4.6 Article

Five key lncRNAs considered as prognostic targets for predicting pancreatic ductal adenocarcinoma

Journal

JOURNAL OF CELLULAR BIOCHEMISTRY
Volume 119, Issue 6, Pages 4559-4569

Publisher

WILEY
DOI: 10.1002/jcb.26598

Keywords

lncRNAs; pancreatic ductal adenocarcinoma; weighted gene co-expression network analysis

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Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, and the 5-year survival rate was only 7.7%. To improve prognosis, a screening biomarker for early diagnosis of pancreatic cancer is in urgent need. Long non-coding RNA (lncRNA) expression profiles as potential cancer prognostic biomarkers play critical roles in development of tumorigenesis and metastasis of cancer. However, lncRNA signatures in predicting the survival of a patient with PDAC remain unknown. In the current study, we try to identify potential lncRNA biomarkers and their prognostic values in PDAC. LncRNAs expression profiles and corresponding clinical information for 182 cases with PDAC were acquired from The Cancer Genome Atlas (TCGA). A total of 14470 lncRNA were identified in the cohort, and 175 PDAC patients had clinical variables. We obtained 108 differential expressed lncRNA via R packages. Univariate and multivariate Cox proportional hazards regression, lasso regression was performed to screen the potential prognostic lncRNA. Five lncRNAs have been recognized to significantly correlate with OS. We established a linear prognostic model of five lncRNA (C9orf139, MIR600HG, RP5-965G21.4, RP11-436K8.1, and CTC-327F10.4) and divided patients into high- and low-risk group according to the prognostic index. The five lncRNAs played independent prognostic biomarkers of OS of PDAC patients and the AUC of the ROC curve for the five lncRNAs signatures prediction 5-year survival was 0.742. In addition, targeted genes of MIR600HG, C9orf139, and CTC-327F10.4 were explored and functional enrichment was also conducted. These results suggested that this five-lncRNAs signature could act as potential prognostic biomarkers in the prediction of PDAC patient's survival.

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