Prognostic Alternative mRNA Splicing in Adrenocortical Carcinoma.
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ABSTRACT: Background
This paper aims to identify alternative RNA splicing landscape and its prognostic value in adrenocortical carcinoma.Methods
The 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.Results
One 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.Conclusion
Our 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.
SUBMITTER: Liang W
PROVIDER: S-EPMC7994755 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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.
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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.
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Project description:BackgroundIncreasing evidence indicated a close relationship between aberrant splicing variants and carcinoma, whereas comprehensive analysis of prognostic alternative splicing (AS) profiling in breast cancer (BRCA) is lacking and largely unknown.MethodsRNA-seq data and corresponding clinical information of BRCA patients were obtained and integrated from The Cancer Genome Atlas (TCGA). Then SpliceSeq software was used to assess seven AS types and calculate the Percent Spliced In (PSI) value. Univariate followed by stepwise multivariate Cox regression analyses identified survival associated AS events and constructed the AS signature, which were further sent for enrichment analysis, respectively. Besides, the splicing correlation network was constructed. Additionally, nomogram incorporating AS signature and clinicopathological characteristics was developed and its efficacy was evaluated with respect to discrimination, calibration and clinical utility.ResultsA total of 45,421 AS events were detected, among which 3071 events were found associated with overall survival (OS) after strict filtering. Parent genes of these prognostic events were involved in BRCA-related processes including NF-kappaB and HIF-1 signaling pathway. Besides, the final prognostic signature built with 20 AS events performed well with an area under the curve (AUC) of receiver operating characteristic (ROC) curve up to 0.957 for 5 years. And gene set enrichment analysis (GSEA) also confirmed the candidate 20 AS events contributed to progression of BRCA. Moreover, the nomogram that incorporated 20-AS-event-based classifier, age, pathological stage and Her-2 status showed good calibration and moderate discrimination, with C-index of 0.883 (95% CI, 0.844-0.921). Decision curve analysis (DCA) confirmed more benefit was added to survival prediction with our nomogram, especially in 5 or 8 years with threshold probability up to 80%. Finally, splicing correlation network revealed an obvious regulatory pattern of prognostic splicing factors (SF) in BRCA.ConclusionThis study provided a systematic portrait of survival-associated AS events involved in BRCA and further presented a AS-clinicopathological nomogram, which could be conveniently used to assist the individualized prediction of long-term survival probability for BRCA patients. And a series of bioinformatic analysis provided a promising perspective for further uncovering the underlying mechanisms of AS events and validating therapeutic targets for BRCA.
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Project description:RNA-binding motif protein 25 (RBM25) is a poorly characterized RNA-binding protein that is involved in several biological processes and regulates the proliferation and metastasis of tumor cells. The regulatory role of RBM25 in hepatocellular carcinoma (HCC) is unknown. Here, RBM25 expression and outcomes in HCC patients were evaluated using The Cancer Genome Atlas database. RBM25 was overexpressed in HCC patients compared with the healthy group. The high expression of RBM25 in tumor tissues was significantly related to poor overall survival (P<0.001). Overexpression of RBM25 significantly contributed to poorer survival in male patients and N0 stage patients (P<0.001). Spearman analysis and weighted gene co-expression network analysis identified 694 RBM25-related genes. Protein-protein interaction network analysis revealed the Cluster with the highest score, which positively correlated with RBM25. CDCA5 and INCENP were identified as the core functional genes related to RBM25. The overexpression of CDCA5 and INCENP in HCC patients was examined using the Human Protein Atlas database. The findings collectively indicated that RBM25 may interact with CDCA5 and INCENP to regulate HCC. Our detailed characterization of RBM25 protein interactions and related core functional genes provides a basis for further studies aimed at identifying molecular regulatory pathways or splicing events.
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Project description:BackgroundHepatocellular carcinoma (HCC) ranks the sixth prevalent tumors with high mortality globally. Alternative splicing (AS) drives protein diversity, the imbalance of which might act an important factor in tumorigenesis. This study aimed to construct of AS-based prognostic signature and elucidate the role in tumor immune microenvironment (TIME) and immunotherapy in HCC.MethodsUnivariate Cox regression analysis was performed to determine the prognosis-related AS events and gene set enrichment analysis (GSEA) was employed for functional annotation, followed by the development of prognostic signatures using univariate Cox, LASSO and multivariate Cox regression. K-M survival analysis, proportional hazards model, and ROC curves were conducted to validate prognostic value. ESTIMATE R package, ssGSEA algorithm and CIBERSORT method and TIMER database exploration were performed to uncover the context of TIME in HCC. Quantitative real-time polymerase chain reaction was implemented to detect ZDHHC16 mRNA expression. Cytoscape software 3.8.0 were employed to visualize AS-splicing factors (SFs) regulatory networks.ResultsA total of 3294 AS events associated with survival of HCC patients were screened. Based on splicing subtypes, eight AS prognostic signature with robust prognostic predictive accuracy were constructed. Furthermore, quantitative prognostic nomogram was developed and exhibited robust validity in prognostic prediction. Besides, the consolidated signature was significantly correlated with TIME diversity and ICB-related genes. ZDHHC16 presented promising prospect as prognostic factor in HCC. Finally, the splicing regulatory network uncovered the potential functions of splicing factors (SFs).ConclusionHerein, exploration of AS patterns may provide novel and robust indicators (i.e., risk signature, prognostic nomogram, etc.,) for prognostic prediction of HCC. The AS-SF networks could open up new approach for investigation of potential regulatory mechanisms. And pivotal players of AS events in context of TIME and immunotherapy efficiency were revealed, contributing to clinical decision-making and personalized prognosis monitoring of HCC.
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Project description:BACKGROUND This study aimed to explore the transcript preference of PTK7 in adrenocortical cancer (ACC), the prognostic value, and the potential underlying genetic alterations. MATERIAL AND METHODS Data from the Cancer Genome Atlas-Adrenocortical Cancer (TCGA-ACC) and the Genotype-Tissue Expression (GTEx)-normal adrenal gland were used for analysis. RESULTS A non-canonical alternative transcript, ENST00000489707.5, which only encodes an extracellular immunoglobulin (Ig)-like domain and an intracellular kinase domain, is the dominant isoform of PTK7 in both ACC and normal adrenal gland. Its expression percentage was significantly higher in ACC than in normal adrenal gland. ACC tissues showed preferred expression of this transcript compared with other cancers with known PTK7 expression. Prognostic analysis showed that ENST00000489707.5 had independent prognostic value in progression-free survival (PFS) (HR: 1.227, 95%CI: 1.077-1.398, p=0.002) and disease-specific survival (DSS) (HR: 1.419, 95%CI: 1.154-1.745, p=0.001) after adjustment of other risk factors. cg20819617 methylation was negatively correlated with both PTK7 and ENST00000489707.5 expression. CONCLUSIONS ENST00000489707.5 is a preferred alternative splicing product of PTK7, with a significantly increased proportion in ACC compared with other cancers. Its expression shows potential prognostic value in terms of PFS and DSS in ACC patients. The methylation status of cg20819617 might play a critical role in modulating PTK7 transcription and ENST00000489707.5 expression.
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Project description:Alternative splicing (AS) has been widely reported to play an important role in cancers, including esophageal carcinoma (ESCA). However, no study has comprehensively investigated the clinical use of combination of prognostic AS events and clinicopathological parameters. Therefore, we collected 165 ESCA patients including 83 esophageal adenocarcinoma (EAC) and 82 esophageal squamous cell carcinoma (ESCC) patients from The Cancer Genome Atlas to explore the survival rate associated with seven types of AS events. Prognostic predictors for the clinical outcomes of ESCA patients were built. Predictive prognosis models of the alternative acceptor site in ESCA (area under the curve [AUC] = 0.83), alternative donor site in EAC (AUC = 0.99), and alternative terminator site in ESCC (AUC = 0.974) showed the best predictive efficacy. A novel combined prognostic model of AS events and clinicopathological parameters in ESCA was also constructed. Combined prognostic models of ESCA all showed better predictive efficacy than independent AS models or clinicopathological parameters model. Through constructing splicing regulatory network, the expression of AS factor was found to be negatively correlated with the most favorable AS events. Moreover, gene amplification, mutation, and copy number variation of AS genes were commonly observed, which may indicate the molecular mechanism of how the AS events influence survival. Conclusively, the constructed prognostic models based on AS events, especially the combined prognostic models of AS signatures and clinicopathological parameters could be used to predict the outcome of ESCA patients. Moreover, the splicing regulatory network and genomic alteration in ESCA could be used for illuminating the potential molecular mechanism.
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Project description:BackgroundIncreasing 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).MethodsBased 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.Results2770 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.ConclusionAS 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:PurposeAdrenocortical carcinoma (ACC) is an aggressive tumor characterized by a high recurrence rate and poor response to treatment. This study analyzes a consecutive series of ACC patients to evaluate the prognostic value of various clinical and pathological characteristics.MethodsWe retrospectively evaluated 32 ACC patients followed at our Medical Center from 1997 to 2015 and evaluated the prognostic value of age at diagnosis, gender, tumor functional status, stage, and type of treatment with respect to overall survival (OS) and disease-free survival (DFS), as determined by Kaplan-Meier curves.ResultsACC was associated with hormonal overproduction in 50% of cases, and patients with isolated hyperandrogenism had a better prognosis. Recurrence was observed in 12/26 (46.2%) patients with no evidence of disease after surgery. Tumor size [hazard ratio (HR) 1.32, 95% confidential intervals (CI) 1.12-1.64; p = 0.007], ki-67 (HR 1.06, 95% CI 1.02-1.11; p = 0.009) and advanced stage at diagnosis (III-IV) (HR 6.51, 95% CI 1.65-24.68; p = 0.006) were associated with recurrence in the 26 R0 patients in the univariate analysis. Advanced stage was an independent risk factor for recurrence in the multivariate analysis (HR 8.10, 95% CI 1.55-41.35; p = 0.01). Five-year survival was 40.0%. Positive resection margins (HR 10.61, 95% CI 3.02-38.31; p = < 0.001), ki-67 (HR 1.04, 95% CI 1.01-1.07; p = 0.01) and advanced stage (HR 11.31, 95% CI 1.45-87.76; p = 0.02) were associated with poor survival in all 32 patients, but only positive resection margins were an independent predictor of mortality in the multivariate analysis (HR 6.22, 95% CI 1.44-26.05; p = 0.01).ConclusionACC has a poor prognosis with a high recurrence rate. Tumor stage at diagnosis and the completeness of surgical excision are the most relevant prognostic factors.
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