Chemoresistance is a major obstacle to the curative cancer chemotherapy and presents one of the most formidable challenges in both research and management of cancer. From the detailed studies of a multi-chemosensitive (5637) versus a chemoresistant (H-bc) bladder cancer cell lines, we showed that miR-193a-3p [GenBank: NR_029710.1] promotes the multi-chemoresistance of bladder cancer cells. We further demonstrated that lysyl oxidase-like 4 (LOXL4) gene [GenBank: NM_032211.6] is a direct target of miR-193a-3p and executes the former’s impact on bladder cancer chemoresistance. The Oxidative Stress pathway activity is drastically affected by a forced reversal of miR-193a-3p or LOXL4 levels in cell and may act at the downstream of LOXL4 gene to relay the miR-193a-3p’s impact on the multi-chemoresistance in both cultured cells and the tumor xenografts in nude mice. In addition to a new mechanistic insight, our results provide a set of the essential genes in this newly identified miR-193a-3p/LOXL4/Oxidative Stress axis as the diagnostic targets for a guided anti-bladder cancer chemotherapy.

Context. Polycystic ovary syndrome (PCOS) is a gynecological endocrine disease, and approximately 60 of patients with PCOS have different degrees of insulin resistance (IR). The regulatory role of metabolic networks in human follicular fluid (FF) related to IR in PCOS remains unclear. Aims. To explore the effect of IR on the metabolism of PCOS by analyzing the changes in FF metabolites in PCOS patients who are undergoing assisted reproductive technology based on the metabonomic platform of ultraperformance gas chromatography coupled to mass spectrometry (GC/MS). Method. Eight PCOS patients with IR (PCOS-IR) and 8 PCOS patients without IR (PCOS-NIR) were enrolled. All patients received controlled ovarian stimulation by using the gonadotropin-releasing hormone (GnRH) antagonist protocol, and the FF of a single dominant follicle was collected on the day of oocyte retrieval. The metabolite profiles of the FF were determined by GC/MS. Key Results. A total of 20 differentially expressed metabolites in FF were identified. Compared with levels in the PCOS-NIR group, stearic acid, palmitic acid, pentadecanoic acid, stigmasterol, citric acid, isocitric acid, thymine, and pyruvic acid in FF were significantly increased in the PCOS-IR group. Lithocholic acid and sinapinic acid in FF decreased significantly. The affected metabolic pathways with potential regulatory roles were identified by KEGG annotation. Conclusion. Compared with the PCOS-NIR group, the PCOS-IR group showed more significant metabolic abnormalities. Implications. These results will help us to understand the pathogenesis of PCOS combined with IR and will provide new clues for studying metabolic disorders associated with PCOS, e.g., IR.

Endometriosis, affecting 6%-10% of women, often leads to pain and infertility and its underlying inflammatory mechanisms are poorly understood. We established endometriosis models in wild-type and IL16KO mice, revealing the driver function of IL-16 in initiating endometriosis-related inflammation. Using an in vitro system, we confirmed iron overload-induced GSDME-mediated pyroptosis as a key trigger for IL-16 activation and release. In addition, our research led to the development of Z30702029, a compound inhibiting GSDME-NTD-mediated pyroptosis, which shows promise as a therapeutic intervention for endometriosis. Importantly, our findings extend beyond endometriosis, highlighting GSDME-mediated pyroptosis as a broader pathway for IL-16 release and offering insights into potential treatments for various inflammatory conditions.

Uterine Corpus Endometrial Carcinoma (UCEC) is one of the most common malignancies of the female genital tract and there remains a major public health problem. Although significant progress has been made in explaining the progression of UCEC, it is still warranted that molecular mechanisms underlying the tumorigenesis of UCEC are to be elucidated. The aim of the current study was to investigate key modules and hub genes related to UCEC pathogenesis, and to explore potential biomarkers and therapeutic targets for UCEC. The RNA-seq dataset and corresponding clinical information for UCEC patients were obtained from the Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened between 23 paired UCEC tissues and adjacent non-cancerous tissues. Subsequently, the co-expression network of DEGs was determined via weighted gene co-expression network analysis (WGCNA). The Blue and Brown modules were identified to be significantly positively associated with neoplasm histologic grade. The highly connected genes of the two modules were then investigated as potential key factors related to tumor differentiation. Additionally, a protein-protein interaction (PPI) network for all genes in the two modules was constructed to obtain key modules and nodes. 10 genes were identified by both WGCNA and PPI analyses, and it was shown by Kaplan-Meier curve analysis that 6 out of the 10 genes were significantly negatively related to the 5-year overall survival (OS) in patients (AURKA, BUB1, CDCA8, DLGAP5, KIF2C, TPX2). Besides, according to the DEGs from the two modules, lncRNA-miRNA-mRNA and lncRNA-TF-mRNA networks were constructed to explore the molecular mechanism of UCEC-related lncRNAs. 3 lncRNAs were identified as being significantly negatively related to the 5-year OS (AC015849.16, DUXAP8 and DGCR5), with higher expression in UCEC tissues compared to non-tumor tissues. Finally, quantitative Real-time PCR was applied to validate the expression patterns of hub genes. Cell proliferation and colony formation assays, as well as cell cycle distribution and apoptosis analysis, were performed to test the effects of representative hub genes. Altogether, this study not only promotes our understanding of the molecular mechanisms for the pathogenesis of UCEC but also identifies several promising biomarkers in UCEC development, providing potential therapeutic targets for UCEC.