Dataset Information

Genetic Interaction-Based Biomarkers Identification for Drug Resistance and Sensitivity in Cancer Cells.

ABSTRACT: Cancer cells generally harbor hundreds of alterations in the cancer genomes and act as crucial factors in the development and progression of cancer. Gene alterations in the cancer genome form genetic interactions, which affect the response of patients to drugs. We developed an algorithm that mines copy number alteration and whole-exome mutation profiles from The Cancer Genome Atlas (TCGA), as well as functional screen data generated to identify potential genetic interactions for specific cancer types. As a result, 4,529 synthetic viability (SV) interactions and 10,637 synthetic lethality (SL) interactions were detected. The pharmacogenomic datasets revealed that SV interactions induced drug resistance in cancer cells and that SL interactions mediated drug sensitivity in cancer cells. Deletions of HDAC1 and DVL1, both of which participate in the Notch signaling pathway, had an SV effect in cancer cells, and deletion of DVL1 induced resistance to HDAC1 inhibitors in cancer cells. In addition, patients with low expression of both HDAC1 and DVL1 had poor prognosis. Finally, by integrating current reported genetic interactions from other studies, the Cancer Genetic Interaction database (CGIdb) (http://www.medsysbio.org/CGIdb) was constructed, providing a convenient retrieval for genetic interactions in cancer.

SUBMITTER: Han Y

PROVIDER: S-EPMC6700431 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Genetic Interaction-Based Biomarkers Identification for Drug Resistance and Sensitivity in Cancer Cells.

Han Yue Y Wang Chengyu C Dong Qi Q Chen Tingting T Yang Fan F Liu Yaoyao Y Chen Bo B Zhao Zhangxiang Z Qi Lishuang L Zhao Wenyuan W Liang Haihai H Guo Zheng Z Gu Yunyan Y

Molecular therapy. Nucleic acids 20190717

Cancer cells generally harbor hundreds of alterations in the cancer genomes and act as crucial factors in the development and progression of cancer. Gene alterations in the cancer genome form genetic interactions, which affect the response of patients to drugs. We developed an algorithm that mines copy number alteration and whole-exome mutation profiles from The Cancer Genome Atlas (TCGA), as well as functional screen data generated to identify potential genetic interactions for specific cancer ...[more]

PMID: 31400611

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Dataset Information

Genetic Interaction-Based Biomarkers Identification for Drug Resistance and Sensitivity in Cancer Cells.

Publications

Genetic Interaction-Based Biomarkers Identification for Drug Resistance and Sensitivity in Cancer Cells.

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