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Heterogeneity within molecular subtypes of breast cancer

期刊

AMERICAN JOURNAL OF PHYSIOLOGY-CELL PHYSIOLOGY
卷 321, 期 2, 页码 C343-C354

出版社

AMER PHYSIOLOGICAL SOC
DOI: 10.1152/ajpcell.00109.2021

关键词

cell-state heterogeneity; dynamic interconversion; hierarchical heterogeneity; intratumoral heterogeneity; plasticity

资金

  1. National Institutes of Health (NIH) [R01 CA211066, R01 HL073394, R01 NS094144]

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Breast cancer exemplifies how molecular characterization influences therapeutic decisions. The compartmentalization of breast cancer into diverse subtypes is well-documented, but intratumoral heterogeneity, driven by both intrinsic and extrinsic factors, complicates this model. Evidence suggests that intratumoral molecular subtypes are dynamic and interconversion between subtypes contributes to tumor progression, metastases, and treatment resistance. Therapeutic strategies need to address this heterogeneity to improve treatment outcomes.
Breast cancer is the quintessential example of how molecular characterization of tumor biology guides therapeutic decisions. From the discovery of the estrogen receptor to current clinical molecular profiles to evolving single-cell analytics, the characterization and compartmentalization of breast cancer into divergent subtypes is clear. However, competing with this divergent model of breast cancer is the recognition of intratumoral heterogeneity, which acknowledges the possibility that multiple different subtypes exist within a single tumor. Intratumoral heterogeneity is driven by both intrinsic effects of the tumor cells them-selves as well as extrinsic effects from the surrounding microenvironment. There is emerging evidence that these intratumoral molecular subtypes are not static; rather, plasticity between divergent subtypes is possible. Interconversion between seemingly different subtypes within a tumor drives tumor progression, metastases, and treatment resistance. Therapeutic strategies must, therefore, contend with changing phenotypes in an individual patient's tumor. Identifying targetable drivers of molecular hetero-geneity may improve treatment durability and disease progression.

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