Autor: |
Qian Wang, Xiangmei Li, Jiayue Qiu, Yalan He, Jiashuo Wu, Ji Li, Wei Liu, Junwei Han |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
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Zdroj: |
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 2536-2546 (2023) |
Druh dokumentu: |
article |
ISSN: |
2001-0370 |
DOI: |
10.1016/j.csbj.2023.04.004 |
Popis: |
Immune checkpoint inhibitor (ICI) therapy has become a powerful clinical strategy for treating melanoma. The relationship between somatic mutations and the clinical benefits of immunotherapy has been widely recognized. However, the gene-based predictive biomarkers are less stable due to the heterogeneity of cancer at the individual gene level. Recent studies have suggested that the accumulation of gene mutations in biological pathways may activate antitumor immune responses. Herein, a novel pathway mutation signature (PMS) was constructed to predict the survival and efficacy of ICI therapy. In a dataset of melanoma patients treated with anti-CTLA-4, we mapped the mutated genes into the pathways and then identified seven significant mutation pathways associated with survival and immunotherapy response, which were used to construct the PMS model. According to the PMS model, the patients in the PMS-high group showed better overall survival (hazard ratio (HR) = 0.37; log-rank test, p |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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