1464 Endogenous retroviral protein particles in malignant pleural mesothelioma as potential immunotherapy targets; novel approaches for identification and prioritization
Bibliographic record
Abstract
Background Malignant pleural mesothelioma (MPM) is an aggressive cancer with median survival of 18 months. Due to the lack of proper tumour targets, no cellular immunotherapy is currently available for MPM. New non-ablative radiation and surgery combination therapy programs for MPM are underway at the Princess Margaret Cancer Centre in Toronto. As part of a comprehensive multiomics study of tumor microenvironment, we implemented a computational method for discovery and prioritization of endogenous retroviral protein (ERV) particles as novel antigen-specific targets in MPM. Methods We performed ERV gene-discovery based on identification of protein-coding open-reading frames with viral or bacterial origins.1 An extended human reference genome was constructed with novel open-reading frames and single-cell RNAseq sequencing (10Xgenomics Inc.) reads of tumor samples were aligned and gene-count tables were computed. ERVs with less than ten aligned reads or present in only one patient were removed from the analysis. ERVs with transcripts overlapping GTEx Consortium database (10K samples, 56 tissues) were removed to ensure no remaining ERV was constitutively expressed in normal tissues. The ERVs were further annotated with experimentally validated T and B cell epitopes in the Immune Epitope Database (IEDB).2 BLAST searches performed to identify humongous epitope of ERVs in human pathogen. A select set of identified transcripts were validated with PCR. Results Single-cell RNAseq expression of tumor microenvironment of 19 MPM patients was analyzed. All patients expressed two ERVs annotated in the human reference genome (ERV3–1, ERVK3–1) with another four (ERVFRD-1, ERVH48–1, ERVMER34–1, ERVW-1) expressed in at least 5 patients. We identified 400 ERVs not curated in the human reference genome with lengths of 95–3935 amino acids (1520.9525 +- 1069). From this, 224 contained at least one T-cell epitope (with presentation at MHC class-I and class-II) or B epitope (antibody binding) record in IEDB. 135 ERVs had at least one epitope with 100% homology in human pathogens. We further measured the expression (in terms of TPM) of identified genes in 2708 publicly available cell lines of 14 cancers. All 400 ERVs were shared with at least one and some with all 14 other cancers. Conclusions We identified several ERV proteins present in MPM tumors that are prominently encoded in intronic regions of but not curated in the human reference genome. Annotation of these proteins with homologues epitopes of human pathogen and IEDB epitopes provide opportunities for prioritization of these novel targets for T-cell therapies or antibody drugs. References Nakagawa S, Takahashi MU. gEVE: a genome-based endogenous viral element database provides comprehensive viral protein-coding sequences in mammalian genomes. Database, 2016;2016:1–8. https://doi.org/10.1093/database/baw087 Vita R, Mahajan S, Overton JA, Dhanda SK, Martini S, Cantrell JR, Wheeler DK, Sette A, Peters B. The Immune Epitope Database (IEDB): 2018 update. Nucleic Acids Research, 2019;47(D1):D339-D343. https://doi.org/10.1093/nar/gky1006
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".