Signature-Reversal Drug Repurposing for Triple-Negative Breast Cancer: A Multi-Database Computational Screen Using TCGA, Connectivity Map and DepMap

I conducted an independent computational research project on drug repurposing for triple-negative breast cancer (TNBC), using public datasets from TCGA, Connectivity Map (CMap), and DepMap. The study analysed gene-expression patterns in tumour and normal breast tissue, identified potential drug candidates through signature reversal, and compared their sensitivity across TNBC, luminal, and HER2-positive breast cancer cell lines. The results highlighted trametinib as a possible candidate for further investigation, although no drug showed statistically significant TNBC-selective activity. This preliminary study demonstrates how computational biology and publicly available data can help generate research hypotheses for future experimental validation.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-31
DOI
https://doi.org/10.5281/zenodo.23830290
Primary Topic
Computational Drug Discovery Methods
Type
preprint
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preprint

Signature-Reversal Drug Repurposing for Triple-Negative Breast Cancer: A Multi-Database Computational Screen Using TCGA, Connectivity Map and DepMap

Mirza Sheezan Baig
Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
preprint

Signature-Reversal Drug Repurposing for Triple-Negative Breast Cancer: A Multi-Database Computational Screen Using TCGA, Connectivity Map and DepMap

Mirza Sheezan Baig
preprint en

Abstract

I conducted an independent computational research project on drug repurposing for triple-negative breast cancer (TNBC), using public datasets from TCGA, Connectivity Map (CMap), and DepMap. The study analysed gene-expression patterns in tumour and normal breast tissue, identified potential drug candidates through signature reversal, and compared their sensitivity across TNBC, luminal, and HER2-positive breast cancer cell lines. The results highlighted trametinib as a possible candidate for further investigation, although no drug showed statistically significant TNBC-selective activity. This preliminary study demonstrates how computational biology and publicly available data can help generate research hypotheses for future experimental validation.

Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
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