Exploiting non-canonical translation to identify new targets for T cell-based cancer immunotherapy

Translation dysregulation in cancer as a source for targetable antigens

Aberrant peptides presented by major histocompatibility complex (MHC) molecules are targets for tumor eradication, as these peptides can be recognized as foreign by T cells. Protein synthesis in malignant cells is dysregulated, which may result in the generation and presentation of aberrant peptides that can be exploited for T cell-based therapies. To investigate the role of translational dysregulation in immunological tumor control, we disrupt translation fidelity by deleting tRNA wybutosine (yW)-synthesizing protein 2 (TYW2) in tumor cells and characterize the downstream impact on translation fidelity and immunogenicity using immunopeptidomics, genomics, and functional assays. These analyses reveal that TYW2 knockout (KO) cells generate immunogenic out-of-frame peptides. Furthermore, Tyw2 loss increases tumor immunogenicity and leads to anti-programmed cell death 1 (PD-1) checkpoint blockade sensitivity in vivo. Importantly, reduced TYW2 expression is associated with increased response to checkpoint blockade in patients. Together, we demonstrate that defects in translation fidelity drive tumor immunogenicity and may be leveraged for cancer immunotherapy.

Immunogenic cryptic peptides dominate the antigenic landscape of ovarian cancer

Increased infiltration of CD3+ and CD8+ T cells into ovarian cancer (OC) is linked to better prognosis, but the specific antigens involved are unclear. Recent reports suggest that HLA class I can present peptides from noncoding genomic regions, known as noncanonical or cryptic peptides, but their immunogenicity is underexplored. To address this, we used immunopeptidomic analysis and RNA sequencing on five metastatic OC samples, which identified 311 cryptic peptides (40 to 83 per patient). Despite comprising less than 1% of total peptides, cryptic peptides from noncoding transcripts emerged as the predominant antigen class when compared to the other major classes of known tumor-specific and tumor-associated antigens in OC samples. Notably, nearly 70% of the prioritized cryptic peptides elicited T cell activation, as evidenced by increased 4-1BB and IFN-γ expression in autologous CD8+ T cells. This study reveals noncoding cryptic peptides as an important class of immunogenic antigens in OC.

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

Crucial Parameters for Immunopeptidome Characterization: A Systematic Evaluation

Immunopeptidomics is the area of knowledge focused on the study of peptides assembled in the major histocompatibility complex (MHC), or human leukocyte antigen (HLA) in humans, which could activate the immune response via specific and selective T cell recognition. Advances in high-sensitivity mass spectrometry have enabled the detailed identification and quantification of the immunopeptidome, significantly impacting fields like oncology, infections, and autoimmune diseases. Current immunopeptidomics approaches primarily focus on workflows to identify immunopeptides from HLA molecules, requiring the isolation of the HLA from relevant cells or tissues. Common critical steps in these workflows, such as cell lysis, HLA immunoenrichment, and peptide isolation, significantly influence outcomes. A systematic evaluation of these steps led to the creation of an 'Immunopeptidome Score' to enhance the reproducibility and robustness of these workflows. This score, derived from LC-MS/MS datasets (ProteomeXchange identifier PXD038165), in combination with available information from public databases, aids in optimizing the immunopeptidome characterization process. The 'Immunopeptidome Score' has been applied in a systematic analysis of protein extraction, HLA immunoprecipitation, and peptide recovery yields across several tumor cell lines enabling the selection of peptides with optimal features and, therefore, the identification of potential biomarker and therapeutic targets.

Immunogenicity of Non-Mutated Ovarian Cancer-Specific Antigens

Epithelial ovarian cancer (EOC) has not significantly benefited from advances in immunotherapy, mainly because of the lack of well-defined actionable antigen targets. Using proteogenomic analyses of primary EOC tumors, we previously identified 91 aberrantly expressed tumor-specific antigens (TSAs) originating from unmutated genomic sequences. Most of these TSAs derive from non-exonic regions, and their expression results from cancer-specific epigenetic changes. The present study aimed to evaluate the immunogenicity of 48 TSAs selected according to two criteria: presentation by highly prevalent HLA allotypes and expression in a significant fraction of EOC tumors. Using targeted mass spectrometry analyses, we found that pulsing with synthetic TSA peptides leads to a high-level presentation on dendritic cells. TSA abundance correlated with the predicted binding affinity to the HLA allotype. We stimulated naïve CD8 T cells from healthy blood donors with TSA-pulsed dendritic cells and assessed their expansion with two assays: MHC-peptide tetramer staining and TCR Vβ CDR3 sequencing. We report that these TSAs can expand sizeable populations of CD8 T cells and, therefore, represent attractive targets for EOC immunotherapy.

Recent Findings on Therapeutic Cancer Vaccines: An Updated Review

Cancer remains one of the global leading causes of death and various vaccines have been developed over the years against it, including cell-based, nucleic acid-based, and viral-based cancer vaccines. Although many vaccines have been effective in in vivo and clinical studies and some have been FDA-approved, there are major limitations to overcome: (1) developing one universal vaccine for a specific cancer is difficult, as tumors with different antigens are different for different individuals, (2) the tumor antigens may be similar to the body's own antigens, and (3) there is the possibility of cancer recurrence. Therefore, developing personalized cancer vaccines with the ability to distinguish between the tumor and the body's antigens is indispensable. This paper provides a comprehensive review of different types of cancer vaccines and highlights important factors necessary for developing efficient cancer vaccines. Moreover, the application of other technologies in cancer therapy is discussed. Finally, several insights and conclusions are presented, such as the possibility of using cold plasma and cancer stem cells in developing future cancer vaccines, to tackle the major limitations in the cancer vaccine developmental process.

FusionVAC22_01: a phase I clinical trial evaluating a DNAJB1-PRKACA fusion transcript-based peptide vaccine combined with immune checkpoint inhibition for fibrolamellar hepatocellular carcinoma and other tumor entities carrying the oncogenic driver fusion

The DNAJB1-PRKACA fusion transcript was identified as the oncogenic driver of tumor pathogenesis in fibrolamellar hepatocellular carcinoma (FL-HCC), also known as fibrolamellar carcinoma (FLC), as well as in other tumor entities, thus representing a broad target for novel treatment in multiple cancer entities. FL-HCC is a rare primary liver tumor with a 5-year survival rate of only 45%, which typically affects young patients with no underlying primary liver disease. Surgical resection is the only curative treatment option if no metastases are present at diagnosis. There is no standard of care for systemic therapy. Peptide-based vaccines represent a low side-effect approach relying on specific immune recognition of tumor-associated human leucocyte antigen (HLA) presented peptides. The induction (priming) of tumor-specific T-cell responses against neoepitopes derived from gene fusion transcripts by peptide-vaccination combined with expansion of the immune response and optimization of immune function within the tumor microenvironment achieved by immune-checkpoint-inhibition (ICI) has the potential to improve response rates and durability of responses in malignant diseases. The phase I clinical trial FusionVAC22_01 will enroll patients with FL-HCC or other cancer entities carrying the DNAJB1-PRKACA fusion transcript that are locally advanced or metastatic. Two doses of the DNAJB1-PRKACA fusion-based neoepitope vaccine Fusion-VAC-XS15 will be applied subcutaneously (s.c.) with a 4-week interval in combination with the anti-programmed cell death-ligand 1 (PD-L1) antibody atezolizumab starting at day 15 after the first vaccination. Anti-PD-L1 will be applied every 4 weeks until end of the 54-week treatment phase or until disease progression or other reason for study termination. Thereafter, patients will enter a 6 months follow-up period. The clinical trial reported here was approved by the Ethics Committee II of the University of Heidelberg (Medical faculty of Mannheim) and the Paul-Ehrlich-Institute (P-00540). Clinical trial results will be published in peer-reviewed journals.

Trial registration numbers

EU CT Number: 2022-502869-17-01 and ClinicalTrials.gov Registry (NCT05937295).

Precision medicine in the era of multi-omics: can the data tsunami guide rational treatment decision?

Precision medicine for cancer is rapidly moving to an approach that integrates multiple dimensions of the biology in order to model mechanisms of cancer progression in each patient. The discovery of multiple drivers per tumor challenges medical decision that faces several treatment options. Drug sensitivity depends on the actionability of the target, its clonal or subclonal origin and coexisting genomic alterations. Sequencing has revealed a large diversity of drivers emerging at treatment failure, which are potential targets for clinical trials or drug repurposing. To effectively prioritize therapies, it is essential to rank genomic alterations based on their proven actionability. Moving beyond primary drivers, the future of precision medicine necessitates acknowledging the intricate spatial and temporal heterogeneity inherent in cancer. The advent of abundant complex biological data will make artificial intelligence algorithms indispensable for thorough analysis. Here, we will discuss the advancements brought by the use of high-throughput genomics, the advantages and limitations of precision medicine studies and future perspectives in this field.

Combination of multiple omics techniques for a personalized therapy or treatment selection

Despite targeted therapies and immunotherapies have revolutionized the treatment of cancer patients, only a limited number of patients have long-term responses. Moreover, due to differences within cancer patients in the tumor mutational burden, composition of the tumor microenvironment as well as of the peripheral immune system and microbiome, and in the development of immune escape mechanisms, there is no "one fit all" therapy. Thus, the treatment of patients must be personalized based on the specific molecular, immunologic and/or metabolic landscape of their tumor. In order to identify for each patient the best possible therapy, different approaches should be employed and combined. These include (i) the use of predictive biomarkers identified on large cohorts of patients with the same tumor type and (ii) the evaluation of the individual tumor with "omics"-based analyses as well as its ex vivo characterization for susceptibility to different therapies.

What Can Ribo-Seq, Immunopeptidomics, and Proteomics Tell Us About the Noncanonical Proteome?

Ribosome profiling (Ribo-Seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of noncanonical sites of ribosome translation outside the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7000 noncanonical ORFs are translated, which, at first glance, has the potential to expand the number of human protein CDSs by 30%, from ∼19,500 annotated CDSs to over 26,000 annotated CDSs. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of noncanonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome but searching for guidance on how to proceed. Here, we discuss the current state of noncanonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein coding."

The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells

Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.

Peptide-based vaccine for cancer therapies

Different strategies based on peptides are available for cancer treatment, in particular to counter-act the progression of tumor growth and disease relapse. In the last decade, in the context of therapeutic strategies against cancer, peptide-based vaccines have been evaluated in different tumor models. The peptides selected for cancer vaccine development can be classified in two main type: tumor-associated antigens (TAAs) and tumor-specific antigens (TSAs), which are captured, internalized, processed and presented by antigen-presenting cells (APCs) to cell-mediated immunity. Peptides loaded onto MHC class I are recognized by a specific TCR of CD8+ T cells, which are activated to exert their cytotoxic activity against tumor cells presenting the same peptide-MHC-I complex. This process is defined as active immunotherapy as the host's immune system is either de novo activated or restimulated to mount an effective, tumor-specific immune reaction that may ultimately lead to tu-mor regression. However, while the preclinical data have frequently shown encouraging results, therapeutic cancer vaccines clinical trials, including those based on peptides have not provided satisfactory data to date. The limited efficacy of peptide-based cancer vaccines is the consequence of several factors, including the identification of specific target tumor antigens, the limited immunogenicity of peptides and the highly immunosuppressive tumor microenvironment (TME). An effective cancer vaccine can be developed only by addressing all such different aspects. The present review describes the state of the art for each of such factors.

Antigen-specific and cross-reactive T cells in protection and disease

Human T cells have a diverse T-cell receptor (TCR) repertoire that endows them with the ability to identify and defend against a broad spectrum of antigens. The universe of possible antigens that T cells may encounter, however, is even larger. To effectively surveil such a vast universe, the T-cell repertoire must adopt a high degree of cross-reactivity. Likewise, antigen-specific and cross-reactive T-cell responses play pivotal roles in both protective and pathological immune responses in numerous diseases. In this review, we explore the implications of these antigen-driven T-cell responses, with a particular focus on CD8+ T cells, using infection, neurodegeneration, and cancer as examples. We also summarize recent technological advances that facilitate high-throughput profiling of antigen-specific and cross-reactive T-cell responses experimentally, as well as computational biology approaches that predict these interactions.

What can Ribo-seq and proteomics tell us about the non-canonical proteome?

Ribosome profiling (Ribo-seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of non-canonical sites of ribosome translation outside of the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7,000 non-canonical open reading frames (ORFs) are translated, which, at first glance, has the potential to expand the number of human protein-coding sequences by 30%, from ∼19,500 annotated CDSs to over 26,000. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of non-canonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome, but searching for guidance on how to proceed. Here, we discuss the current state of non-canonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein-coding".

In brief

The human genome encodes thousands of non-canonical open reading frames (ORFs) in addition to protein-coding genes. As a nascent field, many questions remain regarding non-canonical ORFs. How many exist? Do they encode proteins? What level of evidence is needed for their verification? Central to these debates has been the advent of ribosome profiling (Ribo-seq) as a method to discern genome-wide ribosome occupancy, and immunopeptidomics as a method to detect peptides that are processed and presented by MHC molecules and not observed in traditional proteomics experiments. This article provides a synthesis of the current state of non-canonical ORF research and proposes standards for their future investigation and reporting.

Highlights

Combined use of Ribo-seq and proteomics-based methods enables optimal confidence in detecting non-canonical ORFs and their protein products.Ribo-seq can provide more sensitive detection of non-canonical ORFs, but data quality and analytical pipelines will impact results.Non-canonical ORF catalogs are diverse and span both high-stringency and low-stringency ORF nominations.A framework for standardized non-canonical ORF evidence will advance the research field.

The biogenesis of the immunopeptidome

The immunopeptidome is the repertoire of peptides bound and presented by the MHC class I, class II, and non-classical molecules. The peptides are produced by the degradation of most cellular proteins, and in some cases, peptides are produced from extracellular proteins taken up by the cells. This review attempts to first describe some of its known and well-accepted concepts, and next, raise some questions about a few of the established dogmas in this field: The production of novel peptides by splicing is questioned, suggesting here that spliced peptides are extremely rare, if existent at all. The degree of the contribution to the immunopeptidome by degradation of cellular protein by the proteasome is doubted, therefore this review attempts to explain why it is likely that this contribution to the immunopeptidome is possibly overstated. The contribution of defective ribosome products (DRiPs) and non-canonical peptides to the immunopeptidome is noted and methods are suggested to quantify them. In addition, the common misconception that the MHC class II peptidome is mostly derived from extracellular proteins is noted, and corrected. It is stressed that the confirmation of sequence assignments of non-canonical and spliced peptides should rely on targeted mass spectrometry using spiking-in of heavy isotope-labeled peptides. Finally, the new methodologies and modern instrumentation currently available for high throughput kinetics and quantitative immunopeptidomics are described. These advanced methods open up new possibilities for utilizing the big data generated and taking a fresh look at the established dogmas and reevaluating them critically.

Antigen discovery for the development of cancer immunotherapy

Central to successful cancer immunotherapy is effective T cell antitumor immunity. Multiple targeted immunotherapies engineered to invigorate T cell-driven antitumor immunity rely on identifying the repertoire of T cell antigens expressed on the tumor cell surface. Mass spectrometry-based survey of such antigens ("immunopeptidomics") combined with other omics platforms and computational algorithms has been instrumental in identifying and quantifying tumor-derived T cell antigens. In this review, we discuss the types of tumor antigens that have emerged for targeted cancer immunotherapy and the immunopeptidomics methods that are central in MHC peptide identification and quantification. We provide an overview of the strength and limitations of mass spectrometry-driven approaches and how they have been integrated with other technologies to discover targetable T cell antigens for cancer immunotherapy. We highlight some of the emerging cancer immunotherapies that successfully capitalized on immunopeptidomics, their challenges, and mass spectrometry-based strategies that can support their development.

PGNneo: A Proteogenomics-Based Neoantigen Prediction Pipeline in Noncoding Regions

The development of a neoantigen-based personalized vaccine has promise in the hunt for cancer immunotherapy. The challenge in neoantigen vaccine design is the need to rapidly and accurately identify, in patients, those neoantigens with vaccine potential. Evidence shows that neoantigens can be derived from noncoding sequences, but there are few specific tools for identifying neoantigens in noncoding regions. In this work, we describe a proteogenomics-based pipeline, namely PGNneo, for use in discovering neoantigens derived from the noncoding region of the human genome with reliability. In PGNneo, four modules are included: (1) noncoding somatic variant calling and HLA typing; (2) peptide extraction and customized database construction; (3) variant peptide identification; (4) neoantigen prediction and selection. We have demonstrated the effectiveness of PGNneo and applied and validated our methodology in two real-world hepatocellular carcinoma (HCC) cohorts. TP53, WWP1, ATM, KMT2C, and NFE2L2, which are frequently mutating genes associated with HCC, were identified in two cohorts and corresponded to 107 neoantigens from non-coding regions. In addition, we applied PGNneo to a colorectal cancer (CRC) cohort, demonstrating that the tool can be extended and verified in other tumor types. In summary, PGNneo can specifically detect neoantigens generated by noncoding regions in tumors, providing additional immune targets for cancer types with a low tumor mutational burden (TMB) in coding regions. PGNneo, together with our previous tool, can identify coding and noncoding region-derived neoantigens and, thus, will contribute to a complete understanding of the tumor immune target landscape. PGNneo source code and documentation are available at Github. To facilitate the installation and use of PGNneo, we provide a Docker container and a GUI.

TCR-engineered T cell therapy in solid tumors: State of the art and perspectives

T cell engineering has changed the landscape of cancer immunotherapy. Chimeric antigen receptor T cells have demonstrated a remarkable efficacy in the treatment of B cell malignancies in hematology. However, their clinical impact on solid tumors has been modest so far. T cells expressing an engineered T cell receptor (TCR-T cells) represent a promising therapeutic alternative. The target repertoire is not limited to membrane proteins, and intrinsic features of TCRs such as high antigen sensitivity and near-to-physiological signaling may improve tumor cell detection and killing while improving T cell persistence. In this review, we present the clinical results obtained with TCR-T cells targeting different tumor antigen families. We detail the different methods that have been developed to identify and optimize a TCR candidate. We also discuss the challenges of TCR-T cell therapies, including toxicity assessment and resistance mechanisms. Last, we share some perspectives and highlight future directions in the field.

Leveraging a powerful allogeneic dendritic cell line towards neoantigen-based cancer vaccines

In recent years, immunotherapy has finally found its place in the anti-cancer therapeutic arsenal, even becoming standard of care as first line treatment for metastatic forms. The clinical benefit provided by checkpoint blockers such as anti-PD-1/PD-L1 in many cancers revolutionized the field. However, too many patients remain refractory to these treatments due to weak baseline anti-cancer immunity. There is therefore a need to boost the frequency and function of patients' cytotoxic CD8+ cellular effectors by targeting immunogenic and tumor-restricted antigens, such as neoantigens using an efficient vaccination platform. Dendritic cells (DC) are the most powerful immune cell subset for triggering cellular immune response. However, autologous DC-based vaccines display several limitations, such as the lack of reproducibility and the limited number of cells that can be manufactured. Here we discuss the advantages of a new therapeutic vaccine based on an allogeneic Plasmacytoid DC cell line, which is easy to produce and represents a powerful platform for priming and expanding anti-neoantigen cytotoxic CD8+ T-cells.

T cells of colorectal cancer patients' stimulated by neoantigenic and cryptic peptides better recognize autologous tumor cells

BACKGROUND

Patients with cancers that exhibit extraordinarily high somatic mutation numbers are ideal candidates for immunotherapy and enable identifying tumor-specific peptides through stimulation of tumor-reactive T cells (Tc).

METHODS

Colorectal cancers (CRC) HROC113 and HROC285 were selected based on high TMB, microsatellite instability and HLA class I expression. Their HLA ligandome was characterized using mass spectrometry, compared with the HLA ligand atlas and HLA class I-binding affinity was predicted. Cryptic peptides were identified using Peptide-PRISM. Patients' Tc were isolated from either peripheral blood (pTc) or tumor material (tumor-infiltrating Tc, TiTc) and expanded. In addition, B-lymphoblastoid cells (B-LCL) were generated and used as antigen-presenting cells. pTc and TiTc were stimulated twice for 7 days using peptide pool-loaded B-LCL. Subsequently, interferon gamma (IFNγ) release was quantified by ELISpot. Finally, cytotoxicity against autologous tumor cells was assessed in a degranulation assay.

RESULTS

100 tumor-specific candidate peptides-97 cryptic peptides and 3 classically mutated neoantigens-were selected. The neoantigens originated from single nucleotide substitutions in the genes IQGAP1, CTNNB1, and TRIT1. Cryptic and neoantigenic peptides inducing IFNγ secretion of Tc were further investigated. Stimulation of pTc and TiTc with neoantigens and selected cryptic peptides resulted in increased release of cytotoxic granules in the presence of autologous tumor cells, substantiating their improved tumor cell recognition. Tetramer staining showed an enhanced number of pTc and TiTc specific for the IQGAP1 neoantigen. Subpopulation analysis prior to peptide stimulation revealed that pTc mainly consisted of memory Tc, whereas TiTc constituted primarily of effector and effector memory Tc. This allows to infer that TiTc reacting to neoantigens and cryptic peptides must be present within the tumor microenvironment.

CONCLUSION

These results prove that the analyzed CRC present both mutated neoantigenic and cryptic peptides on their HLA class I molecules. Moreover, stimulation with these peptides significantly strengthened tumor cell recognition by Tc. Since the overall number of neoantigenic peptides identifiable by HLA ligandome analysis hitherto is small, our data emphasize the relevance of increasing the target scope for cancer vaccines by the cryptic peptide category.

The oncogenic fusion protein DNAJB1-PRKACA can be specifically targeted by peptide-based immunotherapy in fibrolamellar hepatocellular carcinoma

The DNAJB1-PRKACA fusion transcript is the oncogenic driver in fibrolamellar hepatocellular carcinoma, a lethal disease lacking specific therapies. This study reports on the identification, characterization, and immunotherapeutic application of HLA-presented neoantigens specific for the DNAJB1-PRKACA fusion transcript in fibrolamellar hepatocellular carcinoma. DNAJB1-PRKACA-derived HLA class I and HLA class II ligands induce multifunctional cytotoxic CD8+ and T-helper 1 CD4+ T cells, and their cellular processing and presentation in DNAJB1-PRKACA expressing tumor cells is demonstrated by mass spectrometry-based immunopeptidome analysis. Single-cell RNA sequencing further identifies multiple T cell receptors from DNAJB1-PRKACA-specific T cells. Vaccination of a fibrolamellar hepatocellular carcinoma patient, suffering from recurrent short interval disease relapses, with DNAJB1-PRKACA-derived peptides under continued Poly (ADP-ribose) polymerase inhibitor therapy induces multifunctional CD4+ T cells, with an activated T-helper 1 phenotype and high T cell receptor clonality. Vaccine-induced DNAJB1-PRKACA-specific T cell responses persist over time and, in contrast to various previous treatments, are accompanied by durable relapse free survival of the patient for more than 21 months post vaccination. Our preclinical and clinical findings identify the DNAJB1-PRKACA protein as source for immunogenic neoepitopes and corresponding T cell receptors and provide efficacy in a single-patient study of T cell-based immunotherapy specifically targeting this oncogenic fusion.

The role of neoantigens in tumor immunotherapy

Tumor neoantigens are aberrant polypeptides produced by tumor cells as a result of genomic mutations. They are also tumor-specific antigens (TSA). Neoantigens are more immunogenic than tumor-related antigens and do not induce autoimmunity. Based on the rapid development of bioinformatics and the continuous update of sequencing technology, cancer immunotherapy with tumor neoantigens has made promising breakthroughs and progress. In this review, the generation, prediction, and identification of novel antigens, as well as the individualized treatments of neoantigens, were first introduced. Secondly, the mechanism of Chimeric Antigen Receptor T-Cell Immunotherapy (CAR-T) therapy and immune checkpoint blockade therapy in the treatment of tumors were outlined, and the three treatment methods were compared. Thirdly, the application of neoantigens in CAR-T therapy and PD-1/PD-L1 blockade therapy was briefly described. The benefits of the neoantigen vaccines over common vaccines were summarized as well. Finally, the prospect of neoantigen therapy was presented.

New insights and approaches for analyses of immunopeptidomes

Human leucocyte antigen (HLA) molecules play a key role in health and disease by presenting antigen to T-lymphocytes for immunosurveillance. Immunopeptidomics involves the study of the collection of peptides presented within the antigen-binding groove of HLA molecules. Identifying their nature and diversity is crucial to understanding immunosurveillance especially during infection or for the recognition and potential eradication of tumours. This review discusses recent advances in the isolation, identification, and quantitation of these peptide antigens. New informatics approaches and databases have shed light on the extent of peptide antigens derived from unconventional sources including peptides derived from transcripts associated with frame shifts, long noncoding RNA, incorrectly annotated untranslated regions, post-translational modifications, and proteasomal splicing. Several challenges remain in successful analysis of immunopeptides, yet recent developments point to unexplored biology waiting to be unravelled.

Upstream open reading frames regulate translation of cancer-associated transcripts and encode HLA-presented immunogenic tumor antigens

BACKGROUND

Upstream open reading frames (uORFs) represent translational control elements within eukaryotic transcript leader sequences. Recent data showed that uORFs can encode for biologically active proteins and human leukocyte antigen (HLA)-presented peptides in malignant and benign cells suggesting their potential role in cancer cell development and survival. However, the role of uORFs in translational regulation of cancer-associated transcripts as well as in cancer immune surveillance is still incompletely understood.

METHODS

We examined the translational regulatory effect of 29 uORFs in 13 cancer-associated genes by dual-luciferase assays. Cellular expression and localization of uORF-encoded peptides (uPeptides) were investigated by immunoblotting and immunofluorescence-based microscopy. Furthermore, we utilized mass spectrometry-based immunopeptidome analyses in an extensive dataset of primary malignant and benign tissue samples for the identification of naturally presented uORF-derived HLA-presented peptides screening for more than 2000 uORFs.

RESULTS

We provide experimental evidence for similarly effective translational regulation of cancer-associated transcripts through uORFs initiated by either canonical AUG codons or by alternative translation initiation sites (aTISs). We further demonstrate frequent cellular expression and reveal occasional specific cellular localization of uORF-derived peptides, suggesting uPeptide-specific biological implications. Immunopeptidome analyses delineated a set of 125 naturally presented uORF-derived HLA-presented peptides. Comparative immunopeptidome profiling of malignant and benign tissue-derived immunopeptidomes identified several tumor-associated uORF-derived HLA ligands capable to induce multifunctional T cell responses.

CONCLUSION

Our data provide direct evidence for the frequent expression of uPeptides in benign and malignant human tissues, suggesting a potentially widespread function of uPeptides in cancer biology. These findings may inspire novel approaches in direct molecular as well as immunotherapeutic targeting of cancer-associated uORFs and uPeptides.

Navigating Critical Challenges Associated with Immunopeptidomics-Based Detection of Proteasomal Spliced Peptide Candidates

Within the tumor immunology community, the topic of proteasomal spliced peptides (PSP) has generated a great deal of controversy. In the earliest reports, careful biological validation led to the conclusion that proteasome-catalyzed peptide splicing was a rare event. To date, six PSPs have been validated biologically. However, the advent of algorithms to identify candidate PSPs in mass spectrometry data challenged this notion, with several studies concluding that the frequency of spliced peptides binding to MHC class I was quite high. Since this time, much debate has centered around the methodologies used in these studies. Several reanalyses of data from these studies have led to questions about the validity of the conclusions. Furthermore, the biological and technical validation that should be necessary for verifying PSP assignments was often lacking. It has been suggested therefore that the research community should unite around a common set of standards for validating candidate PSPs. In this review, we propose and highlight the necessary steps for validation of proteasomal splicing at both the mass spectrometry and biological levels. We hope that these guidelines will serve as a foundation for critical assessment of results from proteasomal splicing studies.

Beyond Sequencing: Prioritizing and Delivering Neoantigens for Cancer Vaccines

Neoantigens are tumor-specific proteins and peptides that can be highly immunogenic. Immune-mediated tumor rejection is strongly associated with cytotoxic responses to neoantigen-derived peptides in noncovalent association with self-HLA molecules. Neoantigen-based therapies, such as adoptive T cell transfer, have shown the potential to induce remission of treatment-resistant metastatic disease in select patients. Cancer vaccines are similarly designed to elicit or amplify antigen-specific T cell populations and stimulate directed antitumor immunity, but the selection and prioritization of the neoantigens remains a challenge. Bioinformatic algorithms can predict tumor neoantigens from somatic mutations, insertion-deletions, and other aberrant peptide products, but this often leads to hundreds of potential neoepitopes, all unique for that tumor. Selecting neoantigens for cancer vaccines is complicated by the technical challenges of neoepitope discovery, the diversity of HLA molecules, and intratumoral heterogeneity of passenger mutations leading to immune escape. Despite strong preclinical evidence, few neoantigen cancer vaccines tested in vivo have generated epitope-specific T cell populations, suggesting suboptimal immune system activation. In this chapter, we review factors affecting the prioritization and delivery of candidate neoantigens in the design of therapeutic and preventive cancer vaccines and consider synergism with standard chemotherapies.

Identification of tumor antigens with immunopeptidomics

The identification of actionable tumor antigens is indispensable for the development of several cancer immunotherapies, including T cell receptor-transduced T cells and patient-specific mRNA or peptide vaccines. Most known tumor antigens have been identified through extensive molecular characterization and are considered canonical if they derive from protein-coding regions of the genome. By eluting human leukocyte antigen-bound peptides from tumors and subjecting these to mass spectrometry analysis, the peptides can be identified by matching the resulting spectra against reference databases. Recently, mass-spectrometry-based immunopeptidomics has enabled the discovery of noncanonical antigens-antigens derived from sequences outside protein-coding regions or generated by noncanonical antigen-processing mechanisms. Coupled with transcriptomics and ribosome profiling, this method enables the identification of thousands of noncanonical peptides, of which a substantial fraction may be detected exclusively in tumors. Spectral matching against the immense noncanonical reference may generate false positives. However, sensitive mass spectrometry, analytical validation and advanced bioinformatics solutions are expected to uncover the full landscape of presented antigens and clinically relevant targets.

Enhancing therapeutic performance of personalized cancer vaccine via delivery vectors

In recent years, personalized cancer vaccines have gained increasing attention as emerging immunotherapies with the capability to overcome interindividual differences and show great benefits for individual patients in the clinic due to the highly tailored vaccine formulations. A large number of materials have been studied as delivery vectors to enhance the therapeutic performance of personalized cancer vaccines, including artificial materials, engineered microorganisms, cells and cell derivatives. These delivery vectors with distinct features are employed to change antigen biodistributions and to facilitate antigen uptake, processing and presentation, improving the strength, velocity, and duration of the immune response when delivered by different strategies. Here, we provide an overview of personalized cancer vaccine delivery vectors, describing their materials, physicochemical properties, delivery strategies and challenges for clinical transformation.

Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome

Human leukocyte antigen (HLA) molecules are cell-surface glycoproteins that present peptide antigens on the cell surface for surveillance by T lymphocytes, which contemporaneously seek signs of disease. Mass spectrometric analysis allows us to identify large numbers of these peptides (the immunopeptidome) following affinity purification of solubilized HLA-peptide complexes. However, in recent years, there has been a growing awareness of the "dark side" of the immunopeptidome: unconventional peptide epitopes, including neoepitopes, which elude detection by conventional search methods because their sequences are not present in reference protein databases (DBs). Here, we establish a bioinformatics workflow to aid identification of peptides generated by noncanonical translation of mRNA or by genome variants. The workflow incorporates both standard transcriptomics software and novel computer programs to produce cell line-specific protein DBs based on three-frame translation of the transcriptome. The final protein DB also includes sequences resulting from variants determined by variant calling on the same RNA-Seq data. We then searched our experimental data against both transcriptome-based and standard DBs using PEAKS Studio (Bioinformatics Solutions, Inc). Finally, further novel software helps to compare the various result sets arising for each sample, pinpoint putative genomic origins for unconventional sequences, and highlight potential neoepitopes. We applied the workflow to study the immunopeptidome of the acute myeloid leukemia cell line THP-1, using RNA-Seq and immunopeptidome data. We confidently identified over 14,000 peptides from three replicates of purified HLA peptides derived from THP-1 cells using the conventional UniProt human proteome. Using the transcriptome-based DB generated using our workflow, we recapitulated >85% of these and also identified 1029 unconventional peptides not explained by UniProt, including 16 sequences caused by nonsynonymous variants. Our workflow, which we term "immunopeptidogenomics," can provide DBs, which include pertinent unconventional sequences and allow neoepitope discovery, without becoming too large to search. Immunopeptidogenomics is a step toward unbiased search approaches that are needed to illuminate the dark side of the immunopeptidome.

Profiling Human CMV-specific T cell responses reveals novel immunogenic ORFs

Despite the prevalence and medical significance of human cytomegalovirus (HCMV) infections, a systematic analysis of the targets of T cell recognition in humans that spans the entire genome and includes recently described potential novel ORFs is not available. Here, we screened a library of epitopes predicted to bind HLA class II that spans over 350 different HCMV ORFs and includes ∼150 previously described and ∼200 recently described potential novel ORFs using an ex vivo IFNγ fluorospot assay. We identified 235 unique HCMV specific epitopes derived from 100 ORFs, some previously described as immunodominant and others that were not previously described to be immunogenic. Of those, 41 belong to the set of recently reported novel ORFs, thus providing evidence that at least some of these are actually expressed in vivo in humans. These data reveal that the breadth of the human T cell response to HCMV is much greater than previously thought. The ORFs and epitopes identified will help elucidate how T cell immunity relates to HCMV pathogenesis and instruct ongoing HCMV vaccine research. Importance To understand the crucial role of adaptive immunity in controlling cytomegalovirus infection and disease, we systematically analyzed the CMV 'ORFeome' to identify new CMV epitopes targeted primarily by CD4 T cells in humans. Our study identified >200 new T cell epitopes derived from both canonical and novel ORFs, highlighting the substantial breadth of anti-CMV T cell response and providing new targets for vaccine design.

Increased expression of peptides from non-coding genes in cancer proteomics datasets suggests potential tumor neoantigens

Neoantigen-based immunotherapy has yielded promising results in clinical trials. However, it is limited to tumor-specific mutations, and is often tailored to individual patients. Identifying suitable tumor-specific antigens is still a major challenge. Previous proteogenomics studies have identified peptides encoded by predicted non-coding sequences in human genome. To investigate whether tumors express specific peptides encoded by non-coding genes, we analyzed published proteomics data from five cancer types including 933 tumor samples and 275 matched normal samples and compared these to data from 31 different healthy human tissues. Our results reveal that many predicted non-coding genes such as DGCR9 and RHOXF1P3 encode peptides that are overexpressed in tumors compared to normal controls. Furthermore, from the non-coding genes-encoded peptides specifically detected in cancers, we predict a large number of “dark antigens” (neoantigens from non-coding genomic regions), which may provide an alternative source of neoantigens beyond standard tumor specific mutations.

Rong Xiang et al. analyze the expression of non-coding genes encoded peptides in publicly-available proteomics data from five cancer types and matched controls. They identify peptides from non-coding genes including DGCR9 and RHOXF1P3 that are upregulated in tumors compared to controls, suggesting that non-coding gene-encoded peptides may be a source of neoantigens in some cancers.

Adoptive Immunotherapy beyond CAR T-Cells

Adoptive cell immunotherapy (ACT) is a vibrant field of cancer treatment that began progressive development in the 1980s. One of the most prominent and promising examples is chimeric antigen receptor (CAR) T-cell immunotherapy for the treatment of B-cell hematologic malignancies. Despite success in the treatment of B-cell lymphomas and leukemia, CAR T-cell therapy remains mostly ineffective for solid tumors. This is due to several reasons, such as the heterogeneity of the cellular composition in solid tumors, the need for directed migration and penetration of CAR T-cells against the pressure gradient in the tumor stroma, and the immunosuppressive microenvironment. To substantially improve the clinical efficacy of ACT against solid tumors, researchers might need to look closer into recent developments in the other branches of adoptive immunotherapy, both traditional and innovative. In this review, we describe the variety of adoptive cell therapies beyond CAR T-cell technology, i.e., exploitation of alternative cell sources with a high therapeutic potential against solid tumors (e.g., CAR M-cells) or aiming to be universal allogeneic (e.g., CAR NK-cells, γδ T-cells), tumor-infiltrating lymphocytes (TILs), and transgenic T-cell receptor (TCR) T-cell immunotherapies. In addition, we discuss the strategies for selection and validation of neoantigens to achieve efficiency and safety. We provide an overview of non-conventional TCRs and CARs, and address the problem of mispairing between the cognate and transgenic TCRs. Finally, we summarize existing and emerging approaches for manufacturing of the therapeutic cell products in traditional, semi-automated and fully automated Point-of-Care (PoC) systems.

Anti-tumour immunity induces aberrant peptide presentation in melanoma

Extensive tumour inflammation, which is reflected by high levels of infiltrating T cells and interferon-γ (IFNγ) signalling, improves the response of patients with melanoma to checkpoint immunotherapy^1,2. Many tumours, however, escape by activating cellular pathways that lead to immunosuppression. One such mechanism is the production of tryptophan metabolites along the kynurenine pathway by the enzyme indoleamine 2,3-dioxygenase 1 (IDO1), which is induced by IFNγ^3-5. However, clinical trials using inhibition of IDO1 in combination with blockade of the PD1 pathway in patients with melanoma did not improve the efficacy of treatment compared to PD1 pathway blockade alone^6,7, pointing to an incomplete understanding of the role of IDO1 and the consequent degradation of tryptophan in mRNA translation and cancer progression. Here we used ribosome profiling in melanoma cells to investigate the effects of prolonged IFNγ treatment on mRNA translation. Notably, we observed accumulations of ribosomes downstream of tryptophan codons, along with their expected stalling at the tryptophan codon. This suggested that ribosomes bypass tryptophan codons in the absence of tryptophan. A detailed examination of these tryptophan-associated accumulations of ribosomes-which we term 'W-bumps'-showed that they were characterized by ribosomal frameshifting events. Consistently, reporter assays combined with proteomic and immunopeptidomic analyses demonstrated the induction of ribosomal frameshifting, and the generation and presentation of aberrant trans-frame peptides at the cell surface after treatment with IFNγ. Priming of naive T cells from healthy donors with aberrant peptides induced peptide-specific T cells. Together, our results suggest that IDO1-mediated depletion of tryptophan, which is induced by IFNγ, has a role in the immune recognition of melanoma cells by contributing to diversification of the peptidome landscape.

A Roadmap Toward the Definition of Actionable Tumor-Specific Antigens

The search for tumor-specific antigens (TSAs) has considerably accelerated during the past decade due to the improvement of proteogenomic detection methods. This provides new opportunities for the development of novel antitumoral immunotherapies to mount an efficient T cell response against one or multiple types of tumors. While the identification of mutated antigens originating from coding exons has provided relatively few TSA candidates, the possibility of enlarging the repertoire of targetable TSAs by looking at antigens arising from non-canonical open reading frames opens up interesting avenues for cancer immunotherapy. In this review, we outline the potential sources of TSAs and the mechanisms responsible for their expression strictly in cancer cells. In line with the heterogeneity of cancer, we propose that discrete families of TSAs may be enriched in specific cancer types.

Identifying and Targeting Human Tumor Antigens for T Cell-Based Immunotherapy of Solid Tumors

Cancer elimination in humans can be achieved with immunotherapy that relies on T lymphocyte-mediated recognition of tumor antigens. Several types of these antigens have been recognized based on their cellular origins and expression patterns, while their detection has been greatly facilitated by recent achievements in next-generation sequencing and immunopeptidomics. Some of them have been targeted in clinical trials with various immunotherapy approaches, while many others remain untested. Here, we discuss molecular identification of different tumor antigen types, and the clinical safety and efficacy of targeting them with immunotherapy. Additionally, we suggest strategies to increase the efficacy and availability of antigen-directed immunotherapies for treatment of patients with metastatic cancer.

Putting into Perspective the Future of Cancer Vaccines: Targeted Immunotherapy

Pre-clinical models and human clinical trials have confirmed the ability of cancer vaccines to induce immune responses that are tumour-specific and, in some cases, associated with clinical response. However, cancer vaccines as a targeted immunotherapy strategy have not yet come of age. So, why the discordance after so much research has been invested in cancer vaccines? There are several reasons for this that include: limited tumour immunogenicity (limited targeted antigen expression, antigen tolerance); antigenic heterogeneity in tumours; heterogeneity of individual immune responses; multiple mechanisms associated with suppressed functional activity of immune effector cells, the underlying rationale for the use of immune checkpoint inhibitors; and immune system exhaustion. The success of checkpoint therapy has refocussed investigations into defining relationships between tumours and host immune systems, appreciating the mechanisms by which tumour cells escape immune surveillance and reinforcing recognition of the potential of vaccines in the treatment and prevention of cancer. Recent developments in cancer immunotherapies, together with associated technologies, for instance, the unparalleled achievements by immune checkpoint inhibitors and neo-antigen identification tools, may foster potential improvements in cancer vaccines for the treatment of malignancies.

The Origin and Immune Recognition of Tumor-Specific Antigens

The dominant paradigm holds that spontaneous and therapeutically induced anti-tumor responses are mediated mainly by CD8 T cells and directed against tumor-specific antigens (TSAs). The presence of specific TSAs on cancer cells can only be proven by mass spectrometry analyses. Bioinformatic predictions and reverse immunology studies cannot provide this type of conclusive evidence. Most TSAs are coded by unmutated non-canonical transcripts that arise from cancer-specific epigenetic and splicing aberrations. When searching for TSAs, it is therefore important to perform mass spectrometry analyses that interrogate not only the canonical reading frame of annotated exome but all reading frames of the entire translatome. The majority of aberrantly expressed TSAs (aeTSAs) derive from unstable short-lived proteins that are good substrates for direct major histocompatibility complex (MHC) I presentation but poor substrates for cross-presentation. This is an important caveat, because cancer cells are poor antigen-presenting cells, and the immune system, therefore, depends on cross-presentation by dendritic cells (DCs) to detect the presence of TSAs. We, therefore, postulate that, in the untreated host, most aeTSAs are undetected by the immune system. We present evidence suggesting that vaccines inducing direct aeTSA presentation by DCs may represent an attractive strategy for cancer treatment.

Identification of the Cryptic HLA-I Immunopeptidome

The success of cancer immunotherapy relies on the ability of cytotoxic T cells to specifically recognize and eliminate tumor cells based on peptides presented by HLA-I. Although the peptide epitopes that elicit the corresponding immune response often remain unidentified, it is generally assumed that neoantigens, due to tumor-specific mutations, are the most common targets. Here, we used a mass spectrometric approach to show an underappreciated class of epitopes that accounts for up to 15% of HLA-I peptides for certain HLA alleles in various tumors and patients. These peptides are translated from cryptic open reading frames in supposedly noncoding regions in the genome and are mostly unidentifiable with conventional computational analyses of mass spectrometry (MS) data. Our approach, Peptide-PRISM, identified thousands of such cryptic peptides in tumor immunopeptidomes. About 20% of these HLA-I peptides represented the C-terminus of the corresponding translation product, suggesting frequent proteasome-independent processing. Our data also revealed HLA-I allele-dependent presentation of cryptic peptides, with HLA-A*03 and HLA-A*11 presenting the highest percentage of cryptic peptides. Our analyses refute the reported frequent presentation of HLA peptides generated by proteasome-catalyzed peptide splicing. Thus, Peptide-PRISM represents an important step toward comprehensive identification of HLA-I immunopeptidomes and reveals cryptic peptides as an abundant class of epitopes with potential relevance for novel immunotherapeutic approaches.

Advancing CAR T-Cell Therapy for Solid Tumors: Lessons Learned from Lymphoma Treatment

Chimeric antigen receptor (CAR) immunotherapy is one of the most promising modern approaches for the treatment of cancer. To date only two CAR T-cell products, Kymriah^® and Yescarta^®, have been approved by the Food and Drug Administration (FDA) for the treatment of lymphoblastic leukemia and B-cell lymphoma. Administration of CAR T-cells to control solid tumors has long been envisaged as one of the most difficult therapeutic tasks. The first two clinical trials conducted in sarcoma and neuroblastoma patients showed clinical benefits of CAR T-cells, yet multiple obstacles still hold us back from having accessible and efficient therapy. Why did such an effective treatment for relapsed and refractory hematological malignancies demonstrate only relatively modest efficiency in the context of solid tumors? Is it due to the lucky selection of the “magic” CD19 antigen, which might be one of a kind? Or do lymphomas lack the immunosuppressive features of solid tumors? Here we review the existing knowledge in the field of CAR T-cell therapy and address the heterogeneity of solid tumors and their diverse strategies of immunoevasion. We also provide an insight into prospective developments of CAR T-cell technologies against solid tumors.

The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases

The science that investigates the ensembles of all peptides associated to human leukocyte antigen (HLA) molecules is termed "immunopeptidomics" and is typically driven by mass spectrometry (MS) technologies. Recent advances in MS technologies, neoantigen discovery and cancer immunotherapy have catalyzed the launch of the Human Immunopeptidome Project (HIPP) with the goal of providing a complete map of the human immunopeptidome and making the technology so robust that it will be available in every clinic. Here, we provide a long-term perspective of the field and we use this framework to explore how we think the completion of the HIPP will truly impact the society in the future. In this context, we introduce the concept of immunopeptidome-wide association studies (IWAS). We highlight the importance of large cohort studies for the future and how applying quantitative immunopeptidomics at population scale may provide a new look at individual predisposition to common immune diseases as well as responsiveness to vaccines and immunotherapies. Through this vision, we aim to provide a fresh view of the field to stimulate new discussions within the community, and present what we see as the key challenges for the future for unlocking the full potential of immunopeptidomics in this era of precision medicine.

The Genomic Landscape of Antigenic Targets for T Cell-Based Leukemia Immunotherapy

Intensive fundamental and clinical research in cancer immunotherapy has led to the emergence and evolution of two parallel universes with surprisingly little interactions: the realm of hematologic malignancies and that of solid tumors. Treatment of hematologic cancers using allogeneic hematopoietic cell transplantation (AHCT) serendipitously led to the discovery that T cells specific for minor histocompatibility antigens (MiHAs) could cure hematopoietic cancers. Besides, studies based on treatment of solid tumor with ex vivo-expanded tumor infiltrating lymphocytes or immune checkpoint therapy demonstrated that anti-tumor responses could be achieved by targeting tumor-specific antigens (TSAs). It is our contention that much insight can be gained by sharing the tremendous amount of data generated in the two-abovementioned universes. Our perspective article has two specific goals. First, to discuss the value of methods currently used for MiHA and TSA discovery and to explain the key role of mass spectrometry analyses in this process. Second, to demonstrate the importance of broadening the scope of TSA discovery efforts beyond classic annotated protein-coding genomic sequences.

Peptides encoded by noncoding genes: challenges and perspectives

In recent years, noncoding gene (NCG) translation events have been frequently discovered. The resultant peptides, as novel findings in the life sciences, perform unexpected functions of increasingly recognized importance in many fundamental biological and pathological processes. The emergence of these novel peptides, in turn, has advanced the field of genomics while indispensably aiding living organisms. The peptides from NCGs serve as important links between extracellular stimuli and intracellular adjustment mechanisms. These peptides are also important entry points for further exploration of the mysteries of life that may trigger a new round of revolutionary biotechnological discoveries. Insights into NCG-derived peptides will assist in understanding the secrets of life and the causes of diseases, and will also open up new paths to the treatment of diseases such as cancer. Here, a critical review is presented on the action modes and biological functions of the peptides encoded by NCGs. The challenges and future trends in searching for and studying NCG peptides are also critically discussed.

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.

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.

Best practices for bioinformatic characterization of neoantigens for clinical utility

Neoantigens are newly formed peptides created from somatic mutations that are capable of inducing tumor-specific T cell recognition. Recently, researchers and clinicians have leveraged next generation sequencing technologies to identify neoantigens and to create personalized immunotherapies for cancer treatment. To create a personalized cancer vaccine, neoantigens must be computationally predicted from matched tumor-normal sequencing data, and then ranked according to their predicted capability in stimulating a T cell response. This candidate neoantigen prediction process involves multiple steps, including somatic mutation identification, HLA typing, peptide processing, and peptide-MHC binding prediction. The general workflow has been utilized for many preclinical and clinical trials, but there is no current consensus approach and few established best practices. In this article, we review recent discoveries, summarize the available computational tools, and provide analysis considerations for each step, including neoantigen prediction, prioritization, delivery, and validation methods. In addition to reviewing the current state of neoantigen analysis, we provide practical guidance, specific recommendations, and extensive discussion of critical concepts and points of confusion in the practice of neoantigen characterization for clinical use. Finally, we outline necessary areas of development, including the need to improve HLA class II typing accuracy, to expand software support for diverse neoantigen sources, and to incorporate clinical response data to improve neoantigen prediction algorithms. The ultimate goal of neoantigen characterization workflows is to create personalized vaccines that improve patient outcomes in diverse cancer types.

Therapeutic vaccine strategies to induce tumor-specific T-cell responses

Haploidentical stem cell transplantation is increasingly used worldwide as an alternative donor transplantation method. Although novel preparative regimens and T-cell deletion techniques have improved engraftment rates and viral safety, relapses of the underlying leukemia/lymphoma are still frequent, thus representing a significant and unsolved problem. Recent technological advances now enable us to individually decipher the MHC-associated immunopeptidome of cancer cells in reasonable time. These tumor-specific peptides can then be used to skew the early immune reconstitution toward anti-leukemia T-cell responses. In this meeting contribution, we summarize recent innovations in the field and present preliminary data on using this technique for cancer epitope discovery in a paradigmatic pediatric brain tumor with very low mutational burden.

Proteogenomics: advances in cancer antigen research

T cells recognize antigen peptides displayed by HLA molecules and specifically eliminate their target cells. Identification of responsible antigens as well as understanding the mechanism by which antigens are produced inside cells are equally crucial for cancer immunology. In this review, we introduce proteogenomics and its applications in cancer antigen research, which leverages mass spectrometry and next-generation sequencing. The approach comprehensively captures immunopeptidome displayed by HLA, revealing new classes of antigens, such as mutation-derived neoantigens, spliced peptides, and non-coding region derived peptides. These antigens may serve as therapeutic targets or biomarkers. Thus, proteogenomics is a promising approach for cancer antigen research and contributes to immunotherapy development.