Unique Neoantigens Arise from Somatic Mutations in Patients with Gastrointestinal Cancers

Cancer systems immunology

Tumor immunology is undergoing a renaissance due to the recent profound clinical successes of tumor immunotherapy. These advances have coincided with an exponential growth in the development of -omics technologies. Armed with these technologies and their associated computational and modeling toolsets, systems biologists have turned their attention to tumor immunology in an effort to understand the precise nature and consequences of interactions between tumors and the immune system. Such interactions are inherently multivariate, spanning multiple time and size scales, cell types, and organ systems, rendering systems biology approaches particularly amenable to their interrogation. While in its infancy, the field of 'Cancer Systems Immunology' has already influenced our understanding of tumor immunology and immunotherapy. As the field matures, studies will move beyond descriptive characterizations toward functional investigations of the emergent behavior that govern tumor-immune responses. Thus, Cancer Systems Immunology holds incredible promise to advance our ability to fight this disease.

The Landscape of Tumor-Specific Antigens in Colorectal Cancer

Over the last few decades, major efforts in cancer research and treatment have intensified. Apart from standard chemotherapy approaches, immunotherapy has gained substantial traction. Personalized immunotherapy has become an important tool for cancer therapy with the discovery of immune checkpoint inhibitors. Traditionally, tumor-associated antigens are used in immunotherapy-based treatments. Nevertheless, these antigens lack specificity and may have increased toxicity. With the advent of next-generation technologies, the identification of new tumor-specific antigens is becoming more important. In colorectal cancer, several tumor-specific antigens were identified and functionally validated. Multiple clinical trials from vaccine-based and adoptive cell therapy utilizing tumor-specific antigens have commenced. Herein, we will summarize the current landscape of tumor-specific antigens particularly in colorectal cancer.

Towards new horizons: characterization, classification and implications of the tumour antigenic repertoire

Immune-checkpoint inhibition provides an unmatched level of durable clinical efficacy in various malignancies. Such therapies promote the activation of antigen-specific T cells, although the precise targets of these T cells remain unknown. Exploiting these targets holds great potential to amplify responses to treatment, such as by combining immune-checkpoint inhibition with therapeutic vaccination or other antigen-directed treatments. In this scenario, the pivotal hurdle remains the definition of valid HLA-restricted tumour antigens, which requires several levels of evidence before targets can be established with sufficient confidence. Suitable antigens might include tumour-specific antigens with alternative or wild-type sequences, tumour-associated antigens and cryptic antigens that exceed exome boundaries. Comprehensive antigen classification is required to enable future clinical development and the definition of innovative treatment strategies. Furthermore, clinical development remains challenging with regard to drug manufacturing and regulation, as well as treatment feasibility. Despite these challenges, treatments based on diligently curated antigens combined with a suitable therapeutic platform have the potential to enable optimal antitumour efficacy in patients, either as monotherapies or in combination with other established immunotherapies. In this Review, we summarize the current state-of-the-art approaches for the identification of candidate tumour antigens and provide a structured terminology based on their underlying characteristics.

Immune-checkpoint inhibition has transformed the treatment of patients with advanced-stage cancers. Nonetheless, the specific antigens targeted by T cells that are activated or reactivated by these agents remain largely unknown. In this Review, the authors describe the characterization and classification of tumour antigens including descriptions of the most appropriate detection methods, and discuss potential regulatory issues regarding the use of tumour antigen-based therapeutics.

Immune-checkpoint inhibition has profoundly changed the paradigm for the care of several malignancies. Although these therapies activate antigen-specific T cells, the precise mechanisms of action and their specific targets remain largely unknown.

Anticancer immunotherapies encompass two fundamentally different therapeutic principles based on knowledge of their therapeutic targets, that either have been characterized (antigen-aware) or have remained elusive (antigen-unaware).

HLA-presented tumour antigens of potential therapeutic relevance can comprise alternative or wild-type amino acid sequences and can be subdivided into different categories based on their mechanisms of formation.

The available methods for the detection of HLA-presented antigens come with intrinsic challenges and limitations and, therefore, warrant multiple lines of evidence of robust tumour specificity before being considered for clinical use.

Knowledge obtained using various antigen-detection strategies can be combined with different therapeutic platforms to create individualized therapies that hold great promise, including when combined with already established immunotherapies.

Tailoring immunotherapies while taking into account the substantial heterogeneity of malignancies as well as that of HLA loci not only requires innovative science, but also demands innovative approaches to trial design and drug regulation.

Engineering Polymeric Prodrug Nanoplatform for Vaccination Immunotherapy of Cancer

Neoantigen-based cancer vaccines are promising for boosting cytotoxic T lymphocyte (CTL) responses. However, the therapeutic effect of cancer vaccines is severely blunted by functional suppression of the dendritic cells (DCs). Herein, we demonstrated an acid-responsive polymeric nanovaccine for activating the stimulator of interferon genes (STING) pathway and improving cancer immunotherapy. The nanovaccines were fabricated by integrating an acid-activatable polymeric conjugate of the STING agonist and neoantigen into one single nanoplatform. The nanovaccines efficiently accumulated at the lymph nodes for promoting DC uptake and facilitating cytosol release of the neoantigens. Meanwhile, the STING agonist activated the STING pathway in the DCs to elicit interferon-β secretion and to boost T-cell priming with the neoantigen. The nanovaccine dramatically inhibited tumor growth and occurrence of B16-OVA melanoma and 4T1 breast tumors in immunocompetent mouse models. Combination immunotherapy with the nanovaccines and anti-PD-L1 antibody demonstrated further improved antitumor efficacy in a 4T1 breast tumor model.

Structural basis for oligoclonal T cell recognition of a shared p53 cancer neoantigen

Adoptive cell therapy (ACT) with tumor-specific T cells can mediate cancer regression. The main target of tumor-specific T cells are neoantigens arising from mutations in self-proteins. Although the majority of cancer neoantigens are unique to each patient, and therefore not broadly useful for ACT, some are shared. We studied oligoclonal T-cell receptors (TCRs) that recognize a shared neoepitope arising from a driver mutation in the p53 oncogene (p53R175H) presented by HLA-A2. Here we report structures of wild-type and mutant p53-HLA-A2 ligands, as well as structures of three tumor-specific TCRs bound to p53R175H-HLA-A2. These structures reveal how a driver mutation in p53 rendered a self-peptide visible to T cells. The TCRs employ structurally distinct strategies that are highly focused on the mutation to discriminate between mutant and wild-type p53. The TCR-p53R175H-HLA-A2 complexes provide a framework for designing TCRs to improve potency for ACT without sacrificing specificity.

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 Outcome of Ex Vivo TIL Expansion Is Highly Influenced by Spatial Heterogeneity of the Tumor T-Cell Repertoire and Differences in Intrinsic In Vitro Growth Capacity between T-Cell Clones

PURPOSE

During our efforts to develop tumor-infiltrating lymphocyte (TIL) therapy to counter the devastating recurrence rate in patients with primary resectable pancreatic ductal adenocarcinoma (PDA), we found that PDA TILs can readily be expanded in vitro and that the majority of resulting TIL cultures show reactivity against the autologous tumor. However, the fraction of tumor-reactive T cells is low. We investigated to which extent this was related to the in vitro expansion.

EXPERIMENTAL DESIGN

We compared the clonal composition of TIL preparations before and after in vitro expansion using T-cell receptor (TCR) deep sequencing. Our findings for PDA were benchmarked to experiments with melanoma TILs.

RESULTS

We found that the TIL TCR repertoire changes dramatically during in vitro expansion, leading to loss of tumor- dominant T-cell clones and overgrowth by newly emerging T-cell clones that are barely detectable in the tumor. These changes are primarily driven by differences in the intrinsic in vitro expansion capacity of T-cell clones. Single-cell experiments showed an association between poor proliferative capacity and expression of markers related to antigen experience and dysfunction. Furthermore, we found that spatial heterogeneity of the TIL repertoire resulted in TCR repertoires that are greatly divergent between TIL cultures derived from distant tumor samples of the same patient.

CONCLUSIONS

Culture-induced changes in clonal composition are likely to affect tumor reactivity of TIL preparations. TCR deep sequencing provides important insights into the factors that govern the outcome of in vitro TIL expansion and thereby a path toward optimization of the production of TIL preparations with high therapeutic efficacy.See related commentary by Lozano-Rabella and Gros, p. 4177.

Immunotherapy in Metastatic Colorectal Cancer: Could the Latest Developments Hold the Key to Improving Patient Survival?

Immunotherapy has considerably increased the number of anticancer agents in many tumor types including metastatic colorectal cancer (mCRC). Anti-PD-1 (programmed death 1) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) immune checkpoint inhibitors (ICI) have been shown to benefit the mCRC patients with mismatch repair deficiency (dMMR) or high microsatellite instability (MSI-H). However, ICI is not effective in mismatch repair proficient (pMMR) colorectal tumors, which constitute a large population of patients. Several clinical trials evaluating the efficacy of immunotherapy combined with chemotherapy, radiation therapy, or other agents are currently ongoing to extend the benefit of immunotherapy to pMMR mCRC cases. In dMMR patients, MSI testing through immunohistochemistry and/or polymerase chain reaction can be used to identify patients that will benefit from immunotherapy. Next-generation sequencing has the ability to detect MSI-H using a low amount of nucleic acids and its application in clinical practice is currently being explored. Preliminary data suggest that radiomics is capable of discriminating MSI from microsatellite stable mCRC and may play a role as an imaging biomarker in the future. Tumor mutational burden, neoantigen burden, tumor-infiltrating lymphocytes, immunoscore, and gastrointestinal microbiome are promising biomarkers that require further investigation and validation.

Adoptive Cell Therapy: A Novel and Potential Immunotherapy for Glioblastoma

Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults with very poor prognosis and few advances in its treatment. Recently, fast-growing cancer immunotherapy provides a glimmer of hope for GBM treatment. Adoptive cell therapy (ACT) aims at infusing immune cells with direct anti-tumor activity, including tumor-infiltrating lymphocyte (TIL) transfer and genetically engineered T cells transfer. For example, complete regressions in patients with melanoma and refractory lymphoma have been shown by using naturally tumor-reactive T cells and genetically engineered T cells expressing the chimeric anti-CD19 receptor, respectively. Recently, the administration of ACT showed therapeutic potentials for GBM treatment as well. In this review, we summarize the success of ACT in the treatment of cancer and provide approaches to overcome some challenges of ACT to allow its adoption for GBM treatment.

Antigen Experienced T Cells from Peripheral Blood Recognize p53 Neoantigens

PURPOSE

The purpose of this study was to evaluate antigen experienced T cells in peripheral blood lymphocytes (PBL) for responses to p53 neoantigens.

EXPERIMENTAL DESIGN

PBLs from patients with a mutated TP53 tumor were sorted for antigen-experienced T cells and in vitro stimulation (IVS) was performed with p53 neoantigens. The IVS cultures were stimulated with antigen-presenting cells expressing p53 neoantigens, enriched for 41BB/OX40 and grown with rapid expansion protocol.

RESULTS

T-cell responses were not observed in the PBLs of 4 patients who did not have tumor-infiltrating lymphocyte (TIL) responses to mutated TP53. In contrast, 5 patients with TIL responses to mutated TP53 also had similar T-cell responses in their PBLs, indicating that the PBLs and TILs were congruent in p53 neoantigen reactivity. CD4⁺ and CD8⁺ T cells were specific for p53^R175H, p53^Y220C, or p53^R248W neoantigens, including a 78% reactive T-cell culture against p53^R175H and HLA-A*02:01. Tracking TCRB clonotypes (clonality, top ranked, and TP53 mutation-specific) supported the enrichment of p53 neoantigen-reactive T cells from PBLs. The same T-cell receptor (TCR) from the TIL was found in the IVS cultures in three cases and multiple unique TCRs were found in another patient. TP53 mutation-specific T cells also recognized tumor cell lines bearing the appropriate human leukocyte antigen restriction element and TP53 mutation, indicating these T cells could recognize processed and presented p53 neoantigens.

CONCLUSIONS

PBL was a noninvasive source of T cells targeting TP53 mutations for cell therapy and can provide a window into intratumoral p53 neoantigen immune responses.See related commentary by Olivera et al., p. 1203.

Neoantigen-specific immunity in low mutation burden colorectal cancers of the consensus molecular subtype 4

Background

The efficacy of checkpoint blockade immunotherapies in colorectal cancer is currently restricted to a minority of patients diagnosed with mismatch repair-deficient tumors having high mutation burden. However, this observation does not exclude the existence of neoantigen-specific T cells in colorectal cancers with low mutation burden and the exploitation of their anti-cancer potential for immunotherapy. Therefore, we investigated whether autologous neoantigen-specific T cell responses could also be observed in patients diagnosed with mismatch repair-proficient colorectal cancers.

Methods

Whole-exome and transcriptome sequencing were performed on cancer and normal tissues from seven colorectal cancer patients diagnosed with mismatch repair-proficient tumors to detect putative neoantigens. Corresponding neo-epitopes were synthesized and tested for recognition by in vitro expanded T cells that were isolated from tumor tissues (tumor-infiltrating lymphocytes) and from peripheral mononuclear blood cells stimulated with tumor material.

Results

Neoantigen-specific T cell reactivity was detected to several neo-epitopes in the tumor-infiltrating lymphocytes of three patients while their respective cancers expressed 15, 21, and 30 non-synonymous variants. Cell sorting of tumor-infiltrating lymphocytes based on the co-expression of CD39 and CD103 pinpointed the presence of neoantigen-specific T cells in the CD39⁺CD103⁺ T cell subset. Strikingly, the tumors containing neoantigen-reactive TIL were classified as consensus molecular subtype 4 (CMS4), which is associated with TGF-β pathway activation and worse clinical outcome.

Conclusions

We have detected neoantigen-targeted reactivity by autologous T cells in mismatch repair-proficient colorectal cancers of the CMS4 subtype. These findings warrant the development of specific immunotherapeutic strategies that selectively boost the activity of neoantigen-specific T cells and target the TGF-β pathway to reinforce T cell reactivity in this patient group.

High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets

Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on in silico estimation of MHC binding affinity and are limited by low predictive value for actual peptide presentation, inadequate support for rare MHC alleles, and poor scalability to high-throughput data sets. To address these limitations, we developed MHCnuggets, a deep neural network method that predicts peptide-MHC binding. MHCnuggets can predict binding for common or rare alleles of MHC class I or II with a single neural network architecture. Using a long short-term memory network (LSTM), MHCnuggets accepts peptides of variable length and is faster than other methods. When compared with methods that integrate binding affinity and MHC-bound peptide (HLAp) data from mass spectrometry, MHCnuggets yields a 4-fold increase in positive predictive value on independent HLAp data. We applied MHCnuggets to 26 cancer types in The Cancer Genome Atlas, processing 26.3 million allele-peptide comparisons in under 2.3 hours, yielding 101,326 unique predicted immunogenic missense mutations (IMM). Predicted IMM hotspots occurred in 38 genes, including 24 driver genes. Predicted IMM load was significantly associated with increased immune cell infiltration (P < 2 × 10^-16), including CD8⁺ T cells. Only 0.16% of predicted IMMs were observed in more than 2 patients, with 61.7% of these derived from driver mutations. Thus, we describe a method for neoantigen prediction and its performance characteristics and demonstrate its utility in data sets representing multiple human cancers.

A Non-interventional Clinical Trial Assessing Immune Responses After Radiofrequency Ablation of Liver Metastases From Colorectal Cancer

Background: Radiofrequency ablation (RFA) is an established treatment option for malignancies located in the liver. RFA-induced irreversible coagulation necrosis leads to the release of danger signals and cellular content. Hence, RFA may constitute an endogenous in situ tumor vaccination, stimulating innate and adaptive immune responses, including tumor-antigen specific T cells. This may explain a phenomenon termed abscopal effect, namely tumor regression in untreated lesions evidenced after distant thermal ablation or irradiation. In this study, we therefore assessed systemic and local immune responses in individual patients treated with RFA.

Methods: For this prospective clinical trial, patients with liver metastasis from colorectal carcinoma (mCRC) receiving RFA and undergoing metachronous liver surgery for another lesion were recruited (n = 9) during a 5-year period. Tumor and non-malignant liver tissue samples from six patients were investigated by whole transcriptome sequencing and tandem-mass spectrometry, characterizing naturally presented HLA ligands. Tumor antigen-derived HLA-restricted peptides were selected by different predefined approaches. Further, candidate HLA ligands were manually curated. Peripheral blood mononuclear cells were stimulated in vitro with epitope candidate peptides, and functional T cell responses were assessed by intracellular cytokine staining. Immunohistochemical markers were additionally investigated in surgically resected mCRC from patients treated with (n = 9) or without RFA (n = 7).

Results: In all six investigated patients, either induced immune responses and/or pre-existing T cell immunity against the selected targets were observed. Multi-cytokine responses were inter alia directed against known tumor antigens such as cyclin D1 but also against a (predicted) mutation contained in ERBB3. Immunohistochemistry did not show a relevant influx of immune cells into distant malignant lesions after RFA treatment (n = 9) as compared to the surgery only mCRC group (n = 7).

Conclusions: Using an individualized approach for target selection, RFA induced and/or boosted T cell responses specific for individual tumor antigens were more frequently detectable as compared to previously published observations with well-characterized tumor antigens. However, the witnessed modest RFA-induced immunological effects alone may not be sufficient for the rejection of established tumors. Therefore, these findings warrant further clinical investigation including the assessment of RFA combination therapies e.g., with immune stimulatory agents, cancer vaccination, and/or immune checkpoint inhibitors.

The Cancer Immunotherapy Biomarker Testing Landscape

CONTEXT.—

Cancer immunotherapy provides unprecedented rates of durable clinical benefit to late-stage cancer patients across many tumor types, but there remains a critical need for biomarkers to accurately predict clinical response. Although some cancer immunotherapy tests are associated with approved therapies and considered validated, other biomarkers are still emerging and at various states of clinical and translational exploration.

OBJECTIVE.—

To provide pathologists with a current and practical update on the evolving field of cancer immunotherapy testing. The scientific background, clinical data, and testing methodology for the following cancer immunotherapy biomarkers are reviewed: programmed death ligand-1 (PD-L1), mismatch repair, microsatellite instability, tumor mutational burden, polymerase δ and ε mutations, cancer neoantigens, tumor-infiltrating lymphocytes, transcriptional signatures of immune responsiveness, cancer immunotherapy resistance biomarkers, and the microbiome.

DATA SOURCES.—

Selected scientific publications and clinical trial data representing the current field of cancer immunotherapy.

CONCLUSIONS.—

The cancer immunotherapy field, including the use of biomarker testing to predict patient response, is still in evolution. PD-L1, mismatch repair, and microsatellite instability testing are helping to guide the use of US Food and Drug Administration-approved therapies, but there remains a need for better predictors of response and resistance. Several categories of tumor and patient characteristics underlying immune responsiveness are emerging and may represent the next generation of cancer immunotherapy predictive biomarkers. Pathologists have important roles and responsibilities as the field of cancer immunotherapy continues to develop, including leadership of translational studies, exploration of novel biomarkers, and the accurate and timely implementation of newly approved and validated companion diagnostics.

Immunogenomics of Colorectal Tumors: Facts and Hypotheses on an Evolving Saga

Immunotherapy with immune checkpoint inhibitors is an approved treatment option for a subpopulation of patients with colorectal cancers that display microsatellite instability. However, not all individuals within this subgroup respond to immunotherapy, and molecular biomarkers for effective patient stratification are still lacking. In this opinion article, we provide an overview of the different biological parameters that contribute to rendering colorectal cancers with microsatellite instability potentially sensitive to immunotherapy. We critically discuss the reasons why such parameters have limited predictive value and the implications therein. We also consider that a more informed knowledge of response determinants in this tumor subtype could help understand the mechanisms of immunotherapy resistance in microsatellite stable tumors. We conclude that the dynamic nature of the interactions between cancer and immune cells complicates conventional biomarker development and argue that a new generation of adaptive metrics, borrowed from evolutionary genetics, may improve the effectiveness and reliability of clinical decision making.

Single-Cell Transcriptome Analysis Reveals Gene Signatures Associated with T-cell Persistence Following Adoptive Cell Therapy

Adoptive cell therapy (ACT) using tumor-infiltrating lymphocytes (TIL) can mediate responses in some patients with metastatic epithelial cancer. Identifying gene signatures associated with successful ACT might enable the development of improved therapeutic approaches. The persistence of transferred T cells in the peripheral blood is one indication of clinical effectiveness, but many T-cell and host factors may influence T-cell persistence. To limit these variables, we previously studied a patient with metastatic colorectal cancer treated with polyclonal TILs targeting the KRAS(G12D) hotspot mutation, who experienced a partial response for 9 months. Three dominant clonotypes specifically recognizing KRAS(G12D) epitopes were identified, but we found that only two clonotypes persisted 40 days after ACT. Because of these findings, in this study, we performed the single-cell transcriptome analysis of the infused TILs. The analysis revealed a total of 472 genes that were differentially expressed between clonotypes 9.1-NP and 9.2-P single cells, and 528 genes between 9.1-NP and 10-P. Following these clonotypes in the peripheral blood after ACT, the gene expression patterns changed, but IL7R, ITGB1, KLF2, and ZNF683 remained expressed in the persistent 9.2-P and 10-P cells, compared with the nonpersistent 9.1-NP cells. In addition, four autologous TILs, which were used for treatment but persisted poorly 1 month after ACT, did not express the gene profiles associated with persistence. These results suggest that certain TIL populations possess a unique gene expression profile that can lead to the persistence of T cells. Thus, this single-patient study provides insight into how to improve ACT for solid cancer.

pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

BACKGROUND

Cancer neoantigens are expressed only in cancer cells and presented on the tumor cell surface in complex with major histocompatibility complex (MHC) class I proteins for recognition by cytotoxic T cells. Accurate and rapid identification of neoantigens play a pivotal role in cancer immunotherapy. Although several in silico tools for neoantigen prediction have been presented, limitations of these tools exist.

RESULTS

We developed pTuneos, a computational pipeline for prioritizing tumor neoantigens from next-generation sequencing data. We tested the performance of pTuneos on the melanoma cancer vaccine cohort data and tumor-infiltrating lymphocyte (TIL)-recognized neopeptide data. pTuneos is able to predict the MHC presentation and T cell recognition ability of the candidate neoantigens, and the actual immunogenicity of single-nucleotide variant (SNV)-based neopeptides considering their natural processing and presentation, surpassing the existing tools with a comprehensive and quantitative benchmark of their neoantigen prioritization performance and running time. pTuneos was further tested on The Cancer Genome Atlas (TCGA) cohort data as well as the melanoma and non-small cell lung cancer (NSCLC) cohort data undergoing checkpoint blockade immunotherapy. The overall neoantigen immunogenicity score proposed by pTuneos is demonstrated to be a powerful and pan-cancer marker for survival prediction compared to traditional well-established biomarkers.

CONCLUSIONS

In summary, pTuneos provides the state-of-the-art one-stop and user-friendly solution for prioritizing SNV-based candidate neoepitopes, which could help to advance research on next-generation cancer immunotherapies and personalized cancer vaccines. pTuneos is available at https://github.com/bm2-lab/pTuneos , with a Docker version for quick deployment at https://cloud.docker.com/u/bm2lab/repository/docker/bm2lab/ptuneos .

Developing neoantigen-targeted T cell-based treatments for solid tumors

Stimulating an immune response against cancer through adoptive transfer of tumor-targeting lymphocytes has shown great promise in hematological malignancies, but clinical efficacy against many common solid epithelial cancers remains low. Targeting 'neoantigens'-the somatic mutations expressed only by tumor cells-might enable tumor destruction without causing undue damage to vital healthy tissues. Major challenges to targeting neoantigens with T cells include heterogeneity and variability in antigen processing and presentation of targets by tumors, and an incomplete understanding of which T cell qualities are essential for clinically effective therapies. Finally, the prospect of targeting somatic tumor mutations to promote T cell destruction of cancer must contend with the biology that not all tumor-expressed 'neoepitopes' actually generate neoantigens that can be functionally recognized and provoke an effective immune response. In this Review, we discuss the promise, progress and challenges for improving neoantigen-targeted T cell-based immunotherapies for cancer.

Adoptive cell therapy with tumour-infiltrating lymphocytes: the emerging importance of clonal neoantigen targets for next-generation products in non-small cell lung cancer

Immune checkpoint blockade has significantly improved clinical outcomes for patients with non-small cell lung cancer (NSCLC) and other solid tumours, but many patients do not respond and acquired resistance is common. Aspects of the tumour microenvironment linked to clinical outcomes include the proportion of tumour-infiltrating lymphocytes (TIL), tumour programmed death ligand 1 ( PD-L1) score and tumour mutation burden. Adoptive cell therapy (ACT), a technique that works by infusing ex vivo expanded T lymphocytes to increase the effector cell pool in tumours, is anticipated to become a viable therapeutic option for patients with solid tumours, akin to chimeric antigen receptor T cell (CAR-T) therapy in haematological malignancies. TIL therapy has shown durable clinical responses in heavily pre-treated patients with melanoma and other solid tumours. We review the experience of ACT with TILs and the recent evidence that clonal neoantigens might be the most relevant immunotherapeutic targets in heterogeneous solid tumours such as NSCLC. Clonal (or truncal) neoantigens arise from the earliest mutagenic events in tumour evolution, and are retained over time in all tumour cells within a patient, making them the ideal target for T cell therapy. NSCLC has one of the highest clonal mutation burdens of all cancers through exposure to carcinogens in tobacco smoke, providing a strong rationale to develop clonal neoantigen reactive T cells (cNeT) for this indication. The first treatment modality to test this concept clinically is ATL001, a cNeT product that is derived from autologous TILs and enriched for T cells specifically recognizing clonal neoantigenic epitopes by selective expansion. Clinical studies of ATL001 will commence in 2019.

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Immune checkpoint inhibitors improve outcomes in non-small cell lung cancer (NSCLC), but resistance is common.

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Adoptive cell therapy with tumour-infiltrating lymphocytes has shown durable responses in melanoma and epithelial cancers.

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Clonal neoantigens may be the most relevant immunotherapeutic targets.

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NSCLC has one of the highest clonal mutational burdens of all cancers.

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Clonal neoantigen reactive T cells are now in clinical development.

Toward in silico Identification of Tumor Neoantigens in Immunotherapy

Cancer immunotherapy includes cancer vaccination, adoptive T cell transfer (ACT) with chimeric antigen receptor (CAR) T cells, and administration of tumor-infiltrating lymphocytes and immune-checkpoint blockade such as anti-CTLA4/anti-PD1 inhibitors that can directly or indirectly target tumor neoantigens and elicit a T cell response. Accurate, rapid, and cost-effective identification of neoantigens, however, is critical for successful immunotherapy. Here, we review computational issues for neoantigen identification by summarizing the various sources of neoantigens and their identification from high-throughput sequencing data. Several opinions are presented to inspire further discussions toward improving neoantigen identification. Continuing efforts are required to improve the sensitivity and specificity of bona fide neoantigens, taking advantage of the development of high-throughput sequencing techniques for effective and personalized cancer immunotherapy.

Neoantigen vaccine: an emerging tumor immunotherapy

Genetic instability of tumor cells often leads to the occurrence of a large number of mutations, and expression of non-synonymous mutations can produce tumor-specific antigens called neoantigens. Neoantigens are highly immunogenic as they are not expressed in normal tissues. They can activate CD4+ and CD8+ T cells to generate immune response and have the potential to become new targets of tumor immunotherapy. The development of bioinformatics technology has accelerated the identification of neoantigens. The combination of different algorithms to identify and predict the affinity of neoantigens to major histocompatibility complexes (MHCs) or the immunogenicity of neoantigens is mainly based on the whole-exome sequencing technology. Tumor vaccines targeting neoantigens mainly include nucleic acid, dendritic cell (DC)-based, tumor cell, and synthetic long peptide (SLP) vaccines. The combination with immune checkpoint inhibition therapy or radiotherapy and chemotherapy might achieve better therapeutic effects. Currently, several clinical trials have demonstrated the safety and efficacy of these vaccines. Further development of sequencing technologies and bioinformatics algorithms, as well as an improvement in our understanding of the mechanisms underlying tumor development, will expand the application of neoantigen vaccines in the future.