Prognostic alternative splicing regulatory network of splicing events in acute myeloid leukemia patients based on SpliceSeq data from 136 cases.

Abstract

This study aimed to create prognostic signatures to predict AML patients' survival using alternative splicing (AS) events. The AS data, RNA sequencing data, and the survival statistics of 136 AML patients were obtained from The Cancer Genome Atlas (TCGA) and TCGA SpliceSeq databases. Total 34,984 AS events generated from 8,656 genes, 2,583 of which were survival-associated AS events, were identified using univariate Cox regression. The prognostic models constructed using independent survival-associated AS events revealed that low-risk splicing better predicted patients' survival. ROC analysis indicated that the predictive efficacy of the alternate terminator model was best in the area under the curve at 0.781. Enrichment analysis revealed several important genes (TP53, BCL2, AURKB, PPP2R1B, FOS, and BIRC5) and pathways, such as the protein processing pathway in the endoplasmic reticulum, RNA transport pathway, and HTLV-I infection pathway. The splicing network of splicing events and factors revealed interesting interactions, such as the positive correlation between HNRNPH3 and CALHM2-13010-AT, which may indicate the potential splicing regulatory mechanism. Taken together, survival-associated splicing events and the prognostic signatures for predicting survival can help provide an overview of splicing in AML patients and facilitate clinical practice. The splicing regulatory network may improve the understanding of spliceosomes in AML.