Esophageal cancer (EC) remains a significant challenge globally, having the 8th highest incidence and 6th highest mortality worldwide. Esophageal squamous cell carcinoma (ESCC) is the most common form of EC in Asia. Crucially, more than 90% of EC cases in China are ESCC. The high mortality rate of EC is likely due to the limited number of effective therapeutic options. To increase patient survival, novel therapeutic strategies for EC patients must be devised. Unfortunately, the development of novel drugs also presents its own significant challenges as most novel drugs do not make it to market due to lack of efficacy or safety concerns. A more time and cost-effective strategy is to identify existing drugs, that have already been approved for treatment of other diseases, which can be repurposed to treat EC patients, with drug repositioning. This can be achieved by comparing the gene expression profiles of disease-states with the effect on gene-expression by a given drug. In our analysis, we used previously published microarray data and identified 167 differentially expressed genes (DEGs). Using weighted key driver analysis, 39 key driver genes were then identified. These driver genes were then used in Overlap Analysis and Network Analysis in Pharmomics. By extracting drugs common to both analyses, 24 drugs are predicted to demonstrate therapeutic effect in EC patients. Several of which have already been shown to demonstrate a therapeutic effect in EC, most notably Doxorubicin, which is commonly used to treat EC patients, and Ixazomib, which was recently shown to induce apoptosis and supress growth of EC cell lines. Additionally, our analysis predicts multiple psychiatric drugs, including Venlafaxine, as repositioned drugs. This is in line with recent research which suggests that psychiatric drugs should be investigated for use in gastrointestinal cancers such as EC. Our study shows that a drug repositioning approach is a feasible strategy for identifying novel ESCC therapies and can also improve the understanding of the mechanisms underlying the drug targets.
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http://dx.doi.org/10.3389/fgene.2022.991842 | DOI Listing |
Comput Biol Med
January 2025
Department of Orthopedics, Affiliated Huzhou Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Huzhou, China; Department of Sports Medicine & Orthopedic Surgery, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Institute of sports medicine, Zhejiang University, Hangzhou, China; Orthopedics Research Institute of Zhejiang University, Hangzhou, China; Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou, China; Clinical Research Center of Motor System Disease of Zhejiang Province, Hangzhou, China. Electronic address:
Background: Effective drugs for tendinopathy are lacking, resulting in significant morbidity and re-tearing rate after operation. Applying systems biology to identify new applications for current pharmaceuticals can decrease the duration, expenses, and likelihood of failure associated with the development of new drugs.
Methods: We identify tendinopathy signature genes employing a transcriptomics database encompassing 154 clinical tendon samples.
Sci Rep
January 2025
State Key Laboratory of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China.
Tyrosine-protein kinase Src plays a key role in cell proliferation and growth under favorable conditions, but its overexpression and genetic mutations can lead to the progression of various inflammatory diseases. Due to the specificity and selectivity problems of previously discovered inhibitors like dasatinib and bosutinib, we employed an integrated machine learning and structure-based drug repurposing strategy to find novel, targeted, and non-toxic Src kinase inhibitors. Different machine learning models including random forest (RF), k-nearest neighbors (K-NN), decision tree, and support vector machine (SVM), were trained using already available bioactivity data of Src kinase targeting compounds.
View Article and Find Full Text PDFFundam Clin Pharmacol
February 2025
Department of Pharmacology and Toxicology, Faculty of Pharmacy, Beni-Suef University, Beni-Suef, 62514, Egypt.
Drug repurposing of well-established drugs to be targeted against lung cancer has been a promising strategy. Bosentan is an endothelin 1 (ET-1) blocker widely used in pulmonary hypertension. The current experiment intends to inspect the anticancer and antiangiogenic mechanism of bosentan targeting epidermal growth factor receptor (EGFR) /extra-cellular Signal Regulated Kinase (ERK) /c-Jun/vascular endothelial growth factor (VEGF) carcinogenic pathway.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Endocrinology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No. 88, Jiefang Road, Shangcheng District, Hangzhou, 310000, Zhejiang Province, China.
Primary aldosteronism (PA), characterized by autonomous aldosterone overproduction, is a major cause of secondary hypertension with significant cardiovascular complications. Current treatments mainly focus on symptom management rather than addressing underlying mechanisms. This study aims to discover novel therapeutic targets for PA using integrated bioinformatics and experimental validation approaches.
View Article and Find Full Text PDFJ Comput Chem
January 2025
Centre for Inflammation, Centenary Institute and University of Technology Sydney, Faculty of Science, School of Life Sciences, Sydney, New South Wales, Australia.
Phosphodiesterase 5 (PDE5) inhibitors have shown great potential in treating Alzheimer's disease by improving memory and cognitive function. In this study, we evaluated fluspirilene, a drug commonly used to treat schizophrenia, as a potential PDE5 inhibitor using computational methods. Molecular docking revealed that fluspirilene binds strongly to PDE5, supported by hydrophobic and aromatic interactions.
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