» Articles » PMID: 24681298

Evolution of Acquired Resistance to Anti-cancer Therapy

Overview
Journal J Theor Biol
Publisher Elsevier
Specialty Biology
Date 2014 Apr 1
PMID 24681298
Citations 115
Authors
Affiliations
Soon will be listed here.
Abstract

Acquired drug resistance is a major limitation for the successful treatment of cancer. Resistance can emerge due to a variety of reasons including host environmental factors as well as genetic or epigenetic alterations in the cancer cells. Evolutionary theory has contributed to the understanding of the dynamics of resistance mutations in a cancer cell population, the risk of resistance pre-existing before the initiation of therapy, the composition of drug cocktails necessary to prevent the emergence of resistance, and optimum drug administration schedules for patient populations at risk of evolving acquired resistance. Here we review recent advances towards elucidating the evolutionary dynamics of acquired drug resistance and outline how evolutionary thinking can contribute to outstanding questions in the field.

Citing Articles

TNBC response to paclitaxel phenocopies interferon response which reveals cell cycle-associated resistance mechanisms.

Calistri N, Liby T, Hu Z, Zhang H, Dane M, Gross S Sci Rep. 2025; 15(1):4294.

PMID: 39905117 PMC: 11794704. DOI: 10.1038/s41598-024-82218-9.


Multilevel Mechanisms of Cancer Drug Resistance.

Roszkowska M Int J Mol Sci. 2024; 25(22).

PMID: 39596466 PMC: 11594576. DOI: 10.3390/ijms252212402.


High-density sampling reveals volume growth in human tumours.

Angaji A, Owusu M, Velling C, Dick N, Weghorn D, Berg J Elife. 2024; 13.

PMID: 39587846 PMC: 11594531. DOI: 10.7554/eLife.95338.


Exploring Genetic Silencing: RNAi and CRISPR-Cas Potential against Drug Resistance in Malaria.

Gaona-Lopez C, Rivera G Mini Rev Med Chem. 2024; 25(2):128-137.

PMID: 38932611 DOI: 10.2174/0113895575306957240610102626.


TNBC response to paclitaxel phenocopies interferon response which reveals cell cycle-associated resistance mechanisms.

Calistri N, Liby T, Hu Z, Zhang H, Dane M, Gross S bioRxiv. 2024; .

PMID: 38895265 PMC: 11185620. DOI: 10.1101/2024.06.04.596911.


References
1.
Sarkar S, Ma W, Sandri G . On fluctuation analysis: a new, simple and efficient method for computing the expected number of mutants. Genetica. 1992; 85(2):173-9. DOI: 10.1007/BF00120324. View

2.
Martin R, Fisher M, Minchin R, Teo K . Optimal control of tumor size used to maximize survival time when cells are resistant to chemotherapy. Math Biosci. 1992; 110(2):201-19. DOI: 10.1016/0025-5564(92)90038-x. View

3.
Tredan O, Galmarini C, Patel K, Tannock I . Drug resistance and the solid tumor microenvironment. J Natl Cancer Inst. 2007; 99(19):1441-54. DOI: 10.1093/jnci/djm135. View

4.
Orr H . The distribution of fitness effects among beneficial mutations. Genetics. 2003; 163(4):1519-26. PMC: 1462510. DOI: 10.1093/genetics/163.4.1519. View

5.
Gorre M, Mohammed M, Ellwood K, Hsu N, Paquette R, Rao P . Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification. Science. 2001; 293(5531):876-80. DOI: 10.1126/science.1062538. View