Drug Sensitivity Prediction From Cell Line-Based Pharmacogenomics Data: Guidelines for Developing Machine Learning Models
Drug Sensitivity Prediction From Cell Line-Based Pharmacogenomics Data: Guidelines for Developing Machine Learning Models
ABSTRACT The goal of precision oncology is to tailor treatment for patients individually using the genomic profile of their tumors. Pharmacogenomics datasets such as cancer cell lines are among the most valuable resources for drug sensitivity prediction, a crucial task of precision oncology. Machine learning methods have been employed to predict drug sensitivity based on the multiple omics data available for large panels of cancer cell lines. However, there are no comprehensive guidelines on how to properly train and validate such machine learning models for drug sensitivity prediction. In this paper, we introduce a set of guidelines for different aspects of training gene expression-based predictors using cell line datasets. These guidelines provide extensive analysis of the generalization of drug sensitivity predictors, and challenge many current practices in the community including the choice of training dataset and measure of drug sensitivity. Application of these guidelines in future studies will enable the development of more robust preclinical biomarkers.
Haibe-Kains Benjamin、Smirnov Petr、Mammoliti Anthony、Mer Arvind Singh、Jahangiri-Tazehkand Soheil、Hon Casey、Nair Sisira Kadambat、Ester Martin、Sharifi-Noghabi Hossein
Department of Medical Biophysics, University of Toronto||Princess Margaret Cancer Centre||Ontario Institute for Cancer Research||University of TorontoDepartment of Medical Biophysics, University of Toronto||Princess Margaret Cancer Centre||University of TorontoDepartment of Medical Biophysics, University of Toronto||Princess Margaret Cancer Centre||University of TorontoDepartment of Medical Biophysics, University of Toronto||Princess Margaret Cancer Centre||University of TorontoDepartment of Medical Biophysics, University of Toronto||Princess Margaret Cancer Centre||University of TorontoPrincess Margaret Cancer Centre||University of TorontoPrincess Margaret Cancer CentreSchool of Computing Science, Simon Fraser University||Vancouver Prostate CenterSchool of Computing Science, Simon Fraser University||Vancouver Prostate Center||Princess Margaret Cancer Centre
医学研究方法肿瘤学药学
Haibe-Kains Benjamin,Smirnov Petr,Mammoliti Anthony,Mer Arvind Singh,Jahangiri-Tazehkand Soheil,Hon Casey,Nair Sisira Kadambat,Ester Martin,Sharifi-Noghabi Hossein.Drug Sensitivity Prediction From Cell Line-Based Pharmacogenomics Data: Guidelines for Developing Machine Learning Models[EB/OL].(2025-03-28)[2025-05-15].https://www.biorxiv.org/content/10.1101/2021.04.09.439076.点此复制
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