A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion.

Abstract

BACKGROUND:

Hepatocellular carcinoma (HCC) is prevalent worldwide with a high mortality rate. Prognosis prediction is crucial for improving HCC patient outcomes, but effective tools are still lacking. Characteristics related to vascular invasion (VI), an important process involved in HCC recurrence and metastasis, may provide ideas on prognosis prediction.

METHODS:

Tools, including R 4.0.3, Funrich version 3, Cytoscape 3.8.2, STRING 11.5, Venny 2.1.0, and GEPIA 2, were used to perform bioinformatic analyses. The VI-related microRNAs (miRNAs) were identified using Gene Expression Omnibus HCC miRNA dataset GSE67140, containing 81 samples of HCC with VI and 91 samples of HCC without VI. After further evaluated the identified miRNAs based on The Cancer Genome Atlas database, a prognostic model was constructed via Cox regression analysis. The miRNAs in this model were also verified in HCC patients. Moreover, a nomogram was developed by integrating risk score from the prognostic model with clinicopathological parameters. Finally, a potential miRNA-mRNA network related to VI was established through weighted gene co-expression network analysis of HCC mRNA dataset GSE20017, containing 40 samples of HCC with VI and 95 samples of HCC without VI.

RESULTS:

A prognostic model of 5 VI-related miRNAs (hsa-miR-126-3p, hsa-miR-148a-3p, hsa-miR-15a-5p, hsa-miR-30a-5p, hsa-miR-199a-5p) was constructed. The area under receiver operating characteristic curve was 0.709 in predicting 5-year survival rate, with a sensitivity of 0.74 and a specificity of 0.63. The nomogram containing risk score could also predict prognosis. Moreover, a VI-related miRNA-mRNA network covering 4 miRNAs and 15 mRNAs was established.

CONCLUSION:

The prognostic model and nomogram might be potential tools in HCC management, and the VI-related miRNA-mRNA network gave insights into how VI was developed.

• Authors: Wei Chen, Hao Wang, Tong Li, Te Liu, Wenjing Yang, Anli Jin, Lin Ding, Chunyan Zhang, Baishen Pan, Wei Guo, Beili Wang
• Journal: BMC medical genomics (BMC Med Genomics) Vol. 15 Issue 1 Pg. 34 (02 24 2022) ISSN: 1755-8794 [Electronic] England
• PMID: 35197055 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: © 2022. The Author(s).

Chemical References

• Biomarkers, Tumor
• MIRN30a microRNA, human
• MicroRNAs
• RNA, Messenger

Topics

• Biomarkers, Tumor (genetics, metabolism)
• Carcinoma, Hepatocellular (pathology)
• Gene Expression Profiling
• Humans
• Liver Neoplasms (pathology)
• MicroRNAs (genetics, metabolism)
• Prognosis
• RNA, Messenger (genetics)