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

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...

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Autores principales: Chen, Wei, Wang, Hao, Li, Tong, Liu, Te, Yang, Wenjing, Jin, Anli, Ding, Lin, Zhang, Chunyan, Pan, Baishen, Guo, Wei, Wang, Beili
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867887/
https://www.ncbi.nlm.nih.gov/pubmed/35197055
http://dx.doi.org/10.1186/s12920-022-01162-7
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author Chen, Wei
Wang, Hao
Li, Tong
Liu, Te
Yang, Wenjing
Jin, Anli
Ding, Lin
Zhang, Chunyan
Pan, Baishen
Guo, Wei
Wang, Beili
author_facet Chen, Wei
Wang, Hao
Li, Tong
Liu, Te
Yang, Wenjing
Jin, Anli
Ding, Lin
Zhang, Chunyan
Pan, Baishen
Guo, Wei
Wang, Beili
author_sort Chen, Wei
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01162-7.
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spelling pubmed-88678872022-02-25 A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion Chen, Wei Wang, Hao Li, Tong Liu, Te Yang, Wenjing Jin, Anli Ding, Lin Zhang, Chunyan Pan, Baishen Guo, Wei Wang, Beili BMC Med Genomics Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01162-7. BioMed Central 2022-02-24 /pmc/articles/PMC8867887/ /pubmed/35197055 http://dx.doi.org/10.1186/s12920-022-01162-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Wei
Wang, Hao
Li, Tong
Liu, Te
Yang, Wenjing
Jin, Anli
Ding, Lin
Zhang, Chunyan
Pan, Baishen
Guo, Wei
Wang, Beili
A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion
title A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion
title_full A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion
title_fullStr A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion
title_full_unstemmed A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion
title_short A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion
title_sort novel prognostic model for hepatocellular carcinoma based on 5 micrornas related to vascular invasion
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8867887/
https://www.ncbi.nlm.nih.gov/pubmed/35197055
http://dx.doi.org/10.1186/s12920-022-01162-7
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