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.

scholarly journals GENE-49. RNA PROCESSING GENES CHARACTERIZE RNA SPLICING AND FURTHER STRATIFY LOWER-GRADE GLIOMA

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi108-vi108
Author(s):  
Rui-Chao Chai ◽  
tao jiang ◽  
Yong-Zhi Wang
Keyword(s):  
Alternative Splicing ◽  
Risk Score ◽  
Rna Processing ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Validation Dataset ◽  
Lower Grade ◽  
Aberrant Expression ◽  
Alternative Splicing Events ◽  
Genome Atlas

Abstract Aberrant expression of RNA processing genes may drive the alterative RNA profile in lower-grade gliomas (LGGs). Thus, we aimed to further stratify LGGs based on the expression of RNA processing genes. This study included 446 LGGs from The Cancer Genome Atlas (TCGA, training set) and 171 LGGs from the Chinese Glioma Genome Atlas (CGGA, validation set). The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was conducted to develop a risk-signature. The ROC curves and Kaplan–Meier curves were used to study the prognosis value of the risk-signature. Among the tested 784 RNA processing genes, 276 were significantly correlated with the OS of LGGs. Further LASSO Cox regression identified a 19-gene risk-signature, whose risk score was also an independently prognosis factor (P< 0.0001, multiplex Cox regression) in the validation dataset. The signature had better prognostic value than the traditional factors “age”, “grade” and “WHO 2016 classification” for 3‐ and 5‐year survival both two datasets (AUCs > 85%). Importantly, the risk-signature could further stratify the survival of LGGs in specific subgroups of WHO 2016 classification. Furthermore, alternative splicing events for genes such as EGFR and FGFR were found to be associated with the risk score. RNA expression levels for genes, which participated in cell proliferation and other processes, were significantly correlated to the risk score. Our results highlight the role of RNA processing genes for further stratifying the survival of patients with LGGs and provide insight into the alternative splicing events underlying this role.

scholarly journals Implementation of exon arrays: alternative splicing during T-cell proliferation as determined by whole genome analysis

BMC Genomics ◽  
2010 ◽  
Vol 11 (1) ◽  
Author(s):  
Toni Whistler ◽  
Cheng-Feng Chiang ◽  
William Lonergan ◽  
Mark Hollier ◽  
Elizabeth R Unger
Keyword(s):  
Cell Proliferation ◽  
Alternative Splicing ◽  
T Cell ◽  
Genome Analysis ◽  
T Cell Proliferation ◽  
Whole Genome ◽  
Whole Genome Analysis ◽  
Exon Arrays

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.

scholarly journals Ral GEF with the PH Domain and SH3 Binding Motif 1 Regulated by Splicing Factor Junction Plakoglobin and Pyrimidine Metabolism Are Prognostic in Uterine Carcinosarcoma

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Hongjun Guo ◽  
Siqiao Wang ◽  
Aiqing Xie ◽  
Wenhuizi Sun ◽  
Chenlu Wei ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Risk Score ◽  
Cox Regression ◽  
Multivariate Model ◽  
The Cancer Genome Atlas ◽  
Binding Motif ◽  
Uterine Carcinosarcoma ◽  
Pyrimidine Metabolism ◽  
Cox Regression Analysis ◽  
Alternative Splicing Events

Uterine carcinosarcoma (UCS) is a highly invasive malignant tumor that originated from the uterine epithelium. Many studies suggested that the abnormal changes of alternative splicing (AS) of pre-mRNA are related to the occurrence and metastasis of the tumor. This study investigates the mechanism of alternative splicing events (ASEs) in the tumorigenesis and metastasis of UCS. RNA-seq of UCS samples and alternative splicing event (ASE) data of UCS samples were downloaded from The Cancer Genome Atlas (TCGA) and TCGASpliceSeq databases, several times. Firstly, we performed the Cox regression analysis to identify the overall survival-related alternative splicing events (OSRASEs). Secondly, a multivariate model was applied to approach the prognostic values of the risk score. Afterwards, a coexpressed network between splicing factors (SFs) and OSRASEs was constructed. In order to explore the relationship between the potential prognostic signaling pathways and OSRASEs, we fabricated a network between these pathways and OSRASEs. Finally, validations from multidimension platforms were used to explain the results unambiguously. 1,040 OSRASEs were identified by Cox regression. Then, 6 OSRASEs were incorporated in a multivariable model by Lasso regression. The area under the curve (AUC) of the receiver operator characteristic (ROC) curve was 0.957. The risk score rendered from the multivariate model was corroborated to be an independent prognostic factor ( P < 0.001 ). In the network of SFs and ASEs, junction plakoglobin (JUP) noteworthily regulated RALGPS1-87608-AT ( P < 0.001 , R = 0.455 ). Additionally, RALGPS1-87608-AT ( P = 0.006 ) showed a prominent relationship with distant metastasis. KEGG pathways related to prognosis of UCS were selected by gene set variation analysis (GSVA). The pyrimidine metabolism ( P < 0.001 , R = − 0.470 ) was the key pathway coexpressed with RALGPS1. We considered that aberrant JUP significantly regulated RALGPS1-87608-AT and the pyrimidine metabolism pathway might play a significant part in the metastasis and prognosis of UCS.

scholarly journals Integrated analysis of methylation-driven genes and pretreatment prognostic factors in patients with hepatocellular carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dongsheng He ◽  
Shengyin Liao ◽  
Lifang Cai ◽  
Weiming Huang ◽  
Xuehua Xie ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Factors ◽  
Risk Score ◽  
Prognostic Model ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Integrated Analysis ◽  
Calibration Plot ◽  
Clinical Parameters ◽  
T Stage

Abstract Background The potential reversibility of aberrant DNA methylation indicates an opportunity for oncotherapy. This study aimed to integrate methylation-driven genes and pretreatment prognostic factors and then construct a new individual prognostic model in hepatocellular carcinoma (HCC) patients. Methods The gene methylation, gene expression dataset and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Methylation-driven genes were screened with a Pearson’s correlation coefficient less than − 0.3 and a P value less than 0.05. Univariable and multivariable Cox regression analyses were performed to construct a risk score model and identify independent prognostic factors from the clinical parameters of HCC patients. The least absolute shrinkage and selection operator (LASSO) technique was used to construct a nomogram that might act to predict an individual’s OS, and then C-index, ROC curve and calibration plot were used to test the practicability. The correlation between clinical parameters and core methylation-driven genes of HCC patients was explored with Student’s t-test. Results In this study, 44 methylation-driven genes were discovered, and three prognostic signatures (LCAT, RPS6KA6, and C5orf58) were screened to construct a prognostic risk model of HCC patients. Five clinical factors, including T stage, risk score, cancer status, surgical method and new tumor events, were identified from 13 clinical parameters as pretreatment-independent prognostic factors. To avoid overfitting, LASSO analysis was used to construct a nomogram that could be used to calculate the OS in HCC patients. The C-index was superior to that from previous studies (0.75 vs 0.717, 0.676). Furthermore, LCAT was found to be correlated with T stage and new tumor events, and RPS6KA6 was found to be correlated with T stage. Conclusion We identified novel therapeutic targets and constructed an individual prognostic model that can be used to guide personalized treatment in HCC patients.

scholarly journals Alternative splicing acts as an independent prognosticator in ovarian carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yan Ouyang ◽  
Kaide Xia ◽  
Xue Yang ◽  
Shichao Zhang ◽  
Li Wang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Regression Analysis ◽  
Alternative Splicing ◽  
Ovarian Carcinoma ◽  
Cancer Patients ◽  
Cox Regression ◽  
Excision Repair ◽  
Splicing Factors ◽  
Prognostic Signature ◽  
Cox Regression Analysis

AbstractAlternative splicing (AS) events associated with oncogenic processes present anomalous perturbations in many cancers, including ovarian carcinoma. There are no reliable features to predict survival outcomes for ovarian cancer patients. In this study, comprehensive profiling of AS events was conducted by integrating AS data and clinical information of ovarian serous cystadenocarcinoma (OV). Survival-related AS events were identified by Univariate Cox regression analysis. Then, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to construct the prognostic signatures within each AS type. Furthermore, we established a splicing-related network to reveal the potential regulatory mechanisms between splicing factors and candidate AS events. A total of 730 AS events were identified as survival-associated splicing events, and the final prognostic signature based on all seven types of AS events could serve as an independent prognostic indicator and had powerful efficiency in distinguishing patient outcomes. In addition, survival-related AS events might be involved in tumor-related pathways including base excision repair and pyrimidine metabolism pathways, and some splicing factors might be correlated with prognosis-related AS events, including SPEN, SF3B5, RNPC3, LUC7L3, SRSF11 and PRPF38B. Our study constructs an independent prognostic signature for predicting ovarian cancer patients’ survival outcome and contributes to elucidating the underlying mechanism of AS in tumor development.

scholarly journals Whole-genome analysis uncovers loss of blaZ associated to carriage isolates belonging to MRSA clone ST5-VI in Cape Verde

2021 ◽  
Author(s):  
Magdalena Wysocka ◽  
Tamar Monteiro ◽  
Carine de Pina ◽  
Deisy Gonçalves ◽  
Sandrine de Pina ◽  
...  
Keyword(s):  
Genome Analysis ◽  
Cape Verde ◽  
Whole Genome ◽  
Whole Genome Analysis
Sign in / Sign up

Export Citation Format

Share Document