Identification of Overlapping Genetic Signatures Between Obstructive Sleep Apnea and Lung Cancer: Moving Beyond “One Drug, One Disease” Paradigm of Pharmaceutical Innovation DOI
Sanjukta Dasgupta

OMICS A Journal of Integrative Biology, Journal Year: 2025, Volume and Issue: unknown

Published: April 8, 2025

Traditional paradigms of pharmaceutical innovation have long relied on the "one drug, one disease" premise. However, a network mindset in unpacking disease mechanisms can be fruitful to move toward polydisease" paradigm drug discovery and development. A case point is obstructive sleep apnea (OSA) lung cancer, which are two prevalent respiratory disorders that share common risk factors may potentially exhibit overlapping molecular mechanisms. The putative mechanistic linkages between OSA cancer remain underexplored; however, this study offers new evidence genetic signatures with an in-silico approach. Bioinformatics analysis publicly available datasets (GSE135917 GSE268175) identified 123 upregulated 13 downregulated genes 3175 2272 cancer. total four (C1GALT1, TMEM106B, ZNF117, ZNF486) were significantly both disorders, highlighting shared Pathway cell enrichment indicated mucin type O-glycan biosynthesis pathway endothelial cells strongly associated these genes, lending support for their potential roles diseases. Moreover, hsa-miR-34a-5p, hsa-let-7g-5p, hsa-miR-19a-3p found genes. Validation using GEPIA2 tool confirmed consistent expression patterns Machine learning highlighted TMEM106B as most significant biomarker candidate distinguishing from controls. In summary, supports overarching concept human diseases pathways specific example While findings call further research validation, they invite rethinking current beyond concept.

Language: Английский

Multiplexed Molecular Endophenotypes Help Identify Hub Genes in Non-Small Cell Lung Cancer: Unlocking Next-Generation Cancer Phenomics DOI
Sanjukta Dasgupta

OMICS A Journal of Integrative Biology, Journal Year: 2025, Volume and Issue: 29(1), P. 8 - 17

Published: Jan. 1, 2025

Next-generation cancer phenomics by deployment of multiple molecular endophenotypes coupled with high-throughput analyses gene expression offer veritable opportunities for triangulation discovery findings in non-small cell lung (NSCLC) research. This study reports differentially expressed genes NSCLC using publicly available datasets (GSE18842 and GSE229253), uncovering 130 common that may potentially represent crucial signatures NSCLC. Additionally, network GeneMANIA STRING revealed significant coexpression interaction patterns among these genes, four notable hub genes-GRK5, CAV1, PPARG, CXCR2-identified as pivotal progression. Validation indicated their consistent downregulation tumor tissues compared to normal counterparts. Gene across the representing pathological stages distinct trends, emphasizing putative roles biomarkers Moreover, three miRNAs (hsa-miR-429, hsa-miR-335-5p, hsa-miR-126-3p) showed strong associations while SREBF1 emerged a relevant transcription factor. Pathway enrichment analysis identified chemokine signaling pathway significantly associated highlighting its role progression immune evasion. Cell-type endothelial cells play pathogenesis. Finally, survival demonstrated GRK5 is potential oncogenic marker, whereas CAV1 have protective effect. These collectively underscore critical interactions suggest novel paths translational research, targeted therapies, prognostic markers clinical settings. They also attest promises next-generation findings.

Language: Английский

Citations

0
Drug Design in the Age of Network Medicine and Systems Biology: Transcriptomics Identifies Potential Drug Targets Shared by Sarcoidosis and Pulmonary Hypertension DOI
Sanjukta Dasgupta

OMICS A Journal of Integrative Biology, Journal Year: 2025, Volume and Issue: unknown

Published: April 21, 2025

Network medicine considers the interconnectedness of human diseases and their underlying molecular substrates. In this context, sarcoidosis pulmonary hypertension (PH) have long been thought as distinct diseases, but there is growing evidence shared mechanisms. This study reports on common differentially expressed genes (DEGs), regulatory elements, pathways between two diseases. Publicly available transcriptomic datasets for (GSE157671) PH (GSE236251) were retrieved from Gene Expression Omnibus database. DEGs identified using GEO2R, followed by pathway enrichment gene interaction analyses via GeneMANIA STRING. Importantly, a total 13 PH, with 7 upregulated 6 downregulated genes. The SMAD2/3 nuclear was enriched pathway, suggesting role in fibrosis immune regulation. There also divergences PH. For example, set analysis indicated significant associations IFN-gamma signaling TNF-alpha miRNA network hsa-miR-34a-5p, hsa-let-7g-5p, hsa-miR-19a-3p key regulators linked to both Finally, DGIdb revealed potential therapeutic candidates targeting these contributes field drug design discovery standpoint. links uncovered point several biomarkers targets. Further experimental validation translational medical research are called diagnostics drugs, which can effectively safely help clinical management

Language: Английский

Citations

0
Idiopathic Pulmonary Fibrosis: In Silico Therapeutic Potential of Doxycycline, Pirfenidone, and Nintedanib, and the Role of Next-Generation Phenomics in Drug Discovery DOI
Sanjukta Dasgupta

OMICS A Journal of Integrative Biology, Journal Year: 2025, Volume and Issue: 29(3), P. 87 - 95

Published: Feb. 3, 2025

Innovation in drug discovery for human diseases stands to benefit from systems science and next-generation phenomics approaches. An example is idiopathic pulmonary fibrosis (IPF) that a chronic disorder leading respiratory failure which preventive therapeutic medicines are sorely needed. Matrix metalloproteinases (MMPs), particularly MMP1 MMP7, have been associated with IPF pathogenesis thus relevant discovery. This study evaluates the comparative potentials of doxycycline, pirfenidone, nintedanib relation MMP7 using molecular docking, dynamics simulations, approach. Adsorption, distribution, metabolism, excretion, toxicity analysis revealed doxycycline adhered Lipinski's rule five, while pirfenidone exhibited no violations. The favorable safety profiles, lethal dose 50 values being 2240kg, 580, 500 mg/kg, respectively. Homology modeling validated accuracy structures target proteins, is, MMP7. Protein Contacts Atlas tool, platform broadens scope research, was employed visualize protein contacts at atomic levels, revealing interaction surfaces Docking studies superior binding affinities candidate proteins (-6.9 kcal/mol -7.9 MMP7) compared pirfenidone. Molecular simulations further demonstrated stability protein-ligand complexes. These findings highlight notable potential future therapeutics innovation. By integrating silico approach, this opens up new avenues development possibly, precision/personalized consider signatures candidates each patient.

Language: Английский

Citations

0
Identification of Overlapping Genetic Signatures Between Obstructive Sleep Apnea and Lung Cancer: Moving Beyond “One Drug, One Disease” Paradigm of Pharmaceutical Innovation DOI
Sanjukta Dasgupta

OMICS A Journal of Integrative Biology, Journal Year: 2025, Volume and Issue: unknown

Published: April 8, 2025

Traditional paradigms of pharmaceutical innovation have long relied on the "one drug, one disease" premise. However, a network mindset in unpacking disease mechanisms can be fruitful to move toward polydisease" paradigm drug discovery and development. A case point is obstructive sleep apnea (OSA) lung cancer, which are two prevalent respiratory disorders that share common risk factors may potentially exhibit overlapping molecular mechanisms. The putative mechanistic linkages between OSA cancer remain underexplored; however, this study offers new evidence genetic signatures with an in-silico approach. Bioinformatics analysis publicly available datasets (GSE135917 GSE268175) identified 123 upregulated 13 downregulated genes 3175 2272 cancer. total four (C1GALT1, TMEM106B, ZNF117, ZNF486) were significantly both disorders, highlighting shared Pathway cell enrichment indicated mucin type O-glycan biosynthesis pathway endothelial cells strongly associated these genes, lending support for their potential roles diseases. Moreover, hsa-miR-34a-5p, hsa-let-7g-5p, hsa-miR-19a-3p found genes. Validation using GEPIA2 tool confirmed consistent expression patterns Machine learning highlighted TMEM106B as most significant biomarker candidate distinguishing from controls. In summary, supports overarching concept human diseases pathways specific example While findings call further research validation, they invite rethinking current beyond concept.

Language: Английский

Citations

0