Individual longitudinal analysis of circulating materials for monitoring and adapting neoantigen cancer vaccines

Abstract

Administering to a subject in need thereof an initial immunogenic composition comprising a plurality of tumor-specific neoantigens, wherein the plurality of tumor-specific neoantigens each correspond to a member of a first set of tumor-associated variants in the subject and do not correspond to any member of a second set of tumor-associated variants in the subject, and quantifying each member of the first set of tumor-associated variants and each member of the second set of tumor-associated variants in a circulating material comprising tumor-associated variants isolated from the subject at each of a plurality of time points, are disclosed.

Description

Technical Field

[0001] Cross - Reference to Related Applications This application claims the benefit of U.S. Provisional Application Nos. 63 / 389,384 and 63 / 380,286, filed on July 15, 2022 and October 20, 2022, respectively, the entire contents of which are incorporated herein by reference.

Background Art

[0002] Cancer is a globally major cause of death, accounting for one - fourth of all deaths. Siegel et al., CA: A Cancer Journal for Clinicians, 68:7 - 30 (2018). In 2018, there were 18.1 million new cancer cases and 9.6 million cancer - related deaths. Bray et al., CA: A Cancer Journal for Clinicians, 68(6):394 - 424. There are several existing standard - of - care cancer therapies, including ablation techniques (e.g., surgical procedures and radiation) and chemical approaches (e.g., chemotherapeutic agents). Unfortunately, such therapies often involve significant risks, harmful side effects, extremely high costs, and uncertain effects.

[0003] Cancer immunotherapy (e.g., cancer vaccines) has emerged as a promising cancer treatment. The goal of cancer immunotherapy is to utilize the immune system to selectively destroy cancer while leaving normal tissues intact. Conventional cancer vaccines typically target tumor - associated antigens. Tumor - associated antigens are usually present in normal tissues but are overexpressed in cancer. However, since these antigens are often present in normal tissues, immune activation may be blocked by immune tolerance. In several clinical trials targeting tumor - associated antigens, a sustained beneficial effect could not be demonstrated compared to standard therapies. Li et al., Ann Oncol., 28(Suppl 12):xii11 - xii17(2017).

[0004] Neoantigens are attractive targets for cancer immunotherapy. Neoantigens are non-self proteins with individual differences. Neoantigens are derived from random somatic mutations in the tumor cell genome and are not expressed on the surface of normal cells. Ibid. Neoantigens are expressed only in tumor cells and thus do not induce central immune tolerance. Therefore, cancer vaccines targeting cancer neoantigens have potential advantages such as a reduction in central immune tolerance and an improvement in the safety profile. Ibid.

[0005] The mutation status of cancer is complex, and tumor mutations are generally specific to individual subjects. Most of the somatic mutations detected by sequencing do not result in effective neoantigens. Only a small fraction of the mutations in tumor DNA or tumor cells are transcribed, translated, and processed into tumor-specific neoantigens with sufficient accuracy to design a potentially effective vaccine. Furthermore, not all neoantigens are immunogenic. In fact, the proportion of T cells that naturally recognize endogenous neoantigens is approximately 1% - 2%. See Karpanen et al., Front Immunol., 8:1718 (2017). Additionally, the costs and time associated with the production of neoantigen vaccines are substantial.

[0006] Combining these challenges, the prediction of neoantigen immunogenicity is not complete. This may result in the overall effect of neoantigen vaccines being lower than desired. Therefore, there is a need to identify neoantigens that are not effective when included in neoantigen vaccines. There is a further need to replace such ineffective neoantigens with effective neoantigens during the process of the treatment vaccination plan for the subject.

Prior Art Documents

Non-Patent Documents

[0007]

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Brief Description of the Drawings

[0008]

Figure 1

Mode for Carrying Out the Invention

[0009] The present disclosure relates to a method for identifying neoantigens that are not effective when included in a neoantigen vaccine. The present disclosure also relates to a method for replacing such ineffective neoantigens with effective neoantigens during the treatment planning process of a subject.

[0010] In some embodiments, the present disclosure relates to a method comprising administering to a subject in need thereof an initial immunogenic composition comprising a plurality of tumor-specific neoantigens, each tumor-specific neoantigen corresponding to a member of a first set of tumor-associated mutations in the subject, and the tumor-specific neoantigens not corresponding to members of a second set of tumor-associated mutations in the subject. The method also includes quantifying each member of the first set of tumor-associated mutations and each member of the second set of tumor-associated mutations in a circulating material isolated from the subject at each of a plurality of time points. The circulating material can be circulating tumor DNA (ctDNA), cell-free circulating DNA (cfDNA), circulating tumor cells (CTC), circulating tumor proteins, extracellular vesicles, or two or more of them.

[0011] The method can further include replacing a tumor-specific neoantigen corresponding to a member of the first set of tumor-associated mutations from the initial immunogenic composition with a substituted tumor-specific neoantigen corresponding to a member of the second set of tumor-associated mutations, resulting in a reformulated immunogenic composition in response to an increase in the amount of a member of the first set of tumor-associated mutations from an earlier time point to a later time point.

[0012] The method can further include administering the reformulated immunogenic composition to the subject.

[0013] The subject can have any type of cancer having cancerous cells with genetic mutations, including, but not limited to, melanoma, breast cancer, sarcoma, ovarian cancer, prostate cancer, kidney cancer, gastric cancer, colon cancer, testicular cancer, head and neck cancer, pancreatic cancer, brain cancer, bone cancer, B-cell lymphoma, acute myeloid leukemia, chronic myeloid leukemia, chronic lymphocytic leukemia, T-cell lymphocytic leukemia, colon cancer, urothelial cancer, or lung cancer.

[0014] The tumor-associated mutations can include at least one mutation specific to the subject.

[0015] The tumor-associated mutations can include at least one tumor hot spot mutation.

[0016] The tumor can be ER+ / HER2-breast cancer, and at least one tumor hot spot mutation can be a gene selected from the group consisting of AKT1, APC, ARID1A, ATM, BRAF, BRCA1, BRCA2, CDH1, CDKN2A, ESR1, GATA3, GNAS, HER2, KRAS, NF1, PIK3CA, PTEN, RB1, SMAD4, and TP53.

[0017] The tumor can be melanoma.

[0018] In some embodiments, each tumor-specific neoantigen corresponding to a member of the first set of tumor-related mutations can have a higher immunogenicity score than any tumor-specific neoantigen corresponding to a member of the second set of tumor-related mutations.

[0019] At least one of the plurality of time points can be before the initial immunogenic composition is administered.

[0020] The initial immunogenic composition can be administered multiple times before replacement of the tumor-specific neoantigen.

[0021] The reformulated immunogenic composition can be administered multiple times after replacement of the tumor-specific neoantigen.

[0022] In some embodiments, the amount of the second set of members of the tumor-related mutations corresponding to the substituted tumor-specific neoantigen can remain the same or increase (i.e., not decrease) from an earlier time point to a later time point.

[0023] Quantifying tumor-related variants can include various methods depending on the circulating material in which the tumor-related variants are quantified. Quantifying tumor-related variants can include sequencing ctDNA using whole exome sequencing (WES), whole genome sequencing (WGS), targeted sequencing, polymerase chain reaction (PCR), or hybridization methods, sequencing cfDNA using quantitative polymerase chain reaction (qPCR) or next-generation sequencing, assaying the ctDNA, cfDNA, or DNA methylation or chromatin content derived from CTCs, performing a mass spectrometry assay or an elution assay on circulating tumor proteins, proteins derived from CTCs, or proteins derived from extracellular vesicles, performing fluorescence-activated cell sorting (FACS) on CTCs, or sequencing nucleic acids or extracellular vesicles derived from CTCs using WES, WGS, targeted sequencing, PCR, qPCR, next-generation sequencing, single-cell RNA sequencing, or hybridization methods.

[0024] One of the plurality of time points can be at least about 1 week, about 2 weeks, about 3 weeks, about 4 weeks, about 5 weeks, about 6 weeks, about 7 weeks, about 8 weeks, about 9 weeks, about 10 weeks, about 11 weeks, or about 12 weeks after administration of the initial immunogenic composition or the reformulated immunogenic composition.

[0025] One of the plurality of time points can be at least about 1 month, about 2 months, about 3 months, about 4 months, about 5 months, about 6 months, about 7 months, about 8 months, about 9 months, about 10 months, about 11 months, or about 12 months after administration of the initial immunogenic composition or the reformulated immunogenic composition.

[0026] One of the plurality of time points can be at least about 1 year, about 2 years, about 3 years, about 4 years, about 5 years, about 6 years, about 7 years, about 8 years, about 9 years, or about 10 years after administration of the initial immunogenic composition or the reformulated immunogenic composition.

[0027] Circulating materials can be isolated from a blood sample, a serum sample, a plasma sample, a urine sample, or a cerebrospinal fluid sample.

[0028] Circulating materials can be isolated from at least about 10 ml of the subject's whole blood.

[0029] Circulating materials can be isolated from at least about 20 ml of the subject's whole blood.

[0030] The method can further include detecting the occurrence at a first time point of at least one tumor-related mutation not included in a first set of tumor-related mutations or a second set of tumor-related mutations.

[0031] The method can also further include adding, at a time point after the first time point, the expressed tumor-related mutations to the second set of tumor-related mutations.

[0032] All publications and patents cited in this disclosure are incorporated by reference in their entirety. To the extent that the materials incorporated by reference conflict with or are inconsistent with this specification, this specification prevails over any such materials. The citation of any reference in this specification does not constitute an admission that such reference is prior art to the present disclosure. When a range of values is recited, embodiments using any specific value within that range are included. Further, references to values within a range include any value within that range. All ranges include their endpoints and are combinable. By the use of the preceding "about", when a value is presented as an approximation, it is understood that a particular value forms another embodiment. References to a particular numerical value include at least that particular value unless otherwise clearly indicated by the context. The use of "or" means "and / or" unless otherwise indicated by the particular context of its use.

[0033] Throughout this specification and the claims, various terms are used that relate to aspects of the specification. Unless otherwise indicated, such terms are to be given their ordinary meaning in the relevant art. Other terms that are specifically defined are to be construed in a manner consistent with the definitions set forth herein. The techniques and procedures described or referenced herein are generally well understood by those skilled in the art and are commonly used using conventional methodologies, such as the widely utilized molecular cloning methods described in Sambrook et al., Molecular Cloning: A Laboratory Manual 4th ed. (2012) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY. Procedures, including the use of commercially available kits and reagents, are generally carried out in accordance with the protocols and conditions defined by the manufacturer, unless otherwise noted.

[0034] As used herein, the singular forms "a", "an", and "the" include the plural forms unless the context clearly dictates otherwise. Terms such as "including", "such as", etc. are intended to convey non-limiting inclusion unless otherwise specified.

[0035] Unless otherwise indicated, the terms "at least", "less than", and "about", or similar terms that precede a series of elements or a range, are to be understood as referring to all elements within the series or range. Those skilled in the art will be able to recognize, or confirm, using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. Such equivalents are intended to be encompassed by the following claims.

[0036] The term "cancer" refers to a physiological state in a subject characterized by uncontrolled growth, immortality, metastatic ability, rapid growth and proliferation rate, and / or certain morphological features of a cell population. In many cases, cancer can be in the form of a tumor or mass, but it can also exist alone within a subject, or circulate in the bloodstream as independent cells such as leukemic or lymphatic cells. The term "cancer" includes all types of cancer and metastases, including malignant blood diseases, solid tumors, sarcomas, carcinomas, and other solid and non-solid tumors. Examples of cancer include, but are not limited to, carcinomas, lymphomas, blastomas, sarcomas, and leukemias. More specific examples of such cancers include squamous cell carcinoma, small cell lung cancer, non-small cell lung cancer, adenocarcinoma of the lung, squamous cell carcinoma of the lung, peritoneal cancer, hepatocellular carcinoma, gastrointestinal cancer, pancreatic cancer, glioma, cervical cancer, ovarian cancer, liver cancer, bladder cancer, hepatoma, breast cancer (e.g., triple-negative breast cancer, hormone receptor-positive breast cancer), osteosarcoma, melanoma, colon cancer, colorectal cancer, endometrial (e.g., serous) cancer or uterine cancer, salivary gland cancer, kidney cancer, liver cancer, prostate cancer, vulvar cancer, thyroid cancer, liver cancer, and various types of head and neck cancers.

[0037] As used herein, the term "subject" refers to any animal, such as any mammal including, but not limited to, humans, non-human primates, rodents, mammals commonly kept as pets (e.g., dogs and cats), livestock (e.g., cows, sheep, goats, pigs, horses, and camels), etc. In some embodiments, the mammal is a mouse. In some embodiments, the mammal is a human.

[0038] As used herein, the term "tumor cell" refers to any cell that is a cancer cell or is derived from a cancer cell. The term "tumor cell" can also refer to cells that exhibit cancer-like properties, such as uncontrolled replication, resistance to anti-proliferative signals, the ability to metastasize, and loss of the ability to undergo programmed cell death.

[0039] Additional explanations of the method and guidelines for the implementation of the method are provided herein.

[0040] A. Tumor-related mutations and corresponding tumor-specific neoantigens Tumor-derived DNA generally exhibits one or more mutations compared to DNA from normal or healthy tissues. Some of these tumor-related mutations are relatively prevalent in the patient population. Such relatively prevalent tumor-related mutations can be referred to as tumor hot spot mutations. The gene(s) in which tumor hot spot mutations occur depend on the specific cancer. For example, in ER+ / HER2-breast cancer, tumor hot spot mutations can be genes selected from the group consisting of AKT1, APC, ARID1A, ATM, BRAF, BRCA1, BRCA2, CDH1, CDKN2A, ESR1, GATA3, GNAS, HER2, KRAS, NF1, PIK3CA, PTEN, RB1, SMAD4, and TP53. Other tumor hot spot mutations and the genes in which they occur are known in other cancers such as melanoma.

[0041] In some embodiments, the tumor-related mutation includes at least one tumor hot spot mutation.

[0042] Other tumor-related mutations can be subject-specific. These specific tumor-related mutations cannot be predicted in advance but can only be identified from a workflow that includes sequencing healthy and tumor nucleic acid sequences, such as whole exome sequencing (WES) or whole genome sequencing (WGS) of DNA from healthy and tumor tissues, single cell RNA (scRNA) sequencing of healthy or tumor cells, or other techniques. Next, the normal and tumor sequences can be aligned and compared, and the differences between the two aligned sequences are identified as tumor-related mutations.

[0043] In WES and scRNA sequencing, the sequenced data is from nucleic acid sequences that are transcribed and translated into peptides. The data from WGS includes nucleic acid sequences that are transcribed and translated into peptides. Thus, any tumor-related mutations found by WES or scRNA sequencing of tumor nucleic acids will, upon translation, result in peptides that are expected to be present in the tumor and not present in healthy tissue. Such peptides can be considered tumor-specific neoantigens. Tumor-specific neoantigens can be considered to correspond to tumor-related mutations. Similarly, at least some of the tumor-related mutations found by WGS sequencing of tumor DNA have corresponding tumor-specific neoantigens.

[0044] Figure 1 shows a conceptual model for illustration. In the upper left, WES, WGS, or scRNA sequencing (RNA-seq) is performed on normal and healthy tissues. The sequenced data is aligned, showing three tumor-related mutations: CATTGG→CCTTGG, CGATTT→CGATGT, and ACAGAG→ACAGCG. Each of these three tumor-related mutations has a corresponding tumor-specific neoantigen as follows: Peptide 1 containing ProTrp, Peptide 2 containing ArgCys, and Peptide 3 containing ThrAla. In reality, more tumor-related mutations and longer tumor-specific neoantigen sequences will be found.

[0045] When identifying subject-specific tumor-related mutations, two factors need to be considered. One is that subclonal mutations can occur after the initial determination, which can enable the tumor to evolve resistance to immunogenic compositions that do not target tumor-specific neoantigens corresponding to such subclonal mutations. Second, clonal hematopoiesis of indeterminate potential (CHIP) is a certain age-related accumulation of mutations in white blood cells. This latter factor can be at least partially alleviated by performing additional sequence analysis of white blood cells to exclude CHIP-related variants.

[0046] In some embodiments, the tumor-related mutations include at least one mutation specific to the subject.

[0047] B. Immunogenic composition Once the polypeptide sequence data of one or more tumor-specific neoantigens is obtained, a numerical probability score can be generated to predict whether one or more tumor-specific neoantigens are immunogenic (e.g., induce an immune response in the subject). For example, the polypeptide sequence data and MHC molecules can be input into a machine learning platform (i.e., the model(s)). The machine learning platform can generate a numerical probability score.

[0048] MHC molecules transport and present peptides on the cell surface. MHC molecules are classified as class I and class II MHC molecules. MHC class I molecules are present on the surface of almost all cells of the body, including most tumor cells. MHC class I proteins usually contain many endogenous proteins or antigens derived from pathogens present inside the cell, which are then presented to cytotoxic T lymphocytes (i.e., CD8+). MHC class I molecules can include HLA-A, HLA-B, or HLA-C. Class II MHC molecules are present only on dendritic cells, B lymphocytes, macrophages, and other antigen-presenting cells. They mainly present peptides processed from an external antigen source, i.e., outside the cell, to T helper (Th) cells (i.e., CD4+). MHC class II molecules can include HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DRA, and HLA-DRB1. In some cases, MHC class II molecules can also be expressed on cancer cells.

[0049] MHC class I molecules and / or MHC class II molecules can be input into a machine learning platform. Usually, either an MHC class I molecule or an MHC class II molecule is input into the machine learning platform. In some embodiments, an MHC class I molecule is input into the machine learning platform. In some embodiments, an MHC class II molecule is input into the machine learning platform. In some embodiments, an MHC class I machine learning platform can be trained with MHC class I training data. In some embodiments, an MHC class II machine learning platform can be trained with MHC class II training data. In some embodiments, the same machine learning platform can be trained with both MHC class I and class II training data. In some embodiments, the machine learning platform can include an MHC class I model and an MHC class II model.

[0050] MHC class I molecules bind to short peptides. MHC class I molecules can generally accommodate peptides that are about 8 to about 10 amino acids in length. In embodiments, the sequence data encoding one or more tumor-specific neoantigens are short peptides that are about 8 to about 10 amino acids in length. MHC class II molecules bind to longer peptides. MHC class II can generally accommodate peptides that are about 13 to about 25 amino acids in length. In embodiments, the sequence data encoding one or more tumor-specific neoantigens are long peptides that are about 13 to 25 amino acids in length.

[0051] Array data encoding one or more tumor-specific neoantigens can be about 5 amino acids in length, about 6 amino acids in length, about 7 amino acids in length, about 8 amino acids in length, about 9 amino acids in length, about 10 amino acids in length, about 11 amino acids in length, about 12 amino acids in length, about 13 amino acids in length, about 14 amino acids in length, about 15 amino acids in length, about 16 amino acids in length, about 17 amino acids in length, about 18 amino acids in length, about 19 amino acids in length, about 20 amino acids in length, about 21 amino acids in length, about 22 amino acids in length, about 23 amino acids in length, about 24 amino acids in length, about 25 amino acids in length, about 26 amino acids in length, about 27 amino acids in length, about 28 amino acids in length, about 29 amino acids in length, or about 30 amino acids in length.

[0052] Immunogenic tumor-specific neoantigens are not expressed in normal tissues. They can be presented by antigen-presenting cells to CD4+ T cells and CD8+ T cells to generate an immune response. In embodiments, the immune response in a subject induced by one or more tumor-specific neoantigens includes the presentation of one or more tumor-specific neoantigens on the surface of tumor cells. More specifically, the immune response in a subject induced by one or more tumor-specific neoantigens includes the presentation of one or more tumor-specific neoantigens by one or more MHC molecules on tumor cells. The immune response induced by one or more tumor-specific neoantigens is expected to be a T cell-mediated response. The immune response in a subject induced by one or more tumor-specific neoantigens may be accompanied by one or more tumor-specific neoantigens that can be presented to T cells by antigen-presenting cells such as dendritic cells. In one aspect, one or more tumor-specific neoantigens can activate CD8+ T cells and / or CD4+ T cells.

[0053] In an embodiment, the machine learning platform can predict the likelihood that one or more tumor-specific neoantigens activate CD8+ T cells. In an embodiment, the machine learning platform can predict the likelihood that one or more tumor-specific neoantigens activate CD4+ T cells. In some cases, the machine learning platform can predict the antibody titers that one or more tumor-specific neoantigens can induce. In other examples, the machine learning platform can predict the frequency of CD8+ activation by one or more tumor-specific neoantigens.

[0054] The machine learning platform can include a model trained with training data. The training data can be obtained from a series of different subjects. The training data can include data from healthy subjects and subjects with cancer. The training data can include various data that can be used to generate a probability score indicating whether one or more tumor-specific neoantigens induce an immune response in a subject. Exemplary training data can include data representing nucleotide or polypeptide sequences derived from normal tissues and / or cells, data representing nucleotide or polypeptide sequences derived from tumor tissues, data representing MHC peptide sequences derived from normal and tumor tissues, peptide-MHC binding affinity measurements, or combinations thereof. The training data can further include mass spectrometry data, DNA sequencing data, RNA sequencing data, clinical data from healthy and cancerous subjects, cytokine profiling data, T cell cytotoxicity assay data, peptide-MHC monomer or multimer data, and single allele cell lines engineered to express a given MHC allele and then exposed to synthetic proteins, normal and tumor human cell lines, fresh and frozen primary samples, and proteomics data related to T cell assays.

[0055] The machine learning platform can be a supervised learning platform, an unsupervised learning platform, or a semi-supervised learning platform. The machine learning platform can use an array-based approach to generate a numerical probability that one or more tumor-specific neoantigens can induce an immune response (e.g., induce a high or low antibody response or a CD8+ response). Array-based prediction can include supervised machine learning modules such as artificial neural networks (e.g., deep or otherwise), support vector machines, k-nearest neighbor methods, logistic multiple network constrained regression (LogMiNeR), regression trees, random forests, adaBoost, XGBoost, or hidden Markov models. These platforms require a training dataset that includes known MHC-binding peptides.

[0056] To predict whether tumor-specific neoantigens can be presented on MHC molecules and induce an immune response, many prediction programs have been adopted. Exemplary prediction programs include, for example, HLAminer (Warren et al., Genome Med., 4:95 (2012); HLA type predicted by correctly judging the assembly of shotgun sequence data and comparing it with a reference allele sequence database), The Ensembl Variant Effect Predictor (McLaren et al., Genome Biol., 17:122 (2016)), NetMHCpan (Andreatta et al., Bioinformatics, 32:511-517 (2016); sequence of a comparative method based on an artificial neural network and prediction of the affinity of a peptide-MHC class I molecule), UCSC browser (Kent et al., Genome Res., 12:996-1006 (2002)), CloudNeo pipeline (Bais et al., Bioinformatics, 33:3110-2 (2017)), OptiType (Szolek et al., Bioinformatics, 30:3310-3316 (2014)), ATHLATES (Liu C et al., Nucleic Acids Res. 41:e142 (2013)), pVAC-Seq (Hundal et al., Genome Med. 8:11 (2016)), MuPeXI (Bjerregaard et al., Cancer Immunol. Immunother., 66:1123-30 (2017)), Strelka (Saunders et al., Bioinformatics, 28:1811-7 (2012)), Strelka2 (Kim et al., Nat Methods. 15:591-4 (2018)), VarScan2 (Koboldt et al., Genome Res., 22:568-76 (2012)), SomaticSeq (Fang L et al., Genome Biol., 16:197 (2015)), SMMPMBEC (Kim et al., BMC Bioinformatics, 10:394(2009)), NeoPredPipe(Schenck RO, BMC Bioinformatics, 20:264(2019)), Weka(Witten et al., Data mining: practical machine - learning tools and techniques. 4. th ed. Elsevier, ISBN: 97801280435578(ebook)(2017)), or Orange(Demsar et al., Orange: Data Mining Toolbox in Python., J. Mach. Learn. Res., 14:2349 - 2353(2013)). To generate a numerical probability score indicating whether a neoantigen induces an immune response, any known prediction program may be used as a machine - learning platform.

[0057] Depending on the machine - learning platform employed, additional filters may be applied to prioritize tumor - specific neoantigen candidates, including exclusion of virtual (Riken) proteins, i.e., use of an antigen - processing algorithm to exclude epitopes that are unlikely to be produced proteolytically by constitutive or immunoproteasomes, and prioritization of neoantigens if they have a higher predicted binding affinity than the corresponding wild - type sequence.

[0058] The numerical probability score may be a number between 0 and 1. In embodiments, the numerical probability score may be a number of 0, 0.0001, 0.0002, 0.0003, 0.0004, 0.0005, 0.0006, 0.0007, 0.0008, 0.0009, 0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90, or 1. A tumor-specific neoantigen having a high numerical probability score compared to a low numerical probability score indicates that the tumor-specific neoantigen induces a higher immune response in a subject and thus is likely to be a suitable candidate for an immunogenic composition. For example, a tumor-specific neoantigen having a numerical probability score of 1 is more likely to induce a higher immune response in a subject than a tumor-specific neoantigen having a numerical probability score of 0.05. Similarly, a tumor-specific neoantigen having a numerical probability score of 0.5 is more likely to induce a higher immune response in a subject than a tumor-specific neoantigen having a numerical probability score of 0.1.

[0059] A higher numerical probability score than a lower numerical probability score is preferred. Preferably, a tumor-specific neoantigen having a numerical probability score of at least 0.80, 0.81, 0.82, 0.83, 0.84, 0.85, 0.86, 0.87, 0.88, 0.89, 0.90, 0.95, 0.96, 0.97, 0.98, 0.99, or 1 indicates that an immune response is likely to be induced in a subject.

[0060] A higher numerical probability score is preferred, but even a lower numerical probability score can indicate that a tumor-specific neoantigen is likely to be a suitable candidate because the tumor-specific neoantigen can induce a sufficient immune response.

[0061] For example, the machine learning platform can also predict the likelihood that one or more tumor-specific neoantigens will be presented by MHC molecules on tumor cells. The machine learning platform can predict the likelihood that one or more tumor-specific neoantigens will be presented by MHC class I molecules or MHC class II molecules.

[0062] A method for selecting one or more tumor-specific neoantigens can further include the step of in silico measuring the affinity of one or more tumor-specific neoantigens that bind to MHC molecules in a subject. Tumor-specific neoantigens with a binding affinity to MHC molecules of less than about 1000 nM indicate that one or more tumor-specific neoantigens may be suitable for an immunogenic composition. Tumor-specific neoantigens with a binding affinity to MHC molecules of less than about 500 nM, less than about 400 nM, less than about 300 nM, less than about 200 nM, less than about 100 nM, or less than about 50 nM may indicate that one or more tumor-specific neoantigens may be suitable for an immunogenic composition. The affinity of one or more tumor-specific neoantigens that bind to MHC molecules in a subject can predict the immunogenicity of the tumor-specific neoantigen. Alternatively, the median affinity can be an effective method for predicting the immunogenicity of tumor-specific neoantigens. The median affinity can be calculated using epitope prediction algorithms such as NetMHCpan, artificial neural network (ANN), stabilized matrix method (SMM), and SMMPMBEC.

[0063] The RNA expression of one or more tumor-specific neoantigens can also be quantified. Quantifying the RNA expression of one or more tumor-specific neoantigens can identify one or more neoantigens that induce an immune response in a subject. There are various methods for measuring RNA expression. Known techniques capable of measuring RNA expression include RNA-seq, as well as in situ hybridization (e.g., FISH), Northern blot, DNA microarray, tiling array, and quantitative polymerase chain reaction (qPCR). Other known techniques in the art can be used to quantify RNA expression. The RNA can be messenger RNA (mRNA), small interfering RNA (siRNA), microRNA (miRNA), circular RNA (circRNA), transfer RNA (tRNA), ribosomal RNA (rRNA), small nuclear RNA (snRNA), Piwi-interacting RNA (piRNA), long non-coding RNA (long ncRNA), subgenomic RNA (sgRNA), RNA derived from an integrated or non-integrated virus, or any other RNA. In one embodiment, mRNA expression is measured.

[0064] This technique can further reduce the likelihood of selecting tumor-specific neoantigens that can induce an autoimmune response in normal tissue. Tumor-specific neoantigens having sequences similar to normal antigens are expected to be able to induce an autoimmune response in normal tissue. For example, tumor-specific neoantigens that are at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99% similar to normal antigens can induce an autoimmune response. Tumor-specific neoantigens predicted to induce an autoimmune response are not prioritized in immunogenic compositions. Tumor-specific neoantigens predicted to induce an autoimmune response are usually not selected for immunogenic compositions. The method can further include measuring the ability of one or more tumor-specific neoantigens to induce immune tolerance. Tumor-specific neoantigens predicted to induce immune tolerance are not prioritized in immunogenic compositions.

[0065] Tumor subclone profiles can be used to inform the selection of tumor-specific neoantigens for immunogenic compositions. For example, for any tumor subclones identified prior to the formulation of an initial immunogenic composition, it may be considered to include at least one tumor-specific neoantigen associated with each subclone in the initial immunogenic composition.

[0066] An immunogenicity score can be determined for each tumor-specific neoantigen based on one or more of a numerical probability score, the likelihood of CD8+ T cell activation, predicted antibody titers, one or more additional filters, the likelihood of presentation by MHC class I or MHC class II molecules, the affinity of binding to MHC molecules, RNA quantification, or the likelihood of an autoimmune response.

[0067] Considering the immunogenicity scores of each tumor-specific neoantigen, one or more tumor-specific neoantigens can be selected for formulation of a subject-specific initial immunogenic composition. The selection can be for any tumor-specific neoantigen whose immunogenicity score is above a desired value, or for the n highest-ranked tumor-specific neoantigens ranked by immunogenicity score. In some embodiments, each tumor-specific neoantigen corresponding to a member of the first set of tumor-associated mutations has a higher immunogenicity score than any tumor-specific neoantigen corresponding to a member of the second set of tumor-associated mutations.

[0068] In embodiments, at least about 1, at least about 2, at least about 3, at least about 4, at least about 5, at least about 6, at least about 7, at least about 8, at least about 9, at least about 10, at least about 11, at least about 12, at least about 13, at least about 14, at least about 15, at least about 16, at least about 17, at least about 18, at least about 19, at least about 20, at least about 25, at least about 30, at least about 35, at least about 40, at least about 50 or more tumor-specific neoantigens are selected for the initial immunogenic composition. Typically, at least about 10 tumor-specific neoantigens are selected. In other examples, at least about 20 tumor-specific neoantigens are selected.

[0069] The immunogenic composition can further include a natural or synthetic antigen. The natural or synthetic antigen can enhance the immune response. Exemplary natural or synthetic antigens include, but are not limited to, the pan-DR epitope (PADRE) and the tetanus toxin antigen.

[0070] The immunogenic composition can be of any type, for example, a synthetic long-chain peptide, RNA, DNA, cell, dendritic cell, nucleotide sequence, polypeptide sequence, plasmid, or vector.

[0071] Tumor-specific neoantigens can also be included in virus vector-based vaccine platforms such as vaccinia, fowlpox, self-replicating alphavirus, Maraba virus, adenovirus (see, e.g., Tatsis et al., Molecular Therapy, 10:616-629 (2004)), or, without limitation, lentivirus including second, third, or hybrid second / third generation lentiviruses and any generation of recombinant lentiviruses designed to target specific cell types or receptors (see, e.g., Hu et al., Immunol Rev. 239(1):45-61 (2011), Sakma et al, Biochem J., 443(3):603-18 (2012)). Depending on the packaging capacity of the virus vector-based vaccine platforms described above, this approach can deliver one or more nucleotide sequences encoding one or more tumor-specific neoantigen peptides. The sequences may be adjacent non-mutated sequences, may be separated by linkers, or may be preceded by one or more sequences targeting intracellular compartments (see, e.g., Gros et al., Nat Med., 22(4):433-8 (2016), Stronen et al., Science., 352(6291):1337-1341 (2016), Lu et al., Clin Cancer Res., 20(13):3401-3410 (2014)). Upon introduction into the host, the infected cells express one or more tumor-specific neoantigens, thereby inducing a host immune (e.g., CD8+ or CD4+) response to one or more tumor-specific neoantigens. Vaccinia vectors and methods useful in immunization protocols are described, for example, in U.S. Patent No. 4,722,848. Another vector is BCG (Bacillus Calmette Guerin). The BCG vector is described in Stover et al. (Nature 351:456-460 (1991)). A wide variety of other vaccine vectors useful for the therapeutic administration or immunization of neoantigens may also be used, as will be apparent to those skilled in the art from the description herein.

[0072] An immunogenic composition can contain individualized components according to the individual needs of a particular subject.

[0073] The immunogenic compositions described herein can further include an adjuvant. An adjuvant is any substance that, when mixed into an immunogenic composition, enhances, or otherwise augments and / or potentiates, the immune response to a tumor-specific neoantigen, but does not elicit an immune response to the tumor-specific neoantigen when the substance is administered alone. The adjuvant preferably elicits an immune response to the neoantigen and does not cause an allergic or other adverse reaction. It is contemplated herein that the immunogenic composition can be administered together, simultaneously, or after the administration of the immunogenic composition.

[0074] Adjuvants can enhance the immune response by several mechanisms, including, for example, lymphocyte mobilization, stimulation of B cells and / or T cells, and stimulation of macrophages. When the immunogenic composition of the present invention contains an adjuvant or is administered together with one or more adjuvants, adjuvants that can be used include, but are not limited to, inorganic salt adjuvants or inorganic salt gel adjuvants, particulate adjuvants, particulate adjuvants, mucosal adjuvants, and immunostimulatory adjuvants. Examples of adjuvants include, but are not limited to, aluminum salts (alum) (such as aluminum hydroxide, aluminum phosphate, and aluminum sulfate), 3-de-O-acylated monophosphoryl lipid A (MPL) (see GB2220211), MF59 (Novartis), AS03 (Glaxo SmithKline), AS04 (Glaxo SmithKline), polysorbate 80 (Tween® 80, ICL Americas, Inc.), imidazopyridine compounds (see International Application No. PCT / US2007 / 064857 published as International Publication No. WO2007 / 109812), imidazoquinoxaline compounds (see International Application No. PCT / US2007 / 064858 published as International Publication No. WO2007 / 109813), and saponins such as QS21 (Kensil et al, in Vaccine Design: The Subunit and Adjuvant Approach (eds. Powell & Newman, Plenum Press, NY, 1995), see U.S. Patent No. 5,057,540). In some embodiments, the adjuvant is Freund's adjuvant (complete or incomplete). Other adjuvants are oil-in-water emulsions (such as squalene or peanut oil) and are optionally used in combination with an immunostimulant, for example, monophosphoryl lipid A (see Stoute et al, N. Engl. J. Med. 336, 86-91 (1997)).

[0075] CpG immunostimulatory oligonucleotides have also been reported to enhance the effect of adjuvants in vaccine settings. Other TLR-binding molecules such as RNA that binds to TLR7, TLR8, and / or TLR9 can also be used.

[0076] Other examples of useful adjuvants include chemically modified CpGs (e.g., CpR, Idera), poly(I:C) (e.g., polyi:CI2U), polyICLC, non-CpG bacterial DNA or RNA, and immunomodulatory small molecules and antibodies such as cyclophosphamide, sunitinib, bevacizumab, celecoxib, NCX-4016, sildenafil, tadalafil, vardenafil, sorafenib, XL-999, CP-547632, pazopanib, ZD2171, AZD2171, ipilimumab, tremelimumab, and SC58175, but are not limited thereto. In an embodiment, polyICLC is an adjuvant.

[0077] The immunogenic composition may contain one or more of the tumor-specific neoantigens described herein alone or together with a pharmaceutically acceptable carrier. A suspension or dispersion of one or more tumor-specific neoantigens, particularly an isotonic aqueous suspension, dispersion, or amphiphilic solvent, can be used. The immunogenic composition may be sterilized and / or may contain excipients such as preservatives, stabilizers, wetting agents and / or emulsifiers, solubilizing agents, salts and / or buffers for adjusting osmotic pressure, and is prepared by methods known per se, for example, by conventional dispersion and suspension processes. In certain embodiments, such a dispersion or suspension may contain a viscosity modifier. The suspension or dispersion can be maintained at a temperature of about 2°C to 8°C or preferentially frozen for longer-term storage and then thawed immediately before use. For injection, the vaccine or immunogenic preparation can preferably be formulated in an aqueous solution in a physiologically compatible buffer such as Hank's solution, Ringer's solution, or saline buffer. This solution may contain formulation agents such as suspending agents, stabilizers, and / or dispersing agents.

[0078] In certain embodiments, the compositions described herein further comprise a preservative, such as the mercury derivative thimerosal. In certain embodiments, the pharmaceutical compositions described herein comprise 0.001% to 0.01% thimerosal. In other embodiments, the pharmaceutical compositions described herein are preservative-free.

[0079] Excipients may exist independently of the adjuvant. The function of an excipient may be, for example, to increase the molecular weight of the immunogenic composition, increase activity or immunogenicity, confer stability, increase biological activity, or extend the serum half-life. Excipients may also be used to assist in the presentation of one or more tumor-specific neoantigens to T cells (e.g., CD4+ T cells or CD8+ T cells). Excipients can be, but are not limited to, carrier proteins such as keyhole limpet hemocyanin, serum proteins such as transferrin, bovine serum albumin, human serum albumin, thyroglobulin or ovalbumin, immunoglobulins, or hormones or palmitic acid such as insulin. In the case of human immunization, the carrier is generally a physiologically acceptable carrier that is acceptable and safe for humans. Alternatively, the carrier can be dextran, such as sepharose.

[0080] Cytotoxic T cells recognize antigens not in the form of intact foreign antigens themselves, but rather in the form of peptides bound to MHC molecules. The MHC molecules themselves are located on the cell surface of antigen-presenting cells. Thus, activation of cytotoxic T cells is possible when a trimeric complex of peptide antigen, MHC molecule, and antigen-presenting cell (APC) is present. Instead of using only one or more tumor-specific antigens for activation of cytotoxic T cells, the addition of additional APCs having respective MHC molecules can enhance the immune response. Thus, in some embodiments, the immunogenic composition further contains at least one APC.

[0081] The immunogenic composition may contain an acceptable carrier (e.g., an aqueous carrier). For example, various aqueous carriers such as water, buffered water, 0.9% saline, 0.3% glycine, hyaluronic acid, etc. can be used. These compositions can be sterilized by conventional, well-known sterilization techniques or may be sterile filtered. The resulting aqueous solution can be packaged for use as is or can be lyophilized, and the lyophilized formulation is combined with a sterile solution prior to administration. The composition may contain pharmaceutically acceptable auxiliary substances such as pH adjusters and buffers, tonicity agents, wetting agents, etc., for example, sodium acetate, sodium lactate, sodium chloride, potassium chloride, calcium chloride, sorbitan monolaurate, triethanolamine oleate, etc., as required to approximate physiological conditions.

[0082] Neoantigens can also be administered via liposomes that target the neoantigen to specific cell tissues such as lymphoid tissue. Liposomes are also useful for extending the half-life. Liposomes include emulsions, foams, micelles, insoluble monolayers, liquid crystals, phospholipid dispersions, lamellar layers, etc. In these formulations, the neoantigen to be delivered is incorporated as part of the liposome, alone or in combination with a molecule that binds to a receptor that spreads among lymphocytes, such as a monoclonal antibody that binds to the CD45 antigen, or together with other therapeutic or immunogenic compositions. Therefore, liposomes filled with the desired neoantigen can be directed to the site of lymphocytes, and then the liposomes deliver the selected immunogenic composition. Liposomes can generally be formed from standard vesicle-forming lipids that include neutral and negatively charged phospholipids and sterols such as cholesterol. The choice of lipid is generally guided by considerations such as, for example, liposome size, acid lability, and stability of the liposome in the bloodstream. To prepare liposomes, various methods described, for example, in Szoka et al., Annu. Rev. Biophys. Bioeng. 9;467(1980), U.S. Patent Nos. 4,235,871, 4,501,728, 4,501,728, 4,837,028, and 5,019,369 can be utilized.

[0083] In the case of targeting immune cells, the ligand incorporated into the liposome can include, for example, an antibody or a fragment thereof specific for a cell surface determinant of a desired immune system cell. The liposome suspension can be administered intravenously, locally, topically, etc. at different doses, depending inter alia on the mode of administration, the peptide to be delivered, and the stage of the disease being treated.

[0084] As an alternative method for targeting immune cells, components of the immunogenic composition, such as an antigen (i.e., a tumor-specific neoantigen), a ligand, or an adjuvant (e.g., TLR), can be incorporated into poly(lactic-co-glycolic) microspheres. The poly(lactic-co-glycolic) microspheres can encapsulate the components of the immunogenic composition as an endosomal delivery device.

[0085] For therapeutic or immunization purposes, the nucleic acids encoding the tumor-specific neoantigens described herein can also be administered to a patient. Several methods are advantageously used to deliver the nucleic acids to the patient. For example, the nucleic acids can be delivered directly as "naked DNA". This approach is described, for example, in Wolff et al., Science 247:1465-1468 (1990), as well as in U.S. Pat. Nos. 5,580,859 and 5,589,466. The nucleic acids can also be administered using ballistic delivery as described, for example, in U.S. Pat. No. 5,204,253. Particles composed of only DNA can be administered. Alternatively, the DNA can be attached to particles such as gold particles. Approaches for delivering nucleic acid sequences can include viral vectors, mRNA vectors, and DNA vectors, with or without electroporation. The nucleic acids can also be delivered by forming a complex with a cationic compound such as a cationic lipid.

[0086] The immunogenic compositions provided herein can be administered to a subject by a variety of routes including, but not limited to, oral, intradermal, intratumoral, intramuscular, intraperitoneal, intravenous, topical, subcutaneous, transdermal, intranasal, and inhalation routes, and can also be administered via scarification (e.g., scratching the upper layer of the skin using a bifurcated needle). The immunogenic compositions can be administered to the tumor site to induce a local immune response against the tumor.

[0087] The dosage of one or more tumor-specific neoantigens can depend on the type of composition, as well as the age, weight, body surface area, individual condition, individual pharmacokinetic data, and mode of administration of the subject.

[0088] Also disclosed herein is a method of manufacturing an immunogenic composition comprising one or more tumor-specific neoantigens selected by performing the steps of the methods disclosed herein. The immunogenic compositions described herein can be manufactured using methods known in the art. For example, methods of generating the tumor-specific neoantigens or vectors disclosed herein (e.g., vectors comprising at least one sequence encoding one or more tumor-specific neoantigens) can include culturing host cells under conditions suitable for expressing the neoantigen or vector, wherein the host cells comprise at least one polynucleotide encoding the neoantigen or vector and purifying the neoantigen or vector. Standard purification methods include chromatographic techniques, electrophoretic techniques, immunological techniques, precipitation techniques, dialysis techniques, filtration techniques, concentration techniques, and chromatographic fractionation techniques.

[0089] The host cells can include Chinese hamster ovary (CHO) cells, NS0 cells, yeast, or HEK293 cells. The host cells can be transformed with one or more polynucleotides comprising at least one nucleic acid sequence encoding one or more tumor-specific neoantigens or vectors disclosed herein. In certain embodiments, the isolated polynucleotide can be cDNA.

[0090] When selecting tumor-specific neoantigens for an initial immunogenic composition, tumor-associated mutations can be divided into multiple sets, such as two sets. The first set includes the tumor-associated mutations corresponding to the selected tumor-specific neoantigens. The second set includes tumor-associated mutations that do not correspond to any of the selected tumor-specific neoantigens.

[0091] Figure 1 provides further assistance for visualization. In the upper right corner, the immunogenicity of three peptides of the virtual model is recorded and ranked as follows: Peptide 1 containing ProTrp, immunogenicity score 0.8; Peptide 2 containing ArgCys, immunogenicity score 0.6; Peptide 3 containing ThrAla, immunogenicity score 0.5. As shown in the lower left corner, the initial immunogenic composition is selected to include Peptide 1 and Peptide 2, which are the two top-ranked tumor-specific neoantigens. Peptide 3 is excluded from the initial immunogenic composition.

[0092] C. Administration of the immunogenic composition to a subject in need thereof The above immunogenic composition, which contains tumor-specific neoantigens corresponding to the first set of tumor-associated mutations and not corresponding to the second set of tumor-associated mutations, can be administered to a subject in need thereof, for example, a subject suffering from cancer or at risk of developing cancer.

[0093] The cancer can be any solid tumor or any hematological tumor. The tumor can be a primary tumor or a metastasis. Examples of solid tumors include, but are not limited to, breast cancer tumors, ovarian cancer tumors, prostate cancer tumors, lung cancer tumors, kidney cancer tumors, stomach cancer tumors, testicular cancer tumors, head and neck cancer tumors, pancreatic cancer tumors, brain cancer tumors, and melanoma tumors. Examples of hematological tumors include, but are not limited to, tumors derived from lymphoma (e.g., B-cell lymphoma) and leukemia (e.g., acute myeloid leukemia, chronic myeloid leukemia, chronic lymphocytic leukemia, and T-cell lymphocytic leukemia).

[0094] The methods disclosed herein can be used for any suitable cancerous tumor, including malignant blood diseases, solid tumors, sarcomas, carcinomas, and other solid and non-solid tumors. Exemplary suitable cancers include, for example, acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), adrenocortical carcinoma, anal cancer, appendiceal cancer, astrocytoma, basal cell carcinoma, brain tumor, bile duct cancer, bladder cancer, bone cancer, breast cancer, bronchial tumor, cancer of unknown primary origin, cardiac tumor, cervical cancer, chordoma, colon cancer, colorectal cancer, craniopharyngioma, ductal carcinoma in situ, fetal tumor, endometrial cancer, epithelioma, esophageal cancer, nasal neuroblastoma, fibrous histiocytoma, Ewing sarcoma, eye cancer, germ cell tumor, gallbladder cancer, gastric cancer, gastrointestinal carcinoid tumor, gastrointestinal stromal tumor, gestational trophoblastic disease, glioma, head and neck cancer, hepatocellular carcinoma, histiocytosis, Hodgkin lymphoma, hypopharyngeal cancer, intraocular melanoma, islet cell tumor, Kaposi sarcoma, kidney cancer, Langerhans cell histiocytosis, laryngeal cancer, lip and oral cavity cancer, liver cancer, lobular carcinoma in situ, lung cancer, macroglobulinemia, malignant fibrous histiocytoma, melanoma, Merkel cell carcinoma, mesothelioma, metastatic squamous neck cancer of unknown primary origin, midline carcinoma associated with the NUT gene, oral cancer, multiple endocrine neoplasia syndrome, multiple myeloma, mycosis fungoides, myelodysplastic syndrome, myelodysplastic / myeloproliferative neoplasm, nasal and paranasal cancer, nasopharyngeal cancer, neuroblastoma, non-small cell lung cancer, oropharyngeal cancer, osteosarcoma, ovarian cancer, pancreatic cancer, papillomatosis, paraganglioma, parathyroid cancer, penile cancer, pharyngeal cancer, pheochromocytoma, pituitary tumor, pleuropulmonary blastoma, primary central nervous system lymphoma, prostate cancer, rectal cancer, renal cell carcinoma, renal pelvis and ureter cancer, retinoblastoma, rhabdoid tumor, salivary gland cancer, Sézary syndrome, skin cancer, small cell lung cancer, small intestine cancer, soft tissue sarcoma, spinal cord tumor, stomach cancer, T cell lymphoma, teratoid tumor, testicular cancer, throat cancer, thymoma and thymic carcinoma, thyroid cancer, urethral cancer, uterine cancer, vaginal cancer, vulvar cancer, and Wilms tumor. In one aspect, the cancer is melanoma, breast cancer, ovarian cancer, prostate cancer, kidney cancer, gastric cancer, colon cancer, testicular cancer, head and neck cancer, pancreatic cancer, brain cancer, B cell lymphoma, acute myeloid leukemia, chronic myeloid leukemia, chronic lymphocytic leukemia, T cell lymphocytic leukemia, bladder cancer, or lung cancer. Melanoma is of particular interest. Breast cancer, lung cancer, and bladder cancer are also of particular interest.

[0095] An immunogenic composition stimulates the immune system of a subject, particularly the response of specific CD8+ T cells or CD4+ T cells. Interferon gamma produced by CD8+ cells and T helper CD4+ cells regulates the expression of PD-L1. The expression of PD-L1 in tumor cells is upregulated when attacked by T cells. Thus, a tumor vaccine may induce the production of specific T cells and at the same time upregulate the expression of PD-L1, which may limit the effectiveness of the immunogenic composition. Furthermore, during the activation of the immune system, the expression of the T cell surface reporter CTLA-4 increases accordingly, and this CTLA-4 binds to the ligands B7-1 / B7-2 on antigen-presenting cells and exerts an immunosuppressive effect. Thus, in some cases, a subject may be further administered an anti-immunosuppressant or immunostimulant such as a checkpoint inhibitor. Checkpoint inhibitors may include, but are not limited to, anti-CTL4-A antibodies, anti-PD-1 antibodies, and anti-PD-L1 antibodies. These checkpoint inhibitors bind to T cell immune checkpoint proteins to remove the inhibition of T cell function by tumor cells. Blocking CTLA-4 or PD-L1 with an antibody can enhance the immune response against a patient's cancer cells. CTLA-4 has been shown to be effective when following a vaccination protocol.

[0096] An immunogenic composition comprising one or more tumor-specific neoantigens can be administered to a subject diagnosed with cancer, a subject already suffering from cancer, a subject with recurrent cancer (i.e., recurrence), or a subject at risk of developing cancer. An immunogenic composition comprising one or more tumor-specific neoantigens can be administered to a subject resistant to other forms of cancer treatment (e.g., chemotherapy, immunotherapy, or radiation). An immunogenic composition comprising one or more tumor-specific neoantigens can be administered to a subject prior to other standard cancer therapies (e.g., chemotherapy, immunotherapy, or radiation). An immunogenic composition comprising one or more tumor-specific neoantigens can be administered to a subject simultaneously with, after, or in combination with other standard cancer therapies (e.g., chemotherapy, immunotherapy, or radiation).

[0097] The subject can be a human, a dog, a cat, a horse, or any animal for which a tumor-specific response is desired.

[0098] The immunogenic composition is administered to the subject in an amount sufficient to induce an immune response against the tumor-specific neoantigen and to destroy or at least partially arrest the symptoms and / or complications. In embodiments, the immunogenic composition can provide a long-term immune response. The long-term immune response can be established by administering additional doses of the immunogenic composition to the subject. The immune response to the immunogenic composition can be extended by administering additional doses to the subject. In embodiments, at least 1, at least 2, at least 3, or more additional doses can be administered to effect remission of the cancer. The first additional dose can increase the immune response by at least 50%, at least 100%, at least 200%, at least 300%, at least 400%, at least 500%, or at least 1000% compared to the initial immune response. The second additional dose can increase the immune response by at least 50%, at least 100%, at least 200%, at least 300%, at least 400%, at least 500%, or at least 1000% compared to the initial immune response. The third additional dose can increase the immune response by at least 50%, at least 100%, at least 200%, at least 300%, at least 400%, at least 500%, or at least 1000% compared to the initial immune response.

[0099] An amount sufficient to induce an immune response is defined as a "therapeutically effective dose". The amount effective for this use depends, for example, on the composition, the mode of administration, the stage and severity of the disease under treatment, the weight and general health of the patient, and the judgment of the prescribing physician. It should be recognized that immunogenic compositions can generally be used in severe disease states, i.e., life-threatening or potentially life-threatening situations, particularly when cancer has metastasized. In such cases, in view of the minimization of foreign substances and the relatively non-toxic nature of neoantigens, it may be possible and desirable for the treating physician to administer substantially excessive amounts of these immunogenic compositions.

[0100] An immunogenic composition comprising one or more tumor-specific neoantigens can be administered to a subject, either alone or in combination with other therapeutic agents. The therapeutic agent can be, for example, a chemotherapeutic agent, radiation therapy, or immunotherapy. Any suitable therapeutic treatment for a particular cancer may be administered. Exemplary chemotherapeutic agents include, but are not limited to, aldesleukin, altretamine, amifostine, asparaginase, bleomycin, capecitabine, carboplatin, carmustine, cladribine, cisapride, cisplatin, cyclophosphamide, cytarabine, dacarbazine (DTIC), dactinomycin, docetaxel, doxorubicin, dronabinol, epoetin alfa, etoposide, filgrastim, fludarabine, fluorouracil, gemcitabine, granisetron, hydroxyurea, idarubicin, ifosfamide, interferon alfa, irinotecan, lansoprazole, levamisole, leucovorin, megestrol, mesna, methotrexate, metoclopramide, mitomycin, mitotane, mitoxantrone, omeprazole, ondansetron, paclitaxel (Taxol®), pilocarpine, prochlorperazine, rituximab, tamoxifen, topotecan hydrochloride, trastuzumab, vinblastine, vincristine, and vinorelbine tartrate. The subject can be administered small molecule or targeted therapies (e.g., kinase inhibitors). The subject can further be administered an anti-CTLA antibody, an anti-PD-1 antibody, or an anti-PD-L1 antibody. Blockade of CTLA-4 or PD-L1 by an antibody can enhance the immune response against the patient's cancer cells.

[0101] D. Quantification of Circulating Materials and Tumor-Related Mutations Each of the tumor-specific neoantigens in the initial immunogenic composition is expected to be effective against the tumor, but in reality, it is highly likely that at least some of the tumor-specific neoantigens can be ineffective targets of the initial immunogenic composition. Even if all tumor-specific neoantigens are effective, it is not possible to predict this in advance.

[0102] The present disclosure further relates to monitoring the levels of each tumor-related variant within a subject's tumor at multiple time points. If a tumor-related variant in a first set of tumor-related variants increases over time, it can be concluded that the tumor-specific neoantigen corresponding to that tumor-related variant is an ineffective target.

[0103] The level of each tumor-related variant can be determined by quantifying each member of a first set of tumor-related variants and each member of a second set of tumor-related variants in circulating material isolated from the subject.

[0104] Circulating material can be any material generated by the subject's tumor cells or healthy cells and found in the subject's bloodstream. Examples of circulating material include circulating tumor DNA (ctDNA), cell-free DNA (cfDNA), circulating tumor cells (CTCs), circulating tumor proteins, extracellular vesicles, or two or more of these.

[0105] Circulating tumor DNA is DNA derived from tumor cells and thus is expected to contain tumor-related variants. Even when the tumor itself is growing, individual tumor cells can die and release ctDNA either directly or via the normal action of macrophages.

[0106] The abundance of ctDNA is a function of the total surface area of the tumor-vascular interface. This includes all metastases. Thus, ctDNA aggregates information from all of the subject's tumors, whereas quantifying tumor-related variants by tissue WES, WGS, or scRNA sequencing instead of blood is limited to the specific tumor from which the tissue is extracted for sequencing. Also, blood sampling is a simpler and less invasive process than extracting tissue from most internal tumors.

[0107] Exemplary amounts of ctDNA in a biological sample (e.g., plasma or serum) can range from about 1 femtogram (fg) to about 1 picogram (pg), from about 1 pg to about 200 nanograms (ng), from about 1 ng to about 100 ng, or from about 10 ng to about 1000 ng. For example, the amount of the ctDNA can be up to about 600 ng, up to about 500 ng, up to about 400 ng, up to about 300 ng, up to about 200 ng, up to about 100 ng, up to about 50 ng, or up to about 20 ng. The amount of the ctDNA can be at least 1 fg, at least 10 fg, at least 100 fg, at least 1 pg, at least 10 pg, at least 100 pg, at least 1 ng, at least 10 ng, at least 100 ng, at least 150 ng, or at least 200 ng. The amount of the ctDNA molecules can be up to 1 fg, 10 fg, 100 fg, 1 pg, 10 pg, 100 pg, 1 ng, 10 ng, 100 ng, 150 ng, or 200 ng. The method can include obtaining 1 fg to 200 ng of ctDNA.

[0108] CtDNA can have an exemplary size distribution of about 100 to 500 nucleotides. CtDNA can be about 100, about 105, about 110, about 115, about 120, about 125, about 130, about 135, about 140, about 145, about 150, about 155, about 160, about 165, about 170, about 175, about 180, about 185, about 190, about 195, about 200, about 210, about 215, about 220, about 225, about 230, about 235, about 240, about 245, about 250, about 255, about 260, about 265, about 270, about 275, about 280, about 285, about 290, about 295, about 300, about 305, about 310, about 315, about 320, about 325, about 330, about 335, about 340, about 345, about 350, about 355, about 360, about 365, about 370, about 375, about 380, about 385, about 390, about 395, about 400, about 405, about 410, about 415, about 420, about 425, about 430, about 435, about 440, about 445, about 450, about 455, about 460, about 465, about 470, about 475, about 480, about 485, about 490, about 495, or about 500 nucleotides.

[0109] In the broadest definition, cell-free DNA is any DNA present in the bloodstream. In this specification, cfDNA is used to refer to DNA released from non-tumor cells into the bloodstream. In other words, ctDNA and cfDNA are distinct aspects of the present disclosure.

[0110] In addition to ctDNA, the bloodstream also contains cell-free DNA (cfDNA) of non-tumor origin, i.e., from normal cells. Generally, 1 ml of blood contains on average 6 ng of cell-free DNA, or approximately 1800 cell genomes. The concentrations of cfDNA and ctDNA vary widely between different individuals and depend on many factors including age, lifestyle, condition, and in the context of cancer treatment, the type and stage of cancer. Most of these cell genomes are derived from healthy cells. For example, a 10 mm diameter breast cancer tumor is expected to contribute approximately 0.03 cancer genomes per ml of blood. In another example, a 10 mm diameter melanoma tumor is expected to contribute approximately 1 - 2 cancer genomes per ml of blood.

[0111] CfDNA is DNA derived from non-tumor cells and thus would not seemingly contain tumor-related mutations at first glance. However, DNA from non-tumor cells present in the tumor microenvironment can undergo epigenetic changes such as changes in methylation or chromatin content that reflect tumor-related mutations.

[0112] Circulating tumor proteins are proteins derived from tumor cells and are thus expected to contain tumor-related mutations. Circulating tumor proteins can be released from dead or dying tumor cells, secreted by living tumor cells, or introduced into the bloodstream of a subject by any other mechanism known.

[0113] CTCs are tumor cells present in the bloodstream, regardless of whether they are alive, dying, or dead. They are cells and are expected to contain tumor DNA and tumor proteins and thus tumor-related mutations.

[0114] Extracellular vesicles are vesicles defined by a membrane that can be released from the surface of tumor cells or normal cells. Extracellular vesicles usually contain RNA and proteins derived from the parent cell, which can provide information regarding tumor-related mutations. For example, extracellular vesicles from tumor cells can be a source of tumor proteins, and any extracellular vesicles can be a source of nucleic acids that exhibit epigenetic changes in tumor cells or normal cells that result in changes in DNA transcription (and consequently, changes in RNA levels).

[0115] To quantify tumor-related mutations in the circulating material, a sample containing the circulating material can be collected from a subject and the circulating material can be isolated therefrom.

[0116] Samples can be obtained from human or non-human subjects. In one aspect, the sample is obtained from a human. Samples can be obtained from a variety of biological sources.

[0117] Various assays (e.g., sequencing assays) can be used to detect the circulating material. The methods provided herein can include the isolation and analysis of circulating material from the blood (e.g., plasma or serum) of a subject of interest (i.e., a subject having cancer, a subject in remission from cancer, or a subject suspected of having cancer). The method can include isolating plasma and circulating material from blood depleted of intact cells. The method can include centrifugation to produce plasma and extraction of nucleic acids from the plasma.

[0118] Circulating materials can be derived from a bodily fluid of interest (e.g., a blood sample). Circulating materials can be obtained from the plasma fraction, serum fraction, or both of a blood sample. In some embodiments, the bodily sample includes whole blood, serum, plasma, cerebrospinal fluid, synovial fluid, lymphatic fluid, ascites, interstitial fluid or extracellular fluid, gingival crevicular fluid, bone marrow, pleural effusion, cerebrospinal fluid, saliva, mucus, sputum, semen, sweat, urine, or any combination thereof. In some embodiments, the circulating DNA is obtained from blood and its fractions. The sample may be in the form initially isolated from the subject and may be subjected to further processing to remove or add components such as cells or to concentrate one component relative to another. The sample can be isolated or obtained from the subject and transported to the site of sample analysis. The sample can be stored and transported at a desired temperature, e.g., room temperature, 4°C, -20°C, and / or -80°C. The sample can be isolated or obtained from the subject at the site of sample analysis. The subject can be a human, mammal, animal, companion animal, service animal, or pet. The subject may not have cancer or detectable cancer symptoms. The subject may be treated with one or more cancer treatments, e.g., chemotherapy, antibodies, vaccines, or biologics. The subject may be in remission. The subject may be suspected of having cancer or any cancer-related genetic mutations.

[0119] The biological sample can be obtained from the subject by any means including, but not limited to, tumor biopsy, needle aspiration, scraping, surgical resection, surgical incision, venipuncture, or other means known in the art. One of ordinary skill in the art will recognize other suitable techniques for obtaining a biological sample.

[0120] The biological sample can be obtained from the subject in a single procedure. The biological sample can be obtained from the subject repeatedly over a period of time. For example, the biological sample can be obtained once a day, once a week, monthly, semi-annually, or annually. Obtaining multiple samples over a period of time can be useful for identifying and selecting novel tumor-specific neoantigens.

[0121] Circulating materials can be isolated from body fluids (e.g., plasma) through a fractionation or partitioning step that separates the circulating materials found in solution from intact cells and other insoluble components of the body fluids. Partitioning can include techniques such as centrifugation or filtration. Alternatively, the cells in the body fluid can be lysed and the cell-free nucleic acids and cellular nucleic acids can be processed together. Generally, after the addition step and washing step of the buffer, the nucleic acids can be precipitated with alcohol. Further cleanup steps, such as silica-based columns, can be used to remove contaminants or salts. After such processing, the sample can contain nucleic acids in various forms, including double-stranded DNA and single-stranded DNA. In some embodiments, the single-stranded DNA can be converted to the double-stranded form so that they are included in subsequent processing steps and analysis steps.

[0122] In some embodiments, the circulating materials are isolated from a blood sample, a serum sample, a plasma sample, a urine sample, or a cerebrospinal fluid sample. In one aspect, the sample is a blood sample, a serum sample, or a plasma sample.

[0123] In embodiments where the sample is a blood sample, a serum sample, or a plasma sample, the circulating materials can be isolated from at least about 10 ml of the subject's whole blood, e.g., at least about 20 ml of the subject's whole blood. These blood volumes can be particularly useful considering the relatively small amount of cancer genome per ml of blood when the circulating materials contain ctDNA.

[0124] In some embodiments, in the case of ctDNA, tumor-associated variants may be found with an allele frequency in the cfDNA pool of less than 10.0%, such as less than 9.9%, less than 9.8%, less than 9.7%, less than 9.6%, less than 9.5%, less than 9.4%, less than 9.3%, less than 9.2%, less than 9.1%, less than 9.0%, less than 8.9%, less than 8.8%, less than 8.7%, less than 8.6%, less than 8.5%, less than 8.4%, less than 8.3%, less than 8.2%, less than 8.1%, less than 8.0%, less than 7.9%, less than 7.8%, less than 7.7%, less than 7.6%, less than 7.5%, less than 7.4%, less than 7.3%, less than 7.2%, less than 7.1%, less than 7.0%, less than 6.9%, less than 6.8%, less than 6.7%, less than 6.6%, less than 6.5%, less than 6.4%, less than 6.3%, less than 6.2%, less than 6.1%, less than 6.0%, less than 5.9%, less than 5.8%, less than 5.7%, less than 5.6%, less than 5.5%, less than 5.4%, less than 5.3%, less than 5.2%, less than 5.1%, less than 5.0%, less than 4.9%, less than 4.8%, less than 4.7%, less than 4.6%, less than 4.5%, less than 4.4%, less than 4.3%, less than 4.2%, less than 4.1%, less than 4.0%, less than 3.9%, less than 3.8%, less than 3.7%, less than 3.6%, less than 3.5%, less than 3.4%, less than 3.3%, less than 3.2%, less than 3.1%, less than 3.0%, less than 2.9%, less than 2.8%, less than 2.7%, less than 2.6%, less than 2.5%, less than 2.4%, less than 2.3%, less than 2.2%, less than 2.1%, less than 2.0%, less than 1.9%, less than 1.8%, less than 1.7%, less than 1.6%, less than 1.5%, less than 1.4%, less than 1.3%, less than 1.2%, less than 1.1%, less than 1.0%, less than 0.9%, less than 0.8%, less than 0.7%, less than 0.6%, less than 0.5%, less than 0.4%, less than 0.3%, less than 0.2%, or less than 0.1%.

[0125] In some embodiments, the blood sample is taken at least once before treatment, followed by serial sampling guided by the effectiveness of the immunogenic composition and the frequency of monitoring disease progression.

[0126] Within 5 days of the biopsy collected for paired genomic (including but not limited to WGS / WES) tumor-normal sequencing before treatment and within 2 to 4 weeks of administration of the immunogenic composition, 10 to 20 ml of blood can be collected from the subject.

[0127] After treatment, at regularly scheduled intervals based on the medically informed indication of disease progression, the clinically observed response to the immunogenic composition, or if the patient is scheduled to receive a follow-up dose of the initial immunogenic composition or a reformulated immunogenic composition, and at least once at the time of administration of the initial immunogenic composition and once within 10 weeks of administration of the initial immunogenic composition, serial collection of blood samples can be performed.

[0128] Quantifying tumor-associated variants can include various methods depending on the circulating material under consideration. Quantifying can include sequencing ctDNA using WES, WGS, targeted sequencing, polymerase chain reaction (PCR), or hybridization methods.

[0129] In the case of cfDNA, quantifying tumor-associated variants can include quantitative polymerase chain reaction (qPCR) or next-generation sequencing.

[0130] Given that DNA can be prepared from RNA present in CTCs or extracellular vesicles using a reverse transcription process (e.g., use of reverse transcriptase), tumor-associated variants in nucleic acids derived from CTCs or extracellular vesicles can be quantified by any of the techniques described herein. Also, the RNA can be directly subjected to single-cell RNA sequencing (scRNAseq) to identify and quantify tumor-associated variants derived from the RNA.

[0131] For any genomic DNA-based method such as CTC-derived ctDNA, cfDNA, or DNA, quantifying tumor-related mutations can include assaying the methylation or chromatin content of one or more epigenetic markers. Chromatin content can be assayed, among other techniques known to those skilled in the art, by assay for transposase-accessible chromatin using high-throughput sequencing (ATAC-Seq).

[0132] There are various methods for obtaining the genomic sequence data described herein. Sequencing methods are well known in the art and include, but are not limited to, whole-genome sequencing (WGS), whole-exome sequencing (WES), targeted sequencing, PCR-based methods including real-time PCR (RT-PCR), deep sequencing, high-throughput sequencing, or combinations thereof. In some cases, the foregoing techniques and procedures can be carried out according to, for example, the methods described in Sambrook et al., Molecular Cloning: A Laboratory Manual 4th ed. (2012) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY. See also Austell et al., Current Protocols in Molecular Biology, ed., Greene Publishing and Wiley-Interscience New York (1992) (with periodic updates).

[0133] Genomic sequence data can be obtained from WGS, WES, targeted sequencing, DNA hybridization methods, or combinations thereof. Genomic sequencing data can be sequence data derived from high-depth WGS data.

[0134] In some embodiments, the DNA may be sequenced to obtain sequence reads. The sequence data includes sequence reads of multiple polynucleotides from a subject. The sequence reads can include from about 2 to about 5000 nucleotides. For example, about 2, about 3, about 4, about 5, about 10, about 20, about 30, about 40, about 50, about 60, about 70, about 80, about 90, about 100, about 110, about 120, about 130, about 140, about 150, about 160, about 170, about 180, about 190, about 200, about 210, about 220, about 230, about 240, about 250, about 260, about 270, about 280, about 290, about 300, about 310, about 320, about 330, about 340, about 350, about 360, about 370, about 380, about 390, about 400, about 410, about 420, about 430, about 440, about 450, about 460, about 470, about 480, about 490, about 500, about 550, about 600, about 700, about 800, about 900, about 1,000, about 1,100, about 1,200, about 1,300, about 1,400, about 1,500, about 1,600, about 1,700, about 1,800, about 1,900, about 2,000, about 2,100, about 2,200, about 2,300, about 2,400, about 2,500, about 2,600, about 2,700, about 2,800, about 2,900, about 3,000, about 3,100, about 3,200, about 3,300, about 3,400, about 3,500, about 3,600, about 3,700, about 3,800, about 3,900, about 4,000, about 4,100, about 4,200, about 4,300, about 4,400, about 4,500, about 4,600, about 4,700, about 4,800, about 4,900, or about 5,000 nucleotides.

[0135] The DNA sequence data can be analyzed using integration of variant reads (INVAR) as described in International Application No.: PCT / EP2019 / 055610. The DNA sequence data can be analyzed using an objective function outlined in Equation 1:

Number

[0136] Where ξi is the estimated cell disease rate of the i-th subclone. P~iα is the probability that peptide α is present in the i-th subclone, and sα is the individual score of the α-th peptide obtained from machine learning modeling. All of these estimates of disease rates and subclonality are calculated from a combination of biopsy and DNA sequencing. "big-OR" is obtained for the best L peptides at L = 20, and the sum is obtained for all of the C subclones, where C has a parameter returned by the subclonality estimation algorithm. Usually, 1 < C < 15.

[0137] DNA sequence data can be analyzed using the objective function outlined in Equation 2:

Number

[0138] Where ξα is the cell disease rate of the α-th mutation, and sα is the individual score of the α-th peptide obtained from machine learning modeling. The linear classification of all peptides by the product ξαsα optimizes this function.

[0139] DNA sequence data can be analyzed using a machine learning platform. Exemplary machine learning models that may be appropriate include, but are not limited to, neural networks, Bayesian classifiers, logistic regression, decision trees, gradient boosting decision trees, random forests, support vector machines, gradient boosting trees, multilayer perceptrons, one-versus-all, or Gaussian naive Bayes.

[0140] In some embodiments, a blood sample can be processed within 4 hours, and circulating free DNA can be isolated from plasma using standard methods or kits (e.g., DNeasy™ kit (Qiagen N.V., Venlo, Netherlands), QIAmp™ kit (ibid.), or Quick-cfDNA™ kit (Zymo Research, Irvine, CA)). In pre-treatment specimen processing, in addition to isolating circulating free DNA from plasma, germline genomic DNA can also be extracted using peripheral blood lymphocytes from the first centrifugation step in the isolation of circulating free DNA and used as a concordance standard for genomic analysis. A minimum yield of 20 ng of DNA per blood aliquot is desirable.

[0141] As described herein, the circulating material can include circulating tumor proteins, proteins derived from CTCs, or proteins derived from extracellular vesicles, any of which can contain tumor-related mutations. Quantifying tumor-related mutations in proteins can include performing a mass spectrometry assay or an elution assay on circulating tumor proteins, proteins derived from CTCs, or proteins derived from extracellular vesicles.

[0142] As described herein, CTCs can be a source of tumor proteins or tumor nucleic acids. Also, quantification of tumor-related mutations in CTC-derived materials can include performing fluorescence-activated cell sorting (FACS) on CTCs. This can be part of an initial classification or separation of CTCs from other cells in circulation. In some embodiments, particularly when the tumor-related mutations are within proteins exposed on the surface of tumor cells, FACS can be used to sort CTCs based at least in part on the tumor-related mutations, thus providing a direct quantification of the tumor-related mutations.

[0143] The quantification unit can be molecules / ml or another metric of the number of tumor-related variant copies per weight or volume of the sample. Quantification can be normalized, if desired, by, for example, normalizing the number of tumor-related variant copies against the total amount of the starting material, the number of copies of a healthy tissue marker gene expected to have a certain number of copies in the starting material, etc.

[0144] Quantification of tumor-related variants can be performed at each of multiple time points. By doing so, the quantity of each tumor-related variant can be tracked over time.

[0145] Quantification of tumor-related variants can be performed using the same circulating material at each time point. In one hypothetical example, if a first tumor-related variant is quantified from ctDNA at a first time point, the first tumor-related variant can be quantified from ctDNA at a second time point. This may be desirable to enhance the consistency and accuracy of measurements over multiple time points.

[0146] Contemplated is the quantification of a first tumor-related variant from a first circulating material at a first time point and a second circulating material at a second time point. In another hypothetical example, a first tumor-related variant can be quantified from ctDNA at a first time point and from CTC at a second time point. By appropriately normalizing the quantified values determined by each technique to reference values expected to remain substantially constant within each circulating material and substantially proportional between the two circulating materials over various time points, the accuracy of measurements over multiple time points can be maintained at an acceptable high level.

[0147] Multiple circulating materials can be used to quantify multiple tumor-related variants. In yet another hypothetical example, a first tumor-related variant can be quantified from ctDNA at a first time point and a second time point, and a second tumor-related variant can be quantified from, for example, circulating tumor protein at the first time point and the second time point.

[0148] In some embodiments, at least one of the plurality of time points can be before the initial immunogenic composition is administered.

[0149] The virtual model illustrated in FIG. 1 shows the quantification of three tumor-specific neoantigens, peptides 1-3, derived from ctDNA. As described above, peptides 1 and 2 are included in the immunogenic composition and correspond to members of the first set of tumor-associated mutations. Peptide 3 is not included in the immunogenic composition and corresponds to a member of the second set of tumor-associated mutations. The three tumor-associated mutations corresponding to peptides 1-3 are quantified in ctDNA at four time points: week E, week 0, week 4, and week 8. Week E is the time point at which the tumor-associated mutations of the subject are identified. The immunogenic composition, referred to as a vaccine in FIG. 1, is manufactured before week 0. The immunogenic composition is administered to the subject at week 0, week 4, and week 8, as represented by the notation "VAC". Thus, week E, which is at least one of the time points of quantification, is before the initial immunogenic composition is administered.

[0150] Continuing with the virtual model of FIG. 1, the amount of each tumor-associated mutation is graphed over time. After week 8, the following is observed: The amount of the tumor-associated mutation corresponding to peptide 1, which contains ProTrp, decreased over time. This indicates that the tumor-specific neoantigen of peptide 1 in the initial immunogenic composition suppressed the tumor cells containing this tumor-associated mutation; The amount of the tumor-associated mutation corresponding to peptide 2, which contains ArgCys, increased over time. This indicates that the tumor-specific neoantigen of peptide 2 in the initial immunogenic composition was unable to suppress the tumor cells containing this tumor-associated mutation; The amount of the tumor-associated mutation corresponding to peptide 3, which contains ThrAla, increased slightly over time. However, it should be borne in mind that the tumor-specific neoantigen of peptide 3 was not included in the initial immunogenic composition.

[0151] Multiple time points for quantifying tumor - related mutations can occur at various intervals and / or at different times, as discussed in more detail herein, compared to other actions by the present method.

[0152] E. Reformulation of immunogenic compositions By quantifying tumor - related mutations in circulating materials over multiple time points, it can be discovered that the amount of members of a first set of tumor - related mutations (i.e., tumor - related mutations having the corresponding tumor - specific neoantigens included in the initial immunogenic composition) increases from an earlier time point to a later time point. As described above, such a discovery indicates that the corresponding tumor - specific neoantigen is an ineffective component of the initial immunogenic composition.

[0153] The method may further include replacing the tumor - specific neoantigens corresponding to members of the first set of tumor - related mutations from the initial immunogenic composition with substituted tumor - specific neoantigens corresponding to members of a second set of tumor - related mutations, in response to the increase in the amount of members of the first set of tumor - related mutations from an earlier time point to a later time point, resulting in a reformulated immunogenic composition.

[0154] As is apparent, a plurality of tumor - specific neoantigens respectively corresponding to members of the first set of tumor - related mutations can be replaced if the condition that the amount of members of the first set of tumor - related mutations corresponding to that tumor - specific neoantigen increases from an earlier time point to a later time point is satisfied.

[0155] In some embodiments, the amount of members of the second set of tumor - related mutations corresponding to the substituted tumor - specific neoantigen did not decrease from an earlier time point to a later time point. This may be desirable on the premise that if the amount of such tumor - related mutations decreases, there would be no further benefit in targeting it with the substituted tumor - specific neoantigen even if the corresponding tumor - specific neoantigen is not targeted by the immunogenic composition.

[0156] Members of the second set of tumor-related variants may change if the method is performed over multiple iterations. This may include regular monitoring of the subject's circulating material for the emergence of novel neoantigens. If a novel neoantigen emerges and is detected, the sequence encoding it may be added to the second set of tumor-related variants.

[0157] In some embodiments, the method further includes detecting the emergence of at least one tumor-related variant at a first time point that is not included in the first set of tumor-related variants or the second set of tumor-related variants, and adding the emerged tumor-related variant to the second set of tumor-related variants at a time point after the first time point. After adding the emerged tumor-related variant to the second set, at the time of addition, the immunogenic composition may be reformulated to include the emerged tumor-related variant.

[0158] As a specific virtual example, an initial immunogenic composition may be prepared based in part on the finding that peptide p is not encoded by the subject's ctDNA. In other words, peptide p is not due to a tumor-related variant and is thus not suitable for inclusion in the initial immunogenic composition. At a first time point (e.g., after performing at least once the quantification of members of the second set of tumor-related variants and monitoring for the emergence of novel neoantigens), a novel neoantigen is detected. The novel neoantigen can be added to the second set of tumor-related variants and the method is continued to a later time point. If the amount of the novel neoantigen does not decrease at two or more time points, the novel neoantigen may be a highly desirable reformulation candidate as it may reflect the dynamic response of the tumor to treatment (e.g., a novel subclone carrying the novel neoantigen may have acquired resistance to all components in the initial immunogenic composition). By reformulating the composition to include the novel neoantigen, the ability of the subclone to evade treatment may be minimized.

[0159] The replacement tumor-specific neoantigen can be selected based on any one or more criteria that will be apparent to those skilled in the art. In some embodiments, the tumor-specific neoantigens corresponding to a second set of tumor-associated mutations can be ranked by an immunogenicity score, and the highest-ranked tumor-specific neoantigen can be selected as the replacement tumor-specific neoantigen. In some embodiments, the change in the amount of a second set of tumor-associated mutations over multiple time points can be ranked, and the tumor-specific neoantigen corresponding to the tumor-associated mutation with the greatest increase can be selected as the replacement tumor-specific neoantigen.

[0160] The replacement can be carried out at any time after administration of the initial immunogenic composition. In some embodiments, the initial immunogenic composition can be administered once before replacement of the tumor-specific neoantigen.

[0161] In some embodiments, the initial immunogenic composition can be administered multiple times before replacement of the tumor-specific neoantigen.

[0162] Returning to the virtual model of FIG. 1, the initial immunogenic composition is administered three times (at week 0, week 4, and week 8). Thereafter, tumor-associated mutations from the first set of tumor-associated mutations, which was the peptide 2 containing ArgCys and had an increasing amount from week E to week 8 (along with the corresponding tumor-specific neoantigen included in the initial immunogenic composition), are replaced in the immunogenic composition with peptide 3 containing ThrAla. Although not necessary in the method of the present invention, the amount of the corresponding tumor-associated mutation for peptide 3 did not decrease from week E to week 8. The resulting reformulated immunogenic composition contains peptide 1 (containing ProTrp) and peptide 3 (containing ThrAla). The reformulated immunogenic composition can be administered at week 12, week 16, and week 20. In other words, the regimen of immunogenic composition administration can remain the same, except that the reformulated immunogenic composition, instead of the initial immunogenic composition, is administered at the scheduled administration times after replacing the previous tumor-specific neoantigen with the replacement tumor-specific neoantigen.

[0163] The replacement immunogenic composition can be administered at any time after replacement. In some embodiments, the reformulated immunogenic composition is administered once after replacing the tumor-specific neoantigen.

[0164] In some embodiments, the reformulated immunogenic composition can be administered multiple times after replacing the tumor-specific neoantigen.

[0165] F. Selection of Time Points for Quantification As described above, in some embodiments, at least one of the multiple time points for quantification can be selected compared to the timing of other operations by the method.

[0166] In some embodiments, one of the multiple time points is at least about 1 week, about 2 weeks, about 3 weeks, about 4 weeks, about 5 weeks, about 6 weeks, about 7 weeks, about 8 weeks, about 9 weeks, about 10 weeks, about 11 weeks, or about 12 weeks after administering the initial immunogenic composition or the reformulated immunogenic composition.

[0167] In some embodiments, one of the multiple time points is at least about 1 month, about 2 months, about 3 months, about 4 months, about 5 months, about 6 months, about 7 months, about 8 months, about 9 months, about 10 months, about 11 months, or about 12 months after administering the initial immunogenic composition or the reformulated immunogenic composition.

[0168] In some embodiments, one of the multiple time points is at least about 1 year, about 2 years, about 3 years, about 4 years, about 5 years, about 6 years, about 7 years, about 8 years, about 9 years, or about 10 years after administering the initial immunogenic composition or the reformulated immunogenic composition.

[0169] G. Treatment Regimen Comprising Three or More Reformulated Immunogenic Compositions The foregoing description of the initial immunogenic composition and the reformulated immunogenic composition is not limited to situations such as the visualization model illustrated in FIG. 1. The initial immunogenic composition is the first immunogenic composition administered to a subject, and the reformulated immunogenic composition is the second and final immunogenic compositions administered to the subject. More generally, the immunogenic composition referred to herein as the "initial immunogenic composition" can be the x-th immunogenic composition of n immunogenic compositions administered to a subject during the course of a treatment plan, where x is from 1 to n-1 (inclusive), and the reformulated immunogenic composition is the x+1-th of the n immunogenic compositions administered to the subject, where x+1 is from 2 to n (inclusive). This definition encompasses the virtual model of FIG. 1 and includes embodiments where n = 3, 4, 5, 6, or more, as well as n = 2.

[0170] Accordingly, in some embodiments, the methods disclosed herein can be performed multiple times during the course of a treatment plan. For example, when n = 3, the methods disclosed herein can be performed twice. In the first performance, the first immunogenic composition administered during the treatment plan is the first initial immunogenic composition, and the second immunogenic composition administered during the treatment plan is the first reformulated immunogenic composition. In the second performance, the first reformulated immunogenic composition is also the second initial immunogenic composition, and the third immunogenic composition administered during the treatment plan is the second reformulated immunogenic composition.

[0171] 4. Equivalents Other suitable modifications and adaptations of the methods of the invention described herein will be apparent, and it will be readily apparent to those skilled in the art that they can be made using suitable equivalents without departing from the scope of this disclosure or the embodiments.

Claims

1. An immunogenic composition for use in an immunotherapeutic treatment for cancer in a subject, or for use in a prophylactic immunotherapeutic treatment for a subject at risk of developing cancer, wherein the immunogenic composition is to be administered to the subject and comprises a plurality of tumor-specific neoantigens, each tumor-specific neoantigen corresponding to a member of a first set of tumor-associated mutations in the subject, and none of the tumor-specific neoantigens corresponding to a member of a second set of tumor-associated mutations in the subject. The immunogenic composition is characterized in that, at each of several time points, each member of a first set of tumor-associated mutations and each member of a second set of tumor-associated mutations are to be quantified in a circulating material containing tumor-associated mutations isolated from the subject.

2. The immunogenic composition for use according to claim 1, wherein the circulating material comprises circulating tumor DNA (ctDNA), circulating free DNA (cfDNA), circulating tumor cells (CTCs), circulating tumor proteins, extracellular vesicles, or a combination thereof.

3. In response to an increase in the amount of members of the first set of tumor-associated mutations from an earlier time point to a later time point, the immunogenic composition should be reformulated by replacing the tumor-specific neoantigens corresponding to the members of the first set of tumor-associated mutations with substituted tumor-specific neoantigens corresponding to the members of the second set of tumor-associated mutations in the immunogenic composition, The immunogenic composition for use according to claim 1, characterized in that the reformulated immunogenic composition is subsequently administered to the subject.

4. The immunogenic composition for use according to claim 1, wherein the subject is melanoma, breast cancer, sarcoma, ovarian cancer, prostate cancer, kidney cancer, gastric cancer, colon cancer, testicular cancer, head and neck cancer, pancreatic cancer, brain cancer, bone cancer, B-cell lymphoma, acute myeloid leukemia, chronic myeloid leukemia, chronic lymphocytic leukemia, T-cell lymphocytic leukemia, colon cancer, urothelial carcinoma, or lung cancer.

5. The tumor-associated mutation includes at least one mutation specific to the subject, and / or The immunogenic composition for use according to claim 1, wherein the tumor-associated mutation comprises at least one tumor hotspot mutation.

6. The tumor-associated mutation includes at least one tumor hotspot mutation, (i) The tumor is ER+ / HER2- breast cancer, and the at least one tumor hotspot mutation is in a gene selected from the group consisting of AKT1, APC, ARID1A, ATM, BRAF, BRCA1, BRCA2, CDH1, CDKN2A, ESR1, GATA3, GNAS, HER2, KRAS, NF1, PIK3CA, PTEN, RB1, SMAD4, and TP53, or (ii) The immunogenic composition for use according to claim 5, wherein the tumor is melanoma.

7. The immunogenic composition for use according to claim 1, wherein each tumor-specific neoantigen corresponding to a member of the first set of tumor-associated mutations has a higher immunogenicity score than any tumor-specific neoantigen corresponding to a member of the second set of tumor-associated mutations.

8. The immunogenic composition for use according to claim 1, wherein at least one of the aforementioned multiple time points is prior to the administration of the immunogenic composition.

9. The immunogenic composition for use according to claim 3, characterized in that the immunogenic composition is administered multiple times before replacing the tumor-specific neoantigen corresponding to the member of the first set of tumor-associated mutations with the substituted tumor-specific neoantigen corresponding to the member of the second set of tumor-associated mutations.

10. The immunogenic composition for use according to claim 3, characterized in that the reformulated immunogenic composition is to be administered multiple times after replacing the tumor-specific neoantigen corresponding to the member of the first set of tumor-associated mutations with a substituted tumor-specific neoantigen corresponding to the member of the second set of tumor-associated mutations.

11. The immunogenic composition for use according to claim 3, wherein the amount of the member of the second set of tumor-associated mutations corresponding to the substituted tumor-specific neoantigen did not decrease from an earlier time point to a later time point.

12. The quantification of the tumor-associated mutations is Sequencing ctDNA using whole exome sequencing (WES), whole genome sequencing (WGS), targeted sequencing, polymerase chain reaction (PCR), or hybridization methods. Sequencing cfDNA using quantitative polymerase chain reaction (qPCR) or next-generation sequencing. Assaying the methylation or chromatin content of ctDNA, cfDNA, or DNA derived from CTCs, Perform a mass spectrometry assay or elution assay for circulating tumor proteins, CTC-derived proteins, or extracellular vesicle-derived proteins. Performing fluorescence-activated cell sorting (FACS) on CTCs, or Sequencing nucleic acids derived from CTCs or extracellular vesicles using WES, WGS, targeting sequencing, PCR, qPCR, next-generation sequencing, single-cell RNA sequencing, or hybridization methods. An immunogenic composition for use according to claim 2, comprising:

13. One of the aforementioned multiple time points is at least about 1 week, about 2 weeks, about 3 weeks, about 4 weeks, about 5 weeks, about 6 weeks, about 7 weeks, about 8 weeks, about 9 weeks, about 10 weeks, about 11 weeks, or about 12 weeks after the administration of the immunogenic composition or the reformulated immunogenic composition, and / or One of the aforementioned multiple time points is at least about 1 month, about 2 months, about 3 months, about 4 months, about 5 months, about 6 months, about 7 months, about 8 months, about 9 months, about 10 months, about 11 months, or about 12 months after the administration of the immunogenic composition or the re-formulated immunogenic composition, or The immunogenic composition for use according to claim 1, wherein one of the aforementioned multiple time points is at least about 1 year, about 2 years, about 3 years, about 4 years, about 5 years, about 6 years, about 7 years, about 8 years, about 9 years, or about 10 years after the immunogenic composition or the reformulated immunogenic composition was administered.

14. The immunogenic composition for use according to claim 1, wherein the circulating material is isolated from a blood sample, serum sample, plasma sample, urine sample, or cerebrospinal fluid sample.

15. The circulating material is isolated from at least about 10 ml of the whole blood of the subject, or The immunogenic composition for use according to claim 1, wherein the circulating material is isolated from at least about 20 ml of the whole blood of the subject.

16. The immunogenic composition for use according to claim 1, characterized in that, if the appearance of at least one tumor-associated mutation not included in the first set of tumor-associated mutations or the second set of tumor-associated mutations is detected at a first time point, the appeared tumor-associated mutation should be added to the second set of tumor-associated mutations at a time point after the first time point.

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