Diagnostic performance of the biomarkers HE4 and CA125 in type I and type II epithelial ovarian cancer

AbstractObjectiveTo evaluate the diagnostic performance of HE4 and CA125 in patients presenting with suspicious malignant ovarian cysts. We especially wanted to investigate the levels of HE4 and CA125 with regard to the gene and histology-unifying model of type I and type II epithelial ovarian cancer (EOC).MethodsPlasma from 373 women presenting with a suspicious malignant ovarian cyst was collected prior to surgery. Histology, grade, and stage were determined according to FIGO-classification. HE4 and CA125 were analyzed using ELISA, and the markers were evaluated for significance separately and in combination. Receiver operating curves, the area under the curve, sensitivity and specificity were estimated.ResultsThe combination of HE4 and CA125 resulted in the best diagnostic power in comparing benign tumors to EOC (ROC AUC 0.93, sensitivity 94.4% at 75% specificity) for type II. Diagnostic power in type I (ROC AUC 0.79, sensitivity 61.9% at 75% specificity) was less impressive. In particular, mucinous benign vs. malignant tumors could not significantly be separated by the dual marker combination. Impressively high ROC AUC 0.99 was found for the late stage type II EOC with 100% sensitivity at 75% specificity.ConclusionsHE4 and CA125 have a good ability to diagnose the more aggressive type II tumors but a poor diagnostic ability when patients are presenting with slow-growing type I in the early stage. Our results support the hypothesis that EOC should be looked upon as several different diseases, and that we lack biomarkers for sub-groups of EOC

Diagnostic potential of nanoparticle aided assays for MUC16 and MUC1 glycovariants in ovarian cancer

Our study reports the discovery and evaluation of nanoparticle aided sensitive assays for glycovariants of MUC16 and MUC1 in a unique collection of paired ovarian cyst fluids and serum samples obtained at or prior to surgery for ovarian carcinoma suspicion. Selected glycovariants and the immunoassays for CA125, CA15-3 and HE4 were compared and validated in 347 cyst fluid and serum samples. Whereas CA125 and CA15-3 performed poorly in cyst fluid to separate carcinoma and controls, four glycovariants including MUC16(MGL), MUC16(STn), MUC1(STn) and MUC1(Tn) provided highly improved separations. In serum, the two STn glycovariants outperformed conventional CA125, CA15-3 and HE4 assays in all subcategories analyzed with main benefits obtained at high specificities and at postmenopausal and early-stage disease. Serum MUC16(STn) performed best at high specificity (90%-99%), but sensitivity was also improved by the other glycovariants and CA15-3. The highly improved specificity, excellent analytical sensitivity and robustness of the nanoparticle assisted glycovariant assays carry great promise for improved identification and early detection of ovarian carcinoma in routine differential diagnostics.Peer reviewe

Diagnostic potential of nanoparticle aided assays for MUC16 and MUC1 glycovariants in ovarian cancer

Our study reports the discovery and evaluation of nanoparticle aided sensitive assays for glycovariants of MUC16 and MUC1 in a unique collection of paired ovarian cyst fluids and serum samples obtained at or prior to surgery for ovarian carcinoma suspicion. Selected glycovariants and the immunoassays for CA125, CA15-3 and HE4 were compared and validated in 347 cyst fluid and serum samples. Whereas CA125 and CA15-3 performed poorly in cyst fluid to separate carcinoma and controls, four glycovariants including MUC16(MGL), MUC16(STn), MUC1(STn) and MUC1(Tn) provided highly improved separations. In serum, the two STn glycovariants outperformed conventional CA125, CA15-3 and HE4 assays in all subcategories analyzed with main benefits obtained at high specificities and at postmenopausal and early-stage disease. Serum MUC16(STn) performed best at high specificity (90%-99%), but sensitivity was also improved by the other glycovariants and CA15-3. The highly improved specificity, excellent analytical sensitivity and robustness of the nanoparticle assisted glycovariant assays carry great promise for improved identification and early detection of ovarian carcinoma in routine differential diagnostics

Increased Diagnostic Accuracy of Adnexal Tumors with A Combination of Established Algorithms and Biomarkers

Ovarian cancer is the most lethal gynecologic cancer. Pre-diagnostic testing lacks sensitivity and specificity, and surgery is often the only way to secure the diagnosis. Exploring new biomarkers is of great importance, but the rationale of combining validated well-established biomarkers and algorithms could be a more effective way forward. We hypothesized that we can improve differential diagnostics and reduce false positives by combining (a) risk of malignancy index (RMI) with serum HE4, (b) risk of ovarian malignancy algorithm (ROMA) with a transvaginal ultrasound score or (c) adding HE4 to CA125 in a simple algorithm. With logistic regression modeling, new algorithms were explored and validated using leave-one-out cross validation. The analyses were performed in an existing cohort prospectively collected prior to surgery, 2013-2016. A total of 445 benign tumors and 135 ovarian cancers were included. All presented models improved specificity at cut-off compared to the original algorithm, and goodness of fit was significant (p < 0.001). Our findings confirm that HE4 is a marker that improves specificity without hampering sensitivity or diagnostic accuracy in adnexal tumors. We provide in this study "easy-to-use" algorithms that could aid in the triage of women to the most appropriate level of care when presenting with an unknown ovarian cyst or suspicious ovarian cancer

Targeted selected reaction monitoring verifies histology specific peptide signatures in epithelial ovarian cancer

Epithelial ovarian cancer (OC) is a disease with high mortality due to vague early clinical symptoms. Benign ovarian cysts are common and accurate diagnosis remains a challenge because of the molecular heterogeneity of OC. We set out to investigate whether the disease diversity seen in ovarian cyst fluids and tumor tissue could be detected in plasma. Using existing mass spectrometry (MS)-based proteomics data, we constructed a selected reaction monitoring (SRM) assay targeting peptides from 177 cancer-related and classical proteins associated with OC. Plasma from benign, borderline, and malignant ovarian tumors were used to verify expression (n = 74). Unsupervised and supervised multivariate analyses were used for comparisons. The peptide signatures revealed by the supervised multivariate analysis contained 55 to 77 peptides each. The predictive (Q2) values were higher for benign vs. low-grade serous Q2 = 0.615, mucinous Q2 = 0.611, endometrioid Q2 = 0.428 and high-grade serous Q2 = 0.375 (stage I–II Q2 = 0.515; stage III Q2 = 0.43) OC compared to benign vs. all malignant Q2 = 0.226. With targeted SRM MS we constructed a multiplexed assay for simultaneous detection and relative quantification of 185 peptides from 177 proteins in only 20 µL of plasma. With the approach of histology-specific peptide patterns, derived from pre-selected proteins, we may be able to detect not only high-grade serous OC but also the less common OC subtypes

Univariate and classification analysis reveals potential diagnostic biomarkers for early stage ovarian cancer Type 1 and Type 2

Biomarkers for early detection of ovarian tumors are urgently needed. Tumors of the ovary grow within cysts and most are benign. Surgical sampling is the only way to ensure accurate diagnosis, but often leads to morbidity and loss of female hormones. The present study explored the deep proteome in well-defined sets of ovarian tumors, FIGO stage I, Type 1 (low-grade serous, mucinous, endometrioid; n = 9), Type 2 (high-grade serous; n = 9), and benign serous (n = 9) using TMT–LC–MS/MS. Data are available via ProteomeXchange with identifier PXD010939. We evaluated new bioinformatics tools in the discovery phase. This innovative selection process involved different normalizations, a combination of univariate statistics, and logistic model tree and naive Bayes tree classifiers. We identified 142 proteins by this combined approach. One biomarker panel and nine individual proteins were verified in cyst fluid and serum: transaldolase-1, fructose-bisphosphate aldolase A (ALDOA), transketolase, ceruloplasmin, mesothelin, clusterin, tenascin-XB, laminin subunit gamma-1, and mucin-16. Six of the proteins were found significant (p <.05) in cyst fluid while ALDOA was the only protein significant in serum. The biomarker panel achieved ROC AUC 0.96 and 0.57 respectively. We conclude that classification algorithms complement traditional statistical methods by selecting combinations that may be missed by standard univariate tests. Significance: In the discovery phase, we performed deep proteome analyses of well-defined histology subgroups of ovarian tumor cyst fluids, highly specified for stage and type (histology and grade). We present an original approach to selecting candidate biomarkers combining several normalization strategies, univariate statistics, and machine learning algorithms. The results from validation of selected proteins strengthen our prior proteomic and genomic data suggesting that cyst fluids are better than sera in early stage ovarian cancer diagnostics

Consideration should be given to smoking, endometriosis, renal function (eGFR) and age when interpreting CA125 and HE4 in ovarian tumor diagnostics

To evaluate the impact of different biologic, histopathologic and lifestyle factors on serum levels of human epididymis protein 4 (HE4) and Cancer antigen 125 (CA125) in the diagnostic work up of women with an ovarian cyst or pelvic tumor. The statistical evaluation was performed on a population of 445 women diagnosed with a benign ovarian disease, included in a large Swedish multicenter trial (ClinicalTrials.gov NCT03193671). Multivariable logistic regression analyses were performed to distinguish between the true negatives and false positives through adjusting for biologic, histopathologic and lifestyle factors on serum samples of CA125 and HE4 separately. The likelihood ratio test was used to determine statistical significance and Benjamini-Hochberg correction to adjust for multiple testing. A total of 31% of the women had false positive CA125 but only 9% had false positive results of HE4. Smoking (OR 6.62 95% CI 2.93-15.12) and impaired renal function, measured by eGFR (OR 0.18 95% CI 0.08-0.39), were independently predictive of falsely elevated serum levels of HE4. Endometriosis was the only variable predictive of falsely elevated serum levels of CA125 (OR 7.96 95% CI 4.53-14.39). Age correlated with increased serum levels of HE4. Smoking, renal failure, age and endometriosis are factors that independently should be considered when assessing serum levels of HE4 and CA125 in women with an ovarian cyst or pelvic mass to avoid false indications of malignant disease. CC BY 4.0© 2021Pre-published online by De Gruyter August 12, 2021The study was funded by the Swedish Cancer Foundation (KS), LUA-ALF (KS), the Assar Gabrielsson Foundation (ML, BK, CM), the Hjalmar Svensson Foundation (ML), and the Gothenburg Medical Society (ML). Roche Diagnostics Scandinavia covered the cost of running biomarker assays at the accredited laboratory at Sahlgrenska University Hospital, Gothenburg, Sweden. The funding organizations played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.</p

Early Diagnosis of Epithelial Ovarian Cancer - Analysis of Novel Biomarkers

Early Diagnosis of Epithelial Ovarian Cancer - Analysis of Novel Biomarkers Björg Kristjánsdóttir Department of Obstetrics & Gynecology, Institute of Clinical Sciences at Sahlgrenska Academy, University of Gothenburg, Sweden ABSTRACT Background: Majority of epithelial ovarian cancer (EOC) is detected in advanced stage with bad prognosis and high mortality. Reliable diagnostic markers are lacking, pre-cancerous lesions in the more aggressive tumors are not clearly defined, vague or unspecific early symptoms, and the localization of the ovaries, deep in the pelvis contributes to late diagnose. Heterogeneity, not only different type of histology, but also different intrinsic biology and behavior characterizes ovarian cancer. Invasive surgery with histological examination is needed to confirm the diagnosis. Less than 25% EOC are diagnosed early, when there is great possibility to cure and 5-year survival >90%, in contrast to 20-30% 5-year survival in late stage EOC. Thus, early detection is of utmost importance. Proximal fluids, like ovarian cyst fluid, are promising in the search for early markers. Cancer antigen 125 (CA125), the most used biomarker since 30 years, and a promising marker human epididymis 4 (HE4) have recently been approved by FDA to be used in the prediction of malignancy in women with a pelvic mass. Aims: To explore ovarian cyst fluid as a source mining for new diagnostic biomarkers for EOC, and to validate the markers found together with CA125 (Paper I-III); and to evaluate the diagnostic performance of HE4 and CA125, to distinguish between benign cysts and EOC, and EOC divided into slow growing type I and the aggressive type II EOC (Paper IV-V). Method: Cross sectional, observational, explorative, and diagnostic clinical studies, with prospective and consecutive collection of cystic fluid, blood and tumor tissue at the time of operation and retrospective analysis. Women with suspicious malignant pelvic cysts, already scheduled for operation at our clinic for tumor surgery were included. High throughput proteomic analyses were used for searching for novel markers, and selected proteins were validated with ELISA or immunoblot. Paper I: The cyst fluid proteome was mined with surfaceenhanced laser desorption/ionization time of flight (SELDI-TOF) mass spectrometry (MS) (n=192). Paper II: Enrichment of a selection of known cancer antigens to overcome high abundant proteins, and with focus on inflammation, was followed by Immunoprecipitation MS (n=38). Significantly differently expressed chemokines were validated (n=256). Paper III: Serous cystadenoma (n=5) and serous adenocarcinoma (n=10) of different stages were analyzed with isobaric tag for relative and absolute quantification (iTRAQ), followed by immunoblot validation (n=68). Paper IV-V: HE4 and CA125 levels in plasma were analyzed with ELISA and Risk of Ovarian Malignancy Algorithm (ROMA) was calculated (n=393). Significant differences, receiver operator characteristics (ROC) area under the curve (AUC), cut-off levels, sensitivity and specificity were estimated with regard to malignancy, grade, stage histologic subtype and type I and type II. Results: Paper I: Combination of Apolipoprotein CIII and Protein C inhibitor had the best AUC (0.91) in cyst fluid, and improved by CA125 (0.94). Abundant proteins were a problem in the cyst fluid analyses. Paper II: Interleukin-8 and Chemoattractant Protein-I were highly significantly increased expressed in cyst fluid. Increased inflammatory response was present in early tumor development and earlier than in blood. Paper III: Two of 87 differentially expressed proteins in cyst fluid, with high significance and fold change, Serum Amyloid A-4 (SAA4) and astacin-like metalloendopeptidase (ASTL) were validated, and SAA4 was significantly increased in cyst fluid, but not in blood. Paper IV: HE4 complemented CA125 in the diagnosis of ovarian cysts, especially in the premenopausal women. Sensitivity for ROMA at set specificity of 75% was highest in the postmenopausal cohort (87%). Paper V: HE4 and CA125 diagnosed the aggressive type II EOC most correctly (AUC 0.93), but the results were not acceptable in early stage type II (AUC 0.85) or in type I EOC (AUC 0.79) respective early type I AUC 0.73). Conclusion: Ovarian cyst fluid is an excellent source for the search of novel biomarkers for early diagnosis of EOC. Early events are found near the tumor in the early phase, like the inflammatory response and later on in the peripheral circulation. HE4 complements CA125 in predicting malignancy in cystic ovarian tumors. The result from this thesis support, that EOC should be looked upon as several different diseases. Finding early markers that are specific for each histology subgroup will be the future challenge. Combination of such markers in a panel could improve the early diagnosis of EOC. Keywords: EOC; ovarian adenocarcinoma; ovarian cyst fluid; pelvic mass; tumor biomarker; mass spectrometry; SELDI-TOF MS; iTRAQ; ISBN 978-91-628-8727-8 http://hdl.handle.net/2077/3309