Te Liu

Anisomycin Induces Senescence and Death of Ovarian Cancer Stem Cells Through the MicroRNA‐340/SENP6/SUMOylation Pathway

ABSTRACT Ovarian cancer remains a leading cause of gynecologic cancer mortality, in part due to the persistence of ovarian cancer stem cells (OCSCs) that drive tumor recurrence, metastasis, and drug resistance. Anisomycin, a natural antibiotic derived from Streptomyces coelicolor , has previously been shown to exert antitumor effects, but the mechanisms by which it targets OCSCs remain unclear. In this study, primary human OCSCs were isolated and treated with anisomycin to investigate its biological and molecular effects. Cell proliferation, apoptosis, migration, and colony formation were assessed in vitro, and tumorigenicity was evaluated in xenograft mouse models. Transcriptomic, biochemical, and molecular assays were performed to identify downstream pathways. Anisomycin treatment markedly inhibited proliferation and promoted senescence and cell death of OCSCs. Mechanistically, anisomycin induced upregulation of microRNA‐340, which in turn suppressed the deSUMOylating enzyme SENP6. This repression increased SUMOylation of key senescence‐related proteins, including p53 and p16, leading to stabilization of their expression and enforcement of cell‐cycle arrest. Overexpression of microRNA‐340 reproduced these effects, both in vitro and in vivo, confirming its central role in mediating anisomycin activity. Bioinformatic analyses further revealed that expression of SENP6 and senescence‐associated genes correlated with disease progression and patient survival in ovarian cancer cohorts. These findings identify a previously unrecognized epigenetic mechanism by which anisomycin induces senescence and death in OCSCs, suggesting that targeting the microRNA‐340/SENP6/SUMOylation pathway may represent a promising therapeutic approach.

Construction and validation of molecular subtype and signature of immune cell‐related telomeric genes and prediction of prognosis and immunotherapy efficacy in ovarian cancer patients

AbstractBackgroundOvarian cancer (OVC) has emerged as a fatal gynecological malignancy as a result of a lack of reliable methods for early detection, limited biomarkers and few treatment options. Immune cell‐related telomeric genes (ICRTGs) show promise as potential biomarkers.MethodsICRTGs were discovered using weighted gene co‐expression network analysis (WGCNA). ICRTGs were screened for significant prognosis using one‐way Cox regression analysis. Subsequently, molecular subtypes of prognosis‐relevant ICRTGs were constructed and validated for OVC, and the immune microenvironment's landscape across subtypes was compared. OVC prognostic models were built and validated using prognosis‐relevant ICRTGs. Additionally, chemotherapy susceptibility drugs for OVC patients in the low‐ and high‐risk groups of ICRTGs were screened using genomics of drug susceptibility to cancer (GDSC). Finally, the immunotherapy response in the low‐ and high‐risk groups was detected using the data from GSE78220. We conducted an immune index correlation analysis of ICRTGs with significant prognoses. The MAP3K4 gene, for which the prognostic correlation coefficient is the highest, was validated using tissue microarrays for a prognostic‐immune index correlation.ResultsWGCNA analysis constructed a gene set of ICRTGs and screened 22 genes with prognostic significance. Unsupervised clustering analysis revealed the best molecular typing for two subtypes. The Gene Set Variation Analysis algorithm was used to calculate telomere scores and validate the molecular subtyping. A prognostic model was constructed using 17 ICRTGs. In the The Cancer Genome Atlas‐OVC training set and the Gene Expression Omnibus validation set (GSE30161), the risk score model's predicted risk groups and the actual prognosis were shown to be significantly correlated. GDSC screened Axitinib, Bexarotene, Embelin and the GSE78220 datasets and demonstrated that ICRTGs effectively distinguished the group that responds to immunotherapy from the non‐responsive group. Additionally, tissue microarray validation results revealed that MAP3K4 significantly predicted patient prognosis. Furthermore, MAP3K4 exhibited a positive association with PD‐L1 and a negative relationship with the M1 macrophage markers CD86 and INOS.ConclusionsICRTGs may be reliable biomarkers for the molecular typing of patients with OVC, enabling the prediction of prognosis and immunotherapy efficacy.