Abstract

BackgroundA growing number of investigations have suggested a close link between cancer stem cells (CSCs), epithelial-to-mesenchymal transition (EMT), and the tumor microenvironment (TME). However, the relationships between these physiological processes in bladder urothelial carcinoma (BLCA) remain unclear.MethodsWe first explored biomarkers of tumor stemness (TS) by single-cell sequencing analysis. Then, subtypes of bladder urothelial carcinoma (BLCA) were identified using clustering analysis based on TS biomarkers. The TS score was constructed using principal component analysis to quantify tumor stemness in BLCA. Then, meta-analysis was performed to measure the hazard ratio of the TS score in BLCA cohorts. Moreover, we evaluated the clinical value of the TS score for predicting the response to tumor immunotherapy using immunotherapy cohorts. Finally, we built an EMT cell model by treating T24 cells with TGF-β and validated the relationship between the TS score and the EMT process in tumors by real-time quantitative PCR, cell invasion assays, and RNA-seq. In total, 3846 BLCA cells, 6 cell lines, 1627 BLCA samples, and 9858 samples from 32 other types of tumors were included in our study.ResultsThree TS clusters and two TS-related gene clusters were identified with differential EMT activity status, CSC features, and TME characteristics in BLCA. Then, a TS scoring system was established with 61 TS-related genes to quantify the TS. The prognostic value of the TS score was then confirmed in multiple independent cohorts. A high TS score was associated with high EMT activity, CSC characteristics, high stromal cell content, high TP53 mutation rate, poor prognosis, and high tumor immunotherapy tolerance. The cell line experiment and RNA-seq further validated that our TS score can reflect the EMT and CSC characterization of tumor cells.ConclusionOverall, this research provides a better understanding of tumor invasion and metastasis mechanisms through an analysis of TS patterns with different EMT processes and CSC characteristics. The TS score provides an index for EMT and CSC research and helps clinicians develop treatment plans and predict outcomes for patients.

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