Cancer stem cells (CSCs) are crucial for lung adenocarcinoma (LUAD). This study investigates tumor stem cell gene signatures in LUAD using single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq), aiming to develop a prognostic tumor stem cell marker signature (TSCMS) model. LUAD scRNA-seq and RNA-seq data were analyzed. CytoTRACE software quantified the stemness score of tumor-derived epithelial cell clusters. Gene Set Variation Analysis (GSVA) identified potential biological functions in different clusters. The TSCMS model was constructed using Lasso-Cox regression, and its prognostic value was assessed through Kaplan–Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses. Immune infiltration was evaluated using the Cibersortx algorithm, and drug response prediction was performed using the pRRophetic package. TAF10 functional investigations in LUAD cells involved bioinformatics analysis, qRT-PCR, Western blot, immunohistochemistry, and assays for cell proliferation. Seven distinct cell clusters were identified by CytoTRACE, with epithelial cell cluster 1 (Epi_C1) showing the highest stemness potential. The TSCMS model included 49 tumor stemness-related genes; high-risk patients exhibited lower immune and ESTIMATE scores and increased tumor purity. Significant differences in immune landscapes and chemotherapy sensitivity were observed between risk groups. TAF10 positively correlated with RNA expression-based stemness scores in various tumors, including LUAD. It was over-expressed in LUAD cell lines and clinical tumor tissues, with high expression linked to poor prognosis. Silencing TAF10 inhibited LUAD cell proliferation and tumor sphere formation. This study demonstrates the TSCMS model's prognostic value in LUAD, reveals insights into immune infiltration and therapeutic response, and identifies TAF10 as a potential therapeutic target.

Background: Small cell lung cancer (SCLC) is an aggressive malignancy with limited treatment options and poor prognosis, underscoring the need for new therapeutic agents.Methods: A library of 640 natural products was screened for anti-proliferative activity in SCLC cells. The effects of Cepharanthine (CE) on SCLC cells were assessed in vitro and in vivo. Network pharmacology and RNA sequencing (RNA-seq) were used to elucidate the molecular mechanisms. Pathway enrichment analysis was performed using Gene Set Enrichment Analysis (GSEA) with Hallmark and Reactome gene sets. Protein-protein interaction (PPI) networks, along with the Cytoscape cytoHubba plugin, were used to identify key hub genes. RT-PCR and Western blotting were employed to validate mRNA and protein expression. Molecular docking studies assessed the binding affinity of CE to potential targets. Bioinformatics analyses, including expression profiling, prognostic evaluation, and loss-of-function studies, were used to explore the role of specific genes in SCLC.Results: CE was identified as a promising SCLC inhibitor. In vitro, CE significantly inhibited SCLC cell proliferation, colony formation, migration, and invasion, while promoting apoptosis. In vivo, CE treatment notably reduced tumor volume in xenograft models. Network pharmacology identified 60 potential target genes, with enrichment analysis indicating their involvement in cholesterol metabolism regulation. RNA-seq and experimental validation further confirmed that CE inhibits cholesterol synthesis in SCLC cells by downregulating key enzymes, including HMGCR, HMGCS1, IDI1, FDFT1, and SQLE. Molecular docking studies confirmed the binding of CE to these enzymes. Additionally, these enzymes were found to be highly expressed in SCLC cells, with elevated levels of HMGCS1, HMGCR, and IDI1 correlating with poor prognosis. Functional assays revealed that silencing these genes significantly suppressed SCLC cell proliferation.Conclusion: This study identifies CE as a potential therapeutic agent for SCLC, acting through the suppression of cholesterol synthesis, and uncovers novel therapeutic targets for the treatment of this aggressive cancer.

PurposeIn this study, we sought to explore the function of seven important enzymes(MSMO1, EBP, HMGCS1, IDI2, DHCR7, FDFT1, and SQLE) involved in cholesterol biosynthesis especially SQLE in PDAC therapy. Methods and results The TCGA and Oncomine dataset were used to explore the expression of the seven enzymes in normal and cancerous pancreatic individual, and their anti-proliferation efficiency against PDAC cells was measured by cell viability assay. Expression level and prognostic values of SQLE were evaluated by western blot and Kaplan-Meier analysis. The influence of SQLE knockdown by shRNA in PDAC cells was assessed by Transwell, colony formation and cell cycle analysis. RNA-seq and GSEA were utilized to investigate the potential mechanisms. The synergistic effect of SQLE inhibitor, terbinafine, combined with six chemotherapeutic drugs in PDAC cells was tested by CCK-8 method. We demonstrated that downregulation of those enzymes especially SQLE significantly suppressed PDAC cells survival. SQLE was upregulated in PDAC cell lines, and the elevated level of SQLE is correlated with poor prognosis in pancreatic cancer samples. SQLE knockdown could significantly inhibit the proliferation and migration of PDAC cells. Cell cycle was blocked in S phase after SQLE silencing. Mechanistically, GSEA analysis with RNA-seq data revealed that SQLE silencing negatively mediated mTORC1 and TNFα/NF-κB signaling pathways. Besides, SQLE inhibitor terbinafine enhanced chemotherapeutic sensitivity of the six compounds. ConclusionsThis study demonstrated that SQLE is a novel target for PDAC therapy. The synergism role of SQLE inhibition and chemotherapy may be potential therapeutic strategies for pancreatic cancer treatment.