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Predicting Cellular Drug Sensitivity using Conditional Modulation of Gene Expression

View ORCID ProfileWill Connell, View ORCID ProfileMichael Keiser
doi: https://doi.org/10.1101/2021.03.15.435529
Will Connell
1Department of Pharmaceutical Chemistry Institute for Neurodegenerative Diseases University of California, San Francisco San Francisco, CA 94143
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  • For correspondence: connell@keiserlab.org
Michael Keiser
2Department of Pharmaceutical Chemistry Institute for Neurodegenerative Diseases University of California, San Francisco San Francisco, CA 94143
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  • For correspondence: keiser@keiserlab.org keiser@keiserlab.org
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Abstract

Selecting drugs most effective against a tumor’s specific transcriptional signature is an important challenge in precision medicine. To assess oncogenic therapy options, cancer cell lines are dosed with drugs that can differentially impact cellular viability. Here we show that basal gene expression patterns can be conditioned by learned small molecule structure to better predict cellular drug sensitivity, achieving an R2 of 0.7190±0.0098 (a 5.61% gain). We find that 1) transforming gene expression values by learned small molecule representations outperforms raw feature concatenation, 2) small molecule structural features meaningfully contribute to learned representations, and 3) an affine transformation best integrates these representations. We analyze conditioning parameters to determine how small molecule representations modulate gene expression embeddings. This ongoing work formalizes in silico cellular screening as a conditional task in precision oncology applications that can improve drug selection for cancer treatment.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/keiserlab/film-gex

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 16, 2021.
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Predicting Cellular Drug Sensitivity using Conditional Modulation of Gene Expression
Will Connell, Michael Keiser
bioRxiv 2021.03.15.435529; doi: https://doi.org/10.1101/2021.03.15.435529
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Predicting Cellular Drug Sensitivity using Conditional Modulation of Gene Expression
Will Connell, Michael Keiser
bioRxiv 2021.03.15.435529; doi: https://doi.org/10.1101/2021.03.15.435529

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