pyGeno: A Python package for precision medicine and proteogenomics

Breast cancer immunopeptidomes contain numerous shared tumor antigens

Hormone receptor-positive breast cancer (HR+) is immunologically cold and has not benefited from advances in immunotherapy. In contrast, subsets of triple-negative breast cancer (TNBC) display high leukocytic infiltration and respond to checkpoint blockade. CD8+ T cells, the main effectors of anticancer responses, recognize MHC I-associated peptides (MAPs). Our work aimed to characterize the repertoire of MAPs presented by HR+ and TNBC tumors. Using mass spectrometry, we identified 57,094 unique MAPs in 26 primary breast cancer samples. MAP source genes highly overlapped between both subtypes. We identified 25 tumor-specific antigens (TSAs) mainly deriving from aberrantly expressed regions. TSAs were most frequently identified in TNBC samples and were more shared among The Cancer Genome Atlas (TCGA) database TNBC than HR+ samples. In the TNBC cohort, the predicted number of TSAs positively correlated with leukocytic infiltration and overall survival, supporting their immunogenicity in vivo. We detected 49 tumor-associated antigens (TAAs), some of which derived from cancer-associated fibroblasts. Functional expansion of specific T cell assays confirmed the in vitro immunogenicity of several TSAs and TAAs. Our study identified attractive targets for cancer immunotherapy in both breast cancer subtypes. The higher prevalence of TSAs in TNBC tumors provides a rationale for their responsiveness to checkpoint blockade.

Induced pluripotent stem cells display a distinct set of MHC I-associated peptides shared by human cancers

Previous reports showed that mouse vaccination with pluripotent stem cells (PSCs) induces durable anti-tumor immune responses via T cell recognition of some elusive oncofetal epitopes. We characterize the MHC I-associated peptide (MAP) repertoire of human induced PSCs (iPSCs) using proteogenomics. Our analyses reveal a set of 46 pluripotency-associated MAPs (paMAPs) absent from the transcriptome of normal tissues and adult stem cells but expressed in PSCs and multiple adult cancers. These paMAPs derive from coding and allegedly non-coding (48%) transcripts involved in pluripotency maintenance, and their expression in The Cancer Genome Atlas samples correlates with source gene hypomethylation and genomic aberrations common across cancer types. We find that several of these paMAPs were immunogenic. However, paMAP expression in tumors coincides with activation of pathways instrumental in immune evasion (WNT, TGF-β, and CDK4/6). We propose that currently available inhibitors of these pathways could synergize with immune targeting of paMAPs for the treatment of poorly differentiated cancers.

Immunopeptidomic analyses of colorectal cancers with and without microsatellite instability

Colorectal cancer is the second leading cause of cancer death worldwide, and the incidence of this disease is expected to increase as global socioeconomic changes occur. Immune checkpoint inhibition therapy is effective in treating a minority of colorectal cancer tumors; however, microsatellite stable tumors do not respond well to this treatment. Emerging cancer immunotherapeutic strategies aim to activate a cytotoxic T cell response against tumor-specific antigens, presented exclusively at the cell surface of cancer cells. These antigens are rare and are most effectively identified with a mass spectrometry-based approach, which allows the direct sampling and sequencing of these peptides. Although the few tumor-specific antigens identified to date are derived from coding regions of the genome, recent findings indicate that a large proportion of tumor-specific antigens originate from allegedly noncoding regions. Here, we employed a novel proteogenomic approach to identify tumor antigens in a collection of colorectal cancer-derived cell lines and biopsy samples consisting of matched tumor and normal adjacent tissue. The generation of personalized cancer databases paired with mass spectrometry analyses permitted the identification of more than 30,000 unique MHC I-associated peptides. We identified 19 tumor-specific antigens in both microsatellite stable and unstable tumors, over two-thirds of which were derived from noncoding regions. Many of these peptides were derived from source genes known to be involved in colorectal cancer progression, suggesting that antigens from these genes could have therapeutic potential in a wide range of tumors. These findings could benefit the development of T cell-based vaccines, in which T cells are primed against these antigens to target and eradicate tumors. Such a vaccine could be used in tandem with existing immune checkpoint inhibition therapies, to bridge the gap in treatment efficacy across subtypes of colorectal cancer with varying prognoses. Data are available via ProteomeXchange with identifier PXD028309.

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation

MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates MAPs. In this study, we investigated whether codon arrangement (usage and placement) regulates MAP biogenesis. We developed an artificial neural network called Codon Arrangement MAP Predictor (CAMAP), predicting MAP presentation solely from mRNA sequences flanking the MAP-coding codons (MCCs), while excluding the MCC per se. CAMAP predictions were significantly more accurate when using original codon sequences than shuffled codon sequences which reflect amino acid usage. Furthermore, predictions were independent of mRNA expression and MAP binding affinity to MHC-I molecules and applied to several cell types and species. Combining MAP ligand scores, transcript expression level and CAMAP scores was particularly useful to increase MAP prediction accuracy. Using an in vitro assay, we showed that varying the synonymous codons in the regions flanking the MCCs (without changing the amino acid sequence) resulted in significant modulation of MAP presentation at the cell surface. Taken together, our results demonstrate the role of codon arrangement in the regulation of MAP presentation and support integration of both translational and post-translational events in predictive algorithms to ameliorate modeling of the immunopeptidome.

MHC-I associated peptides (MAPs) are small fragments of intracellular proteins presented at the surface of cells and used by the immune system to detect and eliminate cancerous or virus-infected cells. While it is theoretically possible to predict which portions of the intracellular proteins will be naturally processed by the cells to ultimately reach the surface, current methodologies have prohibitively high false discovery rates. Here we introduce an artificial neural network called Codon Arrangement MAP Predictor (CAMAP) which integrates information from mRNA-to-protein translation to other factors regulating MAP biogenesis (e.g. MAP ligand score and transcript expression levels) to improve MAP prediction accuracy. While most MAP predictive approaches focus on MAP sequences per se, CAMAP’s novelty is to analyze the MAP-flanking mRNA sequences, thereby providing completely independent information for MAP prediction. We show on several datasets that the integration of CAMAP scores with other known factors involved in MAP presentation (i.e. MAP ligand score and mRNA expression) significantly improves MAP prediction accuracy, and further validate CAMAP learned features using an in-vitro assay. These findings may have major implications for the design of vaccines against cancers and viruses, and in times of pandemics could accelerate the identification of relevant MAPs of viral origins.

Proteogenomic interrogation of cancer cell lines: an overview of the field

Introduction: Cancer cell lines (CCLs) have been a major resource for cancer research. Over the past couple of decades, they have been instrumental in omic profiling method development and as model systems to generate new knowledge in cell and cancer biology. More recently, with the increasing amount of genomic, transcriptomic and proteomic data being generated in hundreds of CCLs, there is growing potential for integrative proteogenomic data analyses to be performed.Areas covered: In this review, we first describe the most commonly used proteome profiling methods in CCLs. We then discuss how these proteomics data can be integrated with genomics data for proteogenomics analyses. Finally, we highlight some of the recent biological discoveries that have arisen from proteogenomics analyses of CCLs.Expert opinion: Protegeonomics analyses of CCLs have so far enabled the discovery of novel proteins and proteoforms. It has also improved our understanding of biological processes including post-transcriptional regulation of protein abundance and the presentation of antigens by major histocompatibility complex alleles. With proteomics data to be generated in hundreds to thousands of CCLs in coming years, there will be further potential for large-scale proteogenomics analyses and data integration with the phenotypically well-characterized CCLs.

Atypical acute myeloid leukemia-specific transcripts generate shared and immunogenic MHC class-I-associated epitopes

Acute myeloid leukemia (AML) has not benefited from innovative immunotherapies, mainly because of the lack of actionable immune targets. Using an original proteogenomic approach, we analyzed the major histocompatibility complex class I (MHC class I)-associated immunopeptidome of 19 primary AML samples and identified 58 tumor-specific antigens (TSAs). These TSAs bore no mutations and derived mainly (86%) from supposedly non-coding genomic regions. Two AML-specific aberrations were instrumental in the biogenesis of TSAs, intron retention, and epigenetic changes. Indeed, 48% of TSAs resulted from intron retention and translation, and their RNA expression correlated with mutations of epigenetic modifiers (e.g., DNMT3A). AML TSA-coding transcripts were highly shared among patients and were expressed in both blasts and leukemic stem cells. In AML patients, the predicted number of TSAs correlated with spontaneous expansion of cognate T cell receptor clonotypes, accumulation of activated cytotoxic T cells, immunoediting, and improved survival. These TSAs represent attractive targets for AML immunotherapy.

Widespread and tissue-specific expression of endogenous retroelements in human somatic tissues

BACKGROUND

Endogenous retroelements (EREs) constitute about 42% of the human genome and have been implicated in common human diseases such as autoimmunity and cancer. The dominant paradigm holds that EREs are expressed in embryonic stem cells (ESCs) and germline cells but are repressed in differentiated somatic cells. Despite evidence that some EREs can be expressed at the RNA and protein levels in specific contexts, a system-level evaluation of their expression in human tissues is lacking.

METHODS

Using RNA sequencing data, we analyzed ERE expression in 32 human tissues and cell types, including medullary thymic epithelial cells (mTECs). A tissue specificity index was computed to identify tissue-restricted ERE families. We also analyzed the transcriptome of mTECs in wild-type and autoimmune regulator (AIRE)-deficient mice. Finally, we developed a proteogenomic workflow combining RNA sequencing and mass spectrometry (MS) in order to evaluate whether EREs might be translated and generate MHC I-associated peptides (MAP) in B-lymphoblastoid cell lines (B-LCL) from 16 individuals.

RESULTS

We report that all human tissues express EREs, but the breadth and magnitude of ERE expression are very heterogeneous from one tissue to another. ERE expression was particularly high in two MHC I-deficient tissues (ESCs and testis) and one MHC I-expressing tissue, mTECs. In mutant mice, we report that the exceptional expression of EREs in mTECs was AIRE-independent. MS analyses identified 103 non-redundant ERE-derived MAPs (ereMAPs) in B-LCLs. These ereMAPs preferentially derived from sense translation of intronic EREs. Notably, detailed analyses of their amino acid composition revealed that ERE-derived MAPs presented homology to viral MAPs.

CONCLUSIONS

This study shows that ERE expression in somatic tissues is more pervasive and heterogeneous than anticipated. The high and diversified expression of EREs in mTECs and their ability to generate MAPs suggest that EREs may play an important role in the establishment of self-tolerance. The viral-like properties of ERE-derived MAPs suggest that those not expressed in mTECs can be highly immunogenic.

Proteogenomics Uncovers a Vast Repertoire of Shared Tumor-Specific Antigens in Ovarian Cancer

High-grade serous ovarian cancer (HGSC), the principal cause of death from gynecologic malignancies in the world, has not significantly benefited from advances in cancer immunotherapy. Although HGSC infiltration by lymphocytes correlates with superior survival, the nature of antigens that can elicit anti-HGSC immune responses is unknown. The goal of this study was to establish the global landscape of HGSC tumor-specific antigens (TSA) using a mass spectrometry pipeline that interrogated all reading frames of all genomic regions. In 23 HGSC tumors, we identified 103 TSAs. Classic TSA discovery approaches focusing only on mutated exonic sequences would have uncovered only three of these TSAs. Other mutated TSAs resulted from out-of-frame exonic translation (n = 2) or from noncoding sequences (n = 7). One group of TSAs (n = 91) derived from aberrantly expressed unmutated genomic sequences, which were not expressed in normal tissues. These aberrantly expressed TSAs (aeTSA) originated primarily from nonexonic sequences, in particular intronic (29%) and intergenic (22%) sequences. Their expression was regulated at the transcriptional level by variations in gene copy number and DNA methylation. Although mutated TSAs were unique to individual tumors, aeTSAs were shared by a large proportion of HGSCs. Taking into account the frequency of aeTSA expression and HLA allele frequencies, we calculated that, in Caucasians, the median number of aeTSAs per tumor would be five. We conclude that, in view of their number and the fact that they are shared by many tumors, aeTSAs may be the most attractive targets for HGSC immunotherapy.

Noncoding regions are the main source of targetable tumor-specific antigens

Tumor-specific antigens (TSAs) represent ideal targets for cancer immunotherapy, but few have been identified thus far. We therefore developed a proteogenomic approach to enable the high-throughput discovery of TSAs coded by potentially all genomic regions. In two murine cancer cell lines and seven human primary tumors, we identified a total of 40 TSAs, about 90% of which derived from allegedly noncoding regions and would have been missed by standard exome-based approaches. Moreover, most of these TSAs derived from nonmutated yet aberrantly expressed transcripts (such as endogenous retroelements) that could be shared by multiple tumor types. Last, we demonstrated that, in mice, the strength of antitumor responses after TSA vaccination was influenced by two parameters that can be estimated in humans and could serve for TSA prioritization in clinical studies: TSA expression and the frequency of TSA-responsive T cells in the preimmune repertoire. In conclusion, the strategy reported herein could considerably facilitate the identification and prioritization of actionable human TSAs.

Global proteogenomic analysis of human MHC class I-associated peptides derived from non-canonical reading frames

In view of recent reports documenting pervasive translation outside of canonical protein-coding sequences, we wished to determine the proportion of major histocompatibility complex (MHC) class I-associated peptides (MAPs) derived from non-canonical reading frames. Here we perform proteogenomic analyses of MAPs eluted from human B cells using high-throughput mass spectrometry to probe the six-frame translation of the B-cell transcriptome. We report that ∼10% of MAPs originate from allegedly noncoding genomic sequences or exonic out-of-frame translation. The biogenesis and properties of these ‘cryptic MAPs' differ from those of conventional MAPs. Cryptic MAPs come from very short proteins with atypical C termini, and are coded by transcripts bearing long 3′UTRs enriched in destabilizing elements. Relative to conventional MAPs, cryptic MAPs display different MHC class I-binding preferences and harbour more genomic polymorphisms, some of which are immunogenic. Cryptic MAPs increase the complexity of the MAP repertoire and enhance the scope of CD8 T-cell immunosurveillance.

Cryptic translation of the 'non-coding' genome is increasingly recognised, however its biological significance remains unclear. Laumont et al. employ proteogenomic techniques to map the human immunoproteome, and find that approximately 10% of MHC class I-associated peptides are cryptic.