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The causes and consequences of genetic heterogeneity in cancer evolution

Author

Listed:
  • Rebecca A. Burrell

    (Translational Cancer Therapeutics Laboratory, Cancer Research UK London Research Institute)

  • Nicholas McGranahan

    (Translational Cancer Therapeutics Laboratory, Cancer Research UK London Research Institute
    Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX), University College London)

  • Jiri Bartek

    (Danish Cancer Society Research Center
    Institute of Molecular and Translational Medicine, Palacky University)

  • Charles Swanton

    (Translational Cancer Therapeutics Laboratory, Cancer Research UK London Research Institute
    UCL Cancer Institute, Paul O'Gorman Building)

Abstract

Recent studies have revealed extensive genetic diversity both between and within tumours. This heterogeneity affects key cancer pathways, driving phenotypic variation, and poses a significant challenge to personalized cancer medicine. A major cause of genetic heterogeneity in cancer is genomic instability. This instability leads to an increased mutation rate and can shape the evolution of the cancer genome through a plethora of mechanisms. By understanding these mechanisms we can gain insight into the common pathways of tumour evolution that could support the development of future therapeutic strategies.

Suggested Citation

  • Rebecca A. Burrell & Nicholas McGranahan & Jiri Bartek & Charles Swanton, 2013. "The causes and consequences of genetic heterogeneity in cancer evolution," Nature, Nature, vol. 501(7467), pages 338-345, September.
    • Handle: RePEc:nat:nature:v:501:y:2013:i:7467:d:10.1038_nature12625
    DOI: 10.1038/nature12625
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    Cited by:

    1. Shen Zhao & De-Pin Chen & Tong Fu & Jing-Cheng Yang & Ding Ma & Xiu-Zhi Zhu & Xiang-Xue Wang & Yi-Ping Jiao & Xi Jin & Yi Xiao & Wen-Xuan Xiao & Hu-Yunlong Zhang & Hong Lv & Anant Madabhushi & Wen-Tao, 2023. "Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    2. Li Chen & Peter L Choyke & Niya Wang & Robert Clarke & Zaver M Bhujwalla & Elizabeth M C Hillman & Ge Wang & Yue Wang, 2014. "Unsupervised Deconvolution of Dynamic Imaging Reveals Intratumor Vascular Heterogeneity and Repopulation Dynamics," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
    3. Lianfeng Shan & Ming Li & Jianzhong Ma & Huidan Zhang, 2014. "PCR-Based Assays versus Direct Sequencing for Evaluating the Effect of KRAS Status on Anti-EGFR Treatment Response in Colorectal Cancer Patients: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-7, September.
    4. Humberto Contreras-Trujillo & Jiya Eerdeng & Samir Akre & Du Jiang & Jorge Contreras & Basia Gala & Mary C. Vergel-Rodriguez & Yeachan Lee & Aparna Jorapur & Areen Andreasian & Lisa Harton & Charles S, 2021. "Deciphering intratumoral heterogeneity using integrated clonal tracking and single-cell transcriptome analyses," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    5. Duncan Ingram & Guy-Bart Stan, 2023. "Modelling genetic stability in engineered cell populations," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    6. Nick Henscheid & Eric Clarkson & Kyle J Myers & Harrison H Barrett, 2018. "Physiological random processes in precision cancer therapy," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-25, June.
    7. Richard Newton & Lorenz Wernisch, 2019. "A meta-analysis of multiple matched aCGH/expression cancer datasets reveals regulatory relationships and pathway enrichment of potential oncogenes," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-28, July.
    8. Gunnarsson, Einar Bjarki & Leder, Kevin & Foo, Jasmine, 2021. "Exact site frequency spectra of neutrally evolving tumors: A transition between power laws reveals a signature of cell viability," Theoretical Population Biology, Elsevier, vol. 142(C), pages 67-90.
    9. Jacob C Kimmel & Amy Y Chang & Andrew S Brack & Wallace F Marshall, 2018. "Inferring cell state by quantitative motility analysis reveals a dynamic state system and broken detailed balance," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-29, January.
    10. Shiqian Ma & Daniel Johnson & Cody Ashby & Donghai Xiong & Carole L Cramer & Jason H Moore & Shuzhong Zhang & Xiuzhen Huang, 2015. "SPARCoC: A New Framework for Molecular Pattern Discovery and Cancer Gene Identification," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-19, March.
    11. Marion Porcherie & Nyan Linn & Anne Roué Le Gall & Marie-Florence Thomas & Emmanuelle Faure & Stéphane Rican & Jean Simos & Nicola Cantoreggi & Zoé Vaillant & Linda Cambon & Jean-Philippe Regnaux, 2021. "Relationship between Urban Green Spaces and Cancer: A Scoping Review," IJERPH, MDPI, vol. 18(4), pages 1-19, February.

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