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Tumor heterogeneity: how could we use it to achieve better clinical outcomes?

  • Arsani Yousef , Lucianna Ghobrial and Eleftherios P. Diamandis ORCID logo EMAIL logo
Published/Copyright: October 12, 2023

Abstract

Differences in tumors related to location, tissue type, and histological subtype have been well documented for decades. Tumors are also molecularly very diverse. In this short review we describe the current classification schemes for tumor heterogeneity. We enlist the various drivers of tumor heterogeneity generation and comment on their clinical significance. New molecular techniques promise to assess tumor heterogeneity at affordable cost, so that these techniques can soon enter the clinic. While tumor heterogeneity currently represents a major unfavorable barrier in the field of oncology, it may also be a key in revolutionizing cancer diagnosis and treatment. Information regarding tumor heterogeneity has the potential to provide more thorough prognostic information, guide more efficacious combination treatment regimens, and lead to the development of novel therapeutic strategies and identification of new targets. For these gains to be realized, assessment of tumor heterogeneity needs to be incorporated into current diagnostic protocols but standardized and reproducible assessment methods are required. Fortunately, when these advances are realized, tumor heterogeneity has the potential to improve clinical outcomes.


Corresponding author: Eleftherios P. Diamandis, MD, PhD, FRCP(C), FRSC, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, 60 Murray St. Box 32, Floor 6, Rm L6-201, Toronto, ON, M5T 3L9, Canada, Phone: (416) 586 8443, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Competing interests: Eleftherios Diamandis holds an advisory and consultation role with Abbott Diagnostics. All other authors state no conflict of interest.

  5. Research funding: None declared.

  6. Data availability: Not applicable.

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Received: 2023-08-16
Accepted: 2023-09-17
Published Online: 2023-10-12

© 2023 Walter de Gruyter GmbH, Berlin/Boston

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