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Drug-Adapted Cancer Cell Lines as Preclinical Models of Acquired Resistance

Michaelis, Martin, Wass, Mark N., Cinatl, Jindrich (2019) Drug-Adapted Cancer Cell Lines as Preclinical Models of Acquired Resistance. Cancer Drug Resistance, . ISSN 2578-532X. (doi:10.20517/cdr.2019.005)

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https://doi.org/10.20517/cdr.2019.005

Abstract

Acquired resistance formation limits the efficacy of anti-cancer therapies. Acquired and intrinsic resistance differ conceptually. Acquired resistance is the consequence of directed evolution, whereas intrinsic resistance depends on the (stochastic) presence of pre-existing resistance mechanisms. Preclinical model systems are needed to study acquired drug resistance because they enable: (1) in depth functional studies; (2) the investigation of non-standard treatments for a certain disease condition (which is necessary to identify small groups of responders); and (3) the comparison of multiple therapies in the same system. Hence, they complement data derived from clinical trials and clinical specimens, including liquid biopsies. Many groups have successfully used drug-adapted cancer cell lines to identify and elucidate clinically relevant resistance mechanisms to targeted and cytotoxic anti-cancer drugs. Hence, we argue that drug-adapted cancer cell lines represent a preclinical model system in their own right that is complementary to other preclinical model systems and clinical data.

Item Type: Article
DOI/Identification number: 10.20517/cdr.2019.005
Uncontrolled keywords: Cancer, acquired drug resistance, cancer cell lines, drug adaptation, cancer therapy, cancer models
Subjects: R Medicine > RM Therapeutics. Pharmacology
Divisions: Faculties > Sciences > School of Biosciences
Depositing User: Martin Michaelis
Date Deposited: 04 Sep 2019 09:11 UTC
Last Modified: 05 Sep 2019 11:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/76175 (The current URI for this page, for reference purposes)
Michaelis, Martin: https://orcid.org/0000-0002-5710-5888
Wass, Mark N.: https://orcid.org/0000-0001-5428-6479
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