Abstract
BACKGROUND: Cancer stem cells (CSCs) are crucial contributors to the development and progression of esophageal cancer (ESCA). This study utilized single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) to identify gene signatures of CSCs in ESCA, aiming to construct a prognostic tumor stem cell marker signature (TSCMS) model. METHODS: We analyzed scRNA-seq and RNA-seq data of ESCA. CytoTRACE was used to quantify the stemness of tumor-derived epithelial cell clusters. The TSCMS model was developed using Lasso-Cox regression, and its prognostic significance was evaluated via Kaplan-Meier survival analysis, Cox regression, and ROC curve analysis. Drug response predictions were conducted using the pRRophetic package. Functional studies of TSPO in ESCA cells included bioinformatics analysis, quantitative reverse transcription PCR (qRT-PCR), Western blotting, immunohistochemistry, and cell proliferation assays. RESULTS: Distinct cell cluster stemness potentials were identified using CytoTRACE. The TSCMS model consists of 18 tumor stemness-related genes. High-risk patients showed reduced immune and ESTIMATE scores, along with elevated tumor purity. Notable differences in immune infiltration and chemotherapy sensitivity were observed between risk groups. TSPO was found to be positively correlated with RNA expression-based stemness scores in various tumors, including ESCA. Its expression was diminished in ESCA cell lines and clinical tumor tissues, with low expression correlating with poor prognosis. Overexpression of TSPO inhibits the proliferation of ESCA cells and the formation of tumor clones. In a mouse model of esophageal carcinoma in situ, TSPO expression was significantly lower than in normal tissues. CONCLUSION: This study underscores the prognostic significance of the TSCMS model in ESCA, elucidates the immune landscape and treatment response, and identifies TSPO as a potential therapeutic target.