Jie Zhang

Preoperative evaluation and a nomogram prediction model for pelvic lymph node metastasis in endometrial cancer

The primary objective of this study is to explore the preoperative risk factors of pelvic lymph node metastasis (PLNM) in endometrial cancer patients, and construct a nomogram prediction model. We retrospectively collected various preoperative clinical characteristics of patients and analyzed their relationship with PLNM. Logistic regression analysis was used to screen for independent risk factors for PLNM of endometrial cancer. A nomogram prediction model was constructed, the receiver operating characteristic (ROC), calibration curve and decision curve analysis (DCA) were constructed and used to assess discrimination, calibration, and net benefit. Out of the 276 patients, 74 (26.81%) with postoperative pathological confirmation of PLNM. Multivariate logistic regressive analysis demonstrated that preoperative depth of myometrial invasion (DIM) ≥50% determined by Magnetic Resonance Imaging (MRI) (p = 0.003), carbohydrate antigen 125 (CA125) (p = 0.030), carbohydrate antigen 19-9 (CA 19-9) (p = 0.044), and platelet/lymphocyte ratio (PLR) (p = 0.025) could serve as independent risk factors for PLNM. A risk factors-based nomogram prediction model was constructed, which showed good discrimination (AUC = 0.841, p < 0.001) and good efficacy (C-index = 0.842) and good calibration (mean absolute error = 0.046). DCA showed that the model can provide clinical benefits. Preoperative DIM ≥50% determined by MRI, serum CA 19-9, CA125 and PLR could be utilized to predict PLNM in endometrial cancer patients. This nomogram prediction model can provide preoperative help for evaluation and identification of patients with endometrial cancer, and provide a theoretical basis for clinical intervention.

Exploration of the effect and mechanism of Scutellaria barbata D. Don in the treatment of ovarian cancer based on network pharmacology and in vitro experimental verification

The mortality rate of ovarian cancer is the highest among gynecological cancers, posing a serious threat to women health and life. Scutellaria barbata D. Don (SBD) can effectively treat ovarian cancer. However, its mechanism of action is unclear. The aim of this study was to elucidate the mechanism of SBD in the treatment of ovarian cancer using network pharmacology, and to verify the experimental results using human ovarian cancer SKOV3 cells. The Herb and Disease Gene databases were searched to identify common targets of SBD and ovarian cancer. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Protein-Protein Interaction (PPI) network analyses were performed to identify the potential molecular mechanisms behind SBD. Finally, the molecular docking and main possible pathways were verified by experimental studies. Cell proliferation, the mRNA expression level of key genes and signaling pathway were all investigated and evaluated in vitro. A total of 29 bioactive ingredients and 137 common targets in SBD were found to inhibit ovarian cancer development. The active ingredients identified include quercetin, luteolin, and wogonin. Analysis of the PPI network showed that AKT1, VEGFA, JUN, TNF, and Caspase-3 shared centrality among all target genes. The results of the KEGG pathway analysis indicated that the cancer pathway, PI3K-Akt signaling pathway, and MAPK signaling pathways mediated the effects of SBD against ovarian cancer progression. Cell experiments showed that quercetin, luteolin, and wogonin inhibited the proliferation and clone formation of SKOV3 cells and regulated mRNA expression of 5 key genes by inhibiting PI3K/Akt signaling pathway. Our results demonstrate that SBD exerted anti-ovarian cancer effects through its key components quercetin, luteolin and wogonin. Mechanistically, its anti-cancer effects were mediated by inhibition of the PI3K/Akt signaling pathways. Therefore, SBD might be a candidate drug for ovarian cancer treatment.

Role of T2 mapping of magnetic resonance imaging in the differentiation of endometrial cancer and benign endometrial lesions

The T2 mapping of magnetic resonance imaging (MRI) in endometrial cancer (EC), benign endometrial lesions (BELs), and normal endometrium (NE) has rarely been reported. This study aimed to determine the T2 values of MRI in EC, BELs, and NE to investigate whether the T2 values can differentiate them and to assess the aggressiveness of EC. In total, 73 patients [EC, 51 (age, 57.4 ± 5.4 years); BELs, 22 (age, 57.8 ± 11.8 years)] and 23 normal volunteers (age, 56.1 ± 6.6 years) were included. The T2 values of MRI of the EC (type I and II), BEL, and NE groups were described and compared. The relationships between the T2 values of MRI in EC and the pathological characteristics [International Federation of Gynecology and Obstetrics (FIGO) stage and grade] were analyzed. The median T2 values of NE, BEL, and EC were 197.5 (142.9-324.0) ms, 131.1 (103.2-247.9) ms, and 103.0 (71.6-243.5) ms ( T2 mapping of MRI has the potential to quantitatively differentiate between EC, BELs, and NE as well as between type I and type II EC.

Zengmian Yiliu formula suppresses cell cycle in immune-rich ovarian cancer patient-derived organoids

Ovarian cancer, often diagnosed at advanced stages, has a 5-year survival rate below 50%, indicating a critical need for innovative treatments. The Zengmian Yiliu (ZMYL) formula, a Traditional Chinese Medicine (TCM) prescription, has shown potential in enhancing chemotherapy efficacy and improving patients' quality of life, PURPOSE: To investigate the effects of the ZMYL formula on ovarian cancer organoids, focusing on its impact on organoid phenotypes and underlying mechanisms, and to explore its potential as an immunotherapeutic agent. Ovarian cancer organoids were established from surgical tissues and treated with the ZMYL formula at varying concentrations. Network pharmacology was utilized to predict the formula's therapeutic targets and pathways, and molecular docking was conducted to validate ingredient-target interactions. Phenotypic changes were monitored, and RNA sequencing was performed post-treatment to analyze gene expression alterations. A total of 34 overlapping targets of 10 compounds in the ZMYL formula and ovarian cancer were predicted by Network pharmacology analysis. The ZMYL formula induced dose-dependent morphological changes in organoids, including a reduction in size and structural sparsity at higher concentrations. RNA sequencing revealed significant modulation of cell cycle and immune response pathways, with a particular focus on immunomodulatory effects. The formula's treatment targeted key genes involved in these processes, reshaping the tumor's molecular landscape. This study establishes ZMYL's capacity to simultaneously target oncogenic drivers (e.g., cell cycle regulators) and immune checkpoints (e.g., CXCL10-mediated T cell recruitment) in ovarian cancer organoids. Unlike conventional monotherapy-focused approaches, ZMYL's multi-component mechanism offers a synergistic framework for integrating TCM with modern immunotherapies. These findings provide a foundation for future clinical evaluation of ZMYL as a precision medicine strategy to enhance treatment efficacy and mitigate chemoresistance in ovarian cancer.