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A Four-Cell-Senescence-Regulator-Gene Prognostic Index Verified by Genome-Wide CRISPR Can Depict the Tumor Microenvironment and Guide Clinical Treatment of Bladder Cancer

清脆的 调节器 肿瘤微环境 衰老 基因组 主调节器 膀胱癌 基因 癌症 细胞 生物 计算生物学 生物信息学 癌症研究 肿瘤细胞 遗传学 转录因子
作者
Jian‐Xuan Sun,Chen‐Qian Liu,Jin‐Zhou Xu,Ye An,Mengyao Xu,Xingyu Zhong,Na Zeng,Si-Yang Ma,Hao‐Dong He,Zong-Biao Zhang,Shaogang Wang,Qi‐Dong Xia
出处
期刊:Frontiers in Immunology [Frontiers Media]
卷期号:13 被引量:14
标识
DOI:10.3389/fimmu.2022.908068
摘要

Bladder cancer (BCa) is the 10th most commonly diagnosed cancer worldwide, and cellular senescence is defined as a state of permanent cell cycle arrest and considered to play important roles in the development and progression of tumor. However, the comprehensive effect of senescence in BCa has not ever been systematically evaluated. Using the genome-wide CRISPR screening data acquired from DepMap (Cancer Dependency Map), senescence genes from the CellAge database, and gene expression data from The Cancer Genome Atlas (TCGA), we screened out 12 senescence genes which might play critical roles in BCa. A four-cell-senescence-regulator-gene prognostic index was constructed using the least absolute shrinkage and selection operator (LASSO) and multivariate COX regression model. The transcriptomic data and clinical information of BCa patients were downloaded from TCGA and Gene Expression Omnibus (GEO). We randomly divided the patients in TCGA cohort into training and testing cohorts and calculated the risk score according to the expression of the four senescence genes. The validity of this risk score was validated in the testing cohort (TCGA) and validation cohort (GSE13507). The Kaplan–Meier curves revealed a significant difference in the survival outcome between the high- and low-risk score groups. A nomogram including the risk score and other clinical factors (age, gender, stage, and grade) was established with better predictive capacity of OS in 1, 3, and 5 years. Besides, we found that patients in the high-risk group had higher tumor mutation burden (TMB); lower immune, stroma, and ESTIMATE scores; higher tumor purity; aberrant immune functions; and lower expression of immune checkpoints. We also performed gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) to investigate the interaction between risk score and hallmark pathways and found that a high risk score was connected with activation of senescence-related pathways. Furthermore, we found that a high risk score was related to better response to immunotherapy and chemotherapy. In conclusion, we identified a four-cell-senescence-regulator-gene prognostic index in BCa and investigated its relationship with TMB, the immune landscape of tumor microenvironment (TME), and response to immunotherapy and chemotherapy, and we also established a nomogram to predict the prognosis of patients with BCa.
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