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Life Sci Alliance. 2019 Jun 28;2(4). pii: e201900445. doi: 10.26508/lsa.201900445. Print 2019 Aug.

The cancer cell proteome and transcriptome predicts sensitivity to targeted and cytotoxic drugs.

Author information

1
Charité-Universitätsmedizin, Institute of Pathology, Berlin, Germany.
2
Genentech Inc., Oncology Biomarker Development, South San Francisco CA, USA.
3
Humboldt Universität zu Berlin, Integrative Research Institute for the Life Sciences, Berlin, Germany.
4
Genentech Inc., Oncology Biomarker Development, South San Francisco CA, USA yan.yibing@gene.com.
5
Charité-Universitätsmedizin, Institute of Pathology, Berlin, Germany nils.bluethgen@charite.de.

Abstract

Tumors of different molecular subtypes can show strongly deviating responses to drug treatment, making stratification of patients based on molecular markers an important part of cancer therapy. Pharmacogenomic studies have led to the discovery of selected genomic markers (e.g., BRAFV600E), whereas transcriptomic and proteomic markers so far have been largely absent in clinical use, thus constituting a potentially valuable resource for further substratification of patients. To systematically assess the explanatory power of different -omics data types, we assembled a panel of 49 melanoma cell lines, including genomic, transcriptomic, proteomic, and pharmacological data, showing that drug sensitivity models trained on transcriptomic or proteomic data outperform genomic-based models for most drugs. These results were confirmed in eight additional tumor types using published datasets. Furthermore, we show that drug sensitivity models can be transferred between tumor types, although after correcting for training sample size, transferred models perform worse than within-tumor-type predictions. Our results suggest that transcriptomic/proteomic signals may be alternative biomarker candidates for the stratification of patients without known genomic markers.

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