The most comprehensive catalogue of tumor-specific T cell targets to date — 16,687 empirically detected HLA-presented antigens across 21 cancer types, spanning 11 classes of molecular aberrations and identified in 88% of analyzed tumors.
Hover any pin on the human-body map to preview that cancer, or click to jump straight to its filtered view in the explorer below.
Every row is a tumor-specific peptide with its gene of origin, aberration class, HLA alleles, recurrence, abundance, tumor-vs-normal expression window, and DepMap essentiality. Click any row for the full annotation drawer.
Keyboard: press Esc to close the detail drawer.
| ⧉ | Cancer | Peptide | Gene | Class | Recurrence | Abundance | Spectral | T/N window | DepMap | Homog. | HLAs |
|---|---|---|---|---|---|---|---|---|---|---|---|
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Each tile's donut (NC = non-canonical) shows the fraction of the repertoire from non-canonical sources — splicing, cryptic ORFs, retroelements, mutations, fusions, microbial. Click a tile to filter the explorer above.
Selected discoveries from the manuscript — each has experimental validation and, in several cases, direct evidence of T cell anti-tumor activity.
A novel PMEL peptide produced when exon 5 is skipped, detected in 89% of SKCM samples. Presented more abundantly than canonical PMEL targets with negligible expression in normal skin.
First evidence of native LINE1 ORF2 protein expression across 12 tumor types. Three peptides synthesized and confirmed by LC-MS/MS.
Recurrent tumor-resident microbes in gynecologic cancers. CMV peptides presented on HLA across 7 tumor types — first evidence of endogenous CMV epitopes in primary human tumors.
69% of the non-canonical immunopeptidome derives from cryptic ORFs. Ribo-Seq confirmed 62% ribosomal occupancy in neuroblastoma PDXs.
MAGE-A4 (FDA-approved TCR-T target) observed across 13 cancer types. PRAME GQHLHLETF detected in 67% of B*15:01 carriers vs 27% for the canonical SLLQHLIGL.
2,401 immunopeptidome-evidenced neoantigens, including 127 public neoantigens shared across multiple tumor samples — of which 96% are not documented in the IEDB database. Covers well-known drivers (KRAS G12V, NPM1 frameshift, CTNNB1 T41A) plus newly identified shared neoantigens.
ImmunoVerse interrogates canonical self-antigens plus 10 non-canonical classes, each contributing distinct opportunities for cancer immunotherapy. Click any card to filter the explorer by that class.
An integrative multimodal pipeline combining transcriptomic events, tri-engine immunopeptidomic search, stringent multi-modal safety filtering, and single-cell essentiality analysis.
7,188 tumor RNA-Seq + 17,384 GTEx normals assembled into a histology-specific catalogue of canonical and non-canonical sources — filtered against 51 normal tissues.
1,823 immunopeptidomes searched with three complementary engines — MaxQuant, MS2Rescore, and the AI-driven Tesorai Search. Tesorai achieved up to 125% improvement in peptide IDs under high-confidence thresholds.
Candidates screened against the HLA Ligand Atlas (21 donors across 30 tissue types) and a Ribo-Seq healthy cryptic ORF database spanning 8 normal tissues — excluding an additional 19% (n=4,372) of candidates with normal-tissue evidence.
Predicted HLA binding layered onto empirical detection wherever HLA typing was available, excluding non-binders across all three search engines.
Each peptide scored on abundance, recurrence, normal-tissue exclusion, HLA affinity, DepMap essentiality, scRNA homogeneity, and MS confidence.
Entire pipeline available as a code-free cloud workflow on Cancer Genomics Cloud — run your own data through ImmunoVerse in under an hour.
Per-cancer JSON tables power this portal. Raw CSVs (with full abundance, HLA, and source annotations) are available through the main data repository — contact the corresponding author or clone the pipeline for the complete resource.
Each file contains every ranked candidate peptide for that cancer with the compact schema used by the explorer. For the complete annotated CSVs (including PSM-level intensities, NetMHCpan scores, and all matched HLA alleles), see the links below.
If you use ImmunoVerse data, pipeline, or derived targets in your research, please cite the manuscript.