Epithelial ovarian cancer remains the most devastating gynecologic cancer with drug resistance and rapid recurrence. Pregnane X receptor (PXR) is a nuclear receptor that affects drug metabolism/efflux and drug-drug interaction through control of multiple drug resistance 1 (MDR1), which implies a major role in multidrug resistance, and other genes. We examined whether the inhibition of PXR-mediated pathway using siRNA interference and an antagonist for PXR could influence the paclitaxel and cisplatin cytotoxicity in ovarian cancer cells. PXR agonists, phthalate and pregnenolone had significant positive effects on cytochrome P450 (CYP) 3A4 expression and PXR-mediated transcription through the CYP3A4 promoter, whereas MDR1 expression and PXR-mediated transcription though the MDR1 promoter were significantly increased in the presence of paclitaxel or cisplatin. Downregulation of PXR suppressed the augmented MDR1 expression and PXR-mediated transcription by PXR ligands, and significantly enhanced cell growth inhibition and apoptosis in the presence of paclitaxel or cisplatin. Additionally, ketoconazole, a PXR antagonist, suppressed the augmented MDR1 expression and PXR-mediated transactivation by paclitaxel and cisplatin, and enhanced cell growth inhibition and apoptosis in their presence. In conclusion, inhibition of PXR-mediated pathways could be a novel means of augmenting sensitivity, or overcoming resistance to anticancer agents for ovarian cancer.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.3892/ijo.2016.3611 | DOI Listing |
Breast Cancer Res
January 2025
Servicio de Oncología, Centro Universitario Contra el Cáncer (CUCC), Hospital Universitario "Dr. José Eleuterio González", Universidad Autónoma de Nuevo León, 66451, Monterrey, Nuevo León, México.
Background: Hereditary predisposition to breast and ovarian cancer syndrome (HBOC) is a pathological condition with increased cancer risk, including breast (BC), ovarian cancer (OC), and others. HBOC pathogenesis is caused mainly by germline pathogenic variants (GPV) in BRCA1 and BRCA2 genes. However, other relevant genes are related to this syndrome diagnosis, prognosis, and treatment, including TP53, PALB2, CHEK2, ATM, etc.
View Article and Find Full Text PDFBMC Surg
January 2025
Department of Obstetrics and Gynecology, Firoozgar Clinical Research and Development Center (FCRDC), School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Background: Complete Cytoreduction (CC) in ovarian cancer (OC) has been associated with better outcomes. Outcomes after CC have a multifactorial and interrelated cause that may not be predictable by conventional statistical methods. Artificial intelligence (AI) may be more accurate in predicting outcomes.
View Article and Find Full Text PDFBMC Cancer
January 2025
Department of Gynecologic Oncology, Fudan University Shanghai Cancer Centre, Shanghai, China.
Background: To assess the utility of the TCGA molecular classification of endometrial cancer in a well-annotated, moderately sized, consecutive cohort of Chinese patients with ovarian clear cell carcinoma (OCCC).
Methods: We performed DNA sequencing on 80 OCCC patients via a panel that contains 520 cancer-related genes. The TCGA molecular subtyping method was utilized for classification.
Sci Rep
January 2025
Assisted Reproduction Unit, Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Primary leiomyoma is one of the rarest benign ovarian tumors. Since the first case was identified, less than 100 cases have been reported worldwide. This study aimed to analyze the clinical characteristics and discuss the proper management of this tumor.
View Article and Find Full Text PDFAcad Radiol
January 2025
Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui, China (Y.Z., Y.D., Q.Z., C.Z.). Electronic address:
Rationale And Objectives: This study aimed to develop a predictive model for peritoneal metastasis (PM) in ovarian cancer using a combination radiomics and clinical biomarkers to improve diagnostic accuracy.
Patients And Methods: This retrospective cohort study of 619 ovarian cancer patients involved demographic data, radiomics, O-RADS standardized description, clinical biomarkers, and histological findings. Radiomics features were extracted using 3D Slicer and Pyradiomics, with selective feature extraction using Least Absolute Shrinkage and Selection Operator regression.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!