[논문]Computational inference of cancer-specific vulnerabilities in clinical samples

Jang, Kiwon; Park, Min Ji; Park, Jae Soon; Hwangbo, Haeun; Sung, Min Kyung; Kim, Sinae; Jung, Jaeyun; Lee, Jong Won; Ahn, Sei-Hyun; Chang, Suhwan; Choi, Jung Kyoon

doi:10.1186/s13059-020-02077-1

[해외논문] Computational inference of cancer-specific vulnerabilities in clinical samples 원문보기

Genome biology, v.21 no.1 = v.21, 2020년, pp.155 -

Jang, Kiwon (Department of Bio and Brain Engineering, KAIST, Daejeon, 34141 Republic of Korea) , Park, Min Ji (Department of Biomedical Sciences, University of Ulsan College of Medicine, Asan Medical Center, Seoul, 05505 Republic of Korea) , Park, Jae Soon (Department of Bio and Brain Engineering, KAIST, Daejeon, 34141 Republic of Korea) , Hwangbo, Haeun (Department of Bio and Brain Engineering, KAIST, Daejeon, 34141 Republic of Korea) , Sung, Min Kyung (Department of Bio and Brain Engineering, KAIST, Daejeon, 34141 Republic of Korea) , Kim, Sinae (Department of Biomedical Sciences, University of Ulsan College of Medicine, Asan Medical Center, Seoul, 05505 Republic of Korea) , Jung, Jaeyun (Department of Biomedical Sciences, University of Ulsan College of Medicine, Asan Medical Center, Seoul, 05505 Republic of Korea) , Lee, Jong Won (Department of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, 05505 Republic of Korea) , Ahn, Sei-Hyun (Department of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, 05505 Republic of Korea) , Chang, Suhwan (Department of Biomedical Sciences, Univers) , Choi, Jung Kyoon

Abstract ▼ AI-Helper

BackgroundSystematic in vitro loss-of-function screens provide valuable resources that can facilitate the discovery of drugs targeting cancer vulnerabilities.ResultsWe develop a deep learning-based method to predict tumor-specific vulnerabilities in patient samples by leveraging a wealth of in vitro screening data. Acquired dependencies of tumors are inferred in cases in which one allele is disrupted by inactivating mutations or in association with oncogenic mutations. Nucleocytoplasmic transport by Ran GTPase is identified as a common vulnerability in Her2-positive breast cancers. Vulnerability to loss of Ku70/80 is predicted for tumors that are defective in homologous recombination and rely on nonhomologous end joining for DNA repair. Our experimental validation for Ran, Ku70/80, and a proteasome subunit using patient-derived cells shows that they can be targeted specifically in particular tumors that are predicted to be dependent on them.ConclusionThis approach can be applied to facilitate the development of precision therapeutic targets for different tumors.

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