Abstract

Background: Alternative splicing events have been increasingly reported for anomalous perturbations in various cancers, including papillary thyroid cancer (PTC).Methods: Integration analysis of RNA sequencing and clinical information were utilized to identify survival associated splicing events in PTC. Then, several prognosis-related splicing events were submitted to develop moderate predictors for survival monitoring by using least absolute shrinkage and selection operator model. In addition, several biomedical computational algorithms were conducted to identify pathways enriched by genes with prognostic splicing events and construct regulatory network dominated by splicing factors.Results: Survival analysis in 496 PTC patients indicated that TNM stage, tumor stage, distant metastasis and tumor status were significantly correlated with PTC patients' progression-free interval. 2799 splicing events were identified as prognostic molecular events. Functional enrichment analysis suggested that prognostic splicing events are associated with several energy metabolism-related processes. Based on these prognostic events, several prognostic signatures were developed. The final prognostic signature acted as an independent prognostic factor after adjusting for several clinical parameters. Interestingly, splicing regulatory network was constructed to display potential regulatory mechanisms of splicing events in PTC.Conclusions: Our analysis provides the status of splicing events involved in the progression and may represent an underappreciated hallmark of PTC.

Highlights

  • Progress using high-throughput sequencing technologies has spurred cancer genome research

  • Several biomedical computational algorithms were conducted to identify pathways enriched by genes with prognostic splicing events and construct regulatory network dominated by splicing factors

  • Survival analysis in 496 papillary thyroid cancer (PTC) patients indicated that TNM stage, tumor stage, distant metastasis and tumor status were significantly correlated with PTC patients' progression-free interval. 2799 splicing events were identified as prognostic molecular events

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Summary

Introduction

Progress using high-throughput sequencing technologies has spurred cancer genome research. Recent analyses of cancer genomes have predominantly focused on evaluating the clinical significance of AS events and SFs in tumors, their potentially pathogenic impact for downstream pathways and the development of their regulatory network. Methods: Integration analysis of RNA sequencing and clinical information were utilized to identify survival associated splicing events in PTC. Several biomedical computational algorithms were conducted to identify pathways enriched by genes with prognostic splicing events and construct regulatory network dominated by splicing factors. Functional enrichment analysis suggested that prognostic splicing events are associated with several energy metabolism-related processes. Based on these prognostic events, several prognostic signatures were developed.

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