Multidrug resistance remains a major obstacle in cancer therapy and is driven by hyperactive efflux transporters and dysregulated signaling pathways. In this study, text mining and network analyses were performed to identify key genes associated with breast cancer drug resistance. Critical regulatory nodes were identified using the Boykov-Kolmogorov algorithm applied to a directed protein–protein interaction network. Molecular docking and molecular dynamics simulations were subsequently conducted to screen FDA-approved drugs for potential interactions with these targets. Cytotoxicity, migration, apoptosis, efflux activity, and relative gene expression assays were performed in drug-resistant and parental breast and gastric cancer cell lines to experimentally evaluate drug effects. ESR1, PPARD, and NFKB1 were identified as essential cut nodes sustaining MDR network connectivity. Drug repurposing analyses predicted celecoxib, desloratadine, and dutasteride as ligands targeting these proteins. Experimental validation demonstrated that the triple-drug combination significantly increased mitoxantrone sensitivity (
P
< 0.001) in multidrug-resistant breast cancer cells. This effect was accompanied by marked inhibition of drug efflux, including significant suppression of BCRP activity (
P
< 0.05) and up to a 20-fold reduction in BCRP gene expression (
P
< 0.001), while more limited effects were observed on MDR1 expression in gastric cells. Collectively, the combination treatment restored chemotherapy responsiveness, reduced cell migration, and promoted apoptosis. Overall, this study suggests that integrating network-based analysis with drug repurposing may provide a useful framework for identifying potential multidrug strategies against drug resistance. These findings offer a computational basis for further experimental validation and potential development of anti-resistance therapeutic approaches.
Najmeh. Fattahi, C. Eslahchi, F. Ghasemi et al.· npj Systems Biology and Appl...· 0 citations
Background Muscular dystrophies (MDs) are a genetically heterogeneous group of disorders, posing significant diagnostic challenges, especially in populations with high consanguinity. Despite advances in genetic testing, a substantial proportion of patients remain undiagnosed. Whole‐exome sequencing (WES) has emerged as a powerful tool for identifying causal variants in such unresolved cases. To identify the genetic basis of nondystrophinopathic MDs in Iranian families with inconclusive prior genetic testing and to evaluate the diagnostic yield and mutational spectrum in this population. Methods We performed WES on one affected individual from each of 10 unrelated Iranian families with clinically diagnosed MD. Candidate variants were prioritized based on in silico prediction tools (SIFT, PolyPhen‐2, CADD, SpliceAI), population frequency databases (gnomAD, 1000 Genomes, EVS), and ACMG/AMP guidelines. Findings were validated by Sanger sequencing, MLPA, and STR haplotype analysis. Segregation analysis was performed in available family members. Results WES led to a diagnostic yield of 69.2% (9/13 variants in 10 families) after segregation analysis and ACMG‐based reclassification. We identified 13 candidate variants in 10 known MD‐associated genes, including DYSF, SGCA, TK2, MAP3K20, LMNA, COL6A1, COL6A2, ITGA7, MICU1, and SGCB. Among these, seven variants (54%) were novel. The majority of cases (84.6%) followed an autosomal recessive pattern, consistent with high parental consanguinity (70%). Notably, a de novo splice‐site variant in COL6A2 (c.1053+1G>T) was identified in a sporadic case, confirming an autosomal dominant inheritance. Challenges in variant interpretation were observed in families with variants in tightly linked genes (COL6A1 and COL6A2), highlighting the role of linkage disequilibrium in founder populations. Conclusion WES is a highly effective diagnostic strategy for genetically heterogeneous MDs, particularly in consanguineous populations. Our study expands the mutational spectrum of MDs in Iran and provides critical data for genetic counseling, prenatal diagnosis, and future therapeutic development. The high rate of novel variants underscores the importance of population‐specific genomic studies.
Nasibeh Soltani, Zahra Shahbazi, M. Fallah et al.· Human Mutation· 0 citations
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