Identification of Individual Cancer-Specific Somatic Mutations for Neoantigen-Based Immunotherapy of Lung Cancer

NSCLC: from tumorigenesis, immune checkpoint misuse to current and future targeted therapy

Non-small cell lung cancer (NSCLC) is largely promoted by a multistep tumorigenesis process involving various genetic and epigenetic alterations, which essentially contribute to the high incidence of mortality among patients with NSCLC. Clinical observations revealed that NSCLC also co-opts a multifaceted immune checkpoint dysregulation as an important driving factor in NSCLC progression and development. For example, a deregulated PI3K/AKT/mTOR pathway has been noticed in 50-70% of NSCLC cases, primarily modulated by mutations in key oncogenes such as ALK, EGFR, KRAS, and others. Additionally, genetic association studies containing patient-specific factors and local reimbursement criteria expose/reveal mutations in EGFR/ALK/ROS/BRAF/KRAS/PD-L1 proteins to determine the suitability of available immunotherapy or tyrosine kinase inhibitor therapy. Thus, the expression of such checkpoints on tumors and immune cells is pivotal in understanding the therapeutic efficacy and has been extensively studied for NSCLC treatments. Therefore, this review summarizes current knowledge in NSCLC tumorigenesis, focusing on its genetic and epigenetic intricacies, immune checkpoint dysregulation, and the evolving landscape of targeted therapies. In the context of current and future therapies, we emphasize the significance of antibodies targeting PD-1/PD-L1 and CTLA-4 interactions as the primary therapeutic strategy for immune system reactivation in NSCLC. Other approaches involving the promising potential of nanobodies, probodies, affibodies, and DARPINs targeting immune checkpoints are also described; these are under active research or clinical trials to mediate immune regulation and reduce cancer progression. This comprehensive review underscores the multifaceted nature, current state and future directions of NSCLC research and treatment.

Recent advances in neoantigen vaccines for treating non-small cell lung cancer

The breakthrough of programmed cell death protein 1 (PD-1) blockade therapy has changed the clinical treatment of non-small cell lung cancer (NSCLC) in the past few years. The success of PD-1 blockade therapy has been attributed to high tumor mutation burden and high immunogenicity of lung cancer cells. To further improve the efficacy of NSCLC immunotherapy and overcome the resistance of lung cancer cells to immune checkpoint blockade, new approaches that enhance the active immune response, such as neoantigen vaccines and cellular-based therapies, are urgently required. Neoantigens are considered ideal targets for cancer immunotherapy because of their high immunogenicity and specificity. In this mini review, we first discuss the current advances in neoantigen vaccines for treating cancers and then review the results of preclinical studies and early-phase human clinical trials of neoantigen-based therapies for NSCLC. Finally, we focus on the identification of neoantigens in patients with NSCLC and review the candidate mutations reported by recent studies and our investigations. The review concludes that, in addition to immune checkpoint blockade, approaches targeting neoantigens are promising for improving the efficacy of NSCLC immunotherapy.

The Importance of the Immune System and Molecular Cell Signaling Pathways in the Pathogenesis and Progression of Lung Cancer

Lung cancer is a disease that in recent years has become one of the greatest threats to modern society. Every year there are more and more new cases and the percentage of deaths caused by this type of cancer increases. Despite many studies, scientists are still looking for answers regarding the mechanisms of lung cancer development and progression, with particular emphasis on the role of the immune system. The aim of this literature review was to present the importance of disorders of the immune system and the accompanying changes at the level of cell signaling in the pathogenesis of lung cancer. The collected results showed that in the process of immunopathogenesis of almost all subtypes of lung cancer, changes in the tumor microenvironment, deregulation of immune checkpoints and abnormalities in cell signaling pathways are involved, which contribute to the multistage and multifaceted carcinogenesis of this type of cancer. We, therefore, suggest that in future studies, researchers should focus on a detailed analysis of tumor microenvironmental immune checkpoints, and to validate their validity, perform genetic polymorphism analyses in a wide range of patients and healthy individuals to determine the genetic susceptibility to lung cancer development. In addition, further research related to the analysis of the tumor microenvironment; immune system disorders, with a particular emphasis on immunological checkpoints and genetic differences may contribute to the development of new personalized therapies that improve the prognosis of patients.

Screening and identification of HLA-A2-restricted neoepitopes for immunotherapy of non-microsatellite instability-high colorectal cancer

Colorectal cancer has one of the highest mortality rates among malignant tumors, and most patients with non-microsatellite instability-high (MSI-H) colorectal cancer do not benefit from targeted therapy or immune checkpoint inhibitors. Identification of immunogenic neoantigens is a promising strategy for inducing specific antitumor T cells for cancer immunotherapy. Here, we screened potential high-frequency neoepitopes from non-MSI-H colorectal cancer and tested their abilities to induce tumor-specific cytotoxic T cell responses. Three HLA-A2-restricted neoepitopes (P31, P50, and P52) were immunogenic and could induce cytotoxic T lymphocytes in peripheral blood mononuclear cells from healthy donors and colorectal cancer patients. Cytotoxic T lymphocytes induced in HLA-A2.1/K^b transgenic mice could recognize and lyse mutant neoepitope-transfected HLA-A2⁺ cancer cells. Adoptive transfer of cytotoxic T lymphocytes induced by the peptide pool of these three neoepitopes effectively inhibited tumor growth and increased the therapeutic effects of anti-PD-1 antibody. These results revealed the potential of high-frequency mutation-specific peptide-based immunotherapy as a personalized treatment approach for patients with non-MSI-H colorectal cancer. The combination of adoptive T cell therapy based on these neoepitopes with immune checkpoint inhibitors, such as anti-PD-1, could provide a promising treatment strategy for non-MSI-H colorectal cancer.

T-Cell Receptor Mimic Antibodies for Cancer Immunotherapy

Antibody-based immunotherapies show clinical effectiveness in various cancer types. However, the target repertoire is limited to surface or soluble antigens, which are a relatively small percentage of the cancer proteome. Most proteins of the human proteome are intracellular. Short peptides from intracellular targets can be presented by MHC class I (MHC-I) molecules on cell surface, making them potential targets for cancer immunotherapy. Antibodies can be developed to target these peptide/MHC complexes, similar to the recognition of such complexes by the T-cell receptor (TCR). These antibodies are referred to as T-cell receptor mimic (TCRm) or TCR-like antibodies. Ongoing preclinical and clinical studies will help us understand their mechanisms of action and selection of target epitopes for immunotherapy. The present review will summarize and discuss the selection of intracellular antigens, production of the peptide/MHC complexes, isolation of TCRm antibodies for therapeutic applications, limitations of TCRm antibodies, and possible ways to advance TCRm antibody-based approaches into the clinic.

Personal Neoantigens From Patients With NSCLC Induce Efficient Antitumor Responses

Objective

To develop a neoantigen-targeted personalized cancer treatment for non-small cell lung cancer (NSCLC), neoantigens were obtained from collected human lung cancer samples, and the utility of neoantigen and neoantigen-reactive T cells (NRTs) was assessed.

Methods

Tumor specimens from three patients with NSCLC were obtained and analyzed by whole-exome sequencing, and neoantigens were predicted accordingly. Dendritic cells and T lymphocytes were isolated, NRTs were elicited and IFN-γ ELISPOT tests were conducted. HLA-A2.1/K^b transgenic mice were immunized with peptides from HLA-A*02:01⁺patient with high immunogenicity, and NRTs were subjected to IFN-γ, IL-2 and TNF-α ELISPOT as well as time-resolved fluorescence assay for cytotoxicity assays to verify the immunogenicity in vitro. The HLA-A*02:01⁺lung cancer cell line was transfected with minigene and inoculated into the flanks of C57BL/6^nu/nu mice and the NRTs induced by the immunogenic polypeptides from autologous HLA-A2.1/K^b transgenic mice were adoptively transfused to verify their immunogenicity in vivo.

Results

Multiple putative mutation-associated neoantigens with strong affinity for HLA were selected from each patient. Immunogenic neoantigen were identified in all three NSCLC patients, the potency of ACAD8-T105I, BCAR1-G23V and PLCG1-M425L as effective neoantigen to active T cells in suppressing tumor growth was further proven both in vitro and in vivo using HLA-A2.1/Kb transgenic mice and tumor-bearing mouse models.

Conclusion

Neoantigens with strong immunogenicity can be screened from NSCLC patients through the whole-exome sequencing of patient specimens and machine-learning-based neoantigen predictions. NRTs shown efficient antitumor responses in transgenic mice and tumor-bearing mouse models. Our results indicate that the development of neoantigen-based personalized immunotherapies in NSCLC is possible.

Precis

Neoantigens with strong immunogenicity were screened from NSCLC patients. This research provides evidence suggesting that neoantigen-based therapy might serve as feasible treatment for NSCLC.

Role of in silico structural modeling in predicting immunogenic neoepitopes for cancer vaccine development

In prior studies, we delineated the landscape of neoantigens arising from nonsynonymous point mutations in a murine pancreatic cancer model, Panc02. We developed a peptide vaccine by targeting neoantigens predicted using a pipeline that incorporates the MHC binding algorithm NetMHC. The vaccine, when combined with immune checkpoint modulators, elicited a robust neoepitope-specific antitumor immune response and led to tumor clearance. However, only a small fraction of the predicted neoepitopes induced T cell immunity, similarly to that reported for neoantigen vaccines tested in clinical studies. While these studies have used binding affinities to MHC I as surrogates for T cell immunity, this approach does not include spatial information on the mutated residue that is crucial for TCR activation. Here, we investigate conformational alterations in and around the MHC binding groove induced by selected minimal neoepitopes, and we examine the influence of a given mutated residue as a function of its spatial position. We found that structural parameters, including the solvent-accessible surface area (SASA) of the neoepitope and the position and spatial configuration of the mutated residue within the sequence, can be used to improve the prediction of immunogenic neoepitopes for inclusion in cancer vaccines.

Structural parameters, including the solvent exposed surface area of the neoepitope and the position and spatial configuration of the mutated residue can be used to improve the prediction of immunogenic neoepitopes for inclusion in cancer vaccines.

INeo-Epp: A Novel T-Cell HLA Class-I Immunogenicity or Neoantigenic Epitope Prediction Method Based on Sequence-Related Amino Acid Features

In silico T-cell epitope prediction plays an important role in immunization experimental design and vaccine preparation. Currently, most epitope prediction research focuses on peptide processing and presentation, e.g., proteasomal cleavage, transporter associated with antigen processing (TAP), and major histocompatibility complex (MHC) combination. To date, however, the mechanism for the immunogenicity of epitopes remains unclear. It is generally agreed upon that T-cell immunogenicity may be influenced by the foreignness, accessibility, molecular weight, molecular structure, molecular conformation, chemical properties, and physical properties of target peptides to different degrees. In this work, we tried to combine these factors. Firstly, we collected significant experimental HLA-I T-cell immunogenic peptide data, as well as the potential immunogenic amino acid properties. Several characteristics were extracted, including the amino acid physicochemical property of the epitope sequence, peptide entropy, eluted ligand likelihood percentile rank (EL rank(%)) score, and frequency score for an immunogenic peptide. Subsequently, a random forest classifier for T-cell immunogenic HLA-I presenting antigen epitopes and neoantigens was constructed. The classification results for the antigen epitopes outperformed the previous research (the optimal AUC = 0.81, external validation data set AUC = 0.77). As mutational epitopes generated by the coding region contain only the alterations of one or two amino acids, we assume that these characteristics might also be applied to the classification of the endogenic mutational neoepitopes also called "neoantigens." Based on mutation information and sequence-related amino acid characteristics, a prediction model of a neoantigen was established as well (the optimal AUC = 0.78). Further, an easy-to-use web-based tool "INeo-Epp" was developed for the prediction of human immunogenic antigen epitopes and neoantigen epitopes.

Machine Learning for Cancer Immunotherapies Based on Epitope Recognition by T Cell Receptors

In the last years, immunotherapies have shown tremendous success as treatments for multiple types of cancer. However, there are still many obstacles to overcome in order to increase response rates and identify effective therapies for every individual patient. Since there are many possibilities to boost a patient's immune response against a tumor and not all can be covered, this review is focused on T cell receptor-mediated therapies. CD8+ T cells can detect and destroy malignant cells by binding to peptides presented on cell surfaces by MHC (major histocompatibility complex) class I molecules. CD4+ T cells can also mediate powerful immune responses but their peptide recognition by MHC class II molecules is more complex, which is why the attention has been focused on CD8+ T cells. Therapies based on the power of T cells can, on the one hand, enhance T cell recognition by introducing TCRs that preferentially direct T cells to tumor sites (so called TCR-T therapy) or through vaccination to induce T cells in vivo. On the other hand, T cell activity can be improved by immune checkpoint inhibition or other means that help create a microenvironment favorable for cytotoxic T cell activity. The manifold ways in which the immune system and cancer interact with each other require not only the use of large omics datasets from gene, to transcript, to protein, and to peptide but also make the application of machine learning methods inevitable. Currently, discovering and selecting suitable TCRs is a very costly and work intensive in vitro process. To facilitate this process and to additionally allow for highly personalized therapies that can simultaneously target multiple patient-specific antigens, especially neoepitopes, breakthrough computational methods for predicting antigen presentation and TCR binding are urgently required. Particularly, potential cross-reactivity is a major consideration since off-target toxicity can pose a major threat to patient safety. The current speed at which not only datasets grow and are made available to the public, but also at which new machine learning methods evolve, is assuring that computational approaches will be able to help to solve problems that immunotherapies are still facing.

Integrative analysis of rare copy number variants and gene expression data in alopecia areata implicates an aetiological role for autophagy

Alopecia areata (AA) is a highly prevalent autoimmune disease that attacks the hair follicle and leads to hair loss that can range from small patches to complete loss of scalp and body hair. Our previous linkage and genome-wide association studies (GWAS) generated strong evidence for aetiological contributions from inherited genetic variants at different population frequencies, including both rare mutations and common polymorphisms. Additionally, we conducted gene expression (GE) studies on scalp biopsies of 96 patients and controls to establish signatures of active disease. In this study, we performed an integrative analysis on these two datasets to test the hypothesis that rare CNVs in patients with AA could be leveraged to identify drivers of disease in our AA GE signatures. We analysed copy number variants (CNVs) in a case-control cohort of 673 patients with AA and 16 311 controls independent of the case-control cohort of 96 research participants used in our GE study. Using an integrative computational analysis, we identified 14 genes whose expression levels were altered by CNVs in a consistent direction of effect, corresponding to gene expression changes in lesional skin of patients. Four of these genes were affected by CNVs in three or more unrelated patients with AA, including ATG4B and SMARCA2, which are involved in autophagy and chromatin remodelling, respectively. Our findings identified new classes of genes with potential contributions to AA pathogenesis.

Novel TCR-based biologics: mobilising T cells to warm 'cold' tumours

Immunotherapeutic strategies have revolutionised cancer therapy in recent years, bringing meaningful improvements in outcomes for patients with previously intractable conditions. These successes have, however, been largely limited to certain types of liquid tumours and a small subset of solid tumours that are known to be particularly immunogenic. Broadening these advances across the majority of tumour indications, which are characterised by an immune-excluded, immune-deserted or immune-suppressed ('cold') phenotype, will require alternative approaches that are able to specifically address this unique biological environment. Several newer therapeutic modalities, including adoptive cell therapy and T cell redirecting bispecific molecules, are considered to hold particular promise and are being investigated in early phase clinical trials across various solid tumour indications. ImmTAC molecules are a novel class of T cell redirecting bispecific biologics that exploit TCR-based targeting of tumour cells; providing potent and highly specific access to the vast landscape of intracellular targets. The first of these reagents to reach the clinic, tebentafusp (IMCgp100), has generated demonstrable clinical efficacy in an immunologically cold solid tumour with a high unmet need. Here, we highlight the key elements of the ImmTAC platform that make it ideally positioned to overcome the cold tumour microenvironment in an off-the-shelf format.

Neoantigen identification strategies enable personalized immunotherapy in refractory solid tumors

BACKGROUND

Recent genomic and bioinformatic technological advances have made it possible to dissect the immune response to personalized neoantigens encoded by tumor-specific mutations. However, timely and efficient identification of neoantigens is still one of the major obstacles to using personalized neoantigen-based cancer immunotherapy.

METHODS

Two different pipelines of neoantigens identification were established in this study: (1) Clinical grade targeted sequencing was performed in patients with refractory solid tumor, and mutant peptides with high variant allele frequency and predicted high HLA-binding affinity were de novo synthesized. (2) An inventory-shared neoantigen peptide library of common solid tumors was constructed, and patients' hotspot mutations were matched to the neoantigen peptide library. The candidate neoepitopes were identified by recalling memory T-cell responses in vitro. Subsequently, neoantigen-loaded dendritic cell vaccines and neoantigen-reactive T cells were generated for personalized immunotherapy in six patients.

RESULTS

Immunogenic neo-epitopes were recognized by autologous T cells in 3 of 4 patients who utilized the de novo synthesis mode and in 6 of 13 patients who performed shared neoantigen peptide library, respectively. A metastatic thymoma patient achieved a complete and durable response beyond 29 months after treatment. Immune-related partial response was observed in another patient with metastatic pancreatic cancer. The remaining four patients achieved the prolonged stabilization of disease with a median PFS of 8.6 months.

CONCLUSIONS

The current study provided feasible pipelines for neoantigen identification. Implementing these strategies to individually tailor neoantigens could facilitate the neoantigen-based translational immunotherapy research.TRIAL REGSITRATION. ChiCTR.org ChiCTR-OIC-16010092, ChiCTR-OIC-17011275, ChiCTR-OIC-17011913; ClinicalTrials.gov NCT03171220.

FUNDING

This work was funded by grants from the National Key Research and Development Program of China (Grant No. 2017YFC1308900), the National Major Projects for "Major New Drugs Innovation and Development" (Grant No.2018ZX09301048-003), the National Natural Science Foundation of China (Grant No. 81672367, 81572329, 81572601), and the Key Research and Development Program of Jiangsu Province (No. BE2017607).

Neoantigens in Chronic Obstructive Pulmonary Disease and Lung Cancer: A Point of View

The goal of this manuscript is to explore the role of clinical proteomics for detecting mutations in chronic obstructive pulmonary disease (COPD) and lung cancer by mass spectrometry-based technology. COPD and lung cancer caused by smoke inhalation are most likely linked by challenging the immune system via partly shared pathways. Genome-wide association studies have identified several single nucleotide polymorphisms which predispose an increased susceptibility to COPD and lung cancer. In lung cancer, this leads to coding mutations in the affected tissues, development of neoantigens, and different functionality and abundance of proteins in specific pathways. If a similar reasoning can also be applied in COPD will be discussed. The technology of mass spectrometry has developed into an advanced technology for proteome research detecting mutated peptides or proteins and finding relevant molecular mechanisms that will enable predicting the response to immunotherapy in COPD and lung cancer patients.

Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis

To understand drug combination effect, it is necessary to decipher the interactions between drug targets-many of which are signaling molecules. Previously, such signaling pathway models are largely based on the compilation of literature data from heterogeneous cellular contexts. Indeed, de novo reconstruction of signaling interactions from large-scale molecular profiling is still lagging, compared to similar efforts in transcriptional and protein-protein interaction networks. To address this challenge, we introduce a novel algorithm for the systematic inference of protein kinase pathways, and applied it to published mass spectrometry-based phosphotyrosine profile data from 250 lung adenocarcinoma (LUAD) samples. The resulting network includes 43 TKs and 415 inferred, LUAD-specific substrates, which were validated at >60% accuracy by SILAC assays, including "novel' substrates of the EGFR and c-MET TKs, which play a critical oncogenic role in lung cancer. This systematic, data-driven model supported drug response prediction on an individual sample basis, including accurate prediction and validation of synergistic EGFR and c-MET inhibitor activity in cells lacking mutations in either gene, thus contributing to current precision oncology efforts.

Comprehensive immunoproteogenomic analyses of malignant pleural mesothelioma

We generated a comprehensive atlas of the immunologic cellular networks within human malignant pleural mesothelioma (MPM) using mass cytometry. Data-driven analyses of these high-resolution single-cell data identified 2 distinct immunologic subtypes of MPM with vastly different cellular composition, activation states, and immunologic function; mass spectrometry demonstrated differential abundance of MHC-I and -II neopeptides directly identified between these subtypes. The clinical relevance of this immunologic subtyping was investigated with a discriminatory molecular signature derived through comparison of the proteomes and transcriptomes of these 2 immunologic MPM subtypes. This molecular signature, representative of a favorable intratumoral cell network, was independently associated with improved survival in MPM and predicted response to immune checkpoint inhibitors in patients with MPM and melanoma. These data additionally suggest a potentially novel mechanism of response to checkpoint blockade: requirement for high measured abundance of neopeptides in the presence of high expression of MHC proteins specific for these neopeptides.

A systematic immunoproteogenomic investigation of malignant pleural mesothelioma reveals mechanisms of anti-tumor immunity.

Non-Canonical Thinking for Targeting ALK-Fusion Onco-Proteins in Lung Cancer

Anaplastic lymphoma kinase (ALK) gene rearrangements have been identified in lung cancer at 3–7% frequency, thus representing an important subset of genetic lesions that drive oncogenesis in this disease. Despite the availability of multiple FDA-approved small molecule inhibitors targeting ALK fusion proteins, drug resistance to ALK kinase inhibitors is a common problem in clinic. Thus, there is an unmet need to deepen the current understanding of genomic characteristics of ALK rearrangements and to develop novel therapeutic strategies that can overcome ALK inhibitor resistance. In this review, we present the genomic landscape of ALK fusions in the context of co-occurring mutations with other cancer-related genes, pointing to the central role of genetic epistasis (gene-gene interactions) in ALK-driven advanced-stage lung cancer. We discuss the possibility of targeting druggable domains within ALK fusion partners in addition to available strategies inhibiting the ALK kinase domain directly. Finally, we examine the potential of targeting ALK fusion-specific neoantigens in combination with other treatments, a strategy that could open a new avenue for the improved treatment of ALK positive lung cancer patients.

Trial watch: DNA-based vaccines for oncological indications

DNA-based vaccination is a promising approach to cancer immunotherapy. DNA-based vaccines specific for tumor-associated antigens (TAAs) are indeed relatively simple to produce, cost-efficient and well tolerated. However, the clinical efficacy of DNA-based vaccines for cancer therapy is considerably limited by central and peripheral tolerance. During the past decade, considerable efforts have been devoted to the development and characterization of novel DNA-based vaccines that would circumvent this obstacle. In this setting, particular attention has been dedicated to the route of administration, expression of modified TAAs, co-expression of immunostimulatory molecules, and co-delivery of immune checkpoint blockers. Here, we review preclinical and clinical progress on DNA-based vaccines for cancer therapy.

The frequency of neoantigens per somatic mutation rather than overall mutational load or number of predicted neoantigens per se is a prognostic factor in ovarian clear cell carcinoma

Neoantigens derived from tumor-specific somatic mutations are excellent targets for anti-tumor immune responses. In ovarian clear cell carcinoma (OCCC), checkpoint blockade yields durable responses in a subset of patients. To approach the question of why only some patients respond, we first investigated neoantigen loads and immune signatures using exome sequencing and expression array data for 74 OCCC patients treated conventionally. Neither the number of missense mutations nor total predicted neoantigens assessed in the tumor correlated with clinical outcomes. However, the number of neoantigens per missense mutation ("neoAg frequency") did correlate with clinical outcomes. Cox multivariate regression analysis demonstrated that low neoAg frequencies correlated with increased progression-free survival (PFS) and was an independent predictive factor for PFS in OCCC (p = 0.032), especially at stage I-II (p = 0.0045). Immunity-associated genes including those related to effector memory CD8 T cells were dominantly expressed in tumors with low neoAg frequencies in stage I-II patients, suggesting CD8 T cell-mediated elimination of immunogenic sub-clones expressing neoantigens (immunoediting) had occurred. In contrast, we observed decreased HLA-A, -B, and -C expression (p = 0.036, p = 0.026, and p = 0.030, respectively) as well as increased ratios of CTLA-4, PD-1, Tim-3, and LAG3 to CD8A expression (p = 0.0064, p = 0.017, p = 0.033 and p = 0.0136, respectively) in stage I-II tumors with high neoAg frequencies. Constrained anti-tumor immunity may thus result in limited immunoediting, and poor prognosis. Our results show that neoAg frequency in OCCC is an independent prognostic factor for clinical outcome and may become a potential candidate biomarker for immunomodulatory agent-based treatments.

Genomic analysis of 63,220 tumors reveals insights into tumor uniqueness and targeted cancer immunotherapy strategies

Background

The integration of genomics with immunotherapy has potential value for cancer vaccine development. Given the clinical successes of immune checkpoint modulators, interest in cancer vaccines as therapeutic options has been revived. Current data suggest that each tumor contains a unique set of mutations (mutanome), thus requiring the creation of individualized cancer vaccines. However, rigorous analysis of non-individualized cancer immunotherapy approaches across multiple cancer types and in the context of known driver alterations has yet to be reported. We therefore set out to determine the feasibility of a generalizable cancer vaccine strategy based on targeting multiple neoantigens in an HLA-A/B subtype-directed manner.

Methods

A cancer gene-focused, hybrid capture-based genomic analysis was performed on 63,220 unique tumors. Neoantigens were predicted using a combined peptide processing and MHC-I binding prediction tool (IEDB) for all recurrent (>10 tumors) missense alterations and non-frameshift indels for the two most common HLA-A/B subtypes in North American/European populations.

Results

Despite being overwhelmingly unique overall, many mutanomes (~45%) contain at least one mutation from a set of ten mutations chosen to maximize the number of unique tumors. This held true for tumors driven by KRAS G12C (n = 1799), PIK3CA E545K (n = 1713), or EGFR L858R (n = 478) alterations, which define distinct sample subsets. We therefore hypothesized that sets of carefully selected mutations/neoantigens may allow the development of broadly applicable semi-universal cancer vaccines. To test the feasibility of such an approach, antigen processing and MHC-I binding prediction was applied for HLA subtypes A*01:01/B*08:01 and A*02:01/B*44:02. In tumors with a specific HLA type, 0.7 and 2.5% harbored at least one of a set of ten neoantigens predicted to bind to each subtype, respectively. In comparison, KRAS G12C-driven tumors produced similar results (0.8 and 2.6% for each HLA subtype, respectively), indicating that neoantigen targets still remain highly diverse even within the context of major driver mutations.

Conclusions

This “best case scenario” analysis of a large tumor set across multiple cancer types and in the context of driver alterations reveals that semi-universal, HLA-specific cancer vaccine strategies will be relevant to only a small subset of the general population. Similar analysis of whole exome/genome sequencing, although not currently feasible at scale in a clinical setting, will likely uncover further diversity.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0408-2) contains supplementary material, which is available to authorized users.

Prediction and prioritization of neoantigens: integration of RNA sequencing data with whole-exome sequencing

The importance of neoantigens for cancer immunity is now well-acknowledged. However, there are diverse strategies for predicting and prioritizing candidate neoantigens, and thus reported neoantigen loads vary a great deal. To clarify this issue, we compared the numbers of neoantigen candidates predicted by four currently utilized strategies. Whole-exome sequencing and RNA sequencing (RNA-Seq) of four non-small-cell lung cancer patients was carried out. We identified 361 somatic missense mutations from which 224 candidate neoantigens were predicted using MHC class I binding affinity prediction software (strategy I). Of these, 207 exceeded the set threshold of gene expression (fragments per kilobase of transcript per million fragments mapped ≥1), resulting in 124 candidate neoantigens (strategy II). To verify mutant mRNA expression, sequencing of amplicons from tumor cDNA including each mutation was undertaken; 204 of the 207 mutations were successfully sequenced, yielding 121 mutant mRNA sequences, resulting in 75 candidate neoantigens (strategy III). Sequence information was extracted from RNA-Seq to confirm the presence of mutated mRNA. Variant allele frequencies ≥0.04 in RNA-Seq were found for 117 of the 207 mutations and regarded as expressed in the tumor, and finally, 72 candidate neoantigens were predicted (strategy IV). Without additional amplicon sequencing of cDNA, strategy IV was comparable to strategy III. We therefore propose strategy IV as a practical and appropriate strategy to predict candidate neoantigens fully utilizing currently available information. It is of note that different neoantigen loads were deduced from the same tumors depending on the strategies applied.

MonoSeq Variant Caller Reveals Novel Mononucleotide Run Indel Mutations in Tumors with Defective DNA Mismatch Repair

Next-generation sequencing has revolutionized cancer genetics, but accurately detecting mutations in repetitive DNA sequences, especially mononucleotide runs, remains a challenge. This is a particular concern for tumors with defective mismatch repair (MMR) that accumulate strand-slippage mutations. We developed MonoSeq to improve indel mutation detection in mononucleotide runs, and used MonoSeq to investigate strand-slippage mutations in endometrial cancers, a tumor type that has frequent loss of MMR. We performed extensive Sanger sequencing to validate both clonal and subclonal MonoSeq mutation calls. Eighty-one regions containing mononucleotide runs were sequenced in 540 primary endometrial cancers (223 with defective MMR). Our analyses revealed that the overall mutation rate in MMR-deficient tumors was 20-30-fold higher than in MMR-normal tumors. MonoSeq analysis identified several previously unreported mutations, including a novel hotspot in an A7 run in the terminal exon of ARID5B.The ARID5B indel mutations were seen in both MMR-deficient and MMR-normal tumors, suggesting biologic selection. The analysis of tumor mRNAs revealed the presence of mutant transcripts that could result in translation of neopeptides. Improved detection of mononucleotide run strand-slippage mutations has clear implications for comprehensive mutation detection in tumors with defective MMR. Indel frameshift mutations and the resultant antigenic peptides could help guide immunotherapy strategies.

Opportunities and challenges for TCR mimic antibodies in cancer therapy

INTRODUCTION

Monoclonal antibodies (mAbs) are potent cancer therapeutic agents, but exclusively recognize cell-surface targets whereas most cancer-associated proteins are found intracellularly. Hence, potential cancer therapy targets such as over expressed self-proteins, activated oncogenes, mutated tumor suppressors, and translocated gene products are not accessible to traditional mAb therapy. An emerging approach to target these epitopes is the use of TCR mimic mAbs (TCRm) that recognize epitopes similar to those of T cell receptors (TCR).

AREAS COVERED

TCRm antigens are composed of a linear peptide sequence derived from degraded proteins and presented in the context of cell-surface MHC molecules. We discuss how the nature of the TCRm epitopes provides both advantages (absolute tumor specificity and access to a new universe of important targets) and disadvantages (low density, MHC restriction, MHC down-regulation, and cross-reactive linear epitopes) to conventional mAb therapy. We will also discuss potential solutions to these obstacles.

EXPERT OPINION

TCRm combine the specificity of TCR recognition with the potency, pharmacologic properties, and versatility of mAbs. The structure and presentation of a TCRm epitope has important consequences related to the choice of targets, mAb design, available peptides and MHC subtype restrictions, possible cross-reactivity, and therapeutic activity.

A Tumor-Specific Neo-Antigen Caused by a Frameshift Mutation in BAP1 Is a Potential Personalized Biomarker in Malignant Peritoneal Mesothelioma

Malignant peritoneal mesothelioma (MPM) is an aggressive rare malignancy associated with asbestos exposure. A better understanding of the molecular pathogenesis of MPM will help develop a targeted therapy strategy. Oncogene targeted depth sequencing was performed on a tumor sample and paired peripheral blood DNA from a patient with malignant mesothelioma of the peritoneum. Four somatic base-substitutions in NOTCH2, NSD1, PDE4DIP, and ATP10B and 1 insert frameshift mutation in BAP1 were validated by the Sanger method at the transcriptional level. A 13-amino acids neo-peptide of the truncated Bap1 protein, which was produced as a result of this novel frameshift mutation, was predicted to be presented by this patient's HLA-B protein. The polyclonal antibody of the synthesized 13-mer neo-peptide was produced in rabbits. Western blotting results showed a good antibody-neoantigen specificity, and Immunohistochemistry (IHC) staining with the antibody of the neo-peptide clearly differentiated neoplastic cells from normal cells. A search of the Catalogue of Somatic Mutations in Cancer (COSMIC) database also revealed that 53.2% of mutations in BAP1 were frameshift indels with neo-peptide formation. An identified tumor-specific neo-antigen could be the potential molecular biomarker for personalized diagnosis to precisely subtype rare malignancies such as MPM.