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

ABSTRACT: 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.

SUBMITTER: Walker C

PROVIDER: S-EPMC7830619 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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

Walker Christopher C Nguyen Tuan-Minh TM Jessel Shlomit S Alvero Ayesha B AB Silasi Dan-Arin DA Rutherford Thomas T Draghici Sorin S Mor Gil G

Cancers 20210117 2

<i>Background</i>: 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 fact ...[more]

PMID: 33477343

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Project description:BACKGROUND:There is an urgent need for biomarkers for the early detection of ovarian cancer (OC). The purpose of this study was to assess whether changes in serum levels of lecithin-cholesterol acyltransferase (LCAT), sex hormone-binding globulin (SHBG), glucose-regulated protein, 78?kDa (GRP78), calprotectin and insulin-like growth factor-binding protein 2 (IGFBP2) are observed before clinical presentation and to assess the performance of these markers alone and in combination with CA125 for early detection. METHODS:This nested case-control study used samples from the United Kingdom Collaborative Trial of Ovarian Cancer Screening trial. The sample set consisted of 482 serum samples from 49 OC subjects and 31 controls, with serial samples spanning up to 7 years pre-diagnosis. The set was divided into the following: (I) a discovery set, which included all women with only two samples from each woman, the first at<14 months and the second at >32 months to diagnosis; and (ii) a corroboration set, which included all the serial samples from the same women spanning the 7-year period. Lecithin-cholesterol acyltransferase, SHBG, GRP78, calprotectin and IGFBP2 were measured using ELISA. The performance of the markers to detect cancers pre-diagnosis was assessed. RESULTS:A combined threshold model IGFBP2 >78.5?ng?ml-1?:?LCAT <8.831??g?ml-1?:?CA125 >35?U?ml-1 outperformed CA125 alone for the earlier detection of OC. The threshold model was able to identify the most aggressive Type II cancers. In addition, it increased the lead time by 5-6 months and identified 26% of Type I subjects and 13% of Type II subjects that were not identified by CA125 alone. CONCLUSIONS:Combined biomarker panels (IGFBP2, LCAT and CA125) outperformed CA125 up to 3 years pre-diagnosis, identifying cancers missed by CA125, providing increased diagnostic lead times for Type I and Type II OC. The model identified more aggressive Type II cancers, with women crossing the threshold dying earlier, indicating that these markers can improve on the sensitivity of CA125 alone for the early detection of OC.

Dataset Information

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

Publications

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

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