Unveiling Molecular Drivers of Triple-Negative Breast Cancer (TNBC): Computational Insights into Identification of Key Gene and Potential Novel Molecules

Introduction: Triple-negative breast cancer (TNBC), an aggressive and difficult- to-treat subtype with a grim outlook, relies heavily on chemotherapy due to the lack of molecular targets. In this study, we sought to uncover potential therapeutic targets by analysing differential gene expression between TNBC and normal breast tissue. Methods: Microarray data from the Gene Expression Omnibus (GEO) database was analysed to identify differentially expressed genes. It revealed 514 upregulated and 336 downregulated genes between TNBC and normal breast tissue. A subsequent proteinprotein interaction (PPI) network, visualized through Cytoscape, highlighted critical hub genes linked to the progression of TNBC. Survival analysis linked their overexpression to poor patient outcomes, underscoring it as a key driver of TNBC progression. Following the identification of genes, virtual screening and MMGBSA (Molecular Mechanics Generalized Born Surface Area) studies were conducted, which led to the identification of potential molecules that can target the protein. Results: Critical hub genes associated with TNBC progression were identified, and their overexpression was linked to poor survival outcomes. Virtual screening and MMGBSA studies led to the discovery of potential molecules targeting the identified protein. Conclusion: The findings of this study pave the way for further exploration for improving TNBC outcomes by targeting the key genes involved in TNBC progression and providing potential molecular targets for therapeutic intervention.

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Journal
Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine
Published
2025-03-26
DOI
https://doi.org/10.2174/0118756921361716250311084315
Primary Topic
Computational Drug Discovery Methods
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article
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article

Unveiling Molecular Drivers of Triple-Negative Breast Cancer (TNBC): Computational Insights into Identification of Key Gene and Potential Novel Molecules

M. Elizabeth Sobhia, Vaishnavi Chhabra, A. K. Sahoo
1 links
Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine
Computational Drug Discovery Methods
article

Unveiling Molecular Drivers of Triple-Negative Breast Cancer (TNBC): Computational Insights into Identification of Key Gene and Potential Novel Molecules

M. Elizabeth Sobhia, Vaishnavi Chhabra, A. K. Sahoo
article en

Abstract

Introduction: Triple-negative breast cancer (TNBC), an aggressive and difficult- to-treat subtype with a grim outlook, relies heavily on chemotherapy due to the lack of molecular targets. In this study, we sought to uncover potential therapeutic targets by analysing differential gene expression between TNBC and normal breast tissue. Methods: Microarray data from the Gene Expression Omnibus (GEO) database was analysed to identify differentially expressed genes. It revealed 514 upregulated and 336 downregulated genes between TNBC and normal breast tissue. A subsequent proteinprotein interaction (PPI) network, visualized through Cytoscape, highlighted critical hub genes linked to the progression of TNBC. Survival analysis linked their overexpression to poor patient outcomes, underscoring it as a key driver of TNBC progression. Following the identification of genes, virtual screening and MMGBSA (Molecular Mechanics Generalized Born Surface Area) studies were conducted, which led to the identification of potential molecules that can target the protein. Results: Critical hub genes associated with TNBC progression were identified, and their overexpression was linked to poor survival outcomes. Virtual screening and MMGBSA studies led to the discovery of potential molecules targeting the identified protein. Conclusion: The findings of this study pave the way for further exploration for improving TNBC outcomes by targeting the key genes involved in TNBC progression and providing potential molecular targets for therapeutic intervention.

Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicineVol. 22
National Institute of Pharmaceutical Education and Research (IN)
Openalex Percentile: Top 90%
Computational Drug Discovery Methods
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Unveiling Molecular Drivers of Triple-Negative Breast Cancer (TNBC): Computational Insights into Identification of Key Gene and Potential Novel Molecules — M. Elizabeth Sobhia, Vaishnavi Chhabra, et al. · Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine (2025) | TGRS Research Map | TGRS