Alternative splicing (AS) is reported to be related to the biological process of multiple malignancies. This study is conducted to identify survival-associated AS events and prognostic signatures that may serve as prognostic indicators for pancreatic cancer (PC).
Univariate Cox analysis was used to determine the survival-associated AS events in PC. Prognostic signatures were constructed by LASSO Cox analysis based on seven types of survival-associated AS events. The correlation between the expression of splicing factors (SFs) and the percent spliced in values of AS events was analyzed by Pearson correlation analysis. Risk scores were calculated to determine high- or low-risk patients with different types of AS events. Gene functional annotation analysis was performed to reveal pathways in which prognostic AS is enriched.
A total of 45,313 AS events in 10,624 genes were observed, and there were 1,565 AS events in 1,223 genes significantly correlated with overall survival for PC. Kaplan–Meier analysis, receiver-operator characteristic curve, univariate and multivariate Cox analyses showed that AS prognostic signatures could effectively predict prognosis of patients with PC. Splicing factors–AS regulatory networks were established to demonstrate the interaction between AS events and SFs.
The survival-associated AS events and prognostic signatures identified in this study can serve as useful tool for predicting prognosis of patients with PC. Moreover, the SF–AS regulatory networks may provide clues for the mechanisms underlying AS in PC.