Advances and Challenges in Neoantigen Prediction for Cancer Immunotherapy

Yi Zhang¹Ting-Ting Chen²Xiong Li³Ai-Lin Lan¹Pengfei Ji⁴Yajuan Zhu^5*Xue Yao Ma^6,7*

• ¹The First Clinical Medical College of Lanzhou University, Lanzhou, China., Lanzhou, China
• ²Department of Gastroenterology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China., Lanzhou, China
• ³Department of Gastroenterology, the Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China., Xi'an, China
• ⁴Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
• ⁵Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
• ⁶Lanzhou University Second Hospital, Lanzhou, China
• ⁷Department of Gynecology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China., Lanzhou, China

Neoantigens, derived from tumor-specific mutations, are promising targets of cancer immunotherapy by eliciting tumor-specific T-cell responses while sparing normal cells. Accurate neoantigen prediction relies on immunogenomics and immunopeptidomics. Immunogenomics identifies tumor-specific mutations via next-generation sequencing. Immunopeptidomics detects MHC-presented peptides using mass spectrometry. Integrating these two methods enhances prediction accuracy but faces challenges due to tumor heterogeneity, HLA diversity, and immune evasion. Future advancements will focus on dynamic tumor microenvironment monitoring, multi-omics integration, improved computational models and algorithms to refine neoantigen prediction, and developing optimized personalized vaccines.