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BMC Cancer
Published in: BMC Cancer 1/2020

01-12-2020 | Hepatocellular Carcinoma | Research article

Identification of a protein signature for predicting overall survival of hepatocellular carcinoma: a study based on data mining

Authors: Zeng-hong Wu, Dong-liang Yang

Published in: BMC Cancer | Issue 1/2020

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Abstract

Background

Hepatocellular carcinoma (HCC), is the fifth most common cancer in the world and the second most common cause of cancer-related deaths. Over 500,000 new HCC cases are diagnosed each year. Combining advanced genomic analysis with proteomic characterization not only has great potential in the discovery of useful biomarkers but also drives the development of new diagnostic methods.

Methods

This study obtained proteomic data from Clinical Proteomic Tumor Analysis Consortium (CPTAC) and validated in The Cancer Proteome Atlas (TCPA) and TCGA dataset to identify HCC biomarkers and the dysfunctional of proteogenomics.

Results

The CPTAC database contained data for 159 patients diagnosed with Hepatitis-B related HCC and 422 differentially expressed proteins (112 upregulated and 310 downregulated proteins). Restricting our analysis to the intersection in survival-related proteins between CPTAC and TCPA database revealed four coverage survival-related proteins including PCNA, MSH6, CDK1, and ASNS.

Conclusion

This study established a novel protein signature for HCC prognosis prediction using data retrieved from online databases. However, the signatures need to be verified using independent cohorts and functional experiments.
Appendix
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Metadata
Title
Identification of a protein signature for predicting overall survival of hepatocellular carcinoma: a study based on data mining
Authors
Zeng-hong Wu
Dong-liang Yang
Publication date
01-12-2020
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2020
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-020-07229-x

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