Pien Lof

Early Detection of Ovarian Cancer Using Cell-Free DNA Fragmentomes and Protein Biomarkers

Abstract Ovarian cancer is a leading cause of death for women worldwide, in part due to ineffective screening methods. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker [cancer antigen 125 (CA-125) and human epididymis protein 4 (HE4)] analyses to evaluate 591 women with ovarian cancer, with benign adnexal masses, or without ovarian lesions. Using a machine learning model with the combined features, we detected ovarian cancer with specificity >99% and sensitivities of 72%, 69%, 87%, and 100% for stages I to IV, respectively. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100%, and HE4 alone detected 28%, 27%, 67%, and 100% of ovarian cancers for stages I to IV, respectively. Our approach differentiated benign masses from ovarian cancers with high accuracy (AUC = 0.88, 95% confidence interval, 0.83–0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation. Significance: There is an unmet need for effective ovarian cancer screening and diagnostic approaches that enable earlier-stage cancer detection and increased overall survival. We have developed a high-performing accessible approach that evaluates cfDNA fragmentomes and protein biomarkers to detect ovarian cancer.

Evaluating the effectiveness of pre-operative diagnosis of ovarian cancer using minimally invasive liquid biopsies by combining serum human epididymis protein 4 and cell-free DNA in patients with an ovarian mass

To assess the feasibility of scalable, objective, and minimally invasive liquid biopsy-derived biomarkers such as cell-free DNA copy number profiles, human epididymis protein 4 (HE4), and cancer antigen 125 (CA125) for pre-operative risk assessment of early-stage ovarian cancer in a clinically representative and diagnostically challenging population and to compare the performance of these biomarkers with the Risk of Malignancy Index (RMI). In this case-control study, we included 100 patients with an ovarian mass clinically suspected to be early-stage ovarian cancer. Of these 100 patients, 50 were confirmed to have a malignant mass (cases) and 50 had a benign mass (controls). Using WisecondorX, an algorithm used extensively in non-invasive prenatal testing, we calculated the benign-calibrated copy number profile abnormality score. This score represents how different a sample is from benign controls based on copy number profiles. We combined this score with HE4 serum concentration to separate cases and controls. Combining the benign-calibrated copy number profile abnormality score with HE4, we obtained a model with a significantly higher sensitivity (42% vs 0%; p<0.002) at 99% specificity as compared with the RMI that is currently employed in clinical practice. Investigating performance in subgroups, we observed especially large differences in the advanced stage and non-high-grade serous ovarian cancer groups. This study demonstrates that cell-free DNA can be successfully employed to perform pre-operative risk of malignancy assessment for ovarian masses; however, results warrant validation in a more extensive clinical study.

The diagnostic accuracy of human epididymis protein 4 (HE4) for discriminating between benign and malignant pelvic masses: a systematic review and meta‐analysis

AbstractIntroductionMany women with benign pelvic masses, suspected of ovarian cancer, are unnecessarily referred for treatment at specialized centers. There is an unmet clinical need to improve diagnostic assessment in these patients. Our objective was to obtain summary estimates of the accuracy of human epididymis protein (HE4) for diagnosing ovarian cancer and to compare the performance of HE4 with that of cancer antigen 125 (CA125).Material and methodsWe searched PubMed, Ovid and Scopus using search terms for “pelvic masses” and “HE4”, to identify studies that evaluated HE4 for diagnosing malignant ovarian masses, in adult women presenting with a pelvic mass, suspected of ovarian cancer, and with diagnosis confirmed by histopathology. Screening, data extraction and Risk of Bias assessment with the QUADAS‐2 tool were done independently by two authors. We performed a meta‐analysis of the accuracy of HE4 and CA125 using a random‐effects bivariate logit‐normal model. A study protocol was registered at PROSPERO (CRD42020158073).ResultsIn the 17 eligible studies, which included 3404 patients, ovarian cancer prevalence ranged from 15% to 71%. Overall, the studies were heterogeneous. All studies seemed to have recruited patients in specialized settings. A meta‐analysis of seven HE4 studies resulted in a mean sensitivity of 79.4% (95% confidence interval [CI] 74.1%–83.8%) and a mean specificity of 84.1% (95% CI 79.6%–87.8%), for cut‐off values of 67–72 pmol/L. Based on eight studies, the mean sensitivity of CA125 was 81.4% (95% CI 74.6%–86.2%) and the mean specificity was 56.8% (95% CI 47.9%–65.4%), at a cut‐off of 35 U/ml. Given a 40% ovarian cancer prevalence, the positive predictive value (PPV) for HE4 would be 76.9% (71.9%–81.2%) vs 55.6% (50.2%–60.9%) for CA125. The negative predictive value (NPV) would be 85.9 (82.8%–88.6%) and 81.9% (76.2%–86.4%), respectively. At a 15% prevalence, the NPV would be 95.8% (95% CI 94.4%–96.7%) for HE4 and 94.4% (95% CI 92.3%–96.0%) for CA125. The PPV would be 46.9% (40.4%–53.4%) and 24.9% (21.1%–29.2%), respectively.ConclusionsHE4 had higher specificity and similar sensitivity compared with CA125. At high prevalence, PPV was also higher for HE4, but at low prevalence, it had a similar NPV to CA125. The field would benefit from studies conducted in general settings.