Ovarian cancer screening-ultrasound; impact on ovarian cancer mortality

Neural network-derived multivariate index assay demonstrates effective clinical performance in longitudinal monitoring of ovarian cancer risk

OBJECTIVE

We recently characterized the clinical performance of a multivariate index assay (MIA3G) to assess ovarian cancer risk for adnexal masses at initial presentation. This study evaluated how MIA3G varies when applied longitudinally to monitor risk during clinical follow-up.

METHOD

The study evaluated women presenting with adnexal masses from eleven centers across the US. Patients received an initial blood draw at enrollment and at the standard-of-care follow-up visits. MIA3G was determined for all visits but physicians did not have access to MIA3G scores to determine clinical management. The primary outcome was the relative change value (RCV) of MIA3G over the period of clinical observation.

RESULTS

A total of 510 patients of 785 enrolled met study criteria. Of these, 30.8% had a second, 25.4% a third and 22.2% a fourth blood draw following initial collection. The median duration from initial draw was 131 d to second draw, 301.5 d to the third draw and 365.5 d to the fourth draw. MIA3G RCV of >50% was observed in 22-26% patients, whereas 70-75% patients had MIA3G RCV >5%. An empirical baseline RCV of 56% - transformed to 1 in logarithmic scale - was calculated from averaging RCVs of all patients who had no malignancy risk after 210 days. RCV > 1 log was associated with higher incidence of surgical intervention (29.6%) compared to RCV < 1 log (16.9%).

CONCLUSIONS

Variation in MI3AG does not change the accuracy of the test for excluding malignancy, while marked changes may be associated with a slightly higher likelihood of surgical intervention. In addition to MIA3G score itself, the MIA3G RCV may be important for clinical management.

Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models

No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering that little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights into how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSOC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes were compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.

Evaluating the Effectiveness of 2D and 3D CT Image Features for Predicting Tumor Response to Chemotherapy

Background and Objective: 2D and 3D tumor features are widely used in a variety of medical image analysis tasks. However, for chemotherapy response prediction, the effectiveness between different kinds of 2D and 3D features are not comprehensively assessed, especially in ovarian-cancer-related applications. This investigation aims to accomplish such a comprehensive evaluation. Methods: For this purpose, CT images were collected retrospectively from 188 advanced-stage ovarian cancer patients. All the metastatic tumors that occurred in each patient were segmented and then processed by a set of six filters. Next, three categories of features, namely geometric, density, and texture features, were calculated from both the filtered results and the original segmented tumors, generating a total of 1403 and 1595 features for the 2D and 3D tumors, respectively. In addition to the conventional single-slice 2D and full-volume 3D tumor features, we also computed the incomplete-3D tumor features, which were achieved by sequentially adding one individual CT slice and calculating the corresponding features. Support vector machine (SVM)-based prediction models were developed and optimized for each feature set. Five-fold cross-validation was used to assess the performance of each individual model. Results: The results show that the 2D feature-based model achieved an AUC (area under the ROC curve (receiver operating characteristic)) of 0.84 ± 0.02. When adding more slices, the AUC first increased to reach the maximum and then gradually decreased to 0.86 ± 0.02. The maximum AUC was yielded when adding two adjacent slices, with a value of 0.91 ± 0.01. Conclusions: This initial result provides meaningful information for optimizing machine learning-based decision-making support tools in the future.

Ultrahigh Resolution Lipid Mass Spectrometry Imaging of High-Grade Serous Ovarian Cancer Mouse Models

No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights on how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and a triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide a direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.

Liability, risks, and recommendations for ultrasound use in the diagnosis of obstetrics diseases

This literature review will summarize the liability issues, risks, and ultrasound recommendations for diagnosing obstetrics diseases. One liability issue is related to misdiagnosis or failure to detect abnormalities during an ultrasound examination. Ultrasound images can be subjective interpretations, and errors may occur due to factors such as operator skill, equipment limitations, or fetal positioning. Another liability concern is related to the potential adverse effects of ultrasound exposure on both the mother and fetus. While extensive research has shown that diagnostic ultrasound is generally safe when used appropriately, there are still uncertainties regarding long-term effects. Some studies suggest a possible association between prolonged or excessive exposure to ultrasound waves and adverse outcomes such as low birth weight, developmental delays, or hearing impairment. Additionally, obtaining informed consent from patients is crucial in mitigating liability risks. Patients should be informed about the purpose of the ultrasound examination, its benefits, limitations, potential risks (even if minimal), and any alternative diagnostic options available. This ensures that patients know the procedure and can make informed decisions about their healthcare. Proper documentation helps establish a clear record of the care provided and can serve as evidence in any legal disputes.

The Role of EMT-Related lncRNAs in Ovarian Cancer

Ovarian cancer (OC) is one of the deadliest cancers worldwide; late diagnosis and drug resistance are two major factors often responsible for high morbidity and treatment failure. Epithelial-to-mesenchymal transition (EMT) is a dynamic process that has been closely linked with cancer. Long non-coding RNAs (lncRNAs) have been also associated with several cancer-related mechanisms, including EMT. We conducted a literature search in the PubMed database in order to sum up and discuss the role of lncRNAs in regulating OC-related EMT and their underlying mechanisms. Seventy (70) original research articles were identified, as of 23 April 2023. Our review concluded that the dysregulation of lncRNAs is highly associated with EMT-mediated OC progression. A comprehensive understanding of lncRNAs' mechanisms in OC will help in identifying novel and sensitive biomarkers and therapeutic targets for this malignancy.

The Application of Nanoparticle-Based Imaging and Phototherapy for Female Reproductive Organs Diseases

Various female reproductive disorders affect millions of women worldwide and bring many troubles to women's daily life. Let alone, gynecological cancer (such as ovarian cancer and cervical cancer) is a severe threat to most women's lives. Endometriosis, pelvic inflammatory disease, and other chronic diseases-induced pain have significantly harmed women's physical and mental health. Despite recent advances in the female reproductive field, the existing challenges are still enormous such as personalization of disease, difficulty in diagnosing early cancers, antibiotic resistance in infectious diseases, etc. To confront such challenges, nanoparticle-based imaging tools and phototherapies that offer minimally invasive detection and treatment of reproductive tract-associated pathologies are indispensable and innovative. Of late, several clinical trials have also been conducted using nanoparticles for the early detection of female reproductive tract infections and cancers, targeted drug delivery, and cellular therapeutics. However, these nanoparticle trials are still nascent due to the body's delicate and complex female reproductive system. The present review comprehensively focuses on emerging nanoparticle-based imaging and phototherapies applications, which hold enormous promise for improved early diagnosis and effective treatments of various female reproductive organ diseases.

Electrochemical and Photoelectrochemical Immunosensors for the Detection of Ovarian Cancer Biomarkers

Photoelectrochemical (PEC) sensing is an emerging technological innovation for monitoring small substances/molecules in biological or non-biological systems. In particular, there has been a surge of interest in developing PEC devices for determining molecules of clinical significance. This is especially the case for molecules that are markers for serious and deadly medical conditions. The increased interest in PEC sensors to monitor such biomarkers can be attributed to the many apparent advantages of the PEC system, including an enhanced measurable signal, high potential for miniaturization, rapid testing, and low cost, amongst others. The growing number of published research reports on the subject calls for a comprehensive review of the various findings. This article is a review of studies on electrochemical (EC) and PEC sensors for ovarian cancer biomarkers in the last seven years (2016-2022). EC sensors were included because PEC is an improved EC; and a comparison of both systems has, expectedly, been carried out in many studies. Specific attention was given to the different markers of ovarian cancer and the EC/PEC sensing platforms developed for their detection/quantification. Relevant articles were sourced from the following databases: Scopus, PubMed Central, Web of Science, Science Direct, Academic Search Complete, EBSCO, CORE, Directory of open Access Journals (DOAJ), Public Library of Science (PLOS), BioMed Central (BMC), Semantic Scholar, Research Gate, SciELO, Wiley Online Library, Elsevier and SpringerLink.

Circulating Biomarkers for Cancer Detection: Could Salivary microRNAs Be an Opportunity for Ovarian Cancer Diagnostics?

MicroRNAs (miRNAs) are small non-coding RNAs with the crucial regulatory functions of gene expression at post-transcriptional level, detectable in cell and tissue extracts, and body fluids. For their stability in body fluids and accessibility to sampling, circulating miRNAs and changes of their concentration may represent suitable disease biomarkers, with diagnostic and prognostic relevance. A solid literature now describes the profiling of circulating miRNA signatures for several tumor types. Among body fluids, saliva accurately reflects systemic pathophysiological conditions, representing a promising diagnostic resource for the future of low-cost screening procedures for systemic diseases, including cancer. Here, we provide a review of literature about miRNAs as potential disease biomarkers with regard to ovarian cancer (OC), with an excursus about liquid biopsies, and saliva in particular. We also report on salivary miRNAs as biomarkers in oncological conditions other than OC, as well as on OC biomarkers other than miRNAs. While the clinical need for an effective tool for OC screening remains unmet, it would be advisable to combine within a single diagnostic platform, the tools for detecting patterns of both protein and miRNA biomarkers to provide the screening robustness that single molecular species separately were not able to provide so far.

Spectrum of Ovarian Incidentalomas: Diagnosis and Management

Incidental ovarian lesions are asymptomatic lesions that are accidentally discovered during a CT or MRI examinations that involves the pelvic cavity or during a routine obstetric ultrasound study. Incidental ovarian masses are usually benign with a very low risk of malignancy yet underlying malignant pathology may be discovered during the diagnostic work-up of these lesions. Suspicion of malignancy is directly correlating with the increase in the patient's age, the increase in the size of the lesion, the presence of the solid components or thick septa and a high color scale of the ovarian mass. Following standard reporting and management protocols are essential to choose the proper work-up of these lesions to avoid unnecessary additional imaging and operative intervention. In this article, we will provide a review of the characteristic imaging features of some incidental and yet commonly encountered ovarian lesions. We will also summarize the recently published algorithms that are important for consistent reporting and standard management of these lesions.

Ovarian Cancer: A Landscape of Mitochondria with Emphasis on Mitochondrial Dynamics

Ovarian cancer (OC) represents the main cause of death from gynecological malignancies in western countries. Altered cellular and mitochondrial metabolism are considered hallmarks in cancer disease. Several mitochondrial aspects have been found altered in OC, such as the oxidative phosphorylation system, oxidative stress and mitochondrial dynamics. Mitochondrial dynamics includes cristae remodeling, fusion, and fission processes forming a dynamic mitochondrial network. Alteration of mitochondrial dynamics is associated with metabolic change in tumour development and, in particular, the mitochondrial shaping proteins appear also to be responsible for the chemosensitivity and/or chemoresistance in OC. In this review a focus on the mitochondrial dynamics in OC cells is presented.

The Value of IOTA Simple Rules Combined With CEUS Scoring System in the Diagnosis of Benign and Malignant Ovarian Masses and Its Correlation With MVD and VEGF: A Preliminary Study

OBJECTIVES

To investigate the diagnostic value of International Ovarian Tumor Analysis (IOTA) simple rules combined with contrast-enhanced ultrasound (CEUS) scoring system in the differential diagnosis of ovarian tumors, and the correlations of the scoring system with microvessel density (MVD) and vascular endothelial growth factor (VEGF).

METHODS

One hundred eighty-nine patients with ovarian tumors were examined by routine ultrasound and CEUS. The enhanced characteristics of CEUS were observed, and the masses were classified by IOTA simple rules. To compare the diagnostic value of IOTA simple rules combined with CEUS scoring system and IOTA simple rules in the diagnosis of ovarian tumors. Immunohistochemistry was used to detect the expression of MVD and VEGF in postoperative tissue samples. The correlations between the new scoring system with MVD and VEGF were analyzed.

RESULTS

The sensitivity (93.98%), specificity (94.34%), positive predictive value (92.86%), negative predictive value (95.24%), and accuracy (94.18%) of IOTA simple rules combined with CEUS scoring system in the diagnosis of ovarian tumors were higher than those of IOTA simple rules alone (all P < .05). The score system was significantly positively correlated with MVD and VEGF, and the r values were 0.77 and 0.63, respectively (P < .001).

CONCLUSIONS

IOTA simple rules combined with CEUS scoring system was helpful to improve the accuracy of ultrasound diagnosis of ovarian tumors, which was significantly correlated with MVD and VEGF. It could provide important reference information for treatment scheme formulation and prognosis evaluation.

Ultrasound-enhanced Unet model for quantitative photoacoustic tomography of ovarian lesions

Quantitative photoacoustic tomography (QPAT) is a valuable tool in characterizing ovarian lesions for accurate diagnosis. However, accurately reconstructing a lesion's optical absorption distributions from photoacoustic signals measured with multiple wavelengths is challenging because it involves an ill-posed inverse problem with three unknowns: the Grüneisen parameter ( Γ ) , the absorption distribution, and the optical fluence ( ϕ ) . Here, we propose a novel ultrasound-enhanced Unet model (US-Unet) that reconstructs optical absorption distribution from PAT data. A pre-trained ResNet-18 extracts the US features typically identified as morphologies of suspicious ovarian lesions, and a Unet is implemented to reconstruct optical absorption coefficient maps, using the initial pressure and US features extracted by ResNet-18. To test this US-Unet model, we calculated the blood oxygenation saturation values and total hemoglobin concentrations from 655 regions of interest (ROIs) (421 benign, 200 malignant, and 34 borderline ROIs) obtained from clinical images of 35 patients with ovarian/adnexal lesions. A logistic regression model was used to compute the ROC, the area under the ROC curve (AUC) was 0.94, and the accuracy was 0.89. To the best of our knowledge, this is the first study to reconstruct quantitative PAT with PA signals and US-based structural features.

Energy Metabolism in Gynecological Cancers: A Scoping Review

Determining energy requirements is vital for optimizing nutrition interventions in pro-catabolic conditions such as cancer. Gynecological cancer encompasses the most common malignancies in women, yet there is a paucity of research on its metabolic implications. The aim of this review was to explore the literature related to energy metabolism in gynecological cancers. We were particularly interested in exploring the prevalence of energy metabolism abnormalities, methodological approaches used to assess energy metabolism, and clinical implications of inaccurately estimating energy needs. A search strategy was conducted from inception to 27 July 2021. Studies investigating energy metabolism using accurate techniques in adults with any stage of gynecological cancer and the type of treatment were considered. Of the 874 articles screened for eligibility, five studies were included. The definition of energy metabolism abnormalities varied among studies. Considering this limitation, four of the five studies reported hypermetabolism. One of these studies found that hypermetabolism was more prevalent in ovarian compared to cervical cancer. Of the included studies, one reported normometabolism at the group level; individual-level values were not reported. One of the studies reported hypermetabolism pre- and post-treatment, but normometabolism when re-assessed two years post-treatment. No studies explored clinical implications of inaccurately estimating energy needs. Overall, commonly used equations may not accurately predict energy expenditure in gynecological cancers, which can profoundly impact nutritional assessment and intervention.

Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer

BACKGROUND

Late-stage diagnosis of ovarian cancer, a disease that originates in the ovaries and spreads to the peritoneal cavity, lowers 5-year survival rate from 90% to 30%. Early screening tools that can: i) detect with high specificity and sensitivity before conventional tools such as transvaginal ultrasound and CA-125, ii) use non-invasive sampling methods and iii) longitudinally significantly increase survival rates in ovarian cancer are needed. Studies that employ blood-based screening tools using circulating tumor-cells, -DNA, and most recently tumor-derived small extracellular vesicles (sEVs) have shown promise in non-invasive detection of cancer before standard of care. Our findings in this study show the promise of a sEV-derived signature as a non-invasive longitudinal screening tool in ovarian cancer.

METHODS

Human serum samples as well as plasma and ascites from a mouse model of ovarian cancer were collected at various disease stages. Small extracellular vesicles (sEVs) were extracted using a commercially available kit. RNA was isolated from lysed sEVs, and quantitative RT-PCR was performed to identify specific metastatic gene expression.

CONCLUSION

This paper highlights the potential of sEVs in monitoring ovarian cancer progression and metastatic development. We identified a 7-gene panel in sEVs derived from plasma, serum, and ascites that overlapped with an established metastatic ovarian carcinoma signature. We found the 7-gene panel to be differentially expressed with tumor development and metastatic spread in a mouse model of ovarian cancer. The most notable finding was a significant change in the ascites-derived sEV gene signature that overlapped with that of the plasma-derived sEV signature at varying stages of disease progression. While there were quantifiable changes in genes from the 7-gene panel in serum-derived sEVs from ovarian cancer patients, we were unable to establish a definitive signature due to low sample number. Taken together our findings show that differential expression of metastatic genes derived from circulating sEVs present a minimally invasive screening tool for ovarian cancer detection and longitudinal monitoring of molecular changes associated with progression and metastatic spread.

Current update on the molecular genetics and management of hereditary ovarian cancers: a primer for radiologists

More than one-fifth of ovarian cancers are hereditary, with most of them caused by BRCA genes. Malignant ovarian neoplasms are primarily epithelial tumors, a heterogeneous group of tumors with variable genetic backgrounds that translate into different biologic behaviors and morphologic features. Radiologists play an increasingly important role in the diagnosis and management of oncology patients. Familiarity with hereditary ovarian cancers will have a positive impact on patient management and radiologists' involvement in the multidisciplinary approach needed for this delicate patient population. In this paper, we review the basic histologic and genetic backgrounds of ovarian tumors with an emphasis on hereditary ovarian cancers, as well as the effects that these factors have on patient workup, primarily with regard to imaging studies.

Imaging of ovarian cancers using enzyme activatable probes with second near-infrared window emission

We herein develop two β-galactosidase (β-Gal) activatable NIR fluorescent probes for visualizing ovarian cancers. Particularly, probe BOD-M-βGal produced NIR-II emission light at 900-1300 nm upon β-Gal activation. By using our activatable and target specific NIR-II probe for deep-tissue imaging of β-Gal overexpressed ovarian cancer cells, rapid and accurate imaging of ovarian tumors in nude mice was achieved.

Assessment of peritoneal microbial features and tumor marker levels as potential diagnostic tools for ovarian cancer

Epithelial ovarian cancer (OC) is the most deadly cancer of the female reproductive system. To date, there is no effective screening method for early detection of OC and current diagnostic armamentarium may include sonographic grading of the tumor and analyzing serum levels of tumor markers, Cancer Antigen 125 (CA-125) and Human epididymis protein 4 (HE4). Microorganisms (bacterial, archaeal, and fungal cells) residing in mucosal tissues including the gastrointestinal and urogenital tracts can be altered by different disease states, and these shifts in microbial dynamics may help to diagnose disease states. We hypothesized that the peritoneal microbial environment was altered in patients with OC and that inclusion of selected peritoneal microbial features with current clinical features into prediction analyses will improve detection accuracy of patients with OC. Blood and peritoneal fluid were collected from consented patients that had sonography confirmed adnexal masses and were being seen at SIU School of Medicine Simmons Cancer Institute. Blood was processed and serum HE4 and CA-125 were measured. Peritoneal fluid was collected at the time of surgery and processed for Next Generation Sequencing (NGS) using 16S V4 exon bacterial primers and bioinformatics analyses. We found that patients with OC had a unique peritoneal microbial profile compared to patients with a benign mass. Using ensemble modeling and machine learning pathways, we identified 18 microbial features that were highly specific to OC pathology. Prediction analyses confirmed that inclusion of microbial features with serum tumor marker levels and control features (patient age and BMI) improved diagnostic accuracy compared to currently used models. We conclude that OC pathogenesis alters the peritoneal microbial environment and that these unique microbial features are important for accurate diagnosis of OC. Our study warrants further analyses of the importance of microbial features in regards to oncological diagnostics and possible prognostic and interventional medicine.

Detecting TP53 mutations in diagnostic and archival liquid-based Pap samples from ovarian cancer patients using an ultra-sensitive ddPCR method

High-grade serous ovarian cancer (HGSOC) is the most common subtype of epithelial ovarian cancer and early detection is challenging. TP53 mutations are a hallmark of HGSOC and detection of these mutations in liquid-based Pap samples could provide a method for early diagnosis. Here we evaluate the use of IBSAFE, an ultra-sensitive droplet digital PCR (ddPCR) method, for detecting TP53 mutations in liquid-based Pap samples collected from fifteen women at the time of diagnosis (diagnostic samples) and/or up to seven years prior to diagnosis (archival samples). We analysed tumours for somatic TP53 mutations with next generation sequencing and were able to detect the corresponding mutations in diagnostic samples from six of eight women, while one patient harboured a germline mutation. We further detected a mutation in an archival sample obtained 20 months prior to the ovarian cancer diagnosis. The custom designed IBSAFE assays detected minor allele frequencies (MAFs) with very high assay sensitivity (MAF = 0.0068%) and were successful despite low DNA abundance (0.17–206.14 ng, median: 17.27 ng). These results provide support for further evaluation of archival liquid-based Pap samples for diagnostic purposes and demonstrate that ultra-sensitive ddPCR should be evaluated for ovarian cancer screening in high-risk groups or in the recurrent setting.

NF-κB Signaling in Ovarian Cancer

The NF-κB signaling pathway is a master and commander in ovarian cancer (OC) that promotes chemoresistance, cancer stem cell maintenance, metastasis and immune evasion. Many signaling pathways are dysregulated in OC and can activate NF-κB signaling through canonical or non-canonical pathways which have both overlapping and distinct roles in tumor progression. The activation of canonical NF-κB signaling has been well established for anti-apoptotic and immunomodulatory functions in response to the tumor microenvironment and the non-canonical pathway in cancer stem cell maintenance and tumor re-initiation. NF-κB activity in OC cells helps to create an immune-evasive environment and to attract infiltrating immune cells with tumor-promoting phenotypes, which in turn, drive constitutive NF-κB activation in OC cells to promote cell survival and metastasis. For these reasons, NF-κB is an attractive target in OC, but current strategies are limited and broad inhibition of this major signaling pathway in normal physiological and immunological functions may produce unwanted side effects. There are some promising pre-clinical outcomes from developing research to target and inhibit NF-κB only in the tumor-reinitiating cancer cell population of OC and concurrently activate canonical NF-κB signaling in immune cells to promote anti-tumor immunity.

Weekly cisplatin for the treatment of patients with ovarian cancer: A protocol for a systematic review of randomized controlled trial

BACKGROUND

Ovarian cancer (OC) is one of the most leading causes of deaths in the Chinese women. The objective of this protocol is to perform a full-scale systematic review on the efficacy of weekly cisplatin (WC) for the treatment of patients with OC.

METHODS

Data sources will comprise of PubMed, PsycINFO, Scopus, Opengrey, Cochrane Central Register of Controlled Trials, Embase, Cumulative Index to Nursing and Allied Health Literature, Web of Science, Allied and Complementary Medicine Database, and Chinese Biomedical Literature Database. All relevant randomized controlled trials from searched databases will be identified from their inception to the present. A defined search strategy will be implemented along with eligibility criteria. Relevant data will be extracted according to the predefined data collection form. Methodologic quality will be assessed by using Cochrane risk of bias tool; and data pooled and meta-analysis will be conducted by using fixed-effects, or random-effects model with RevMan 5.3 software.

RESULTS

This proposed systematic review will evaluate the efficacy of WC for patients with OC.

CONCLUSION

The findings of this study may summarize the latest evidence for the WC on OC.

ETHICS AND DISSEMINATION

Ethical approval is not required for this study, because it will be based on published studies, and existing sources of literature. The results of this study will be disseminated through peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

PROSPERO CRD42018120938.

Progesterone reduces cell survival in primary cultures of endometrioid ovarian cancer

Background

Ovarian cancer is the most lethal of all gynecologic malignancies. The relationship between sexual steroids receptors and ovarian cancer progression has been largely evaluated. The presence of progesterone receptors has been associated with an increase of a disease-free period and overall survival in patients with ovarian carcinoma. In the present study, primary cultures of ovarian carcinoma obtained from 35 patients diagnosed with epithelial ovarian cancer were evaluated for cell survival after treatment with 10^− 8 M of 17β-estradiol, progesterone, testosterone and dihydrotestosterone.

Results

The results were analyzed considering histological subtypes: low grade serous, high grade serous, endometrioid and mucinous carcinoma; clear cell carcinoma was not included due to failure in obtaining successful cultures of this subtype. A significant reduction of cell survival was observed after progesterone treatment in endometrioid ovarian carcinoma. Changes were not observed in low grade serous, high grade serous and mucinous carcinoma. The effect of progesterone was related to the presence of progesterone receptor (PR), a 43% reduction in the cell number was observed in PR (+) endometrioid ovarian carcinoma.

Conclusions

This study supports the importance of progesterone and the presence of progesterone receptor in the reduction of ovarian cancer progression in the endometrioid ovarian carcinoma.