Jinhua Wang

BST2 Drives Epithelial Ovarian Cancer Progression via Macrophage M2 Polarization, Neural Remodeling, and Immunosuppressive Microenvironment Formation

Background Epithelial ovarian cancer (EOC) ranks as the most lethal of gynecological cancers. Despite advances in therapeutic interventions that have marginally extended survival rates, the early detection and management of EOC pose significant hurdles. Consequently, identifying novel therapeutic targets is imperative for enhancing the survival outcomes of patients afflicted with this malignancy. Purpose This research is aimed at exploring the functions of Bone Marrow Stromal Antigen 2 (BST2) in the pathogenesis of EOC and their influence on macrophage polarization, evaluating their viability as targets for immunotherapy. Methods Gene expression profiles and clinical data of EOC patients were retrieved from the TCGA repository to develop prognostic models centered on BST2. The expression patterns of BST2 in HGSOC cell lines were quantified via RT‐qPCR and Western blot analyses. The impact of BST2 on the proliferative, migratory, and invasive capacities of EOC cells was assessed through gene silencing and gene overexpression experiments. Results Elevated levels of BST2 expression were observed in EOC tissues, correlating with adverse prognostic indicators. Enhanced BST2 expression facilitated EOC cell growth, motility, and invasiveness, whereas BST2 suppression mitigated these oncogenic attributes. In vivo assessments revealed that BST2 augmentation modified the macrophage phenotypes within grafted ovarian tumors, with BST2 diminution reversing these effects. Conclusion The findings propose that BST2 acts as a pivotal facilitator in the progression of ovarian carcinoma. The expression metrics of BST2 may serve as prognostic markers for patient outcomes in EOC. These findings suggest that BST2 is a key promoter of ovarian cancer progression, and its expression may serve as a prognostic marker. The mechanisms uncovered, including the modulation of macrophage polarization and neural marker expression, indicate that targeting BST2 represents a potential future strategy for immunotherapy in EOC.

Indirubin suppresses ovarian cancer progression by inhibiting PI3K/AKT-mediated EMT and tumor growth without systemic toxicity

This study investigated indirubin's effects on ovarian cancer cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), both in vitro and in vivo, while exploring its underlying mechanisms. The anti-tumor activity of indirubin was evaluated using ovarian cancer cell lines (A2780, SKOV-3, OVCAR-3) through MTT, colony formation, wound healing, and Transwell assays. Patient-derived organoids and a nude mouse xenograft model were employed for further validation. Mechanistic studies integrated bioinformatics analysis (SymMap database and transcriptome sequencing) with experimental assessment of EMT markers and PI3K/AKT pathway activity, including the use of specific inhibitors (MK2206, SB 216763). Indirubin significantly suppressed ovarian cancer cell proliferation, colony formation, migration, and invasion, as well as inhibited patient-derived organoid growth. In a xenograft model, indirubin effectively attenuated tumor growth without inducing pathological changes in major organs. Through SymMap database and transcriptomic analyses, indirubin was shown to modulate multiple signaling pathways, particularly impairing cell adhesion. Mechanistically, indirubin downregulated AKT and GSK-3β phosphorylation in the PI3K/AKT pathway, and upregulated E-cadherin while suppressing Vimentin and N-cadherin, thereby inhibiting EMT. Notably, indirubin, the PI3K/AKT inhibitor MK2206, and the GSK-3β inhibitor SB216763 all exhibited strong antitumor efficacy in vivo. Indirubin exerts broad anti-ovarian cancer effects by inhibiting proliferation, migration, invasion as well as EMT, with demonstrated efficacy in xenograft models and no observed organ toxicity. Its mechanistic overlap with PI3K/AKT inhibitors underscores its potential as a multitargeted therapeutic agent.

Dilution of Molecular–Pathologic Gene Signatures by Medically Associated Factors Might Prevent Prediction of Resection Status After Debulking Surgery in Patients With Advanced Ovarian Cancer

Abstract Purpose: Predicting surgical outcome could improve individualizing treatment strategies for patients with advanced ovarian cancer. It has been suggested earlier that gene expression signatures (GES) might harbor the potential to predict surgical outcome. Experimental Design: Data derived from high-grade serous tumor tissue of FIGO stage IIIC/IV patients of AGO-OVAR11 trial were used to generate a transcriptome profiling. Previously identified molecular signatures were tested. A theoretical model was implemented to evaluate the impact of medically associated factors for residual disease (RD) on the performance of GES that predicts RD status. Results: A total of 266 patients met inclusion criteria, of those, 39.1% underwent complete resection. Previously reported GES did not predict RD in this cohort. Similarly, The Cancer Genome Atlas molecular subtypes, an independent de novo signature and the total gene expression dataset using all 21,000 genes were not able to predict RD status. Medical reasons for RD were identified as potential limiting factors that impact the ability to use GES to predict RD. In a center with high complete resection rates, a GES which would perfectly predict tumor biological RD would have a performance of only AUC 0.83, due to reasons other than tumor biology. Conclusions: Previously identified GES cannot be generalized. Medically associated factors for RD may be the main obstacle to predict surgical outcome in an all-comer population of patients with advanced ovarian cancer. If biomarkers derived from tumor tissue are used to predict outcome of patients with cancer, selection bias should be focused on to prevent overestimation of the power of such a biomarker. See related commentary by Handley and Sood, p. 9

The impact of STAT3 and phospho-STAT3 expression on the prognosis and clinicopathology of ovarian cancer: a systematic review and meta-analysis

Abstract Purpose STAT3 and p-STAT3 are often overexpressed in various human tumours and participate in cancer development and progression. However, whether STAT3/p-STAT3 expression is associated with clinicopathologic characteristics and has prognostic significance for people suffering from ovarian cancer remains controversial. We conducted a systematic review and meta-analyses to clarify the associations between STAT3/p-STAT3 expression and clinicopathologic characteristics and prognostic factors of ovarian cancer. Methods A systematic electronic search in the PubMed, Embase, CNKI, and Wanfang databases was conducted to identify relevant articles published before 3 April 2021. All statistical analyses were performed using Stata 15.1. Results We included 16 eligible studies incorporating 1747 ovarian cancer patients. The expression of STAT3/p-STAT3 was upregulated in ovarian cancer samples versus normal ovarian tissue, benign tumours and borderline tumours (OR = 10.14, p < 0.00001; OR = 9.08, P < 0.00001; OR = 4.01, p < 0.00001, respectively). STAT3/p-STAT3 overexpression was significantly correlated with FIGO stage (I-II vs. III-IV) (OR = 0.36, p < 0.00001), tumour grade (G1 + G2 vs. G3) (OR = 0.55; p = 0.001) and lymph node metastasis (yes vs. no) (OR = 3.39; p < 0.00001). High STAT3/p-STAT3 expression was correlated with poorer prognosis of ovarian cancer patients for both overall survival (OS) (HR = 1.67, p < 0.00001) and progression-free survival (PFS) (HR = 1.40, p = 0.007). Conclusion The present meta-analysis indicated that high STAT3/p-STAT3 expression is likely predictive of an unfavourable prognosis in ovarian cancer patients. Nonetheless, prospective trials are required to confirm these associations.