Researchers at Fudan University, in collaboration with Zhejiang Cancer Hospital (Hangzhou Institute of Medicine, Chinese Academy of Sciences) and Washington University in St. Louis, have released bacNeo, the first comprehensive computational toolkit dedicated to identifying bacteria-derived neoantigens in human cancers. The framework combines three modules, BACC for bacterial component classification, BACH for HLA allele typing, and BACP for bacterial peptide prioritization, into a single one-stop pipeline that accommodates metagenomic, metatranscriptomic, bulk and single-cell sequencing, and mass spectrometry data. A novel scoring system, SPARK (Score for Peptide Antigenicity Recognition and Kinetics), weights TAP transport efficiency against HLA-peptide binding affinity and reaches an area under the ROC curve of 0.81 on experimentally validated peptide-HLA datasets. The work, published in iMetaMed, provides a reproducible and modular foundation for systematic bacterial neoantigen discovery and supports the design of therapeutic vaccines, chimeric antigen receptor (CAR) T-cell therapies, and immune checkpoint blockade strategies across diverse cancer types.
