Evidence map›Paper›PMID 40321824›Full record

ArticlePeerJ2025

Integrative bioinformatics analysis and experimental validation of key biomarkers driving the progression of cirrhotic portal hypertension.

Meilin Li, Lilin Jiang, Yunrui Ru, Zhonghua Lu, Peng Gu

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Article in PeerJ, 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

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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.

Meilin Li *Department of Gastroenterology, The Fifth People's Hospital of Wuxi (Affiliated Wuxi Fifth Hospital of Jiangnan University), Wuxi, China.
Lilin Jiang *Department of Pathology, The Fifth People's Hospital of Wuxi (Affiliated Wuxi Fifth Hospital of Jiangnan University), Wuxi, China.
Yunrui RuExperimental Center, The Fifth People's Hospital of Wuxi (Affiliated Wuxi Fifth Hospital of Jiangnan University), Wuxi, China.
Zhonghua LuDepartment of Hepatology, The Fifth People's Hospital of Wuxi (Affiliated Wuxi Fifth Hospital of Jiangnan University), Wuxi, China.
Peng GuDepartment of Urology, Xishan People's Hospital of Wuxi City, Wuxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Portal hypertension is a driving factor of cirrhosis complications, but the specific molecular mechanism of portal hypertension in cirrhosis remains unclear. The aim of this study was to identify hub genes for predicting persistent progression of portal hypertension in patients with liver cirrhosis. Methods: Related microarray datasets were obtained from the Gene Expression Omnibus database. Weighted gene co-expression network analysis and differential expression genes analysis were used to identify the correlation sets of genes. In addition, protein-protein interaction networks and machine learning algorithms were conducted to screen center of candidate genes. To validate the diagnostic effect of hub genes, receiver operating characteristic curves were utilized in another dataset that is publicly accessible. Furthermore, the CIBERSORT algorithm was employed to investigate the immune infiltration levels of 22 immune cells and their connection to hub gene markers. Immunohistochemistry and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were conducted to validate novel hub genes in clinical specimens. Results: We obtained 671 differentially expressed genes and 11 module genes related to cirrhotic portal hypertension. Two candidate genes namely oncoprotein-induced transcript 3 protein (OIT3) and lysyl oxidase like protein 1 (LOXL1) were identified as biomarkers. RT-qPCR and immunohistochemistry (IHC) verified the expression of LOXL1 and OIT3 at mRNA and protein levels in liver tissue. Conclusions: OIT3 and LOXL1 were identified as potential novel targets for the diagnosis and treatment of cirrhotic portal hypertension (CPH).

Indexed as

Computational BiologyHypertension, PortalLiver CirrhosisAmino Acid OxidoreductasesBiomarkersDisease ProgressionGene Expression ProfilingGene Regulatory NetworksHumansProtein Interaction MapsAmino Acid OxidoreductasesBiomarkersBioinformatic analysisCirrhosisLysyl Oxidase Like Protein 1Machine learningOncoprotein-induced Transcript 3 ProteinPortal hypertensionWeighted gene co-expression network analysis

Identifiers

PMID40321824
PMCPMC12049105

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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.