Dendritic cell subsets and implications for cancer immunotherapy.

Dendritic cells (DCs) play a central role in the orchestration of effective T cell responses against tumors. However, their functional behavior is context-dependent. DC type, transcriptional program, location, intratumoral factors, and inflammatory milieu all impact DCs with regard to promoting or inhibiting tumor immunity. The following review introduces important facets of DC function, and how subset and phenotype can affect the interplay of DCs with other factors in the tumor microenvironment. It will also discuss how current cancer treatment relies on DC function, and survey the myriad ways with which immune therapy can more directly harness DCs to enact antitumor cytotoxicity.

The Value of Microbes in Cancer Neoantigen Immunotherapy.

Tumor neoantigens are widely used in cancer immunotherapy, and a growing body of research suggests that microbes play an important role in these neoantigen-based immunotherapeutic processes. The human body and its surrounding environment are filled with a large number of microbes that are in long-term interaction with the organism. The microbiota can modulate our immune system, help activate neoantigen-reactive T cells, and play a great role in the process of targeting tumor neoantigens for therapy. Recent studies have revealed the interconnection between microbes and neoantigens, which can cross-react with each other through molecular mimicry, providing theoretical guidance for more relevant studies. The current applications of microbes in immunotherapy against tumor neoantigens are mainly focused on cancer vaccine development and immunotherapy with immune checkpoint inhibitors. This article summarizes the related fields and suggests the importance of microbes in immunotherapy against neoantigens.

STMHCpan, an accurate Star-Transformer-based extensible framework for predicting MHC I allele binding peptides.

Peptide-major histocompatibility complex I (MHC I) binding affinity prediction is crucial for vaccine development, but existing methods face limitations such as small datasets, model overfitting due to excessive parameters and suboptimal performance. Here, we present STMHCPan (STAR-MHCPan), an open-source package based on the Star-Transformer model, for MHC I binding peptide prediction. Our approach introduces an attention mechanism to improve the deep learning network architecture and performance in antigen prediction. Compared with classical deep learning algorithms, STMHCPan exhibits improved performance with fewer parameters in receptor affinity training. Furthermore, STMHCPan outperforms existing ligand benchmark datasets identified by mass spectrometry. It can also handle peptides of arbitrary length and is highly scalable for predicting T-cell responses. Our software is freely available for use, training and extension through Github (https://github.com/Luckysoutheast/STMHCPan.git).

In-situ tumor vaccination by percutaneous ablative therapy and its synergy with immunotherapeutics: An update on combination therapy.

Percutaneous tumor ablation is now a widely accepted minimally invasive local treatment option offered by interventional radiology and applied to various organs and tumor histology types. It utilizes extreme temperatures to achieve irreversible cellular injury, where ablated tumor interacts with surrounding tissue and host via tissue remodeling and inflammation, clinically manifesting as post-ablation syndrome. During this process, in-situ tumor vaccination occurs, in which tumor neoantigens are released from ablated tissue and can prime one's immune system which would favorably affect both local and remote site disease control. Although successful in priming the immune system, this rarely turns into clinical benefits for local and systemic tumor control due to intrinsic negative immune modulation of the tumor microenvironment. A combination of ablation and immunotherapy has been employed to overcome these and has shown promising preliminary results of synergistic effect without significantly increased risk profiles. The aim of this article is to review the evidence on post-ablation immune response and its synergy with systemic immunotherapies.

Immunotherapies targeting neoantigens are effective in PD-1 blockade-resistant tumors.

Only a small fraction of tumor-infiltrating lymphocytes can specifically recognize and attack cancer cells in PD-1/PD-L1 blockade therapy. Here, we investigate approaches to expand the neoantigen-specific CD8+ T cells to overcome the difficulties in treating PD-1/PD-L1 blockade-resistant tumors. Mutation-associated neoepitopes of murine nonsmall cell lung cancer ASB-XIV were estimated by whole-exome and RNA sequencing and predicted by MHC-I binding affinity (FPKM >1) in silico. Using ASB-XIV-specific CD8+ T cells, we screened a panel of 257 neoepitope peptides derived from ASB-XIV missense and indel mutations. Mutated Phf3 peptide (mPhf3) was successfully identified as an immunogenic neoepitope. Prophylactic mPhf3-DC vaccination inhibited ASB-XIV tumor growth through CD8+ T cell-mediated antitumor immunity. Combining the mPhf3-DC vaccine and anti-PD-1 treatment elicited robust antitumor activity through the induction of mPhf3-specific CD8+ T cells in the tumor microenvironment. Furthermore, the adoptive transfer of mPhf3-specific CD8+ T cells eradicated ASB-XIV tumors. Likewise, the combination of mutated Cdt1 peptide (mCdt1)-DC vaccine and anti-PD-1 treatment or adoptive transfer of mCdt1-specific CD8+ T cells also led to significant regression of PD-1 blockade-resistant murine gastric YTN16 tumors. In conclusion, a novel immunogenic neoepitope of ASB-XIV was identified for immunotherapy targeting neoantigens. Identification of immunogenic neoantigens can extend the therapeutic strategies by increasing the frequency of neoantigen-specific T cells, even for PD-1/PD-L1 blockade-resistant tumors.

MediMer: a versatile do-it-yourself peptide-receptive MHC class I multimer platform for tumor neoantigen-specific T cell detection.

Peptide-loaded MHC class I (pMHC-I) multimers have revolutionized our capabilities to monitor disease-associated T cell responses with high sensitivity and specificity. To improve the discovery of T cell receptors (TCR) targeting neoantigens of individual tumor patients with recombinant MHC molecules, we developed a peptide-loadable MHC class I platform termed MediMer. MediMers are based on soluble disulfide-stabilized ß2-microglobulin/heavy chain ectodomain single-chain dimers (dsSCD) that can be easily produced in large quantities in eukaryotic cells and tailored to individual patients' HLA allotypes with only little hands-on time. Upon transient expression in CHO-S cells together with ER-targeted BirA biotin ligase, biotinylated dsSCD are purified from the cell supernatant and are ready to use. We show that CHO-produced dsSCD are free of endogenous peptide ligands. Empty dsSCD from more than 30 different HLA-A,B,C allotypes, that were produced and validated so far, can be loaded with synthetic peptides matching the known binding criteria of the respective allotypes, and stored at low temperature without loss of binding activity. We demonstrate the usability of peptide-loaded dsSCD multimers for the detection of human antigen-specific T cells with comparable sensitivities as multimers generated with peptide-tethered ß2m-HLA heavy chain single-chain trimers (SCT) and wild-type peptide-MHC-I complexes prior formed in small-scale refolding reactions. Using allotype-specific, fluorophore-labeled competitor peptides, we present a novel dsSCD-based peptide binding assay capable of interrogating large libraries of in silico predicted neoepitope peptides by flow cytometry in a high-throughput and rapid format. We discovered rare T cell populations with specificity for tumor neoepitopes and epitopes from shared tumor-associated antigens in peripheral blood of a melanoma patient including a so far unreported HLA-C*08:02-restricted NY-ESO-1-specific CD8+ T cell population. Two representative TCR of this T cell population, which could be of potential value for a broader spectrum of patients, were identified by dsSCD-guided single-cell sequencing and were validated by cognate pMHC-I multimer staining and functional responses to autologous peptide-pulsed antigen presenting cells. By deploying the technically accessible dsSCD MHC-I MediMer platform, we hope to significantly improve success rates for the discovery of personalized neoepitope-specific TCR in the future by being able to also cover rare HLA allotypes.

Integration of cancer stemness and neoantigen load to predict responsiveness to anti-PD1/PDL1 therapy.

Background: Anti-programmed cell death 1/programmed cell death ligand 1 (PD1/PDL1) therapy is an important part of comprehensive cancer therapy. However, many patients suffer from non-response to therapy. Tumor neoantigen burden (TNB) and cancer stemness play essential roles in the responsiveness to therapy. Therefore, the identification of drug candidates for anti-PD1/PDL1 therapy remains an unmet need. Methods: Three anti-PD1/PDL1 therapy cohorts were obtained from GEO database and published literatures. Cancer immune characteristics were analyzed using CIBERSORTX, GSVA, and ESTIMATE. WGCNA was employed to identify the gene modules correlated with cancer TNB and stemness. A machine-learning method was used to construct the immunotherapy resistance score (TSIRS). Pharmacogenomic analysis was conducted to explore the potential alternative drugs for anti-PD1/PDL1 therapy resistant patients. CCK-8 assay, EdU assay and wound healing assay were used to validate the effect of the predicted drug on cancer cells. Results: The therapy response and non-response cancer groups have different microenvironment features. TSIRS was developed based on tumor neoantigen and stemness. TSIRS can effectively predict the outcomes of patients with anti-PD1/PDL1 therapy in training, validation and meta cohorts. Meanwhile, TSIRS can reflect the characteristics of tumor microenvironment during anti-PD1/PDL1 therapy. PF-4708671 is identified as a potential alternative drug for patients with resistance to anti-PD1/PDL1 therapy. It possesses significant inhibitive effect on the proliferation and migration of BGC-823 cells. Conclusion: TSIRS is an effective tool in the identification of candidate patients who will be benefit from anti-PD1/PDL1 therapy. Small molecule drug PF-4708671 has the potential to be used in anti-PD1/PDL1 therapy resistant patients.

T Cell Recognition of Tumor Neoantigens and Insights Into T Cell Immunotherapy.

In cancer, non-synonymous DNA base changes alter protein sequence and produce neoantigens that are detected by the immune system. For immune detection, neoantigens must first be presented on class I or II human leukocyte antigens (HLA) followed by recognition by peptide-specific receptors, exemplified by the T-cell receptor (TCR). Detection of neoantigens represents a unique challenge to the immune system due to their high similarity with endogenous 'self' proteins. Here, we review insights into how TCRs detect neoantigens from structural studies and delineate two broad mechanistic categories: 1) recognition of mutated 'self' peptides and 2) recognition of novel 'non-self' peptides generated through anchor residue modifications. While mutated 'self' peptides differ only by a single amino acid from an existing 'self' epitope, mutations that form anchor residues generate an entirely new epitope, hitherto unknown to the immune system. We review recent structural studies that highlight these structurally distinct mechanisms and discuss how they may lead to differential anti-tumor immune responses. We discuss how T cells specific for neoantigens derived from anchor mutations can be of high affinity and provide insights to their use in adoptive T cell transfer-based immunotherapy.

Progress of advanced hepatocellular carcinoma adoptive cell therapy based on tumor neoantigens / 中华肝胆外科杂志

Advanced hepatocellular carcinoma has a high degree of malignancy and poor prognosis. Studies showed that there is a close relationship between the progression of hepatocellular carcinoma and the immune status in tumor microenvironment. Adoptive cell therapy showed anti-tumor effects and improve immunosuppression by infusing patients with activated specific immune cells, which become a central issue in tumor therapy and shown promising effects in the treatment of various malignant tumors, indicating great application potential. Adoptive cell therapy based on neoantigen may become a new hot spot in the treatment of hepatocellular carcinoma, and their application, safety and effectiveness evaluation, efficacy prediction and assessment have become urgent issues to be solved. The purpose of this article is to introduce the progress related to adoptive cell therapy for advanced hepatocellular carcinoma and elaborate the problems that need to be solved in the future.

Beyond Tumor Mutation Burden: Tumor Neoantigen Burden as a Biomarker for Immunotherapy and Other Types of Therapy.

Immunotherapy has significantly improved the clinical outcome of patients with cancer. However, the immune response rate varies greatly, possibly due to lack of effective biomarkers that can be used to distinguish responders from non-responders. Recently, clinical studies have associated high tumor neoantigen burden (TNB) with improved outcomes in patients treated with immunotherapy. Therefore, TNB has emerged as a biomarker for immunotherapy and other types of therapy. In the present review, the potential application of TNB as a biomarker was evaluated. The methods of neoantigen prediction were summarized and the mechanisms involved in TNB were investigated. The impact of high TNB and increased number of infiltrating immune cells on the efficacy of immunotherapy was also addressed. Finally, the future challenges of TNB were discussed.

T-Cell Receptor Therapy in the Treatment of Ovarian Cancer: A Mini Review.

Ovarian cancer, in particularly high-grade serous ovarian cancer (HGSOC) and ovarian carcinosarcoma (OCS), are highly aggressive and deadly female cancers with limited treatment options. These tumors are generally unresponsive to immune check-point inhibitor (ICI) therapy and are referred to as immunologically "cold" tumors. Cell-based therapy, in particular, adoptive T-cell therapy, is an alternative immunotherapy option that has shown great potential, especially chimeric antigen receptor T cell (CAR-T) therapy in the treatment of hematologic malignancies. However, the efficacy of CAR-T therapy in solid tumors has been modest. This review explores the potential of another cell-based therapy, T-cell receptor therapy (TCR-T) as an alternate treatment option for immunological "cold" OC and OCS tumors.

The clinical prognostic value of PD-L1 after concurrent chemoradiotherapy in Chinese nasopharyngeal carcinoma patients.

BACKGROUND: Although immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of nasopharyngeal carcinoma (NPC), it is still the second- or third-line treatment after the failure of radiotherapy or chemotherapy. In this study, we aimed to investigate the impact of concurrent chemoradiotherapy (CCRT) on programmed death-ligand 1 (PD-L1) protein expression in NPC patients. METHODS: We enrolled 24 NPC patients treated with intensity-modulated radiation therapy (IMRT) combined with cisplatin CCRT. PD-L1 expression was evaluated by immunohistochemistry, and next-generation sequencing and annotation were performed to determine the genetic alteration after CCRT. RESULTS: Our results showed that patients with a high expression of PD-L1 were more inclined to a complete response (CR) to chemoradiotherapy, as opposed to a partial response (PR) (P<0.05). Moreover, the mean values of the tumor mutation burden (TMB) and the tumor neoantigen burden (TNB) in the PD-L1 positive group were significantly lower than that of the PD-L1 negative group in our cohort. CONCLUSIONS: We confirmed that the TMB and TNB may be potential clinical indicators in NPC treatment, and PD-L1 expression may be a clinical biomarker in NPC chemoradiotherapy. Finally, through next-generation sequencing and annotation, we found that the most frequent driver gene mutations in NPC were TET2, TP53, and MAPK.

Characterization of Somatic Mutations That Affect Neoantigens in Non-Small Cell Lung Cancer.

Purpose: Immune checkpoint inhibitors (ICIs) have recently emerged as an important option for treating patients with advanced non-small cell lung cancer (NSCLC). Neoantigens are important biomarkers and potential immunotherapy targets that play important roles in the prognosis and treatment of patients with NSCLC. This study aimed to evaluate and characterize the relationships between somatic mutations and potential neoantigens in specimens from patients who underwent surgical treatment for NSCLC. Patients and Methods: This prospective study evaluated specimens from patients with NSCLC who underwent surgical treatment at the Peking Union Medical College, China, from June 2019 to September 2019. Whole-exome sequencing was performed for tumor tissues and corresponding normal tissues. Candidate neoantigens were predicted using generative software, and the relationships between various mutation characteristics and number of neoantigens were evaluated. Results: Neoantigen-related gene mutations were less frequent than mutations affecting the whole genome. Genes with high neoantigen burden had more types and higher frequencies of mutations. The number of candidate neoantigens was positively correlated with missense mutations, code shift insertions/deletions, split-site variations, and nonsense mutations. However, in the multiple linear regression analysis, only missense mutations were positively correlated with the number of neoantigens. The number of neoantigens was also positively correlated with base transversions (A>C/C>A, T>G/G>T, and C>G/G>C) and negatively correlated with base transitions (A>G/G>A and C>T/T>C). Conclusion: The number of candidate neoantigens in NSCLC specimens was associated with mutation frequency, type of mutation, and type of base substitution.

Personalized Cancer Vaccines: Clinical Landscape, Challenges, and Opportunities.

Tremendous innovation is underway among a rapidly expanding repertoire of promising personalized immune-based treatments. Therapeutic cancer vaccines (TCVs) are attractive systemic immunotherapies that activate and expand antigen-specific CD8+ and CD4+ T cells to enhance anti-tumor immunity. Our review highlights key issues impacting TCVs in clinical practice and reports on progress in development. We review the mechanism of action, immune-monitoring, dosing strategies, combinations, obstacles, and regulation of cancer vaccines. Most trials of personalized TCVs are ongoing and represent diverse platforms with predominantly early investigations of mRNA, DNA, or peptide-based targeting strategies against neoantigens in solid tumors, with many in combination immunotherapies. Multiple delivery systems, routes of administration, and dosing strategies are used. Intravenous or intramuscular administration is common, including delivery by lipid nanoparticles. Absorption and biodistribution impact antigen uptake, expression, and presentation, affecting the strength, speed, and duration of immune response. The emerging trials illustrate the complexity of developing this class of innovative immunotherapies. Methodical testing of the multiple potential factors influencing immune responses, as well as refined quantitative methodologies to facilitate optimal dosing strategies, could help resolve uncertainty of therapeutic approaches. To increase the likelihood of success in bringing these medicines to patients, several unique development challenges must be overcome.

The Immunogenic Potential of Recurrent Cancer Drug Resistance Mutations: An In Silico Study.

Cancer somatic mutations have been identified as a source of antigens that can be targeted by cancer immunotherapy. In this work, expanding on previous studies, we analyze the HLA-presentation properties of mutations that are known to drive resistance to cancer targeted-therapies. We survey a large dataset of mutations that confer resistance to different drugs and occur in numerous genes and tumor types. We show that a significant number of them are predicted in silico to be potentially immunogenic across a large proportion of the human population. Further, by analyzing a cohort of patients carrying a small subset of these resistance mutations, we provide evidence that what is observed in the general population may be indicative of the mutations' immunogenic potential in resistant patients. Two of the mutations in our dataset had previously been experimentally validated by others and it was confirmed that some of their associated neopeptides elicit T-cell responses in vitro. The identification of potent cancer-specific antigens can be instrumental for developing more effective immunotherapies. In this work, we propose a novel list of drug-resistance mutations, several of which are recurrent, that could be of particular interest in the context of off-the-shelf precision immunotherapies such as therapeutic cancer vaccines.

Molecular Profiles of Breast Cancer in a Single Institution.

BACKGROUND/AIM: Historically, breast cancer has been treated according to an evaluation of biomarkers, such as the estrogen receptor and HER2 status. Recently, molecular profiling has been used to detect driver mutations and select anti-cancer treatment strategies. In addition to detecting pathogenic mutations, the total mutation count (tumor mutation burden) has been considered as another biomarker. MATERIALS AND METHODS: We performed molecular profiling of 143 breast cancer tissues obtained from resected tissues via surgical operation. RESULTS: Suspected germline mutations were detected in 10% of the patients with a higher somatic mutation ratio. CONCLUSION: As hypermutated breast cancers are more likely to benefit from certain anti-cancer treatment strategies, molecular profiling can be used as a biomarker.

Combination Strategies for Immune-Checkpoint Blockade and Response Prediction by Artificial Intelligence.

The therapeutic concept of unleashing a pre-existing immune response against the tumor by the application of immune-checkpoint inhibitors (ICI) has resulted in long-term survival in advanced cancer patient subgroups. However, the majority of patients do not benefit from single-agent ICI and therefore new combination strategies are eagerly necessitated. In addition to conventional chemotherapy, kinase inhibitors as well as tumor-specific vaccinations are extensively investigated in combination with ICI to augment therapy responses. An unprecedented clinical outcome with chimeric antigen receptor (CAR-)T cell therapy has led to the approval for relapsed/refractory diffuse large B cell lymphoma and B cell acute lymphoblastic leukemia whereas response rates in solid tumors are unsatisfactory. Immune-checkpoints negatively impact CAR-T cell therapy in hematologic and solid malignancies and as a consequence provide a therapeutic target to overcome resistance. Established biomarkers such as programmed death ligand 1 (PD-L1) and tumor mutational burden (TMB) help to select patients who will benefit most from ICI, however, biomarker negativity does not exclude responses. Investigating alterations in the antigen presenting pathway as well as radiomics have the potential to determine tumor immunogenicity and response to ICI. Within this review we summarize the literature about specific combination partners for ICI and the applicability of artificial intelligence to predict ICI therapy responses.

The Immunogenicity and Anti-tumor Efficacy of a Rationally Designed Neoantigen Vaccine for B16F10 Mouse Melanoma.

Tumor neoantigens are ideal targets for cancer immunotherapy as they are recognized by host immune system as foreigners and can elicit tumor-specific immune responses. However, existing strategies utilizing RNA or long peptides for the neoantigen vaccines render limited immune responses since only 20-30% of neoantigens predicted in silico to bind MHC I molecules are capable of eliciting immune responses with the majority of responding T cells are CD4+. Therefore, it warrants further exploration to enhance neoantigen-specific CD8+ T cells responses. Since neoantigens are naturally weak antigens, we asked whether foreign T help epitopes could enhance their immunogenicity. In present study, we chose 4 weak B16F10 neoantigens as vaccine targets, and fused them to the transmembrane domain of diphtheria toxin, namely DTT-neoAg. Strikingly, the vaccine elicited anti-tumor CD8+ T cells responses and enhanced tumor infiltration of both T cells and NK cells. Impressively, DTT-neoAg vaccine significantly deterred tumor growth with the inhibition rate reached 88% in the preventive model and 100% in the therapeutic model at low dose of tumor challenge. Furthermore, after second challenge with higher dose of tumor cells, 33.3% of the immunized mice remained tumor-free for 6 months in the therapeutic model. Because DTT is a non-toxic domain of diphtheria toxin, it may be not of great concern in terms of safety as a Th epitope provider. Thus, the fusion strategy employed by this study may become a feasible and powerful approach for development of personalized cancer vaccines.

Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment.

BACKGROUND: There is strong evidence that immunotherapy-mediated tumor rejection can be driven by tumor-specific CD8+ T cells reinvigorated to recognize neoantigens derived from tumor somatic mutations. Thus, the frequencies or characteristics of tumor-reactive, mutation-specific CD8+ T cells could be used as biomarkers of an anti-tumor response. However, such neoantigen-specific T cells are difficult to reliably identify due to their low frequency in peripheral blood and wide range of potential epitope specificities. METHODS: Peripheral blood mononuclear cells (PBMC) from 14 non-small cell lung cancer (NSCLC) patients were collected pre- and post-treatment with the anti-PD-L1 antibody atezolizumab. Using whole exome sequencing and RNA sequencing we identified tumor neoantigens that are predicted to bind to major histocompatibility complex class I (MHC-I) and utilized mass cytometry, together with cellular 'barcoding', to profile immune cells from patients with objective response to therapy (n = 8) and those with progressive disease (n = 6). In parallel, a highly-multiplexed combinatorial tetramer staining was used to screen antigen-specific CD8+ T cells in peripheral blood for 782 candidate tumor neoantigens and 71 known viral-derived control peptide epitopes across all patient samples. RESULTS: No significant treatment- or response associated phenotypic difference were measured in bulk CD8+ T cells. Multiplexed peptide-MHC multimer staining detected 20 different neoantigen-specific T cell populations, as well as T cells specific for viral control antigens. Not only were neoantigen-specific T cells more frequently detected in responding patients, their phenotypes were also almost entirely distinct. Neoantigen-specific T cells from responder patients typically showed a differentiated effector phenotype, most like Cytomegalovirus (CMV) and some types of Epstein-Barr virus (EBV)-specific CD8+ T cells. In contrast, more memory-like phenotypic profiles were observed for neoantigen-specific CD8+ T cells from patients with progressive disease. CONCLUSION: This study demonstrates that neoantigen-specific T cells can be detected in peripheral blood in non-small cell lung cancer (NSCLC) patients during anti-PD-L1 therapy. Patients with an objective response had an enrichment of neoantigen-reactive T cells and these cells showed a phenotype that differed from patients without a response. These findings suggest the ex vivo identification, characterization, and longitudinal follow-up of rare tumor-specific differentiated effector neoantigen-specific T cells may be useful in predicting response to checkpoint blockade. TRIAL REGISTRATION: POPLAR trial NCT01903993 .

[A new bioinformatics approach for prediction of potential tumor neoantigens based on the cancer genome atlas dataset].

Tumor-specific gene mutations might generate suitable neoepitopes for cancer immunotherapy that are highly immunogenic and absent in normal tissues. The high heterogeneity of the tumor genome poses a big challenge for precision cancer immunotherapy. Mutations characteristic of each tumor can help to distinguish it from other tumors. Based on these mutations' characteristic, it is possible to develop immunotherapeutic strategies for specific tumors. In this study, a tumor neoantigen prediction scheme was proposed, in which both the intracellular antigen presentation process and the ability to bind with extracellular MHC molecule were taken into consideration. The overall design is meritorious and may help reduce the cost for validation experiments compared with conventional methods. This strategy was tested with several cancer genome datasets in the TCGA database, and a number of potential tumor neoantigens were predicted for each dataset. These predicted neoantigens showed tumor type specificity and were found in 20% to 70% of cancer patients. This scheme might prove useful clinically in future.