Molecular Biomarkers for the Early Detection of Ovarian Cancer

MicroRNAs in meningiomas: Potential biomarkers and therapeutic targets

Meningiomas, characterized primarily as benign intracranial or spinal tumors, present distinctive challenges due to their variable clinical behavior, with certain cases exhibiting aggressive features linked to elevated morbidity and mortality. Despite their prevalence, the underlying molecular mechanisms governing the initiation and progression of meningiomas remain insufficiently understood. MicroRNAs (miRNAs), small endogenous non-coding RNAs orchestrating post-transcriptional gene expression, have garnered substantial attention in this context. They emerge as pivotal biomarkers and potential therapeutic targets, offering innovative avenues for managing meningiomas. Recent research delves into the intricate mechanisms by which miRNAs contribute to meningioma pathogenesis, unraveling the molecular complexities of this enigmatic tumor. Meningiomas, originating from arachnoid meningothelial cells and known for their gradual growth, constitute a significant portion of intracranial tumors. The clinical challenge lies in comprehending their progression, particularly factors associated with brain invasion and heightened recurrence rates, which remain elusive. This comprehensive review underscores the pivotal role of miRNAs, accentuating their potential to advance our comprehension of meningioma biology. Furthermore, it suggests promising directions for developing diagnostic biomarkers and therapeutic interventions, holding the promise of markedly improved patient outcomes in the face of this intricate and variable disease.

Ovarian-adnexal reporting and data system ultrasound evaluation and pathological characteristics of ovarian collision tumor

BACKGROUND

Collision tumor are neoplasms, including two histologically distinct tumors that coexist in the same mass without histological admixture. The incidence of collision tumor is low and is rare clinically.

AIM

To investigate ultrasound images and application of ovarian-adnexal reporting and data system (O-RADS) to evaluate the risk and pathological characteristics of ovarian collision tumor.

METHODS

This study retrospectively analyzed 17 cases of ovarian collision tumor diagnosed pathologically from January 2020 to December 2023. All clinical features, ultrasound images and histopathological features were collected and analyzed. The O-RADS score was used for classification. The O-RADS score was determined by two senior doctors in the gynecological ultrasound group. Lesions with O-RADS score of 1-3 were classified as benign tumors, and lesions with O-RADS score of 4 or 5 were classified as malignant tumors.

RESULTS

There were 17 collision tumors detected in 16 of 6274 patients who underwent gynecological surgery. The average age of 17 women with ovarian collision tumor was 36.7 years (range 20-68 years), in whom, one occurred bilaterally and the rest occurred unilaterally. The average tumor diameter was 10 cm, of which three were 2-5 cm, 11 were 5-10 cm, and three were > 10 cm. Five (29.4%) tumors with O-RADS score 3 were endometriotic cysts with fibroma/serous cystadenoma, and unilocular or multilocular cysts contained a small number of parenchymal components. Eleven (64.7%) tumors had an O-RADS score of 4, including two in category 4A, six in category 4B, and three in category 4C; all of which were multilocular cystic tumors with solid components or multiple papillary components. One (5.9%) tumor had an O-RADS score of 5. This case was a solid mass, and a small amount of pelvic effusion was detected under ultrasound. The pathology was high-grade serous cystic cancer combined with cystic mature teratoma. There were nine (52.9%) tumors with elevated serum carbohydrate antigen (CA)125 and two (11.8%) with elevated serum CA19-9. Histological and pathological results showed that epithelial-cell-derived tumors combined with other tumors were the most common, which was different from previous results.

CONCLUSION

The ultrasound images of ovarian collision tumor have certain specificity, but diagnosis by preoperative ultrasound is difficult. The combination of epithelial and mesenchymal cell tumors is one of the most common types of ovarian collision tumor. The O-RADS score of ovarian collision tumor is mostly ≥ 4, which can sensitively detect malignant tumors.

LncRNA HCP5 Facilitates the Progression of Ovarian Cancer by Interacting with the PTBP1 Protein

Ovarian cancer (OC) is a major gynecological malignancy with an annually increasing morbidity that poses a significant threat to the health of women worldwide. Most OC patients are diagnosed at an advanced stage. It is an urgent task to search for biomarkers for the diagnosis and treatment of OC. The lncRNA HCP5 (HCP5) was recently identified as an oncogene in several malignant tumors. However, the function of HCP5 in OC has rarely been reported. Herein, the levels of HCP5 and PTBP1 were found to be markedly increased in malignant OC tumor tissues and OC cell lines. In HCP5-silenced SKOV-3 and HEY cells, cell viability was markedly decreased, and the apoptosis rate was significantly increased, with more cells exhibiting G0/G1 arrest and increased expression of cleaved caspase-3 and cleaved caspase-9. Furthermore, the number of migrated cells, number of invaded cells, and migration distance were notably decreased by the knockdown of HCP5 in SKOV-3 cells and HEY cells. In the xenograft model established with SKOV-3 cells, the number of lung metastases, tumor growth, and Ki67 expression in tumor tissues were markedly decreased by the knockdown of HCP5, accompanied by an increased percentage of TUNEL-positive cells. HCP5 was found to be localized in the nucleus, and the interaction between HCP5 and PTBP1 was verified by RNA pull-down and RNA immunoprecipitation assays. Furthermore, in HCP5-overexpressing OC cells, the impacts of HCP5 on cell proliferation and apoptosis were significantly attenuated by the knockdown of PTBP1. Collectively, these results indicate that HCP5 facilitates the progression of OC by interacting with the PTBP1 protein.

Optimal Cut-Point Selection Methods Under Binary Classification When Subclasses Are Involved

In practice, we often encounter binary classification problems where both main classes consist of multiple subclasses. For example, in an ovarian cancer study where biomarkers were evaluated for their accuracy of distinguishing noncancer cases from cancer cases, the noncancer class consists of healthy subjects and benign cases, while the cancer class consists of subjects at both early and late stages. This article aims to provide a large number of optimal cut-point selection methods for such setting. Furthermore, we also study confidence interval estimation of the optimal cut-points. Simulation studies are carried out to explore the performance of the proposed cut-point selection methods as well as confidence interval estimation methods. A real ovarian cancer data set is analyzed using the proposed methods.

TP53 somatic evolution in cervical liquid-based cytology and blood from individuals with and without ovarian cancer and BRCA1 or BRCA2 germline mutations

Somatic TP53 mutations are prevalent in normal tissue but little is known about their association with cancer risk. Cervical liquid-based cytology (LBC), commonly known as Pap test, provides an accessible gynecological sample to test the value of TP53 somatic mutations as a biomarker for high-grade serous ovarian cancer (HGSC), a cancer type mostly driven by TP53 mutations. We used ultra-deep duplex sequencing to analyze TP53 mutations in LBC and blood samples from 70 individuals (30 with and 40 without HGSC) undergoing gynecologic surgery, 30 carrying BRCA1 or BRCA2 germline pathogenic variants (BRCApv). Only 30% of the tumor mutations were found in LBC samples. However, TP53 pathogenic mutations were identified in nearly all LBC and blood samples, with only 5.4% of mutations in LBC (20/368) also found in the corresponding blood sample. TP53 mutations were more abundant in LBC than in blood and increased with age in both sample types. BRCApv carriers with HGSC had more TP53 clonal expansions in LBC than BRCApv carriers without cancer. Our results show that, while not useful for direct cancer detection, LBC samples capture TP53 mutation burden in the gynecological tract, presenting potential value for cancer risk assessment in individuals at higher hereditary risk for ovarian cancer.

Ultrasensitive and label-free electrochemical immunosensor for the detection of the ovarian cancer biomarker CA125 based on CuCo-ONSs@AuNPs nanocomposites

Cancer antigen 125 (CA125) is pivotal as a tumor marker in early ovarian cancer prevention and diagnosis. In this work, we introduced an ultrasensitive label-free electrochemical immunosensor tailored for CA125 detection, leveraging nanogold-functionalized copper-cobalt oxide nanosheets (CuCo-ONSs@AuNPs) as nanocomposites. For the inaugural application, copper-cobalt oxide nanosheets delivered the requisite DPV electrochemical response for the immunosensors. Their large specific surface area and commendable electrical conductivity amplify electron transfer and enable significant gold nanoparticle loading. Concurrently, AuNPs offer a plethora of active sites, facilitating easy immobilization of biomolecules via the bond between amino groups and AuNPs. We employed scanning electron microscopy, transmission electron microscopy, and x-ray photoelectron spectroscopy to characterize the nanomaterials' surface morphology and elemental composition. The electrochemical sensor response signals were ascertained using differential pulse voltammetry. Under optimal conditions, the immunosensor exhibited a linear detection range from 1×10-7 U/mL to 1×10-3 U/mL and a detection limit of 3.9×10-8 U/mL (S/N=3). The proposed label-free electrochemical immunosensor furnishes a straightforward, dependable, and sensitive approach for CA125 quantification and stands as a promising method for clinical detection of other tumor markers.

Metabolomic biomarkers for benign conditions and malignant ovarian cancer: Advancing early diagnosis

BACKGROUND

Ovarian cancer (OC) is a major global cause of death among gynecological cancers, with a high mortality rate. Early diagnosis, distinguishing between benign conditions and early malignant OC forms, is vital for successful treatment. This research investigates serum metabolites to find diagnostic biomarkers for early OC identification.

METHODS

Metabolomic profiles derived from the serum of 60 patients with benign conditions and 60 patients with malignant OC were examined using ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). Comparative analysis revealed differential metabolites linked to OC, aiding biomarker identification for early-diagnosis of OC via machine learning features. The predictive ability of these biomarkers was evaluated against the traditional biomarker, cancer antigen 125 (CA125).

RESULTS

84 differential metabolites were identified, including 2-Thiothiazolidine-4-carboxylic acid (TTCA), Methionyl-Cysteine, and Citrulline that could serve as potential biomarkers to identify benign conditions and malignant OC. In the diagnosis of early-stage OC, the area under the curve (AUC) for Citrulline was 0.847 (95 % Confidence Interval (CI): 0.719-0.974), compared to 0.770 (95 % CI: 0.596-0.944) for TTCA, and 0.754 for Methionine-Cysteine (95 % CI: 0.589-0.919). These metabolites demonstrate a superior diagnostic capability relative to CA125, which has an AUC of 0.689 (95 % CI: 0.448-0.931). Among these biomarkers, Citrulline stands out as the most promising. Additionally, in the diagnosis of benign conditions and malignant OC, using logistic regression to combine potential biomarkers with CA125 has an AUC of 0.987 (95 % CI: 0.9708-1) has been proven to be more effective than relying solely on the traditional biomarker CA125 with an AUC of 0.933 (95 % CI: 0.870-0.996). Furthermore, among all the differential metabolites, lipid metabolites dominate, significantly impacting glycerophospholipid metabolism pathway.

CONCLUSION

The discovered serum metabolite biomarkers demonstrate excellent diagnostic performance for distinguishing between benign conditions and malignant OC and for early diagnosis of malignant OC.

Polymer-Based Terbium Complex as a Fluorescent Probe for Cancer Antigen 125 Detection: A Promising Tool for Early Diagnosis of Ovarian Cancer

A novel photoprobe, Tb-acetylacetone (Tb-ACAC) doped within a modified epoxy cellulose polymer immobilized with CA-125 monoclonal antibody, offers an accurate and highly selective method for early ovarian cancer (OC) diagnosis by detecting cancer antigen 125 (CA-125) in serum samples. This approach leverages quenching of the Tb-ACAC luminescence upon binding to CA-125. Characterization of the photoprobe film through UV-vis and fluorescence measurements confirmed the presence of Tb-ACAC within the polymer matrix. In aqueous solution (pH 6.8, λex = 365 nm), the characteristic emission band of Tb-ACAC at λem = 546.2 nm exhibited significant quenching upon CA-125 binding. This quenching effect enabled the sensitive and specific detection of CA-125 in diverse serum samples from OC patients, demonstrating the applicability, simplicity, and effectiveness of this novel approach.

Diagnostic Utility of Selected Matrix Metalloproteinases (MMP-2, MMP-3, MMP-11, MMP-26), HE4, CA125 and ROMA Algorithm in Diagnosis of Ovarian Cancer

Ovarian cancer (OC) has an unfavorable prognosis. Due to the lack of effective screening tests, new diagnostic methods are being sought to detect OC earlier. The aim of this study was to evaluate the concentration and diagnostic utility of selected matrix metalloproteinases (MMPs) as OC markers in comparison with HE4, CA125 and the ROMA algorithm. The study group consisted of 120 patients with OC; the comparison group consisted of 70 patients with benign lesions and 50 healthy women. MMPs were determined via the ELISA method, HE4 and CA125 by CMIA. Patients with OC had elevated levels of MMP-3 and MMP-11, similar to HE4, CA125 and ROMA values. The highest SE, SP, NPV and PPV values were found for MMP-26, CA125 and ROMA in OC patients. Performing combined analyses of ROMA with selected MMPs increased the values of diagnostic parameters. The topmost diagnostic power of the test was obtained for MMP-26, CA125, HE4 and ROMA and performing combined analyses of MMPs and ROMA enhanced the diagnostic power of the test. The obtained results indicate that the tested MMPs do not show potential as stand-alone OC biomarkers, but can be considered as additional tests to raise the diagnostic utility of the ROMA algorithm.

Transcriptomic Analysis of Hub Genes Reveals Associated Inflammatory Pathways in Estrogen-Dependent Gynecological Diseases

Gynecological diseases are triggered by aberrant molecular pathways that alter gene expression, hormonal balance, and cellular signaling pathways, which may lead to long-term physiological consequences. This study was able to identify highly preserved modules and key hub genes that are mainly associated with gynecological diseases, represented by endometriosis (EM), ovarian cancer (OC), cervical cancer (CC), and endometrial cancer (EC), through the weighted gene co-expression network analysis (WGCNA) of microarray datasets sourced from the Gene Expression Omnibus (GEO) database. Five highly preserved modules were observed across the EM (GSE51981), OC (GSE63885), CC (GSE63514), and EC (GSE17025) datasets. The functional annotation and pathway enrichment analysis revealed that the highly preserved modules were heavily involved in several inflammatory pathways that are associated with transcription dysregulation, such as NF-kB signaling, JAK-STAT signaling, MAPK-ERK signaling, and mTOR signaling pathways. Furthermore, the results also include pathways that are relevant in gynecological disease prognosis through viral infections. Mutations in the ESR1 gene that encodes for ERα, which were shown to also affect signaling pathways involved in inflammation, further indicate its importance in gynecological disease prognosis. Potential drugs were screened through the Drug Repurposing Encyclopedia (DRE) based on the up-and downregulated hub genes, wherein a bacterial ribosomal subunit inhibitor and a benzodiazepine receptor agonist were the top candidates. Other drug candidates include a dihydrofolate reductase inhibitor, glucocorticoid receptor agonists, cholinergic receptor agonists, selective serotonin reuptake inhibitors, sterol demethylase inhibitors, a bacterial antifolate, and serotonin receptor antagonist drugs which have known anti-inflammatory effects, demonstrating that the gene network highlights specific inflammatory pathways as a therapeutic avenue in designing drug candidates for gynecological diseases.

Limited Immunogenicity of an HLA-A*03:01-restricted Epitope of Erv-k-env in Non-hiv-1 Settings: Implications for Adoptive Cell Therapy in Cancer

Repetitive elements (REs) are often expressed at higher levels in tumor cells than normal cells, implicating these genomic regions as an untapped pool of tumor-associated antigens. In ovarian cancer (OC), protein from the RE ERV-K is frequently expressed by tumor cells. Here we determined whether the targeting of a previously identified immunogenic epitope in the envelope gene (env) of ERV-K resulted in target antigen specificity in non-HIV-1 settings. We found that transducing healthy donor T cells with an ERV-K-Env-specific T cell receptor construct resulted in antigen specificity only when co-cultured with HLA-A*03:01 B lymphoblastoid cells. Furthermore, these transduced T cells were not specific for HLA-A*03:01 + OC cells nor for the cognate peptide in HLA-matched systems from multiple healthy donors. These data suggest that the ERV-K-Env epitope recognized by this T cell receptor is of low immunogenicity and has limited potential as a T cell target for OC.

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

The deregulation of arachidonic acid metabolism in ovarian cancer

Arachidonic acid (AA) is a crucial polyunsaturated fatty acid in the human body, metabolized through the pathways of COX, LOX, and cytochrome P450 oxidase to generate various metabolites. Recent studies have indicated that AA and its metabolites play significant regulatory roles in the onset and progression of ovarian cancer. This article examines the recent research advancements on the correlation between AA metabolites and ovarian cancer, both domestically and internationally, suggesting their potential use as biological markers for early diagnosis, targeted therapy, and prognosis monitoring.

Selected markers of ovarian cancer and their relation to targeted therapy (Review)

Despite advances in surgical treatment techniques and chemotherapy-including anti-angiogenic and immune poly (ADP-ribose) polymerase inhibitors, the 5-year survival rate in ovarian cancer (OC) remains low. The reasons for this are the diagnosis of cancer in advanced clinical stages, chemoresistance and cancer recurrence. New therapeutic approaches are being developed, including the search for new biomarkers that are also targets for targeted therapy. The present review describes new molecular markers with relevance to targeted therapy, which to date have been studied only in experimental research. These include the angiogenic protein angiopoietin-2, the transmembrane glycoprotein ectonucleotide pyrophosphatase/phosphodiesterase 1, the adhesion protein E-cadherin, the TIMP metallopeptidase inhibitor 1 and Kruppel-like factor 7. Drugs affecting cancer stem cells (CSCs) in OC, such as metformin and salinomycin, as well as inhibitors of CSCs markers aldehyde dehydrogenase 1 (with the drug ATRA) and the transcription factor Nanog homeobox (microRNA) are also discussed. A new approach to prevention and possible therapies under investigation such as development of vaccines containing a subpopulation of CD117(+) and CD44(+) stem cells with a promising option for use in women with OC was described.

Serum anti-CFL1, anti-EZR, and anti-CYPA autoantibody as diagnostic markers in ovarian cancer

The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAs) and explore a diagnostic panel for Ovarian cancer (OC). Enzyme-linked immunosorbent assay was used to detect the expression of five anti-TAA autoantibodies in the discovery (70 OC and 70 normal controls) and validation cohorts (128 OC and 128 normal controls). Machine learning methods were used to construct a diagnostic panel. Serum samples from 81 patients with benign ovarian disease were used to identify the specificity of anti-TAA autoantibodies for OC. In both the discovery and validation cohorts, the expression of anti-CFL1, anti-EZR, anti-CYPA, and anti-PFN1 was higher in patients with OC than that in normal controls. The area under the receiver operating characteristic curve, sensitivity, and specificity of the panel containing anti-CFL1, anti-EZR, and anti-CYPA were 0.762, 55.56%, and 81.31%. The panel identified 53.06%, 53.33%, and 51.11% of CA125 negative, HE4 negative and the Risk of Ovarian Malignancy Algorithm negative OC patients, respectively. The combination of the three anti-TAA autoantibodies can serve as a favorable diagnostic tool for OC and has the potential to be a complementary biomarker for CA125 and HE4 in the diagnosis of ovarian cancer.

Deciphering resistance mechanisms and novel strategies to overcome drug resistance in ovarian cancer: a comprehensive review

Ovarian cancer is among the most lethal gynecological cancers, primarily due to the lack of specific symptoms leading to an advanced-stage diagnosis and resistance to chemotherapy. Drug resistance (DR) poses the most significant challenge in treating patients with existing drugs. The Food and Drug Administration (FDA) has recently approved three new therapeutic drugs, including two poly (ADP-ribose) polymerase (PARP) inhibitors (olaparib and niraparib) and one vascular endothelial growth factor (VEGF) inhibitor (bevacizumab) for maintenance therapy. However, resistance to these new drugs has emerged. Therefore, understanding the mechanisms of DR and exploring new approaches to overcome them is crucial for effective management. In this review, we summarize the major molecular mechanisms of DR and discuss novel strategies to combat DR.

The Association between Ovarian Cancer and the Incidence of Newly Developed Dry Eye Disease: A Nationwide Population-Based Study

We aim to investigate the potential correlation between the presence of ovarian cancer and the development of dry eye disease (DED) via the usage of the Longitudinal Health Insurance Database (LHID) of Taiwan. A retrospective cohort study was executed, and patients with ovarian cancer were selected according to the diagnostic and procedure codes. One ovarian cancer patient was matched to four non-ovarian cancer participants which served as control group, and a total of 4992 and 19,968 patients constructed the ovarian cancer and control groups, respectively. The primary outcome in the current study is the development of DED according to the diagnostic and procedure codes. Cox proportional hazard regression was utilized to produce the adjusted hazard ratio (aHR) and related 95% confidence interval (CI) of DED between the two groups. There were 542 and 2502 DED events observed in the ovarian cancer group and the control group, respectively. The ovarian cancer group illustrated a significantly higher incidence of DED development than the control group after the adjustment of several confounders (aHR: 1.10, 95% CI: 1.01-1.21, p = 0.040). In the subgroup analysis stratified by age, ovarian cancer patients aged older than 60 years showed a higher incidence of DED compared to the non-ovarian cancer population (aHR: 1.19, 95% CI: 1.08-1.28, p = 0.011). In addition, ovarian cancer patients with a disease duration longer than five years also showed higher incidence of DED formation than the non-ovarian cancer population (aHR: 1.13, 95% CI: 1.04-1.22, p = 0.027). In conclusion, the presence of ovarian cancer is associated with higher incidence of subsequent DED, especially in those older than 60 years and with a disease interval of more than five years.

An LRPPRC-HAPSTR1-PSMD14 interaction regulates tumor progression in ovarian cancer

Ovarian cancer is the second most common cause of gynecologic cancer death. Chemoresistance and metastasis remain major challenges for current treatment. Previously, HAPSTR1 was shown to be a target gene of a paclitaxel resistance-associated miRNA. However, the biological function and underlying molecular mechanisms of HAPSTR1 in ovarian cancer progression remain unclear. Herein, we aimed to measure HAPSTR1 expression in ovarian cancer specimens and examine its correlations with clinical features and key functional interactions with other genes and proteins. An immunohistochemistry assay showed that HAPSTR1 was overexpressed in ovarian cancer tissues and was significantly associated with the FIGO stage and clinical outcome. HAPSTR1 overexpression promoted proliferation, invasion and migration in cellular and mouse models, whereas inhibition induced the opposite effects. In addition, HAPSTR1 stimulated the EMT pathway and affected the expression of autophagy biomarkers. Mechanistically, we demonstrated that HAPSTR1 is bound to LRPPRC and PSMD14 via immunoprecipitation. HAPSTR1 suppressed LRPPRC ubiquitination and recruited PSMD14 to interact with LRPPRC. Moreover, LRPPRC knockdown reversed HAPSTR1-mediated improvement in cellular proliferation, invasion, and migration. Our study is the first detailed and comprehensive analysis of HAPSTR1 in cancer progression and offers an experimental basis for the clinical treatment of ovarian carcinoma.

Ovarian serous carcinoma with stomach metastasis: a rare case report and literature review

Ovarian cancer is a common tumor among women. It is often asymptomatic in the early stages, with most cases already at stage III to IVE at the time of diagnosis. Direct spread and lymphatic metastasis are the primary modes of metastasis, whereas hematogenous spread is rare. An initial diagnosis of ovarian cancer that has metastasized to the stomach is also uncommon. Therefore, clear treatment methods and prognostic data for such metastasis are lacking. In our hospital, we encountered a patient with an initial imaging diagnosis of a gastric tumor and a history of an ovarian tumor with endoscopic abdominal metastasis. Based on the characteristics of the case, the two tumors were considered to be the same. After chemotherapy, a partial response was observed in the stomach and pelvic lesions, suggesting the effectiveness of the treatment. Through three treatments of recurrence, gastroscopy confirmed the stomach to be a metastatic site. Therefore, determining the primary source of advanced tumors is crucial in guiding treatment decisions. Clinicians must approach this comprehensively, relying on thorough evaluation and personal experience.

Portulaca oleracea L. polysaccharide inhibits ovarian cancer via inducing ACSL4-dependent ferroptosis

The antitumor effect of Portulaca oleracea L. polysaccharide (POL) has been demonstrated, but whether it curbs the development of ovarian cancer has not been reported. Here, we treated ovarian cancer cells with different concentrations of POL, detected cell activity by CCK-8 assay, and apoptosis rate by flow cytometry. The results showed that SKOV3 and Hey cell survival decreased with increasing POL concentration in a dose-dependent manner. POL significantly inhibited ovarian cancer cell migration and increased cell death compared with the control group. Ferroptosis inhibitors, but not apoptosis, necrosis, and autophagy inhibitors, reversed POL-induced cell death. Further studies revealed that POL promoted the accumulation of lipid reactive oxygen species (ROS), Fe2+, malondialdehyde (MDA), and decreased glutathione (GSH) production. Moreover, POL significantly increased the mortality of ovarian cancer cells. In vivo studies confirmed that POL reduced the volume and weight of tumors and increased the levels of Fe2+ and MDA in mice in vivo. Western blot assay revealed that POL increased the expression of ACSL4 in ovarian cancer cells as well as in tumors in mice in vivo. More importantly, the POL-mediated increase in lipid ROS, Fe2+, MDA, and decrease in GSH were significantly reversed after knocking down ACSL4 in ovarian cancer cells. Thus, POL can effectively inhibit ovarian cancer development, which may be achieved by increasing ACSL4-mediated ferroptosis. These results suggest that POL has the potential to be a potential drug for targeted treatment of ovarian cancer.

Recent Advances in Nanotechnology-Based Drug Delivery Systems for the Diagnosis and Treatment of Reproductive Disorders

Over the past decade, nanotechnology has seen extensive integration into biomedical applications, playing a crucial role in biodetection, drug delivery, and diagnostic imaging. This is especially important in reproductive health care, which has become an emerging and significant area of research. Global concerns have intensified around disorders such as infertility, endometriosis, ectopic pregnancy, erectile dysfunction, benign prostate hyperplasia, sexually transmitted infections, and reproductive cancers. Nanotechnology presents promising solutions to address these concerns by introducing innovative tools and techniques, facilitating early detection, targeted drug delivery, and improved imaging capabilities. Through the utilization of nanoscale materials and devices, researchers can craft treatments that are not only more precise but also more effective, significantly enhancing outcomes in reproductive healthcare. Looking forward, the future of nanotechnology in reproductive medicine holds immense potential for reshaping diagnostics, personalized therapies, and fertility preservation. The utilization of nanotechnology-driven drug delivery systems is anticipated to elevate treatment effectiveness, minimize side effects, and offer patients therapies that are not only more precise but also more efficient. This review aims to delve into the various types, properties, and preparation techniques of nanocarriers specifically designed for drug delivery in the context of reproductive disorders, shedding light on the current landscape and potential future directions in this dynamic field.

High-grade serous papillary ovarian carcinoma combined with nonkeratinizing squamous cell carcinoma of the cervix: a case report

Multiple primary malignant neoplasms are a rare gynecologic malignancy; particularly, cases originating from the heterologous organs, such as the ovary and cervix. Here, we report a case of two primary malignant neoplasms in a patient who had undergone laparoscopic radical hysterectomy + bilateral salpingo-oophorectomy + pelvic lymph node dissection + para-aortic lymphadenectomy + appendectomy + omentectomy + metastasectomy under general anesthesia. The patient experienced complete remission after six courses of postoperative chemotherapy with a standard Taxol and Carboplatin regimen. Genetic testing was performed to detect BRCA2 mutations, and poly (ADP-ribose) polymerase (PARP) inhibitors were used for maintenance therapy.

Clinical analysis of 12 cases of ovarian neuroendocrine carcinoma

BACKGROUND

Neuroendocrine neoplasms of the female genital tract are rare.

AIM

To enhance our clinical understanding of neuroendocrine carcinoma (NEC) of the ovary.

METHODS

A retrospective review was conducted on 12 patients diagnosed with NEC of the ovary, analyzing clinicopathological characteristics, treatment modalities, and survival status.

RESULTS

The median age at diagnosis was 34.5 years (range: 20 to 62 years). Among the 12 cases, 9 were small cell carcinoma of the ovary and 3 were large cell NEC. Five cases were stage I tumors, one case was stage IV, and six cases were stage III. Eleven patients underwent surgery as part of their treatment. All patients received adjuvant chemotherapy. Among the 12 patients, one patient received radiotherapy, and one patient with a BRCA2 mutation was administered PARP inhibitor maintenance after chemotherapy. The median progression-free survival was 13 months, and the median overall survival was 19.5 months. Four cases remained disease-free, while eight cases experienced tumor recurrence, including three cases that resulted in death due to disease recurrence.

CONCLUSION

NEC of the ovary is a rare condition that is more common in women of childbearing age and is associated with aggressive behavior and poor clinical outcomes. Surgical resection remains the mainstay of treatment, with some patients benefiting from adjuvant chemoradiation therapy.

Identification of glycosyltransferase-related genes signature and integrative analyses in patients with ovarian cancer

BACKGROUND

Glycosyltransferases (GT) play a crucial role in glycosylation reactions, and aberrant expression of glycosyltransferase-related genes (GTs) leads to abnormal glycosylation, which is associated with tumor progression. However, the prognostic value of aberrant expression of GTs in ovarian cancer (OC) and the correlation between GTs and tumor microenvironment (TME) remain unknown.

METHODS

TCGA and GSE53963 databases were used to obtain data on OC patient samples. The association of GTs with OC was analyzed. Molecular subtypes were identified by consensus unsupervised clustering, followed by immune infiltration and functional enrichment analyses. Survival analysis was performed using Kaplan-Meier curves and log-rank tests. Least Absolute Shrinkage and Selection Operator (LASSO) and multifactorial cox regression were used to screen for signature genes associated with OC and used to establish prognostic models.

RESULT

OC patients were categorized into 5 GTs clusters using consensus unsupervised cluster analysis. Clusters D and E showed significant differences between survival, signaling pathways and immune infiltration. Then, a risk model was developed based on the 12 signature genes, which provides a more accurate evaluation of the prognosis of OC patients. We categorized patients into high-risk and low-risk groups based on the risk score and found that the survival of patients in the high-risk group was significantly lower than that in the low-risk group. Moreover, the risk score was significantly correlated with tumor microenvironment, immune infiltration, and chemotherapy sensitivity.

CONCLUSION

Overall, we performed a comprehensive analysis of GTs in OC patients and developed a risk model for OC. Our findings will provide a new insight to OC prognosis and treatment.

Paradigm Shift: A Comprehensive Review of Ovarian Cancer Management in an Era of Advancements

Ovarian cancer (OC) is the female genital malignancy with the highest lethality. Patients present a poor prognosis mainly due to the late clinical presentation allied with the common acquisition of chemoresistance and a high rate of tumour recurrence. Effective screening, accurate diagnosis, and personalised multidisciplinary treatments are crucial for improving patients' survival and quality of life. This comprehensive narrative review aims to describe the current knowledge on the aetiology, prevention, diagnosis, and treatment of OC, highlighting the latest significant advancements and future directions. Traditionally, OC treatment involves the combination of cytoreductive surgery and platinum-based chemotherapy. Although more therapeutical approaches have been developed, the lack of established predictive biomarkers to guide disease management has led to only marginal improvements in progression-free survival (PFS) while patients face an increasing level of toxicity. Fortunately, because of a better overall understanding of ovarian tumourigenesis and advancements in the disease's (epi)genetic and molecular profiling, a paradigm shift has emerged with the identification of new disease biomarkers and the proposal of targeted therapeutic approaches to postpone disease recurrence and decrease side effects, while increasing patients' survival. Despite this progress, several challenges in disease management, including disease heterogeneity and drug resistance, still need to be overcome.

Identification and Validation of a Novel Anoikis-Related Gene Signature for Predicting Survival in Patients With Serous Ovarian Cancer

Background

Ovarian cancer is an extremely deadly gynecological malignancy, with a 5-year survival rate below 30%. Among the different histological subtypes, serous ovarian cancer (SOC) is the most common. Anoikis significantly contributes to the progression of ovarian cancer. Therefore, identifying an anoikis-related signature that can serve as potential prognostic predictors for SOC is of great significance.

Methods

We intersected 308 anoikis-related genes (ARGs) and identified those significantly associated with SOC prognosis using univariate Cox regression. A LASSO Cox regression model was constructed and evaluated using Kaplan-Meier and receiver operating characteristic (ROC) analyses in TCGA (The Cancer Genome Atlas) and GSE26193 cohorts. We conducted quantitative real-time polymerase chain reaction (qPCR) to assess mRNA levels and applied bioinformatics to investigate the correlation between risk groups and gene expression, mutations, pathways, tumor immune microenvironment (TIME), and drug sensitivity in SOC.

Results

Among 308 ARGs, 28 were significantly associated with SOC prognosis. A 13-gene prognostic model was established through LASSO Cox regression in TCGA cohort. High-risk group had poorer prognosis than low-risk group (median overall survival (mOS): 34.2 vs. 57.1 months, hazard ratio (HR): 2.590, 95% confidence interval (CI): 0.159 - 6.00, P < 0.001). The area under the curve (AUC) values of 0.63, 0.65, and 0.74 reflected the predictive performance for 3-, 5-, and 8-year overall survival (OS) in GSE26193 validation cohort. Functional enrichment, pathway analysis, and TIME analysis identified distinct characteristics between risk groups. Drug sensitivity analysis revealed potential drug advantages for each group. Furthermore, qPCR validation once again confirmed the effectiveness of the risk model in SOC patients.

Conclusions

We developed and validated a robust ARG model, which could be used to predict OS in SOC patients. By systematically analyzing the correlation between the risk score of the ARGs signature model and various patterns, including the TIME and drug sensitivity, our findings suggest that this prognostic model contributes to the advancement of personalized and precise therapeutic strategies. Nevertheless, further validation studies and investigations into the underlying mechanisms are warranted.

An Aptamer-Based Nanoflow Cytometry Method for the Molecular Detection and Classification of Ovarian Cancers through Profiling of Tumor Markers on Small Extracellular Vesicles

Molecular profiling of protein markers on small extracellular vesicles (sEVs) is a promising strategy for the precise detection and classification of ovarian cancers. However, this strategy is challenging owing to the lack of simple and practical detection methods. In this work, using an aptamer-based nanoflow cytometry (nFCM) detection strategy, a simple and rapid method for the molecular profiling of multiple protein markers on sEVs was developed. The protein markers can be easily labeled with aptamer probes and then rapidly profiled by nFCM. Seven cancer-associated protein markers, including CA125, STIP1, CD24, EpCAM, EGFR, MUC1, and HER2, on plasma sEVs were profiled for the molecular detection and classification of ovarian cancers. Profiling these seven protein markers enabled the precise detection of ovarian cancer with a high accuracy of 94.2 %. In addition, combined with machine learning algorithms, such as linear discriminant analysis (LDA) and random forest (RF), the molecular classifications of ovarian cancer cell lines and subtypes were achieved with overall accuracies of 82.9 % and 55.4 %, respectively. Therefore, this simple, rapid, and non-invasive method exhibited considerable potential for the auxiliary diagnosis and molecular classification of ovarian cancers in clinical practice.

Anisomycin inhibits the activity of human ovarian cancer stem cells via regulating antisense RNA NCBP2-AS2/MEK/ERK/STAT3 signaling

BACKGROUND

Ovarian cancer stem cells (OCSCs) are the main cause of relapse and drug resistance in patients with ovarian cancer. Anisomycin has been shown to be an effective antitumor agent, but its mechanism of action in ovarian cancer remains elusive.

METHODS

CD44+/CD133+ human OCSCs were isolated from human ovarian cancer tissues. OCSCs were interfered with using anisomycin and specific small-interfering RNA (siRNA). Microarray assay, MTT, in vivo tumorigenic experiments, transwell assay, cell cycle assay, colony formation assay, angiogenesis assay, and hematoxylin and eosin staining were used to detect the mechanism of anisomycin with respect to inhibiting the activity of OCSCs. Expression of the NCBP2-AS2/mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase (ERK)/signal transducer and activator of transcription 3 (STAT3) pathway was examined using western blotting, a quantitative real-time PCR (RT-qPCR) and immunofluorescence staining. Bioinformatics analysis was used for predictive analysis of NCBP2-AS2 expression in urogenital tumors.

RESULTS

Microarray analysis showed that treatment with anisomycin significantly decreased the expression of antisense RNA NCBP2-AS2 in OCSCs. In vitro cellular experiments showed that interfering with endogenous antisense RNA NCBP2-AS2 using siRNA distinctly inhibited the proliferation, migration and angiogenesis of OCSCs, whereas in vivo animal experiments revealed decreased tumorigenesis in nude mice. Moreover, the results of RT-qPCR and western blotting demonstrated that both anisomycin treatment and NCBP2-AS2 silencing led to significant reductions in the mRNA and protein expression levels of NCBP2-AS2, MEK, ERK and STAT3. From a bioinformatic point of view, antisense RNA NCBP2-AS2 exhibited significantly differential expression between urogenital tumors and normal controls, and a similar expression pattern was found in the genes NCBP2, RPL35A, DNAJC19 and ECE2, which have similarity to NCBP2-AS2.

CONCLUSIONS

Anisomycin suppresses the in vivo and in vitro activity of human OCSCs by downregulating the antisense RNA NCBP2-AS2/MEK/ERK/STAT3 signaling pathway, whereas the antisense RNA NCBP2-AS2 and genes with similarity have the potential to serve as markers for clinical diagnosis and prognosis of urogenital tumors.

Machine learning-derived identification of prognostic signature for improving prognosis and drug response in patients with ovarian cancer

Clinical assessments relying on pathology classification demonstrate limited effectiveness in predicting clinical outcomes and providing optimal treatment for patients with ovarian cancer (OV). Consequently, there is an urgent requirement for an ideal biomarker to facilitate precision medicine. To address this issue, we selected 15 multicentre cohorts, comprising 12 OV cohorts and 3 immunotherapy cohorts. Initially, we identified a set of robust prognostic risk genes using data from the 12 OV cohorts. Subsequently, we employed a consensus cluster analysis to identify distinct clusters based on the expression profiles of the risk genes. Finally, a machine learning-derived prognostic signature (MLDPS) was developed based on differentially expressed genes and univariate Cox regression genes between the clusters by using 10 machine-learning algorithms (101 combinations). Patients with high MLDPS had unfavourable survival rates and have good prediction performance in all cohorts and in-house cohorts. The MLDPS exhibited robust and dramatically superior capability than 21 published signatures. Of note, low MLDIS have a positive prognostic impact on patients treated with anti-PD-1 immunotherapy by driving changes in the level of infiltration of immune cells. Additionally, patients suffering from OV with low MLDIS were more sensitive to immunotherapy. Meanwhile, patients with low MLDIS might benefit from chemotherapy, and 19 compounds that may be potential agents for patients with low MLDIS were identified. MLDIS presents an appealing instrument for the identification of patients at high/low risk. This could enhance the precision treatment, ultimately guiding the clinical management of OV.

Ovarian cancer classification and prognosis assessment model based on prognostic target genes in key microRNA-target gene networks

BACKGROUND

The present study was designed to screen key microRNA (miRNA)-target gene networks for ovarian cancer (OC) and to classify and construct a risk assessment system for OC based on the target genes.

METHODS

OC sample data of The Cancer Genome Atlas dataset and GSE26193, GSE30161, GSE63885 and GSE9891 datasets were retrospectively collected. Pearson correlation analysis and targeted analysis of miRNA and target gene were performed to screen key miRNA-target gene networks. Target genes associated with the prognosis of OC were screened from key miRNA-target gene networks for consensus clustering and least absolute shrinkage and selection operator-based regression machine learning analysis of OC samples.

RESULTS

Twenty target genes of 2651 key miRNA-target gene pairs had significant prognostic correlation in each OC cohort, and OC was divided into three clusters. There were differences in prognostic outcome, biological pathways, immune cell abundance and susceptibility to immune checkpoint blockade (ICB) therapy and anti-tumor drugs among the three molecular clusters. S2 exhibited the least advantage in prognosis and immunotherapy response rate in the three molecular clusters, and the pathways regulating immunity, hypoxia, metabolism and promoting malignant progression of cancer, as well as infiltrating immune and stromal cell population abundance, were the highest in this cluster. An eight-target gene prognostic model was created, and the risk index obtained by using this model not only significantly distinguished the immune characteristics of the sample, but also predicted the response of the sample to ICB treatment, and helped to screen 36 potential anti-OC drugs.

CONCLUSIONS

The present study provides a classification strategy for OC based on prognostic target genes in key miRNA-target gene networks, and creates a risk assessment system for predicting prognosis and response to ICB therapy in OC patients, providing molecular basis for prognosis and precise treatment of OC.

OvaPrint-A Cell-free DNA Methylation Liquid Biopsy for the Risk Assessment of High-grade Serous Ovarian Cancer

PURPOSE

High-grade serous ovarian carcinoma (HGSOC) is the most lethal epithelial ovarian cancer (EOC) and is often diagnosed at late stage. In women with a known pelvic mass, surgery followed by pathologic assessment is the most reliable way to diagnose EOC and there are still no effective screening tools in asymptomatic women. In the current study, we developed a cell-free DNA (cfDNA) methylation liquid biopsy for the risk assessment of early-stage HGSOC.

EXPERIMENTAL DESIGN

We performed reduced representation bisulfite sequencing to identify differentially methylated regions (DMR) between HGSOC and normal ovarian and fallopian tube tissue. Next, we performed hybridization probe capture for 1,677 DMRs and constructed a classifier (OvaPrint) on an independent set of cfDNA samples to discriminate HGSOC from benign masses. We also analyzed a series of non-HGSOC EOC, including low-grade and borderline samples to assess the generalizability of OvaPrint. A total of 372 samples (tissue n = 59, plasma n = 313) were analyzed in this study.

RESULTS

OvaPrint achieved a positive predictive value of 95% and a negative predictive value of 88% for discriminating HGSOC from benign masses, surpassing other commercial tests. OvaPrint was less sensitive for non-HGSOC EOC, albeit it may have potential utility for identifying low-grade and borderline tumors with higher malignant potential.

CONCLUSIONS

OvaPrint is a highly sensitive and specific test that can be used for the risk assessment of HGSOC in symptomatic women. Prospective studies are warranted to validate OvaPrint for HGSOC and further develop it for non-HGSOC EOC histotypes in both symptomatic and asymptomatic women with adnexal masses.

The role of kaempferol in gynaecological malignancies: progress and perspectives

Kaempferol, a flavonoid derived from various herbs such as cocoyam, propolis, and grapefruit, has garnered interest due to its numerous pharmacological benefits, including anti-inflammatory, antioxidant, and anti-diabetic properties. Kaempferol has been shown to possess notable anti-tumour bioactivity, indicating potential for treating gynaecological malignancies. To date, numerous studies have demonstrated the potential of kaempferol to induce tumour cell apoptosis, inhibit proliferation, and prevent metastasis and invasion in several gynaecological malignancies, including breast, ovarian and endometrial cancers. However, there is currently insufficient research investigating the efficacy of kaempferol for the treatment of gynaecological malignancies, and a lack of systematic review of its mechanism of action. Therefore, this review is founded on a literature analysis of the anticancer effects of kaempferol on gynaecological malignancies. The goal is to provide valuable reference material for scientific researchers and medical practitioners.

Clinical role of serum tumor markers SCC, NSE, CA 125, CA 19-9, and CYFRA 21-1 in patients with lung cancer

OBJECTIVE

The aim of the study was to assess the diagnostic value of tumor markers in discriminating between lung cancer and benign chest diseases (BCDs).

METHODS

There were 322 patients enrolled in this investigation including 180 cases of lung cancer and 142 cases of BCD. Serum neuron-specific enolase (NSE), cancer antigen 125, cancer antigen 19-9, squamous cell carcinoma-related antigen, and cytokeratin fragment 19 (CYFRA 21-1) were compared between different populations, cancer stages, and before and after treatment. Logistic regression and receiver operating characteristic curves were used to evaluate the diagnostic markers.

RESULTS

Both NSE and CYFRA 21-1 were significantly associated with lung cancer. The CYFRA 21-1 showed the best performance, as well as its combinations, for lung cancer diagnosis. It also showed significant change 6 months after radical surgery in lung cancer patients.

CONCLUSION

The marker CYFRA 21-1 could be developed as an adjuvant marker for the early diagnosis of lung cancer and as a prognostic marker for lung cancer treatment.

Immunogenic Biomarkers HMGB1 and sRAGE Are Potential Diagnostic Tools for Ovarian Malignancies

BACKGROUND

High mobility group box 1 (HMGB1), soluble receptor of advanced glycation end products (sRAGE) and programmed cell death markers PD-1 and PD-L1 are immunogenic serum biomarkers that may serve as novel diagnostic tools for cancer diagnosis.

METHODS

We investigated the four markers in sera of 231 women, among them 76 with ovarian cancer, 87 with benign diseases and 68 healthy controls, using enzyme immunoassays. Discrimination between groups was calculated using receiver operating characteristic (ROC) curves and sensitivities at fixed 90% and 95% specificities.

RESULTS

HMGB1 levels were significantly elevated and sRAGE levels were decreased in cancer patients as compared to benign and healthy controls. In consequence, the ratio of HMGB1 and sRAGE discriminated best between diagnostic groups. The areas under the curve (AUCs) of the ROC curves for differentiation of cancer vs. healthy were 0.77 for HMGB1, 0.65 for sRAGE and 0.78 for the HMGB1/sRAGE ratio, and slightly lower for the differentiation of cancer vs. benigns with 0.72 for HMGB1, 0.61 for sRAGE and 0.74 for the ratio of both. The highest sensitivities for cancer detection at 90% specificity versus benign diseases were achieved using HMGB1 with 41.3% and the HMGB1/sRAGE ratio with 39.2%, followed by sRAGE with 18.9%. PD-1 showed only minor and PD-L1 no power for discrimination between ovarian cancer and benign diseases.

CONCLUSION

HMGB1 and sRAGE have differential diagnostic potential for ovarian cancer detection and warrant inclusion in further validation studies.

Serum levels of tumor markers and their clinical significance in epithelial ovarian cancer

OBJECTIVES

Tumor markers have been widely used clinically. Detection of serum CA125 is one of the commonly used clinical methods for early screening and early diagnosis of epithelial ovarian cancer, but it is difficult to diagnose epithelial ovarian cancer with a single specific tumor marker. In this study, the combinatorial tumor marker detection method was used to compare the value of each tumor marker alone and different combinations in the diagnosis of epithelial ovarian cancer.

METHODS

The clinical data of patients with epithelial ovarian cancer (n=65) and ovarian benign disease (n=29) were collected. Multiple tumor marker protein chip was used to detect cancer antigen 125 (CA125), carbohydrate antigen 242 (CA242), alpha-fetoprotein (AFP), beta-human chorionic gonadotropin (β-HCG), carcinoembryonic antigen (CEA), cancer antigen 199 (CA199), neuron-specific enolase (NSE), Ferritin, cancer antigen 153 (CA153), and human growth hormone (HGH) serum levels, and to compare the differences between the benign and malignant ovarian tumors. The correlation between tumor markers and clinicopathologic features for ovarian epithelial carcinoma was analyzed by χ2 test. Spearman rank analysis showed the correlation between CA125 expression level and other tumor markers in epithelial ovarian cancer and the correlation between age and the above 10 tumor markers. Sensitivity, specificity, positive predictive value, negative predictive value, Youden index, and diagnostic efficiency were used to evaluate the diagnostic value of single tumor marker and the combination of tumor markers.

RESULTS

The levels of β-HCG, NSE, CA153, and CA125 in the epithelial ovarian cancer group were higher than those in the ovarian benign disease group. The level of NSE in the serum of patients with epithelial ovarian cancer was related to the clinical stage of patients. In addition, the levels of CA242, β-HCG, CEA, NSE, Ferritin, CA153 in the serum of patients with epithelial ovarian cancer were positively correlated with CA125 (rs=0.497, P<0.001; rs=0.612, P<0.001; rs=0.358, P=0.003; rs=0.680, P<0.001; rs=0.322, P=0.009; rs=0.609, P<0.001, respectively), and the levels of β-HCG, Ferritin, CA153 were positively correlated with the patient's age (rs=0.256, P=0.040; rs=0.325, P=0.008; rs=0.249, P=0.046, respectively). In the diagnosis of epithelial ovarian cancer, the sensitivity, Youden index, and diagnostic efficiency of CA125 detection alone were higher than the results of the other 9 separate detections. When CA153, CA199, CA242, Ferritin, and CEA were combined with CA125, the sensitivity of the combined detection of different combinations was higher than that of CA125 alone. The combined detection sensitivities of CA125+CEA and CA125+Ferritin+CEA were 89.2% and 90.8%, respectively, and the diagnostic efficiencies were both 84.1%, which were higher than those of other combinations. The Youden index of CA125+CEA joint detection was 0.616, which was higher than those of other combinations.

CONCLUSIONS

CA125 has a high diagnostic value in the diagnosis of epithelial ovarian cancer. The detection of combined tumor markers in serum has higher sensitivity and specificity in epithelial ovarian cancer.

Trends in Systemic Inflammatory Reaction (SIR) during Paclitaxel and Carboplatin Chemotherapy in Women Suffering from Epithelial Ovarian Cancer

BACKGROUND

Epithelial ovarian cancer (EOC) is the most fatal gynaecological malignancy treated with cytoreductive surgery followed by adjuvant taxane-platinum-based chemotherapy. It has been shown that the pretreatment systemic inflammatory reaction (SIR) in women with OC can be evaluated using the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR) and systemic inflammatory index (SII), depending on the stage of disease, and has prognostic value for overall survival. The aim of this study was to evaluate the changes in NLR, LMR, PLR and SII during chemotherapy.

METHODS

A total of 107 women with EOC (23 with type I and 84 with type II tumours) were included in a retrospective single-centre analysis. The Kologomorov-Smirnoff, Kruskal-Wallis or Friedman analysis of variance tests were used for data analysis, and a p value of 0.05 was considered statistically significant.

RESULTS

A significant decrease in NLR, PLR and SII but not LMR was observed during adjuvant treatment. Pretreatment NLR, PLR and SII were dependent on disease stage and tumour grade; however, this association was lost during therapy. Additionally, strong and positive mutual correlations between NLR, LMR, PLR and SII were sustained during the whole course of chemotherapy.

CONCLUSIONS

During first-line adjuvant chemotherapy in women with EOC, a decrease in SIR is confirmed.

ZFP57 promotes ovarian cancer progression by transcriptionally regulating BRCA1 and managing G1 checkpoint

Ovarian cancer (OC) which is one of the frequently-occurring gynecologic malignant tumors, endangers the health of women. The zinc finger protein 57 (ZFP57) plays crucial functions during the progression of cancer and is reported as a prognostic and therapeutic candidate in a variety of cancer. However, the biological function as well as the underlying mechanism of ZFP57 during OC progression remains unknown. Here, ZFP57 expression was found prominently increased in OC tissues and correlated with the prognosis of OC patients. Knock down of ZFP57 in OC cells inhibited the cell proliferation and migration, and also arrested the cells at G1 phase as well as accelerated the apoptosis. Additionally, ZFP57 transcriptionally regulated BRCA1 expression in OC, indicating that ZFP57 may affect BRCA1 mediated G1 checkpoint to regulate the cell cycle of OC cells and further influence the progression of OC. Taken together, our present study discovered a novel function of ZFP57 in OC, suggesting that ZFP57 could be potentially treated as a prognostic biomarker and therapeutic target for OC patients.

Glucose-6-phosphate dehydrogenase: a therapeutic target for ovarian cancer

INTRODUCTION

Ovarian cancer (OC) is a gynecological tumor disease, which is usually diagnosed at an advanced stage and has a poor prognosis. It has been established that the glucose metabolism rate of cancer cells is significantly higher than that of normal cells, and the pentose phosphate pathway (PPP) is an important branch pathway for glucose metabolism. Glucose-6-phosphate dehydrogenase (G6PD) is the key rate-limiting enzyme in the PPP, which plays an important role in the initiation and development of cancer (such as OC), and has been considered as a promisinganti-cancer target.

AREAS COVERED

In this review, based on the structure and biological function of G6PD, recent research on the roles of G6PD in the progression, metastasis, and chemoresistance of OC are summarized and accompanied by proposed molecular mechanisms, which may provide a systematic understanding of targeting G6PD for the treatment of patients with OC.

EXPERT OPINION

Accumulating evidence demonstrates that G6PD is a promising target of cancer. The development of G6PD inhibitors for cancer treatment merits broad application prospects.

Novel proteomic technologies to address gaps in pre-clinical ovarian cancer biomarker discovery efforts

INTRODUCTION

An estimated 20,000 women in the United States will receive a diagnosis of ovarian cancer in 2023. Late-stage diagnosis is associated with poor prognosis. There is a need for novel diagnostic biomarkers for ovarian cancer to improve early-stage detection and novel prognostic biomarkers to improve patient treatment.

AREAS COVERED

This review provides an overview of the clinicopathological features of ovarian cancer and the currently available biomarkers and treatment options. Two affinity-based platforms using proximity extension assays (Olink) and DNA aptamers (SomaLogic) are described in the context of highly reproducible and sensitive multiplexed assays for biomarker discovery. Recent developments in ion mobility spectrometry are presented as novel techniques to apply to the biomarker discovery pipeline. Examples are provided of how these aforementioned methods are being applied to biomarker discovery efforts in various diseases, including ovarian cancer.

EXPERT OPINION

Translating novel ovarian cancer biomarkers from candidates in the discovery phase to bona fide biomarkers with regulatory approval will have significant benefits for patients. Multiplexed affinity-based assay platforms and novel mass spectrometry methods are capable of quantifying low abundance proteins to aid biomarker discovery efforts by enabling the robust analytical interrogation of the ovarian cancer proteome.

Molecular Mechanisms of Tumor Cell Stemness Modulation during Formation of Spheroids

Cancer stem cells (CSCs), their properties and interaction with microenvironment are of interest in modern medicine and biology. There are many studies on the emergence of CSCs and their involvement in tumor pathogenesis. The most important property inherent to CSCs is their stemness. Stemness combines ability of the cell to maintain its pluripotency, give rise to differentiated cells, and interact with environment to maintain a balance between dormancy, proliferation, and regeneration. While adult stem cells exhibit these properties by participating in tissue homeostasis, CSCs behave as their malignant equivalents. High tumor resistance to therapy, ability to differentiate, activate angiogenesis and metastasis arise precisely due to the stemness of CSCs. These cells can be used as a target for therapy of different types of cancer. Laboratory models are needed to study cancer biology and find new therapeutic strategies. A promising direction is three-dimensional tumor models or spheroids. Such models exhibit properties resembling stemness in a natural tumor. By modifying spheroids, it becomes possible to investigate the effect of therapy on CSCs, thus contributing to the development of anti-tumor drug test systems. The review examines the niche of CSCs, the possibility of their study using three-dimensional spheroids, and existing markers for assessing stemness of CSCs.

"DEPHENCE" system-a novel regimen of therapy that is urgently needed in the high-grade serous ovarian cancer-a focus on anti-cancer stem cell and anti-tumor microenvironment targeted therapies

Ovarian cancer, especially high-grade serous type, is the most lethal gynecological malignancy. The lack of screening programs and the scarcity of symptomatology result in the late diagnosis in about 75% of affected women. Despite very demanding and aggressive surgical treatment, multiple-line chemotherapy regimens and both approved and clinically tested targeted therapies, the overall survival of patients is still unsatisfactory and disappointing. Research studies have recently brought some more understanding of the molecular diversity of the ovarian cancer, its unique intraperitoneal biology, the role of cancer stem cells, and the complexity of tumor microenvironment. There is a growing body of evidence that individualization of the treatment adjusted to the molecular and biochemical signature of the tumor as well as to the medical status of the patient should replace or supplement the foregoing therapy. In this review, we have proposed the principles of the novel regimen of the therapy that we called the "DEPHENCE" system, and we have extensively discussed the results of the studies focused on the ovarian cancer stem cells, other components of cancer metastatic niche, and, finally, clinical trials targeting these two environments. Through this, we have tried to present the evolving landscape of treatment options and put flesh on the experimental approach to attack the high-grade serous ovarian cancer multidirectionally, corresponding to the "DEPHENCE" system postulates.

MicroRNAs as Potential Biomarkers in Gynecological Cancers

MicroRNAs are non-coding transcripts that, thanks to the ability to regulate the mRNA of target genes, can affect the expression of genes encoding tumor suppressors and oncogenes. They can control many important cellular processes, including apoptosis, differentiation, growth, division, and metabolism. Therefore, miRNAs play an important role in the development of many cancers, including gynecological cancers. Ovarian cancer, endometrial cancer, cervical cancer, and vulvar cancer are the most common cancers in women and are a frequent cause of death. The heterogeneity of the pathogenesis of these gynecological diseases makes the diagnostic process a significant obstacle for modern medicine. To date, many studies have been carried out, in which particular attention has been paid to the molecular pathomechanism of these diseases, with particular emphasis on miRNAs. To date, the changed profile of many miRNAs, which influenced the promotion of proliferation, migration, invasion processes and the simultaneous inhibition of programmed cell death, has been proven many times. Detailed understanding of the molecular effects of miRNAs in the above-mentioned gynecological cancers will enable the development of potential predictive and prognostic biomarkers, as well as the optimization of the diagnostic process.

Aptamers Versus Vascular Endothelial Growth Factor (VEGF): A New Battle against Ovarian Cancer

Cancer is one of the diseases that causes a high mortality as it involves unregulated and abnormal cell growth proliferation that can manifest in any body region. One of the typical ovarian cancer symptoms is damage to the female reproductive system. The death rate can be reduced through early detection of the ovarian cancer. Promising probes that can detect ovarian cancer are suitable aptamers. Aptamers, i.e., so-called chemical antibodies, have a strong affinity for the target biomarker and can typically be identified starting from a random library of oligonucleotides. Compared with other probes, ovarian cancer targeting using aptamers has demonstrated superior detection effectiveness. Various aptamers have been selected to detect the ovarian tumor biomarker, vascular endothelial growth factor (VEGF). The present review highlights the development of particular aptamers that target VEGF and detect ovarian cancer at its earliest stages. The therapeutic efficacy of aptamers in ovarian cancer treatment is also discussed.

Adnexal Lesion Imaging: Past, Present, and Future

Currently, imaging is part of the standard of care for patients with adnexal lesions prior to definitive management. Imaging can identify a physiologic finding or classic benign lesion that can be followed up conservatively. When one of these entities is not present, imaging is used to determine the probability of ovarian cancer prior to surgical consultation. Since the inclusion of imaging in the evaluation of adnexal lesions in the 1970s, the rate of surgery for benign lesions has decreased. More recently, data-driven Ovarian-Adnexal Reporting and Data System (O-RADS) scoring systems for US and MRI with standardized lexicons have been developed to allow for assignment of a cancer risk score, with the goal of further decreasing unnecessary interventions while expediting the care of patients with ovarian cancer. US is used as the initial modality for the assessment of adnexal lesions, while MRI is used when there is a clinical need for increased specificity and positive predictive value for the diagnosis of cancer. This article will review how the treatment of adnexal lesions has changed due to imaging over the decades; the current data supporting the use of US, CT, and MRI to determine the likelihood of cancer; and future directions of adnexal imaging for the early detection of ovarian cancer.

Evaluation of the Potential Diagnostic Utility of the Determination of Selected Immunological and Molecular Parameters in Patients with Ovarian Cancer

Ovarian cancer is one of the most serious challenges in modern gynaecological oncology. Due to its non-specific symptoms and the lack of an effective screening procedure to detect the disease at an early stage, ovarian cancer is still marked by a high mortality rate among women. For this reason, a great deal of research is being carried out to find new markers that can be used in the detection of ovarian cancer to improve early diagnosis and survival rates of women with ovarian cancer. Our study focuses on presenting the currently used diagnostic markers and the latest selected immunological and molecular parameters being currently investigated for their potential use in the development of new diagnostic and therapeutic strategies.

The Role of Selected Adipocytokines in Ovarian Cancer and Endometrial Cancer

Due to their multidirectional influence, adipocytokines are currently the subject of numerous intensive studies. Significant impact applies to many processes, both physiological and pathological. Moreover, the role of adipocytokines in carcinogenesis seems particularly interesting and not fully understood. For this reason, ongoing research focuses on the role of these compounds in the network of interactions in the tumor microenvironment. Particular attention should be drawn to cancers that remain challenging for modern gynecological oncology-ovarian and endometrial cancer. This paper presents the role of selected adipocytokines, including leptin, adiponectin, visfatin, resistin, apelin, chemerin, omentin and vaspin in cancer, with a particular focus on ovarian and endometrial cancer, and their potential clinical relevance.

LMNB1 deletion in ovarian cancer inhibits the proliferation and metastasis of tumor cells through PI3K/Akt pathway

Ovarian cancer (OC) is a common malignant tumor in gynecology. LMNB1 is an important component of the nuclear skeleton. The expression of LMNB1 in ovarian cancer is significantly higher than that in normal tissues, but its role in tumor still needs comprehensive investigation. In this study, we overexpressed and knocked down LMNB1 in ovarian cancer cells and explore the effect of LMNB1 on the cell proliferation, migration and the underlying mechanism. We analyzed the expression levels of LMNB1 in ovarian cancer and their clinical relevance by using bioinformatics methods, qRT-PCR, Western blot and immunohistochemistry. To state the effect and mechanism of LMNB1 on OC in vitro and in vivo, we performed mouse xenograft studies, CCK8, cloning formation, Edu incorporation, wound healing, transwell and flow cytometry assay in stable LMNB1 knockdown OC cells, following by RNA-seq. Overexpression of LMNB1 indicates the progression of OC. LMNB1 knockdown inhibited the proliferation and migration of OC cells by suppressing the FGF1-mediated PI3K-Akt signaling pathway. Our study shows LMNB1 as a novel prognostic factor and therapeutic target in OC.

Biomarkers for Early Detection of Cancer: Molecular Aspects

According to the World Health Organization, cancer is a leading cause of death worldwide, representing almost 10 million deaths in 2020 [...]

ROMA Index Is an Effective Predictor for Advanced Endometrial Cancer before Surgery

There is a high rate of inconformity between clinical staging and surgical-pathologic staging in endometrial cancer. Many patients with advanced endometrial cancer are preoperatively understaged and thereby do not receive the optimal therapy. Here, we aimed to develop a predictive model or biomarker for preoperative diagnosis of advanced endometrial cancer via multivariate logistic regression analysis. In this study, 259 eligible patients were included, and 195 patients were assigned to the training dataset and 64 patients to validation dataset. Age, menopause status, sterilization situation, parity, body mass index, hypertension, diabetes mellitus, tumor size, and ovarian malignancy algorithm (ROMA) index were included as predictive variables, and the binary outcome was advanced endometrial cancer or not. When the P value was set as less than 0.01 in forward stepwise regression, only ROMA index was retained. The odds ratio of being positive ROMA index was 15.531 times that of negative value. The area under receiver operating characteristic curve was 0.790 in the training dataset and 0.776 in the validation dataset. The decision curve analysis curve showed that the prediction by ROMA index added more net benefits for almost all threshold probabilities. Therefore, ROMA index is an effective predictor for advanced endometrial cancer before surgery. Since ROMA index is a standard, measurable, and reliable laboratory test, it can be used as a reference tool for gynecologists to design the appropriate therapeutic schedule for patients with high-stage endometrial cancer before surgery.