Drug Repositioning of Cardiac Steroids as Potential Agents for the Treatment of Triple‑Negative Breast Cancer.

Authors

Sara A Al-Shun, Magdy M Youssef, Farid A Badria

Published in

Anti-cancer agents in medicinal chemistry. Sep 30, 2026. Epub Sep 30, 2026.

Abstract

Triple-Negative Breast Cancer (TNBC) lacks targeted therapies and is mainly treated with chemotherapeutics limited by toxicity and resistance. This study aims to identify and characterize cardiac steroids as potential anti-TNBC leads using phenotypic screening, drug-likeness evaluation, and in silico targetprofiling.
A panel of natural products was screened against TNBC MDA-MB-231 cells using MTT assay and compared with conventional chemotherapeutics; selectivity indices were calculated using WI-38 fibroblasts. SwissADME was used to predict physiochemical and pharmacokinetic properties. Putative targets of the top hit were predicted, intersected with breast-cancer-associated genes, and subjected to Protein-Protein Interaction (PPI) and enrichment analyses to identify hub targets. VEGFA was selected for Molecular Docking and (MD) molecular dynamics simulations with digitoxigenin.
The cardiac steroids digitoxin, digitoxigenin, and ouabain exhibited the greatest potency with lownanomolar IC₂⁽ values that markedly surpassed those of cisplatin, doxorubicin, and sorafenib. Digitoxigenin displayed the most favorable selectivity (SI = 4.2). SwissADME favored digitoxigenin over digitoxin with no Lipinski violations. Target-profiling highlighted angiogenesis- and signaling-related hub proteins, including VEGFA. Molecular docking and MD simulations suggested a stable digitoxigenin-VEGFA complex.
These data support digitoxigenin as a prioritized cardiac steroid scaffold that combines potent in vitro cytotoxicity with improved selectivity and a more favorable drug-likeness profile than digitoxin, while the in silico analyses provide a mechanistic hypothesis centered on angiogenesis and survival signaling.
Digitoxigenin emerges as a promising anti-TNBC lead. The in silico analyses generate mechanistic hypotheses that warrant future biochemical validation and in vivo efficacy and cardiotoxicity studies in TNBC models.

PMID:
42852749
Bibliographic data and abstract were imported from PubMed on 09 Oct 2026.

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