Identification of Context-Specific Fitness Genes Associated With Metabolic Rearrangements for Prognosis and Potential Treatment Targets for Liver Cancer - Yu, Shizhe; Wang, Haoren; Gao, Jie; Liu, Long; Sun, Xiaoyan; Wang, Zhihui; Wen, Peihao; Shi, Xiaoyi; Shi, Jihua; Guo, Wenzhi; Zhang, Shuijun (Frontiers in Genetics, 2022)
Liver cancer is the most frequent fatal malignancy and lacks effective therapeutics. To construct a prognostic model for potential beneficiary screens and provide novel treatment targets, we performed Adaptive Daisy Model (ADaM) to identify context-specific fitness genes from CRISPR-Cas9 screens database DepMap. Functional analysis and prognostic significance were analyzed with the data from TCGA and ICGC cohorts. Drug sensitivity analysis was assessed with the data in Liver Cancer Model Repository (LIMORE). Finally, a 25-gene prognostic model was established and patients were divided into high-risk and low-risk groups, in which the high-risk group was with higher stemness index and short overall survival time. C-index, time-dependent ROC curves, and multivariate Cox regression analysis confirmed the excellent prognostic ability of this model. Functional enrichment analysis revealed the importance of metabolic rearrangements and serine/threonine kinase activity, which could be targeted by Trametinib, was the key pathway in regulating liver cancer cell viability. In conclusion, the present study provided a prognostic model for patients with liver cancers and might help explore novel therapeutic targets, thus improving patient outcomes.