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Disrupting cellular memory to overcome drug resistance

Harmange, Guillaume and Reyes Hueros, Raúl A. and Schaff, Dylan and Emert, Benjamin and Saint-Antoine, Michael and Nellore, Shivani and Fane, Mitchell E. and Alicea, Gretchen M. and Weeraratna, Ashani T. and Singh, Abhyudai and Shaffer, Sydney M. (2022) Disrupting cellular memory to overcome drug resistance. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20220706-964795000

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Abstract

Plasticity enables cells to change their gene expression state in the absence of a genetic change. At the single-cell level, these gene expression states can persist for different lengths of time which is a quantitative measurement referred to as gene expression memory. Because plasticity is not encoded by genetic changes, these cell states can be reversible, and therefore, are amenable to modulation by disrupting gene expression memory. However, we currently do not have robust methods to find the regulators of memory or to track state switching in plastic cell populations. Here, we developed a lineage tracing-based technique to quantify gene expression memory and to identify single cells as they undergo cell state transitions. Applied to human melanoma cells, we quantified long-lived fluctuations in gene expression that underlie resistance to targeted therapy. Further, we identified the PI3K and TGF-β pathways as modulators of these state dynamics. Applying the gene expression signatures derived from this technique, we find that these expression states are generalizable to in vivo models and present in scRNA-seq from patient tumors. Leveraging the PI3K and TGF-β pathways as dials on memory between plastic states, we propose a “ pretreatment” model in which we first use a PI3K inhibitor to modulate the expression states of the cell population and then apply targeted therapy. This plasticity informed dosing scheme ultimately yields fewer resistant colonies than targeted therapy alone. Taken together, we describe a technique to find modulators of gene expression memory and then apply this knowledge to alter plastic cell states and their connected cell fates.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/2022.06.16.496161DOIDiscussion Paper
https://www.biorxiv.org/content/10.1101/2022.06.16.496161v3.supplementary-materialPublisherSupplementary Material
https://drive.google.com/drive/folders/1-C78090Z43w5kGb1ZW8pXgysjha35jlU?usp=sharingRelated ItemData/Code
ORCID:
AuthorORCID
Harmange, Guillaume0000-0002-3157-5355
Reyes Hueros, Raúl A.0000-0001-7554-051X
Schaff, Dylan0000-0002-3367-9270
Emert, Benjamin0000-0002-4857-2425
Fane, Mitchell E.0000-0001-6163-5753
Alicea, Gretchen M.0000-0001-8436-2890
Weeraratna, Ashani T.0000-0003-0448-6952
Singh, Abhyudai0000-0002-1451-2838
Shaffer, Sydney M.0000-0003-3539-9886
Additional Information: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 4.0 International license. Version 1 - June 17, 2022. Version 2 - August 4, 2022. Version 3 - August 5, 2022. We thank all members of the Shaffer lab for feedback on experiments and the manuscript, P. Gonzalez-Camara and T. Ridky for thoughtful discussions and ideas, W. Niu for help on developing image processing pipelines, L. Bugaj for feedback on the manuscript, and M. Herlyn for providing cell lines. S.M.S. acknowledges support from the NIH Director’s Early Independence Award DP5OD028144 and the Wistar/Penn Skin Cancer SPORE (P50 CA174523). A.S. acknowledges support from R01GM124446. A.T.W. acknowledges support from R01CA207935 and P01CA114046. Software and data availability: All data and code used for this paper can be found here: https://drive.google.com/drive/folders/1-C78090Z43w5kGb1ZW8pXgysjha35jlU?usp=sharing. Author Contributions: G.H. and S.M.S. conceptualized the project and designed the study. G.H. performed all experiments and analysis with the following exceptions. R.A.R.H. helped with the barcode processing pipeline and provided helpful discussion. D.S. performed the ATAC sequencing experiment and its analysis, and helped with the barcode processing pipeline. M.S. and A.S performed the modeling analysis. B.E. provided technical guidance and troubleshooting for the barcoding library. A.T.W, M.E.F, and G.M.A generated the mouse PDX tissue. S.N. helped maintain cell lines and performed computational analyses. G.H. and S.M.S. wrote the paper. Competing interests: S.M.S. receive royalties related to Stellaris RNA FISH probes. All other authors have no competing interests to declare.
Funders:
Funding AgencyGrant Number
NIHDP5OD028144
NIHP50 CA174523
NIHR01GM124446
NIHR01CA207935
NIHP01CA114046
DOI:10.1101/2022.06.16.496161
Record Number:CaltechAUTHORS:20220706-964795000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220706-964795000
Official Citation:Disrupting cellular memory to overcome drug resistance. Guillaume Harmange, Raúl A. Reyes Hueros, Dylan Schaff, Benjamin Emert, Michael Saint-Antoine, Shivani Nellore, Mitchell E. Fane, Gretchen M. Alicea, Ashani T. Weeraratna, Abhyudai Singh, Sydney M. Shaffer. bioRxiv 2022.06.16.496161; doi: https://doi.org/10.1101/2022.06.16.496161
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:115347
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:08 Jul 2022 22:29
Last Modified:16 Aug 2022 22:55

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