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 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.

scholarly journals Validation of Candidate Serum Ovarian Cancer Biomarkers for Early Detection

2007 ◽  
Vol 2 ◽  
pp. 117727190700200 ◽  
Author(s):  
Feng Su ◽  
Jennifer Lang ◽  
Ashutosh Kumar ◽  
Carey Ng ◽  
Brian Hsieh ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Early Detection ◽  
Regression Models ◽  
Serum Proteins ◽  
Early Stage ◽  
Ovarian Tumors ◽  
Ca 125 ◽  
Endometrioid Adenocarcinoma ◽  
Serum Samples ◽  
Early Stage Ovarian Cancer

Objective We have previously analyzed protein profiles using Surface Enhanced Laser Desorption and Ionization Time-Of-Flight Mass Spectroscopy (SELDI-TOF-MS) [Kozak et al. 2003, Proc. Natl. Acad. Sci. U.S.A. 100:12343–8] and identified 3 differentially expressed serum proteins for the diagnosis of ovarian cancer (OC) [Kozak et al. 2005, Proteomics, 5:4589–96], namely, apolipoprotein A-I (apoA-I), transthyretin (TTR) and transferin (TF). The objective of the present study is to determine the efficacy of the three OC biomarkers for the detection of early stage (ES) OC, in direct comparison to CA125. Methods The levels of CA125, apoA-I, TTR and TF were measured in 392 serum samples [82 women with normal ovaries (N), 24 women with benign ovarian tumors (B), 85 women with ovarian tumors of low malignant potential (LMP), 126 women with early stage ovarian cancer (ESOC), and 75 women with late stage ovarian cancer (LSOC)], obtained through the GOG and Cooperative Human Tissue Network. Following statistical analysis, multivariate regression models were built to evaluate the utility of the three OC markers in early detection. Results Multiple logistic regression models (MLRM) utilizing all biomarker values (CA125, TTR, TF and apoA-I) from all histological subtypes (serous, mucinous, and endometrioid adenocarcinoma) distinguished normal samples from LMP with 91% sensitivity (specificity 92%), and normal samples from ESOC with a sensitivity of 89% (specificity 92%). MLRM, utilizing values of all four markers from only the mucinous histological subtype showed that collectively, CA125, TTR, TF and apoA-I, were able to distinguish normal samples from mucinous LMP with 90% sensitivity, and further distinguished normal samples from early stage mucinous ovarian cancer with a sensitivity of 95%. In contrast, in serum samples from patients with mucinous tumors, CA125 alone was able to distinguish normal samples from LMP and early stage ovarian cancer with a sensitivity of only 46% and 47%, respectively. Furthermore, collectively, apoA-I, TTR and TF (excluding CA-125) distinguished i) normal samples from samples representing all histopathologic subtypes of LMP, with a sensitivity of 73%, ii) normal samples from ESOC with a sensitivity of 84% and iii) normal samples from LSOC with a sensitivity of 97%. More strikingly, the sensitivity in distinguishing normal versus mucinous ESOC, utilizing apoA-I, TF and TTR (CA-125 excluded), was 95% (specificity 86%; AUC 95%). Conclusions These results suggest that the biomarker panel consisting of apoA-I, TTR and TF may significantly improve early detection of OC.

scholarly journals Preoperative detection of ovarian cancer by color doppler ultrasonography and CA 125

1970 ◽  
Vol 36 (2) ◽  
pp. 68-73 ◽  
Author(s):  
Fawzia Hossain ◽  
Md Nazmul Karim ◽  
Shah Md Mahfuzur Rahman ◽  
Nazreen Khan ◽  
Maruf Siddiqui ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Early Detection ◽  
Predictive Value ◽  
Ovarian Tumor ◽  
Pulsatility Index ◽  
Color Doppler ◽  
Resistance Index ◽  
Ca 125 ◽  
Ovarian Malignancy ◽  
Age Group

Purpose: Early detection of ovarian malignancy is of great clinical importance. The high mortality rate is due to the difficulties with the early detection of ovarian cancer. Current research attempted to assess the accuracy of Color Doppler Sonography and serum CA-125 level as diagnostic tool of ovarian tumor.Materials and Methods: In this cross-sectional study, 60 consecutive patients with ovarian tumor attending the Department of Obstetrics and Gynecology of BSMMU were recruited. Of the study participants 23.3% belong to 16-25 year age group, 20% belong to 26-35 years age group and 23.30% each were of 46-55 years and > 55 years age group. All the patients recruited were from in-patient department and had undergone surgery. Following excision, routine histopathology revealed 43.30% malignant (n=26) and 56.7% (n=34) benign ovarian lesion. Data were collected from the clinical history form and bimanual pelvic examination, serum CA 125 levels, estimation of Resistance index (RI), Pulsatility Index (PI), Novel Index by CDS and post-operative histo-pathological findings were then recorded. Sensitivity, specificity, accuracy, positive and negative predictive value of the diagnosis made by CDS, CA125, in the discrimination of the benign and malignant ovarian tumors was calculated. Using Receiver operative characteristics analysis the accuracy of RI, PI, CA 125 and Novel Index in the diagnosis of ovarian tumor (benign or malignant) were assessed.Results: With the Cut-off of <.5, Resistance Index is found to be capable of detecting 92% of malignant cases (sensitivity 91.7), and could detect 89% (specificity 88.9) of benign cases correctly which translates in to 90% accuracy in the diagnosis of ovarian tumor. Predictive values for positive (84.6) and negative (94.1) tests were also found to be quite high. Pulsatility index was found to be moderate accuracy (63.3%) with cutoff <1 for malignancy, however low predictive value for a positive test (38.5) questions its use. Both CA-125 and Novel Index showed similar level of sensitivity and specificity. Although Novel Index is derivative of CA125, Novel Index demonstrated better diagnostic accuracy and negative predictive value. The cutoff for CA 125 was mandated as 83.58. With the value the sensitivity is 76.9% and the specificity is 94.1%. RI is found to be more sensitive in detection of positive cases (Malignant) and CA125 is found to be more accurate in detection of negative cases (Benign). However a combination could be tried to make a better detection.Conclusion: Color Doppler ultra-sonography and CA125 excels in different tasks, the study concludes in favor of concurrent use of the methods for improving efficacy and thus early detection of ovarian malignancy. DOI: 10.3329/bmrcb.v36i2.6991Bangladesh Med Res Counc Bull 2010; 36: 68-73

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.

Biological Aspects and Clinical Applications of Serum Biomarkers in Ovarian Cancer

2018 ◽  
Author(s):  
Rouba Ali-Fehmi ◽  
Eman Abdulfatah
Keyword(s):  
Ovarian Cancer ◽  
Early Detection ◽  
Early Stage ◽  
Disease Diagnosis ◽  
Ca 125 ◽  
Diagnostic Tools ◽  
Gynecological Malignancy ◽  
Advanced Stages ◽  
Novel Biomarkers ◽  
Brca1 Brca2

Ovarian cancer, the most aggressive gynecological malignancy, presents at advanced stages with metastatic disease. Diagnosis at an early stage is the most important determinant of survival; however, the majority of patients are asymptomatic at early stages and the current diagnostic tools used in clinics show limited success in early detection and hence the need for new diagnostic biomarkers. With the advance of techniques in genomic and proteomics, numerous biomarkers are emerging which may serve as a platform for early detection of ovarian cancer. These include gene-, protein-, miRNAs, and metabolite- based biomarkers. Examples of gene-based biomarkers include HE4, FLOR1, p16INK4a, BRCA1, BRCA2, MLH1, and MSH2. Protein- based biomarkers include leptin, prolactin, osteopontin, IGF-II, and MIF. This chapter discusses the serum tumor markers (CA-125) in current use for screening, diagnosis and monitoring of ovarian cancer as well as the novel biomarkers that are under investigation and validation.

scholarly journals Multi-analytical test based on serum miRNAs and proteins quantification for ovarian cancer early detection

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255804
Author(s):  
Priscila D. R. Cirillo ◽  
Katia Margiotti ◽  
Marco Fabiani ◽  
Mateus C. Barros-Filho ◽  
David Sparacino ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Early Detection ◽  
Cancer Patients ◽  
Serum Proteins ◽  
Early Stage ◽  
Multivariate Logistic Regression Analysis ◽  
Advanced Ovarian Cancer ◽  
Ca 125 ◽  
Data Series ◽  
Cancer Early Detection

Advanced ovarian cancer is one of the most lethal gynecological tumor, mainly due to late diagnoses and acquired drug resistance. MicroRNAs (miRNAs) are small-non coding RNA acting as tumor suppressor/oncogenes differentially expressed in normal and epithelial ovarian cancer and has been recognized as a new class of tumor early detection biomarkers as they are released in blood fluids since tumor initiation process. Here, we evaluated by droplet digital PCR (ddPCR) circulating miRNAs in serum samples from healthy (N = 105) and untreated ovarian cancer patients (stages I to IV) (N = 72), grouped into a discovery/training and clinical validation set with the goal to identify the best classifier allowing the discrimination between earlier ovarian tumors from health controls women. The selection of 45 candidate miRNAs to be evaluated in the discovery set was based on miRNAs represented in ovarian cancer explorative commercial panels. We found six miRNAs showing increased levels in the blood of early or late-stage ovarian cancer groups compared to healthy controls. The serum levels of miR-320b and miR-141-3p were considered independent markers of malignancy in a multivariate logistic regression analysis. These markers were used to train diagnostic classifiers comprising miRNAs (miR-320b and miR-141-3p) and miRNAs combined with well-established ovarian cancer protein markers (miR-320b, miR-141-3p, CA-125 and HE4). The miRNA-based classifier was able to accurately discriminate early-stage ovarian cancer patients from health-controls in an independent sample set (Sensitivity = 80.0%, Specificity = 70.3%, AUC = 0.789). In addition, the integration of the serum proteins in the model markedly improved the performance (Sensitivity = 88.9%, Specificity = 100%, AUC = 1.000). A cross-study validation was carried out using four data series obtained from Gene Expression Omnibus (GEO), corroborating the performance of the miRNA-based classifier (AUCs ranging from 0.637 to 0.979). The clinical utility of the miRNA model should be validated in a prospective cohort in order to investigate their feasibility as an ovarian cancer early detection tool.

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.

Sign in / Sign up

Export Citation Format

Share Document