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Cited by 417

The DOI matches its Crossref record; 115 of the 115 references it cites were found in a registry or an index.

Tumour heterogeneity and the evolution of polyclonal drug resistance

Open access
Burrell, Rebecca A., Swanton, Charles·2014·Molecular Oncology

Abstract

Cancer drug resistance is a major problem, with the majority of patients with metastatic disease ultimately developing multidrug resistance and succumbing to their disease. Our understanding of molecular events underpinning treatment failure has been enhanced by new genomic technologies and pre‐clinical studies. Intratumour genetic heterogeneity (ITH) is a prominent contributor to therapeutic failure, and it is becoming increasingly apparent that individual tumours may achieve resistance via multiple routes simultaneously – termed polyclonal resistance. Efforts to target single resistance mechanisms to overcome therapeutic failure may therefore yield only limited success. Clinical studies with sequential analysis of tumour material are needed to enhance our understanding of inter‐clonal functional relationships and tumour evolution during therapy, and to improve drug development strategies in cancer medicine.

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Crossref · 10.1016/j.molonc.2014.06.005

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Metadata

Authors
Burrell, R. A., & Swanton, C.
Venue
Molecular Oncology
Publisher
Wiley
Published
2014-07-10
Volume
8
Issue
6
Pages
1095-1111
ISSN
  • 1574-7891 (ISSN-L)
  • 1878-0261
OpenAlex
W2125974203
Cited by
417
References
115
FWCI
12.44
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Tumour heterogeneity and the evolution of polyclonal drug resistance. https://app.cochat.ai/papers/10.1016/j.molonc.2014.06.005
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Burrell, R. A., & Swanton, C. (2014). Tumour heterogeneity and the evolution of polyclonal drug resistance. Molecular Oncology. https://doi.org/10.1016/j.molonc.2014.06.005

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.