Human cancer regression antigens

The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood

T cells recognize tumor antigens and initiate an anticancer immune response in the very early stages of tumor development, and the antigen specificity of T cells is determined by the T-cell receptor (TCR). Therefore, monitoring changes in the TCR repertoire in peripheral blood may offer a strategy to detect various cancers at a relatively early stage. Here, we developed the deep learning framework iCanTCR to identify patients with cancer based on the TCR repertoire. The iCanTCR framework uses TCRβ sequences from an individual as an input and outputs the predicted cancer probability. The model was trained on over 2,000 publicly available TCR repertoires from 11 types of cancer and healthy controls. Analysis of several additional publicly available datasets validated the ability of iCanTCR to distinguish patients with cancer from noncancer individuals and demonstrated the capability of iCanTCR for the accurate classification of multiple cancers. Importantly, iCanTCR precisely identified individuals with early-stage cancer with an AUC of 86%. Altogether, this work provides a liquid biopsy approach to capture immune signals from peripheral blood for noninvasive cancer diagnosis.

SIGNIFICANCE

Development of a deep learning-based method for multicancer detection using the TCR repertoire in the peripheral blood establishes the potential of evaluating circulating immune signals for noninvasive early cancer detection.

DeepLION2: deep multi-instance contrastive learning framework enhancing the prediction of cancer-associated T cell receptors by attention strategy on motifs

Introduction

T cell receptor (TCR) repertoires provide valuable insights into complex human diseases, including cancers. Recent advancements in immune sequencing technology have significantly improved our understanding of TCR repertoire. Some computational methods have been devised to identify cancer-associated TCRs and enable cancer detection using TCR sequencing data. However, the existing methods are often limited by their inadequate consideration of the correlations among TCRs within a repertoire, hindering the identification of crucial TCRs. Additionally, the sparsity of cancer-associated TCR distribution presents a challenge in accurate prediction.

Methods

To address these issues, we presented DeepLION2, an innovative deep multi-instance contrastive learning framework specifically designed to enhance cancer-associated TCR prediction. DeepLION2 leveraged content-based sparse self-attention, focusing on the top k related TCRs for each TCR, to effectively model inter-TCR correlations. Furthermore, it adopted a contrastive learning strategy for bootstrapping parameter updates of the attention matrix, preventing the model from fixating on non-cancer-associated TCRs.

Results

Extensive experimentation on diverse patient cohorts, encompassing over ten cancer types, demonstrated that DeepLION2 significantly outperformed current state-of-the-art methods in terms of accuracy, sensitivity, specificity, Matthews correlation coefficient, and area under the curve (AUC). Notably, DeepLION2 achieved impressive AUC values of 0.933, 0.880, and 0.763 on thyroid, lung, and gastrointestinal cancer cohorts, respectively. Furthermore, it effectively identified cancer-associated TCRs along with their key motifs, highlighting the amino acids that play a crucial role in TCR-peptide binding.

Conclusion

These compelling results underscore DeepLION2's potential for enhancing cancer detection and facilitating personalized cancer immunotherapy. DeepLION2 is publicly available on GitHub, at https://github.com/Bioinformatics7181/DeepLION2, for academic use only.

Current Technologies and Future Perspectives in Immunotherapy towards a Clinical Oncology Approach

Immunotherapy is now established as a potent therapeutic paradigm engendering antitumor immune response against a wide range of malignancies and other diseases by modulating the immune system either through the stimulation or suppression of immune components such as CD4+ T cells, CD8+ T cells, B cells, monocytes, macrophages, dendritic cells, and natural killer cells. By targeting several immune checkpoint inhibitors or blockers (e.g., PD-1, PD-L1, PD-L2, CTLA-4, LAG3, and TIM-3) expressed on the surface of immune cells, several monoclonal antibodies and polyclonal antibodies have been developed and already translated clinically. In addition, natural killer cell-based, dendritic cell-based, and CAR T cell therapies have been also shown to be promising and effective immunotherapeutic approaches. In particular, CAR T cell therapy has benefited from advancements in CRISPR-Cas9 genome editing technology, allowing the generation of several modified CAR T cells with enhanced antitumor immunity. However, the emerging SARS-CoV-2 infection could hijack a patient's immune system by releasing pro-inflammatory interleukins and cytokines such as IL-1β, IL-2, IL-6, and IL-10, and IFN-γ and TNF-α, respectively, which can further promote neutrophil extravasation and the vasodilation of blood vessels. Despite the significant development of advanced immunotherapeutic technologies, after a certain period of treatment, cancer relapses due to the development of resistance to immunotherapy. Resistance may be primary (where tumor cells do not respond to the treatment), or secondary or acquired immune resistance (where tumor cells develop resistance gradually to ICIs therapy). In this context, this review aims to address the existing immunotherapeutic technologies against cancer and the resistance mechanisms against immunotherapeutic drugs, and explain the impact of COVID-19 on cancer treatment. In addition, we will discuss what will be the future implementation of these strategies against cancer drug resistance. Finally, we will emphasize the practical steps to lay the groundwork for enlightened policy for intervention and resource allocation to care for cancer patients.

Overcoming acquired resistance to cancer immune checkpoint therapy: potential strategies based on molecular mechanisms

Immune checkpoint inhibitors (ICIs) targeting CTLA-4 and PD-1/PD-L1 to boost tumor-specific T lymphocyte immunity have opened up new avenues for the treatment of various histological types of malignancies, with the possibility of durable responses and improved survival. However, the development of acquired resistance to ICI therapy over time after an initial response remains a major obstacle in cancer therapeutics. The potential mechanisms of acquired resistance to ICI therapy are still ambiguous. In this review, we focused on the current understanding of the mechanisms of acquired resistance to ICIs, including the lack of neoantigens and effective antigen presentation, mutations of IFN-γ/JAK signaling, and activation of alternate inhibitory immune checkpoints, immunosuppressive tumor microenvironment, epigenetic modification, and dysbiosis of the gut microbiome. Further, based on these mechanisms, potential therapeutic strategies to reverse the resistance to ICIs, which could provide clinical benefits to cancer patients, are also briefly discussed.

DeepLION: Deep Multi-Instance Learning Improves the Prediction of Cancer-Associated T Cell Receptors for Accurate Cancer Detection

Recent studies highlight the potential of T cell receptor (TCR) repertoires in accurately detecting cancers via noninvasive sampling. Unfortunately, due to the complicated associations among cancer antigens and the possible induced T cell responses, currently, the practical strategy for identifying cancer-associated TCRs is the computational prediction based on TCR repertoire data. Several state-of-the-art methods were proposed in recent year or two; however, the prediction algorithms were still weakened by two major issues. To facilitate the computational processes, the algorithms prefer to decompose the original TCR sequences into length-fixed amino acid fragments, while the first dilemma comes as the lengths of cancer-associated motifs are suggested to be various. Moreover, the correlations among TCRs in the same repertoire should be further considered, which are often ignored by the existing methods. We here developed a deep multi-instance learning method, named DeepLION, to improve the prediction of cancer-associated TCRs by considering these issues. First, DeepLION introduced a deep learning framework with alternative convolution filters and 1-max pooling operations to handle the amino acid fragments with different lengths. Then, the multi-instance learning framework modeled the TCR correlations and assigned adjusted weights for each TCR sequence during the predicting process. To validate the performance of DeepLION, we conducted a series of experiments on several cohorts of patients from nine cancer types. Compared to the existing methods, DeepLION achieved, on most of the cohorts, higher prediction accuracies, sensitivities, specificities, and areas under the curve (AUCs), where the AUC reached notably 0.97 and 0.90 for thyroid and lung cancer cohorts, respectively. Thus, DeepLION may further support the detection of cancers from TCR repertoire data. DeepLION is publicly available on GitHub, at https://github.com/Bioinformatics7181/DeepLION, for academic usage only.

Evaluation of T-Cell Responses Against Shared Melanoma Associated Antigens and Predicted Neoantigens in Cutaneous Melanoma Patients Treated With the CSF-470 Allogeneic Cell Vaccine Plus BCG and GM-CSF

The CSF-470 vaccine consists of lethally-irradiated allogeneic cells derived from four cutaneous melanoma cell lines administered plus BCG and GM-CSF as adjuvants. In an adjuvant phase II study vs. IFN-α2b, the vaccine significantly prolonged the distant metastasis-free survival (DMFS) of stages IIB-IIC-III melanoma patients with evidence of the induction of immune responses against vaccine cells. Purpose: The aim of this study was to analyze the antigens against which the immune response was induced, as well as the T-helper profile and lytic ability of immune cells after CSF-470 treatment. Methods: HLA-restricted peptides from tumor-associated antigens (TAAs) were selected from TANTIGEN database for 13 evaluable vaccinated patients. In addition, for patient #006 (pt#006), tumor somatic variants were identified by NGS and candidate neoAgs were selected by predicted HLA binding affinity and similarity between wild type (wt) and mutant peptides. The patient's PBMC reactivity against selected peptides was detected by IFNγ-ELISPOT. T-helper transcriptional profile was determined by quantifying GATA-3, T-bet, and FOXP3 mRNA by RT-PCR, and intracellular cytokines were analyzed by flow cytometry. Autologous tumor cell lysis by PBMC was assessed in an in vitro calcein release assay. Results: Vaccinated patient's PBMC reactivity against selected TAAs derived peptides showed a progressive increase in the number of IFNγ-producing cells throughout the 2-yr vaccination protocol. ELISPOT response correlated with delayed type hypersensitivity (DTH) reaction to CSF-470 vaccine cells. Early upregulation of GATA-3 and Foxp3 mRNA, as well as an increase in CD4+IL4+cells, was associated with a low DMFS. Also, IFNγ response against 9/73 predicted neoAgs was evidenced in the case of pt#006; 7/9 emerged after vaccination. We verified in pt# 006 that post-vaccination PBMC boosted in vitro with the vaccine lysate were able to lyse autologous tumor cells. Conclusions: A progressive increase in the immune response against TAAs expressed in the vaccine and in the patient's tumor was induced by CSF-470 vaccination. In pt#006, we demonstrated immune recognition of patient's specific neoAgs, which emerged after vaccination. These results suggest that an initial response against shared TAAs could further stimulate an immune response against autologous tumor neoAgs.

Biophysicochemical motifs in T cell receptor sequences as a potential biomarker for high-grade serous ovarian carcinoma

We previously showed, in a pilot study with publicly available data, that T cell receptor (TCR) repertoires from tumor infiltrating lymphocytes (TILs) could be distinguished from adjacent healthy tissue repertoires by the presence of TCRs bearing specific, biophysicochemical motifs in their antigen binding regions. We hypothesized that such motifs might allow development of a novel approach to cancer detection. The motifs were cancer specific and achieved high classification accuracy: we found distinct motifs for breast versus colorectal cancer-associated repertoires, and the colorectal cancer motif achieved 93% accuracy, while the breast cancer motif achieved 94% accuracy. In the current study, we sought to determine whether such motifs exist for ovarian cancer, a cancer type for which detection methods are urgently needed. We made two significant advances over the prior work. First, the prior study used patient-matched TILs and healthy repertoires, collecting healthy tissue adjacent to the tumors. The current study collected TILs from patients with high-grade serous ovarian carcinoma (HGSOC) and healthy ovary repertoires from cancer-free women undergoing hysterectomy/salpingo-oophorectomy for benign disease. Thus, the classification task is distinguishing women with cancer from women without cancer. Second, in the prior study, classification accuracy was measured by patient-hold-out cross-validation on the training data. In the current study, classification accuracy was additionally assessed on an independent cohort not used during model development to establish the generalizability of the motif to unseen data. Classification accuracy was 95% by patient-hold-out cross-validation on the training set and 80% when the model was applied to the blinded test set. The results on the blinded test set demonstrate a biophysicochemical TCR motif found overwhelmingly in women with HGSOC but rarely in women with healthy ovaries, strengthening the proposal that cancer detection approaches might benefit from incorporation of TCR motif-based biomarkers. Furthermore, these results call for studies on large cohorts to establish higher classification accuracies, as well as for studies in other cancer types.

Detection of tumor antigens and tumor-antigen specific T cells in NSCLC patients: Correlation of the quality of T cell responses with NSCLC subtype

Allogeneic cancer cell lines serve as universal source of tumor-associated antigens in cancer vaccines. Immunogenic high hydrostatic pressure-killed cancer cells derived from cell lines can be used for the generation of dendritic cell (DC)-based active cellular immunotherapy of non-small cell lung cancer (NSCLC). We investigated the expression of 12 known NSCLC tumor-associated antigens (TAA) (CEA, MAGE-A1, MAGE-A3, MAGE-A4, PRAME, hTERT, HER2, MUC1, Survivin, STEAP1, SOX2 and NY-ESO-1) in 6 NSCLC cell lines as candidates for the generation of DC-based lung cancer vaccine. We showed that the selected antigenic profile of these cell lines overlaps to various degrees with that of primary NSCLC tumors (n = 52), indicating that 4 out of 6 NSCLC cell lines would be suitable for DC-based vaccine generation. We further investigated the presence of TAA-specific T cells in blood of NSCLC patients (n = 32) using commercially available peptide mixes in an in vitro stimulation assay. IFN-γ⁺CD8⁺ and IFN-γ⁺CD4⁺ T cell responses to all antigens were detected in NSCLC patients. Interestingly, despite higher TAA expression in squamous cell carcinoma (SCC) the responsiveness of patients' T cells to stimulation was significantly lower in SCC patients than in adenocarcinoma (AC) patients. This suggests qualitative differences in T cell functionality between NSCLC subtypes. Based on this study, and in order to maximize the amount of treatable patients, we selected a mix of H520 and H522 NSCLC cell lines for DC-based vaccine preparation. We also established a minimal panel of antigenic peptide mixes (CEA, hTERT, PRAME, HER2) for immunomonitoring of T cell responses during the DC-based lung cancer immunotherapy in Phase I lung cancer clinical trial (NCT02470468).

Cancer-testis antigens in canine histiocytic sarcoma and other malignancies

Cancer-testis antigens (CTAs) are a category of self proteins aberrantly expressed in diverse malignancies, mostly solid tumours, due to epigenetic de-repression. Normally expressed only in fetal or gametogenic tissues, CTAs are tantalizing immunotherapy targets, since autoimmunity risks appear minimal. Few prevalent CTAs have been identified in human hematologic cancers, and just two in their veterinary counterparts. We sought to discover new CTAs in canine hematologic cancers such as histiocytic sarcoma (HS) and lymphoma to foster immunotherapy development. To accomplish this, the ligandome binding the dog leukocyte antigen (DLA)-88*508:01 class I allele overexpressed in an HS line was searched by mass spectrometry to identify possible CTA-derived peptides, which could serve as CD8+ T-cell epitopes. Twenty-two peptides mapped to 5 human CTAs and 12 additional proteins with CTA characteristics. Expression of five promising candidates was then evaluated in tumour and normal tissue by quantitative and end-point RT-PCR. The ortholog of an established CTA, IGF2BP3, had unexpectedly high expression in peripheral blood mononuclear cells (PBMCs). Four other testis-enhanced proteins were also assessed. AKR1E2, SPECC1 and TPX2 were expressed variably in HS and T-cell lymphoma biopsies, but also at high levels in critical tissues, including kidney, brain and marrow, diminishing their utility. A more tissue-restricted candidate, NT5C1B, was detected in T-cell lymphomas, but also at low levels in some normal dog tissues. These results illustrate the feasibility of discovering canine CTAs by a reverse approach, proceeding from identification of MHC class I-presented peptides to a comparative RNA expression survey of tumours and normal tissues.

The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy

Checkpoint inhibitor-based immunotherapies that target cytotoxic T lymphocyte antigen 4 (CTLA4) or the programmed cell death 1 (PD1) pathway have achieved impressive success in the treatment of different cancer types. Yet, only a subset of patients derive clinical benefit. It is thus critical to understand the determinants driving response, resistance and adverse effects. In this Review, we discuss recent work demonstrating that immune checkpoint inhibitor efficacy is affected by a combination of factors involving tumour genomics, host germline genetics, PD1 ligand 1 (PDL1) levels and other features of the tumour microenvironment, as well as the gut microbiome. We focus on recently identified molecular and cellular determinants of response. A better understanding of how these variables cooperate to affect tumour-host interactions is needed to optimize the implementation of precision immunotherapy.

Tumour-reactive T cell subsets in the microenvironment of ovarian cancer

BACKGROUND

Solid malignancies are frequently infiltrated with T cells. The success of adoptive cell transfer (ACT) with expanded tumour-infiltrating lymphocytes (TILs) in melanoma warrants its testing in other cancer types. In this preclinical study, we investigated whether clinical-grade TILs could be manufactured from ovarian cancer (OC) tumour specimens.

METHODS

Thirty-four tumour specimens were obtained from 33 individual patients with OC. TILs were analysed for phenotype, antigen specificity and functionality.

RESULTS

Minimally expanded TILs (Young TILs) were successfully established from all patients. Young TILs contained a high frequency of CD3⁺ cells with a variable CD4/CD8 ratio. TILs could be expanded to clinical numbers. Importantly, recognition of autologous tumour cells was demonstrated in TILs in >50% of the patients. We confirmed with mass spectrometry the presentation of multiple tumour antigens, including peptides derived from the cancer-testis antigen GAGE, which could be recognised by antigen-specific TILs. Antigen-specific TILs could be isolated and further expanded in vitro.

CONCLUSION

These findings support the hypothesis that patients with OC can benefit from ACT with TILs and led to the initiation of a pilot clinical trial at our institution .

TRIAL REGISTRATION

clinicaltrials.gov: NCT02482090.

Tumour-reactive T cell subsets in the microenvironment of ovarian cancer

Background

Solid malignancies are frequently infiltrated with T cells. The success of adoptive cell transfer (ACT) with expanded tumour-infiltrating lymphocytes (TILs) in melanoma warrants its testing in other cancer types. In this preclinical study, we investigated whether clinical-grade TILs could be manufactured from ovarian cancer (OC) tumour specimens.

Methods

Thirty-four tumour specimens were obtained from 33 individual patients with OC. TILs were analysed for phenotype, antigen specificity and functionality.

Results

Minimally expanded TILs (Young TILs) were successfully established from all patients. Young TILs contained a high frequency of CD3⁺ cells with a variable CD4/CD8 ratio. TILs could be expanded to clinical numbers. Importantly, recognition of autologous tumour cells was demonstrated in TILs in >50% of the patients. We confirmed with mass spectrometry the presentation of multiple tumour antigens, including peptides derived from the cancer-testis antigen GAGE, which could be recognised by antigen-specific TILs. Antigen-specific TILs could be isolated and further expanded in vitro.

Conclusion

These findings support the hypothesis that patients with OC can benefit from ACT with TILs and led to the initiation of a pilot clinical trial at our institution .

Trial Registration

clinicaltrials.gov: NCT02482090.

Biophysicochemical Motifs in T-cell Receptor Sequences Distinguish Repertoires from Tumor-Infiltrating Lymphocyte and Adjacent Healthy Tissue

Immune repertoire deep sequencing allows comprehensive characterization of antigen receptor-encoding genes in a lymphocyte population. We hypothesized that this method could enable a novel approach to diagnose disease by identifying antigen receptor sequence patterns associated with clinical phenotypes. In this study, we developed statistical classifiers of T-cell receptor (TCR) repertoires that distinguish tumor tissue from patient-matched healthy tissue of the same organ. The basis of both classifiers was a biophysicochemical motif in the complementarity determining region 3 (CDR3) of TCRβ chains. To develop each classifier, we extracted 4-mers from every TCRβ CDR3 and represented each 4-mer using biophysicochemical features of its amino acid sequence combined with quantification of 4-mer (or receptor) abundance. This representation was scored using a logistic regression model. Unlike typical logistic regression, the classifier is fitted and validated under the requirement that at least 1 positively labeled 4-mer appears in every tumor repertoire and no positively labeled 4-mers appear in healthy tissue repertoires. We applied our method to publicly available data in which tumor and adjacent healthy tissue were collected from each patient. Using a patient-holdout cross-validation, our method achieved classification accuracy of 93% and 94% for colorectal and breast cancer, respectively. The parameter values for each classifier revealed distinct biophysicochemical properties for tumor-associated 4-mers within each cancer type. We propose that such motifs might be used to develop novel immune-based cancer screening assays. SIGNIFICANCE: This study presents a novel computational approach to identify T-cell repertoire differences between normal and tumor tissue.See related commentary by Zoete and Coukos, p. 1299.

The role of tumor microenvironment in therapeutic resistance

Cancer cells undergo unlimited progression and survival owing to activation of oncogenes. However, support of the tumor microenvironment is essential to the formation of clinically relevant tumors. Recent evidence indicates that the tumor microenvironment is a critical regulator of immune escape, progression, and distant metastasis of cancer. Moreover, the tumor microenvironment is known to be involved in acquired resistance of tumors to various therapies. Despite significant advances in chemotherapy and radiotherapy, occurrence of therapeutic resistance leads to reduced efficacy. This review highlights myeloid cells, cancer-associated fibroblasts, and mesenchymal stem cells consisting of the tumor microenvironment, as well as the relevant signaling pathways that eventually render cancer cells to be therapeutically resistant.

Molecular Biomarkers of Primary and Acquired Resistance to T-Cell-Mediated Immunotherapy in Cancer: Landscape, Clinical Implications, and Future Directions

The emergence of immunotherapy has revolutionized cancer treatment in recent years. Inhibitors of immune checkpoints, including antibodies against cytotoxic T-lymphocyte-associated protein 4, programmed cell death protein 1, and programmed death ligand 1, have demonstrated notable efficacy in certain advanced cancers. Unfortunately, many patients do not benefit from these therapies and either exhibit primary resistance to treatment or develop acquired mechanisms of resistance after initially responding to therapy. Here, we review the genomic and immune traits that may promote resistance to T-cell-mediated immunotherapy, with a focus on identifying potential biomarkers that could eventually be used in the clinical setting to guide treatment selection. We summarize the clinical evidence for these markers and discuss how current understanding of resistance mechanisms can inform future studies and aid clinical decision-making in order to derive maximum benefit from immunotherapy.

IMPLICATIONS FOR PRACTICE

Immunotherapy has rapidly progressed as a treatment modality for multiple cancers, but it is still unclear which patients are likely to benefit from these therapies. Studies of resistance mechanisms have only recently started to identify biomarkers that can help predict patient outcomes. This review summarizes the available clinical data in regard to immunotherapy resistance, with a focus on molecular biomarkers that may be useful in guiding clinical decision-making. It discusses possible applications of these biomarkers and highlights opportunities for further clinical discovery.

Immunogenic FEAT protein circulates in the bloodstream of cancer patients

BACKGROUND

FEAT is an intracellular protein that potently drives tumorigenesis in vivo. It is only weakly expressed in normal human tissues, including the testis. In contrast, FEAT is aberrantly upregulated in most human cancers. The present study was designed to investigate whether FEAT is applicable to tumor immunotherapy and whether FEAT is discernible in the bloodstream as a molecular biomarker of human cancers.

METHODS

Two mouse FEAT peptides with predicted affinities for major histocompatibility complex H-2Kb and H-2Db were injected subcutaneously into C57BL/6 mice before subcutaneous transplantation of isogenic B16-F10 melanoma cells. Intracellular localization of FEAT was determined by immunogold electron microscopy. Immunoprecipitation was performed to determine whether FEAT was present in blood from cancer patients. A sandwich enzyme-linked immunosorbent assay was used to measure FEAT concentrations in plasma from 30 cancer patients and eight healthy volunteers.

RESULTS

The vaccination experiments demonstrated that FEAT was immunogenic, and that immune responses against FEAT were induced without deleterious side effects in mice. Electron microscopy revealed localization of FEAT in the cytoplasm, mitochondria, and nucleus. Immunoprecipitation identified FEAT in the blood plasma from cancer patients, while FEAT was not detected in plasma exosomes. Plasma FEAT levels were significantly higher in the presence of cancers.

CONCLUSIONS

These findings suggest that FEAT is a candidate for applications in early diagnosis and prevention of some cancers.

Tumour antigen expression in hepatocellular carcinoma in a low-endemic western area

Background:

Identification of tumour antigens is crucial for the development of vaccination strategies against hepatocellular carcinoma (HCC). Most studies come from eastern-Asia, where hepatitis-B is the main cause of HCC. However, tumour antigen expression is poorly studied in low-endemic, western areas where the aetiology of HCC differs.

Methods:

We constructed tissue microarrays from resected HCC tissue of 133 patients. Expression of a comprehensive panel of cancer-testis (MAGE-A1, MAGE-A3/4, MAGE-A10, MAGE-C1, MAGE-C2, NY-ESO-1, SSX-2, sperm protein 17), onco-fetal (AFP, Glypican-3) and overexpressed tumour antigens (Annexin-A2, Wilms tumor-1, Survivin, Midkine, MUC-1) was determined by immunohistochemistry.

Results:

A higher prevalence of MAGE antigens was observed in patients with hepatitis-B. Patients with expression of more tumour antigens in general had better HCC-specific survival (P=0.022). The four tumour antigens with high expression in HCC and no, or weak, expression in surrounding tumour-free-liver tissue, were Annexin-A2, GPC-3, MAGE-C1 and MAGE-C2, expressed in 90, 39, 17 and 20% of HCCs, respectively. Ninety-five percent of HCCs expressed at least one of these four tumour antigens. Interestingly, GPC-3 was associated with SALL-4 expression (P=0.001), an oncofetal transcription factor highly expressed in embryonal stem cells. SALL-4 and GPC-3 expression levels were correlated with vascular invasion, poor differentiation and higher AFP levels before surgery. Moreover, patients who co-expressed higher levels of both GPC-3 and SALL-4 had worse HCC-specific survival (P=0.018).

Conclusions:

We describe a panel of four tumour antigens with excellent coverage and good tumour specificity in a western area, low-endemic for hepatitis-B. The association between GPC-3 and SALL-4 is a novel finding and suggests that GPC-3 targeting may specifically attack the tumour stem-cell compartment.

Strong spontaneous tumor neoantigen responses induced by a natural human carcinogen

A key to improving cancer immunotherapy will be the identification of tumor-specific "neoantigens" that arise from mutations and augment the resultant host immune response. In this study we identified single nucleotide variants (SNVs) by RNA sequencing of asbestos-induced murine mesothelioma cell lines AB1 and AB1-HA. Using the NetMHCpan 2.8 algorithm, the theoretical binding affinity of predicted peptides arising from high-confidence, exonic, non-synonymous SNVs was determined for the BALB/c strain. The immunoreactivity to 20 candidate mutation-carrying peptides of increased affinity and the corresponding wild-type peptides was determined using interferon-γ ELISPOT assays and lymphoid organs of non-manipulated tumor-bearing mice. A strong endogenous immune response was demonstrated to one of the candidate neoantigens, Uqcrc2; this response was detected in the draining lymph node and spleen. Antigen reactive cells were not detected in non-tumor bearing mice. The magnitude of the response to the Uqcrc2 neoantigen was similar to that of the strong influenza hemagglutinin antigen, a model tumor neoantigen. This work confirms that the approach of RNAseq plus peptide prediction and ELISPOT testing is sufficient to identify natural tumor neoantigens.

Innate immune recognition of cancer

The observation that a subset of cancer patients show evidence for spontaneous CD8+ T cell priming against tumor-associated antigens has generated renewed interest in the innate immune pathways that might serve as a bridge to an adaptive immune response to tumors. Manipulation of this endogenous T cell response with therapeutic intent-for example, using blocking antibodies inhibiting PD-1/PD-L1 (programmed death-1/programmed death ligand 1) interactions-is showing impressive clinical results. As such, understanding the innate immune mechanisms that enable this T cell response has important clinical relevance. Defined innate immune interactions in the cancer context include recognition by innate cell populations (NK cells, NKT cells, and γδ T cells) and also by dendritic cells and macrophages in response to damage-associated molecular patterns (DAMPs). Recent evidence has indicated that the major DAMP driving host antitumor immune responses is tumor-derived DNA, sensed by the stimulator of interferon gene (STING) pathway and driving type I IFN production. A deeper knowledge of the clinically relevant innate immune pathways involved in the recognition of tumors is leading toward new therapeutic strategies for cancer treatment.

Acquired and intrinsic resistance in cancer immunotherapy

A number of immunotherapies, in particular immune checkpoint targeting antibodies and adoptive T-cell therapies, are starting to transform the treatment of advanced cancers. The likelihood to respond to these immunotherapies differs strongly across tumor types, with response rates for checkpoint targeting being the highest in advanced melanoma, renal cell cancer and non-small cell lung cancer. However, also non-responsiveness is observed, indicating the presence of intrinsic resistance or naturally acquired resistance. In addition, a subgroup of patients that do initially respond to immunotherapy will later recur, thereby also pointing towards a role of therapy-induced acquired resistance. Here, we review our current understanding of both intrinsic and acquired resistance mechanisms in cancer immunotherapy, and discuss potential strategies to overcome them.

Expression of new antigens on tumor cells by inhibiting nonsense-mediated mRNA decay

The main reason why tumors are not controlled by the immune system of the cancer patient is that tumors do not express potent tumor antigens that can be recognized by the immune system as "foreign." The current focus in developing immune-based modalities is to potentiate an immune response against the existing, albeit weak, antigens expressed in the tumor. An alternative approach is to express new, and hence potent, antigens in tumor cells in situ. To this end, we have developed an approach to generate new antigenic determinants in tumor cells using siRNA technology to inhibit nonsense-mediated mRNA decay (NMD), a surveillance mechanism which prevents the expression of mRNAs containing a premature termination codon. Targeting siRNA inhibition to tumor cells--an essential requisite because of the constitutive nature and physiological roles of the NMD process--is accomplished by using a novel targeting technology based on using oligonucleotide aptamer ligands. Aptamers or aptamer-targeted siRNA conjugates, unlike antibodies, can be synthesized in a chemical process providing a more straightforward and cost-effective manufacturing and regulatory approval process to generate clinical-grade reagents. In murine tumor models, the aptamer-targeted siRNA-mediated NMD inhibition in tumor cells led to significant inhibition of tumor growth, which was superior to best-in-class "conventional" cancer vaccination protocols. Tumor-targeted NMD inhibition forms the basis of a simple, broadly useful, and clinically feasible approach to enhance the antigenicity of disseminated tumors leading to their immune recognition and rejection. The cell-free chemically synthesized oligonucleotide backbone of aptamer-siRNAs reduces the risk of immunogenicity and enhances the feasibility of generating reagents suitable for clinical use.

Antigen-specific culture of memory-like CD8 T cells for adoptive immunotherapy

Cytotoxic T cells typically are expanded ex vivo in culture with IL2 for adoptive immunotherapy. This culture period leads to a differentiated phenotype and acquisition of effector function, as well as a loss of in vivo proliferative capability and antitumor efficacy. Here, we report antigen-specific and polyclonal expansion of cytotoxic T cells in a cocktail of cytokines and small molecules that leads to a memory-like phenotype in mouse and human cells even during extended culture, leading to enhanced in vivo expansion and tumor control in mice.

HLA micropolymorphisms strongly affect peptide-MHC multimer-based monitoring of antigen-specific CD8+ T cell responses

Peptide-MHC (pMHC) multimers have become one of the most widely used tools to measure Ag-specific T cell responses in humans. With the aim of understanding the requirements for pMHC-based personalized immunomonitoring, in which individuals expressing subtypes of the commonly studied HLA alleles are encountered, we assessed how the ability to detect Ag-specific T cells for a given peptide is affected by micropolymorphic differences between HLA subtypes. First, analysis of a set of 10 HLA-A*02:01-restricted T cell clones demonstrated that staining with pMHC multimers of seven distinct subtypes of the HLA-A*02 allele group was highly variable and not predicted by sequence homology. Second, to analyze the effect of minor sequence variation in a clinical setting, we screened tumor-infiltrating lymphocytes of an HLA-A*02:06 melanoma patient with either subtype-matched or HLA-A*02:01 multimers loaded with 145 different melanoma-associated Ags. This revealed that of the four HLA-A*02:06-restricted melanoma-associated T cell responses observed in this patient, two responses were underestimated and one was overlooked when using subtype-mismatched pMHC multimer collections. To our knowledge, these data provide the first demonstration of the strong effect of minor sequence variation on pMHC-based personalized immunomonitoring, and they provide tools to prevent this issue for common variants within the HLA-A*02 allele group.

Alkylating chemotherapy may exert a uniquely deleterious effect upon neo-antigen-targeting anticancer vaccination

Alkylating chemotherapy exerts both antineoplastic and immunostimulatory effects. However, in addition to depleting regulatory T cells (Treg), alkylating agents also mediate a long lasting antiproliferative effect on responder lymphocytes. Our recent findings indicate that this antiproliferative effect profoundly impairs vaccination-induced immune responses, especially in the case of vaccines that target specific tumor-associated neo-antigens that do not require Treg depletion.

Repositioning therapeutic cancer vaccines in the dawning era of potent immune interventions

Based on lessons learned with various immune interventions, this review aims to provide a constructive framework for repositioning therapeutic cancer vaccination. Intensive research throughout the past decade has identified key hurdles interfering with the efficacy of cancer vaccines. The vaccination concept still holds promise if positioned appropriately in minimal residual disease and select early disease stage cancer indications. However, in advanced cancer, it must be integrated with complementary immune interventions to ensure reconstruction of a functional immune repertoire and simultaneous blockade of immune inhibiting mechanisms. Vaccination could render complex and integrative immune interventions simpler, safer and more effective. The near future will witness an explosion of activities in the cancer immunotherapy arena, witnessing a rational repositioning of vaccines rather than their extinction.

A personalized view on cancer immunotherapy

Recent progress in cancer immunotherapy has resulted in complete responses in patients refractory to current standard cancer therapies. However, due to tumor heterogeneity and inter-individual variations in anti-tumor immunity, only subsets of patients experience clinical benefit. This review highlights the implementation of a personalized approach to enhance treatment efficacy and reduce side effects, including the identification of tumor-specific antigens for cancer vaccination and adoptive T cell therapies. Furthermore, together with the current advances and promising clinical outcomes of combination cancer (immuno-)therapies, the screening for predictive biomarkers in a patient-specific manner is emphasized.

MAGE-A3-specific anticancer immunotherapy in the clinical practice

Antigen-specific immunotherapy may offer a unique approach to fight cancer. We have demonstrated that specific immunotherapeutic regimens involving recombinant melanoma antigen family A3 (MAGE-A3) and different immunostimulants exert clinical anticancer activity. In particular, the combination of recombinant MAGE-A3 and AS15, a multicomponent immunostimulant, was found to elicit robust antigen-specific immune responses.