[BK 생명과학과 세미나 안내]
연사 : 김상욱 교수(포항공대 생명과학과)
연제 : Network based approaches for precision medicine
일시 : 2022년 01월 12일 (수) 오전 11시
장소 : 온라인 화상 강의로 진행됩니다.
초청교수 : 지성욱 교수
**Zoom 회의 참가
https://korea-ac-kr.zoom.us/j/87827828926?pwd=NGlZUWtTMnlSMmp1WU9pYUZ5T0J2UT09
회의 ID: 878 2782 8926
암호: Bk#2022-01
Abstract
Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. However, current machine-learning-based predictions of drug response often fail to identify robust translational biomarkers from preclinical models. Here, we present a machine-learning framework to identify robust drug biomarkers by taking advantage of network-based analyses using pharmacogenomic data derived from three-dimensional organoid culture models. The biomarkers identified by our approach accurately predict the drug responses of 114 colorectal cancer patients treated with 5-fluorouracil and 77 bladder cancer patients treated with cisplatin. We further confirm our biomarkers using external transcriptomic datasets of drug-sensitive and -resistant isogenic cancer cell lines. Finally, concordance analysis between the transcriptomic biomarkers and independent somatic mutation-based biomarkers further validate our method. This work presents a method to predict cancer patient drug responses using pharmacogenomic data derived from organoid models by combining the application of gene modules and network-based approaches.