A seven-lncRNA signature predicts overall survival in esophageal squamous cell carcinoma

Abstract

Esophageal squamous cell carcinoma (ESCC) is one of the most common types of cancer and the leading causes of cancer-related mortality worldwide, especially in Eastern Asia. Here, we downloaded the microarray data of lncRNA expression profiles of ESCC patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets and divided into training, validation and test set. The random survival forest (RSF) algorithm and Cox regression analysis were applied to identify a seven-lncRNA signature. Then the predictive ability of the seven-lncRNA signature was evaluated in the validation and test set using Kaplan-Meier test, time-dependent receiver operating characteristic (ROC) curves and dynamic area under curve (AUC). Stratified analysis and multivariate Cox regression also demonstrated the independence of the signature in prognosis prediction from other clinical factors. Besides, the predict accuracy of lncRNA signature was much better than that of tumor-node-metastasis (TNM) stage in all the three sets. LncRNA combined with TNM displayed better prognostic predict ability than either alone. The role of LINC00173 from the signature in modulating the proliferation and cell cycle of ESCC cells was also observed. These results indicated that this seven-lncRNA signature could be used as an independent prognostic biomarker for prognosis prediction of patients with ESCC.

Figure 1

Kaplan-Meier estimates of the OS and DFS in GEO and TCGA patients using the seven-lncRNA signature. The Kaplan-Meier curves were used to visualize and compare the OS of the low-risk versus high-risk group in GEO training set (A), GEO validation set (B) and TCGA test set (C). The Kaplan-Meier curves for the DFS of low-risk versus high-risk group in TCGA test set was also plotted (D).

Figure 2

Risk score analysis of GEO training set. The distribution of seven-lncRNA risk score and heat maps of the corresponding lncRNA expression level.

Figure 3

Kaplan-Meier estimates of the OS in GEO and TCGA patients using the seven-lncRNA signature, stratified by TNM stage. (A) Patients with ESCC of TNM stage I&II in GEO entire set. (B) Patients with ESCC of TNM stage III in GEO entire set. (C) Patients with ESCC of TNM stage I&II in TCGA test set. (D) Patients with ESCC of TNM stage III&IV in TCGA test set.

Figure 4

Prognostic value evaluation of TNM stage the lncRNA signature. The time-dependent ROC curves on the 12th month of follow up were plotted to assess the prognostic efficiency of TNM stage, lncRNA signature and a variable combining both. (A) The dynamic AUC line for TNM stage, lncRNA signature and the combined variable were delineated.

Figure 5

Functional enrichment analysis depicted the biological pathways and processes associated with correlated genes. The results of GO biological process enrichment (A) and KEGG signaling pathways analysis (B).

Figure 6

Regulatory role of LINC00173 in ESCC cell lines. Colony formation assays showed that the knockdown of LINC00173 boosted the colony number (A). Cell cycle analysis demonstrated that LINC00173 knockdown led to a decreased G1/G0 population (B).