We previously characterized the link between WNT7A and the progression of ovarian cancer. Other groups have identified FGF1 as a relevant risk factor in ovarian cancer. Here, we show a linkage between these two signaling pathways that may be exploited to improve treatment and prognosis of patients with ovarian cancer. High expression of WNT7A and FGF1 are correlated in ovarian carcinomas and poor overall patient survival. A chromatin immunoprecipitation assay demonstrated that WNT7A/β-catenin signaling directly regulates FGF1 expression via TCF binding elements in the FGF1-1C promoter locus. In vitro gene manipulation studies revealed that FGF1 is sufficient to drive the tumor-promoting effects of WNT7A. In vivo xenograft studies confirmed that the stable overexpression of WNT7A or FGF1 induced a significant increase in tumor incidence, whereas FGF1 knockdown in WNT7A overexpressing cells caused a significant reduction in tumor size. Niclosamide most efficiently abrogated WNT7A/β-catenin signaling in our model, inhibited β-catenin transcriptional activity and cell viability, and increased cell death. Furthermore, niclosamide decreased cell migration following an increase in E-cadherin subsequent to decreased levels of SLUG. The effects of niclosamide on cell functions were more potent in WNT7A-overexpressing cells. Oral niclosamide inhibited tumor growth and progression in an intraperitoneal xenograft mouse model representative of human ovarian cancer. Collectively, these results indicate that FGF1 is a direct downstream target of WNT7A/β-catenin signaling and this pathway has potential as a therapeutic target in ovarian cancer. Moreover, niclosamide is a promising inhibitor of this pathway and may have clinical relevance.
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http://dx.doi.org/10.1038/onc.2014.277 | DOI Listing |
J Ovarian Res
January 2025
Department of Medical Genetics, National Taiwan University Hospital, 19F, No. 8, Chung-Shan South Road, Taipei City, Taiwan.
Background: The homologous recombination deficiency (HRD) test is an important tool for identifying patients with epithelial ovarian cancer (EOC) benefit from the treatment with poly(adenosine diphosphate-ribose) polymerase inhibitor (PARPi). Using whole exome sequencing (WES)-based platform can provide information of gene mutations and HRD score; however, the clinical value of WES-based HRD test was less validated in EOC.
Methods: We enrolled 40 patients with EOC in the training cohort and 23 in the validation cohort.
J Ovarian Res
January 2025
Department of Health Education, Nanjing Municipal Center for Disease Control and Prevention, No.3, Zizhulin Road, Nanjing, Jiangsu Province, 210003, China.
Background: PARP inhibitors (PARPis) have shown promising effectiveness for ovarian cancer. This network meta-analysis (PROSPERO registration number CRD42024503390) comprehensively evaluated the effectiveness and safety of PARPis in platinum-sensitive recurrent ovarian cancer (PSROC).
Methods: Articles published before January 6, 2024 were obtained from electronic databases.
J Transl Med
January 2025
Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China.
Background: The evidence on the relationship of dietary antioxidant nutrients with the survival of ovarian cancer (OC) remains scarce.
Objective: This study aimed to investigate these associations in a prospective cohort of Chinese patients with OC.
Methods: In this prospective cohort study, patients with epithelial OC completed a food frequency questionnaire at diagnosis and 12 months post-diagnosis, and were followed from 2015 to 2023.
JMIRx Med
January 2025
Department of Biochemistry and Medical Genetics, Cancer Center, University of Illinois Chicago, 900 s Ashland, Chicago, IL, 60617, United States, 1 8479124216.
Background: The causes of breast cancer are poorly understood. A potential risk factor is Epstein-Barr virus (EBV), a lifelong infection nearly everyone acquires. EBV-transformed human mammary cells accelerate breast cancer when transplanted into immunosuppressed mice, but the virus can disappear as malignant cells reproduce.
View Article and Find Full Text PDFNPJ Precis Oncol
January 2025
Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, UK.
Histopathology foundation models show great promise across many tasks, but analyses have been limited by arbitrary hyperparameters. We report the most rigorous single-task validation study to date, specifically in the context of ovarian carcinoma morphological subtyping. Attention-based multiple instance learning classifiers were compared using three ImageNet-pretrained encoders and fourteen foundation models, each trained with 1864 whole slide images and validated through hold-out testing and two external validations (the Transcanadian Study and OCEAN Challenge).
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