Genome wide-scale CRISPR-Cas9 knockout screens identify a fitness score for optimized risk stratification in colorectal cancer

危险分层 清脆的 结直肠癌 分层(种子) 计算生物学 生物信息学 风险评估 医学 癌症 计算机科学 内科学 生物 肿瘤科 遗传学 基因 植物 种子休眠 发芽 计算机安全 休眠
作者
Xiangchou Yang,Jieyu Liu,Shuaibin Wang,Wail Hussein Ahmed Al-Ameer,Jingting Ji,Jiaqi Cao,Hassan Mansour S Dhaen,Ying Lin,Yangyang Zhou,Chenguo Zheng
出处
期刊:Journal of Translational Medicine [BioMed Central]
卷期号:22 (1): 554-554 被引量:8
标识
DOI:10.1186/s12967-024-05323-3
摘要

Abstract Background The molecular complexity of colorectal cancer poses a significant challenge to the clinical implementation of accurate risk stratification. There is still an urgent need to find better biomarkers to enhance established risk stratification and guide risk-adapted treatment decisions. Methods we systematically analyzed cancer dependencies of 17 colorectal cancer cells and 513 other cancer cells based on genome-scale CRISPR-Cas9 knockout screens to identify colorectal cancer-specific fitness genes. A regression model was built using colorectal cancer-specific fitness genes, which was validated in other three independent cohorts. 30 published gene expression signatures were also retrieved. Findings We defined a total of 1828 genes that were colorectal cancer-specific fitness genes and identified a 22 colorectal cancer-specific fitness gene (CFG22) score. A high CFG22 score represented unfavorable recurrence and mortality rates, which was validated in three independent cohorts. Combined with age, and TNM stage, the CFG22 model can provide guidance for the prognosis of colorectal cancer patients. Analysis of genomic abnormalities and infiltrating immune cells in the CFG22 risk stratification revealed molecular pathological difference between the subgroups. Besides, drug analysis found that CFG22 high patients were more sensitive to clofibrate. Interpretation The CFG22 model provided a powerful auxiliary prediction tool for identifying colorectal cancer patients with high recurrence risk and poor prognosis, optimizing precise treatment and improving clinical efficacy.
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