The prognostic value of dividing epithelial ovarian cancer into type I and type II tumors based on pathologic characteristics

Tumor Markers and Their Diagnostic Significance in Ovarian Cancer

Ovarian cancer (OC) is characterized by silent progression and late-stage diagnosis. It is critical to detect and accurately diagnose the disease early to improve survival rates. Tumor markers have emerged as valuable tools in the diagnosis and management of OC, offering non-invasive and cost-effective options for screening, monitoring, and prognosis.

PURPOSE

This paper explores the diagnostic importance of various tumor markers including CA-125, CA15-3, CA 19-9, HE4,hCG, inhibin, AFP, and LDH, and their impact on disease monitoring and treatment response assessment.

METHODS

Article searches were performed on PubMed, Scopus, and Google Scholar. Keywords used for the searching process were "Ovarian cancer", "Cancer biomarkers", "Early detection", "Cancer diagnosis", "CA-125","CA 15-3","CA 19-9", "HE4","hCG", "inhibin", "AFP", "LDH", and others.

RESULTS

HE4, when combined with CA-125, shows improved sensitivity and specificity, particularly in early-stage detection. Additionally, hCG holds promise as a prognostic marker, aiding treatment response prediction and outcome assessment. Novel markers like microRNAs, DNA methylation patterns, and circulating tumor cells offer potential for enhanced diagnostic accuracy and personalized management. Integrating these markers into a comprehensive panel may improve sensitivity and specificity in ovarian cancer diagnosis. However, careful interpretation of tumor marker results is necessary, considering factors such as age, menopausal status, and comorbidities. Further research is needed to validate and refine diagnostic algorithms, optimizing the clinical significance of tumor markers in ovarian cancer management. In conclusion, tumor markers such as CA-125, CA15-3, CA 19-9, HE4, and hCG provide valuable insights into ovarian cancer diagnosis, monitoring, and prognosis, with the potential to enhance early detection.

Deep learning for the ovarian lesion localization and discrimination between borderline and malignant ovarian tumors based on routine MR imaging

To establish a deep learning (DL) model in differentiating borderline ovarian tumor (BOT) from epithelial ovarian cancer (EOC) on conventional MR imaging. We retrospectively enrolled 201 patients of 102 pathologically proven BOTs and 99 EOCs at OB/GYN hospital Fudan University, between January 2015 and December 2017. All imaging data were reviewed on picture archiving and communication systems (PACS) server. Both T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) MR images were used for lesion area determination. We trained a U-net++ model with deep supervision to segment the lesion area on MR images. Then, the segmented regions were fed into a classification model based on DL network to categorize ovarian masses automatically. For ovarian lesion segmentation, the mean dice similarity coefficient (DSC) of the trained U-net++ model in the testing dataset achieved 0.73 [Formula: see text] 0.25, 0.76 [Formula: see text] 0.18, and 0.60 [Formula: see text] 0.24 in the sagittal T2WI, coronal T2WI, and axial T1WI images, respectively. The DL model by combined T2WI computerized network could differentiate BOT from EOC with a significantly higher AUC of 0.87, an accuracy of 83.7%, a sensitivity of 75.0% and a specificity of 87.5%. In comparison, the AUC yielded by radiologist was only 0.75, with an accuracy of 75.5%, a sensitivity of 96.0% and specificity of 54.2% (P < 0.001).The trained DL network model derived from routine MR imaging could help to distinguish BOT from EOC with a high accuracy, which was superior to radiologists' assessment.

Computed Tomographic Radiomics in Differentiating Histologic Subtypes of Epithelial Ovarian Carcinoma

IMPORTANCE

Epithelial ovarian carcinoma is heterogeneous and classified according to the World Health Organization Tumour Classification, which is based on histologic features and molecular alterations. Preoperative prediction of the histologic subtypes could aid in clinical management and disease prognostication.

OBJECTIVE

To assess the value of radiomics based on contrast-enhanced computed tomography (CT) in differentiating histologic subtypes of epithelial ovarian carcinoma in multicenter data sets.

DESIGN, SETTING, AND PARTICIPANTS

In this diagnostic study, 665 patients with histologically confirmed epithelial ovarian carcinoma were retrospectively recruited from 4 centers (Hong Kong, Guangdong Province of China, and Seoul, South Korea) between January 1, 2012, and February 28, 2022. The patients were randomly divided into a training cohort (n = 532) and a testing cohort (n = 133) with a ratio of 8:2. This process was repeated 100 times. Tumor segmentation was manually delineated on each section of contrast-enhanced CT images to encompass the entire tumor. The Mann-Whitney U test and voted least absolute shrinkage and selection operator were performed for feature reduction and selection. Selected features were used to build the logistic regression model for differentiating high-grade serous carcinoma and non-high-grade serous carcinoma.

EXPOSURES

Contrast-enhanced CT-based radiomics.

MAIN OUTCOMES AND MEASURES

Intraobserver and interobserver reproducibility of tumor segmentation were measured by Dice similarity coefficients. The diagnostic efficiency of the model was assessed by receiver operating characteristic curve and area under the curve.

RESULTS

In this study, 665 female patients (mean [SD] age, 53.6 [10.9] years) with epithelial ovarian carcinoma were enrolled and analyzed. The Dice similarity coefficients of intraobserver and interobserver were all greater than 0.80. Twenty radiomic features were selected for modeling. The areas under the curve of the logistic regression model in differentiating high-grade serous carcinoma and non-high-grade serous carcinoma were 0.837 (95% CI, 0.835-0.838) for the training cohort and 0.836 (95% CI, 0.833-0.840) for the testing cohort.

CONCLUSIONS AND RELEVANCE

In this diagnostic study, radiomic features extracted from contrast-enhanced CT were useful in the classification of histologic subtypes in epithelial ovarian carcinoma. Intraobserver and interobserver reproducibility of tumor segmentation was excellent. The proposed logistic regression model offered excellent discriminative ability among histologic subtypes.

Therapeutic Strategies for Ovarian Cancer in Point of HGF/c-MET Targeting

Ovarian cancer is the fifth leading cause of cancer deaths in women and is regarded as one of the most difficult cancers to treat. Currently, studies are being conducted to develop therapeutic agents for effective treatment of ovarian cancer. In this review, we explain the properties of the hepatocyte growth factor (HGF)/mesenchymal-epithelial transition factor (c-MET) and how the signaling pathway of HGF/c-MET is activated in different cancers and involved in tumorigenesis and metastasis of ovarian cancer. We present the findings of clinical studies using small chemicals or antibodies targeting HGF/c-MET signaling in various cancer types, particularly in ovarian cancer. We also discuss that HGF/c-MET-targeted therapy, when combined with chemo drugs, could be an effective strategy for ovarian cancer therapeutics.

Suicide and Accidental Death Among Women With Primary Ovarian Cancer: A Population-Based Study

Background

Women with ovarian cancer had the highest suicidal rate among all patients with gynecological malignancies, but no large studies about suicide and accidental death for women with ovarian cancers in detail were conducted. We aimed to determine the relative risk of suicide and accidental death among patients with ovarian cancer to that of the general population, and to identify risk factors associated with suicide and accidental death.

Methods

Data are from the SEER (surveillance, epidemiology, and end results) cancer registry of women diagnosed with ovarian cancer data from 18 registries for the years 1973–2016. The study population comprised 149,204 patients after inclusion and exclusion criteria were applied. Standardized mortality ratios (SMRs) were calculated and Fine-Gray models were fitted to identify risk factors associated with suicidal and accidental death among cancer patients, with stratifications on demographic and tumor-related characteristics.

Results

Women with ovarian cancer had a higher risk of suicide and accidental death than the cancer-free group [SMR = 1.86; 95% CI (1.54–2.25) and SMR = 1.54; 95% CI (1.39–1.71)]. Subgroup analysis indicated that only patients with type II epithelial ovarian cancer [SMR = 2.31; 95% CI (1.83–2.91)] had an increased risk of suicide, and those with type I and type II epithelial ovarian cancer [SMR = 1.65; 95% CI (1.39–1.97) and SMR = 1.49; 95% CI (1.30–1.70)] were at a higher risk of accidental death. Patients with ovarian cancer who were younger, white, diagnosed with high-grade, non-metastatic cancer and pelvic exenteration were at a higher risk of suicide. The advanced age, earlier year of diagnosis, and non-metastatic cancer were associated with a higher risk of accidental death. Additionally, pelvic exenteration increased the risk of suicide but not the risk of accidental death among women with primary ovarian cancer.

Conclusions

Women with ovarian cancer had a higher risk of suicide and accidental death compared with the general population. The findings suggested that clinicians should identify high-risk subgroups of ovarian cancer patients for suicide and accidental death as early as possible, with appropriate prevention strategies.

Two-dimensional and three-dimensional T2 weighted imaging-based radiomic signatures for the preoperative discrimination of ovarian borderline tumors and malignant tumors

BACKGROUND

Ovarian cancer is the most women malignancy in the whole world. It is difficult to differentiate ovarian cancers from ovarian borderline tumors because of some similar imaging findings.Radiomics study may help clinicians to make a proper diagnosis before invasive surgery.

PURPOSE

To evaluate the ability of T2-weighted imaging (T2WI)-based radiomics to discriminate ovarian borderline tumors (BOTs) from malignancies based on two-dimensional (2D) and three-dimensional (3D) lesion segmentation methods.

METHODS

A total of 95 patients with pathologically proven ovarian BOTs and 101 patients with malignancies were retrospectively included in this study. We evaluated the diagnostic performance of the signatures derived from T2WI-based radiomics in their ability to differentiate between BOTs and malignancies and compared the performance differences in the 2D and 3D segmentation models. The least absolute shrinkage and selection operator method (Lasso) was used for radiomics feature selection and machine learning processing.

RESULTS

The radiomics score between BOTs and malignancies in four types of selected T2WI-based radiomics models differed significantly at the statistical level (p < 0.0001). For the classification between BOTs and malignant masses, the 2D and 3D coronal T2WI-based radiomics models yielded accuracy values of 0.79 and 0.83 in the testing group, respectively; the 2D and 3D sagittal fat-suppressed (fs) T2WI-based radiomics models yielded an accuracy of 0.78 and 0.99, respectively.

CONCLUSIONS

Our results suggest that T2WI-based radiomic features were highly correlated with ovarian tumor subtype classification. 3D-sagittal MRI radiomics features may help clinicians differentiate ovarian BOTs from malignancies with high ACC.

MR-based radiomics-clinical nomogram in epithelial ovarian tumor prognosis prediction: tumor body texture analysis across various acquisition protocols

Background

Epithelial ovarian cancer (EOC) is the most malignant gynecological tumor in women. This study aimed to construct and compare radiomics-clinical nomograms based on MR images in EOC prognosis prediction.

Methods

A total of 186 patients with pathologically proven EOC were enrolled and randomly divided into a training cohort (n = 130) and a validation cohort (n = 56). Clinical characteristics of each patient were retrieved from the hospital information system. A total of 1116 radiomics features were extracted from tumor body on T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), diffusion weighted imaging (DWI) and contrast-enhanced T1-weighted imaging (CE-T1WI). Paired sequence signatures were constructed, selected and trained to build a prognosis prediction model. Radiomic-clinical nomogram was constructed based on multivariate logistic regression analysis with radiomics score and clinical features. The predictive performance was evaluated by receiver operating characteristic curve (ROC) analysis, decision curve analysis (DCA) and calibration curve.

Results

The T2WI radiomic-clinical nomogram achieved a favorable prediction performance in the training and validation cohort with an area under ROC curve (AUC) of 0.866 and 0.818, respectively. The DCA showed that the T2WI radiomic-clinical nomogram was better than other models with a greater clinical net benefit.

Conclusion

MR-based radiomics analysis showed the high accuracy in prognostic estimation of EOC patients and could help to predict therapeutic outcome before treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00941-7.

MicroRNAs as Biomarkers for Early Diagnosis, Prognosis, and Therapeutic Targeting of Ovarian Cancer

Ovarian cancer is the major cause of gynecologic cancer-related mortality. Regardless of outstanding advances, which have been made for improving the prognosis, diagnosis, and treatment of ovarian cancer, the majority of the patients will die of the disease. Late-stage diagnosis and the occurrence of recurrent cancer after treatment are the most important causes of the high mortality rate observed in ovarian cancer patients. Unraveling the molecular mechanisms involved in the pathogenesis of ovarian cancer may help find new biomarkers and therapeutic targets for ovarian cancer. MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression, mostly at the posttranscriptional stage, through binding to mRNA targets and inducing translational repression or degradation of target via the RNA-induced silencing complex. Over the last two decades, the role of miRNAs in the pathogenesis of various human cancers, including ovarian cancer, has been documented in multiple studies. Consequently, these small RNAs could be considered as reliable markers for prognosis and early diagnosis. Furthermore, given the function of miRNAs in various cellular pathways, including cell survival and differentiation, targeting miRNAs could be an interesting approach for the treatment of human cancers. Here, we review our current understanding of the most updated role of the important dysregulation of miRNAs and their roles in the progression and metastasis of ovarian cancer. Furthermore, we meticulously discuss the significance of miRNAs as prognostic and diagnostic markers. Lastly, we mention the opportunities and the efforts made for targeting ovarian cancer through inhibition and/or stimulation of the miRNAs.

Anti-oncogenic PTEN induces ovarian cancer cell senescence by targeting P21

Deletion and mutation of phosphatase and tensin homolog deleted on chromosome10 (PTEN) are closely associated with the occurrence of tumors. Tumor suppressor gene PTEN mutation plays an important role in the pathogenesis of ovarian cancer. However, it has been unclear whether it can regulate the senescence of ovarian cancer cells. We speculated that PTEN might inhibit the occurrence and development of ovarian cancer by promoting the expression of P21. We found that the expression of TRIM39 in human ovarian cancer was significantly diminished. In SKOV3 cells treated with naringin, the expression of TRIM39, which binds P21 and inhibits P21 degradation, was significantly elevated. Real‐time polymerase chain reaction (PCR), Western blot, and immunofluorescence were used to detected the expression of PTEN, p21, and TRIM39, β‐galactosidase Staining was used to detect cell senescence, Ki67 staining was used to observe cell proliferation, Trim39 interference or overexpression assay was used to detect its function. We speculated that PTEN might promote SKOV3 cell senescence by increasing TRIM39 expression and decreasing P21 degradation. Furthermore, by interfering with TRIM39 in SKOV3 cells, we found that the expression of P21 was downregulated, and the number of senescent SKOV3 cells decreased. With overexpression of TRIM39 in SKOV3 cells, the expression of P21 was upregulated, and the number of senescent SKOV3 cells increased. When naringin, a PTEN agonist, was added to SKOV3 cells in which TRIM39 protein was interfered with, the expression of P21 was significantly lower than that in the control group, and the number of senescent ovarian cancer cells was significantly diminished. Our results indicated that PTEN maintained the stability of P21 and decreased the degradation of P21 by increasing TRIM39 expression, thus promoting the senescence of SKOV3 cells, and PTEN maintained the stability of p21 and promoted the aging of SKOV3 cells might be a novel therapeutic target for ovarian cancer.

MicroRNA characteristics in epithelial ovarian cancer

The purpose of the current study was to clarify differences in microRNA expression according to clinicopathological characteristics, and to investigate if miRNA profiles could predict cytoreductive outcome in patients with FIGO stage IIIC and IV ovarian cancer. Patients enrolled in the Pelvic Mass study between 2004 and 2010, diagnosed and surgically treated for epithelial ovarian cancer, were used for investigation. MicroRNA was profiled from tumour tissue with global microRNA microarray analysis. Differences in miRNA expression profiles were analysed according to histologic subtype, FIGO stage, tumour grade, type I or II tumours and result of primary cytoreductive surgery. One microRNA, miR-130a, which was found to be associated with serous histology and advanced FIGO stage, was also validated using data from external cohorts. Another seven microRNAs (miR-34a, miR-455-3p, miR-595, miR-1301, miR-146-5p, 193a-5p, miR-939) were found to be significantly associated with the clinicopathological characteristics (p ≤ 0.001), in our data, but mere not similarly significant when tested against external cohorts. Further validation in comparable cohorts, with microRNA profiled using newest and similar methods are warranted.

CA125 and Ovarian Cancer: A Comprehensive Review

Simple Summary

CA125 has been the most promising biomarker for screening ovarian cancer; however, it still does not have an acceptable accuracy in population-based screening for ovarian cancer. In this review article, we have discussed the role of CA125 in diagnosis, evaluating response to treatment and prognosis of ovarian cancer and provided some suggestions in improving the clinical utility of this biomarker in the early diagnosis of aggressive ovarian cancers. These include using CA125 to screen individuals with symptoms who seek medical care rather than screening the general population, increasing the cutoff point for the CA125 level in the plasma and performing the test at point-of-care rather than laboratory testing. By these strategies, we would detect more aggressive ovarian cancer patients in stages that the tumour can be completely removed by surgery, which is the most important factor in redusing recurrence rate and improving the survival of the patients with ovarian cancer.

Abstract

Ovarian cancer is the second most lethal gynecological malignancy. The tumour biomarker CA125 has been used as the primary ovarian cancer marker for the past four decades. The focus on diagnosing ovarian cancer in stages I and II using CA125 as a diagnostic biomarker has not improved patients’ survival. Therefore, screening average-risk asymptomatic women with CA125 is not recommended by any professional society. The dualistic model of ovarian cancer carcinogenesis suggests that type II tumours are responsible for the majority of ovarian cancer mortality. However, type II tumours are rarely diagnosed in stages I and II. The recent shift of focus to the diagnosis of low volume type II ovarian cancer in its early stages of evolution provides a new and valuable target for screening. Type II ovarian cancers are usually diagnosed in advanced stages and have significantly higher CA125 levels than type I tumours. The detection of low volume type II carcinomas in stage IIIa/b is associated with a higher likelihood for optimal cytoreduction, the most robust prognostic indicator for ovarian cancer patients. The diagnosis of type II ovarian cancer in the early substages of stage III with CA125 may be possible using a higher cutoff point rather than the traditionally used 35 U/mL through the use of point-of-care CA125 assays in primary care facilities. Rapid point-of-care testing also has the potential for effective longitudinal screening and quick monitoring of ovarian cancer patients during and after treatment. This review covers the role of CA125 in the diagnosis and management of ovarian cancer and explores novel and more effective screening strategies with CA125.

The Role of Eicosanoids in Gynecological Malignancies

Eicosanoids, bio-active lipid molecules, evoke a multitude of biological effects that directly affect cancer cells and indirectly affect tumor microenvironment. An emerging role has been shown for eicosanoids in the pathogenesis of gynecological malignancies which include cancers of the vulva, vagina, cervix, uterine, and ovary. Eicosanoid biosynthesis pathways start at the metabolism of phospholipids by phospholipase A2 then proceeding to one of three pathways: the cyclooxygenase (COX), lipoxygenase (LOX), or P450 epoxygenase pathways. The most studied eicosanoid pathways include COX and LOX; however, more evidence is appearing to support further study of the P450 epoxygenase pathway in gynecologic cancers. In this review, we present the current knowledge of the role of COX, LOX and P450 pathways in the pathogenesis of gynecologic malignancies. Vulvar and vaginal cancer, the rarest subtypes, there is association of COX-2 expression with poor disease specific survival in vulvar cancer and, in vaginal cancer, COX-2 expression has been found to play a role in mucosal inflammation leading to disease susceptibility and transmission. Cervical cancer is associated with COX-2 levels 7.4 times higher than in healthy tissues. Additionally, HPV elevates COX-2 levels through the EGFR pathway and HIV promotes elevated COX-2 levels in cervical tissue as well as increases PGE2 levels eliciting inflammation and progression of cancer. Evidence supports significant roles for both the LOX and COX pathways in uterine cancer. In endometrial cancer, there is increased expression of 5-LOX which is associated with adverse outcomes. Prostanoids in the COX pathway PGE2 and PGF2α have been shown to play a significant role in uterine cancer including alteration of proliferation, adhesion, migration, invasion, angiogenesis, and the inflammatory microenvironment. The most studied gynecological malignancy in regard to the potential role of eicosanoids in tumorigenesis is ovarian cancer in which all three pathways have shown to be associated or play a role in ovarian tumorigenesis directly on the tumor cell or through modulation of the tumor microenvironment. By identifying the gaps in knowledge, additional pathways and targets could be identified in order to obtain a better understanding of eicosanoid signaling in gynecological malignancies and identify potential new therapeutic approaches.

Ovarian cancer risk factors by tumor aggressiveness: An analysis from the Ovarian Cancer Cohort Consortium

Ovarian cancer risk factors differ by histotype; however, within subtype, there is substantial variability in outcomes. We hypothesized that risk factor profiles may influence tumor aggressiveness, defined by time between diagnosis and death, independent of histology. Among 1.3 million women from 21 prospective cohorts, 4,584 invasive epithelial ovarian cancers were identified and classified as highly aggressive (death in <1 year, n = 864), very aggressive (death in 1 to < 3 years, n = 1,390), moderately aggressive (death in 3 to < 5 years, n = 639), and less aggressive (lived 5+ years, n = 1,691). Using competing risks Cox proportional hazards regression, we assessed heterogeneity of associations by tumor aggressiveness for all cases and among serous and endometrioid/clear cell tumors. Associations between parity (p_het = 0.01), family history of ovarian cancer (p_het = 0.02), body mass index (BMI; p_het ≤ 0.04) and smoking (p_het < 0.01) and ovarian cancer risk differed by aggressiveness. A first/single pregnancy, relative to nulliparity, was inversely associated with highly aggressive disease (HR: 0.72; 95% CI [0.58-0.88]), no association was observed for subsequent pregnancies (per pregnancy, 0.97 [0.92-1.02]). In contrast, first and subsequent pregnancies were similarly associated with less aggressive disease (0.87 for both). Family history of ovarian cancer was only associated with risk of less aggressive disease (1.94 [1.47-2.55]). High BMI (≥35 vs. 20 to < 25 kg/m² , 1.93 [1.46-2.56] and current smoking (vs. never, 1.30 [1.07-1.57]) were associated with increased risk of highly aggressive disease. Results were similar within histotypes. Ovarian cancer risk factors may be directly associated with subtypes defined by tumor aggressiveness, rather than through differential effects on histology. Studies to assess biological pathways are warranted.

Ovarian cancer risk factors by tumor aggressiveness: An analysis from the Ovarian Cancer Cohort Consortium

Ovarian cancer risk factors differ by histotype; however, within subtype, there is substantial variability in outcomes. We hypothesized that risk factor profiles may influence tumor aggressiveness, defined by time between diagnosis and death, independent of histology. Among 1.3 million women from 21 prospective cohorts, 4,584 invasive epithelial ovarian cancers were identified and classified as highly aggressive (death in <1 year, n = 864), very aggressive (death in 1 to < 3 years, n = 1,390), moderately aggressive (death in 3 to < 5 years, n = 639), and less aggressive (lived 5+ years, n = 1,691). Using competing risks Cox proportional hazards regression, we assessed heterogeneity of associations by tumor aggressiveness for all cases and among serous and endometrioid/clear cell tumors. Associations between parity (phet = 0.01), family history of ovarian cancer (phet = 0.02), body mass index (BMI; phet ≤ 0.04) and smoking (phet < 0.01) and ovarian cancer risk differed by aggressiveness. A first/single pregnancy, relative to nulliparity, was inversely associated with highly aggressive disease (HR: 0.72; 95% CI [0.58-0.88]), no association was observed for subsequent pregnancies (per pregnancy, 0.97 [0.92-1.02]). In contrast, first and subsequent pregnancies were similarly associated with less aggressive disease (0.87 for both). Family history of ovarian cancer was only associated with risk of less aggressive disease (1.94 [1.47-2.55]). High BMI (≥35 vs. 20 to < 25 kg/m2 , 1.93 [1.46-2.56] and current smoking (vs. never, 1.30 [1.07-1.57]) were associated with increased risk of highly aggressive disease. Results were similar within histotypes. Ovarian cancer risk factors may be directly associated with subtypes defined by tumor aggressiveness, rather than through differential effects on histology. Studies to assess biological pathways are warranted.

Ovarian cancer risk factors by tumor aggressiveness: An analysis from the Ovarian Cancer Cohort Consortium

Ovarian cancer risk factors differ by histotype; however, within subtype, there is substantial variability in outcomes. We hypothesized that risk factor profiles may influence tumor aggressiveness, defined by time between diagnosis and death, independent of histology. Among 1.3 million women from 21 prospective cohorts, 4,584 invasive epithelial ovarian cancers were identified and classified as highly aggressive (death in <1 year, n = 864), very aggressive (death in 1 to < 3 years, n = 1,390), moderately aggressive (death in 3 to < 5 years, n = 639), and less aggressive (lived 5+ years, n = 1,691). Using competing risks Cox proportional hazards regression, we assessed heterogeneity of associations by tumor aggressiveness for all cases and among serous and endometrioid/clear cell tumors. Associations between parity (p_het = 0.01), family history of ovarian cancer (p_het = 0.02), body mass index (BMI; p_het ≤ 0.04) and smoking (p_het < 0.01) and ovarian cancer risk differed by aggressiveness. A first/single pregnancy, relative to nulliparity, was inversely associated with highly aggressive disease (HR: 0.72; 95% CI [0.58-0.88]), no association was observed for subsequent pregnancies (per pregnancy, 0.97 [0.92-1.02]). In contrast, first and subsequent pregnancies were similarly associated with less aggressive disease (0.87 for both). Family history of ovarian cancer was only associated with risk of less aggressive disease (1.94 [1.47-2.55]). High BMI (≥35 vs. 20 to < 25 kg/m² , 1.93 [1.46-2.56] and current smoking (vs. never, 1.30 [1.07-1.57]) were associated with increased risk of highly aggressive disease. Results were similar within histotypes. Ovarian cancer risk factors may be directly associated with subtypes defined by tumor aggressiveness, rather than through differential effects on histology. Studies to assess biological pathways are warranted.

Magnetic resonance imaging in categorization of ovarian epithelial cancer and survival analysis with focus on apparent diffusion coefficient value: correlation with Ki-67 expression and serum cancer antigen-125 level

Background

To determine whether magnetic resonance (MR) imaging features combined with apparent diffusion coefficient (ADC) values could be used as a tool for categorizing ovarian epithelial cancer (OEC) and predicting survival, as well as correlating with laboratory tests (serum cancer antigen 125, serum CA-125) and tumor proliferative index (Ki-67 expression).

Methods and materials

MRI examination was undertaken before invasive procedures. MRI features were interpreted and recorded on the picture archive communication system (PACS). ADC measurements were manually performed on post-process workstation. Clinical characteristics were individually retrieved and recorded through the hospital information system (HIS). Cox hazard model was used to estimate the effects of both clinical and MRI features on overall survival.

Results

Both clinical and MRI features differed significantly between Type I and Type II cancer groups (p < 0.05). The mean ADC value was inversely correlated with Ki-67 expression in Type I cancer (ρ = − 0.14, p < 0.05). A higher mean ADC value was more likely to suggest Type I ovarian cancer (Odds Ratio (OR) = 16.80, p < 0.01). Old age and an advanced International Federation of Gynecology and Obstetrics (FIGO) stage were significantly related to Type II ovarian cancer (OR = 0.22/0.02, p < 0.05). An advanced FIGO stage, solid components, and old age were significantly associated with poor survival (Hazard Ratio (HR) = 23.54/3.69/2.46, p < 0.05). Clear cell cancer type had a poorer survival than any other pathological subtypes of ovarian cancer (HR = 13.6, p < 0.01).

Conclusions

MR imaging features combined with ADC value are helpful in categorizing OEC. ADC values can reflect tumor proliferative ability. A solid mass may predict poor prognosis for OEC patients.

Electronic supplementary material

The online version of this article (10.1186/s13048-019-0534-0) contains supplementary material, which is available to authorized users.

Serum folate receptor α (sFR) in ovarian cancer diagnosis and surveillance

Novelty and Impact Statement: Our findings suggest that soluble folate receptor (sFR) could be used in both the initial diagnosis and surveillance of patients with ovarian cancer. Our cohort constitutes one of the largest comparison groups for sFR analyzed so far. We have defined the background level of sFR using healthy volunteers. This is also the first study to prospectively follow patients in the surveillance setting to concurrently identify differential changes in tumor markers CA-125 and sFR.

Serum folate receptor α (sFR) in ovarian cancer diagnosis and surveillance

Novelty and Impact Statement: Our findings suggest that soluble folate receptor (sFR) could be used in both the initial diagnosis and surveillance of patients with ovarian cancer. Our cohort constitutes one of the largest comparison groups for sFR analyzed so far. We have defined the background level of sFR using healthy volunteers. This is also the first study to prospectively follow patients in the surveillance setting to concurrently identify differential changes in tumor markers CA-125 and sFR.

Serum folate receptor α (sFR) in ovarian cancer diagnosis and surveillance

Novelty and Impact Statement: Our findings suggest that soluble folate receptor (sFR) could be used in both the initial diagnosis and surveillance of patients with ovarian cancer. Our cohort constitutes one of the largest comparison groups for sFR analyzed so far. We have defined the background level of sFR using healthy volunteers. This is also the first study to prospectively follow patients in the surveillance setting to concurrently identify differential changes in tumor markers CA‐125 and sFR.

Ovarian Clear Cell Carcinoma: From Morphology to Molecular Biology

Ovarian clear cell carcinoma (oCCC) is a distinctive subtype of ovarian carcinoma, with peculiar genetic and environmental risk factors, precursor lesions, molecular events during oncogenesis, patterns of spread, and response to treatment. Because of low response to chemotherapy and poor prognosis in advanced stages, there is growing interest in investigating the molecular pathways involved in oCCC development, in order to individualize novel/molecular targeted therapies. Until now, the main molecular genetic changes associated with oCCC remain to be identified, and, although several molecular changes have been reported in clear cell tumors, most studies have analyzed a limited number of cases; therefore, the true prevalence of those changes is not known. The present review will present the clinicopathologic features of oCCC, from morphology to molecular biology, discussing the diagnostic and treatment challenges of this intriguing ovarian carcinoma.

Differential cyclooxygenase expression levels and survival associations in type I and type II ovarian tumors

BACKGROUND

High cyclooxygenase (COX)-2 expression in ovarian tumors has been associated with poor prognosis, but the role of COX-1 expression and its relation to survival is less clear. Here, we evaluated COX expression and associations with survival outcomes between type I (clear cell, mucinous, low grade endometrioid and low grade serous) and type II (high grade serous and high grade endometrioid) ovarian tumors.

METHODS

We developed and validated a new COX-1 antibody, and conducted immunohistochemical (IHC) staining for COX-1 and COX-2 on a tissue microarray (TMA) of 190 primary ovarian tumors. In addition to standard IHC scoring and H-scores to combine the percentage of positive cells and staining intensity, we also measured COX-1 and COX-2 mRNA expression by QPCR. High expression was defined as greater than or equal to median values. Clinical characteristics and disease outcomes were ascertained from medical records. Associations with disease-free survival (DFS) and overall survival (OS) were quantified by hazard ratios (HRs) and confidence intervals (CIs) from proportional hazards regression.

RESULTS

Type I tumors had high COX-2 expression, while type II tumors had high COX-1 expression. In multivariable adjusted regression models, higher COX-1 mRNA expression was associated with shorter DFS (HR: 6.37, 95% CI: 1.84-22.01) and OS (HR: 2.26, 95% CI: 1.04-4.91), while higher H-scores for COX-2 expression were associated with shorter DFS (HR: 1.92, 95% CI: 1.06-3.49). Stratified analysis indicated that COX-2 was significantly associated with DFS among cases with Type II tumors (HR: 1.93, 95% CI: 1.06-3.53).

CONCLUSIONS

These findings suggest that ovarian tumor type contributes to differences in COX expression levels and associations with survival.

[Grading of gynecological tumors : Current aspects]

Histopathological assessment of the tumor grade and cell type is central to the management and prognosis of various gynecological malignancies. Conventional grading systems for squamous carcinomas and adenocarcinomas of the vulva, vagina and cervix are poorly defined. For endometrioid tumors of the female genital tract as well as for mucinous endometrial, ovarian and seromucinous ovarian carcinomas, the 3‑tiered FIGO grading system is recommended. For uterine neuroendocrine tumors the grading system of the gastrointestinal counterparts has been adopted. Uterine leiomyosarcomas are not graded. Endometrial stromal sarcomas are divided into low and high grades, based on cellular morphology, immunohistochemical and molecular findings. A chemotherapy response score was established for chemotherapeutically treated high-grade serous pelvic cancer. For non-epithelial ovarian malignancies, only Sertoli-Leydig cell tumors and immature teratomas are graded. At this time molecular profiling has no impact on the grading of tumors of the female genital tract.

CT and MRI findings of type I and type II epithelial ovarian cancer

OBJECTIVE

To assess whether types I and II epithelial ovarian cancer (EOC) differ in CT and MRI imaging features.

METHODS

For this retrospective study, we enrolled 65 patients with 68 ovarian lesions that have been pathologically proven to be EOC. Of these patients, 38 cases underwent MR examinations only, 15 cases underwent CT examinations only, and 12 cases completed both examinations. The clinical information [age, CA-125, menopausal status, and Ki-67] and imaging findings were compared between two types of EOCs. The diagnostic performance of image findings were assessed by receiver-operating characteristic curve(ROC) analysis. The association between EOC type and imaging features was assessed by multivariate logistic regression analysis. The random forest approach was used to build a classifier in differential diagnosis between two types of EOCs.

RESULTS

Of the 68 EOC lesions, 24 lesions were categorized as types I and other 44 lesions as type II based on the immunohistochemical results, respectively. Patients in type I EOCs were more likely to involve menopausal women and showed lower CA-125 and Ki-67 values (Ki-67<30%) than patients in type II EOCs. The imaging characteristics of type II EOCs frequently demonstrated a solid or predominantly solid mass (38.6% vs. 12.5%, P<0.05), smaller lesions (diameter <6cm; 27.3% vs. 4.2%, P<0.05), absence of mural nodules (65.9% vs. 25.9%, P=0.001), and mild enhancement (84.1% vs. 54.2%, P<0.05) compared to type I EOCs. Combination of tumor size, morphology, mural nodule, enhancement degrees (AUC=0.808) has a higher specificity (87.50%) and positive predictive value (90.0%) than any single image finding alone in differential diagnosis between two types of EOCs. The multivariate logistic regression analysis showed that enhancement degrees(OR 0.200, P<0.05),mural nodule(OR 0.158, P<0.05) significantly influence EOC classification. Random forests model identified both as the most important discriminating variables. The diagnostic accuracy of the classifier was 73.53%.

CONCLUSIONS

Differences in imaging characteristics existed between two types of EOCs. Combination of several image findings improved the preoperative diagnostic performance, which is helpful for the clinical treatment and prognosis evaluation.

18F-FDG PET/CT as predictor of tumour biology and prognosis in epithelial ovarian carcinoma

OBJECTIVE

To investigate the relationship between maximum standardised uptake value (SUVmax) of ovarian lesions and histopathology subtypes, and their involvement in the response and prognosis of patients with epithelial ovarian carcinoma (EOC).

MATERIAL AND METHODS

A retrospective analysis of 31 patients with EOC and ¹⁸F-FDG-PET/CT before treatment, including an assessment of the SUVmax of ovarian lesion. Histopathological diagnosis and follow-up was performed. A study was made on the relationship between the SUVmax and histological type (type I and II) and tumour stage, as well as the role of various parameters (SUVmax, histology, stage) on the patient outcomes (complete response [CR], overall survival [OS], disease-free survival [DFS], and disease-free [DF] status, at 12 and 24 months).

RESULTS

The medium SUVmax in type I lesions was lower than in type II (6.3 and 9.3, respectively; P=.03). A 7.1 cut-off was set for SUVmax in order to identify type II EOC (sensitivity: 77.8%, specificity: 69.2%; AUC=0.748; P=.02). No significant relationship was found between tumour stage and SUVmax. CR was more common in early stages; relative risk (RR) of 1.64; P=.003, as well as in type I tumours and a lower SUVmax. Tumour stage was decisive in DFS (P=.04), LE24m (0.07) and OS (P=.08). Longer DFS and a higher percentage of DF 24m were observed in type I tumours (RR: 1.32; P=.26).

CONCLUSIONS

SUVmax was related to EOC histology, so could predict the response and prognosis of these patients. No association was found between glycolytic activity of the primary tumor with the response and prognosis.

VEGF gene polymorphisms and outcome of epithelial ovarian cancer patients

AIM

Since VEGF polymorphisms were associated with variable protein production, we analyzed herein their roles in outcome of epithelial ovarian cancer (EOC) patients.

METHODS

Genotypes of 85 patients with primary EOC were identified in DNA by real-time PCR. Progression-free survival and overall survival were analyzed using Kaplan-Meier method, univariate Cox model and bootstrap resampling study.

RESULTS

At 60 months of follow-up, progression-free survival was shorter in patients with VEGF c.-2578 CC genotype compared with others (52.7 vs 82.2%; p = 0.04). Those patients had 2.15 more chance of presenting disease progression than others (p = 0.04); bootstrap study validated the result (p = 0.03).

CONCLUSION

Our data suggest that VEGF c.-2578C>A polymorphism acts as a prognostic factor in EOC.

Differential role of microRNAs in prognosis, diagnosis, and therapy of ovarian cancer

Ovarian cancer (OC) is the most lethal of malignant gynecological cancers, and has a very poor prognosis, frequently, attributable to late diagnosis and responsiveness to chemotherapy. In spite of the technological and medical approaches over the past four decades, involving the progression of several biological markers (mRNA and proteins biomarkers), the mortality rate of OC remains a challenge due to its late diagnosis, which is expressly ascribed to low specificities and sensitivities. Consequently, there is a crucial need for novel diagnostic and prognostic markers that can advance and initiate more individualized treatment, finally increasing survival of the patients. MiRNAs are non-coding RNAs that control target genes post transcriptionally. They are included in tumorigenesis, apoptosis, proliferation, invasion, metastasis, and chemoresistance. Several studies have within the last decade demonstrated that miRNAs are dysregulated in OC and have possibilities as diagnostic and prognostic biomarkers for OC. Additionally; recent studies have also focused on miRNAs as predictors of chemotherapy sensitivities and their potential as therapeutic targets. In this review, we discuss the current data involving the accumulating evidence of the altered expression of miRNAs in OC, their role in diagnosis, prognosis, and forecast of response to therapy. Given the heterogeneity of this disease, it is likely that advances in long-term survival might be also attained by translating the recent insights of miRNAs participation in OC into new targeted therapies that will have a crucial effect on the management of ovarian cancer.

Association between polymorphisms in xenobiotic detoxification-related genes with prognosis of epithelial ovarian cancer

This study aimed to evaluate whether GSTM1 and GSTT1 (presents or nulls), GSTP1 c.313A>G and NQO2 c.-102A>C polymorphisms, involved in xenobiotic detoxification pathways, alter outcomes of epithelial ovarian cancer (EOC) patients. DNA from 84 EOC patients diagnosed at the University of Campinas Academic Hospital from January 1995 and July 2007 was analyzed by polymerase chain reaction and restriction fragment length polymorphism assays. The prognostic impact of genotypes of polymorphisms on progression-free survival and overall survival (OS) of EOC patients was examined using the Kaplan-Meier probability estimates and univariate and multivariate Cox proportional hazard ratio (HR) regression analyses. The significant results of Cox analyses were validated using a bootstrap resampling study (1000 replications). At 60 months of follow-up, lower OS was seen in patients with GSTT1 null genotype (50.0 vs. 76.7 %, P = 0.02) compared with the other genotype (Kaplan-Meier estimate). This outcome remained the same in univariate Cox analysis (HR 2.22, P = 0.02). After multivariate Cox analysis, patients with GSTT1 null (HR 2.11, P = 0.04, P bootstrap = 0.04) and NQO2 AA (HR 2.13, P = 0.03, P bootstrap = 0.04) genotypes were under greater risks of progressing to death when compared with those with others genotypes. Our data suggest, for the first time, that inherited abnormalities in xenobiotic detoxification pathway related to GSTT1 and NQO2 c.-102A>C polymorphisms act as independent prognostic factors for OS of EOC patients.

Time to diagnosis of Type I or II invasive epithelial ovarian cancers: a multicentre observational study using patient questionnaire and primary care records

OBJECTIVE

To compare time to diagnosis of the typically slow-growing Type I (low-grade serous, low-grade endometrioid, mucinous, clear cell) and the more aggressive Type II (high-grade serous, high-grade endometrioid, undifferentiated, carcinosarcoma) invasive epithelial ovarian cancer (iEOC).

DESIGN

Multicentre observational study.

SETTING

Ten UK gynaecological oncology centres.

POPULATION

Women diagnosed with primary EOC between 2006 and 2008.

METHODS

Symptom data were collected before diagnosis using patient questionnaire and primary-care records. We estimated patient interval (first symptom to presentation) using questionnaire data and diagnostic interval (presentation to diagnosis) using primary-care records. We considered the impact of first symptom, referral and stage on intervals for Type I and Type II iEOC.

MAIN OUTCOME MEASURES

Patient and diagnostic intervals.

RESULTS

In all, 78% of 60 Type I and 21% of 134 Type II iEOC were early-stage. Intervals were comparable and independent of stage [e.g. median patient interval for Type I: early-stage 0.3 months (interquartile range 0.3-3.0) versus late-stage 0.3 months (interquartile range 0.3-4.5), P = 0.8]. Twenty-seven percent of women with Type I and Type II had diagnostic intervals of at least 9 months. First symptom (questionnaire) was also similar, except for the infrequent abnormal bleeding (Type I 15% versus Type II 4%, P = 0.01). More women with Type I disease (57% versus 41%, P = 0.04) had been referred for suspected gynaecological cancer. Median time from referral to diagnosis was 1.4 months for women with iEOC referred via a 2-week cancer referral to any specialty compared with 2.6 months (interquartile range 2.0-3.7) for women who were referred routinely to gynaecology.

CONCLUSION

Overall, shorter diagnostic delays were seen when a cancer was suspected, even if the primary tumour site was not recognised to be ovarian. Despite differences in carcinogenesis and stage for Type I and Type II iEOC, time to diagnosis and symptoms were similar. Referral patterns were different, implying subtle symptom differences. If symptom-based interventions are to impact on ovarian cancer survival, it is likely to be through reduced volume rather than stage-shift. Further research on histological subtypes is needed.

TWEETABLE ABSTRACT

No difference in time to diagnosis for Type I versus Type II invasive epithelial ovarian cancers.

PMS2 expression in epithelial ovarian cancer is posttranslationally regulated by Akt and essential for platinum-induced apoptosis

Epithelial ovarian cancer (EOC) is the most lethal of the gynecologic malignancies, mainly due to the advanced stage at diagnosis and development of cisplatin resistance. The sensitivity of tumor cells to cisplatin is frequently affected by defect in DNA mismatch repair (MMR), which repairs mispaired DNA sequences and regulates DNA-damage-induced apoptosis. However, the role of postmeiotic segregation increased 2 (PMS2), a member of MMR protein family, in cisplatin resistance remains elusive. In the present study, we demonstrated the frequent deficiency of PMS2 and phosphorylation of Akt in EOC cell lines and tissues. Results of complex immunoprecipitation (co-IP) and protein stability assay indicated that activated Akt could directly bind to PMS2 and cause degradation of PMS2 in EOC cells. In addition, functional experiments revealed that PMS2 was required for cisplatin-induced apoptosis and cell cycle arrest in G2/M phase. These findings provide a novel insight into molecular mechanisms linking MMR with chemoresistance and suggest that stabilization of PMS2 expression may be useful in overcoming the cisplatin resistance in EOC.