Gene Signatures and Oncology Treatment Implications

Jessica Scarborough; Davis Weaver; Jacob Scott

doi:10.1016/j.hoc.2024.11.003

Gene Signatures and Oncology Treatment Implications

Hematol Oncol Clin North Am. 2024 Dec 17:S0889-8588(24)00148-5. doi: 10.1016/j.hoc.2024.11.003. Online ahead of print.

Authors

Jessica Scarborough¹, Davis Weaver², Jacob Scott³

Affiliations

¹ Department of Medicine, University of California San Francisco, 505 Parnassus Avenue, San Francisco, CA 94143, USA.
² Department of Translational Hematology and Oncology, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44195, USA; Systems Biology and Bioinformatics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA.
³ Department of Translational Hematology and Oncology, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44195, USA; Department of Molecular Medicine, School of Medicine, Systems Biology and Bioinformatics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA. Electronic address: scottj10@ccf.org.

PMID: 39694780
DOI: 10.1016/j.hoc.2024.11.003

Abstract

Gene expression signatures (GES) are a powerful tool in oncology used for classification, prognostication, and therapeutic response prediction of malignancies. In this article, we review the disease site guidelines by the National Comprehensive Cancer Network that use GES for treatment planning and clinical use. We identified 4 cancer types for which treatment decisions are frequently influenced by GES. Future developments in the field of GES are likely to include expanded data sources to personalize radiation therapy dosing and predict response to immunotherapy. Ongoing challenges in GES may be addressed to ensure that all patients with cancer benefit from precision oncology.

Keywords: Biomarker; Gene expression signature; Genomics; Multiomics; Predictive modeling; Therapeutic response prediction.

Publication types

Review