Evidence map›Paper›PMID 41132227›Full record

ArticleAdvanced biomedical research2025

Determination of Critical Genes and Key Regulatorys in Colorectal Cancer with Meta- and Network Analysis of Microarray Datasets.

Razieh Fatehi, Elham Abbasi, Farinaz Khosravian, Mansoor Salehi, Mohammad Kazemi

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Article in Advanced biomedical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Razieh FatehiDepartment of Genetics and Molecular Biology, Isfahan University of Medical Sciences, Isfahan, Iran.
Elham AbbasiCellular, Molecular and Genetics Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Farinaz KhosravianCellular, Molecular and Genetics Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Mansoor SalehiCellular, Molecular and Genetics Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Mohammad KazemiDepartment of Genetics and Molecular Biology, Isfahan University of Medical Sciences, Isfahan, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: High-throughput data generation is developing in the cancer area and offers a better opportunity of understanding molecular pathways involved in the progression of tumors. Meta-analysis of gene expression based on data integration makes it possible to determine changes in gene expression with more accuracy. This approach and downstream analysis were utilized for colorectal cancer to identify promising biomarkers and drug targets. Materials and Methods: First, a systematic search was performed in the Gene Expression Omnibus (GEO) database. Meta-analysis was used to obtain differentially expressed (DE) genes from the NetworkAnalyst database. Moreover, microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and transcription factors (TFs) enriched with DE genes were determined by the Enrichr database. The integrated DE genes-miRNAs-lncRNAs-TFs network was constructed and analyzed using Cytoscape software. Then, the downstream analyses of hub genes were performed. Results: The primary candidate genes, Conclusion: Employing systems biology approaches with holistic insight can identify essential genes and their regulation as possibilities for further experimental testing.

Indexed as

Gene regulatory networkmeta-analysismicroarrayprotein interaction network

Identifiers

PMID41132227
PMCPMC12543253

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