or is present in a 4,000-base region adjacent to (α) or (β) Either process.

[0203] 2. A specific combination of chromosomal interactions (i) includes all chromosomal interactions represented by the probes in Table 1; or (ii) comprises at least 10, 50, 100, 150, 200 or 300 chromosomal interactions represented by the probes in Table 1; and / or (iii) are present together in at least 10, 50, 100, 150, or 200 regions or genes listed in Table 1; and / or (iv) comprises a chromosomal interaction represented by a probe in Table 1 or comprises at least 10, 50, 100, 150, 200, or 300 chromosomal interactions present in a 4,000 base region adjacent to a chromosomal interaction represented by a probe in Table 1. 10. The process according to claim 1,

[0204] Item 3. A specific combination of chromosomal interactions (i) includes all chromosomal interactions represented by the probes in Table 13; or (ii) comprises at least 10, 50, 100, 150, 200 or 300 chromosomal interactions represented by the probes of Table 13; and / or (iii) are present together in at least 10, 50, 100, 150, or 200 regions or genes listed in Table 13; and / or (iv) comprises a chromosomal interaction represented by a probe in Table 13 or comprises at least 10, 50, 100, 150, 200, or 300 chromosomal interactions present in a 4,000 base region adjacent to a chromosomal interaction represented by a probe in Table 13. 10. The process according to claim 1,

[0205] Item 4. A specific combination of chromosomal interactions (i) includes all chromosomal interactions represented by the probes in Table 16; or (ii) comprises at least 10, 50, 100, 150, 200 or 300 chromosomal interactions represented by the probes of Table 16; and / or (iii) are present together in at least 10, 50, 100, 150, or 200 regions or genes listed in Table 16; and / or (iv) comprises a chromosomal interaction represented by a probe in Table 16 or comprises at least 10, 50, 100, 150, 200, or 300 chromosomal interactions present in a 4,000 base region adjacent to a chromosomal interaction represented by a probe in Table 16. 10. The process according to claim 1,

[0206] 5. Chromosomal interactions are in a sample from an individual, and / or by detecting the presence or absence of DNA loops at the site of chromosomal interaction, and / or by detecting the presence or absence of distal regions of chromosomes that are assembled into a chromosomal conformation, and / or - by detecting the presence of ligated nucleic acids generated during said sorting and whose sequences comprise two regions each corresponding to a region of the chromosome that is recruited in the chromosomal interaction, wherein the detection of the ligated nucleic acids preferably comprises: (i) using a probe having at least 70% identity to any of the specific probe sequences set forth in Table 1, and / or (ii) a primer pair having at least 70% identity to any of the primer pairs in Table 4; or (a) using a probe having at least 70% identity to any of the specific probe sequences set forth in Table 13, and / or (b) a primer pair having at least 70% identity to any of the primer pairs in Table 13; or Chromosomal interactions (α) using a probe having at least 70% identity to any of the specific probe sequences listed in Table 16, and / or (β) a primer pair having at least 70% identity to any of the primer pairs in Table 17. Either 2. The process according to claim 1, which is classified as

[0207] Item 6. - The second set of nucleic acids is from a larger group of individuals than the first set of nucleic acids; and / or - the first set of nucleic acids is from at least 8 individuals; and / or - the first set of nucleic acids is from at least 4 individuals from a first subgroup and at least 4 individuals from a second subgroup that preferably does not overlap with the first subgroup; and / or - the process is carried out to select individuals for medical treatment; and / or - immune responsiveness to immunotherapy or immune checkpoint therapy; and / or - The immune system is responsive to cancer immunotherapy; and / or - the process is carried out to determine immune responsiveness at one or more defined time points, optionally at least one of the time points being during the course of treatment The process according to any one of items 1 to 5 above.

[0208] Item 7. - The second set of nucleic acids represents a non-selected group; and / or - a second set of nucleic acids is attached to the array at defined locations; and / or - the second set of nucleic acids represents chromosomal interactions in at least 100 different genes; and / or - the second set of nucleic acids comprises at least 1,000 different nucleic acids representing at least 1,000 different chromosomal interactions; and / or - the first set of nucleic acids and the second set of nucleic acids comprise at least 100 nucleic acids having a length of 10 to 100 nucleotide bases. The process according to any one of items 1 to 6 above.

[0209] Item 8. The first set of nucleic acids comprises: (i) A bridging step of chromosomal regions clustered in chromosomal interactions; (ii) cleaving the cross-linked region, optionally by enzymatic restriction digestion; and (iii) ligating the cross-linked and cleaved DNA ends to generate a first set of nucleic acids, specifically comprising ligated DNA. 8. The process according to any one of claims 1 to 7, which is obtained by a process comprising:

[0210] Item 9. - At least 10 to 200 different chromosomal interactions are classified, preferably in 10 to 200 different regions or genes; and optionally (a) 50-100 different chromosomal interactions are classified, each in a different gene and / or a different region as defined in Table 1; or (b) between 50 and 100 different chromosomal interactions are classified, each in a different gene and / or a different region as defined in Table 13; or (c) 20-40 different chromosomal interactions are classified, each in a different gene and / or a different region as defined in Table 16; and / or -To select whether an individual will undergo immunotherapy, where the immunotherapy preferably comprises small molecule immunotherapy, antibody immunotherapy or cellular immunotherapy The process according to any one of items 1 to 8 above.

[0211] Item 10. The defined region of the genome comprises: (i) contains a single nucleotide polymorphism (SNP); and / or (ii) expresses microRNA (miRNA); and / or (iii) expresses a non-coding RNA (ncRNA); and / or (iv) expressing a nucleic acid sequence encoding at least 10 contiguous amino acid residues; and / or (v) expressing the control element; and / or (vii) contains a CTCF binding site The process according to any one of items 1 to 9 above.

[0212] Item 11. A process according to any one of items 1 to 10 above, which is carried out to identify or design a therapeutic agent for immunotherapy, - preferably said process is used to detect whether a candidate agent is capable of inducing changes to chromosomal states that are associated with different levels of immune responsiveness; - the chromosomal interaction is represented by any of the probes in Table 1; and / or - the chromosomal interaction is present in any region or gene listed in Table 1; and optionally: - the chromosomal interactions have been identified by a method for determining which chromosomal interactions are associated with a chromosomal status as defined in claim 1, and / or -Changes in chromosomal interactions are monitored using (i) a probe having at least 70% identity to any of the probe sequences listed in Table 1, and / or (ii) a primer pair having at least 70% identity to any of the primer pairs in Table 4. process.

[0213] Item 12. A process according to any one of items 1 to 11 above, which is carried out to identify or design a therapeutic agent for immunotherapy, - preferably said process is used to detect whether a candidate agent is capable of inducing changes to chromosomal states that are associated with different levels of immune responsiveness; - the chromosomal interaction is represented by any of the probes in Table 13; and / or - the chromosomal interaction is present in any region or gene listed in Table 13; and optionally: - the chromosomal interactions have been identified by a method for determining which chromosomal interactions are associated with a chromosomal status as defined in paragraph 1 above, and / or -Changes in chromosomal interactions are monitored using (i) a probe having at least 70% identity to any of the probe sequences listed in Table 13, and / or (ii) a primer pair having at least 70% identity to any of the primer pairs in Table 13. process.

[0214] Item 13. A process according to any one of items 1 to 12 above, which is carried out to identify or design a therapeutic agent for immunotherapy, - preferably said process is used to detect whether a candidate agent is capable of inducing changes to chromosomal states that are associated with different levels of immune responsiveness; - the chromosomal interaction is represented by any of the probes in Table 16; and / or - the chromosomal interaction is present in any region or gene listed in Table 16; and optionally: - the chromosomal interactions have been identified by a method for determining which chromosomal interactions are associated with a chromosomal status as defined in paragraph 1 above, and / or -Changes in chromosomal interactions are monitored using (i) a probe having at least 70% identity to any of the probe sequences listed in Table 16, and / or (ii) a primer pair having at least 70% identity to any of the primer pairs in Table 17. process.

[0215] Item 14. A process according to item 11, 12 or 13 above, comprising selecting a target based on detection of a chromosomal interaction and, preferably, screening modulators of the target to identify therapeutic agents for immunotherapy, said target optionally being a protein.

[0216] Item 15. A therapeutic agent for use in immunotherapy in an individual who has been identified as being in need of the therapeutic agent by the process described in any one of items 1 to 10 above.

[0217] Item 16. The classification or detection comprises specific detection of the ligation products by quantitative PCR (qPCR) using primers capable of amplifying the ligation products and probes that bind to the ligation sites during a PCR reaction, said probes comprising sequences complementary to sequences from each chromosomal region that is clustered in the chromosomal interaction, preferably said probes comprising: an oligonucleotide that specifically binds to the ligation product, and / or a fluorophore covalently attached to the 5' end of the oligonucleotide, and / or a quencher moiety covalently attached to the 3' end of the oligonucleotide, and Optionally, the fluorophore is selected from HEX, Texas Red and FAM; and / or The probe is a nucleic acid sequence having a length of 10 to 40 nucleotide bases, preferably 20 to 30 nucleotide bases. The process according to any one of items 1 to 14 above or the therapeutic agent according to item 15 above,

Claims

1. A process for selecting individuals who will respond to anti-PD-1 or anti-PD-L1 therapy for lung cancer or melanoma, comprising detecting the presence or absence of chromosomal interactions 1, 2, 3, 4 and 5, The individual, the absence of said first chromosomal interaction; the presence of said second chromosomal interaction; the presence of said third chromosomal interaction; the presence of the fourth chromosomal interaction; and The presence of the fifth chromosomal interaction and selecting the patient as responsive to anti-PD-1 or anti-PD-L1 therapy for lung cancer or melanoma based on detection of The detection comprises: (a) bridging individual chromosomal regions that are clustered in chromosomal interactions; (b) severing the crosslinked regions; (c) ligating the cross-linked and cleaved DNA ends to generate a ligated nucleic acid; and (d) detecting the presence or absence of ligated nucleic acid, thereby detecting whether the regions are assembled into a chromosomal interaction. carried out by; and (i) the ligated nucleic acid corresponding to the first chromosomal interaction can be detected by the probe sequence: ACAGTTATTAGAAAAATAAAACATTTGGTCGAACAGCAAAGAGAAGATATTCAACTGCGA (SEQ ID NO:366); (ii) the ligated nucleic acid corresponding to the second chromosomal interaction can be detected by the probe sequence: TTCCATAGATTACTTTTCAAATCATCCTTCGAAGCTGGCGGCTGAGGGCCCGGCGCCAAG (SEQ ID NO:362); (iii) the ligated nucleic acid corresponding to the third chromosomal interaction can be detected by the probe sequence: GTGTCTCGGCCCCCTGGGGCCCCACCCTTCGATTTCCCTGTTGCCGCCGCGTTTGCAAGA (SEQ ID NO:363); (iv) the ligated nucleic acid corresponding to the fourth chromosomal interaction can be detected by the probe sequence: ATCCCAACAAAAGAGAAGAACTTCTCCCTCGATGTTTGGGGGCGGAGGGCTTTGATGAGA (SEQ ID NO:364); (v) the process wherein the ligated nucleic acid corresponding to the fifth chromosomal interaction can be detected by the probe sequence: GTGGCGATGGCGGCCTGCGCGCCGCGCCTCGATGTCTAAGCAACCTGCTAACTGAGGCAG (SEQ ID NO: 365).

2. The process of claim 1, wherein detection of the ligated nucleic acid is by quantitative PCR (qPCR) using primers capable of amplifying the ligated nucleic acid and a probe that binds to the ligation site during a PCR reaction, the probe comprising a sequence complementary to a sequence from each chromosomal region that is clustered in a chromosomal interaction.

3. The probe comprises: - a fluorophore covalently attached to the 5' end of said probe, and / or - a quencher moiety covalently attached to the 3' end of said probe 3. The process of claim 2, comprising:

4. - said fluorophore is selected from HEX, Texas Red and FAM; and / or - said probe comprises a nucleic acid sequence of 10 to 40 nucleotide bases in length, The process of claim 3.

5. The process described in any one of claims 1 to 4, wherein the therapy is with an antibody specific for PD-1 or PD-L1.

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