"A Systematic Review of Datasets that Can Help Elucidate Relationships " by Ifeanyichukwu O. Nwosu and Stephen Piccolo
 

Keywords

Breast cancer, gene-expression profiling, race, immunohistochemistry status, disease subtypes, triple negative breast cancer, health disparities

Abstract

Scholarly requirements have led to a massive increase of transcriptomic data in the public domain, with millions of samples available for secondary research. We identified gene-expression datasets representing 10,214 breast-cancer patients in public databases. We focused on datasets that included patient metadata on race and/or immunohistochemistry (IHC) profiling of the ER, PR, and HER-2 proteins. This review provides a summary of these datasets and describes findings from 32 research articles associated with the datasets. These studies have helped to elucidate relationships between IHC, race, and/or treatment options, as well as relationships between IHC status and the breast-cancer intrinsic subtypes. We have also identified broad themes across the analysis methodologies used in these studies, including breast cancer subtyping, deriving predictive biomarkers, identifying differentially expressed genes, and optimizing data processing. Finally, we discuss limitations of prior work and recommend future directions for reusing these datasets in secondary analyses.

Original Publication Citation

Ifeanyichukwu O. Nwosu & Stephen R. Piccolo (2021) A systematic review of datasets that can help elucidate relationships among gene expression, race, and immunohistochemistry-defined subtypes in breast cancer, Cancer Biology & Therapy, 22:7-9, 417-429, DOI: 10.1080/15384047.2021.1953902

Document Type

Peer-Reviewed Article

Publication Date

2021-08-19

Publisher

Taylor & Francis

Language

English

College

Life Sciences

Department

Biology

University Standing at Time of Publication

Associate Professor

Plum Print visual indicator of research metrics
PlumX Metrics
  • Citations
    • Citation Indexes: 2
  • Usage
    • Downloads: 3
  • Captures
    • Readers: 11
see details

Share

COinS