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Background: The modeled CA-125 elimination constant K (KELIM) is a potential marker of tumor chemosensitivity in ovarian cancer patients treated with neoadjuvant chemotherapy (NACT) before interval surgery. The objective of this study was to externally validate the KELIM (rate of elimination of CA-125) score in patients with high-grade serous ovarian cancer (HGSC) undergoing NACT and explore its relation to the completeness of IDS and survival. Methods: The study was based on a retrospective cohort of 133 patients treated for advanced HGSC, International Federation of Gynecology and Obstetrics (FIGO) stages III–IV, with neoadjuvant chemotherapy, folllowed by interval surgery, in two centres in China. CA-125 concentrations at baseline and during neoadjuvant chemotherapy were collected. We used standardized (std) KELIM for subsequent analysis. Clinicopathologic parameters were collected, and Kaplan‒Meier survival analyses were performed for PFS and OS. Results: KELIM was an independent predictor of the probability of complete surgery and survival in our cohort. The median std KELIM score of patients with complete surgery was significantly higher than that of patients with incomplete IDS (1.20 vs. 0.71, P < 0.001). Multivariate analysis showed that a std KELIM score 0.925 was an independent predictive factor for achieving complete resection (OR = 5.480; 95% CI, 2.409–12.466, P < 0.001) and better PFS (HR = 0.544; 95% CI: 0.349–0.849, P = 0.007) and OS (HR = 0.484; 95% CI: 0.251–0.930, P = 0.030). Conclusions: The tumor-primary tumor chemosensitivity, assessed by the modeled CA-125 KELIM, calculated during NACT, is a major parameter to consider for decision-making regarding IDS attempts and predicting patient survival. [ABSTRACT FROM AUTHOR]

Objectives: Ovarian cancer (OC) can occur at different ages and is affected by a variety of factors. In order to evaluate the risk of cardiovascular mortality in patients with ovarian cancer, we included influencing factors including age, histological type, surgical method, chemotherapy, whether distant metastasis, race and developed a nomogram to evaluate the ability to predict occurrence. At present, we have not found any correlation studies on cardiovascular death events in patients with ovarian cancer. This study was designed to provide targeted measures for effective prevention of cardiovascular death in patients with ovarian cancer. Methods: Kaplan–Meier analysis and multivariable Cox proportional model were performed to evaluate the effectiveness of cardiovascular diseases on overall survival (OS) and ovarian cancer‐specific survival (OCSS). We compared multiple groups including clinical, demographic, therapeutic characteristics and histological types. Cox risk regression analysis, Kaplan–Meier survival curves, and propensity score matching were employed for analyzing the data. Results: A total of 88,653 ovarian cancer patients were collected, of which 2,282 (2.57%) patients died due to cardiovascular-related diseases. Age, chemotherapy and whether satisfactory cytoreduction surgery is still the most important factors affecting the prognosis of ovarian cancer patients, while different histological types, diagnosis time, and race also have a certain impact on the prognosis. The newly developed nomogram model showed excellent predictive performance, with a C-index of 0.759 (95%CI: 0.757–0.761) for the group. Elderly patients with ovarian cancer are still a high-risk group for cardiovascular death [HR: 21.07 (95%CI: 5.21–85.30), p < 0.001]. The calibration curve showed good agreement from predicted survival probabilities to actual observations. Conclusion: This study found that age, histology, surgery, race, chemotherapy, and tumor metastasis are independent prognostic factors for cardiovascular death in patients with ovarian cancer. The nomogram-based model can accurately predict the OS of ovarian cancer patients. It is expected to inform clinical decision-making and help develop targeted treatment strategies for this population. Highlights: • When patients with ovarian cancer are diagnosed, most are at an advanced stage and are diagnosed after menopause. • The nomogram is a powerful prediction model for the occurrence of CVM in elderly patients with ovarian cancer. • The model has good predictive ability and provides personalized treatment for the prevention of CVM in elderly OC patients. [ABSTRACT FROM AUTHOR]

Background: Despite declining mortality in most countries and in Lithuania, ovarian cancer burden has remained high. Studies have indicated that antihypertensive medications use may help to improve ovarian cancer survival, however findings remain controversial. The aim of the study was to analyse the association between post-diagnosis antihypertensive medications intake and cancer-specific survival in ovarian cancer patients. Methods: This retrospective cohort study included 588 ovarian cancer cases diagnosed between 2013 and 2015. Hazard ratios (HR) and corresponding 95% confidence intervals (95%CI) were estimated using multivariable Cox proportional hazards models to assess associations between antihypertensive medications and ovarian cancer-specific mortality. Results: In total, 279 (47%) patients died during the follow-up; 242 (87%) of them died due to ovarian cancer. The risk of ovarian cancer death was reduced in angiotensin-converting enzyme inhibitors (ACE inhibitors) users vs. non-users (HR 0.55, 95% CI: 0.36–0.83). Subgroup analysis showed better ovarian cancer survival in higher dose ACE inhibitors users (HR 0.46, 95% CI: 0.28–0.77, p for trend 0.002); the effect was also stronger in age 51–65 years, stage I–III, surgery or chemotherapy treatment, pre-diagnosis ACE inhibitor users' and pre-diagnosis hypertension subgroups. The risk of cancer-specific death was slightly lower among calcium-channel blocker and angiotensin-receptor blocker users and higher among beta-blocker users as compared to non-users, however chance and confounding could not be ruled out. We found no association between the use of centrally and peripherally acting antiadrenergic agents and diuretics and risk of ovarian cancer-specific mortality. Conclusions: Our findings imply that post-diagnosis use of ACE inhibitors may be associated with reduced ovarian cancer-specific mortality; however, further research is needed for the comprehensive assessment. [ABSTRACT FROM AUTHOR]

Background: Ovarian cancer (OC) is one of the most life-threatening cancers affecting women worldwide. Recent studies have shown that the DNA methylation state can be used in the diagnosis, treatment and prognosis prediction of diseases. Meanwhile, it has been reported that the DNA methylation state can affect the function of immune cells. However, whether DNA methylation-related genes can be used for prognosis and immune response prediction in OC remains unclear. Methods: In this study, DNA methylation-related genes in OC were identified by an integrated analysis of DNA methylation and transcriptome data. Prognostic values of the DNA methylation-related genes were investigated through least absolute shrinkage and selection operator (LASSO) and Cox progression analyses. Immune characteristics were investigated by CIBERSORT, correlation analysis and weighted gene co-expression network analysis (WGCNA). Results: Twelve prognostic genes (CA2, CD3G, HABP2, KCTD14, PI3, SERPINB5, SLAMF7, SLC9A2, STC2, TBP, TREML2 and TRIM27) were identified and a risk score signature and a nomogram based on prognostic genes and clinicopathological features were constructed for the survival prediction of OC patients in the training and two validation cohorts. Subsequently, the differences in the immune landscape between the high- and low-risk score groups were systematically investigated. Conclusions: Taken together, our study explored a novel efficient risk score signature and a nomogram for the survival prediction of OC patients. In addition, the differences of the immune characteristics between the two risk groups were clarified preliminarily, which will guide the further exploration of synergistic targets to improve the efficacy of immunotherapy in OC patients. [ABSTRACT FROM AUTHOR]

Background: The overall survival rate of patients with advanced ovarian cancer (OC) has remained static for several decades. Advanced ovarian cancer is known for its poor prognosis due to extensive metastasis. Epigenetic alterations contribute to tumour progression and therefore are of interest for potential therapeutic strategies. Methods: Following our previous study, we identified that CHD4, a chromatin remodelling factor, plays a strong role in ovarian cancer cell metastasis. We investigated the clinical significance of CHD4 through TCGA and GEO database analyses and explored the effect of CHD4 expression modulation and romidepsin treatment on the biological behaviour of ovarian cancer through CCK-8 and transwell assays. Bioluminescence imaging of tumours in xenografted mice was applied to determine the therapeutic effect of romidepsin. GSEA and western blotting were used to screen the regulatory mechanism of CHD4. Results: In ovarian cancer patient specimens, high CHD4 expression was associated with a poor prognosis. Loss of function of CHD4 in ovarian cancer cells induced suppression of migration and invasion. Mechanistically, CHD4 knockdown suppressed the expression of EZH2 and the nuclear accumulation of β-catenin. CHD4 also suppressed the metastasis of ovarian cancer cells and prevented disease progression in a mouse model. To inhibit the functions of CHD4 that are mediated by histone deacetylase, we evaluated the effect of the HDAC1/2 selective inhibitor romidepsin. Our findings indicated that treatment with romidepsin suppressed the progression of metastases in vitro and in vivo. Conclusions: Collectively, our results uncovered an oncogenic function of CHD4 in ovarian cancer and provide a rationale for clinical trials of romidepsin in ovarian cancer patients. [ABSTRACT FROM AUTHOR]

Background: Ovarian cancer (OVC) is a devastating disease worldwide; therefore the identification of prognostic biomarkers is urgently needed. We aimed to determine a robust microRNA signature-based risk score system that could predict the overall survival (OS) of patients with OVC. Methods: We extracted the microRNA expression profiles and corresponding clinical data of 467 OVC patients from The Cancer Genome Atlas (TCGA) database and further divided this data into training, validation and complete cohorts. The key prognostic microRNAs for OVC were identified and evaluated by robust likelihood-based survival analysis (RLSA) and multivariable Cox regression. Time-dependent receiver operating characteristic (ROC) curves were then constructed to evaluate the prognostic performance of these microRNAs. A total of 172 ovarian cancer samples and 162 normal ovarian tissues were used to verify the credibility and accuracy of the selected markers of the TCGA cohort by quantitative real-time polymerase chain reaction (PCR). Results: We successfully established a risk score system based on a six-microRNA signature (hsa-miR-3074-5p, hsa-miR-758-3p, hsa-miR-877-5p, hsa-miR-760, hsa-miR-342-5p, and hsa-miR-6509-5p). This microRNA based system is able to characterize patients as either high or low risk. The OS of OVC patients, with either high or low risk, was significantly different when compared in the training cohort (p < 0.001), the validation cohort (p < 0.001) and the complete cohort (p < 0.001). Analysis of clinical samples further demonstrated that these microRNAs were aberrantly expressed in OVC tissues. The six-miRNA-based signature was correlated with the prognosis of OVC patients (p < 0.001). Conclusions: The study established a novel risk score system that is predictive of patient prognosis and is a potentially useful guide for the personalized treatment of OVC patients. [ABSTRACT FROM AUTHOR]

Background: Lymphovascular space invasion (LVSI) is the first step of hematogenous metastasis. Exploration of the differential miRNA expression profiles between LVSI-positive and LVSI-negative ovarian cancer tissues may help to identify key miRNAs involved in the hematogenous metastasis of ovarian cancer. This study is aimed to identify microRNAs (miRNAs) that are differentially expressed between LVSI-positive and LVSI-negative ovarian cancer tissues, followed by exploring their association with bevacizumab response in ovarian cancer patients. Methods: The Cancer Genome Altas (TGGA) dataset was used to identify the differentially expressed miRNAs between LVSI-positive and LVSI-negative ovarian cancer tissues. The prognostic value of the differentially expressed miRNAs was determined using GSE140082 dataset. Results: We showed that miR-25 and miR-142 were differentially expressed between LVSI-positive and LVSI-negative ovarian cancer tumors. Kaplan-Meier analysis indicated that high miR-25 expression was associated with increased progression free survival (PFS) and extended overall survival (OS). Moreover, patients with low miR-25 expression benefited significantly from bevacizumab treatment in terms of PFS. A similar trend was observed in terms of OS though without reaching statistical significance. In contrast, no significant survival benefits from bevacizumab were observed in patients with high miR-25 expression in terms of PFS and OS. There was no significant correlation between miR-142 expression and PFS. In contrast, high miR-142 expression was associated with reduced OS. Moreover, patients with high miR-142 expression benefited significantly from bevacizumab treatment in terms of PFS and OS. However, bevacizumab treatment conferred no significant improvements in both PFS and OS in patients with low miR-142 expression. The nomogram for PFS indicated that miR-25 expression had a larger contribution to PFS than debulking status and bevacizumab treatment. And the nomogram for OS illustrated both miR-25 expression and miR-142 expression as sharing a larger contribution to OS than bevacizumab treatment and debulking status. Conclusion: In conclusion, miR-25 expression correlates with a better PFS and OS in ovarian cancer. Patients with low miR-25 expression and high miR-142 expression could benefit from bevacizumab treatment significantly. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to analyze prognostic factors for ovarian metastases (OM) in colorectal cancer (CRC) using data from a Chinese center. In addition, the study aimed at developing a new clinical scoring system for prognosis of OM of CRC patients after surgery. Patients and methods: Data of CRC patients with OM were collected from a single Chinese institution (n = 67). Kaplan-Meier analysis was used to evaluate cumulative survival of patients. Factors associated with prognosis of overall survival (OS) were explored using Cox's proportional hazard regression models. A scoring system to determine effectiveness of prognosis was developed. Results: Median OS values for patients with or without surgery were 22 and 7 months, respectively. Size of OM, number of OM, peritoneal metastasis (PM), Peritoneal cancer index (PCI), and completeness of cytoreduction (CC) were associated with OS of patients through univariate analysis. Multivariate analysis using a Cox regression model showed that only CC was an independent predictor for OS. Three variables (the size of OM >15cm, PCI ≥ 10, and carcinoembryonic antigen (CEA) >30 ng/mL) assigned one point each were used to develop a risk score. The resulting score was used for prognosis of OS. Conclusion: Surgical treatment of metastatic sites is effective and safe for CRC patients with OM. CC-0 is recommended for improved prognosis. The scoring system developed in this study is effective for prediction of OS of patients after surgery. [ABSTRACT FROM AUTHOR]

Background: Both N6-methyladenosine (m6A) modification and lncRNAs play an important role in the carcinogenesis and cancer inhibition of ovarian cancer (OC). However, lncRNAs involved in m6A regulation (LI-m6As) have never been reported in OC. Herein, we aimed to identify and validate a signature based on LI-m6A for OC. Methods: RNA sequencing profiles with corresponding clinical information associated with OC and 23 m6A regulators were extracted from TCGA. The Pearson correlation coefficient (PCC) between lncRNAs and 23 m6A regulators (|PCC|> 0.4 and p < 0.01) was calculated to identify LI-m6As. The LI-m6As with significant prognostic value were screened based on univariate Cox regression analysis to construct a risk model by LASSO Cox regression. Gene Set Enrichment Analysis (GSEA) was implemented to survey the biological functions of the risk groups. Several clinicopathological characteristics were utilized to evaluate their ability to predict prognosis, and a nomogram was constructed to evaluate the accuracy of survival prediction. Besides, immune microenvironment, checkpoint, and drug sensitivity in the two risk groups were compared using comprehensive algorithms. Finally, real-time qPCR analysis and cell counting kit-8 assays were performed on an alternative lncRNA, CACNA1G-AS1. Results: The training cohort involving 258 OC patients and the validation cohort involving 111 OC patients were downloaded from TCGA. According to the PCC between the m6A regulators and lncRNAs, 129 LI-m6As were obtained to perform univariate Cox regression analysis and then 10 significant prognostic LI-m6As were identified. A prognostic signature containing four LI-m6As (AC010894.3, ACAP2-IT1, CACNA1G-AS1, and UBA6-AS1) was constructed according to the LASSO Cox regression analysis of the 10 LI-m6As. The prognostic signature was validated to show completely opposite prognostic value in the two risk groups and adverse overall survival (OS) in several clinicopathological characteristics. GSEA indicated that differentially expressed genes in disparate risk groups were enriched in several tumor-related pathways. At the same time, we found significant differences in some immune cells and chemotherapeutic agents between the two groups. An alternative lncRNA, CACNA1G-AS1, was proven to be upregulated in 30 OC specimens and 3 OC cell lines relative to control. Furthermore, knockdown of CACNA1G‐AS1 was proven to restrain the multiplication capacity of OC cells. Conclusions: Based on the four LI-m6As (AC010894.3, ACAP2-IT1, CACNA1G-AS1, and UBA6-AS1), the risk model we identified can independently predict the OS and therapeutic value of OC. CACNA1G‐AS1 was preliminarily proved to be a malignant lncRNA. [ABSTRACT FROM AUTHOR]

Background: The proline-rich protein 11 (PRR11) is a newly identified oncogene associated with a poor prognosis in several human cancers. Nonetheless, research on its role in ovarian cancer (OC) remains largely understudied. Therefore, this study aims to evaluate the expression levels of PRR11 protein and its role in human ovarian cancer. Methods: Immunohistochemistry analysis was used to evaluate the expression levels of PRR11 protein in human samples obtained from 49 patients diagnosed with OC and subjected to curative surgery in the First Affiliated Hospital of Wenzhou Medical University between 2007 and 2015. Results: In total, 57.1% of the primary OC tumor tissue evaluated demonstrated overexpression of PRR11. Meanwhile, the survival analysis showed that the overall survival (OS) of patients presenting overexpression of PRR11 was significantly lower than the OS of the patients with negative PRR11. In subsequent experiments, it was found that silencing the expression of PRR11 expression inhibited the proliferation of tumor cells and the migration of cells in vitro. Further, cells subjected to PRR11 knockdown exhibited a decrease in tumor growth in vivo. The downregulation of PRR11 was coupled with a decrease in N-cadherin and downregulation in the expression of early growth response protein 1 (EGR1). Conclusions: The findings suggest that PRR11 might be considered as a potential target for prognostic assessment and gene therapy strategies for patients diagnosed with OC. [ABSTRACT FROM AUTHOR]

Background: In clinical practice alterations in CA-125 concentration within normal range in patients with ovarian cancer after first-line treatment are common. Even minor increase in CA-125 concentration is associated with patients' anxiety and difficult interpretation and counselling for clinicians. The aim of this study was to evaluate the significance of CA-125 fluctuations within reference level in patients who suffered from ovarian cancer with complete response after first-line treatment. Results: 168 patients with epithelial ovarian cancer, who achieved complete remission after first line treatment were enrolled in the study. CA-125 concentration assessment was carried out during follow up visits. The recurrence of the disease was diagnosed on the first appearance of symptoms: clinical, radiological or histopathological/cytological. PFS and 5-year survival rate was calculated with Kaplan-Meier plots. Statistical analysis was performed with SAS / STAT® 9.4 / 14.4, SAS Institute Inc., Cary, NC, USA, 2017. Median concentration of CA-125 after first-line therapy was 10 U/ml. Increasing CA-125 concentration by > 5 U/ml, 3 and 6 months after the treatment was associated with higher risk of relapse (HR = 7.6, p < 0.0001 and HR = 5.29, p < 0.0001 respectively). 5-year survival rate was significantly lower in patients with increased CA-125 by 5 U/ml, 3 and 6 months after therapy (56.79% vs 0 and 50.62% vs 15.55%). Conclusions: Increased concentration of CA-125 by > 5 U/ml within normal range, 3 and 6 months after treatment was unfavorable prognostic factor in ovarian cancer patients with complete response to primary therapy. [ABSTRACT FROM AUTHOR]