Clinical Chemistry and Laboratory Medicine (CCLM)

CA-125 glycovariant assays enhance diagnostic sensitivity in the detection of epithelial ovarian cancer

Abstract Objectives Ovarian cancer is the deadliest gynaecologic malignancy. Due to the lack of reliable biomarkers for the detection of the early disease, most patients are diagnosed at an advanced stage resulting in poor survival. We therefore aimed at establishing novel CA-125 glycovariant assays to improve the diagnostic sensitivity and specificity of ovarian cancer. Methods Blood samples of 184 patients with epithelial ovarian cancers (EOC), 127 benign ovarian tumors, and 115 healthy controls were measured using GLYVAR™ Ovarian I and II assays (Uniogen) and the conventional CA-125 protein assay (CanAg CA-125 EIA, Fujirebio). Results The two glycovariant assays differentiated benign and malignant ovarian masses with 88.0 % sensitivity at 99 % specificity, whereas CA-125 showed 72.8 % sensitivity. The improved performance was most evident in patients with borderline or moderately elevated CA-125 concentration at diagnosis, which is a challenging group for differential diagnostics. The CA-125 glycovariant assays showed 2.5 times higher sensitivity (33.3 % with CA-125 vs. 83.3 % with the CA-125 glycovariants) at 94 % specificity. CA-125 glycovariants corrected 82.4 % of false positive results given by CA-125 concentrations with the commonly used cutoff 35 U/mL. Importantly, the CA-125 glycovariant assays detected 63.6 % of early-stage serous carcinomas from benign and healthy controls with very high 99 % specificity, while CA-125 had a sensitivity of only 45.5 %, representing a 40 % increase. Conclusions This is the first study describing the clinical performance of GLYVAR Ovarian I and II assays in ovarian cancer diagnostics. The results indicate that the CA-125 glycovariant assays have remarkable potential to improve ovarian cancer diagnostics.

A new founder BRCA1 haplotype identified in the Puglia region is associated with a specific age-related cancer onset in three unrelated families

Identification of a four-gene methylation biomarker panel in high-grade serous ovarian carcinoma

Abstract Background The lack of effective biomarkers for the screening and early detection of ovarian cancer (OC) is one of the most pressing problems in oncogynecology. Because epigenetic alterations occur early in the cancer development, they provide great potential to serve as such biomarkers. In our study, we investigated a potential of a four-gene methylation panel (including CDH13, HNF1B, PCDH17 and GATA4 genes) for the early detection of high-grade serous ovarian carcinoma (HGSOC). Methods For methylation detection we used methylation sensitive high-resolution melting analysis and real-time methylation specific analysis. We also investigated the relation between gene hypermethylation and gene relative expression using the 2−ΔΔCt method. Results The sensitivity of the examined panel reached 88.5%. We were able to detect methylation in 85.7% (12/14) of early stage tumors and in 89.4% (42/47) of late stage tumors. The total efficiency of the panel was 94.4% and negative predictive value reached 90.0%. The specificity and positive predictive value achieved 100% rates. Our results showed lower gene expression in the tumor samples in comparison to control samples. The more pronounced downregulation was measured in the group of samples with detected methylation. Conclusions In our study we designed the four-gene panel for HGSOC detection in ovarian tissue with 100% specificity and sensitivity of 88.5%. The next challenge is translation of the findings to the less invasive source for biomarker examination, such as plasma. Our results indicate that combination of examined genes deserve consideration for further testing in clinical molecular diagnosis of HGSOC.

Evaluation of circulating Dickkopf-1 as a prognostic biomarker in ovarian cancer patients

Abstract Objectives Dickkopf-1 (DKK1) is a secreted protein, known for suppressing the differentiation and activity of bone-building osteoblasts by acting as an inhibitor of Wnt-signalling. Soluble DKK1 (sDKK1) has been proposed as prognostic biomarker for a wide range of malignancies, however, clinical relevance of sDKK1 as potential blood-based marker for ovarian cancer is unknown. Methods sDKK1 levels were quantified in a cohort of 150 clinically documented ovarian cancer patients by a commercially available DKK1 ELISA (Biomedica, Vienna, Austria). Results Median sDKK1 level was significantly elevated at primary diagnosis of ovarian cancer compared to healthy controls (estimated difference (ED) of 7.75 ng/mL (95% CI: 3.01–12.30 ng/mL, p=0.001)). Higher levels of sDKK1 at diagnosis indicated an increased volume of intraoperative malignant ascites (ED 7.08 pmol/L, 95% CI: 1.46–13.05, p=0.02) and predicted suboptimal debulking surgery (ED 6.88 pmol/L, 95% CI: 1.73–11.87, p=0.01). sDKK1 did not correlate with CA125 and higher sDKK1 levels predicted a higher risk of recurrence and poor survival (PFS: HR=0.507, 95% CI: 0.317–0.809; p=0.004; OS: HR=0.561, 95% CI: 0.320–0.986; p=0.044). Prognostic relevance of sDKK1 was partly sustained in wtBRCA patients (PFS: HR=0.507, 95% CI: 0.317–0.809; p=0.004). Conclusions This is the first study demonstrating the prognostic relevance of sDKK1 in ovarian cancer patients, including those with wtBRCA 1/2 status. Our data encourage further evaluation of sDKK1 in ovarian cancer patients, possibly in terms of a therapy monitoring marker or a response predictor for sDKK1-directed targeted therapies.

Mucin 13 (MUC13) as a candidate biomarker for ovarian cancer detection: potential to complement CA125 in detecting non-serous subtypes

Abstract Objectives Ovarian cancer is the most lethal gynecological malignancy in developed countries. One of the key associations with the high mortality rate is diagnosis at late stages. This clinical limitation is primarily due to a lack of distinct symptoms and detection at the early stages. The ovarian cancer biomarker, CA125, is mainly effective for identifying serous ovarian carcinomas, leaving a gap in non-serous ovarian cancer detection. Mucin 13 (MUC13) is a transmembrane, glycosylated protein with aberrant expression in malignancies, including ovarian cancer. We explored the potential of MUC13 to complement CA125 as an ovarian cancer biomarker, by evaluating its ability to discriminate serous and non-serous subtypes of ovarian cancer at FIGO stages I–IV from benign conditions. Methods We used our newly developed, high sensitivity ELISA to measure MUC13 protein in a large, well-defined cohort of 389 serum samples from patients with ovarian cancer and benign conditions. Results MUC13 and CA125 serum levels were elevated in malignant compared to benign cases (p<0.0001). Receiver-operating characteristic (ROC) curve analysis showed similar area under the curve (AUC) of 0.74 (MUC13) and 0.76 (CA125). MUC13 concentrations were significantly higher in mucinous adenocarcinomas compared to benign controls (p=0.0005), with AUC of 0.80. MUC13 and CA125 showed significant elevation in early-stage cases (stage I–II) in relation to benign controls (p=0.0012 and p=0.014, respectively). Conclusions We report the novel role of MUC13 as a serum ovarian cancer biomarker, where it could complement CA125 for detecting some subtypes of non-serous ovarian carcinoma and early-stage disease.

A predictive and prognostic model for surgical outcome and prognosis in ovarian cancer computed by clinico-pathological and serological parameters (CA125, HE4, mesothelin)

Abstract Objectives Numerous prognostic models have been proposed for ovarian cancer, extending from single serological factors to complex gene-expression signatures. Nonetheless, these models have not been routinely translated into clinical practice. We constructed a robust and readily calculable model for predicting surgical outcome and prognosis of ovarian cancer patients by exploiting commonly available clinico-pathological factors and three selected serum parameters. Methods Serum CA125, human epididymis protein 4 (HE4) and mesothelin (MSL) were quantified by Lumipulse® G chemiluminescent enzyme immunoassay (Fujirebio) in a total of 342 serum samples from 190 ovarian cancer patients, including 152 paired pre- and post-operative samples. Results Detection of pre-operative HE4 and CA125 was the optimal marker combination for blood-based prediction of surgical outcome (AUC=0.86). We constructed a prognostic model, computed by serum levels of pre-operative CA125, post-operative HE4, post-operative MSL and surgical outcome. Prognostic performance of our model was superior to any of these parameters alone and was independent from BRCA1/2 mutational status. We subsequently transformed our model into a prognostic risk index, stratifying patients as “lower risk” or “higher risk”. In “higher risk” patients, relapse or death was predicted with an AUC of 0.89 and they had a significantly shorter progression free survival (HR: 9.74; 95 % CI: 5.95–15.93; p<0.0001) and overall survival (HR: 5.62; 95 % CI: 3.16–9.99; p<0.0001) compared to “lower risk” patients. Conclusions We present a robust predictive/prognostic model for ovarian cancer, which could readily be implemented into routine diagnostics in order to identify ovarian cancer patients at high risk of recurrence.

Diagnostic accuracy of extended HPV DNA genotyping and its application for risk-based cervical cancer screening strategy

Abstract Objectives To evaluate the consistency of 14 high-risk HPVs (hr-HPVs) detection between extended HPV DNA genotyping and a well-validated partial HPV genotyping kit, and to explore the diagnostic accuracy of risk stratification strategy based on extended HPV genotyping for cervical cancer (CC) screening. Methods Baseline data from a clinical trial of recombinant HPV 9-valent vaccine in China was analyzed. All enrolled women aged 20–45 years received cervical cytology, HPV detection by extended and partial HPV genotyping kits. Those who met the indications would further receive colposcopy. The primary endpoints were cervical intraepithelial neoplasia 2/3 or worse (CIN2+/CIN3+). Results A total of 8,000 women were enrolled between April 2020 and July 2020 and 83/33 cases were diagnosed as CIN2+/CIN3+. The overall agreement between the extended and partial HPV genotyping was 92.66 %. And the agreement further increased with the progression of lesions, which lead to similarly high sensitivity and negative predictive value of these kits. A stratified triage strategy of CC screening was constructed based on the immediate CIN2+/CIN3+ risk of specific HPV. Compared with the conventional HPV primary CC screening strategy, the risk-based strategy had higher specificity for CIN (CIN2+: 94.84 vs. 92.46 %, CIN3+: 96.05 vs. 91.92 %), and needed fewer colposcopies for detecting one cervical disease. Conclusions Extended HPV genotyping had good agreement with a well-validated partial HPV genotyping CC primary screening kit in hr-HPV detection. Extended HPV genotyping could facilitate risk-based stratified management strategy and improve the diagnostic accuracy of primary CC screening.

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

Abstract Objectives 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. Methods 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. Results 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. Conclusions 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.

Exploring evolutionary trajectories in ovarian cancer patients by longitudinal analysis of ctDNA

Abstract Objectives We analysed whether temporal heterogeneity of ctDNA encodes evolutionary patterns in ovarian cancer. Methods Targeted sequencing of 275 cancer-associated genes was performed in a primary tumor biopsy and in ctDNA of six longitudinal plasma samples from 15 patients, using the Illumina platform. Results While there was low overall concordance between the mutational spectrum of the primary tumor biopsies vs. ctDNA, TP53 variants were the most commonly shared somatic alterations. Up to three variant clusters were detected in each tumor biopsy, likely representing predominant clones of the primary tumor, most of them harbouring a TP53 variant. By tracing these clusters in ctDNA, we propose that liquid biopsy may allow to assess the contribution of ancestral clones of the tumor to relapsed abdominal masses, revealing two evolutionary patterns. In pattern#1, clusters detected in the primary tumor biopsy were likely relapse seeding clones, as they contributed a major share to ctDNA at relapse. In pattern#2, similar clusters were present in tumors and ctDNA; however, they were entirely cleared from liquid biopsy after chemotherapy and were undetectable at relapse. ctDNA private variants were present among both patterns, with some of them mirroring subclonal expansions after chemotherapy. Conclusions We demonstrate that tracing the temporal heterogeneity of ctDNA, even below exome scale resolution, deciphers evolutionary trajectories in ovarian cancer. Furthermore, we describe two evolutionary patterns that may help to identify relapse seeding clones for targeted therapy.