Developing quantitative experimental model systems to study drug resistance

Date

2021-10-05

Author

Danisik, Nurseda
Baygin, Rana Can
Temena, Mehmet Arda
Acar, Ahmet

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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It is widely known that secondary resistance inevitably leads to treatment failure through Darwinian evolution. Therefore, quantifying the clonal evolution using experimental model systems can hold a great promise in designing evolutionarily informed therapies, and thus, in predicting drug response. In this talk, I present our recently developed strategy that contributed to the understanding of collateral drug sensitivity with its direct link to clonal evolution to overcome the drug resistance in non-small cell lung cancer cell line model system. Additionally, I also present a similar approach that has been developed to delineate chemotherapy induced clonal alterations in colorectal cancer cell line model systems. More specifically, high-complexity cellular barcoding allowed us the identification of the resistance that was ultimately driven by the presence and emergence of multiple pre-existing and de novo resistant clones, respectively. Overall, our work highlights evolutionary tradeoffs and provides an opportunity to exploit the tumour vulnerability.

URI

https://hdl.handle.net/11511/93991

DOI

https://doi.org/10.35407/bag.2021.32.01.suppl.02

Conference Name

XVIII Latin American Congress of Genetics

Collections

Department of Biology, Conference / Seminar

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Citation Formats

N. Danisik, R. C. Baygin, M. A. Temena, and A. Acar, “Developing quantitative experimental model systems to study drug resistance,” presented at the XVIII Latin American Congress of Genetics, 2021, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/93991.