Dataset Information

Modulator-Dependent RBPs Changes Alternative Splicing Outcomes in Kidney Cancer.

ABSTRACT: Alternative splicing alterations can contribute to human disease. The ability of an RNA-binding protein to regulate alternative splicing outcomes can be modulated by a variety of genetic and epigenetic mechanisms. In this study, we use a computational framework to investigate the roles of certain genes, termed modulators, on changing RBPs' effect on splicing regulation. A total of 1,040,254 modulator-mediated RBP-splicing interactions were identified, including 137 RBPs, 4,309 splicing events and 2,905 modulator candidates from TCGA-KIRC RNA sequencing data. Modulators function categories were defined according to the correlation changes between RBPs expression and their targets splicing outcomes. QKI, as one of the RBPs influencing the most splicing events, attracted our attention in this study: 2,014 changing triplets were identified, including 1,101 modulators and 187 splicing events. Pathway enrichment analysis showed that QKI splicing targets were enriched in tight junction pathway, endocytosis and MAPK signaling pathways, all of which are highly associated with cancer development and progression. This is the first instance of a comprehensive study on how alternative splicing outcomes changes are associated with different expression level of certain proteins, even though they were regulated by the same RBP. Our work may provide a novel view on understanding alternative splicing mechanisms in kidney cancer.

SUBMITTER: Wang Y

PROVIDER: S-EPMC7113372 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Modulator-Dependent RBPs Changes Alternative Splicing Outcomes in Kidney Cancer.

Wang Yang Y Chen Steven X SX Rao Xi X Liu Yunlong Y

Frontiers in genetics 20200326

Alternative splicing alterations can contribute to human disease. The ability of an RNA-binding protein to regulate alternative splicing outcomes can be modulated by a variety of genetic and epigenetic mechanisms. In this study, we use a computational framework to investigate the roles of certain genes, termed modulators, on changing RBPs' effect on splicing regulation. A total of 1,040,254 modulator-mediated RBP-splicing interactions were identified, including 137 RBPs, 4,309 splicing events an ...[more]

PMID: 32273884

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Project description:BackgroudCancer stemness is associated with metastases in kidney renal clear cell carcinoma (KIRC) and negatively correlates with immune infiltrates. Recent stemness evaluation methods based on the absolute expression have been proposed to reveal the relationship between stemness and cancer. However, we found that existing methods do not perform well in assessing the stemness of KIRC patients, and they overlooked the impact of alternative splicing. Alternative splicing not only progresses during the differentiation of stem cells, but also changes during the acquisition of the stemness features of cancer stem cells. There is an urgent need for a new method to predict KIRC-specific stemness more accurately, so as to provide help in selecting treatment options.MethodsThe corresponding RNA-Seq data were obtained from the The Cancer Genome Atlas (TCGA) data portal. We also downloaded stem cell RNA sequence data from the Progenitor Cell Biology Consortium (PCBC) Synapse Portal. Independent validation sets with large sample size and common clinic pathological characteristics were obtained from the Gene Expression Omnibus (GEO) database. we constructed a KIRC-specific stemness prediction model using an algorithm called one-class logistic regression based on the expression and alternative splicing data to predict stemness indices of KIRC patients, and the model was externally validated. We identify stemness-associated alternative splicing events (SASEs) by analyzing different alternative splicing event between high- and low- stemness groups. Univariate Cox and multivariable logistic regression analysisw as carried out to detect the prognosis-related SASEs respectively. The area under curve (AUC) of receiver operating characteristic (ROC) was performed to evaluate the predictive values of our model.ResultsHere, we constructed a KIRC-specific stemness prediction model with an AUC of 0.968,and to provide a user-friendly interface of our model for KIRC stemness analysis, we have developed KIRC Stemness Calculator and Visualization (KSCV), hosted on the Shiny server, can most easily be accessed via web browser and the url https://jiang-lab.shinyapps.io/kscv/ . When applied to 605 KIRC patients, our stemness indices had a higher correlation with the gender, smoking history and metastasis of the patients than the previous stemness indices, and revealed intratumor heterogeneity at the stemness level. We identified 77 novel SASEs by dividing patients into high- and low- stemness groups with significantly different outcome and they had significant correlations with expression of 17 experimentally validated splicing factors. Both univariate and multivariate survival analysis demonstrated that SASEs closely correlated with the overall survival of patients.ConclusionsBasing on the stemness indices, we found that not only immune infiltration but also alternative splicing events showed significant different at the stemness level. More importantly, we highlight the critical role of these differential alternative splicing events in poor prognosis, and we believe in the potential for their further translation into targets for immunotherapy.

Dataset Information

Modulator-Dependent RBPs Changes Alternative Splicing Outcomes in Kidney Cancer.

Publications

Modulator-Dependent RBPs Changes Alternative Splicing Outcomes in Kidney Cancer.

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