NeoHunter:Flexible software for systematically detecting neoantigens from sequencing data  

作　　者：Tianxing Ma Zetong Zhao Haochen Li Lei Wei Xuegong Zhang 

机构地区：[1]MOE Key Lab of Bioinformatics,Bioinformatics Division of BNRIST and Department of Automation,Tsinghua University,Beijing,China [2]School of Medicine,Tsinghua University,Beijing,China [3]School of Life Sciences,Tsinghua University,Beijing,China

出　　处：《Quantitative Biology》2024年第1期70-84,共15页定量生物学（英文版）

基　　金：National Key R&D Program of China,Grant/Award Number:2021YFF1200900;National Natural Science Foundation of China,Grant/Award Numbers:61721003,62250005,62103227。

摘　　要：Complicated molecular alterations in tumors generate various mutant peptides.Some of these mutant peptides can be presented to the cell surface and then elicit immune responses,and such mutant peptides are called neoantigens.Accurate detection of neoantigens could help to design personalized cancer vaccines.Although some computational frameworks for neoantigen detection have been proposed,most of them can only detect SNV-and indel-derived neoantigens.In addition,current frameworks adopt oversimplified neoantigen prioritization strategies.These factors hinder the comprehensive and effective detection of neoantigens.We developed NeoHunter,flexible software to systematically detect and prioritize neoantigens from sequencing data in different formats.NeoHunter can detect not only SNV-and indel-derived neoantigens but also gene fusion-and aberrant splicing-derived neoantigens.NeoHunter supports both direct and indirect immunogenicity evaluation strategies to prioritize candidate neoantigens.These strategies utilize binding characteristics,existing biological big data,and T-cell receptor specificity to ensure accurate detection and prioritization.We applied NeoHunter to the TESLA dataset,cohorts of melanoma and non-small cell lung cancer patients.NeoHunter achieved high performance across the TESLA cancer patients and detected 79%(27 out of 34)of validated neoantigens in total.SNV-and indel-derived neoantigens accounted for 90%of the top 100 candidate neoantigens while neoantigens from aberrant splicing accounted for 9%.Gene fusion-derived neoantigens were detected in one patient.NeoHunter is a powerful tool to‘catch all’neoantigens and is available for free academic use on Github(XuegongLab/NeoHunter).

关 键 词：cancer vaccine molecular alteration NEOANTIGEN neoantigen prioritization 

分 类 号：R186[医药卫生—流行病学]