Long non-coding RNAs (lncRNAs) have emerged as useful prognostic markers in many
tumors. In this study, we investigated the potential application of
lncRNA markers for the prognostic prediction of
esophageal squamous cell carcinoma (ESCC). We identified ESCC-associated lncRNAs by comparing ESCC tissues with normal tissues. Subsequently, Kaplan-Meier (KM) method in combination with the univariate Cox proportional hazards regression (UniCox) method was used to screen prognostic lncRNAs. By combining the differential and prognostic lncRNAs, we developed a prognostic model using cox stepwise regression analysis. The obtained prognostic prediction model could effectively predict the 3- and 5-year prognosis and survival of ESCC patients by time-dependent receiver operating characteristic (ROC) curves (area under curve = 0.87 and 0.89, respectively). Besides, a
lncRNA-based classification of ESCC was generated using k-mean clustering method and we obtained two clusters of ESCC patients with association with race and
Barrett's esophagus (BE) (both P < 0.001). Finally, we found that
lncRNA AC007128.1 was upregulated in both ESCC cells and tissues and associated with poor prognosis of ESCC patients. Furthermore, AC007128.1 could promote epithelial-mesenchymal transition (EMT) of ESCC cells by increasing the activation of MAPK/ERK and
MAPK/p38 signaling pathways. Collectively, our findings indicated the potentials of
lncRNA markers in the prognosis, molecular subtyping, and EMT of ESCC.