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Research Paper|Volume 12, Issue 6|pp 4996—5009

Identification of survival-associated alternative splicing events and signatures in adrenocortical carcinoma based on TCGA SpliceSeq data

Ning Xu1, Zhi-Bin Ke1, Xiao-Dan Lin1, Fei Lin1, Shao-Hao Chen1, Yu-Peng Wu1, Ye-Hui Chen1, Yong Wei1, Qing-Shui Zheng1
  • 1Departments of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
* Equal contribution
Received: December 11, 2019Accepted: March 2, 2020Published: March 26, 2020
https://doi.org/10.18632/aging.102924

Copyright © 2020 Xu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Objective: To explore the correlations among alternative splicing (AS), splicing factors (SF) and survival outcome in adrenocortical carcinoma (ACC) patients.

Results: A total of 92 ACC patients were included. Univariate analysis identified 3919 AS events significantly associated with overall survival. Lasso method followed by multivariate analysis revealed that the prognostic capacity of these survival-related AS events is satisfactory. Interestingly, we found that the area under the curve (AUC) of AA, AD, AP and RI were more than 0.9, indicating that these four types of AS were of great significance. Independent prognostic analysis showed that only the risk score was the independent risk factor of ACC survival. Finally, we constructed an interesting interaction network between AS and SF.

Conclusions: This is the first and most comprehensive study to explore the aberrant AS variants in ACC, which might provide novel insights into molecular mechanism of ACC.

Methods: The transcriptome data, clinical information and Percent Spliced In (PSI) values of the ACC were obtained from TCGA database and TCGA SpliceSeq data portal. Lasso method and uni/multivariate Cox regression analysis were used to identify survival-related AS events and develop multi-AS-based signatures. The relationship between AS events and SFs was also investigated.