2023년도 제 17회 BK 통계 세미나 개최를 안내드립니다.
고려대학교 통계학과 통계연구소, BK21 통계학교육연구팀과 DS+ 사업단 주최로 이루어지는 세미나입니다.
일시 : 2023년 12월 08일 (금) 오전 11시
장소 : 고려대학교 정경관 206호
연사 : 박희원 교수 (성신여대 통계학과)
Predictive-Network for gastrc cancer drug response-predictive network analysis
Understanding drug sensitivity and related markers identification are critical tasks in precision medicine, and drug sensitivity prediction has drawn a large amount of attention to understand the mechanism related drug sensitivity of cancer cell lines, because cancer-related mechanisms caused by disturbance in complex gene regulatory system. However, relatively little attention has been paid to the gene network-based prediction. Furthermore, existing studies on network-based analysis were based on pre-constructed gene networks, thus we cannot extract cell line status specific gene networks, leading to difficulty in understanding drug sensitivity related mechanisms and marker identification. We propose a novel computational methodology for clinical characteristic (e.g., drug sensitivity of cell lines) predictive gene network estimation, called a PredictiveNetwork. The objective function of the PredictiveNetwork consists of loss functions for gene network estimation and prediction, and thus we can estimate gene network and predict clinical characteristic, simultaneously. It implies that the network is estimated to be optimized for not only network estimation but also explain the clinical characteristic, thus we can identify clinical characteristic prediction specific molecular interplays. The PredictiveNetwork is applied to gastric cancer drugs (doxorubicin, mitomycin-c, 5-Fluorouracil (5-FU), and docetaxel) response predictive network estimation. Our analysis results suggest that the molecular interplay between ARK family genes and ANXA10/ZNF162 activity play key role in the mechanisms underlying acquired resistance/sensitivity to gastric cancer drugs. Manipulating suppressors and induces of ARK family genes, ANXA10, and ZNF162 may be a way to reduce drug resistance of cancer cell lines.
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