Title

Elucidation of putative key genes involved in triple-negative breast cancer progression

Authors

Alok Kumar¹, Gauri Shankar Upadhyay¹, Mohammad Kashif², Md. Zubbair Malik², Naidu Subbarao² & Maitreyi S. Rajala^1,*

Affiliation

¹School of Biotechnology, Jawaharlal Nehru University, New Delhi, India; ²School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, India; *Corresponding author

Email

Alok Kumar - E-mail: iamaloklalchand@gmail.com
Gauri Shankar Upadhyay - E-mail: gsupadhyay060801@gmail.com
Mohammad Kashif - E-mail: kashifjmi.bioinfo@gmail.com
Md. Zubbair Malik - E-mail: zubair.bioinfo@gmail.com
Naidu Subbarao - E-mail: nsrao.jnu@gmail.com
Maitreyi S. Rajala - E-mail: msrajala@mail.jnu.ac.in

Article Type

Research Article

Date

Received August 1, 2026; Revised August 31, 2026; Accepted August 31, 2026, Published August 31, 2026

Abstract

The molecular basis of TNBC development is poorly understood. Therefore, it is of interest to identify key genes and pathways involved in TNBC development and progression using a systems biology approach, followed by experimental validation. Gene ontology and KEGG enrichment analyses were performed to identify DEG-regulated biological functions and pathways; a PPI network was constructed using the STRING online database. The expression and prognostic value of the hub genes were validated by TCGA survival analysis, resulting in the identification of 727 DEGs (473 downregulated and 254 upregulated) in TNBC samples. The GO and KEGG analyses indicated that the DEGs were mainly related to cell adhesion and tumorigenesis and the PPI network showed six hub genes: CCND1, CDH1, ESR1, FN1, IL6 and PPARG as the top key genes. These were validated by real-time PCR in the TNBC cell line using a non-TNBC cell line as a calibrator and the obtained results were in accordance with the bioinformatics data.

Keywords

Triple negative breast cancer (TNBC), non-TNBC, systems biology, Kyoto Encyclopaedia of genes and genomes (KEGG) analysis, expression profiling, QPCR

Citation

Kumar et al. Bioinformation 22(8): 4781-4786 (2026)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.