Dissemin is shutting down on January 1st, 2025

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Public Library of Science, PLoS ONE, 9(18), p. e0291942, 2023

DOI: 10.1371/journal.pone.0291942

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Investigation of evolutionary dynamics for drug resistance in 3D spheroid model system using cellular barcoding technology

Journal article published in 2023 by Gizem Damla Yalcin, Kubra Celikbas Yilmaz, Tugce Dilber, Ahmet Acar ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Complex evolutionary dynamics governing the drug resistance is one of the major challenges in cancer treatment. Understanding these mechanisms requires a sequencing technology with higher resolution to delineate whether pre-existing or de novo drug mechanisms are behind the drug resistance. Combining this technology with clinically very relevant model system, namely 3D spheroids, better mimicking tumorigenesis and drug resistance have so far been lacking. Thus, we sought to establish dabrafenib and irinotecan resistant derivatives of barcoded 3D spheroids with the ultimate aim to quantify the selection-induced clonal dynamics and identify the genomic determinants in this model system. We found that dabrafenib and irinotecan induced drug resistance in 3D-HT-29 and 3D-HCT-116 spheroids are mediated by pre-existing and de novo resistant barcodes, indicating the presence of polyclonal drug resistance in this system. Moreover, whole-exome sequencing analysis found chromosomal gains and mutations associated with dabrafenib and irinotecan resistance in 3D-HT-29 and 3D-HCT-116 spheroids. Last, we show that dabrafenib and irinotecan resistance are also mediated by multiple drug resistance by detection of upregulation of the drug efflux pumps, ABCB1 and ABCG2, in our spheroid model system. Overall, we present the quantification of drug resistance and evolutionary dynamics in spheroids for the first time using cellular barcoding technology and the underlying genomic determinants of the drug resistance in our model system.