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A Community Challenge for Pancancer Drug Mechanism of Action Inference from Perturbational Profile Data

Authors :
Martino Bertoni
Yuanpeng Xiong
Jing Tang
Charles Karan
Ziaurrehman Tanoli
Tingzhong Tian
Julio Saez-Rodriguez
Chung
Fangping Wan
Robert J. Allaway
Miquel Duran-Frigola
Shuya Li
Andrea Califano
Patrick Aloy
Justin Guinney
Daniela S. Gerhard
Shuyu Zheng
Ronald Realubit
Jianyang Zeng
Bence Szalai
Oriol Guitart-Pla
Wenyu Wang
Pau Badia-i-Mompel
Mohieddin Jafari
Alberto Pessia
Lidia Mateo
Adrià Fernández-Torras
Douglass Ef
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

SUMMARYThe Columbia Cancer Target Discovery and Development (CTD2) Center has developed PANACEA (PANcancer Analysis of Chemical Entity Activity), a collection of dose-response curves and perturbational profiles for 400 clinical oncology drugs in cell lines selected to optimally represent 19 cancer subtypes. This resource, developed to study tumor-specific drug mechanism of action, was instrumental in hosting a DREAM Challenge to assess computational models for de novo drug polypharmacology prediction. Dose-response and perturbational profiles for 32 kinase inhibitors were provided to 21 participating teams, who did not know the identity or nature of the compounds, and they were asked to predict high-affinity binding among ~1,300 possible protein targets. Best performing methods leveraged both gene expression profile similarity analysis, and deep-learning methodologies trained on individual datasets. This study lays the foundation for future integrative analyses of pharmacogenomic data, reconciliation of polypharmacology effects in different tumor contexts, and insights into network-based assessment of context-specific drug mechanism of action.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........8d6105a6b5772c0f9a74a4d1989ec2ee
Full Text :
https://doi.org/10.1101/2020.12.21.423514