A community challenge for a pancancer drug mechanism of action inference from perturbational profile data
The Columbia Cancer Target Discovery and Development (CTD2) Center is developing PANACEA, a resource comprising dose-responses and RNA sequencing (RNA-seq) profiles of 25 cell lines perturbed with ∼400 clinical oncology drugs, to study a tumor-specific drug mechanism of action. Here, this resource s...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
January 18, 2022
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| In: |
Cell reports. Medicine
Year: 2022, Volume: 3, Issue: 1, Pages: 1-13, e1-e7 |
| ISSN: | 2666-3791 |
| DOI: | 10.1016/j.xcrm.2021.100492 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.xcrm.2021.100492 Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S2666379121003694 |
| Author Notes: | Eugene F. Douglass, Robert J. Allaway, Bence Szalai, Wenyu Wang, Tingzhong Tian, Adrià Fernández-Torras, Ron Realubit, Charles Karan, Shuyu Zheng, Alberto Pessia, Ziaurrehman Tanoli, Mohieddin Jafari, Fangping Wan, Shuya Li, Yuanpeng Xiong, Miquel Duran-Frigola, Martino Bertoni, Pau Badia-i-Mompel, Lídia Mateo, Oriol Guitart-Pla, Verena Chung, Jing Tang, Jianyang Zeng, Patrick Aloy, Julio Saez-Rodriguez, Justin Guinney, Daniela S. Gerhard, and Andrea Califano |
| Summary: | The Columbia Cancer Target Discovery and Development (CTD2) Center is developing PANACEA, a resource comprising dose-responses and RNA sequencing (RNA-seq) profiles of 25 cell lines perturbed with ∼400 clinical oncology drugs, to study a tumor-specific drug mechanism of action. Here, this resource serves as the basis for a DREAM Challenge assessing the accuracy and sensitivity of computational algorithms for de novo drug polypharmacology predictions. Dose-response and perturbational profiles for 32 kinase inhibitors are provided to 21 teams who are blind to the identity of the compounds. The teams are asked to predict high-affinity binding targets of each compound among ∼1,300 targets cataloged in DrugBank. The best performing methods leverage gene expression profile similarity analysis as well as 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 assessments of drug mechanisms of action. |
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| Item Description: | Gesehen am 20.12.2022 |
| Physical Description: | Online Resource |
| ISSN: | 2666-3791 |
| DOI: | 10.1016/j.xcrm.2021.100492 |