Long-Term Survival Among Histological Subtypes in Advanced Epithelial Ovarian Cancer: Population-Based Study Using the Surveillance, Epidemiology, and End Results Database

Implication of fibroblast growth factor 7 in ovarian cancer metastases and patient survival

Background/Objectives

Patients with ovarian cancer commonly experience metastases and recurrences, which contribute to high mortality. Our objective was to better understand ovarian cancer metastasis and identify candidate biomarkers and drug targets for predicting and preventing ovarian cancer recurrence.

Methods

Transcripts of 770 cancer-associated genes were compared in cells collected from ascitic fluid versus resected tumors of an ES-2 orthotopic ovarian cancer mouse model. Associated cell types and pathways were explored with bioinformatics. FGF7 protein was measured using capillary-based immunoassays or ELISA in mouse and clinical specimens. Significances of differential gene expression and patient prognosis were determined by volcano plot and log-rank test, respectively.

Results

Tumor transcriptomes exhibited higher endothelial cells, oxygenation, proteasome activity, and metabolism in comparison to ascites, but similar percentages of cancer-associated fibroblasts and immune cells. FGF7 mRNA was significantly higher in mouse tumors compared to ascites. FGF7 protein was significantly higher in tumors than in ascites in independent mouse models and clinical specimens. Serum FGF7 protein levels above the median of 25 patients with ovarian cancer were associated with worse progression-free and overall survival (p = 0.005 and 0.019, respectively) independent of patient and tumor characteristics.

Conclusions

In comparison to ascites, tumors exhibit different transcriptomic profiles that identify candidate biomarkers and drug targets for predicting and preventing recurrence. Among these, elevated tumoral FGF7 validated at the protein level and elevated serum FGF7 were significantly associated with worse patient survival. These results support further development of FGF7 receptor-targeted drugs and serum FGF7 to prevent and predict recurrence, respectively.

Proactive assessment of patient reported outcomes in ovarian cancer studies: a systematic review and call for action in future studies

OBJECTIVE

This systematic review aims to evaluate the proactive or real-time assessment of patient reported outcomes in studies involving patients with ovarian cancer undergoing systemic therapy.

METHODS

PubMed, Embase, and Cochrane databases were searched (from database inception until February 2022), and prospective ovarian cancer studies (experimental or observational) that incorporated patient reported outcomes, including quality of life, were included. The primary objective was to assess the ratio of studies incorporating real-time use of patient reported outcomes among those studies performing patient reported outcomes. A secondary objective was to describe the patient reported outcome reporting. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 checklist was followed. Descriptive statistics were used.

RESULTS

3071 articles were screened, with 117 included in the final analysis. Studies were published between 1990 and 2022, and consisted of 35 735 patients (median 140 patients per study; interquartile range 58-415). Median time from patient enrollment initiation to study publication was 7 years (range 1-15). Most studies were experimental/clinical trials (n=93, 79%) followed by observational (n=23, 20%). Therapeutic strategies were assessed in 98% (91/93) of experimental studies, most frequently chemotherapy (n=53, 58%), followed by antiangiogenics or poly-ADP ribose polymerase (PARP) inhibitors (n=8, 9%, each). Patient reported outcomes were the primary endpoint in 7.5% (7/93) and 83% (19/23) of experimental and observational studies, respectively. The ratio of real-time patient reported outcomes assessment/evaluation was 0.9% (1/117).

CONCLUSIONS

Completion of patient reported outcome questionnaires involves time and effort for patients with ovarian cancer. Responses to these questionnaires were only assessed in real time in <1% of analyzed studies. Efforts should be made to incorporate proactive assessment of patient reported outcomes to optimize patient care and safety.

Causal Effects of Valine on Ovarian Cancer: A Bidirectional Mendelian Randomization Analysis

BACKGROUND

Ovarian cancer is a lethal female cancer with a rising incidence that is often diagnosed late due to a lack of symptoms, affecting survival and quality of life. Studies suggest that dietary factors, especially the levels of branched-chain amino acids such as valine, may influence its development. While valine is essential for metabolism, its specific role in ovarian cancer remains unclear, necessitating further research.

METHODS

This study aimed to elucidate the causal relationship between valine and OC through a bidirectional Mendelian randomization (MR) approach. Data were sourced from the IEU OpenGWAS project, encompassing genome-wide association statistics for valine (N = 115,048) and OC (Ncase = 1,218, Ncontrol = 198,523) among European participants. Independent genetic variants associated with each phenotype at genome-wide significance were employed as instrumental variables (IVs). The primary analysis utilized the inverse variance weighted (IVW) method for two-sample MR analysis. MR‒Egger regression was applied to adjust for potential pleiotropy, whereas the weighted median method provided robust causal estimates under the assumption of valid IVs. Sensitivity analyses, including leave-one-out (LOO) analysis, heterogeneity tests, and horizontal pleiotropy assessments, were conducted to ensure the robustness of the findings.

RESULTS

The results revealed a significant causal relationship between valine and OC, identifying valine as a risk factor for OC (p = 0.043, 95% CI = 1.00008-1.00491, OR = 1.00249) in the forward MR analysis. Sensitivity analyses confirmed the absence of heterogeneity (Q_p value >0.05) and horizontal pleiotropy (p > 0.05), and LOO analysis validated the stability of the results. Conversely, reverse MR analysis revealed no causal effect of OC on valine levels (p = 0.875, 95% CI = 0.34125-2.51495, OR = 1.08528).

CONCLUSIONS

These findings reveal a causal link between high valine levels and an increased OC risk. This research highlights the monitoring of valine levels as a preventive strategy and the significance of valine metabolism in OC. Future studies are needed to investigate the mechanisms and interventions for reducing risk, offering insights for clinical practice and public health initiatives in OC prevention.

VERU-111, an orally available tubulin inhibitor, suppresses ovarian tumor growth and metastasis

Ovarian cancer is the most lethal gynecological malignancy, with a 5-year survival rate of approximately 50%. The dismal prognosis is due in part to metastatic disease and acquired drug resistance to conventional chemotherapies such as taxanes. Colchicine binding site inhibitors (CBSIs) are attractive alternatives to taxanes because they could potentially achieve oral bioavailability and overcome drug resistance associated with the prolonged use of taxanes. VERU-111 is one of the most advanced CBSIs that is orally available, potent, and well tolerated and has shown good efficacy in several preclinical solid tumor models. Here, we demonstrate for the first time the in vitro potency of VERU-111 as well as its efficacy at inhibiting tumor growth and metastasis in an orthotopic ovarian cancer mouse model. VERU-111 has nanomolar potency against ovarian cancer cell lines and strongly inhibits colony formation, proliferation, invasion, and migration. VERU-111 disrupts microtubule formation to induce mitotic catastrophe and ultimately apoptosis in a concentration-dependent manner. The efficacy of VERU-111 was comparable with standard chemotherapy paclitaxel, the current first-line treatment of ovarian cancer, with no observed synergy with combination paclitaxel + VERU-111 treatment. In vivo, VERU-111 markedly suppressed ovarian tumor growth and completely suppressed distant organ metastasis. Together, these results support VERU-111 for its potential as a novel therapy for ovarian cancer, particularly for late-stage metastatic disease. SIGNIFICANCE STATEMENT: VERU-111 is an investigational new drug and has comparable efficacy as paclitaxel in suppressing tumor cell proliferation, colony formation, and migration in ovarian cancer models in vitro and has potent in vivo antitumor and antimetastatic activity in an orthotopic ovarian cancer mouse model. VERU-111 has low systemic toxicity and, unlike paclitaxel, is orally bioavailable and is not a substrate for the major drug efflux transporters, making it a promising and attractive alternative to taxane-based therapy.

Computational pathology: A survey review and the way forward

Computational Pathology (CPath) is an interdisciplinary science that augments developments of computational approaches to analyze and model medical histopathology images. The main objective for CPath is to develop infrastructure and workflows of digital diagnostics as an assistive CAD system for clinical pathology, facilitating transformational changes in the diagnosis and treatment of cancer that are mainly address by CPath tools. With evergrowing developments in deep learning and computer vision algorithms, and the ease of the data flow from digital pathology, currently CPath is witnessing a paradigm shift. Despite the sheer volume of engineering and scientific works being introduced for cancer image analysis, there is still a considerable gap of adopting and integrating these algorithms in clinical practice. This raises a significant question regarding the direction and trends that are undertaken in CPath. In this article we provide a comprehensive review of more than 800 papers to address the challenges faced in problem design all-the-way to the application and implementation viewpoints. We have catalogued each paper into a model-card by examining the key works and challenges faced to layout the current landscape in CPath. We hope this helps the community to locate relevant works and facilitate understanding of the field's future directions. In a nutshell, we oversee the CPath developments in cycle of stages which are required to be cohesively linked together to address the challenges associated with such multidisciplinary science. We overview this cycle from different perspectives of data-centric, model-centric, and application-centric problems. We finally sketch remaining challenges and provide directions for future technical developments and clinical integration of CPath. For updated information on this survey review paper and accessing to the original model cards repository, please refer to GitHub. Updated version of this draft can also be found from arXiv.

The impact of inter-cycle treatment delays on overall survival in patients with advanced-stage ovarian cancer

INTRODUCTION

Chemotherapy forms the cornerstone of systemic treatment for advanced ovarian cancer, extending overall survival; however, drug-related toxicity can lead to treatment delays, potentially diminishing treatment efficacy. This study evaluated the impact of treatment delays on all-cause mortality of patients with ovarian cancer, to better inform decisions on patient management.

METHODS

This retrospective, population-based cohort study included 1517 women with advanced-stage ovarian cancer, receiving first-line adjuvant or neoadjuvant chemotherapy in 2014 and 2015. The frequency of inter-cycle delays >7 days was calculated using drug administration dates. Kaplan-Meier estimates were used to compare 2-year overall survival (OS) between patients who were delayed and those treated to schedule. Cox proportional hazards regression was used to investigate the impact of treatment delay on all-cause mortality. Inverse probability of treatment weighting propensity scores were used to adjust for confounding variables.

RESULTS

Delays >7 days occurred in 35.3% of patients. Two-year OS probability was 62.7% in patients who experienced treatment delays >7 days (95% CI, 58.7-66.9) compared to 69.1% in those treated to schedule (95% CI, 66.2-72.0). Delays were not significantly associated with all-cause mortality when adjusted for confounders (HR 1.00 95% CI, 0.83-1.20, P = .9).

CONCLUSIONS

Delays to chemotherapy treatment were not significantly associated with worsened survival in patients with advanced-stage ovarian cancer. These results can inform clinical decision making that prioritize toxicity management and quality of life for those treated with chemotherapy.

Investigating age and ethnicity as novel high-risk phenotypes in mucinous ovarian cancer: retrospective study in a multi-ethnic population

OBJECTIVES

Primary mucinous ovarian carcinoma represents 3% of ovarian cancers and is typically diagnosed early, yielding favorable outcomes. This study aims to identify risk factors, focussing on the impact of age and ethnicity on survival from primary mucinous ovarian cancer.

METHODS

A retrospective observational study of patients treated at Sandwell and West Birmingham Hospitals NHS Trust and University Hospital Coventry and Warwickshire. Patients included were women aged ≥16 years, with primary mucinous ovarian cancer confirmed by specialist gynecological histopathologist and tumor immunohistochemistry, including cytokeratin-7, cytokeratin-20, and CDX2. Statistical analyses were performed using R integrated development environment, with survival assessed by Cox proportional hazards models and Kaplan-Meier plots.

RESULTS

A total of 163 patients were analyzed; median age at diagnosis was 58 years (range 16-92), 145 (89%) were International Federation of Gynecology and Obstetrics stage I and 43 (26%) patients had infiltrative invasion. Women aged ≤45 years were more likely to have infiltrative invasion (RR=1.38, 95% CI 0.78 to 2.46), with increased risk of death associated with infiltrative invasion (HR=2.29, 95% CI 1.37 to 5.83). Compared with White counterparts, South Asian women were more likely to undergo fertility-sparing surgery (RR=3.52, 95% CI 1.48 to 8.32), and have infiltrative invasion (RR=1.25, 95% CI 0.60 to 2.58). South Asian women undergoing fertility-sparing surgery had worse prognosis than those undergoing traditional staging surgery (HR=2.20, 95% CI 0.39 to 13.14). In FIGO stage I disease, 59% South Asian and 37% White women received adjuvant chemotherapy (p=0.06). South Asian women exhibited a worse overall prognosis than White women (HR=2.07, 95% CI 0.86 to 4.36), particularly pronounced in those aged ≤45 years (HR=8.75, 95% CI 1.22 to 76.38).

CONCLUSION

This study identified young age as a risk factor for diagnosis of infiltrative invasion. Fertility-sparing surgery in South Asian women is a risk factor for poorer prognosis. South Asian women exhibit poorer overall survival than their White counterparts.

Selective targeting of IRAK1 attenuates low molecular weight hyaluronic acid-induced stemness and non-canonical STAT3 activation in epithelial ovarian cancer

Advanced epithelial ovarian cancer (EOC) survival rates are dishearteningly low, with ~25% surviving beyond 5 years. Evidence suggests that cancer stem cells contribute to acquired chemoresistance and tumor recurrence. Here, we show that IRAK1 is upregulated in EOC tissues, and enhanced expression correlates with poorer overall survival. Moreover, low molecular weight hyaluronic acid, which is abundant in malignant ascites from patients with advanced EOC, induced IRAK1 phosphorylation leading to STAT3 activation and enhanced spheroid formation. Knockdown of IRAK1 impaired tumor growth in peritoneal disease models, and impaired HA-induced spheroid growth and STAT3 phosphorylation. Finally, we determined that TCS2210, a known inducer of neuronal differentiation in mesenchymal stem cells, is a selective inhibitor of IRAK1. TCS2210 significantly inhibited EOC growth in vitro and in vivo both as monotherapy, and in combination with cisplatin. Collectively, these data demonstrate IRAK1 as a druggable target for EOC.

Global Incidence of Ovarian Cancer According to Histologic Subtype: A Population-Based Cancer Registry Study

PURPOSE

Ovarian cancer can be categorized into distinct histologic subtypes with varying identifiable risk factors, molecular composition, clinical features, and treatment. The global incidence of ovarian cancer subtypes remains limited, especially in low- and middle-income countries (LMICs) without high-quality cancer registry systems.

MATERIALS AND METHODS

We used data from population-based cancer registries of the Cancer Incidence in Five Continents project to calculate the proportions of serous, mucinous, endometrioid, clear cell, and other histologic subtypes of ovarian cancer. Proportions were applied to the estimated numbers of patients with ovarian cancer from Global Cancer Observatory 2020. Age-standardized incidence rates were calculated.

RESULTS

Globally, an estimated 133,818 new patients of serous cancer, 35,712 new patients of mucinous cancer, 29,319 new patients of endometrioid cancer, and 17,894 new patients of clear cell cancer were identified in 2020. The distribution of ovarian cancer histologic subtypes exhibited regional variation. Eastern Europe had the highest rate of serous and mucinous carcinomas, whereas Northern Africa and Eastern Asia had the highest burden of endometrioid and clear cell carcinomas, respectively.

CONCLUSION

This study provides a global incidence landscape of histologic subtypes of ovarian cancer, particularly in LMICs lacking comprehensive registry systems. Our analysis offers valuable insights into disease burden and guidance for tailored strategies for prevention of ovarian cancer.

Prognostic Factors and a Predictive Nomogram of Cancer-Specific Survival of Epithelial Ovarian Cancer Patients with Pelvic Exenteration Treatment

Objective

The aim of this study was to explore prognostic factors, develop and internally validate a prognostic nomogram model, and predict the cancer-specific survival (CCS) of epithelial ovarian cancer (EOC) patients with pelvic exenteration (PE) treatment.

Methods

A total of 454 EOC patients from the Surveillance, Epidemiology, and End Results (SEER) database were collected according to the inclusion criteria and randomly divided into the training (n = 317) and validation (n = 137) cohorts. Prognostic factors of EOC patients with PE treatment were explored by univariate and multivariate stepwise Cox regression analyses. A predictive nomogram was constructed based on selected risk factors. The predictive power of the constructed nomogram was assessed by the time-dependent receiver operating characteristic (ROC) curve. Kaplan-Meier (KM) curve stratified by patients' nomoscore was also plotted to assess the risk stratification of the established nomogram. In internal validation, the C index, calibration curve, and decision curve analysis (DCA) were employed to assess the discrimination, calibration, and clinical utility of the models, respectively.

Results

In the training cohort, age, histological type, Federation of Gynecology and Obstetrics (FIGO) stage, number of examined lymph nodes, and number of positive lymph nodes were found to be independent prognostic factors of postoperative CSS. A practical nomogram model of EOC patients with PE treatment was constructed based on these selected risk factors. Time-dependent ROC curves and KM curves showed the superior predictive capability and excellent clinical stratification of the nomogram in both training and validation cohorts. In the internal validation, the C index, calibration plots, and DCA in the training and validation cohorts confirmed that the nomogram presents a high level of prediction accuracy and clinical applicability.

Conclusion

Our nomogram exhibited satisfactory survival prediction and prognostic discrimination. It is a user-friendly tool with high clinical pragmatism for estimating prognosis and guiding the long-term management of EOC patients with PE treatment.

Overall survival prediction models for gynecological endometrioid adenocarcinoma with squamous differentiation (GE-ASqD) using machine-learning algorithms

The actual 5-year survival rates for Gynecological Endometrioid Adenocarcinoma with Squamous Differentiation (GE-ASqD) are rarely reported. The purpose of this study was to evaluate how histological subtypes affected long-term survivors of GE-ASqD (> 5 years). We conducted a retrospective analysis of patients diagnosed GE-ASqD from the Surveillance, Epidemiology, and End Results database (2004-2015). In order to conduct the studies, we employed the chi-square test, univariate cox regression, and multivariate cox proportional hazards model. A total of 1131 patients with GE-ASqD were included in the survival study from 2004 to 2015 after applying the inclusion and exclusion criteria and the sample randomly split into a training set and a test set at a ratio of 7:3. Five machine learning algorithms were trained based on nine clinical variables to predict the 5-year overall survival. The AUC of the training group for the LR, Decision Tree, forest, Gbdt, and gbm algorithms were 0.809, 0.336, 0.841, 0.823, and 0.856 respectively. The AUC of the testing group was 0.779, 0.738, 0.753, 0.767 and 0.734, respectively. The calibration curves confirmed good performance of the five machine learning algorithms. Finally, five algorithms were combined to create a machine learning model that forecasts the 5-year overall survival rate of patients with GE-ASqD.

A cross-sectional study of the association between heavy metals and pan-cancers associated with sex hormones in NHANES 1999-2018

Given the complexity of tumorigenesis, numerous studies have also shown that excessive exposure to heavy metals increases the risk of cancers and disrupts the secretion of sex hormones. However, the specific effects of heavy metals on cancers remain to be proven. To confirm the association between heavy metals and pan-cancer sex hormone levels among adults, 94,337 individuals from the National Health and Nutrition Examination Survey were assessed. We examined the associations between pan-cancers associated with sex hormones (ovarian, testicular, breast, and prostate cancers) and heavy metals in blood/urine. The methods (the WQS (weighted quantile sums) and SVYGLM (survey generalized linear model) regressions) were used to evaluate the association between sex hormone-related cancers and each metal category by incorporating covariates. To evaluate the overall effect of heavy metals and detect the dose-response relationship between the prevalence of pan-cancers associated with sex hormones and heavy metals, RCS (restricted cubic splines) were applied. Environmental exposure to heavy metals may be associated with pan-cancers associated with sex hormones in adults in the USA. Prostate cancer was inversely associated with blood cadmium while positively associated with blood lead, urinary tin, and thallium. Breast cancer was inversely associated with blood lead. Ovarian cancer was positively associated with blood cadmium. We also found a non-linear dose-response relationship between pan-cancers associated with sex hormones and heavy metals, which was non-parametric, using RCS models. The OR for breast cancer decreased along with the increase in lead concentration under approximately 20 µg/dl, while the OR for prostate cancer increased between urine thallium levels of approximately 0.17-1.1 ng/ml. Pan-cancers associated with sex hormones are associated with exposure to heavy metals. Considering the design of the NHANES study, further studies need to be conducted on other nationally representative surveys.

What proportion of patients with stage 3 ovarian cancer are potentially cured following intraperitoneal chemotherapy? Analysis of the long term (≥10 years) survivors in NRG/GOG randomized clinical trials of intraperitoneal and intravenous chemotherapy in stage III ovarian cancer

OBJECTIVE

Patients with advanced epithelial ovarian cancer (EOC) alive without progression at a landmark time-point of 10 years from diagnosis are likely cured. We report the proportion of patients with Stage III EOC who were long-term disease-free survivors (LTDFS≥10 years) following either intraperitoneal (IP) or intravenous (IV) chemotherapy as well as the predictors of LTDFS.

METHODS

Data from 3 mature NRG/GOG trials (104, 114, 172) were analyzed and included demographics, clinicopathologic details, route of administration, and survival outcomes of patients living ≥10 years assessed according to the Kaplan-Meier method. Cox regression survival analysis was performed to evaluate independent prognostic predictors of LTDFS.

RESULTS

Of 1174 patients randomized, 10-year overall survival (OS) was 26% (95% CI, 23-28%) and LTDFS ≥10 years was 18% (95% CI, 16-20%). Patients with LTDFS ≥10 years had a median age of 54.6 years (p < 0.001). Younger age (p < 0.001) was the only independent prognostic factor for LTDFS≥10 years on multivariate Cox analysis.

CONCLUSIONS

Approximately 18% of patients were LTDFS ≥10 years. They form the tail end of the survival curve and are likely cured. Our results provide a comparative benchmark to evaluate the impact of PARP inhibitors in 1st line maintenance trials on survival outcomes.

Prognostic implications of PPL expression in ovarian cancer

Periplakin (PPL) is a main member in plakin family, which plays important role in cellular adhesion complexes supporting and cytoskeletal integrity supplying. PPL was reported to be a potential biomarker candidate for several types of cancers. However, the biological functions and underlying mechanisms of PPL in ovarian cancer (OV) remain unclear. In the present study, we used GEPIA 2, Human Protein Atlas, Oncomine, LinkedOmics, Kaplan-Meier Plotter, STRING, CytoHubba plug-in and TIMER to determine the associations among PPL expression, prognosis, and immune cell infiltration in OV. RT-qPCR and IHC analysis were conducted to validated the role of PPL in an independent OV cohort. Compared with the normal ovary tissues, the levels of PPL mRNA and protein expression were both obviously higher in OV tumors from multiple datasets (P < 0.05), and a poor survival was observed to be strongly correlated with high PPL expression (P < 0.05). Moreover, the results were further validated by RT-qPCR and IHC analysis in an independent OV cohort. A gene-clinical nomogram was constructed, including PPL mRNA expression and clinical factors in TCGA. Functional network analysis suggested that PPL participates in the important pathways like Wnt signaling pathway, MAPK signaling pathway. Ten hub genes (LAMC2, PXN, LAMA3, LAMB3, LAMA5, ITGA3, TLN1, ACTN4, ACTN1, and ITGB4) were identified to be positively associated with PPL. Furthermore, PPL expression was negatively correlated with infiltrating levels of CD4+ T cell, macrophages, neutrophils, and dendritic cells. In conclusion, PPL may be an unfavorable prognostic biomarker candidate in OV, which was also correlated with immune infiltrating and function in immunotherapy response.