The serum glycome to discriminate between early-stage epithelial ovarian cancer and benign ovarian diseases.
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ABSTRACT:
SUBMITTER: Biskup K
PROVIDER: S-EPMC4145549 | biostudies-other | 2014
REPOSITORIES: biostudies-other
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Project description:Ovarian cancer is the major cause of death from gynecological cancer and the third most common gynecological malignancy worldwide. Despite a slight improvement in the overall survival of ovarian carcinoma patients in recent decades, the cure rate has not improved. This is mainly due to late diagnosis and resistance to therapy. It is therefore urgent to develop effective methods for early detection and prognosis. We hypothesized that, besides being able to distinguish serum samples of patients with ovarian cancer from those of patients with benign ovarian tumors, 1H-NMR metabolomics analysis might be able to predict the malignant potential of tumors. For this, serum 1H-NMR metabolomics analyses were performed, including patients with malignant, benign and borderline ovarian tumors. The serum metabolic profiles were analyzed by multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) methods. A metabolic profile associated with ovarian malignant tumors was defined, in which lactate, 3-hydroxybutyrate and acetone were increased and acetate, histidine, valine and methanol were decreased. Our data support the use of 1H-NMR metabolomics analysis as a screening method for ovarian cancer detection and might be useful for predicting the malignant potential of borderline tumors.
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Project description:We aimed to determine prognostic factors of early stage (I/II) epithelial ovarian carcinoma (EOC) including clinicopathologic and chemotherapeutic regimens. Four hundred and thirty-seven women who underwent primary staging surgery with adjuvant chemotherapy between January 1, 2000 and December 31, 2010 were retrospectively reviewed and analyzed from two medical centers. The prognostic factors were determined from multivariate survival analyses using Cox regression models. The majority of women were diagnosed with stage Ic (244/437, 55.8%). The histopathologic types were clear cell (37.5%), endometrioid (27.2%), serous (14.0%), and mucinous (13.3%). Fifty-seven percent (249/437) of the women received taxane-based (platinum plus paclitaxel) regimens and 43.0% received non-taxane (platinum plus cyclophosphamide) regimens as frontline adjuvant chemotherapy. Clear cell tumors (adjusted Hazard ratio (aHR) 0.37, 95% confidence interval (CI) 0.21⁻0.73, p = 0.001) showed better 5-year disease-free survival (DFS) than serous tumors. Women diagnosed at FIGO (International Federation of Gynecology and Obstetrics) stage II (aHR 5.97, 95% CI = 2.47⁻14.39, p < 0.001), grade 3 tumor without clear cell (aHR 2.28, 95% CI = 1.02⁻5.07, p = 0.004) and who received 3⁻5 cycles of non-taxane regimens (aHR 3.29, 95% CI = 1.47⁻7.34, p = 0.004) had worse 5-year overall survival (OS). Clear cell histology treated with taxane-based regimens showed significantly higher 5-year DFS (91.2% vs. 82.0%, aHR = 0.45, 95% CI = 0.21⁻0.93, p = 0.043) and 5-year OS (93.5% vs. 79.0%, aHR = 0.30, 95% CI = 0.13⁻0.70, p = 0.005) than those treated with non-taxane-based regimens. We conclude that stage, tumor grade, and chemotherapeutic regimens/cycles are independent prognostic factors for early stage ovarian cancer.
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Project description:Comprehensive serum glycopeptide spectra analysis (CSGSA) evaluates >10,000 serum glycopeptides and identifies unique glycopeptide peaks and patterns via supervised orthogonal partial least-squares discriminant modeling. CSGSA was more accurate than cancer antigen 125 (CA125) or human epididymis protein 4 (HE4) for detecting early stage epithelial ovarian cancer. Combined CSGSA, CA125, and HE4 had improved diagnostic performance. Thus, CSGSA may be a useful screening tool for detecting early stage epithelial ovarian cancer.
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Project description:Epithelial ovarian carcinoma (EOC) is one of the most common gynecologic malignancies with a high mortality rate. Serum biomarkers and imaging approaches are insufficient in identifying EOC patients at an early stage. This study is to set up a combination of proteins from serum small extracellular vesicles (sEVs) for the diagnosis of early-stage EOC and to determine its performance. A biomarker for early-stage ovarian cancer (BESOC) cohort was used as a Chinese multi-center population-based biomarker study and registered as a Chinese Clinical Trial ChiCTR2000040136. The sEV protein levels of CA125, HE4, and C5a were measured in 299 subjects. Logistic regression was exploited to calculate the odds ratio and to create the sEV protein model for the predicted probability and subsequently receiver-operating characteristic (ROC) analysis. The combined sEV marker panel of CA125, HE4, and C5a as a sEV model obtained an area under curve (AUC) of 0.912, which was greater than the serum model (0.809), by ROC analysis to identify EOC patients from the whole cohort. With the cutoff of 0.370, the sensitivity and specificity of the sEV model were 0.80 and 0.89, which were much better performance than the serum markers (sensitivity: 0.55~0.66; specificity: 0.59~0.68) and the risk of ovarian malignancy algorithm (ROMA) index approved by the U.S. Food and Drug Administration (sensitivity: 0.65; specificity: 0.61), to identify EOC patients from patients with benign ovarian diseases or other controls. The sEV levels of CA125 significantly differed among early-stage and late-stage EOC (p < 0.001). Moreover, the AUC of ROC to identify early-stage EOC patients was 0.888. Further investigation revealed that the sEV levels of these 3 proteins significantly decreased after cytoreductive surgery (CA125, p = 0.008; HE4, p = 0.025; C5a, p = 0.044). In summary, our study showed that CA125, HE4, and C5a levels in serum sEVs can identify EOC patients at the early stage, elucidating the possibility of using a sEV model for the diagnosis of early-stage EOC.
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Project description:Carcinoembryonic antigen (CEA) is not only used to aid the diagnosis of lung cancer, but also help monitor recurrence and determine the prognosis of lung cancer as well as evaluate the therapeutic efficacy for lung cancer. However, studies have also shown that CEA is present at low levels in the serum of patients with benign lung diseases (BLD), which will interfere with the accurate judgment of the disease. Due to difference in sample size, detection methods, cutoff values and sources of BLD, the positive rate of CEA in BLD is different with different literature. Therefore, it is necessary to define CEA levels in patients of different BLD in a large sample study. 4796 patients with BLD were included in this study. The results showed that the CEA levels of 3.1% (149/4796) patients with BLD were elevated, with three cases exceeds 20 ng/mL (0.06%, 3/4796). The results from the literature showed that BLD had a mean positive rate of 5.99% (53/885) and only two cases had CEA above 20 ng/mL. The CEA elevations mainly distributed in chronic obstructive pulmonary disease (COPD), pneumonitis and interstitial lung disease and significantly correlated with age of patients (OR 2.69, 95% CI 1.94-3.73, p < 0.001). Pulmonary tuberculosis (7/1311, 0.53%) had the lowest positive rate of CEA elevations while pulmonary alveolar proteinosis (6/27, 22.22%) had the highest positive rate. The majority of patients with abnormally elevated CEA levels had multiple underlying diseases, mainly diseases of the circulatory system (42.28% [63/149]), endocrine diseases (26.85% [40/149]), and respiratory or heart failure (24.16% [36/149]. In endocrine diseases, 87.5% (35/40) of patients had diabetes. In conclusion, CEA is present at a low positive rate in the serum of patients with BLD, but few exceed 20 ng/mL. For lung disease patients, if CEA levels rise, we should carry out comprehensive analysis of types of lung diseases, age of patients, and comorbid diseases.
| S-EPMC8463604 | biostudies-literature
Project description:To examine the trends and survival for women with early-stage epithelial ovarian cancer who underwent adequate lymphadenectomy during surgical treatment.This is a retrospective observational study examining the Surveillance, Epidemiology, End Results program between 1988 and 2013. We evaluated 21,537 cases of stage I-II epithelial ovarian cancer including serous (n=7,466), clear cell (n=6,903), mucinous (n=4,066), and endometrioid (n=3,102) histology. A time-trend analysis of the proportion of patients who underwent adequate pelvic lymphadenectomy (?8 per Gynecologic Oncology Group [GOG] criteria, ?12 per Collaborative Group Report [CGR] criteria for bladder cancer, and >22 per Mayo criteria for endometrial cancer) and a survival analysis associated with adequate pelvic lymphadenectomy were performed.There were significant increases in the proportion of women who underwent adequate lymphadenectomy: GOG criteria 3.6% to 28.6% (1988-2010); CGR criteria 2.4% to 22.4% (1988-2013); and Mayo criteria 0.7% to 9.5% (1988-2013) (all, p<0.05). On multivariable analysis, adequate lymphadenectomy was independently associated with improved cause-specific survival compared to inadequate lymphadenectomy: GOG criteria, adjusted-hazard ratio (HR)=0.75, CGR criteria, adjusted-HR=0.77, and Mayo criteria, adjusted-HR=0.85 (all, p<0.05). Compared to inadequate lymphadenectomy, adequate lymphadenectomy was significantly associated with improved cause-specific survival for serous (HR range=0.67-0.73), endometrioid (HR range=0.59-0.61), and clear cell types (HR range=0.66-0.73) (all, p<0.05) but not in mucinous type (HR range=0.80-0.91; p>0.05).Quality of lymphadenectomy during the surgical treatment for early-stage epithelial ovarian cancer has significantly improved. Adequate lymphadenectomy is associated with a 15%-25% reduction in ovarian cancer mortality compared to inadequate lymphadenectomy.
| S-EPMC6078885 | biostudies-other
Project description:Early-stage epithelial ovarian cancer (eEOC) patients have a generally favorable prognosis but heterogeneous behavior at recurrence. Accurate prediction of the risk of relapse is still a major concern, essentially to avoid overtreatment. We have identified a robust miRNA-based signature named MiROvaR able to predict early disease recurrence in case materials of mostly advanced-stage EOC patients. We challenged MiROvaR in the eEOC sub-setting (stage IA-IIB) and it proved to accurately classify eEOC patients according to their risk of relapse.
2022-12-21 | GSE169314 | GEO
Project description:To increase accuracy of the detection and differential diagnosis of the early epithelial ovarian cancer (EOC) with transvaginal contrast-enhanced ultrasonography (TVCEUS) combining serum human epididymisprotein 4 (HE4), and resistance index (RI). Methods: This retrospectively case-control study of 230 patients with ovarian tumors were reviewed at the Department of Gynecology and Obstetrics, Zhongnan Hospital, Wuhan University, Wuhan, China between June 2008 and September 2015. Before the operation of 110 cases with EOC (Group A) and 120 cases of patients with benign ovarian tumor (Group B), we observe and calculate both Groups' tumor vascular contrast-enhanced ultrasonography morphology scores (U), time-intensity curve (TIC) of contrast-enhanced ultrasonography, HE4, and RI. Results were compared with the histopathological analysis results. Results: The ultrasonography morphology scores, peak intensity (PI) enhancement rate (ER) with the parameters of the TIC and HE4 are higher in Group A compared with patients in Group B and the RI was lower than Group B. The detection rates for all indexes in the benign and malignant groups and their comparisons to the histopathological results were determined. The detection rate differences for HE4 (p=0.001), RI (p=0.001), U (p=0.001), PI (p=0.001), and ER (p=0.001) were all statistically significant (p less than 0.05). Conclusion: The high clinical value through combined TVCEUS, HE4, and RI detection can increase the sensitivity of the diagnosis and differential diagnosis of the early EOC.
| S-EPMC5541181 | biostudies-other
Project description:The aim of the present study was to identify the appropriate DNA sequence and design high-quality primers for methylation-specific polymerase chain reaction (MSP). These primers may be used to examine and identify patients with early-stage epithelial ovarian carcinoma (EOC). Opioid binding protein/cell adhesion molecule like (OPCML), Runt-related transcription factor 3 and tissue factor pathway inhibitor 2 were selected as possible molecular markers. MSP primer sets were designed to monitor the methylation of the three markers. Free circulating DNA (fcDNA) from 194 patients with epithelial ovarian carcinoma and healthy donors were templates in the nested MSP. OPCML MSP was effective with respect to screening methylated fcDNA. One-way ANOVA P-values indicated that the difference in cancer antigen 125 (CA125), a biomarker for EOC diagnosis, level between early EOC and healthy donors was not significant. The methylation of OPCML was significantly altered in early-stage EOC compared with healthy donors (P<0.0001), and this supported the hypothesis that specific fcDNA methylation was able to distinguish patients with early-stage EOC from healthy donors. With respect to detecting early EOC, compared with the results of the CA125 test, MSP increased the κ coefficient from 0.140 to 0.757. Therefore, OPCML combined with fcDNA may be used to establish an improved clinical assay compared with the current CA125 test.
| S-EPMC5494804 | biostudies-other
Project description:BackgroundThis study aimed to identify the diagnostic value of models constructed using computed tomography-based radiomics features for discrimination of benign and early stage malignant ovarian tumors.MethodsThe imaging and clinicopathological data of 197 cases of benign and early stage malignant ovarian tumors (FIGO stage I/II), were retrospectively analyzed. The patients were randomly assigned into training data set and validation data set. Radiomics features were extracted from images of plain computed tomography scan and contrast-enhanced computed tomography scan, were then screened in the training data set, and a radiomics model was constructed. Multivariate logistic regression analysis was used to construct a radiomic nomogram, containing the traditional diagnostic model and the radiomics model. Moreover, the decision curve analysis was used to assess the clinical application value of the radiomics nomogram.ResultsSix textural features with the greatest diagnostic efficiency were finally screened. The value of the area under the receiver operating characteristic curve showed that the radiomics nomogram was superior to the traditional diagnostic model and the radiomics model (P < 0.05) in the training data set. In the validation data set, the radiomics nomogram was superior to the traditional diagnostic model (P < 0.05), but there was no statistically significant difference compared to the radiomics model (P > 0.05). The calibration curve and the Hosmer-Lemeshow test revealed that the three models all had a great degree of fit (All P > 0.05). The results of decision curve analysis indicated that utilization of the radiomics nomogram to distinguish benign and early stage malignant ovarian tumors had a greater clinical application value when the risk threshold was 0.4-1.0.ConclusionsThe computed tomography-based radiomics nomogram could be a non-invasive and reliable imaging method to discriminate benign and early stage malignant ovarian tumors.
| S-EPMC10729460 | biostudies-literature