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.

Proteogenomics and Differential Ion Mobility Enable the Exploration of the Mutational Landscape in Colon Cancer Cells.

The sensitivity and depth of proteomic analyses are limited by isobaric ions and interferences that preclude the identification of low abundance peptides. Extensive sample fractionation is often required to extend proteome coverage when sample amount is not a limitation. Ion mobility devices provide a viable alternate approach to resolve confounding ions and improve peak capacity and mass spectrometry (MS) sensitivity. Here, we report the integration of differential ion mobility with segmented ion fractionation (SIFT) to enhance the comprehensiveness of proteomic analyses. The combination of differential ion mobility and SIFT, where narrow windows of ∼m/z 100 are acquired in turn, is found particularly advantageous in the analysis of protein digests and typically provided more than 60% gain in identification compared to conventional single-shot LC-MS/MS. The application of this approach is further demonstrated for the analysis of tryptic digests from different colorectal cancer cell lines where the enhanced sensitivity enabled the identification of single amino acid variants that were correlated with the corresponding transcriptomic data sets.

Most non-canonical proteins uniquely populate the proteome or immunopeptidome.

Combining RNA sequencing, ribosome profiling, and mass spectrometry, we elucidate the contribution of non-canonical translation to the proteome and major histocompatibility complex (MHC) class I immunopeptidome. Remarkably, of 14,498 proteins identified in three human B cell lymphomas, 2,503 are non-canonical proteins. Of these, 28% are novel isoforms and 72% are cryptic proteins encoded by ostensibly non-coding regions (60%) or frameshifted canonical genes (12%). Cryptic proteins are translated as efficiently as canonical proteins, have more predicted disordered residues and lower stability, and critically generate MHC-I peptides 5-fold more efficiently per translation event. Translating 5' "untranslated" regions hinders downstream translation of genes involved in transcription, translation, and antiviral responses. Novel protein isoforms show strong enrichment for signaling pathways deregulated in cancer. Only a small fraction of cryptic proteins detected in the proteome contribute to the MHC-I immunopeptidome, demonstrating the high preferential access of cryptic defective ribosomal products to the class I pathway.

A multi-scale coevolutionary approach to predict interactions between protein domains.

Interacting proteins and protein domains coevolve on multiple scales, from their correlated presence across species, to correlations in amino-acid usage. Genomic databases provide rapidly growing data for variability in genomic protein content and in protein sequences, calling for computational predictions of unknown interactions. We first introduce the concept of direct phyletic couplings, based on global statistical models of phylogenetic profiles. They strongly increase the accuracy of predicting pairs of related protein domains beyond simpler correlation-based approaches like phylogenetic profiling (80% vs. 30-50% positives out of the 1000 highest-scoring pairs). Combined with the direct coupling analysis of inter-protein residue-residue coevolution, we provide multi-scale evidence for direct but unknown interaction between protein families. An in-depth discussion shows these to be biologically sensible and directly experimentally testable. Negative phyletic couplings highlight alternative solutions for the same functionality, including documented cases of convergent evolution. Thereby our work proves the strong potential of global statistical modeling approaches to genome-wide coevolutionary analysis, far beyond the established use for individual protein complexes and domain-domain interactions.

Meet-U: Educating through research immersion.

We present a new educational initiative called Meet-U that aims to train students for collaborative work in computational biology and to bridge the gap between education and research. Meet-U mimics the setup of collaborative research projects and takes advantage of the most popular tools for collaborative work and of cloud computing. Students are grouped in teams of 4-5 people and have to realize a project from A to Z that answers a challenging question in biology. Meet-U promotes "coopetition," as the students collaborate within and across the teams and are also in competition with each other to develop the best final product. Meet-U fosters interactions between different actors of education and research through the organization of a meeting day, open to everyone, where the students present their work to a jury of researchers and jury members give research seminars. This very unique combination of education and research is strongly motivating for the students and provides a formidable opportunity for a scientific community to unite and increase its visibility. We report on our experience with Meet-U in two French universities with master's students in bioinformatics and modeling, with protein-protein docking as the subject of the course. Meet-U is easy to implement and can be straightforwardly transferred to other fields and/or universities. All the information and data are available at www.meet-u.org.