A novel multidimensional signature predicts prognosis in hepatocellular carcinoma patients
Journal of Cellular Physiology
Published online on November 27, 2018
Abstract
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- "\nUsing bioinformatics analysis methods including Cox’s proportional hazards regression
analysis, the random survival forest algorithm, Kaplan–Meier and receiver operating
characteristic curve analysis, we mined the gene expression profiles of 469 hepatocellular
carcinoma (HCC) patients from The Cancer Genome Atlas (n = 379) and Gene Expression
Omnibus (GSE14520; \nn = 90) public database and found a prognostic protein‐coding
gene‐microRNA signature that predicts survival in patients with HCC patients. The
signature has a bright clinical significance to be a potential prognostic biomarker.\n\n\n\n\n\nAbstract\nThe
abnormal expression of microRNAs (miRNAs) or protein‐coding genes (PCGs) have been
found to be associated with the prognosis of hepatocellular carcinoma (HCC) patients.
Using bioinformatics analysis methods including Cox’s proportional hazards regression
analysis, the random survival forest algorithm, Kaplan–Meier, and receiver operating
characteristic (ROC) curve analysis, we mined the gene expression profiles of 469
HCC patients from The Cancer Genome Atlas (n = 379) and Gene Expression Omnibus
(GSE14520; \nn = 90) public database. We selected a signature comprising one protein‐coding
gene (PCG; DNA polymerase μ) and three miRNAs (hsa‐miR‐149‐5p, hsa‐miR‐424‐5p, hsa‐miR‐579‐5p)
with highest accurate prediction (area under the ROC curve [AUC] = 0.72; \nn = 189)
from the training data set. The signature stratified patients into high‐ and low‐risk
groups with significantly different survival (median 27.9 vs. 55.2 months, log‐rank
test, \np < 0.001) in the training data set, and its risk stratification ability
were validated in the test data set (median 47.4 vs. 84.4 months, log‐rank test,
\np = 0.03) and an independent data set (median 31.0 vs. 46.0 months, log‐rank test,
\np = 0.01). Multivariable Cox regression analysis showed that the signature was
an independent prognostic factor. And the signature was proved to have a better
survival prediction power than tumor–node–metastasis (TNM) stage (AUC\nsignature = 0.72/0.64/0.62
vs. AUC\nTNM = 0.65/0.61/0.61; \np < 0.05). Moreover, we validated the expression
of these prognostic genes from the PCG‐miRNA signature in Huh‐7 cell by real‐time
polymerase chain reaction. In conclusion, we found a signature that can predict
survival of HCC patients and serve as a prognostic marker for HCC."
- 'Journal of Cellular Physiology, EarlyView. '