BCAT2 Expression in IDC Breast Cancer subtypes: A Weighted Feature-Based Approach to Identify and Rank Associated Genes Across Public Datasets

Document Type

Conference Proceeding

Source of Publication

2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

Publication Date

7-19-2024

Abstract

It has been observed that breast cancer is associated with dysregulation of several metabolic pathways that produce metabolite addiction, such as the dependence on glutamine for tumor development. These discoveries might be applied to personalized treatment of this heterogeneous illness by employing specific gene expression or metabolites in cancer therapy. BCAT1 and BCAT2 encode the human branched-chain aminotransferase proteins (hBCAT) involved in cellular metabolism process. Here BCAT2 is exploited through weighted feature-based approach to identify and rank associated genes across public datasets of breast cancer invasive ductal carcinoma patients. BCAT2 lower expression was observed to have the worst prognosis, and BCAT2 gene expression which might be associated with triggering the risk, are ranked, and visualized in different subtypes of breast cancer. These findings give a strong clue to further investigate through experimental approach.

ISBN

979-8-3503-7149-9

Publisher

IEEE

Volume

00

First Page

1

Last Page

4

Disciplines

Computer Sciences | Medicine and Health Sciences

Keywords

BCAT2, Breast cancer, Gene expression, Metabolite addiction, Prognosis

Indexed in Scopus

no

Open Access

no

Link to Full Text

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