Dataset Information

Prognostic Significance of Lineage Diversity in Bladder Cancer Revealed by Single-Cell Sequencing.

ABSTRACT: Bladder cancer is the most common malignant tumor of the urinary system. We investigated the clinical implications of cell lineages in bladder cancer by integrating single-cell and bulk transcriptome data. By investigating the single-cell transcriptional profiles of 12,424 cells from normal bladder, eleven cell types and five types of epithelial sub-population were identified. Based on the signature of cell types identified in single-cell profiles, deconvolution analysis was employed to estimate cell types and epithelial lineages in the bulk RNA sequencing bladder cancer cohort. Cancer subtypes with clinical implications were further identified based on the heterogeneity of the epithelial lineage across patients. This study suggests that the EMT-like subtype is robustly correlated with poor prognosis and the umbrella subtype is a positive factor for the patient survival. Our research has a high potential for accurate prognostic and therapeutic stratification of bladder cancer.

SUBMITTER: Yu L

PROVIDER: S-EPMC9162490 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prognostic Significance of Lineage Diversity in Bladder Cancer Revealed by Single-Cell Sequencing.

Yu Lu L Hu Rixin R Peng Guoyu G Ding Qiuxia Q Tao Tao T Wu Song S

Frontiers in genetics 20220519

Bladder cancer is the most common malignant tumor of the urinary system. We investigated the clinical implications of cell lineages in bladder cancer by integrating single-cell and bulk transcriptome data. By investigating the single-cell transcriptional profiles of 12,424 cells from normal bladder, eleven cell types and five types of epithelial sub-population were identified. Based on the signature of cell types identified in single-cell profiles, deconvolution analysis was employed to estimate ...[more]

PMID: 35664301

Similar Datasets

Project description:Background: Pancreatic cancer (PC), the most common fatal solid malignancy, has a very dismal prognosis. Clinical computerized tomography (CT) and pathological TNM staging are no longer sufficient for determining a patient's prognosis. Although numerous studies have suggested that glycolysis is important in the onset and progression of cancer, there are few publications on its impact on PC. Methods: To begin, the single-sample gene set enrichment analysis (ssGSEA) approach was used to quantify the glycolysis pathway enrichment fraction in PC patients and establish its prognostic significance. The genes most related to the glycolytic pathway were then identified using weighted gene co-expression network analysis (WGCNA). The glycolysis-associated prognostic signature in PC patients was then constructed using univariate Cox regression and lasso regression methods, which were validated in numerous external validation cohorts. Furthermore, we investigated the activation of the glycolysis pathway in PC cell subtypes at the single-cell level, performed a quasi-time series analysis on the activated cell subtypes and then detected gene changes in the signature during cell development. Finally, we constructed a decision tree and a nomogram that could divide the patients into different risk subtypes, according to the signature score and their different clinical characteristics and assessed the prognosis of PC patients. Results: Glycolysis plays a risky role in PC patients. Our glycolysis-related signature could effectively discriminate the high-risk and low-risk patients in both the trained cohort and the independent externally validated cohort. The survival analysis and multivariate Cox analysis indicated this gene signature to be an independent prognostic factor in PC. The prognostic ROC curve analysis suggested a high accuracy of this gene signature in predicting the patient prognosis in PC. The single-cell analysis suggested that the glycolytic pathway may be more activated in epithelial cells and that the genes in the signature were also mainly expressed in epithelial cells. The decision tree analysis could effectively identify patients in different risk subgroups, and the nomograms clearly show the prognostic assessment of PC patients. Conclusion: Our study developed a glycolysis-related signature, which contributes to the risk subtype assessment of patients with PC and to the individualized management of patients in the clinical setting.

Project description:Bladder cancer is one of the leading causes of cancer-related death in men, however, there was only limited effective treatment for invasive bladder cancer. DAPK1 has been shown to play important role in apoptosis and autophagy to suppress cancer progression. Previous results have shown that DAPK1 promoter was hypermethylated in the majority of bladder cancer specimens, however, the prognostic significance of DAPK1 in bladder cancer has yet to be demonstrated. In the present study, we found that DAPK1 expression was negatively associated with tumor stage and a low level expression of DAPK1 in bladder cancer specimens were associated with shorter survival in bladder cancer patients in 3 independent bladder cancer datasets (n = 462). Further investigation showed that FGFR3 knockdown resulted in downregulation of DAPK1 in bladder cancer cell line, suggesting that FGFR3 may be an upstream factor of DAPK1. Further analysis of the 3 independent bladder cancer datasets have identified ACOX1, UPK2, TRAK1, PLEKHG6 and MT1X genes had their expression significantly correlated with that of DAPK1. Knockdown of DAPK1 in bladder cancer T24 cells resulted in downregulation of ACOX1, UPK2 and TRAK1. Interestingly, TRAK1, by itself, was a favorable prognostic marker in the 3 independent bladder cancer datasets. Importantly, by using connectivity mapping with DAPK1-associated gene signature, we found that vemurafenib and trametinib could possibly reverse DAPK1-associated gene signature, suggesting that inhibition of Raf/MEK pathway may be a potential therapeutic approach for bladder cancer. Indeed, treatment of vemurafenib in T24 bladder cancer cells resulted in upregulation of DAPK1 confirming our connectivity mapping, while knockdown of DAPK1 resulted in reduced sensitivity towards inhibition of Braf signaling by vemurafenib. Together, our results suggest that DAPK1 is an important prognostic marker and therapeutic target for bladder cancer and have identified possible therapeutic agents for future testing in bladder cancer models with low DAPK1 expression.

Dataset Information

Prognostic Significance of Lineage Diversity in Bladder Cancer Revealed by Single-Cell Sequencing.

Publications

Prognostic Significance of Lineage Diversity in Bladder Cancer Revealed by Single-Cell Sequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets