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
- Mirza Sheezan Baig
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