%0 Figure %A Wu, Zhipeng %A Liu, Jinhui %A Sun, Rui %A Chen, Dongming %A Wang, Kai %A Cao, Changchun %A Xu, Xianlin %D 2020 %T Image_3_A Novel Prognostic Index Based on Alternative Splicing in Papillary Renal Cell Carcinoma.pdf %U https://frontiersin.figshare.com/articles/figure/Image_3_A_Novel_Prognostic_Index_Based_on_Alternative_Splicing_in_Papillary_Renal_Cell_Carcinoma_pdf/11744232 %R 10.3389/fgene.2019.01333.s003 %2 https://frontiersin.figshare.com/ndownloader/files/21388062 %K alternative splicing %K prognostic index %K papillary renal cell carcinoma %K splicing factor %K The Cancer Genome Atlas %X Background

Papillary renal cell carcinoma (pRCC) is a heterogeneous multifocal or isolated tumor with an invasive phenotype. Previous studies presented that alternative splicing, as a crucial posttranscriptional regulator in gene expression, is associated with tumorigenesis. However, the association between alternative splicing and pRCC has not been clarified

Methods

The RNA sequencing data and clinical information were downloaded from The Cancer Genome Atlas database and mRNA splicing profiles from TCGASpliceSeq. The percent spliced in data of alternative splicing merged with survival information was firstly calculated by univariate Cox regression analysis to screen for survivalā€associated alternative splicing events, and survivalā€associated alternative splicing events were then analyzed by Gene Ontology categories using Kyoto Encyclopedia of Genes and Genomes. Meanwhile, the least absolute shrinkage and selection operator Cox analysis and multivariate Cox analysis were performed to calculate the prognostic index for each alternative splicing type. In addition, clinical factors were introduced to assess the performance of prognostic index.

Results

A total of 4,084 candidate survival-associated alternative splicing events in 2,558 genes were screened out. Patients were divided into the low-risk group and the high-risk group based on the median prognostic index value. The Kaplan-Meier survival analysis (p < 0.05) and receiver operating characteristics curves (AUC>0.9) indicated that prognostic index was effective and stable for predicting the prognosis of pRCC patients. Furthermore, a regulatory network was constructed incorporating alternative splicing events and survival-associated splicing factors.

Conclusion

Our study provides new insights into the mechanism of alternative splicing events in tumorigenesis and their clinical potential for pRCC.

%I Frontiers