Title of article :
Systematic Identification of Survival-Associated Alternative Splicing Events in Kidney Renal Clear Cell Carcinoma
Author/Authors :
Wei, Yubin Department of Molecular Medicine and Cancer Research Center - Chongqing Medical University - Chongqing, China , Zhang, Zheng Department of Molecular Medicine and Cancer Research Center - Chongqing Medical University - Chongqing, China , Peng, Rui Department of Bioinformatics - Chongqing Medical University - Chongqing, China , Sun, Yan Department of Molecular Medicine and Cancer Research Center - Chongqing Medical University - Chongqing, China , Zhang, Luyu Department of Molecular Medicine and Cancer Research Center - Chongqing Medical University - Chongqing, China , Liu, Handeng Department of Molecular Medicine and Cancer Research Center - Chongqing Medical University - Chongqing, China
Abstract :
There is growing evidence that aberrant alternative splicing (AS) is highly correlated with driving tumorigenesis, but its function in
kidney renal clear cell carcinoma (KIRC) remains to be discovered. In this study, we obtained the level-3 RNA sequencing and
clinical data of KIRC from The Cancer Genome Atlas (TGCA). Combining with the splicing event detail information from
TGCA SpliceSeq database, we established the independent prognosis signatures for KIRC with the univariate and multivariate
Cox regression analyses. Then, we used the Kaplan-Meier analysis and receiver operating characteristic curves (ROCs) to assess
the accuracy of prognosis signatures. We also constructed the regulatory network of splicing factors (SFs) and AS events. Our
results showed that a total of 12029 survival-associated AS events of 5761 genes were found in 524 KIRC patients. All types of
prognosis signatures displayed a satisfactory ability to reliably predict, especially in exon skip model which the area under curve
of ROC was 0.802. Moreover, 18 splicing factors (SFs) highly correlated to AS events were identified. With the construction of
the SF-AS interactive network, we found that SF powerfully promotes the occurrence of abnormal AS and may have a profound
role in KIRC. Collectively, we screened survival-associated AS events and established prognosis signatures for KIRC, coupling
with the SF-AS interactive network, which might provide a key perspective to clarify the potential mechanism of AS in KIRC.
Keywords :
Survival-Associated , Cell , Kidney , KIRC
Journal title :
Computational and Mathematical Methods in Medicine