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Quantitative in vivo analyses reveal a complex pharmacogenomic landscape in lung adenocarcinoma

View ORCID ProfileChuan Li, Wen-Yang Lin, Hira Rizvi, Hongchen Cai, Christopher D. McFarland, Zoë N. Rogers, Maryam Yousefi, Ian P. Winters, Charles M. Rudin, Dmitri A. Petrov, Monte M. Winslow
doi: https://doi.org/10.1101/2020.01.28.923912
Chuan Li
1Department of Biology, Stanford University, Stanford, CA, USA
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  • ORCID record for Chuan Li
Wen-Yang Lin
2Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
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Hira Rizvi
3Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, USA
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Hongchen Cai
2Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
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Christopher D. McFarland
1Department of Biology, Stanford University, Stanford, CA, USA
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Zoë N. Rogers
2Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
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Maryam Yousefi
2Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
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Ian P. Winters
2Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
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Charles M. Rudin
4Department of Medicine, Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, USA
5Department of Medicine, Weill Cornell Medical College, New York, USA
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Dmitri A. Petrov
1Department of Biology, Stanford University, Stanford, CA, USA
6Cancer Biology Program, Stanford University School of Medicine, Stanford, CA, USA
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  • For correspondence: mwinslow@stanford.edu dpetrov@stanford.edu
Monte M. Winslow
2Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
6Cancer Biology Program, Stanford University School of Medicine, Stanford, CA, USA
7Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
8Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
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  • For correspondence: mwinslow@stanford.edu dpetrov@stanford.edu
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Abstract:

The lack of knowledge about the relationship between tumor genotypes and therapeutic responses remains one of the most important gaps in enabling the effective use of cancer therapies. Here, we couple a multiplexed and quantitative platform with robust statistical methods to enable pharmacogenomic mapping of lung cancer treatment responses in vivo. We uncover a surprisingly complex map of genotype-specific therapeutic responses, with over 20% of possible interactions showing significant resistance or sensitivity. We validate one of these interactions - the resistance of Keap1 mutant tumors to platinum therapy - using a large patient response dataset. Our results highlight the importance of understanding the genetic determinants of treatment responses in the development of precision therapies and define a strategy to identify such determinants.

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Posted January 29, 2020.
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Quantitative in vivo analyses reveal a complex pharmacogenomic landscape in lung adenocarcinoma
Chuan Li, Wen-Yang Lin, Hira Rizvi, Hongchen Cai, Christopher D. McFarland, Zoë N. Rogers, Maryam Yousefi, Ian P. Winters, Charles M. Rudin, Dmitri A. Petrov, Monte M. Winslow
bioRxiv 2020.01.28.923912; doi: https://doi.org/10.1101/2020.01.28.923912
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Quantitative in vivo analyses reveal a complex pharmacogenomic landscape in lung adenocarcinoma
Chuan Li, Wen-Yang Lin, Hira Rizvi, Hongchen Cai, Christopher D. McFarland, Zoë N. Rogers, Maryam Yousefi, Ian P. Winters, Charles M. Rudin, Dmitri A. Petrov, Monte M. Winslow
bioRxiv 2020.01.28.923912; doi: https://doi.org/10.1101/2020.01.28.923912

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