Types Of Epithelial Ovarian Cancer Research Articles

Primary ovarian cancer combined with primary fallopian tube cancer: A case report

BACKGROUND Low grade serous carcinoma of the ovary (LGSOC) is a rare type of epithelial ovarian cancer with a low incidence rate. The origin of ovarian cancer has always been a hot topic in gynecological oncology research, and some scholars believe that the origin of ovarian malignant tumors is the fallopian tubes. Primary fallopian tube cancer is the lowest incidence of malignant tumors in the female reproductive system. There are only a few reports in the literature, but the mortality rate is very high. But in clinical practice, fallopian tube cancer is very common, but in most cases, it is classified as ovarian cancer. CASE SUMMARY We report a 54 years old postmenopausal woman who was hospitalized with a lower abdominal mass and underwent surgical treatment. The final pathological confirmation was low-grade serous carcinoma of the right ovary and low-grade serous carcinoma of the left fallopian tube. No special treatment was performed after the surgery, and the patient was instructed to undergo regular follow-up without any signs of disease progression. CONCLUSION The prognosis of LGSOC is relatively good, over 80% of patients still experience disease recurrence.

Childhood body fatness and the risk of epithelial ovarian cancer: A population-based case-control study in Montreal, Canada

ObjectiveTo assess the association between childhood body fatness and epithelial ovarian cancer (EOC), and whether this association differs by type of EOC. MethodsUsing data from a population-based case-control study (497 cases and 902 controls) in Montreal, Canada conducted 2011–2016, we examined the association between childhood body fatness and EOC, overall and separately for invasive vs. borderline EOCs. A figure rating scale was used to measure body fatness at ages 5 and 10. Multivariable logistic regression was used to estimate adjusted odds ratios (aORs) and 95% confidence intervals (95% CI). Quantitative bias analyses were conducted to assess the impact of exposure misclassification and non-participation. ResultsThe aOR (95% CI) of overall EOC for high vs. low body fatness was 1.07 (0.85–1.34) at age 5 and 1.28 (0.98–1.68) at age 10. The associations were stronger for invasive EOC, specifically the endometrioid histological type. For borderline cancers, the aORs were below the null value with wide confidence intervals. Bias analyses did not reveal a strong influence of non-participation. Non-differential exposure misclassification may have biased aORs towards the null for invasive cancers but did not appear to have an appreciable influence on the aORs for borderline cancers. ConclusionsChildhood body fatness may be a risk factor for invasive EOC in later adult life. Our study highlights the potential importance of examining early life factors for a comprehensive understanding of EOC development.

New Achievements from Molecular Biology and Treatment Options for Refractory/Relapsed Ovarian Cancer-A Systematic Review.

Ovarian cancer (OC) has a high rate of mortality and is the fifth most common cause of death in females all over the world. The etiology is still unclear. Numerous factors such as smoking, obesity, and unhealthy diet may affect the risk of OC. Having a family history of breast and OC is one of the main risks for developing OC. Mutations of BRCA1/2 are associated with OC risk as well. The histopathological classification of OC reveals the four most common types: serous, clear cell, endometrioid, and mucinous; these are epithelial OC types, and other types are rare. Furthermore, OC can be subdivided into types I and II. Type I tumors are most probably caused by atypical proliferative tumors. Type II tumors include high-grade carcinoma of the serous type, carcinosarcoma, and carcinoma, which are not differentiated and generally originate from tubal intraepithelial carcinoma of the serous type. Typically, type I tumors are present in early stages, usually with good prognosis. Type II tumors are classified as high-grade tumors and are most often diagnosed at advanced FIGO stages with poor prognosis. High-grade serous OC accounts for 90% of serous OC. Tumor heterogeneity aggravates OC treatment. The standard care for primary epithelial ovarian cancer (EOC) is cytoreductive surgery followed by platinum-based chemotherapy. Neoadjuvant chemotherapy can be used in certain cases followed by cytoreductive surgery. The main prognostic factor is complete tumor resection. However, about 70% of patients relapse. Resistance to chemotherapeutic agents remains a major challenge in EOC treatment, in which many different factors are involved. In recent years, the examination of molecular parameters and their prognostic impact has become increasingly relevant in EOC, and furthermore, the use of immunotherapy has expanded the therapeutic range. As the clinical need is greatest for relapsed patients, this systematic review will focus on recent advances in molecular biology with prognostic and predictive markers and treatment options for recurrent/refractory OC. Inclusion criteria for the review: potential prospective or predictive biomarkers in preclinical or clinical use in relapsed and refractory OC, prognostic impact, clinical and preclinical trials, and immunotherapy. Exclusion criteria for the review: primary OC, no full text or abstract available, not the topic mentioned above, and text not available in English. Risk of bias: the included studies were evaluated descriptively for the topics mentioned above, and data were not compared with each other. The objective is to highlight the molecular mechanisms of the most promising targeted agents under clinical investigation to demonstrate their potential relevance in recurrent/refractory OC.

Histopathological Types of Ovarian Cancer in Different Age Group of Patients; A Single Institution Experience

Objective: To see the relationship between age and histological types among patients presenting with ovarian cancer at tertiary care hospital, of Karachi Pakistan. Study Design: Cross-sectional study. Place and Duration of study: Department of medical oncology, Jinnah Postgraduate Medical Centre, Karachi Pakistan from Mar 2019 to May 2020. Methodology: Three fifty women presenting with confirmed diagnosis of ovarian carcinoma were included irrespective of their age. The information regarding socio-demographics and family history were noted on pre-designed proforma. Pathology reports were obtained from all the patients and information regarding age, stage and histological type were noted. World Health Organization classification was used to classify the histological type of tumours. All data was entered and analyzed using SPSS version 23. Results: The mean age of the study sample was estimated as 44.27±12.7 years ranging from 14-92 years. According to histological type, most of the females had surface epithelial tumors 307(87.71%), followed by sex cord-stromal tumors 20(5.7%) and germ cell tumors tumors 19(5.43%) respectively. The statistically significant difference was observed between age and histological types and subtypes of ovarian cancer (p<0.05). Conclusion: It is concluded that age is an important factor in determining risk of developing different types of ovarian cancers. Serous type of epithelial ovarian cancer is the most common type and commonly present in 4th to 5th decade of life. Germ cell ovarian tumor is second most common type and present in 2nd decade of life.

VGLL3 expression is associated with macrophage infiltration and predicts poor prognosis in epithelial ovarian cancer.

High-grade serous ovarian carcinoma (HGSOC) is the most common histologic type of epithelial ovarian cancer (EOC). Due to its poor survival outcomes, it is essential to identify novel biomarkers and therapeutic targets. The hippo pathway is crucial in various cancers, including gynaecological cancers. Herein, we examined the expression of the key genes of the hippo pathway and their relationship with clinicopathological significance, immune cells infiltration and the prognosis of HGSOC. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data were curated to analyse the mRNA expression as well as the clinicopathological association and correlation with immune cell infiltration in HGSOC. The protein levels of significant genes in the HGSOC tissue were analysed using Tissue Microarray (TMA)-based immunohistochemistry. Finally, DEGs pathway analysis was performed to find the signalling pathways associated with VGLL3. VGLL3 mRNA expression was significantly correlated with both advanced tumor stage and poor overall survival (OS) (p=0.046 and p=0.003, respectively). The result of IHC analysis also supported the association of VGLL3 protein with poor OS. Further, VGLL3 expression was significantly associated with tumor infiltrating macrophages. VGLL3 expression and macrophages infiltration were both found to be independent prognostic factors (p=0.003 and p=0.024, respectively) for HGSOC. VGLL3 was associated with four known and three novel cancer-related signalling pathways, thus implying that VGLL3 is involved in the deregulation of many genes and pathways. Our study revealed that VGLL3 may play a distinct role in clinical outcomes and immune cell infiltration in patients with HGSOC and that it could potentially be a prognostic marker of EOC.

Insulin-like growth factor (IGF) and hepatocyte growth factor (HGF) in follicular fluid cooperatively promote the oncogenesis of high-grade serous carcinoma from fallopian tube epithelial cells: Dissection of the molecular effects.

Incessant ovulation is believed to be a potential cause of epithelial ovarian cancer (EOC). Our previous investigations have shown that insulin-like growth factor(IGF2) and hepatocyte growth factor(HGF) in the ovulatory follicular fluid (FF) contributed to the malignant transformation initiated by p53 mutations. Here we examined the individual and synergistic impacts of IGF2 and HGF on enhancing the malignant properties of high-grade serous carcinoma (HGSC), the most aggressive type of EOC, and its precursor lesion, serous tubal intraepithelial carcinoma (STIC). In a mouse xenograft co-injection model, we observed that FF co-injection induced tumorigenesis of STIC-mimicking cells, FE25. Co-injection with IGF2 or HGF partially recapitulated the tumorigenic effects of FF, but co-injection with both resulted in a higher tumorigenic rate than FF. We analyzed the different transformation phenotypes influenced by these FF growth signals through receptor inhibition. The IGF signal was necessary for clonogenicity, while the HGF signal played a crucial role in the migration and invasion of STIC and HGSC cells. Both signals were necessary for the malignant phenotype of anchoring-independent growth but had little impact on cell proliferation. The downstream signals responsible for these HGF activities were identified as the tyrosine-protein kinase Met (cMET)/mitogen-activated protein kinase and cMET/AKT pathways. Together with the previous finding that the FF-IGF2 could mediate clonogenicity and stemness activities via the IGF-1R/AKT/mammalian target of rapamycin and IGF-1R/AKT/NANOG pathways, respectively, this study demonstrated the cooperation of the FF-sourced IGF and HGF growth signals in the malignant transformation and progression of HGSC through both common and distinct signaling pathways. These findings help develop targeted prevention of HGSC.

Overexpression of CLDN16 in ovarian cancer is modulated by PI3K and PKC pathways

Epithelial ovarian cancer (EOC) is the gynecological malignant tumor of poorest prognosis and higher mortality rate. Chemotherapy is the base of high-grade serous ovarian cancer (HGSOC) treatment; however, it favors the emergence of chemoresistance and metastasis. Thus, there is an urge to search for new therapeutic targets, such as proteins related to cellular proliferation and invasion. Herein, we investigated the expression profile of claudin-16 (CLDN16 protein and CLDN16 transcript) and its possible functions in EOC. In silico analysis of CLDN16 expression profile was performed using data extracted from GENT2 and GEPIA2 platforms. A retrospective study was carried out with 55 patients to evaluate the expression of CLDN16. The samples were evaluated by immunohistochemistry, immunofluorescence, qRT-PCR, molecular docking, sequencing, and immunoblotting assays. Statistical analyzes were performed using Kaplan-Meier curves, one-way ANOVA, Turkey posttest. Data were analyzed using GraphPad Prism 8.0. In silico experiments showed that CLDN16 is overexpressed in EOC. 80.0% of all EOC types overexpressed CLDN16, of which in 87% of the cases the protein is restricted to cellular cytoplasm. CLDN16 expression was not related to tumor stage, tumor cells differentiation status, tumor responsiveness to cisplatin, or patients' survival rate. When compared to data obtained from in silico analysis regarding EOC stage and degree of differentiation, differences were found in the former but not in the later, neither in survival curves. CLDN16 expression in HGSOC OVCAR-3 cells increased by 1.95-fold (p < 0.001), 2.32-fold (p < 0.001), and 6.57-fold (p < 0.001) via PKC, PI3K, and estrogen pathways, respectively. Altogether, our results suggest that despite the low number of samples included in our in vitro studies, adding to the expression profile findings, we provided a comprehensive study of CLDN16 expression in EOC. Therefore, we hypothesize that CLDN16 is a potential target in the diagnosis and treatment of the disease.

Deep learning-based segmentation of epithelial ovarian cancer on T2-weighted magnetic resonance images.

Epithelial ovarian cancer (EOC) segmentation is an indispensable step in assessing the extent of disease and guiding the treatment plan that follows. Currently, manual segmentation is the most commonly used method, despite it being tedious, time-consuming and subject to inter- and intra-observer variability. This study aims to assess the feasibility of deep learning methods in the automatic segmentation of EOC on T2-weighted magnetic resonance images. A total of 339 EOC patients from eight different clinical centers were enrolled and divided into 4 groups: training set (n=154), validation set (n=25), internal test set (n=50) and external test set (n=110). Six common-used algorithms, including convolutional neural networks (CNNs) (U-Net, DeepLabv3, U-Net++ and PSPNet) and transformers (TransUnet and Swin-Unet), were used to conduct automatic segmentations. The performances of these automatic segmentation methods were evaluated by means of dice similarity coefficient (DSC), Hausdorff distance (HD), average symmetric surface distance (ASSD), precision and recall. All the results look promising, which demonstrates the feasibility of using deep learning for EOC segmentation. Overall, CNNs and transformers showed similar performances in both internal and external test sets. Among all the models, U-Net++ performed best with a DSC, HD, ASSD, precision and recall of 0.851, 25.3, 1.75, 0.838, 0.882 and 0.740, 42.5, 4.21, 0.825, 0.725 in internal and external test sets, respectively. Fully automated segmentation of EOC is possible with deep learning. The segmentation performance is related to the International Federation of Gynecology and Obstetrics (FIGO) stages and histological types of EOC.

Characterization of Primary Mucinous Ovarian Cancer by Diffusion-Weighted and Dynamic Contrast Enhancement MRI in Comparison with Serous Ovarian Cancer

(1) Background. The purpose of this study is to evaluate the diagnostic accuracy of a quantitative analysis of diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE) MRI of mucinous ovarian cancer (MOC). It also aims to differentiate between low grade serous carcinoma (LGSC), high-grade serous carcinoma (HGSC) and MOC in primary tumors. (2) Materials and Methods. Sixty-six patients with histologically confirmed primary epithelial ovarian cancer (EOC) were included in the study. Patients were divided into three groups: MOC, LGSC and HGSC. In the preoperative DWI and DCE MRI, selected parameters were measured: apparent diffusion coefficients (ADC), time to peak (TTP), and perfusion maximum enhancement (Perf. Max. En.). ROI comprised a small circle placed in the solid part of the primary tumor. The Shapiro-Wilk test was used to test whether the variable had a normal distribution. The Kruskal-Wallis ANOVA test was used to determine the p-value needed to compare the median values of interval variables. (3) Results. The highest median ADC values were found in MOC, followed by LGSC, and the lowest in HGSC. All differences were statistically significant (p < 0.000001). This was also confirmed by the ROC curve analysis for MOC and HGSC, showing that ADC had excellent diagnostic accuracy in differentiating between MOC and HGSC (p < 0.001). In the type I EOCs, i.e., MOC and LGSC, ADC has less differential value (p = 0.032), and TTP can be considered the most valuable parameter for diagnostic accuracy (p < 0.001). (4) Conclusions. DWI and DCE appear to be very good diagnostic tools in differentiating between serous carcinomas (LGSC, HGSC) and MOC. Significant differences in median ADC values between MOC and LGSC compared with those between MOC and HGSC indicate the usefulness of DWI in differentiating between less and more aggressive types of EOC, not only among the most common serous carcinomas. ROC curve analysis showed that ADC had excellent diagnostic accuracy in differentiating between MOC and HGSC. In contrast, TTP showed the greatest value for differentiating between LGSC and MOC.

Next-generation sequencing shows the genomic features of ovarian clear cell cancer and compares the genetic architectures of high-grade serous ovarian cancer and clear cell carcinoma in ovarian and endometrial tissues.

Ovarian clear cell carcinoma (OCCC) is a special histological type of epithelial ovarian cancer (EOC) that is not derived from epithelial cells of the ovarian or fallopian tube as the most common type of ovarian cancer, high-grade serous ovarian carcinoma (HGSOC), but is closely related to endometriosis and similar to endometrial clear cell carcinoma (ECCC) at morphologic and phenotypic features. However, limited data was shown in OCCC genomic features and compared with that in OCCC, HGSOC and ECCC. Herein, we utilized next-generation sequencing analysis of a panel of 1,021 genes to profile the mutational alterations in 34 OCCC and compared them to those from HGSOC (402 cases) and ECCC (30 cases). In result, the ARID1A and PIK3CA are high-frequency mutations of OCCC. Clonal architectures showed that all the mutations of genes occur in the later stage in the OCCC progress, whereas KRAS mutation is the earlier event compared with mutation of ARID1A or PIK3CA, which usually occurs in a group of ARID1A or PIK3CA mutations. The mutation frequency of main driver genes is similar between OCCC and ECCC, while TP53 is the main mutation in HGSOC and ECCC. Shared mutational signatures between OCCC and ECCC tissues with commonly observed a C>T change indicated a common carcinogens-exposed between these two carcinomas, but HGSOC and ECCC have common and distinct mutational signatures across cohorts respectively. In addition, we identified some novel CNV gains in NF1, ASXL1, TCF7L2, CREBBP and LRP1B and loss in ATM, FANCM, RB1 and FLT in OCCC. Our study offered a new perspective for OCCC tumorigenesis from two organs, the ovary and uterus, at genomic architectures and revealed novel CNV events for helping to provide theoretical support for OCCC treatment.

The stromal tumor-infiltrating lymphocytes, cancer stemness, epithelial-mesenchymal transition, and B7-H4 expression in ovarian serous carcinoma

BackgroundB7-H4 is expressed in various types of cancers and its expression inversely correlates with the degree of tumor-infiltrating lymphocytes (TILs). Studies have shown the relationship between B7-H4, cancer stem cell (CSC) properties, and epithelial-mesenchymal transition (EMT) in various cancers. However, very few studies have investigated the relationship between B7-H4, TILs, cancer stemness, and EMT in epithelial ovarian cancer (EOC). The present study aimed to elucidate whether B7-H4 is involved in immune evasion and examine whether B7-H4 is associated with cancer stemness or EMT in ovarian serous carcinoma, the most common type of EOC. The clinical significance of B7-H4 was also investigated to evaluate its potential as a therapeutic target.MethodsA total of 145 patients included in this study. The degree of stromal TILs was evaluated using hematoxylin and eosin (H&E)-stained slides. Immunohistochemical analysis of B7-H4, CSC-related biomarkers (CD24, CD44s, CD133, and ALDH1), and EMT-related biomarkers (E-cadherin, N-cadherin, and vimentin) was performed using tissue microarray. qRT-PCR for VTCN1, CD24, CD44, PROM1, ALDH1, CDH1, CDH2, and VIM genes was performed on 38 frozen tissue samples. The mRNA expression levels were analyzed using Gene Expression Profiling Interactive Analysis (GEPIA) online analysis tool.ResultsB7-H4 protein expression positively correlated with the degree of stromal TILs. CD24, CD44s, and CD133 expression showed a positive correlation with B7-H4 expression at both the protein and mRNA levels, but ALDH1 correlated only at the protein level. E-cadherin expression was positively correlated with B7-H4 expression at both the protein and mRNA levels. N-cadherin and vimentin expression was inversely related to B7-H4 expression only at the mRNA level. B7-H4 positive patients were associated with higher tumor grade and lower overall survival rate than B7-H4 negative patients, especially in ovarian serous carcinoma with low stromal TILs.ConclusionsThe present study demonstrates that B7-H4 may not be involved in the immune evasion mechanism, but is involved in cancer stemness and mesenchymal-epithelial transition. In addition, B7-H4 may be a therapeutic target for the treatment of ovarian serous carcinoma, especially with low stromal TILs.

PD-L1 is highly expressed in ovarian cancer and associated with cancer stem cells populations expressing CD44 and other stem cell markers

BackgroundImmune checkpoint inhibitors, including PD-L1 (programmed death ligand-1) inhibitors have well documented anticancer therapeutic effect in most types of cancers but its use in the treatment of ovarian cancer is not yet proven. The aim of our study is to explore the predictive biomarkers in ovarian cancer and its association with the outcomes. We have investigated the role of PD-L1 expressions in the tumor microenvironment cells including immune cells and cancer stem cells in different types of ovarian cancer.MethodsA total of 119 surgical archived ovarian cancer samples were collected from the pathology department at King Fahad Specialist Hospital, Dammam, Saudi Arabia that included serous carcinomas, clear cell carcinomas, mucinous carcinomas, endometrioid carcinomas, and granulosa cell tumors. Immunohistochemistry (IHC) staining was performed using (i) PD-L1 antibodies to detect PD-L1 expressions; (ii) CD8 and CD4 to detect Tumor Infiltrating Lymphocytes (TILs); and (iii) CD44, LGR5, and ALDH2 to detect stem cell markers. The clinicopathological data were collected from patients’ medical record to investigate the association with PD-L1, TILs, and stem cells expressions.ResultsWe report high PD-L1 expressions in 47.8% of ovarian cancer samples. PD-L1 expressions were detected in different types of epithelial ovarian cancer and were not associated with poor prognosis of ovarian cancer. However, determining the expression levels of TILs in the ovarian cancer tissues found that 81% (n = 97) of ovarian cancer samples have TILs that express both of CD8 and CD4 and significantly associated with high PD-L1 expressions. Interestingly, we have found that ovarian cancer tissues with high expressions of PD-L1 were associated with high expressions of stem cells expressing CD44 and LGR5.ConclusionsPD-L1 is highly expressed in the serous type of ovarian carcinomas and the overall expression of PD-L1 is not associated with poor survival rate. Furthermore, PD-L1 expressions are strongly associated with TILs and stem cell markers in ovarian cancer. Inhibiting the PD-L1 using immune checkpoint inhibitors might downregulate stem cell population that known to be associated with cancer recurrence.

Profiling the Expression and Prognostic Values of FYN, A Non-Receptor Tyrosine Kinase, in Different Histological Types of Epithelial Ovarian Cancer.

This study was aimed at evaluating FYN expression among different histologic types of epithelial ovarian cancer (EOC) and its associated prognostics. The FYN expression levels using quantitative real-time PCR method were evaluated in 98 primary EOC. Receiver operating characteristic curve were used to select an optimal cut-off value for determining the presence or absence of a disease progression. The median level of FYN expression varied among different EOC types, being the highest in high-grade serous carcinomas and the lowest in clear cell carcinomas (CCC). Using the cutoff FYN value to predict disease progression, the FYN-positive group had a poorer progression-free survival (PFS) compared to the FYN-negative group (p = 0.001). In multivariate Cox regression analysis, FYN expression was an independent predictor for disease progression (Hazard ratio = 2.30; 95% CI: 1.21- 4.38; p = 0.011). In subgroup analysis, FYN expression was significantly associated with lower PFS in early stage CCC patients (p = 0.009). FYN expression is variable among different types of EOC while impacting on the prognostic values in patients with early stage CCC.

Search for New Participants in the Pathogenesis of High-Grade Serous Ovarian Cancer with the Potential to Be Used as Diagnostic Molecules.

Recent studies have attempted to develop molecular signatures of epithelial ovarian cancer (EOC) based on the quantitation of protein-coding and non-coding RNAs to predict disease prognosis. Due to the heterogeneity of EOC, none of the developed prognostic signatures were directly applied in clinical practice. Our work focuses on high-grade serous ovarian carcinoma (HGSOC) due to the highest mortality rate relative to other types of EOC. Using deep sequencing of small non-coding RNAs in combination with quantitative real-time PCR, we confirm the dualistic classification of epithelial ovarian cancers based on the miRNA signature of HGSOC (type 2), which differs from benign cystadenoma and borderline cystadenoma-precursors of low-grade serous ovarian carcinoma (type 1)-and identified two subtypes of HGSOC, which significantly differ in the level of expression of the progesterone receptor in the tumor tissue, the secretion of miR-16-5p, miR-17-5p, miR-93-5p, miR-20a-5p, the level of serum CA125, tumor size, surgical outcome (optimal or suboptimal cytoreduction), and response to chemotherapy. It was found that the combined determination of the level of miR-16-5p, miR-17-5p, miR-20a-5p, and miR-93-5p circulating in blood plasma of patients with primary HGSOC tumors makes it possible to predict optimal cytoreduction with 80.1% sensitivity and 70% specificity (p = 0.022, TPR = 0.8, FPR = 0.3), as well as complete response to adjuvant chemotherapy with 77.8% sensitivity and 90.9% specificity (p = 0.001, TPR = 0.78, FPR = 0.09). After the additional verification of the obtained data in a larger HGSOC patient cohort, the combined quantification of these four miRNAs is proposed to be used as a criterion for selecting patients either for primary cytoreduction or neoadjuvant chemotherapy followed by interval cytoreduction.

ATR Inhibitors in Platinum-Resistant Ovarian Cancer

Platinum-resistant ovarian cancer (PROC) is one of the deadliest types of epithelial ovarian cancer, and it is associated with a poor prognosis as the median overall survival (OS) is less than 12 months. Targeted therapy is a popular emerging treatment method. Several targeted therapies, including those using bevacizumab and poly (ADP-ribose) polymerase inhibitor (PARPi), have been used to treat PROC. Ataxia telangiectasia and RAD3-Related Protein Kinase inhibitors (ATRi) have attracted attention as a promising class of targeted drugs that can regulate the cell cycle and influence homologous recombination (HR) repair. In recent years, many preclinical and clinical studies have demonstrated the efficacy of ATRis in PROC. This review focuses on the anticancer mechanism of ATRis and the progress of research on ATRis for PROC.

Exvivo assessment of cancer drug sensitivity in epithelial ovarian cancer and its association with histopathological type, treatment history and clinical outcome.

Epithelial ovarian cancer (EOC) is divided into type I and type II based on histopathological features. Type I is clinically more indolent, but also less sensitive to chemotherapy, compared with type II. The basis for this difference is not fully clarified. The present study investigated the pattern of drug activity in type I and type II EOC for standard cytotoxic drugs and recently introduced tyrosine kinase inhibitors (TKIs), and assessed the association with treatment history and clinical outcome. Isolated EOC tumor cells obtained at surgery were investigated for their sensitivity to seven standard cytotoxic drugs and nine TKIs using a short-term fluorescent microculture cytotoxicity assay (FMCA). Drug activity was compared with respect to EOC subtype, preoperative chemotherapy, cross-resistance and association with progression-free survival (PFS). Out of 128 EOC samples, 120 samples, including 21 type I and 99 type II, were successfully analyzed using FMCA. Patients with EOC type I had a significantly longer PFS time than patients with EOC type II (P=0.01). In line with clinical experience, EOC type I samples were generally more resistant than type II samples to both standard cytotoxic drugs and the TKIs, reaching statistical significance for cisplatin (P=0.03) and dasatinib (P=0.002). A similar pattern was noted in samples from patients treated with chemotherapy prior to surgery compared with treatment-naive samples, reaching statistical significance for fluorouracil, irinotecan, dasatinib and nintedanib (all P<0.05). PFS time gradually shortened with increasing degree of drug resistance. Cross-resistance between drugs was in most cases statistically significant yet moderate in degree (r<0.5). The clinically observed relative drug resistance of EOC type I, as well as in patients previously treated, is at least partly due to mechanisms in the tumor cells. These mechanisms seemingly also encompass kinase inhibitors. Ex vivo assessment of drug activity is suggested to have a role in the optimization of drug therapy in EOC.

Comparing Intraperitoneal and Intravenous Personalized ErbB2CAR-T for the Treatment of Epithelial Ovarian Cancer.

High-grade serous ovarian carcinoma (HGSOC) is the most common type of epithelial ovarian cancer. The majority of cases are diagnosed at advanced stages, when intraperitoneal (IP) spread has already occurred. Despite significant surgical and chemotherapeutic advances in HGSOC treatment over the past decades, survival rates with HGSOC have only modestly improved. Chimeric antigen receptor (CAR)-T cells enable T cells to directly bind to tumor-associated antigens in a major histocompatibility complex-independent manner, thereby inducing tumor rejection. While CAR-T cell therapy shows great promise in hematological malignancies, its use in solid tumors is limited. Therefore, innovative approaches are needed to increase the specificity of CAR-modified T cells against solid tumors. The aim of this study was to assess the efficacy and safety of intraperitoneal (IP) versus intravenous (IV) CAR-T cell therapy in the treatment of HGSOC. We constructed a CAR that targets the ErbB2/HER2 protein (ErbB2CAR), which is overexpressed in HGSOC, and evaluated the functionality of ErbB2CAR on ovarian cancer cell lines (OVCAR8, SKOV3, and NAR). Our findings show that an IP injection of ErbB2CAR-T cells to tumor-bearing mice led to disease remission and increased survival compared to the IV route. Moreover, we found that IP-injected ErbB2CART cells circulate to a lesser extent, making them safer for non-tumor tissues than IV-injected cells. Further supporting our findings, we show that the effect of ErbB2CAR-T cells on primary HGSOC tumors is correlated with ErbB2 expression. Together, these data demonstrate the advantages of an IP administration of CAR-T cells over IV administration, offering not only a safer strategy but also the potential for counteracting the effect of ErbB2CAR in HGSOC. Significance: IP-injected ErbB2CAR-T cells led to disease remission and increased survival compared to the IV route. These findings demonstrate the advantages of IP administration, offering a safe treatment strategy with the potential for counteracting the effect of ErbB2CAR in HGSOC.

Nomogram based on ultrasound radiomics score and clinical variables for predicting histologic subtypes of epithelial ovarian cancer.

Ovarian cancer is one of the most common causes of death in gynecological tumors, and its most common type is epithelial ovarian cancer (EOC). This study aimed to establish a radiomics signature based on ultrasound images to predict the histopathological types of EOC. Overall, 265 patients with EOC who underwent preoperative ultrasonography and surgery were eligible. They were randomly sorted into two cohorts (training cohort: test cohort = 7:3). We outlined the region of interest of the tumor on the ultrasound images of the lesion. Then, the radiomics features were extracted. Clinical, Rad-score and combined models were constructed based on the least absolute shrinkage, selection operator, and logistic regression analysis. The performance of the models was evaluated using receiver operating characteristic curves and decision curve analysis (DCA). A nomogram was formulated based on the combined prediction model. The combined model had good performance in predicting EOC histopathological types, with an AUC of 0.83 (95% CI: 0.77-0.90) and 0.82 (95% CI: 0.71-0.93) in the training and test cohorts, respectively. The calibration curves showed that the nomogram estimation was consistent with the actual observations. DCA also verified the clinical value of the combined model. The combined model containing clinical and ultrasound radiomics features showed an excellent performance in predicting type I and type II EOC. This study presents the first application of ultrasound radiomics features to distinguish EOC histopathological types. The proposed clinical-radiomics nomogram could help gynecologists non-invasively identify EOC types before surgery.

An Application of Machine Learning That Uses the Magnetic Resonance Imaging Metric, Mean Apparent Diffusion Coefficient, to Differentiate between the Histological Types of Ovarian Cancer.

This retrospective single-center study included patients diagnosed with epithelial ovarian cancer (EOC) using preoperative pelvic magnetic resonance imaging (MRI). The apparent diffusion coefficient (ADC) of the axial MRI maps that included the largest solid portion of the ovarian mass was analysed. The mean ADC values (ADCmean) were derived from the regions of interest (ROIs) of each largest solid portion. Logistic regression and three types of machine learning (ML) applications were used to analyse the ADCs and clinical factors. Of the 200 patients, 103 had high-grade serous ovarian cancer (HGSOC), and 97 had non-HGSOC (endometrioid carcinoma, clear cell carcinoma, mucinous carcinoma, and low-grade serous ovarian cancer). The median ADCmean of patients with HGSOC was significantly lower than that of patients without HGSOCs. Low ADCmean and CA 19-9 levels were independent predictors for HGSOC over non-HGSOC. Compared to stage I disease, stage III disease was associated with HGSOC. Gradient boosting machine and extreme gradient boosting machine showed the highest accuracy in distinguishing between the histological findings of HGSOC versus non-HGSOC and between the five histological types of EOC. In conclusion, ADCmean, disease stage at diagnosis, and CA 19-9 level were significant factors for differentiating between EOC histological types.

BRCA1/2 Mutation Types Do Not Affect Prognosis in Ovarian Cancer Patients.

Background: High grade serous ovarian carcinoma (HGSOC) is the most lethal type of epithelial ovarian cancer, with a prevalence of germline BRCA1/2 mutations as high as 20%. Our objective is to determine whether the location of mutations in the different domains of the BRCA1/2 genes affects the clinical outcome of HGSOC patients. Methods: A total of 51 women with BRCA1 or BRCA2 mutated ovarian cancer were identified. Progression-free survival (PFS) and overall survival (OS) were analyzed. Results: In our study cohort, 35 patients were carriers of germline mutations in BRCA1 and 16 in BRCA2. The median PFS time following completion of the primary therapy was 23.8 months (95% CI 20.1–27.5) and the median OS was 92.9 months (95% CI 69.8–116.1) in all BRCA carriers. After multivariate analysis, no significant association among the location or type of BRCA1/2 mutation with PFS or OS was identified. Notably, significant differences in PFS between carriers of identical mutations in the same BRCA gene were detected. Conclusions: Among HGSOC patients, BRCA1/2 carriers with mutations in different locations of the genes show no significant difference in survival outcomes, in terms of PFS and OS, suggesting the potential effect of other genetic abnormalities and co-contributing risk factors.