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Overexpression of MUC16 predicts favourable prognosis in MUC16-mutant cervical cancer related to immune response.

ABSTRACT: Cervical cancer (CC) is the fourth ranking gynaecologic tumour in women worldwide, with respect to both incidence and mortality. MUC16 is one of the most frequently mutated genes, which functions as a tumour marker in CC. In the present study, mutation, clinical and RNA-Seq data collected from The Cancer Genome Atlas database were used to investigate the association between MUC16 mutation, immune response and clinical prognosis in CC. mRNA expression levels from the TCGA datasets and the results from the present study demonstrated that MUC16 was overexpressed in CC samples; however, there was no difference between mutant and wild-type CC samples. Furthermore, the results indicated that patients with MUC16-mutant overexpression had a prolonged survival time. In addition, overexpression of MUC16 was associated with immune responses in the microenvironment of MUC16-mutant CC. Immune responses were upregulated in patients with early-stage MUC16-mutant. The results from the present study provided novel biomarkers for potential immunotherapy approaches for CC.

SUBMITTER: Wang H

PROVIDER: S-EPMC7388571 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Overexpression of MUC16 predicts favourable prognosis in MUC16-mutant cervical cancer related to immune response.

Wang Hao H Yan Chao C Ye Hong H

Experimental and therapeutic medicine 20200604 2

Cervical cancer (CC) is the fourth ranking gynaecologic tumour in women worldwide, with respect to both incidence and mortality. MUC16 is one of the most frequently mutated genes, which functions as a tumour marker in CC. In the present study, mutation, clinical and RNA-Seq data collected from The Cancer Genome Atlas database were used to investigate the association between MUC16 mutation, immune response and clinical prognosis in CC. mRNA expression levels from the TCGA datasets and the results ...[more]

PMID: 32765681

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Project description:Background The tumor microenvironment plays an important role in the progression and malignancy of lung adenocarcinoma and affects the immunotherapy response. There is increasing evidence that long non-coding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) have significant functions in the development and treatment response of various kinds of cancer. This study aimed to explore the association between immune-related lncRNA-microRNA (miRNA)-messenger RNA (mRNA)-ceRNA networks, and the prognosis of and immunotherapy response in lung adenocarcinoma. Methods RNA-sequencing (RNA-seq) and miRNA-seq data from The Cancer Genome Atlas (TCGA) were used to evaluate the infiltration of immune cells in lung adenocarcinoma samples by undertaking a single-sample gene set enrichment analysis (ssGSEA) to divide the cells into high and low immune cell infiltration groups. The differentially expressed mRNA (DEmRNA) was further analyzed by a weighted gene co-expression network analysis (WGCNA), search tool for recurring instances of neighboring genes (STRING), and Cytoscape to select hub genes. The ceRNA network was constructed using Cytoscape. Additionally, survival analyses were conducted to screen out prognostic candidate genes. Results Seven thousand five hundred and thirty-eight mRNAs, 540 lncRNAs, and 138 miRNAs were found to be differentially expressed between the high and low immune cell infiltration groups. The two DEmRNA modules most significantly associated with immune cell infiltration were further analyzed, and four clusters, including 179 DEmRNAs, were selected based on Molecular Complex Detection (MCODE) scores. The selected DEmRNAs in the four clusters were mainly enriched in pathways involved in regulating the immune response. Ultimately, a ceRNA network of SNHG6-hsa-miR-30e-5p-CYSLTR1 was identified as being associated with the prognosis of and immunotherapy response in lung adenocarcinoma. Conclusions The present study extends understandings of immune-related lncRNA-miRNA-mRNA-ceRNA networks and identifies novel targets and a regulatory pathway for anti-tumor immunotherapy.

Project description:Objective: Immunity plays a vital role in the human papilloma virus (HPV) persistent infection, and closely associates with occurrence and development of cervical squamous cell carcinoma (CSCC). Herein, we performed an integrated bioinformatics analysis to establish an immune-gene signature and immune-associated nomogram for predicting prognosis of CSCC patients. Methods: The list of immunity-associated genes was retrieved from ImmPort database. The gene and clinical information of CSCC patients were obtained from The Cancer Genome Atlas (TCGA) website. The immune gene signature for predicting overall survival (OS) of CSCC patients was constructed using the univariate Cox-regression analysis, random survival forests, and multivariate Cox-regression analysis. This signature was externally validated in GSE44001 cohort from Gene Expression Omnibus (GEO). Then, based on the established signature and the TCGA cohort with the corresponding clinical information, a nomogram was constructed and evaluated via Cox regression analysis, concordance index (C-index), receiver operating characteristic (ROC) curves, calibration plots and decision curve analyses (DCAs). Results: A 5-immune-gene prognostic signature for CSCC was established. Low expression of ICOS, ISG20 and high expression of ANGPTL4, SBDS, LTBR were risk factors for CSCC prognosis indicating poor OS. Based on this signature, the OS was significantly worse in high-risk group than in low-risk group (p-value < 0.001), the area under curves (AUCs) for 1-, 3-, 5-years OS were, respectively, 0.784, 0.727, and 0.715. A nomogram incorporating the risk score of signature and the clinical stage was constructed. The C-index of this nomogram was 0.76. AUC values were 0.811, 0.717, and 0.712 for 1-, 3-, 5-years OS. The nomogram showed good calibration and gained more net benefits than the 5-immune-gene signature and the clinical stage. Conclusion: The 5-immune-gene signature may serve as a novel, independent predictor for prognosis in patients with CSCC. The nomogram incorporating the signature risk score and clinical stage improved the predictive performance than the signature and clinical stage alone for predicting 1-year OS.

Project description:BACKGROUND Cervical cancer is one of the most common malignances among women globally. This study aimed to construct a novel immune-related signature to predict the prognosis and immune infiltration of cervical cancer. MATERIAL AND METHODS Transcriptomic profiles and corresponding clinical information of cervical cancer patients were obtained from The Cancer Genome Atlas (TCGA) database and GEO database. The hub immune-related genes were screened and selected using Cox regression analysis and LASSO regression analysis. A novel signature was established based on the expression levels and corresponding coefficients of the selected hub immune-related genes. Kaplan-Meier survival curve and ROC curve illustrated the prognostic value of this novel signature in cervical cancer. The predictive accuracy and stability of this novel signature were confirmed in the validation cohort, internal testing set and external testing set. Then, a nomogram was constructed to predict individual survival probability of cervical cancer patient. The association between the risk scores of novel signature and immune infiltration was investigated through single-sample gene set enrichment analysis (ssGSEA). RESULTS Ten hub immune-related genes (TFRC, SPP1, CAMP, CSF2, TUBB3, ZAP70, CHIT1, LEPR, DLL4, and DES) were selected to construct a novel signature. The risk score of this novel signature could be an independent prognostic factor in cervical cancer, which divided patients into high-risk and low-risk groups. The patients in high-risk groups showed significantly worse overall survival rates than those in low-risk groups in all training and validation cohorts (all P<0.05). A nomogram model was constructed based on the risk score of the novel signature and other clinical characteristics, which achieved the highest clinical net benefit across the entire range of reasonable threshold probabilities (concordance index=0.813). Furthermore, gene enrichment analysis revealed that the novel signature was closely related with immunology. The novel signature was negatively correlated with the infiltration of most immune cell types, especially T cell subsets (P<0.001). CONCLUSIONS The novel signature could comprehensively predict the prognosis and immune infiltration of cervical cancer. It may provide new insights for the precise treatment in cervical cancer.

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Overexpression of MUC16 predicts favourable prognosis in MUC16-mutant cervical cancer related to immune response.

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Overexpression of MUC16 predicts favourable prognosis in MUC16-mutant cervical cancer related to immune response.

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