Elevated Interleukin-6 Levels in the Circulation and Peritoneal Fluid of Patients with Ovarian Cancer as a Potential Diagnostic Biomarker: A Systematic Review and Meta-Analysis

Ovarian cancer (OC) is one of the most lethal cancers, largely due to a late diagnosis. This study aimed to provide a comprehensive meta-analysis on the diagnostic performance of IL6 in the blood and ascites separately for advanced and early-stage OC. We included 37 studies with 6948 participants detecting serum or plasma IL6. The plasma/serum IL6 mean level in the late-stage OC was 23.88 pg/mL (95% CI: 13.84–41.23), and the early-stage OC was 16.67 pg/mL (95% CI: 510.06–27.61), significantly higher than the healthy controls at 3.96 pg/mL (95% CI: 2.02–7.73), but not significantly higher than those found in the controls with benign growths in the ovary, which was 9.63 pg/mL (95% CI: 4.16–22.26). To evaluate IL6 in ascites as a diagnostic marker, we included 26 studies with 1590 participants. The mean level of ascitic IL6 in the late-stage OC was 3676.93 pg/mL (95% CI: 1891.7–7146.7), and the early-stage OC was 1519.21 pg/mL (95% CI: 604.6–3817.7), significantly higher than the benign controls at 247.33 pg/mL (95% CI: 96.2–636.0). There was no significant correlation between the levels of circulating and ascitic IL6. When pooling all OC stages for analysis, we found that serum/plasma IL6 provided 76.7% sensitivity (95% CI: 0.71–0.92) and 72% specificity (95% CI: 0.64–0.79). Ascitic IL6 provided higher sensitivity at 84% (95% CI: 0.710–0.919) and specificity at 74% (95% CI: 0.646–0.826). This study highlights the utility of ascitic IL6 for early detection of OC.

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Diagnostic Performance of Risk of Ovarian Malignancy Algorithm Against CA125 and HE4 in Connection With Ovarian Cancer: A Meta-analysis

International Journal of Gynecological Cancer ◽

10.1097/igc.0000000000000804 ◽

2016 ◽

Vol 26 (9) ◽

pp. 1586-1593 ◽

Cited By ~ 30

Author(s):

Farshid Dayyani ◽

Steffen Uhlig ◽

Bertrand Colson ◽

Kirsten Simon ◽

Vinzent Rolny ◽

...

Keyword(s):

Ovarian Cancer ◽

Confidence Interval ◽

Late Stage ◽

Diagnostic Performance ◽

Clinical Decision Making ◽

Early Stage ◽

Area Under The Curve ◽

Ovarian Malignancy ◽

Eligibility Criteria ◽

Sensitivity Specificity

ObjectivesThe aim of this study was to determine whether the Risk of Ovarian Malignancy Algorithm (ROMA) is more accurate than the human epididymis 4 (HE4) or carbohydrate antigen 125 (CA125) biomarkers with respect to the differential diagnosis of women with a pelvic mass. The secondary objective is to assess the performance of ROMA in early-stage ovarian cancer (OC) and late-stage OC, as well as premenopausal and postmenopausal patient populations.Methods/MaterialsThe PubMed and Google Scholar databases were searched for relevant clinical studies. Eligibility criteria included comparison of ROMA with both HE4 and CA125 levels in OC (unspecified, epithelial, and borderline ovarian tumors), use of only validated ROMA assays, presentation of area under the curve and sensitivity/specificity data, and results from early-stage OC, late-stage OC and premenopausal and postmenopausal women. Area under the curve (AUC), sensitivity/specificity, and the diagnostic odds ratio (DOR) results were summarized.ResultsFive studies were selected comprising 1975 patients (premenopausal, n = 1033; postmenopausal, n = 925; benign, n = 1387; early stage, n = 192; and late stage, n = 313). On the basis of the AUC (95% confidence interval) data for all patients, ROMA (0.921 [0.855–0.960]) had a numerically greater diagnostic performance than CA125 (0.883 [0.771–0.950]) and HE4 (0.899 [0.835–0.943]). This was also observed in each of the subgroup populations, in particular, the postmenopausal patients and patients with early OC. The sensitivity and specificity (95% confidence interval) results showed ROMA (sensitivity, 0.873 [0.752–0.940]; specificity, 0.855 [0.719–0.932]) to be numerically superior to CA125 (sensitivity, 0.796 [0.663–0.885]; specificity, 0.825 [0.662–0.919]) and HE4 (sensitivity, 0.817 [0.683–0.902]; specificity, 0.851 [0.716–0.928]) in all patients and for the early- and late-stage OC subgroups. Finally, the ROMA log DOR results were better than HE4 and CA125 log DOR results especially for the early-stage patient group.ConclusionsThe results presented support the use of ROMA to improve clinical decision making, most notably in patients with early OC.

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The Serum Glycome to Discriminate between Early-Stage Epithelial Ovarian Cancer and Benign Ovarian Diseases

Disease Markers ◽

10.1155/2014/238197 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10 ◽

Cited By ~ 19

Author(s):

Karina Biskup ◽

Elena Iona Braicu ◽

Jalid Sehouli ◽

Rudolf Tauber ◽

Véronique Blanchard

Keyword(s):

Ovarian Cancer ◽

Epithelial Ovarian Cancer ◽

Late Stage ◽

Early Stage ◽

Diagnostic Methods ◽

Healthy Controls ◽

Common Cause ◽

Ovarian Diseases ◽

Novel Biomarkers ◽

Moderate Sensitivity

Epithelial ovarian cancer (EOC) is the sixth most common cause of cancer deaths in women because the diagnosis occurs mostly when the disease is in its late-stage. Current diagnostic methods of EOC show only a moderate sensitivity, especially at an early-stage of the disease; hence, novel biomarkers are needed to improve the diagnosis. We recently reported that serum glycome modifications observed in late-stage EOC patients by MALDI-TOF-MS could be combined as a glycan score named GLYCOV that was calculated from the relative areas of the 11 N-glycan structures that were significantly modulated. Here, we evaluated the ability of GLYCOV to recognize early-stage EOC in a cohort of 73 individuals comprised of 20 early-stage primary serous EOC, 20 benign ovarian diseases (BOD), and 33 age-matched healthy controls. GLYCOV was able to recognize stage I EOC whereas CA125 values were statistically significant only for stage II EOC patients. In addition, GLYCOV was more sensitive and specific compared to CA125 in distinguishing early-stage EOC from BOD patients, which is of high relevance to clinicians as it is difficult for them to diagnose malignancy prior to operation.

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A MYC-Driven Plasma Polyamine Signature for Early Detection of Ovarian Cancer

Cancers ◽

10.3390/cancers13040913 ◽

2021 ◽

Vol 13 (4) ◽

pp. 913

Author(s):

Johannes Fahrmann ◽

Ehsan Irajizad ◽

Makoto Kobayashi ◽

Jody Vykoukal ◽

Jennifer Dennison ◽

...

Keyword(s):

Ovarian Cancer ◽

Early Stage ◽

Area Under The Curve ◽

Polyamine Metabolism ◽

Healthy Controls ◽

Test Set ◽

Exact Test ◽

Oncogenic Driver ◽

Characteristic Area ◽

Validation Set

MYC is an oncogenic driver in the pathogenesis of ovarian cancer. We previously demonstrated that MYC regulates polyamine metabolism in triple-negative breast cancer (TNBC) and that a plasma polyamine signature is associated with TNBC development and progression. We hypothesized that a similar plasma polyamine signature may associate with ovarian cancer (OvCa) development. Using mass spectrometry, four polyamines were quantified in plasma from 116 OvCa cases and 143 controls (71 healthy controls + 72 subjects with benign pelvic masses) (Test Set). Findings were validated in an independent plasma set from 61 early-stage OvCa cases and 71 healthy controls (Validation Set). Complementarity of polyamines with CA125 was also evaluated. Receiver operating characteristic area under the curve (AUC) of individual polyamines for distinguishing cases from healthy controls ranged from 0.74–0.88. A polyamine signature consisting of diacetylspermine + N-(3-acetamidopropyl)pyrrolidin-2-one in combination with CA125 developed in the Test Set yielded improvement in sensitivity at >99% specificity relative to CA125 alone (73.7% vs 62.2%; McNemar exact test 2-sided P: 0.019) in the validation set and captured 30.4% of cases that were missed with CA125 alone. Our findings reveal a MYC-driven plasma polyamine signature associated with OvCa that complemented CA125 in detecting early-stage ovarian cancer.

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Automated Assay of a Four-Protein Biomarker Panel for Improved Detection of Ovarian Cancer

Cancers ◽

10.3390/cancers13020325 ◽

2021 ◽

Vol 13 (2) ◽

pp. 325

Author(s):

Christopher Walker ◽

Tuan-Minh Nguyen ◽

Shlomit Jessel ◽

Ayesha B. Alvero ◽

Dan-Arin Silasi ◽

...

Keyword(s):

Ovarian Cancer ◽

Early Detection ◽

Predictive Value ◽

Early Stage ◽

Ca 125 ◽

Healthy Controls ◽

Classification Models ◽

Serum Samples ◽

Protein Biomarker ◽

Biomarker Panel

Background: Mortality from ovarian cancer remains high due to the lack of methods for early detection. The difficulty lies in the low prevalence of the disease necessitating a significantly high specificity and positive-predictive value (PPV) to avoid unneeded and invasive intervention. Currently, cancer antigen- 125 (CA-125) is the most commonly used biomarker for the early detection of ovarian cancer. In this study we determine the value of combining macrophage migration inhibitory factor (MIF), osteopontin (OPN), and prolactin (PROL) with CA-125 in the detection of ovarian cancer serum samples from healthy controls. Materials and Methods: A total of 432 serum samples were included in this study. 153 samples were from ovarian cancer patients and 279 samples were from age-matched healthy controls. The four proteins were quantified using a fully automated, multi-analyte immunoassay. The serum samples were divided into training and testing datasets and analyzed using four classification models to calculate accuracy, sensitivity, specificity, PPV, negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC). Results: The four-protein biomarker panel yielded an average accuracy of 91% compared to 85% using CA-125 alone across four classification models (p = 3.224 × 10−9). Further, in our cohort, the four-protein biomarker panel demonstrated a higher sensitivity (median of 76%), specificity (median of 98%), PPV (median of 91.5%), and NPV (median of 92%), compared to CA-125 alone. The performance of the four-protein biomarker remained better than CA-125 alone even in experiments comparing early stage (Stage I and Stage II) ovarian cancer to healthy controls. Conclusions: Combining MIF, OPN, PROL, and CA-125 can better differentiate ovarian cancer from healthy controls compared to CA-125 alone.

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Comparison of the survival outcomes of laparoscopy versus laparotomy in treatment of early-stage ovarian cancer: a systematic review and meta-analysis

Journal of Ovarian Research ◽

10.1186/s13048-021-00793-1 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Qingduo Kong ◽

Hongyi Wei ◽

Jing Zhang ◽

Yilin Li ◽

Yongjun Wang

Keyword(s):

Ovarian Cancer ◽

Overall Survival ◽

Early Stage ◽

Meta Analysis ◽

Progression Free Survival ◽

Cochrane Library ◽

Survival Outcomes ◽

Free Survival ◽

Review Manager ◽

Early Stage Ovarian Cancer

Abstract Background Laparoscopy has been widely used for patients with early-stage epithelial ovarian cancer (eEOC). However, there is limited evidence regarding whether survival outcomes of laparoscopy are equivalent to those of laparotomy among patients with eEOC. The result of survival outcomes of laparoscopy is still controversial. The aim of this meta-analysis is to analyze the survival outcomes of laparoscopy versus laparotomy in the treatment of eEOC. Methods According to the keywords, Pubmed, Embase, Cochrane Library and Clinicaltrials.gov were searched for studies from January 1994 to January 2021. Studies comparing the efficacy and safety of laparoscopy versus laparotomy for patients with eEOC were assessed for eligibility. Only studies including outcomes of overall survival (OS) were enrolled. The meta-analysis was performed using Stata software (Version 12.0) and Review Manager (Version 5.2). Results A total of 6 retrospective non-random studies were included in this meta-analysis. The pooled results indicated that there was no difference between two approaches for patients with eEOC in OS (HR = 0.6, P = 0.446), progression-free survival (PFS) (HR = 0.6, P = 0.137) and upstaging rate (OR = 1.18, P = 0.54). But the recurrence rate of laparoscopic surgery was lower than that of laparotomic surgery (OR = 0.48, P = 0.008). Conclusions Laparoscopy and laparotomy appear to provide comparable overall survival and progression-free survival outcomes for patients with eEOC. Further high-quality studies are needed to enhance this statement.

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Systematic review of adjuvant therapy for early stage (epithelial) ovarian cancer

International Journal of Gynecological Cancer ◽

10.1136/ijgc-00009577-200307000-00001 ◽

2003 ◽

Vol 13 (4) ◽

pp. 395-404 ◽

Cited By ~ 7

Author(s):

B. Winter-Roach ◽

L. Hooper ◽

H. Kitchener

Keyword(s):

Systematic Review ◽

Ovarian Cancer ◽

Adjuvant Chemotherapy ◽

Adjuvant Therapy ◽

Early Stage ◽

Meta Analysis ◽

Disease Free Survival ◽

Significant Difference ◽

Well Differentiated ◽

Platinum Chemotherapy

A systematic review and meta analysis has been undertaken in order to evaluate the effectiveness of adjuvant therapy following surgery for early ovarian cancer. Trials reported since 1990 have been of a higher quality enabling a meta analysis of adjuvant chemotherapy vs adjuvant radiotherapy and a meta analysis of adjuvant chemotherapy vs observation. There was no significant difference between radiotherapy and chemotherapy, though these comprised studies which demonstrated considerable heterogeneity. Chemotherapy did confer significant benefit over observation in terms of both overall and disease free survival. Except for women in whom adequate surgical staging has revealed well differentiated disease confined to one or both ovaries with intact capsule, platinum chemotherapy should be offered to reduce risk of recurrence.

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Magnetic Resonance Imaging for Surveillance of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Diagnostics ◽

10.3390/diagnostics11091665 ◽

2021 ◽

Vol 11 (9) ◽

pp. 1665

Author(s):

Dong Hwan Kim ◽

Sang Hyun Choi ◽

Ju Hyun Shim ◽

So Yeon Kim ◽

Seung Soo Lee ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Hepatocellular Carcinoma ◽

Magnetic Resonance ◽

Sensitivity And Specificity ◽

Diagnostic Performance ◽

Early Stage ◽

Meta Analysis ◽

Random Effects Model ◽

Resonance Imaging ◽

Meta Regression

Our meta-analysis aimed to evaluate the diagnostic performance of surveillance magnetic resonance imaging (sMRI) for detecting hepatocellular carcinoma (HCC), and to compare the diagnostic performance of sMRI between different protocols. Original articles about the diagnostic accuracy of sMRI for detecting HCC were found in major databases. The meta-analytic pooled sensitivity and specificity of sMRI for detecting HCC were determined using a bivariate random effects model. The pooled sensitivity and specificity of full MRI and abbreviated MRI protocols were compared using bivariate meta-regression. In the total seven included studies (1830 patients), the pooled sensitivity of sMRI for any-stage HCC and very early-stage HCC were 85% (95% confidence interval, 79–90%; I2 = 0%) and 77% (66–85%; I2 = 32%), respectively. The pooled specificity for any-stage HCC and very early-stage HCC were 94% (90–97%; I2 = 94%) and 94% (88–97%; I2 = 96%), respectively. The pooled sensitivity and specificity of abbreviated MRI protocols were 87% (80–94%) and 94% (90–98%), values that were comparable with those of full MRI protocols (84% [76–91%] and 94% [89–99%]; p = 0.83). In conclusion, sMRI had good sensitivity for detecting HCC, particularly very early-stage HCC. Abbreviated MRI protocols for HCC surveillance had comparable diagnostic performance to full MRI protocols.

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A Serum Marker for Early Pancreatic Cancer with a Possible Link to Diabetes

JNCI Journal of the National Cancer Institute ◽

10.1093/jnci/djab191 ◽

2021 ◽

Author(s):

Hoonsik Nam ◽

Sunmi Kang ◽

Min Seok Park ◽

Suyeon Kang ◽

Han Sun Kim ◽

...

Keyword(s):

Pancreatic Cancer ◽

Cell Lines ◽

Normal Cell ◽

Diagnostic Performance ◽

Early Stage ◽

Serum Marker ◽

Diabetic Patients ◽

Diagnostic Biomarker ◽

Diabetic Status ◽

Validation Set

Abstract Background Pancreatic cancer (PC) has a grim prognosis, and an early diagnostic biomarker has been highly desired. The molecular link between diabetes and PC has not been well-established. Methods Bioinformatics screening was performed for a serum PC marker. Experiments in cell lines (5 PC and 1 normal cell lines), mouse models, and human tissue staining (37 PC and 10 normal cases) were performed to test asprosin production from PC. Asprosin’s diagnostic performance was tested with serums from multi-center cohorts (347 PC, 209 normal, and 55 additional diabetic subjects) and evaluated according to PC status, stages, and diabetic status, which was compared with that of CA19-9. Results Asprosin, a diabetes-related hormone, was found from the bioinformatics screening, and its production from PC was confirmed. Serum asprosin levels from multi-center cohorts yielded an age-adjusted diagnostic AUC of 0.987 (95% confidence interval [CI] = 0.961 to 0.997), superior to that of CA19-9 (AUC = 0.876, 95% CI = 0.847 to 0.905), and a cut-off of 7.18 ng/mL, at which the validation set exhibited a sensitivity of 0.957 and a specificity of 0.924. Importantly, the performance was maintained in early-stage and non-metastatic PC, consistent with the tissue staining. A slightly lower performance against additional diabetic patients (n = 55) was restored by combining asprosin and CA19-9 (AUC = 0.985, 95% CI = 0.975 to 0.995). Conclusion Asprosin is presented as an early-stage PC serum marker that may provide clues for PC-induced diabetes. Larger prospective clinical studies are warranted to solidify its utility.

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Identifying Potential Markers for Monitoring Progression to Ovarian Cancer Using Plasma Label-free Proteomics

10.21203/rs.2.19189/v1 ◽

2019 ◽

Author(s):

Wenjie Wang ◽

Hongyu Xie ◽

Bairong Xia ◽

LiuChao Zhang ◽

Ce Wang ◽

...

Keyword(s):

Ovarian Cancer ◽

Cancer Patients ◽

Plasma Protein ◽

Late Stage ◽

Early Stage ◽

Label Free ◽

Absolute Quantitation ◽

Keywords Ovarian Cancer ◽

Benign Ovarian Tumor ◽

Increased Risk

Abstract PurposeCancer antigen 125 (CA125) is considered to have high sensitivity but poor specificity for ovarian cancer. New biomarkers utilized to early detect and monitor the progression of ovarian cancer patients are critically needed. Methods A total of 80 patients including 16 early stage, and matched with 17 late stage, 23 benign ovarian tumor (BOT) and 24 uterine fibroid (UF) patients were utilized to perform plasma proteomics analysis using isobaric tag for relative and absolute quantitation (iTRAQ) method to identify differential diagnostic proteins of ovarian cancer patients. A validation set of 9 early stage, 11 late stage, 17 BOT and 16 UF collected by an independent cohort of samples with the same matching principles was examined to confirm the expressed levels of differential expression proteins by ELISA analysis. Results CRP and ARHGEF 11 were identified as potential diagnostic biomarkers of ovarian cancer. Results of area under the curve (AUC) analysis suggested that combination of diagnostic proteins and CA125 achieved a much higher diagnostic accuracy compared with CA125 alone (AUC values: 0.98 versus 0.80), especially improved the specificity (0.97 versus 0.77). In addition, elevated plasma CRP levels were associated with increased risk of ovarian cancer. Conclusions Current study found that plasma protein CRP was an indicator for monitoring the progression of ovarian cancer. Combination of plasma protein biomarkers with CA125 could be utilized to early diagnose of ovarian cancer patients. Keywords ovarian cancer, proteomics, diagnosis, progression, CRP

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Development of a Multimarker Assay for Early Detection of Ovarian Cancer

Journal of Clinical Oncology ◽

10.1200/jco.2008.19.2484 ◽

2010 ◽

Vol 28 (13) ◽

pp. 2159-2166 ◽

Cited By ~ 178

Author(s):

Zoya Yurkovetsky ◽

Steven Skates ◽

Aleksey Lomakin ◽

Brian Nolen ◽

Trenton Pulsipher ◽

...

Keyword(s):

Ovarian Cancer ◽

Early Detection ◽

Late Stage ◽

Early Stage ◽

Screening Strategy ◽

Ca 125 ◽

Great Promise ◽

Biomarker Panel ◽

Healthy Women ◽

Early Stage Ovarian Cancer

PurposeEarly detection of ovarian cancer has great promise to improve clinical outcome.Patients and MethodsNinety-six serum biomarkers were analyzed in sera from healthy women and from patients with ovarian cancer, benign pelvic tumors, and breast, colorectal, and lung cancers, using multiplex xMAP bead-based immunoassays. A Metropolis algorithm with Monte Carlo simulation (MMC) was used for analysis of the data.ResultsA training set, including sera from 139 patients with early-stage ovarian cancer, 149 patients with late-stage ovarian cancer, and 1,102 healthy women, was analyzed with MMC algorithm and cross validation to identify an optimal biomarker panel discriminating early-stage cancer from healthy controls. The four-biomarker panel providing the highest diagnostic power of 86% sensitivity (SN) for early-stage and 93% SN for late-stage ovarian cancer at 98% specificity (SP) was comprised of CA-125, HE4, CEA, and VCAM-1. This model was applied to an independent blinded validation set consisting of sera from 44 patients with early-stage ovarian cancer, 124 patients with late-stage ovarian cancer, and 929 healthy women, providing unbiased estimates of 86% SN for stage I and II and 95% SN for stage III and IV disease at 98% SP. This panel was selective for ovarian cancer showing SN of 33% for benign pelvic disease, SN of 6% for breast cancer, SN of 0% for colorectal cancer, and SN of 36% for lung cancer.ConclusionA panel of CA-125, HE4, CEA, and VCAM-1, after additional validation, could serve as an initial stage in a screening strategy for epithelial ovarian cancer.

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