Feng Xu, Tang Mengfan, Dede Merve, Su Dan, Pei Guangsheng, Jiang Dadi, Wang Chao, Chen Zhen, Li Mi, Nie Litong, Xiong Yun, Li Siting, Park Jeong-Min, Zhang Huimin, Huang Min, Szymonowicz Klaudia, Zhao Zhongming, Hart Traver, Chen Junjie
Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Sci Adv. 2022 May 13;8(19):eabm6638. doi: 10.1126/sciadv.abm6638.
Exploiting cancer vulnerabilities is critical for the discovery of anticancer drugs. However, tumor suppressors cannot be directly targeted because of their loss of function. To uncover specific vulnerabilities for cells with deficiency in any given tumor suppressor(s), we performed genome-scale CRISPR loss-of-function screens using a panel of isogenic knockout cells we generated for 12 common tumor suppressors. Here, we provide a comprehensive and comparative dataset for genetic interactions between the whole-genome protein-coding genes and a panel of tumor suppressor genes, which allows us to uncover known and new high-confidence synthetic lethal interactions. Mining this dataset, we uncover essential paralog gene pairs, which could be a common mechanism for interpreting synthetic lethality. Moreover, we propose that some tumor suppressors could be targeted to suppress proliferation of cells with deficiency in other tumor suppressors. This dataset provides valuable information that can be further exploited for targeted cancer therapy.
利用癌症脆弱性对于抗癌药物的发现至关重要。然而，由于肿瘤抑制因子功能丧失，无法直接将其作为靶点。为了揭示任何给定肿瘤抑制因子缺陷细胞的特定脆弱性，我们使用为12种常见肿瘤抑制因子生成的一组同基因敲除细胞进行了全基因组CRISPR功能丧失筛选。在此，我们提供了一个关于全基因组蛋白质编码基因与一组肿瘤抑制基因之间遗传相互作用的全面且具有可比性的数据集，这使我们能够揭示已知和新的高可信度合成致死相互作用。通过挖掘该数据集，我们发现了必需的旁系同源基因对，这可能是解释合成致死性的一种常见机制。此外，我们提出某些肿瘤抑制因子可作为靶点来抑制其他肿瘤抑制因子缺陷细胞的增殖。该数据集提供了有价值的信息，可进一步用于靶向癌症治疗。
