scholarly journals Diagnostic Value of Plasma Annexin A2 in Early-Stage High-Grade Serous Ovarian Cancer

Diagnostics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 69
Author(s):  
Noor A. Lokman ◽  
Carmela Ricciardelli ◽  
Andrew N. Stephens ◽  
Thomas W. Jobling ◽  
Peter Hoffmann ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Early Detection ◽  
Early Stage ◽  
Diagnostic Value ◽  
Annexin A2 ◽  
High Grade ◽  
Healthy Controls ◽  
Operating Characteristics ◽  
Logistic Regression Models ◽  
Stage Ia

Ovarian cancer (OC) is commonly diagnosed at advanced stage when prognosis is poor. Consequently, there is an urgent clinical need to identify novel biomarkers for early detection to improve survival. We examined the diagnostic value of the calcium phospholipid binding protein annexin A2 (ANXA2), which plays an important role in OC metastasis. Annexin A2 plasma levels in patients with high grade serous OC (n = 105), benign ovarian lesions (n = 55) and healthy controls (n = 143) were measured by ELISA. Annexin A2 levels were found to be significantly increased in patients with stage I (p < 0.0001) and stage IA (p = 0.0027) OC when compared to healthy controls. In the logistic regression models followed by receiver operating characteristics (ROC) curve analyses, plasma annexin A2 showed 46.7% sensitivity at 99.6% specificity in distinguishing stage IA OC patients from healthy controls and 75% sensitivity at 65.5% specificity in the diagnosis of stage IA versus benign ovarian tumors. In the diagnosis of stage IA OC versus normal controls, the combination of plasma annexin A2 and CA125 showed 80% sensitivity at 99.6% specificity (AUC = 0.970) which was significantly higher than for CA125 (53.3% sensitivity at 99.6% specificity; AUC = 0.891) alone. The diagnostic accuracy in distinguishing stage IA OC from benign ovarian disease when combining annexin A2 and CA125 (71.4% accuracy at 100% sensitivity) was almost twice as high compared to CA125 (37.1% accuracy at 100% sensitivity) alone. In conclusion, annexin A2 in combination with CA125 has potential as a biomarker for the early detection of OC and to predict malignancy in patients with ovarian lesions, warranting further investigations.

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

Cancers ◽  
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.

scholarly journals Serum Anti-PDLIM1 Autoantibody as Diagnostic Marker in Ovarian Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Cuipeng Qiu ◽  
Yaru Duan ◽  
Bofei Wang ◽  
Jianxiang Shi ◽  
Peng Wang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Detection ◽  
Early Stage ◽  
Diagnostic Value ◽  
Tissue Array ◽  
Enzyme Linked Immunosorbent Assay ◽  
Positive Staining ◽  
Healthy Controls ◽  
Autoantibody Response ◽  
Validation Set

BackgroundSerum autoantibodies (AAbs) against tumor-associated antigens (TAAs) could be useful biomarkers for cancer detection. This study aims to evaluate the diagnostic value of autoantibody against PDLIM1 for improving the detection of ovarian cancer (OC).MethodsImmunohistochemistry (IHC) test in tissue array containing 280 OC tissues, 20 adjacent tissues, and 8 normal ovarian tissues was performed to analyze the expression of PDLIM1 in tissues. Enzyme-linked immunosorbent assay (ELISA) was employed to measure the autoantibody to PDLIM1 in 545 sera samples from 182 patients with OC, 181 patients with ovarian benign diseases, and 182 healthy controls.ResultsThe results of IHC indicated that 84.3% (236/280) OC tissues were positively stained with PDLIM1, while no positive staining was found in adjacent or normal ovarian tissues. The frequency of anti-PDLIM1 autoantibody was significantly higher in OC patients than that in healthy and ovarian benign controls in both training (n=122) and validation (n=423) sets. The area under the curves (AUCs) of anti-PDLIM1 autoantibody for discriminating OC from healthy controls were 0.765 in training set and 0.740 in validation set, and the AUC of anti-PDLIM1 autoantibody for discriminating OC from ovarian benign controls was 0.757 in validation set. Overall, it was able to distinguish 35.7% of OC, 40.6% of patients with early-stage, and 39.5% of patients with late-stage. When combined with CA125, the AUC increased to 0.846, and 79.2% of OC were detected, which is statistically higher than CA125 (61.7%) or anti-PDLIM1(35.7%) alone (p&lt;0.001). Also, anti-PDLIM1 autoantibody could identify 15% (18/120) of patients that were negative with CA125 (CA125 &lt;35 U/ml).ConclusionsThe anti-PDLIM1 autoantibody response in OC patients was positively correlated with PDLIM1 high expression in OC tissues, suggesting that the autoantibody against PDLIM1 might have the potential to be a novel serological biomarker of OC, serving as a complementary measure of CA125, which could improve the power of OC detection.

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

Cancers ◽  
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.

scholarly journals BARD1 Autoantibody Blood Test for Early Detection of Ovarian Cancer

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 969
Author(s):  
Maxim Pilyugin ◽  
Magda Ratasjka ◽  
Maciej Stukan ◽  
Nicole Concin ◽  
Robert Zeillinger ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Early Detection ◽  
Blood Test ◽  
Menopausal Status ◽  
Clinical Samples ◽  
Average Risk ◽  
Healthy Controls ◽  
Cancer Antigen 125 ◽  
Cancer Syndrome ◽  
Ovarian Cancer Screening

Background: Ovarian cancer (OC) is the most lethal gynaecological cancer. It is often diagnosed at an advanced stage with poor chances for successful treatment. An accurate blood test for the early detection of OC could reduce the mortality of this disease. Methods: Autoantibody reactivity to 20 epitopes of BARD1 and concentration of cancer antigen 125 (CA125) were assessed in 480 serum samples of OC patients and healthy controls. Autoantibody reactivity and CA125 were also tested for 261 plasma samples of OC with or without mutations in BRCA1/2, BARD1, or other predisposing genes, and healthy controls. Lasso statistic regression was applied to measurements to develop an algorithm for discrimination between OC and controls. Findings and interpretation: Measurement of autoantibody binding to a number of BARD1 epitopes combined with CA125 could distinguish OC from healthy controls with high accuracy. This BARD1-CA125 test was more accurate than measurements of BARD1 autoantibody or CA125 alone for all OC stages and menopausal status. A BARD1-CA125-based test is expected to work equally well for average-risk women and high-risk women with hereditary breast and ovarian cancer syndrome (HBOC). Although these results are promising, further data on well-characterised clinical samples shall be used to confirm the potential of the BARD1-CA125 test for ovarian cancer screening.

scholarly journals Meeting report from the 2018 12th Biennial Ovarian Cancer Research Symposium detection and prevention of ovarian cancer

2019 ◽  
Vol 29 (Suppl 2) ◽  
pp. s2-s6 ◽  
Author(s):  
Wa Xian ◽  
Sophia George
Keyword(s):  
Ovarian Cancer ◽  
Cancer Research ◽  
Early Detection ◽  
Molecular Mechanisms ◽  
Effective Means ◽  
Meeting Report ◽  
Clear Understanding ◽  
High Grade ◽  
Cellular Origin ◽  
Oral Presentations

The objective of this review is to summarize recent research advances in the detection and prevention of ovarian cancer and discuss the experts’ opinions of future directions. The 12th Biennial Ovarian Cancer Research Symposium was held in Seattle, Washington, in September 2018. At this meeting, experts in ovarian cancer research gathered to present and discuss recent breakthroughs and their visions of future ovarian cancer research. Session 1 of the symposium focused on the detection and prevention of ovarian cancer. It included two invited oral presentations from Ranjit Manchanda, MD, PhD (Barts Cancer Institute) and Rosana Risques, PhD (University of Washington). Another eight oral presentations were selected from abstract submissions. Fifteen abstracts were presented in poster format. These presentations covered topics including cellular origin of high-grade serous cancer, risk factors for ovarian cancer, new methods for early detection of ovarian cancer, mechanisms underlying ovarian cancer development, and new therapeutic approaches for preventing ovarian cancer from forming or progressing. In conclusion, a clear understanding of the cellular origin and molecular mechanisms underlying the initiation of high-grade serous cancer is essential for developing effective means for early detection and prevention of this most devastating type of ovarian cancer. Recognizing the complexity of ovarian cancer and appreciating that ovarian cancer is not a single disease will help us to generate proper models, design rational experiments, and collect and analyze patient data in a meaningful way. A concerted effort in the field will help to bridge the basic science and clinical applications and lead to more precise and effective detection and treatment.

Evaluating exosome proteins as biomarkers for the early detection of high-grade serous ovarian cancer

2018 ◽  
Vol 149 ◽  
pp. 71
Author(s):  
K.D.P. Dorayappan ◽  
R.A. Zingarelli ◽  
C.L. Hisey ◽  
B.Q. Smith ◽  
R. Wanner ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Early Detection ◽  
High Grade ◽  
Serous Ovarian Cancer

scholarly journals Development of a Multimarker Assay for Early Detection of Ovarian Cancer

2010 ◽  
Vol 28 (13) ◽  
pp. 2159-2166 ◽  
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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