CAN-IMMUNE: Cancer Mutant Peptide and Neoantigen Database
A comprehensive platform for cancer-specific immunopeptidomics-based neoantigen mapping and evaluation
e.g., HCC-1395, MDA-MB-231, and more
e.g., Skin, Liver, Lung, and more
e.g., Adenoma, Carcinoma... etc
Documented mutations per cancer type. Stacked: cell line (blue) + tissue (orange). Drag the slider to browse all cancer types.
Key database metrics at a glance: curated cancer types, cell lines, total mutations, tissue sites, unique mutant peptides and genes across all data sources.
Mutation composition across sources: nucleotide substitution spectrum, amino-acid change distribution, and mutation frequency by data source (COSMIC Tissue, COSMIC Cell line, DepMap/CCLE, PubMed & Neoantigen DBs).
Number of samples and genes per tissue lineage, for cell lines and tissue samples. Bubble size = #samples or #genes; colour = total mutations (log scale). Same data as manuscript Fig. 1.
About CAN-IMMUNE
Neoantigens are formed due to the somatic mutations that arise during carcinogenesis; they give rise to unique neo-peptides bearing cancer-specific mutations that are presented on the surface of the tumour in complex with human leukocyte antigen (HLA) molecules for scrutiny by T cells. Some neoepitopes can be recognised by tumoricidal T cells and serve as targets for cancer vaccines and immunotherapies. Liquid chromatography-mass spectrometry (LC-MS/MS) identifies HLA-presented peptides through spectral matching against reference proteome databases. However, reference proteome databases usually contain only canonical sequences and lack cancer-specific mutations, limiting neoantigen discovery.
To tackle this challenge, we developed a comprehensive platform, CAN-IMMUNE, to browse, search, and generate cancer-specific mutant peptide libraries, thereby enabling the identification of common mutant peptides during LC-MS/MS spectral searches. Major highlights of CAN-IMMUNE include (i) by curating multiple sources of mutation data, CAN-IMMUNE documents 4,531,600 unique mutant peptides across 55 curated cancer types from 2,052 cancer cell lines and 31 tissue lineages, facilitating the generation of bespoke cancer-relevant mutant peptide libraries; (ii) MutPep, a component of CAN-IMMUNE to allow local generation of mutant peptide libraries using inputs from users; and (iii) a computational strategy for prioritising mutant peptides.
We showcased the use of CAN-IMMUNE by searching immunopeptidomics datasets of triple-negative breast cancer and melanoma cell lines. Using CAN-IMMUNE libraries, we computationally identified and prioritised mutant peptides not represented in canonical reference proteome searches, thereby providing potential neoantigen candidates for further immunogenicity assessment. We anticipate CAN-IMMUNE can accelerate the identification of cancer neoantigens for the development of targeted cancer immunotherapies.
Cite CAN-IMMUNE
If you use CAN-IMMUNE in your research, please cite:
Krishna, S. & Li, C. (2026). CAN-IMMUNE: A comprehensive cancer neoantigen database for immunopeptidomics-based mutation mapping and MHC-I binding evaluation. Computational and Structural Biotechnology Journal (under revision).
Available at: https://canelib.erc.monash.edu