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

Abstract

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 14 470 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.

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

Figure 1

The heatmap of DElncRNAs expression in PDCA. 108 DElncRNAs were detected. Among these DElncRNAs, 3 DElncRNAs was up‐regulated genes and 105 DElncRNAs were down‐regulated genes. The color from blue to red shows a trend from low expression to high expression

Figure 2

The plot of Regression coefficient diagram using the Lasso regression method

Figure 3

LncRNA risk score analysis of PDCA patients in TCGA. A, LncRNA risk score distribution; B, The survival status and duration of PDCA patients; C, Heatmap of the five LncRNA expression profiles in PDCA patients.

Figure 4

Different differential expression of the five key lncRNA between PDCA and adjunct noncancerous pancreas tissues based on TCGA data. (A) C9orf139; (B) MIR600HG; (C) RP5‐965G21.4; (D) RP11‐436K8.1; and (E) CTC‐327F10.4

Figure 5

Kaplan‐Meier survival curves for overall survival outcomes according to the risk cutoff point. The P‐value of the log‐rank test was less than 0.01

Figure 6

Time‐dependent ROC curves analysis for 5‐year survival prediction by the five key lncRNA

Figure 7

Kaplan‐Meier survival curves in stratified analysis according to different clinical features. (A) New tumor event after initial treatment, (B) Primary therapy outcome success, (C) Cancer status, (D) Grade, and (E) Age

Figure 8

Prediction value of risk scores for early stage (I‐II)

Figure 9

The network of lncRNA MIR600HG (A), C9orf139 (B), and CTC‐327F10.4 (C) with co‐expression genes by WGCNA

Figure 10

GO terms shows as an interaction network using Cytoscape plug‐in ClueGO

Figure 11

KEGG pathways displayed as an interaction network Cytoscape plug‐in ClueGO