Integration of single-cell and bulk RNA sequencing to identify a distinct tumor stem cells and construct a novel prognostic signature for evaluating prognosis and immunotherapy in LUAD

Abstract

Abstract Background Cancer stem cells (CSCs) play a crucial role in the progression of lung adenocarcinoma (LUAD).This study aimed to explore the gene signatures of tumor stem cells in LUAD through Single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing (RNA-seq) data, and establish a tumor stem cell marker signature(TSCMS)prognostic risk model. Methods The LUAD scRNA-seq data and bulk RNA-seq data from the GEO and TCGA databases were collected. CytoTRACE software was used to quantify the stemness score of tumor-derived epithelial cell clusters. Gene Set Variation Analysis (GSVA) was performed to identify potential biological functions in different clusters. The TSCMS prognostic risk model was constructed using Lasso-Cox regression analysis, and its prognostic value was assessed through Kaplan-Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses. The Cibersortx algorithm was used to evaluate immune infiltration, and drug response prediction was conducted using the pRRophetic package. Functional investigations of TAF10 in LUAD cells were performed using bioinformatics analysis, qRT-PCR, Western blot, Immunohistochemistry, cell proliferation and clone formation assay. Results Seven distinct cell clusters were identified by CytoTRACE (Epi C1 to C7), with Epi C1 demonstrating the highest stemness potential. The TSCMS prognostic risk model incorporated 49 tumor stemness-related genes, and high-risk patients exhibited reduced immune scores, lower ESTIMATE scores, and increased tumor purity. Furthermore, significant differences in immune landscapes and chemotherapy sensitivity were observed between high and low risk groups. TAF10 was found to be positively correlated with the RNA expression-based stemness score (RNAss) in various tumors, including LUAD. And we demonstrated that TAF10 was over-expressed in LUAD cell lines and tumor tissues of clinical patients, and high TAF10 expression was correlated with poor prognosis in LUAD patients. Silencing TAF10 inhibited LUAD cell proliferation and clone formation. Conclusions Our investigation highlights the prognostic utility of the TSCMS model for evaluating the clinical outcomes of LUAD patients, uncovering critical insights into immune cell infiltration and therapeutic response, and positions TAF10 as a novel therapeutic target for LUAD.