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Biology subjects

KUMAR, D.

Publications and source records attributed to KUMAR, D..

2 recordsLinked to original sources

Transcriptomic landscape of Gallbladder cancer reveals altered pathways related to cell cycle and Aurora kinase

BackgroundGallbladder cancer (GBC) is a rare but aggressive biliary tract malignancy. This study explores the transcriptomic profile of GBC to identify differentially expressed genes (DEGs) and dysregulated pathways involved in its pathogenesis. MethodsRNA sequencing was performed on 13 GBC tumors and 6 matched controls. Functional enrichment analysis as well as WGCNA were used to identify dysregulated pathways, functionally relevant gene modules and hub genes. Key targets were validated in patient tissues and cell lines. ResultsA total of 621 DEGs were identified (247 upregulated, 374 downregulated). Gene set enrichment analysis revealed activation of E2F targets and G2/M checkpoint, with downregulation of bile acid metabolism and estrogen response pathways. A tumor grade-correlated WGCNA module was enriched in cell cycle genes. TPX2 emerged as a central hub gene. Inhibitors of aurora kinase, TPX2 dependent enzyme, significantly reduced proliferation, migration, and invasion in GBC cells. High-grade tumors confirmed elevated Aurora kinase expression. ConclusionsThis first transcriptomic analysis of GBC in South-East Asian Indians uncovers key drivers like TPX2 and Aurora kinases in disease progression. The study highlights cell cycle dysregulation and sex-linked signatures, offering insights for biomarker discovery and targeted therapies.

cancer biology↗

Identification of Potential Hub Genes and Therapeutic Targets in Colorectal Cancer Using Integrated Bioinformatics Approaches

In this study, we took a comprehensive approach using bioinformatics to uncover potential therapeutic targets for colorectal cancer (CRC). We started by analyzing gene expression data from GEO2R to identify genes that were differentially expressed in CRC. Then, using FunRich software, we created Venn diagrams to visualize these genes. From the 191 upregulated genes we found, we focused on potential "hub genes" by looking at their network connections and strength, using the STRING database.To understand the roles of these hub genes, we performed functional analyses like Gene Ontology (GO) and pathway enrichment through the DAVID platform. This helped us pinpoint key biological processes and pathways linked to the genes we identified. We also looked at patient survival data from GEPIA, along with information on gene expression related to disease stages and metastatic progression. This helped us identify which hub genes were most relevant for CRC.In addition, we examined genetic changes and gene expression patterns in CRC patients through databases like cBioPortal and the Human Protein Atlas. This gave us more evidence supporting the involvement of these genes in the disease. Ultimately, our analysis highlighted CXCL8, FOXC1, ICOS, and MCF2 as potential hub genes with important roles in CRC. These genes may serve as useful biomarkers for both diagnosing CRC and predicting patient outcomes, and they could also help guide the development of targeted treatments to improve survival rates.

bioinformatics↗