» Articles » PMID: 33144628

Weighted MiRNA Co-expression Networks Analysis Identifies Circulating MiRNA Predicting Overall Survival in Hepatocellular Carcinoma Patients

Overview
Journal Sci Rep
Specialty Science
Date 2020 Nov 4
PMID 33144628
Citations 16
Authors
Affiliations
Soon will be listed here.
Abstract

The weighted gene co-expression network analysis (WGCNA) has been used to explore gene expression datasets by constructing biological networks based on the likelihood expression profile among genes. In recent years, WGCNA found application in biomarker discovery studies, including miRNA. Serum samples from 20 patients with hepatocellular carcinoma (HCC) were profiled through miRNA 3.0 gene array and miRNAs biomarker candidates were identified through WGCNA. Results were validated by qRT-PCR in 102 HCC serum samples collected at diagnosis. WGCNA identified 16 miRNA modules, nine of them were significantly associated with the clinical characteristics of the patient. The Red module had a significant negative correlation with patients Survival (- 0.59, p = 0.007) and albumin (- 0.52, p = 0.02), and a positive correlation with PCR (0.61, p = 0.004) and alpha-fetoprotein (0.51, p = 0.02). In the red module, 16 circulating miRNAs were significantly associated with patient survival. MiR-3185 and miR-4507 were identified as predictors of patient survival after the validation phase. At diagnosis, high expression of circulating miR-3185 and miR-4507 identifies patients with longer survival (HR 2.02, 95% CI 1.10-3.73, p = 0.0086, and HR of 1.75, 95% CI 1.02-3.02, p = 0.037, respectively). Thought a WGCNA we identified miR-3185 and miR-4507 as promising candidate biomarkers predicting a longer survival in HCC patients.

Citing Articles

Space radiation damage rescued by inhibition of key spaceflight associated miRNAs.

McDonald J, Kim J, Farmerie L, Johnson M, Trovao N, Arif S Nat Commun. 2024; 15(1):4825.

PMID: 38862542 PMC: 11166944. DOI: 10.1038/s41467-024-48920-y.


An evolutionary learning-based method for identifying a circulating miRNA signature for breast cancer diagnosis prediction.

Yerukala Sathipati S, Tsai M, Aimalla N, Moat L, Shukla S, Allaire P NAR Genom Bioinform. 2024; 6(1):lqae022.

PMID: 38406797 PMC: 10894035. DOI: 10.1093/nargab/lqae022.


Construction of a prognostic prediction model in liver cancer based on genes involved in integrin cell surface interactions pathway by multi-omics screening.

Yu X, Zhang H, Li J, Gu L, Cao L, Gong J Front Cell Dev Biol. 2024; 12:1237445.

PMID: 38374893 PMC: 10875080. DOI: 10.3389/fcell.2024.1237445.


Battle of the biopsies: Role of tissue and liquid biopsy in hepatocellular carcinoma.

Lehrich B, Zhang J, Monga S, Dhanasekaran R J Hepatol. 2023; 80(3):515-530.

PMID: 38104635 PMC: 10923008. DOI: 10.1016/j.jhep.2023.11.030.


Integrated analysis of inflammatory mRNAs, miRNAs, and lncRNAs elucidates the molecular interactome behind bovine mastitis.

Hasankhani A, Bakherad M, Bahrami A, Shahrbabak H, Pecho R, Shahrbabak M Sci Rep. 2023; 13(1):13826.

PMID: 37620551 PMC: 10449796. DOI: 10.1038/s41598-023-41116-2.


References
1.
Li B, Pu K, Wu X . Identifying novel biomarkers in hepatocellular carcinoma by weighted gene co-expression network analysis. J Cell Biochem. 2019; 120(7):11418-11431. DOI: 10.1002/jcb.28420. View

2.
Zhou X, Huang X, Liang S, Tang S, Wu S, Huang T . Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysis. Onco Targets Ther. 2018; 11:2815-2830. PMC: 5961473. DOI: 10.2147/OTT.S163891. View

3.
Pratama M, Cavalletto L, Tiribelli C, Chemello L, Pascut D . Selection and validation of miR-1280 as a suitable endogenous normalizer for qRT-PCR Analysis of serum microRNA expression in Hepatocellular Carcinoma. Sci Rep. 2020; 10(1):3128. PMC: 7035418. DOI: 10.1038/s41598-020-59682-0. View

4.
Tufekci K, Oner M, Meuwissen R, Genc S . The role of microRNAs in human diseases. Methods Mol Biol. 2013; 1107:33-50. DOI: 10.1007/978-1-62703-748-8_3. View

5.
Long X, Zhang Y, Zhang M, Chen K, Zheng X, Wang H . Identification of an 88-microRNA signature in whole blood for diagnosis of hepatocellular carcinoma and other chronic liver diseases. Aging (Albany NY). 2017; 9(6):1565-1584. PMC: 5509456. DOI: 10.18632/aging.101253. View