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Exploring the Prognostic Features of Hepatocellular Carcinoma via Text Mining and Data Analysis

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Abstract

Transcatheter arterial chemoembolization is one of the interventional treatments for hepatocellular carcinoma (HCC). This treatment is generally used for patients with intermediate to advanced hepatocellular carcinoma, and identifying the role of HCC-related genes can help improve the efficiency of transcatheter arterial chemoembolization. To investigate the role of HCC-related genes and to provide valid evidence for transcatheter arterial chemoembolization treatment, we performed a comprehensive bioinformatics analysis. Through text mining (“hepatocellular carcinoma”) and microarray data analysis (GSE104580), we obtained a standard gene set, which was followed by gene ontology and Kyoto Gene and Genome Encyclopedia analysis. The significant 8 genes clustered in protein-protein interactions network were chosen to be used in the follow-up analysis. Through survival analysis low expression of the key genes were found to be strongly associated with survival in HCC patients in this study. The correlation between the expression of the key genes and tumor immune infiltration was assessed by Pearson correlation analysis. As a result, 15 drugs targeting seven of the eight genes have been identified, and therefore can be considered as potential components for transcatheter arterial chemoembolization treatment of HCC.

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ACKNOWLEDGMENTS

Thanks to Zhao’s team (Official Wechat Account: SCIPhD) of Sheng **n Zhu Shou for suggestions and grammarly editing on the article.

Funding

This research was funded by Minhang Hospital, Fudan University, Hospital-level Project (2022MHLC05), project title: SERPINE1 expression is regulated by YAP and TGF-β crosstalk in hepatocellular carcinoma.

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Authors and Affiliations

  1. School of Criminal Law, East China University of Political Science and Law, 200042, Shanghai, China

    Z. H. Yang

  2. Department of Transfusion, Minhang Hospital, Fudan University, 201199, Shanghai, China

    S. X. Wang

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Contributions

Z.H. Yang: Investigation, Conceptualization, Data curation, Formal analysis, Methodology, Software, Supervision, Validation, Visualization, Writing original draft, Writing review & editing. S.X. Wang: Data curation, Formal analysis, Methodology, Validation, Visualization, Writing review & editing.

Corresponding author

Correspondence to S. X. Wang.

Ethics declarations

COMPLIANCE WITH ETHICAL STANDARDS

All participated authors declare that they have no known competing financial interests or personal relationships that couldhave appeared to influence the work reported in this paper. This article does not contain any research involving humans or animals as subjects of research.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are openly available in the NCBI-Gene Expression Omnibus database (NCBI-GEO) (website: https://www.ncbi.nlm. nih.gov/geo/query/acc.cgi?acc=GSE104580).

ADDITIONAL INFORMATION

The text was submitted by the author(s) in English.

Additional information

Abbreviations: HCC, hepatocellular carcinoma; BCLC, Barcelona Clinical Hepatocellular Carcinoma; LT, liver transplantation; TACE, transcatheter arterial chemoembolization; HRGs, HCC-related genes; PPI, protein-protein interactions; TMGs, text mining genes; DEGs, differentially expressed genes; FC, fold change; GO, Gene Ontology; BP, biological process; CC, cellular component; MF, molecular function; OS, overall survival; AUC, area under the curve; TIMER, Tumor IMmune Estimation Resource; TAM, tumor-associated macrophages.

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Yang, Z.H., Wang, S.X. Exploring the Prognostic Features of Hepatocellular Carcinoma via Text Mining and Data Analysis. Mol Biol 57, 530–543 (2023). https://doi.org/10.1134/S0026893323030160

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