Int J Med Sci 2021; 18(9):2063-2075. doi:10.7150/ijms.51703 This issue

Research Paper

Characteristics and prognostic value of potential dependency genes in clear cell renal cell carcinoma based on a large-scale CRISPR-Cas9 and RNAi screening database DepMap

Bowen Shi*, Jie Ding*, Jun Qi, Zhengqin Gu

Department of Urology, School of Medicine, Xinhua Hospital Affiliated to Shanghai Jiao Tong University, Shanghai 200092, P.R. China.
* These authors contributed equally.

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Citation:
Shi B, Ding J, Qi J, Gu Z. Characteristics and prognostic value of potential dependency genes in clear cell renal cell carcinoma based on a large-scale CRISPR-Cas9 and RNAi screening database DepMap. Int J Med Sci 2021; 18(9):2063-2075. doi:10.7150/ijms.51703. Available from https://www.medsci.org/v18p2063.htm

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Abstract

Graphic abstract

Background: Large-scale loss-of-function screening database such as Cancer Dependency Map (Depmap) provide abundant resources. Investigation of these potential dependency genes from human cancer cell lines in the real-world patients cohort would evaluate their prognostic value thus facilitate their clinical application and guide drug development.

Methods: A few genes were selected from top clear cell renal cell carcinoma (ccRCC) lineage preferential dependency candidates from Depmap. Their characteristic including expression levels both in normal and tumor tissues and correlations with methylation or copy number, genetic alterations, functional enrichment, immune-associated interactions, prognostic value were evaluated in KIRC cohort from TCGA, GTEx, and multiple other open databases and platforms.

Results: 16 genes were collected from 106 ccRCC preferential candidates and further analyzed including B4GALT4, BCL2L1, CDH2, COPG1, CRB3, FERMT2, GET4, GPX4, HNF1B, ITGAV, MDM2, NFE2L2, PAX8, RUVBL1, TFRC, and TNFSF10. The normalized gene effect scores of these genes varied from different ccRCC cell lines and principal component analysis (PCA) showed their tissue specificity expression profiles. Genetic alteration rates of them were low to moderate (0.7%-13%) in KIRC cohort. CDH2, MDM2, TNFSF10 showed a statistically significant higher level in tumors than normal tissues while PAX8 and FERMT2 were significantly downregulated. Moderate positive or negative correlations were observed in several genes between their expression and relative gene copy number or methylation levels, respectively. Based on the multivariable COX regression model adjusted by critical clinical variables revealed the expression of GET4 (p=0.002, HR=1.023 95%CI 1.009-1.038) and CRB3 (p<0.001, HR=0.969 95%CI 0.960-0.980) were independent predictive factors for overall survival in KIRC cohort.

Conclusions: A dependency gene validated in cell lines didn't directly represent its role in corresponding patients with same histological type and their prognostic value might be determined by multiple factors including dependency driven types, genetic alteration rates and expression levels. GET4 and CRB3 were the independent prognostic factors for ccRCC patients. CRB3 seemed like a potential broad tumor suppressor gene while GET4 might be a ccRCC preferential dependency gene with a ligandable structure.

Keywords: Clear cell renal cell carcinoma, Depmap database, Dependency, Prognostic value, TCGA.