ArticleJournal of biological research (Thessalonike, Greece)2021
Genome-scale meta-analysis of breast cancer datasets identifies promising targets for drug development.
Article in Journal of biological research (Thessalonike, Greece), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- A meta-analysis of genome-wide gene expression differences identifies promising targets for type 2 diabetes mellitus.Frontiers in endocrinology · 2022Pooled it
- Identification and validation of differentially expressed genes for targeted therapy in NSCLC using integrated bioinformatics analysis.Frontiers in oncology · 2023Article
- Cytotoxic Evaluation, Molecular Docking, and 2D-QSAR Studies of Dihydropyrimidinone Derivatives as Potential Anticancer Agents.Journal of oncology · 2022Article
- Investigation of anti-diabetic potential and molecular simulation studies of dihydropyrimidinone derivatives.Frontiers in endocrinology · 2022Article
- Virtual screening and drug repositioning of FDA-approved drugs from the ZINC database to identify the potential hTERT inhibitors.Frontiers in pharmacology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBecause of the highly heterogeneous nature of breast cancer, each subtype differs in response to several treatment regimens. This has limited the therapeutic options for metastatic breast cancer disease requiring exploration of diverse therapeutic models to target tumor specific biomarkers.
methodsDifferentially expressed breast cancer genes identified through extensive data mapping were studied for their interaction with other target proteins involved in breast cancer progression. The molecular mechanisms by which these signature genes are involved in breast cancer metastasis were also studied through pathway analysis. The potential drug targets for these genes were also identified.
resultsFrom 50 DEGs, 20 genes were identified based on fold change and p-value and the data curation of these genes helped in shortlisting 8 potential gene signatures that can be used as potential candidates for breast cancer. Their network and pathway analysis clarified the role of these genes in breast cancer and their interaction with other signaling pathways involved in the progression of disease metastasis. The miRNA targets identified through miRDB predictor provided potential miRNA targets for these genes that can be involved in breast cancer progression. Several FDA approved drug targets were identified for the signature genes easing the therapeutic options for breast cancer treatment.
conclusionThe study provides a more clarified role of signature genes, their interaction with other genes as well as signaling pathways. The miRNA prediction and the potential drugs identified will aid in assessing the role of these targets in breast cancer.
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