Evidence map›Paper›PMID 39854135›Full record

ArticleCancer reports (Hoboken, N.J.)2025

Integration of Gastric Cancer RNA-Seq Datasets Along With PPI Network Suggests That Nonhub Nodes Have the Potential to Become Biomarkers.

Akram Siavoshi, Mehran Piran, Ali Sharifi-Zarchi, Fatemeh Ataellahi

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Article in Cancer reports (Hoboken, N.J.), 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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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Akram SiavoshiDepartment of Alborz Health Technology Development Center, Alborz University of Medical Sciences, Alborz, Iran.ORCID 0000-0002-6343-9710
Mehran PiranDepartment of Medical Biotechnology, Drug Design and Bioinformatics Unit, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran.ORCID 0000-0001-7891-728X
Ali Sharifi-ZarchiDepartment of Computer Engineering, Sharif University of Technology, Tehran, Iran.ORCID 0000-0002-0087-7596
Fatemeh AtaellahiDepartment of Biology, College of Sciences, Shiraz University, Shiraz, Iran.ORCID 0000-0003-3928-0014

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe breakthrough discovery of novel biomarkers with prognostic and diagnostic value enables timely medical intervention for the survival of patients diagnosed with gastric cancer (GC). Typically, in studies focused on biomarker analysis, highly connected nodes (hubs) within the protein-protein interaction network (PPIN) are proposed as potential biomarkers. However, this study revealed an unexpected finding following the clustering of network nodes. Consequently, it is essential not to overlook weakly connected nodes (nonhubs) when determining suitable biomarkers from PPIN. METHODS AND

resultsIn this study, several potential biomarkers for GC were proposed based on the findings from RNA-sequencing (RNA-Seq) datasets, along with differential gene expression (DGE) analysis, PPINs, and weighted gene co-expression network analysis (WGCNA). Considering the overall survival (OS) analysis and the evaluation of expression levels alongside statistical parameters of the PPIN cluster nodes, it is plausible to suggest that THY1, CDH17, TGIF1, and AEBP1, categorized as nonhub nodes, along with ITGA5, COL1A1, FN1, and MMP2, identified as hub nodes, possess characteristics that render them applicable as biomarkers for the GC. Additionally, insulin-like growth factor (IGF)-binding protein-2 (IGFBP2), classified as a nonhub node, demonstrates a significant negative correlation with both groups within the same cluster. This observation underscores the conflicting findings regarding IGFBP2 in various cancer studies and enhances the potential of this gene to serve as a biomarker.

conclusionThe findings of the current study not only identified the hubs and nonhubs that may serve as potential biomarkers for GC but also revealed a PPIN cluster that includes both hubs and nonhubs in conjunction with IGFBP2, thereby enhancing the understanding of the complex behavior associated with IGFBP2.

Indexed as

Biomarkers, TumorProtein Interaction MapsStomach NeoplasmsCollagen Type I, alpha 1 ChainGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansPrognosisRNA-SeqBiomarkers, TumorCollagen Type I, alpha 1 Chainbiomarker discoverygastric cancerIGFBP2integration of RNA‐seq datasetsnonhubsprotein–protein interaction network

Identifiers

PMID39854135
PMCPMC11757912

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.