Dataset Information

An eight-mRNA signature predicts the prognosis of patients with bladder urothelial carcinoma.

ABSTRACT:

Background

Bladder cancer is one of the most common cancers, and its histopathological type is mainly bladder urothelial carcinoma, accounting for about 90%. The prognostic biomarkers of bladder cancer are classified into clinical features biomarkers and molecular biomarkers. Nevertheless, due to the existence of individual specificity, patients with similar pathological characteristics still have great differences in the risk of disease recurrence. Therefore, it is often inaccurate to predict the survival status of patients based on clinical characteristic biomarkers, and a prognostic molecular biomarker that can grade the risk of bladder cancer patients is needed.

Methods

A total of three bladder urothelial carcinoma datasets were used in this study from the Cancer Genome Atlas database and Gene Expression Omnibus database. In order to avoid overfitting, all samples were randomly divided into one training set and three validation sets, which were used to construct and test the prognostic biomarker model of bladder urothelial carcinoma. Univariate and multivariate Cox regression were used to screen candidate mRNAs and construct prognostic biomarkers model. Kaplan-Meier survival analysis and the receiver operating characteristic (ROC) curve were used to evaluate the predictive performance of the model.

Results

A prognostic biomarker model of bladder urothelial carcinoma combining with eight mRNA was constructed. Kaplan-Meier analyses indicated that a significant difference in the survival time of patients between the high-risk and the low-risk group. The area under the ROC curve were 0.632 (95% confidence interval (CI) [0.541-0.723]), 0.693 (95% CI [0.601-0.784]) and 0.686 (95% CI [0.540-0.831]) when the model was used to predict the patient's survival time in three validation datasets. The model showed high accuracy and applicability.

SUBMITTER: Zhu R

PROVIDER: S-EPMC6814068 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

An eight-mRNA signature predicts the prognosis of patients with bladder urothelial carcinoma.

Zhu Rui R Yang Xin X Guo Wenna W Xu Xin-Jian XJ Zhu Liucun L

PeerJ 20191022

<h4>Background</h4>Bladder cancer is one of the most common cancers, and its histopathological type is mainly bladder urothelial carcinoma, accounting for about 90%. The prognostic biomarkers of bladder cancer are classified into clinical features biomarkers and molecular biomarkers. Nevertheless, due to the existence of individual specificity, patients with similar pathological characteristics still have great differences in the risk of disease recurrence. Therefore, it is often inaccurate to p ...[more]

PMID: 31660264

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Project description:Pentatricopeptide repeat domain 1 (PTCD1) was reported to regulate mitochondrial metabolism and oxidative phosphorylation. However, the effect and mechanism of PTCD1 in the development of bladder urothelial carcinoma (BLCA) remain unclear. The databases from The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) were used to analyze the expression changes, clinical features, and prognostic values of PTCD1. A nomogram was built to predict the prognostic outcomes of BLCA cases. The potential genes interacting with PTCD1 were explored by Weighted Gene Coexpression Network Analysis (WGCNA). The estimation of associations between PTCD1 and tumor mutations, tumor immunities, and m6A methylations was performed. The study found that the gradual decrease of PTCD1 expression was observed with the increase of stage and grade. Low PTCD1 expression was greatly correlated with higher pathological stage, N stage, and poor prognosis in TCGA cohorts; interestingly, low-grade BLCA cases all exhibited high expression of PTCD1. HPA database analysis implied that the expression of PTCD1 protein in BLCA was lower than that in normal bladder tissue, and the protein expression of PTCD1 in high-grade BLCA was lower than that in low-grade BLCA. Multivariate Cox regression analysis indicated that PTCD1 may serve as an independent factor influencing prognosis of BLCA. Mechanistically, PTCD1 played a regulatory role in BLCA progression through multiple tumor-related pathways containing PI3K-Akt signaling, ECM-receptor interaction, oxidative phosphorylation, and extracellular matrix organization. WGCNA reported that PTCD1 had a strong positive correlation with POLR2J, ZNHT1, ATP5MF, PDAP1, BUD31, and COPS6. Besides, the mRNA expression of PTCD1 was negatively associated with immune cells' infiltrations, immune functions, and checkpoints, especially with some m6A methylation regulators in BLCA. In sum, downregulation of PTCD1 expression may be involved in the development of BLCA and remarkably correlated with poor prognosis. Meantime, it showed an influence in immune cell infiltration and may serve as an agreeable prognostic indicator in BLCA.

Project description:Background: The TP53 tumor suppressor gene plays a crucial role in the carcinogenesis of many malignancies, including urothelial carcinoma (UC). Overexpression of p53 is associated with poor prognosis in UC. Recently, RING finger protein 128 (RNF128) was shown to be involved in p53-induced apoptosis, forming a negative feedback loop. However, the significance of RNF128 in patients with UC remains unknown. In this study, our aim was to evaluate the expression of RNF128 in UC and to assess its predictive and prognostic value in a well-established cohort. Methods: Through data mining from a published transcriptome (GSE31684), RNF128 was identified as the most differentially expressed gene in UC among those associated with negative regulation of the cytokine biosynthetic process (GO:0042036). Its immunoexpression was further evaluated using the H-scores of 340 patients with upper urinary tract UC (UTUC) and 295 with urinary bladder UC (UBUC). The scores were correlated with clinicopathological features, disease-specific survival (DSS) and metastasis-free survival (MeFS). We also used Western blot analysis to evaluate RNF128 protein expression in human urothelial cell (HUC) lines. Results: Downregulation of RNF128 expression was significantly associated with advanced pT stage (p<0.001), high histological grade (UTUC, p<0.001; UBUC, p=0.035), nodal metastasis (UTUC, p<0.001; UBUC, p=0.001), vascular invasion (UTUC, p<0.001; UBUC, p=0.008) and high mitotic rate (UTUC, p=0.003; UBUC, p=0.023). Low expression of RNF128 was an adverse prognosticator for DSS (UTUC, p<0.0001; UBUC, p<0.0001) and MeFS (UTUC, p<0.0001; UBUC, p=0.0002). Moreover, low expression was predictive of poor DSS (UTUC, p=0.006; UBUC, p=0.003) and MeFS (UTUC, p=0.009; UBUC, p=0.036) in multivariate comparisons. Western blot analysis showed that the RNF128 protein was downregulated in invasive urothelial cancer cell lines. Conclusion: Our findings showed that downregulation of RNF128 was correlated with cancer invasiveness and metastasis as well as reduced survival in patients with UTUC and UBUC, identifying RNF128 as a prognostic factor in UC.

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Project description:Epithelial membrane protein 1 (EMP1) is a key gene that regulates cell proliferation and metastatic capability in various types of cancer, and serves an important role in tumor-immune interactions. However, the association between EMP1 and clinical prognosis, as well as the presence of tumor-infiltrating lymphocytes in bladder urothelial carcinoma (BLCA) remains unclear. The present study aimed to explore the relationship between EMP1 expression and tumor immune cell infiltration in BLCA. In the present study, EMP1 expression in BLCA was analyzed using the Oncomine database, The Cancer Genome Atlas (TCGA) and the Tumor Immune Estimation Resource (TIMER). The effects of EMP1 on clinical prognosis were evaluated using the Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis. The correlations between EMP1, cancer immune infiltrates and lymphocyte abundance were determined using the TIMER and Tumor immune system interaction database. In addition, correlations between EMP1 expression and gene markers in immune infiltrates were analyzed using cBioportal. The results demonstrated that, compared with adjacent normal tissues, EMP1 was downregulated in BLCA tissues. High expression of EMP1 was significantly associated with poor overall survival (OS) in BLCA cases obtained from TCGA. Multivariate Cox analysis revealed that EMP1 was an independent predictor of OS in patients with BLCA. Gene set enrichment analysis revealed that EMP1 was associated with cancer-related pathways and was positively correlated with the levels of infiltrating CD8+ T cells, macrophages, neutrophils and dendritic cells in BLCA. Further analysis demonstrated that EMP1 was significantly associated with the enrichment of multiple types of lymphocyte. EMP1 expression exhibited a strong correlation with a range of immune markers in BLCA. In conclusion, the results of the present study demonstrated that EMP1 was associated with a poor prognosis in patients with BLCA, and that the levels of immune infiltration and multiple immunomarker groups were associated with EMP1 expression. These results suggested that EMP1 may be used as a predictive biomarker to determine the prognosis and immune infiltration in BLCA.

Project description:Background: Ferroptosis is closely related to the occurrence and development of cancer. An increasing number of studies have induced ferroptosis as a treatment strategy for cancer. However, the predictive value of ferroptosis-related lncRNAs in bladder cancer (BC) still need to be further elucidated. The purpose of this study was to construct a predictive signature based on ferroptosis-related long noncoding RNAs (lncRNAs) to predict the prognosis of BC patients. Methods: We downloaded RNA-seq data and the corresponding clinical and prognostic data from The Cancer Genome Atlas (TCGA) database and performed univariate and multivariate Cox regression analyses to obtain ferroptosis-related lncRNAs to construct a predictive signature. The Kaplan-Meier method was used to analyze the overall survival (OS) rate of the high-risk and low-risk groups. Gene set enrichment analysis (GSEA) was performed to explore the functional differences between the high- and low-risk groups. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the relationship between the predictive signature and immune status. Finally, the correlation between the predictive signature and the treatment response of BC patients was analyzed. Results: We constructed a signature composed of nine ferroptosis-related lncRNAs (AL031775.1, AL162586.1, AC034236.2, LINC01004, OCIAD1-AS1, AL136084.3, AP003352.1, Z84484.1, AC022150.2). Compared with the low-risk group, the high-risk group had a worse prognosis. The ferroptosis-related lncRNA signature could independently predict the prognosis of patients with BC. Compared with clinicopathological variables, the ferroptosis-related lncRNA signature has a higher diagnostic efficiency, and the area under the receiver operating characteristic curve was 0.707. When patients were stratified according to different clinicopathological variables, the OS of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the high-risk group. ssGSEA showed that the predictive signature was significantly related to the immune status of BC patients. High-risk patients were more sensitive to anti-PD-1/L1 immunotherapy and the conventional chemotherapy drugs sunitinib, paclitaxel, cisplatin, and docetaxel. Conclusion: The predictive signature can independently predict the prognosis of BC patients, provides a basis for the mechanism of ferroptosis-related lncRNAs in BC and provides clinical treatment guidance for patients with BC.

Dataset Information

An eight-mRNA signature predicts the prognosis of patients with bladder urothelial carcinoma.

Background

Methods

Results

Publications

An eight-mRNA signature predicts the prognosis of patients with bladder urothelial carcinoma.

Similar Datasets

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