Evidence map›Paper›PMID 40390492›Full record

ArticleJournal, genetic engineering & biotechnology2025

Identification of key biomarker genes in liver hepatocellular carcinoma and kidney renal clear cell carcinoma progression: A shared high-throughput screening and molecular docking method with potentials for targeted therapeutic interventions.

Maisha Tasneem, Shipan Das Gupta, Md Jubair Ahmed Jony, Maya Minkara, Rajib Kumar Dey, Jannatul Ferdoush

Abstract read
In one paragraph

Article in Journal, genetic engineering & biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Maisha TasneemDepartment of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh.
Shipan Das GuptaDepartment of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh.
Md Jubair Ahmed JonyDepartment of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh.
Maya MinkaraDepartment of Biology, Geology, and Environmental Science, University of Tennessee at Chattanooga, 615 McCallie Ave, Chattanooga, TN 37403, USA.
Rajib Kumar DeyChittagong Medical College Hospital, Chattogram, Bangladesh.
Jannatul FerdoushDepartment of Biology, Geology, and Environmental Science, University of Tennessee at Chattanooga, 615 McCallie Ave, Chattanooga, TN 37403, USA. Electronic address: jannatul-ferdoush@utc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesLiver Hepatocellular Carcinoma (LIHC) and Kidney Renal Clear Cell Carcinoma (KIRC) are leading causes of cancer death worldwide, but their early detections remain hindered by a lack of genetic markers. Our study aims to find prospective biomarkers that could serve as prognostic indicators for efficient drug candidates for KIRC and LIHC treatment.

methodsTo detect differentially expressed genes (DEGs), four datasets were used: GSE66271 and GSE213324 for KIRC, and GSE135631 and GSE202853 for LIHC. Visualization of DEGs was done using heatmaps, volcano plots, and Venn diagrams. Hub genes were identified via PPI analysis and the cytoHubba plugin in Cytoscape. Their expression was evaluated using box plots, stage plots, and survival plots for prognostic assessment via GEPIA2. Molecular docking with PyRx's AutoDock Vina identified optimal binding interactions between compounds and proteins. Pharmacokinetic and toxicity analyses reinforced the drug-likeness and safety of these compounds.

resultsIn this study, 47 DEGs were identified, with the top 10 hub genes being TOP2A, BUB1, PTTG1, CCNB2, NUSAP1, KIF20A, BIRC5, RRM2, NDC80 and CDC45, chosen for their high MCC scores. Data mining revealed a correlation between TOP2A expression and clinical survival outcomes in KIRC and LIHC patients. Docking studies of the TOP2A structure identified a promising compound from Andrographis paniculata with high binding energy and interactions with TOP2A. Pharmacokinetic and toxicity assessments support its potential as a drug candidate.

conclusionOur study emphasizes TOP2A's prognostic significance in KIRC and LIHC and recognizes Andrographis paniculata compound as potential therapeutics, offering prospective for enhanced treatment and patient outcomes in these cancers.

Indexed as

BiomarkerDEGsHub genesKIRCLIHCMolecular dockingTOP2A

Identifiers

PMID40390492
PMCPMC12049835

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