Identification of early diagnostic biomarkers via WGCNA in gastric cancer.


Journal

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
ISSN: 1950-6007
Titre abrégé: Biomed Pharmacother
Pays: France
ID NLM: 8213295

Informations de publication

Date de publication:
Jan 2022
Historique:
received: 10 10 2021
revised: 14 11 2021
accepted: 23 11 2021
pubmed: 6 12 2021
medline: 11 3 2022
entrez: 5 12 2021
Statut: ppublish

Résumé

Gastric cancer (GC) is the world's second-leading cause of cancer-related mortality, continuing to make it a serious healthcare concern. Even though the prevalence of GC reduces, the prognosis for GC patients remains poor in terms of a lack of reliable biomarkers to diagnose early GC and predict chemosensitivity and recurrence. We integrated the gene expression patterns of gastric cancers from four RNAseq datasets (GSE113255, GSE142000, GSE118897, and GSE130823) from Gene Expression Omnibus (GEO) database to recognize differentially expressed genes (DEGs) between normal and GC samples. A gene co-expression network was built using weighted co-expression network analysis (WGCNA). Furthermore, RT-qPCR was performed to validate the in silico results. The red modules in GSE113255, Turquoise in GSE142000, Brown in GSE118897, and the green-yellow module in GSE130823 datasets were found to be highly correlated with the anatomical site of GC. ITGAX, CCL14, ADHFE1, and HOXB13) as the hub gene are differentially expressed in tumor and non-tumor gastric tissues in this study. RT-qPCR demonstrated a high level of the expression of this gene. The expression levels of ITGAX, CCL14, ADHFE1, and HOXB13 in GC tumor tissues are considerably greater than in adjacent normal tissues. Systems biology approaches identified that these genes could be possible GC marker genes, providing ideas for other experimental studies in the future.

Sections du résumé

BACKGROUND BACKGROUND
Gastric cancer (GC) is the world's second-leading cause of cancer-related mortality, continuing to make it a serious healthcare concern. Even though the prevalence of GC reduces, the prognosis for GC patients remains poor in terms of a lack of reliable biomarkers to diagnose early GC and predict chemosensitivity and recurrence.
METHODS AND MATERIAL METHODS
We integrated the gene expression patterns of gastric cancers from four RNAseq datasets (GSE113255, GSE142000, GSE118897, and GSE130823) from Gene Expression Omnibus (GEO) database to recognize differentially expressed genes (DEGs) between normal and GC samples. A gene co-expression network was built using weighted co-expression network analysis (WGCNA). Furthermore, RT-qPCR was performed to validate the in silico results.
RESULTS RESULTS
The red modules in GSE113255, Turquoise in GSE142000, Brown in GSE118897, and the green-yellow module in GSE130823 datasets were found to be highly correlated with the anatomical site of GC. ITGAX, CCL14, ADHFE1, and HOXB13) as the hub gene are differentially expressed in tumor and non-tumor gastric tissues in this study. RT-qPCR demonstrated a high level of the expression of this gene.
CONCLUSION CONCLUSIONS
The expression levels of ITGAX, CCL14, ADHFE1, and HOXB13 in GC tumor tissues are considerably greater than in adjacent normal tissues. Systems biology approaches identified that these genes could be possible GC marker genes, providing ideas for other experimental studies in the future.

Identifiants

pubmed: 34864309
pii: S0753-3322(21)01263-4
doi: 10.1016/j.biopha.2021.112477
pii:
doi:

Substances chimiques

Biomarkers, Tumor 0
CCL14 protein, human 0
Chemokines, CC 0
HOXB13 protein, human 0
Homeodomain Proteins 0
Mitochondrial Proteins 0
Alcohol Oxidoreductases EC 1.1.-
hydroxyacid-oxoacid transhydrogenase EC 1.1.99.24

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

112477

Informations de copyright

Copyright © 2021 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Auteurs

Zohreh Rezaei (Z)

Department of Biology, Faculty of Sciences, University of Sistan and Balouchestan, Zahedan, Iran.

Javad Ranjbaran (J)

Department of Clinical Biochemistry, School of Medicine, Birjand University of Medical Sciences, Birjand, Iran; Student Research Committee, Birjand University of Medical Sciences, Birjand, Iran.

Hossein Safarpour (H)

Cellular and Molecular Research Center, Birjand University of Medical Sciences, Birjand, Iran.

Samira Nomiri (S)

Department of Clinical Biochemistry, School of Medicine, Birjand University of Medical Sciences, Birjand, Iran.

Fatemeh Salmani (F)

Department of Epidemiology and Biostatistics, Social Determinants of Health Research Center, Faculty of Health, Birjand University of Medical Sciences, Birjand, Iran.

Elham Chamani (E)

Department of Clinical Biochemistry, School of Medicine, Birjand University of Medical Sciences, Birjand, Iran.

Pegah Larki (P)

Department of Molecular Genetics, Genomic Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Oronzo Brunetti (O)

Medical Oncology Unit, IRCCS Istituto Tumori "Giovanni Paolo II" of Bari, Bari, Italy.

Nicola Silvestris (N)

Medical Oncology Unit, IRCCS Istituto Tumori "Giovanni Paolo II" of Bari, Bari, Italy; Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari, Bari, Italy. Electronic address: n.silvestris@oncologico.bari.it.

Tahmine Tavakoli (T)

Department of Internal Medicine, School of Medicine, Birjand University of Medical Sciences, Birjand, Iran. Electronic address: tahminetavakoli@bums.ac.ir.

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Classifications MeSH