Identification and Validation of Critical Alternative Splicing Events and Splicing Factors in GC Progression in Gastric Cancer

2019 ◽  
Author(s):  
Haoran Feng ◽  
Zhijian Jin ◽  
Kun Liu ◽  
Yi Peng ◽  
Songyao Jiang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Alternative Splicing ◽  
Splicing Factors ◽  
Alternative Splicing Events

scholarly journals The epithelial splicing factors ESRP1 and ESRP2 positively and negatively regulate diverse types of alternative splicing events

RNA Biology ◽  
2009 ◽  
Vol 6 (5) ◽  
pp. 546-562 ◽  
Author(s):  
Claude C. Warzecha ◽  
Shihao Shen ◽  
Yi Xing ◽  
Russ P. Carstens
Keyword(s):  
Alternative Splicing ◽  
Splicing Factors ◽  
Alternative Splicing Events

scholarly journals Prognostic significance of survival-associated alternative splicing events in gastric cancer

Aging ◽  
2020 ◽  
Vol 12 (21) ◽  
pp. 21923-21941
Author(s):  
Shichao Zhang ◽  
Zuquan Hu ◽  
Yingwu Lan ◽  
Jinhua Long ◽  
Yun Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Alternative Splicing ◽  
Prognostic Significance ◽  
Alternative Splicing Events

scholarly journals Systematic profiling of alternative splicing events and splicing factors in left- and right-sided colon cancer

Aging ◽  
2019 ◽  
Vol 11 (19) ◽  
pp. 8270-8293 ◽  
Author(s):  
Xiaoliang Huang ◽  
Jungang Liu ◽  
Xianwei Mo ◽  
Haizhou Liu ◽  
Chunyin Wei ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Alternative Splicing ◽  
Splicing Factors ◽  
Left And Right ◽  
Alternative Splicing Events

scholarly journals Single cell characterization of CRISPR-modified transcript isoforms with nanopore sequencing

2021 ◽  
Author(s):  
Heon Seok Kim ◽  
Susan M Grimes ◽  
Anna C Hooker ◽  
Billy T Lau ◽  
Hanlee P Ji
Keyword(s):  
Alternative Splicing ◽  
Single Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Splicing Factors ◽  
Transcript Isoforms ◽  
Long Read ◽  
Cell Gene Expression ◽  
Transcript Structure ◽  
Alternative Splicing Events

Transcript isoforms are mRNAs that arise from alternative splicing events. During RNA processing, different combinations of a gene's exons lead to a diverse set of isoforms. Polymorphisms or mutations at splice junctions can generate alternative splicing events. Various splicing factors also impact the representation of a gene's transcript isoforms. To assess how these two features contribute to alternative splicing, we developed a single cell approach to introduce CRISPR edits that modify mRNA transcript structure. Our method combines (1) long-read sequencing to characterize the expressed transcripts and identify the edit at single cell resolution; (2) short-read sequencing to match the single cell gene expression profiles of the cells with the altered isoform. First, we modify target exon-intron segments with CRISPR-Cas9. Second, using cDNAs with cell barcodes, we use long read sequencing to directly identify the changes in transcript isoforms from the targeted CRISPR edits. As a variation on this approach, we also determined how modifying specific splicing factors influence isoform expression and structure. Overall, we demonstrate how the integration of single cell long read analysis and CRISPR engineering can be used to directly confirm transcript isoform and target genomic edits at single cell resolution. This approach will improve our understanding of the role of alternative splicing in transcriptional regulation.

scholarly journals Whole Genome Analysis and Prognostic Model Construction Based on Alternative Splicing Events in Endometrial Cancer

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Caixia Wang ◽  
Mingjun Zheng ◽  
Shuang Wang ◽  
Xin Nie ◽  
Qian Guo ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Alternative Splicing ◽  
Risk Score ◽  
Genome Analysis ◽  
Prognostic Model ◽  
Cox Regression ◽  
Splicing Factors ◽  
Whole Genome ◽  
Whole Genome Analysis ◽  
Alternative Splicing Events

Objectives. A growing body of evidence has shown that aberrant alternative splicing (AS) is closely related to the occurrence and development of cancer. However, prior studies mainly have concentrated on a few genes that exhibit aberrant AS. This study aimed to determine AS events through whole genome analysis and construct a prognostic model of endometrial cancer (EC). Methods. We downloaded gene expression RNAseq data from UCSC Xena, and seven types of AS events from TCGA SpliceSeq. Univariate Cox regression was employed to analyze the prognostic-related alternative splicing events (PASEs) and splicing factors; multivariate Cox regression was conducted to analyze the effect of risk score (All) and clinicopathological parameters on EC prognosis. An underlying interaction network of PASEs of EC was constructed by Cytoscape Reactome FI, GO, and KEGG pathway enrichment was performed by DAVID. ROC curves and Kaplan-Meir analysis were used to assess the diagnostic value of prognostic model. The correlation between PASEs and splicing factors was analyzed by GraphPad Prism; then a network was constructed using Cytoscape. Results. In total, 28,281 AS events in EC were identified, which consisted of 1166 PASEs. RNPS1, NEK2, and CTNNB1 were the hub genes in the network of the top 600 PASEs. The area under the curve (AUC) of risk score (All) reached 0.819. Risk score (All) together with FIGO stage, cancer status, and primary therapy outcome success was risk factors of the prognosis of EC patients. Splicing factors YBX1, HNRNPDL, and HNRNPA1 were significantly related to the overall survival (OS). The splicing network indicated that the expression of splicing factors was significantly correlated with percent-splice-in (PSI) value of PASEs. Conclusion. We constructed a model for predicting the prognosis of EC patients based on PASEs using whole genome analysis of AS events and thereby provided a reliable theoretical basis for EC clinical prognosis evaluation.

Identification of Prognostic Alternative Splicing Signature in Gastric Cancer

2021 ◽  
Author(s):  
Zhiwu Wang ◽  
Qiong Wu ◽  
Yankun Liu ◽  
Jingwu Li
Keyword(s):  
Gastric Cancer ◽  
Alternative Splicing ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Splicing Factors ◽  
Rna Seq ◽  
Oncogenic Pathways ◽  
Splicing Variants ◽  
Cancer Genome Atlas

Abstract Aberrant alternative splicing (AS) events serve as prognostic indicators in a large number of malignancies, whereas comprehensive analysis of prognostic AS in gastric cancer (GC) has not yet been understood. To identify prognostic AS events and clarify the function of the splicing variants in GC. RNA-Seq data, clinical information and percent spliced in (PSI) values were available in the cancer genome atlas (TCGA) and TCGA SpliceSeq data portal. A three-step regression method was conducted to screen prognostic AS events and construct multi-AS-based signatures. The associations between prognostic AS events and splicing factors were also investigated. We identified a total of 1318 survival related AS events in GC, Parent genes of which were implicated in numerous oncogenic pathways. The final prognostic signatures stratified by seven types of AS events or not stratified performed well in risk prediction for GC patients. Moreover, five signatures base on AA, AD, AT, ES and RI events function as independent prognostic indicators after multivariate adjustment of clinicalpathological variables. Splicing network also showed marked correlation between the expression of splicing factors and PSI value of AS events in GC patients. The AS derived signatures allow to predict GC prognosis and might serve as potential therapeutic target for GC.

scholarly journals Prognostic Signature of Alternative Splicing Events in Bladder Urothelial Carcinoma Based on Spliceseq Data from 317 Cases

2018 ◽  
Vol 48 (3) ◽  
pp. 1355-1368 ◽  
Author(s):  
Rong-quan He ◽  
Xian-guo Zhou ◽  
Qiao-yong Yi ◽  
Cai-wang Deng ◽  
Jia-min Gao ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Urothelial Carcinoma ◽  
Risk Score ◽  
Regulatory Network ◽  
Pearson Correlation ◽  
Risk Scores ◽  
Pathway Enrichment Analysis ◽  
Splicing Factors ◽  
Bladder Urothelial Carcinoma ◽  
Alternative Splicing Events

Background/Aims: Increasing evidences indicated the important roles of alternative splicing in the progression and prognosis of bladder urothelial carcinoma (BLCA). However, most previous research has focused on one or several alternative splicing events, without a comprehensive evaluation of the prognostic value of splicing events in BLCA. In this study, we aimed to determine risk scores for predicting prognosis of BLCA patients based on splicing events. Methods: RNA-sequencing data and clinical information of BLCA patients were downloaded from The Cancer Genome Atlas, and data of splicing events were obtained from the SpliceSeq database. Univariate and multivariate Cox regression analyses were employed to identify survival-associated alternative spicing events (SASEs) and to calculate risk scores. Protein-protein interaction analysis of genes of the SASEs was performed using STRING, a database of known and predicted protein-protein interactions, and pathway enrichment analysis of the genes was implemented using the Database for Annotation, Visualization and Integrated Discovery (version 6.8). Receiver operating characteristic (ROC) curves and Kaplan-Meier analysis were used to evaluate the clinical significance of genes from the SASEs for building a risk score in BLCA. Correlation between splicing events of splicing factors and non-splicing factors were analyzed with Pearson correlation coefficient. A potential regulatory network was then built using Cytoscape 3.5. Results: In total, 39,508 alternative splicing events in 317 patients with BLCA were analyzed, including 4,632 SASEs. The area under the curve of the ROC of risk score (all) was 0.748 for predicting survival status of BLCA patients. Low- and high-risk score groups classified using the median “risk score (all)” value displayed remarkably different survival time (Low vs. High = 3304.841±239.758 vs 1198.614±152.460 days). The potential regulatory network with SASEs of splicing factors and other genes was constructed, which might be part of the biological mechanisms associated with prognosis of BLCA patients. Conclusions: In this study, prognostic signatures constructed using splicing events could be used for predicting the prognosis of BLCA patients.

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