Dataset Information

Identification and validation of an alternative splicing-based prognostic signature for head and neck squamous cell carcinoma.

ABSTRACT: Increasing evidence has demonstrated that changes in alternative splicing (AS) events are closely associated with the initiation and progression of cancer. However, the concrete role of AS in tumorigenesis of head and neck squamous cell carcinoma (HNSCC) is poorly known. In this study, we aimed to investigate the AS profile in HNSCC, and build up a robust AS-based prognostic signature for HNSCC. Our results revealed a total of 4068 overall survival (OS) associated AS events in the TCGA HNSCC cohort. The whole TCGA HNSCC cohort was randomly divided into discovery cohort and validation cohort. A prognostic signature including five AS events was developed with the discovery cohort based on the most significant OS-associated AS events. Then it was further successfully validated in the validation cohort. The AS-based risk signature was an independent prognostic indicator in both discovery cohort and validation cohort. This prognostic signature-based nomogram model showed excellent performance for predicting the OS of HNSCC. Splicing network analysis have identified the most correlated splicing factor-AS network in HNSCC. Collectively, we have constructed a robust AS-based prognostic signature which might contribute to improve the clinical outcome of HNSCC.

SUBMITTER: Zhao X

PROVIDER: S-EPMC7255372 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification and validation of an alternative splicing-based prognostic signature for head and neck squamous cell carcinoma.

Zhao Xinyuan X Si Shanshan S Li Xiaona X Sun Wenjuan W Cui Li L

Journal of Cancer 20200518 15

Increasing evidence has demonstrated that changes in alternative splicing (AS) events are closely associated with the initiation and progression of cancer. However, the concrete role of AS in tumorigenesis of head and neck squamous cell carcinoma (HNSCC) is poorly known. In this study, we aimed to investigate the AS profile in HNSCC, and build up a robust AS-based prognostic signature for HNSCC. Our results revealed a total of 4068 overall survival (OS) associated AS events in the TCGA HNSCC coh ...[more]

PMID: 32489474

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Project description:Background: Head and neck squamous cell carcinoma (HNSC) is a prevalent and heterogeneous malignancy with poor prognosis and high mortality rates. There is significant evidence of alternative splicing (AS) contributing to tumor development, suggesting its potential in predicting prognosis and therapeutic efficacy. This study aims to establish an AS-based prognostic signature in HNSC patients. Methods: The expression profiles and clinical information of 486 HNSC patients were downloaded from the TCGA database, and the AS data were downloaded from the TCGA SpliceSeq database. The survival-associated AS events were identified by conducting a Cox regression analysis and utilized to develop a prognostic signature by fitting into a LASSO-regularized Cox regression model. Survival analysis, univariate and multivariate Cox regression analysis, and receiver operating characteristic (ROC) curve analysis were performed to evaluate the signature and an independent cohort was used for validation. The immune cell function and infiltration were analyzed by CIBERSORT and the ssGSEA algorithm. Results: Univariate Cox regression analysis identified 2726 survival-associated AS events from 1714 genes. The correlation network reported DDX39B, PRPF39, and ARGLU1 as key splicing factors (SF) regulating these AS events. Eight survival-associated AS events were selected and validated by LASSO regression to develop a prognostic signature. It was confirmed that this signature could predict HNSC outcomes independent of other variables via multivariate Cox regression analysis. The risk score AUC was more than 0.75 for 3 years, highlighting the signature's prediction capability. Immune infiltration analysis reported different immune cell distributions between the two risk groups. The immune cell content was higher in the high-risk group than in the low-risk group. The correlation analysis revealed a significant correlation between risk score, immune cell subsets, and immune checkpoint expression. Conclusion: The prognostic signature developed from survival-associated AS events could predict the prognosis of HNSC patients and their clinical response to immunotherapy. However, this signature requires further research and validation in larger cohort studies.

Project description:ObjectiveHead and neck squamous cell carcinoma (HNSCC) is a highly heterotopic malignant tumor. Alternative splicing (AS) and RNA modification have been reported to be involved in tumorigenesis. Therefore, we constructed RNA modification-associated AS (RMA-AS) signature model to predict the prognosis of HNSCC.MethodsAS events and RNA-modified gene expression information were downloaded from TCGA-HNSCC database. Univariate Cox regression analysis was employed for analyzing prognosis-related AS events. RMA-AS events were obtained by constructing a coexpression network between RNA modification-associated genes and AS events using WGCNA package. The prognostic signatures were analyzed by LASSO, univariate Cox, and multivariate Cox regression. Kaplan-Meier survival analysis, proportional hazard model, and ROC curve were performed to verify the prognostic value. "ESTIMATE" R package, ssGSEA algorithm, and CIBERSORT method were used to detect immune microenvironment in HNSCC. Cytoscape was utilized to build a regulatory network of splicing factor-regulated RMA-AS.ResultsThere were 16,574 prognostic AS events and 4 differentially expressed RNA modification-associated genes in HNSCC. Based on RMA-AS events, we obtained a risk model consisting of 14 AS events, named RMA-AS_Score. The samples were divided into RMA-AS_Score high- and RMA-AS_Score low-risk groups, according to the risk score. The RMA-AS_Score high group was related to poor prognosis. Moreover, the RMA-AS_Score signature was an independent prognostic predictor and was related to tumor grade. Meanwhile, the AUC value of RMA-AS_Score was 0.652, which is better than other clinical characteristics. Besides, a nomogram prediction model of quantitative prognosis has also been developed, which has robust effectiveness in predicting prognosis. In addition, the prognostic signature was observably related to immune microenvironment and immune checkpoint. Finally, 14 splicing factors were identified and constructed into a network of splicing factor-regulated RMA-AS.ConclusionWe identified the RMA-AS signature of HNSCC. This signature could be treated as an independent prognostic predictor.

Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a life-threatening disease with poor prognosis. Pyroptosis has been recently disclosed as a programmed cell death triggered by invasive infection, involved in cancer development. However, the prognosis role of pyroptosis-related genes in HNSCC has not been discussed.MethodsThe RNA sequence data of pyroptosis-related genes were obtained from The Cancer Genome Atlas (TCGA) database. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were performed to screen the HNSCC survival-related signature genes. We established a HNSCC risk model with the identified prognostic genes, then divided the HNSCC patients into low- and high-risk subgroups according to median risk score. Moreover, we utilized Gene Expression Omnibus (GEO) dataset to validate the risk model. Go and KEGG analyses were conducted to reveal the potential function of differential expression of genes that identified between low- and high-risk subgroups. ESTIMATE algorithm was performed to investigate the immune infiltration of tumors. Correlation between signature gene expression and drug-sensitivity was disclosed by Spearman's analysis.ResultsWe constructed a HNSCC risk model with identified seven pyroptosis-related genes (CASP1, GSDME, IL6, NLRP1, NLRP2, NLRP6, and NOD2) as prognostic signature genes. High-risk subgroup of HNSCC patients in TCGA cohort correlated with lower survival probability than patients from low-risk subgroup (p < .001), and the result is verified with GEO dataset. In addition, 161 genes were identified differentially expressed between the low- and high-risk subgroups in the TCGA cohort, mainly related to immune response. Higher PD-L1 expression level was found in the high-risk subgroup that indicated the possible employment of immune checkpoint inhibitors. IL6 was positively correlated with WZ3105 and MPS-1-IN-1 in the cancer therapeutics response portal database.ConclusionWe built and verified a risk model for HNSCC prognosis using seven pyroptosis-related signature genes, which could predict the overall survival of HNSCC patients and facilitate treatment.

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.

Dataset Information

Identification and validation of an alternative splicing-based prognostic signature for head and neck squamous cell carcinoma.

Publications

Identification and validation of an alternative splicing-based prognostic signature for head and neck squamous cell carcinoma.

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