Songying Zhang

GANT61 Modulates Autophagy and Lipid Metabolism in Ovarian Cancer

GANT61 induced autophagy via the AKT pathway and promoted the accumulation of lipid droplets in both cell lines. The molecular mechanism behind this lipid accumulation appears to involve the mediation of SREBP1. Furthermore, the combination of GANT61 with CQ/Fatostatin significantly inhibited the proliferation and clonogenicity of SKOV3 and SKOV3PTX cells.

The Sonic Hedgehog signaling pathway regulates autophagy and migration in ovarian cancer

AbstractBackgroundThe Sonic Hedgehog (SHH) signaling pathway plays an important role in various types of human cancers including ovarian cancer; however, its function and underlying mechanism in ovarian cancer are still not entirely understood.MethodsWe detected the expressions of SHH and SQSTM1 in borderline ovarian tumor tissues, epithelial ovarian cancer (EOC) tissues and benign ovarian tumor tissues. Cyclopamine (Cyp, a well‐known inhibitor of SHH signaling pathway) and chloroquine (CQ, the pharmaceutical inhibitor of autophagy) were used in vivo and in vitro (autophagic flux, CCK‐8 assay, wound healing assay, transwell assay, tumor xenograft model). The mechanism of action was explored through Quantitative RT‐PCR and Western Blot.ResultsWe found up‐regulation of SHH and accumulation of SQSTM1/P62 in epithelial ovarian cancer. Cyp induced autophagy through the PI3K/AKT signaling pathway. Moreover, low‐dose Cyp and chloroquine (CQ) significantly promoted the migratory ability of SKOV3 cells.ConclusionsOur findings suggest that inhibition of the SHH pathway and autophagy may be a potential and effective therapy for the treatment of ovarian cancer.

A Novel Eight-Gene Signature for Lipid Metabolism Predicts the Progression of Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Recently, studies on the mechanisms underlying lipid metabolic reprogramming in cancer have increased. However, its significance in cervical cancer remains unclear. In the present study, a prognostic signature was constructed for patients with cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) using the expression profiles of lipid metabolism-related genes (LMRGs). Furthermore, using various bioinformatics methods, a prognostic gene signature was developed for progression-free survival (PFS). This signature was externally validated using a cervical cancer dataset (GSE44001). The characteristics of the molecular subgroups of LMRGs were analyzed, and target LMRGs were identified via differential gene analysis of the expression profiles and weighted gene correlation network analysis. Thereafter, the identified target genes were used to develop the prognostic gene signature using univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses. The performance of the LMRG signature was evaluated using Kaplan-Meier curves, time-dependent receiver operating characteristic curves, decision curve analysis, mutation landscapes, gene set enrichment analysis, and immune score calculation. As a result, a novel eight-LMRG signature comprising ALDH3B2, CERS3, FA2H, GLTP, NR1H3, PLIN3, SLC44A3, and SQLE was constructed. Using this gene signature, patients with CESC and significantly distinguished PFS were divided. This eight-LMRG signature exhibited independent prognostic potential and superior predictive performance compared with a previously developed 12-gene signature. Our findings suggest that our novel eight-LMRG signature contributes to the implementation of precision medicine strategies for managing patients with cervical cancer by facilitating CESC prognosis.