ArticleBMC cancer2020
Identification of a protein signature for predicting overall survival of hepatocellular carcinoma: a study based on data mining.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- A multi-omics framework for survival mediation analysis of high-dimensional proteogenomic data.PLoS computational biology · 2026Article
- Advancing liver cancer diagnosis and treatment with multi-omics approaches: a systematic review.Discover oncology · 2025Review
- Article
- Mechanism of action of protopanaxadiol ginsenosides on hepatocellular carcinoma and network pharmacological analysis.Chinese herbal medicines · 2024Review
- Proteogenomic data and resources for pan-cancer analysis.Cancer cell · 2023Review
- Molecular and genetic markers in hepatocellular carcinoma:World journal of gastrointestinal pathophysiology · 2022Article
- Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine.Biomedicines · 2021Review
- Identification of a Novel Protein-Based Signature to Improve Prognosis Prediction in Renal Clear Cell Carcinoma.Frontiers in molecular biosciences · 2021Article
- Identification of a Novel Four-Gene Signature Correlated With the Prognosis of Patients With Hepatocellular Carcinoma: A Comprehensive Analysis.Frontiers in oncology · 2021Article
- Review
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2 authors.
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Abstract
backgroundHepatocellular 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.
methodsThis 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.
resultsThe 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.
conclusionThis 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.
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