ENST00000489707.5 Is a Preferred Alternative Splicing Variant of PTK7 in Adrenocortical Cancer and Shows Potential Prognostic Value.
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ABSTRACT:
SUBMITTER: Bie J
PROVIDER: S-EPMC6857428 | biostudies-literature | 2019 Nov
REPOSITORIES: biostudies-literature
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Project description:BackgroundThis paper aims to identify alternative RNA splicing landscape and its prognostic value in adrenocortical carcinoma.MethodsThe alternative splicing events data with corresponding clinical information data of 79 ACC patients were obtained from the Cancer Genome Atlas and SpliceSeq package. Prognosis-associated AS events by using univariate Cox regression analysis were selected. Gene functional enrichment analysis demonstrated the potential pathways enriched by survival-associated AS. Prognosis-related splicing events were submitted to develop moderate predictors using Lasso regression model.ResultsOne thousand five survival-associated alternative splicing events were identified. The prognostic genes included ATXN2L, MEIS1, IKBKB, COX4I1. Functional enrichment analysis suggested that prognostic splicing events are associated with Wnt signaling pathway. A prediction model including 12 alternative splicing events was constructed by Lasso regression using train set. ROC analysis showed good performance of the prediction model in test set. Then, a nomogram integrating the clinical-pathological factors and riskscore was constructed for predicting 1- and 3-year survival rate.ConclusionOur data provide a comprehensive bioinformatics analysis of AS events in ACC, providing biomarkers for disease progression and a potentially rich source of novel therapeutic targets.
| S-EPMC7994755 | biostudies-literature
Project description:Alternative splicing is involved in the pathogenesis of human diseases, including cancer. Here, we investigated the potential application of alternative splicing events (ASEs) and splicing factors (SFs) in the prognosis of adrenocortical carcinoma (ACC). Transcriptome data from 79 ACC cases were downloaded from The Cancer Genome Atlas database, and percent spliced-in values of seven splicing types were downloaded from The Cancer Genome Atlas SpliceSeq database. By the univariate Cox regression analysis, 1,839 survival-related ASEs were identified. Prognostic indices based on seven types of survival-related ASEs were calculated by multivariate Cox regression analysis. Survival curves and receiver operating characteristic curves were used to assess the diagnostic value of the prognostic model. Independent prognosis analysis identified several ASEs (e.g., THNSL2| 54469| ME) that could be used as biomarkers to predict the prognosis of patients with ACC accurately. By analyzing the co-expression correlation between SFs and ASEs, 188 highly correlated interactions were established. From the protein interaction network, we finally screened six hub SFs, including YBX1, SART1, PRCC, SNRPG, SNRPE, and SF3B4, whose expression levels were significantly related to the overall survival and prognosis of ACC. Our findings provide a reliable model for predicting the prognosis of ACC patients based on aberrant alternative splicing patterns.
| S-EPMC7494975 | biostudies-literature
Project description:Background:Increasing evidence suggests that aberrant alternative splicing (AS) events are associated with progression of cancer. This study evaluated the prognostic value and clarify the role of AS events in cervical cancer (CC). Methods:Based on RNA-seq AS event data and clinical information of CC patients in The Cancer Genome Atlas (TCGA) database, we sought to identify prognosis-related AS events in this setting. We selected several survival-associated AS events to construct a prognostic predictor for CC through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. Moreover, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed on genes with prognosis-related AS events and constructed an AS-splicing factors (SFs) regulatory network. Results:2770 AS events were significantly correlated with overall survival (OS). The area under the curve (AUC) values of receiver-operator characteristic curve (ROC) for the final prognostic predictor were 0.926, 0.946 and 0.902 at 3, 5, and 10 years, respectively. These values indicated efficiency in prognostic risk stratification for patients with CC. The final prognostic predictor was an independent predictor of OS (HR: 1.24; 95% CI: 1.020-1.504; P < 0.05). The AS-SFs correlation network may reveal an underlying regulatory mechanism of AS events. Conclusion:AS events are essential participants in the prognosis of CC and hold great potentials for the prognostic stratification and development of treatment strategy.
| S-EPMC7394696 | biostudies-literature
Project description:Breast cancer has the highest mortality and morbidity among women, especially in elderly women over 60 years old. Abnormal alternative splicing (AS) events are associated with the occurrence and development of geriatric breast cancer (GBC), yet strong evidence is lacking for the prognostic value of AS in GBC and the regulatory network of AS in GBC, which may highlight the mechanism through which AS contributes to GBC. In the present study, we obtained splicing event information (SpliceSeq) and clinical information for GBC from The Cancer Genome Atlas, and we constructed a GBC prognosis model based on AS events to predict the survival outcomes of GBC. Kaplan-Meier analysis was conducted to evaluate the predictive accuracy among different molecular subtypes of GBC. We conducted enrichment analysis and constructed a splicing network between AS and the splicing factor (SF) to examine the possible regulatory mechanisms of AS in GBC. We constructed eight prognostic signatures with very high statistical accuracy in predicting GBC survival outcomes from 45,421 AS events of 10,480 genes detected in 462 GBC patients; the prognostic model based on exon skip (ES) events had the highest accuracy, indicating its significant value in GBC prognosis. The constructed regulatory SF-AS network may explain the potential regulatory mechanism between SF and AS, which may be the mechanism through which AS events contribute to GBC survival outcomes. The findings confirm that AS events have a significant prognostic value in GBC, and we found a few effective prognostic signatures. We also hypothesized the mechanism underlying AS in GBC and discovered a potential regulatory mechanism between SF and AS.
| S-EPMC7074345 | biostudies-literature
Project description:Alternative splicing (AS), an important post-transcriptional regulatory mechanism that regulates the translation of mRNA isoforms and generates protein diversity, has been widely demonstrated to be associated with oncogenic processes. In this study, we systematically analyzed genome-wide AS patterns to explore the prognostic implications of AS in endometrial cancer (EC). A total of 2,324 AS events were identified as being associated with the overall survival of EC patients, and eleven of these events were further selected using a random forest algorithm. With the implementation of a generalized, boosted regression model, a prognostic AS model that aggregated these eleven markers was ultimately established with high performance for risk stratification in EC patients. Functional analysis of these eleven AS markers revealed various potential signaling pathways implicated in the progression of EC. Splicing network analysis demonstrated the notable correlation between the expression of splicing factors and AS markers in EC and further determined eight candidate splicing factors that could be therapeutic targets for EC. Taken together, the results of this study present the utility of AS profiling in identifying biomarkers for the prognosis of EC and provide comprehensive insight into the molecular mechanisms involved in EC processes.
| S-EPMC6889075 | biostudies-literature
Project description:Importance:The risk stratification of adrenocortical carcinoma (ACC) based on tumor proliferation index and stage is limited. Adjuvant therapy after surgery is recommended for most patients. Pan-genomic studies have identified distinct molecular groups closely associated with outcome. Objective:To compare the molecular classification for prognostic assessment of ACC with other known prognostic factors. Design, Setting, and Participants:In this retrospective biomarker analysis, ACC tumor samples from 368 patients who had undergone surgical tumor removal were collected from March 1, 2005, to September 30, 2015 (144 in the training cohort and 224 in the validation cohort) at 21 referral centers with a median follow-up of 35 months (interquartile range, 18-74 months). Data were analyzed from March 2016 to March 2018. Exposures:Meta-analysis of pan-genomic studies (transcriptome, methylome, chromosome alteration, and mutational profiles) was performed on the training cohort. Targeted biomarker analysis, including targeted gene expression (BUB1B and PINK1), targeted methylation (PAX5, GSTP1, PYCARD, and PAX6), and targeted next-generation sequencing, was performed on the training and validation cohorts. Main Outcomes and Measures:Disease-free survival. Cox proportional hazards regression and C indexes were used to assess the prognostic value of each model. Results:Of the 368 patients (mean [SD] age, 49 [16] years), 144 were in the training cohort (100 [69.4%] female) and 224 were in the validation cohort (142 [63.4%] female). In the training cohort, pan-genomic measures classified ACC into 3 molecular groups (A1, A2, and A3-B), with 5-year survival of 9% for group A1, 45% for group A2, and 82% for group A3-B (log-rank P?<?.001). Molecular class was an independent prognostic factor of recurrence in stage I to III ACC after complete surgery (hazard ratio, 55.91; 95% CI, 8.55-365.40; P?<?.001). The combination of European Network for the Study of Adrenal Tumors (ENSAT) stage, tumor proliferation index, and molecular class provided the most discriminant prognostic model (C index, 0.88). In the validation cohort, the molecular classification, determined by targeted biomarker measures, was confirmed as an independent prognostic factor of recurrence (hazard ratio, 5.96 [95% CI, 1.81-19.58], P?=?.003 for the targeted classifier combining expression, methylation, and chromosome alterations; and 2.61 [95% CI, 1.31-5.19], P?=?.006 for the targeted classifier combining methylation, chromosome alterations, and mutational profile). The prognostic value of the molecular markers was limited for patients with stage IV ACC. Conclusions and Relevance:The findings suggest that in localized ACC, targeted classifiers may be used as independent markers of recurrence. The determination of molecular class may improve individual prognostic assessment and thus may spare unnecessary adjuvant treatment.
| S-EPMC6624825 | biostudies-literature
Project description:Alternative splicing (AS), an essential process for the maturation of mRNAs, is involved in tumorigenesis and tumor progression, including angiogenesis, apoptosis, and metastasis. AS changes can be frequently observed in different tumors, especially in geriatric lung adenocarcinoma (GLAD). Previous studies have reported an association between AS events and tumorigenesis but have lacked a systematic analysis of its underlying mechanisms. In the present study, we obtained splicing event information from SpliceSeq and clinical information regarding GLAD from The Cancer Genome Atlas. Survival-associated AS events were selected to construct eight prognostic index (PI) models. We also constructed a correlation network between splicing factors (SFs) and survival-related AS events to identify a potential molecular mechanism involved in regulating AS-related events in GLAD. Our study findings confirm that AS has a strong prognostic value for GLAD and sheds light on the clinical significance of targeting SFs in the treatment of GLAD.
| S-EPMC7569206 | biostudies-literature
Project description:BACKGROUND:Previously developed classifications of glioma have provided enormous advantages for the diagnosis and treatment of glioma. Although the role of alternative splicing (AS) in cancer, especially in glioma, has been validated, a comprehensive analysis of AS in glioma has not yet been conducted. In this study, we aimed at classifying glioma based on prognostic AS. METHODS:Using the TCGA glioblastoma (GBM) and low-grade glioma (LGG) datasets, we analyzed prognostic splicing events. Consensus clustering analysis was conducted to classified glioma samples and correlation analysis was conducted to characterize regulatory network of splicing factors and splicing events. RESULTS:We analyzed prognostic splicing events and proposed novel splicing classifications across pan-glioma samples (labeled pST1-7) and across GBM samples (labeled ST1-3). Distinct splicing profiles between GBM and LGG were observed, and the primary discriminator for the pan-glioma splicing classification was tumor grade. Subtype-specific splicing events were identified; one example is AS of zinc finger proteins, which is involved in glioma prognosis. Furthermore, correlation analysis of splicing factors and splicing events identified SNRPB and CELF2 as hub splicing factors that upregulated and downregulated oncogenic AS, respectively. CONCLUSION:A comprehensive analysis of AS in glioma was conducted in this study, shedding new light on glioma heterogeneity and providing new insights into glioma diagnosis and treatment.
| S-EPMC6858651 | biostudies-literature
Project description:Alternative splicing events (ASEs) play a role in cancer development and progression. We investigated whether ASEs are prognostic for overall survival (OS) in hepatocellular carcinoma (HCC). RNA sequencing data was obtained for 343 patients included in The Cancer Genome Atlas. Matched splicing event data for these patients was then obtained from the TCGASpliceSeq database, which includes data for seven types of ASEs. Univariate and multivariate Cox regression analysis demonstrated that 3,814 OS-associated splicing events (OS-SEs) were correlated with OS. Prognostic indices were developed based on the most significant OS-SEs. The prognostic index based on all seven types of ASEs (PI-ALL) demonstrated superior efficacy in predicting OS of HCC patients at 2,000 days compared to those based on single ASE types. Patients were stratified into two risk groups (high and low) based on the median prognostic index. Kaplan-Meier survival analysis demonstrated that PI-ALL had the greatest capacity to distinguish between patients with favorable vs. poor outcomes. Finally, univariate Cox regression analysis demonstrated that the expression of 23 splicing factors was correlated with OS-SEs in the HCC cohort. Our data indicate that a prognostic index based on ASEs is prognostic for OS in HCC.
| S-EPMC6660027 | biostudies-literature
Project description:Signal transducer and activator of transcription 3 (STAT3) plays a central role in the activation of multiple oncogenic pathways. Splicing variant STAT3? uses an alternative acceptor site within exon 23 that leads to a truncated isoform lacking the C-terminal transactivation domain. Depending on the context, STAT3? can act as a dominant-negative regulator of transcription and promote apoptosis. We show that modified antisense oligonucleotides targeted to a splicing enhancer that regulates STAT3 exon 23 alternative splicing specifically promote a shift of expression from STAT3? to STAT3?. Induction of endogenous STAT3? leads to apoptosis and cell-cycle arrest in cell lines with persistent STAT3 tyrosine phosphorylation compared with total STAT3 knockdown obtained by forced splicing-dependent nonsense-mediated decay (FSD-NMD). Comparison of the molecular effects of splicing redirection to STAT3 knockdown reveals a unique STAT3? signature, with a down-regulation of specific targets (including lens epithelium-derived growth factor, p300/CBP-associated factor, CyclinC, peroxisomal biogenesis factor 1, and STAT1?) distinct from canonical STAT3 targets typically associated with total STAT3 knockdown. Furthermore, similar in vivo redirection of STAT3 alternative splicing leads to tumor regression in a xenograft cancer model, demonstrating how pharmacological manipulation of a single key splicing event can manifest powerful antitumorigenic properties and validating endogenous splicing reprogramming as an effective cancer therapeutic approach.
| S-EPMC3203802 | biostudies-other