Machine-Learning and Chemicogenomics Approach Defines and Predicts Cross-Talk of Hippo and MAPK Pathways

机器学习和化学基因组学方法定义并预测 Hippo 和 MAPK 通路的相互作用

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作者:Trang H Pham #, Thijs J Hagenbeek #, Ho-June Lee #, Jason Li, Christopher M Rose, Eva Lin, Mamie Yu, Scott E Martin, Robert Piskol, Jennifer A Lacap, Deepak Sampath, Victoria C Pham, Zora Modrusan, Jennie R Lill, Christiaan Klijn, Shiva Malek, Matthew T Chang #, Anwesha Dey #

Significance

An integrated chemicogenomics strategy was developed to identify a lineage-independent signature for the Hippo pathway in cancers. Evaluating transcriptional profiles using a machine-learning method led to identification of a relationship between YAP/TAZ dependency and MAPK pathway activity. The results help to nominate potential combination therapies with Hippo pathway inhibition.This article is highlighted in the In This Issue feature, p. 521.

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