ArticleAmerican journal of translational research2020
Identification and validation of a ten-gene set variation score as a diagnostic and prognostic stratification tool in hepatocellular carcinoma.
Article in American journal of translational research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- A Prognostic Model of Differentiated Thyroid Cancer Based on Up-Regulated Glycolysis-Related Genes.Frontiers in endocrinology · 2022Article
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Authors and funding
11 authors.
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Abstract
We aimed to identify a hepatocellular carcinoma (HCC)-specific gene set during progression. Using the HCC data set from The Cancer Genome Atlas, we found that 10 genes were gradually upregulated with the progression of HCC and associated with survival, classified as HCC-unfavorable genes; 29 genes were gradually downregulated and associated with survival, classified as HCC-favorable genes. Gene set variation analysis (GSVA) was used to score individual samples against the two gene sets. Receiver operating characteristic (ROC) curve analysis showed that both the HCC-unfavorable GSVA score and HCC-favorable GSVA score were reliable biomarkers for diagnosing HCC. Moreover, tROC curve analysis and univariate/multivariate Cox proportional hazards analyses indicated that the HCC-unfavorable GSVA score was an independent prognostic biomarker. The results were validated in an external independent data set. Our results support a ten-gene set variation score as a diagnostic and predictive strategy tool in HCC.
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33042448PMC7540149What OpenQuestion holds
Registered trials
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