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Characterization of Somatic Mutations That Affect Neoantigens in Non-Small Cell Lung Cancer

PURPOSE: Immune checkpoint inhibitors (ICIs) have recently emerged as an important option for treating patients with advanced non-small cell lung cancer (NSCLC). Neoantigens are important biomarkers and potential immunotherapy targets that play important roles in the prognosis and treatment of patie...

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Detalles Bibliográficos
Autores principales: Liang, Hongge, Xu, Yan, Chen, Minjiang, Zhao, Jing, Zhong, Wei, Liu, Xiaoyan, Gao, Xiaoxing, Li, Shanqing, Li, Ji, Guo, Chao, Jia, He, Wang, Mengzhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959482/
https://www.ncbi.nlm.nih.gov/pubmed/35356154
http://dx.doi.org/10.3389/fimmu.2021.749461
Descripción
Sumario:PURPOSE: Immune checkpoint inhibitors (ICIs) have recently emerged as an important option for treating patients with advanced non-small cell lung cancer (NSCLC). Neoantigens are important biomarkers and potential immunotherapy targets that play important roles in the prognosis and treatment of patients with NSCLC. This study aimed to evaluate and characterize the relationships between somatic mutations and potential neoantigens in specimens from patients who underwent surgical treatment for NSCLC. PATIENTS AND METHODS: This prospective study evaluated specimens from patients with NSCLC who underwent surgical treatment at the Peking Union Medical College, China, from June 2019 to September 2019. Whole-exome sequencing was performed for tumor tissues and corresponding normal tissues. Candidate neoantigens were predicted using generative software, and the relationships between various mutation characteristics and number of neoantigens were evaluated. RESULTS: Neoantigen-related gene mutations were less frequent than mutations affecting the whole genome. Genes with high neoantigen burden had more types and higher frequencies of mutations. The number of candidate neoantigens was positively correlated with missense mutations, code shift insertions/deletions, split-site variations, and nonsense mutations. However, in the multiple linear regression analysis, only missense mutations were positively correlated with the number of neoantigens. The number of neoantigens was also positively correlated with base transversions (A>C/C>A, T>G/G>T, and C>G/G>C) and negatively correlated with base transitions (A>G/G>A and C>T/T>C). CONCLUSION: The number of candidate neoantigens in NSCLC specimens was associated with mutation frequency, type of mutation, and type of base substitution.