ImmuneMirror: A machine learning-based integrative pipeline and web server for neoantigen prediction.

ABSTRACT: Neoantigens are derived from somatic mutations in the tumors but are absent in normal tissues. Emerging evidence suggests that neoantigens can stimulate tumor-specific T-cell-mediated antitumor immune responses, and therefore are potential immunotherapeutic targets. We developed ImmuneMirror as a stand-alone open-source pipeline and a web server incorporating a balanced random forest model for neoantigen prediction and prioritization. The prediction model was trained and tested using known immunogenic neopeptides collected from 19 published studies. The area under the curve of our trained model was 0.87 based on the testing data. We applied ImmuneMirror to the whole-exome sequencing and RNA sequencing data obtained from gastrointestinal tract cancers including 805 tumors from colorectal ca

SUBMITTER: Chuwdhury GS 

PROVIDER: S-EPMC10859690 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature