Lindsay Bergan

Assessing Lead Time of Selected Ovarian Cancer Biomarkers: A Nested Case–Control Study

Background CA125, human epididymis protein 4 (HE4), mesothelin, B7-H4, decoy receptor 3 (DcR3), and spondin-2 have been identified as potential ovarian cancer biomarkers. Except for CA125, their behavior in the prediagnostic period has not been evaluated. Methods Immunoassays were used to determine concentrations of CA125, HE4, mesothelin, B7-H4, DcR3, and spondin-2 proteins in prediagnostic serum specimens (1–11 samples per participant) that were contributed 0–18 years before ovarian cancer diagnosis from 34 patients with ovarian cancer (15 with advanced-stage serous carcinoma) and during a comparable time interval before the reference date from 70 matched control subjects who were participating in the Carotene and Retinol Efficacy Trial. Lowess curves were fit to biomarker levels in cancer patients and control subjects separately to summarize mean levels over time. Receiver operating characteristic curves were plotted, and area-under-the curve (AUC) statistics were computed to summarize the discrimination ability of these biomarkers by time before diagnosis. Results Smoothed mean concentrations of CA125, HE4, and mesothelin (but not of B7-H4, DcR3, and spondin-2) began to increase (visually) in cancer patients relative to control subjects approximately 3 years before diagnosis but reached detectable elevations only within the final year before diagnosis. In descriptive receiver operating characteristic analyses, the discriminatory power of these biomarkers was limited (AUC statistics range = 0.56–0.75) but showed increasing accuracy with time approaching diagnosis (eg, AUC statistics for CA125 were 0.57, 0.68, and 0.74 for ≥4, 2–4, and <2 years before diagnosis, respectively). Conclusion Serum concentrations of CA125, HE4, and mesothelin may provide evidence of ovarian cancer 3 years before clinical diagnosis, but the likely lead time associated with these markers appears to be less than 1 year.

Use of a Symptom Index, CA125, and HE4 to predict ovarian cancer

BACKGROUND Prior studies suggest that combining the Symptom Index (SI) with a serum HE4 test or a CA125 test may improve prediction of ovarian cancer. However, these three tests have not been evaluated in combination. METHODS A prospective case-control study design including 74 women with ovarian cancer and 137 healthy women was used with logistic regression analysis to evaluate the independent contributions of HE4 and CA125, and the SI to predict ovarian cancer status in a multivariate model. The diagnostic performance of various decision rules for combinations of these tests was assessed to evaluate potential use in predicting ovarian cancer. RESULTS The SI, HE4, and CA125 all made significant independent contributions to ovarian cancer prediction. A decision rule based on any one of the three tests being positive had a sensitivity of 95% with specificity of 80%. A rule based on any two of the three tests being positive had a sensitivity of 84% with a specificity of 98.5%. The SI alone had sensitivity of 64% with specificity of 88%. If the SI index is used to select women for CA125 and HE4 testing, specificity is 98.5% and sensitivity is 58% using the 2-of-3-positive decision rule. CONCLUSIONS A 2-of-3-positive decision rule yields acceptable specificity, and higher sensitivity when all 3 tests are performed than when the SI is used to select women for screening by CA125 and HE4. If positive predictive value is a high priority, testing by CA125 and HE4 prior to imaging may be warranted for women with ovarian cancer symptoms.

Systematic Evaluation of Candidate Blood Markers for Detecting Ovarian Cancer

Background Epithelial ovarian cancer is a significant cause of mortality both in the United States and worldwide, due largely to the high proportion of cases that present at a late stage, when survival is extremely poor. Early detection of epithelial ovarian cancer, and of the serous subtype in particular, is a promising strategy for saving lives. The low prevalence of ovarian cancer makes the development of an adequately sensitive and specific test based on blood markers very challenging. We evaluated the performance of a set of candidate blood markers and combinations of these markers in detecting serous ovarian cancer. Methods and Findings We selected 14 candidate blood markers of serous ovarian cancer for which assays were available to measure their levels in serum or plasma, based on our analysis of global gene expression data and on literature searches. We evaluated the performance of these candidate markers individually and in combination by measuring them in overlapping sets of serum (or plasma) samples from women with clinically detectable ovarian cancer and women without ovarian cancer. Based on sensitivity at high specificity, we determined that 4 of the 14 candidate markers-MUC16, WFDC2, MSLN and MMP7-warrant further evaluation in precious serum specimens collected months to years prior to clinical diagnosis to assess their utility in early detection. We also reported differences in the performance of these candidate blood markers across histological types of epithelial ovarian cancer. Conclusions By systematically analyzing the performance of candidate blood markers of ovarian cancer in distinguishing women with clinically apparent ovarian cancer from women without ovarian cancer, we identified a set of serum markers with adequate performance to warrant testing for their ability to identify ovarian cancer months to years prior to clinical diagnosis. We argued for the importance of sensitivity at high specificity and of magnitude of difference in marker levels between cases and controls as performance metrics and demonstrated the importance of stratifying analyses by histological type of ovarian cancer. Also, we discussed the limitations of studies (like this one) that use samples obtained from symptomatic women to assess potential utility in detection of disease months to years prior to clinical detection.

Influence of ovarian cancer risk status on the diagnostic performance of the serum biomarkers mesothelin, HE4, and CA125.

Objective: To evaluate the effect of ovarian cancer risk on the performance of the serum biomarkers mesothelin, human epididymis protein 4 (HE4), and CA125. Methods: We measured mesothelin, HE4, and CA125 levels from women with invasive ovarian cancer (n = 143), benign gynecologic conditions (n = 124), and controls (n = 344). Demographic, epidemiologic, reproductive, medical, and family history data were collected using a standardized questionnaire. Pedigree and BRCA 1/2 test results were used to stratify women into average and high-risk groups. The diagnostic accuracy of each biomarker was characterized using receiver operating characteristic curve methods. Results: Baseline characteristics did not vary by risk or case status. The distribution of stage and histology was similar in average and high-risk women. All three markers discriminated ovarian cancer cases from risk-matched healthy and benign controls. Marker performance did not vary by risk status. The sensitivity at 95% specificity for discriminating cases from risk-matched healthy control women in the average and high-risk groups, respectively, was 53.9% and 39.0% for mesothelin, 80.4% and 87.8% for HE4, and 79.4% and 82.9% for CA125. The performance of the markers was not as robust when cases were compared with benign controls. Area under the curve values for cases versus healthy and benign controls did not vary by risk status. Conclusions: The ability of serum mesothelin, HE4, and CA 125 levels to discriminate ovarian cancer cases from healthy and benign controls is not influenced by risk status. Our findings support the pursuit of additional studies evaluating the early detection potential of these markers in high-risk populations. (Cancer Epidemiol Biomarkers Prev 2009;18(5):1365–72)

Effects of personal characteristics on serum CA125, mesothelin, and HE4 levels in healthy postmenopausal women at high-risk for ovarian cancer.

Objective: To evaluate if serum levels of candidate ovarian cancer biomarkers vary with individual characteristics of healthy women who are likely candidates for an ovarian cancer screening program. Methods: We analyzed serum CA125, mesothelin, and HE4 levels in a sample of 155 healthy postmenopausal women at increased risk for developing ovarian cancer based on personal and family cancer history. Information on reproductive, family and medical histories, lifestyle factors, and anthropometry was collected by self-report. Twenty-two factors were examined using univariate and multiple linear regression models for the three biomarker levels. Results: In the multivariate models, CA125 levels were significantly higher in women who had used talcum powder (P = 0.02) and were lower in women who were parous (P = 0.05). Mesothelin levels were significantly higher in older women (P = 0.01) and lower in heavier women (P = 0.03). HE4 levels were higher in older women (P = 0.001) and in women who began menstruating at an older age (P = 0.03). Conclusions: CA125, mesothelin, and HE4 levels in healthy, postmenopausal women at increased risk for ovarian cancer are significantly associated with a few ovarian cancer risk factors. Since the effects of these personal characteristics on these serum markers are not large, their incorporation in screening algorithms may be unnecessary. This is true especially if a longitudinal algorithm is used because the marker level at the previous screen reflects personal characteristics such as age, body mass index, and age of menarche. Understanding the influence of personal factors on levels of novel early detection markers in healthy, unaffected women may have clinical utility in interpreting biomarker levels. (Cancer Epidemiol Biomarkers Prev 2008;17(9):2480–7)

Combining a symptoms index with CA 125 to improve detection of ovarian cancer

The current study sought to examine whether an index based on the specific pattern of symptoms commonly reported by women with ovarian cancer could be used in combination with CA 125 to improve the sensitivity or specificity of experimental methods of screening for ovarian cancer.

Potential Role of HE4 in Multimodal Screening for Epithelial Ovarian Cancer

In screening for epithelial ovarian cancer, unnecessary surgery can be reduced by limiting use of transvaginal ultrasound (TVU) to women with increasing CA125 serum levels. Replacing or augmenting TVU with measurement of a serum marker specific for malignancy might further improve screening performance. Serum samples from 112 invasive ovarian cancer patients and 706 matched control subjects from the Prostate, Lung, Colorectal, and Ovarian trial were used to evaluate human epididymis protein 4 (HE4), mesothelin, matrix metalloproteinase 7 (MMP7), SLPI, Spondin2, and insulin-like growth factor binding protein 2 (IGFBP2) for their potential use in screening. TVU results were available for a subset of 84 patients and 516 control subjects used to compare the best marker with TVU. HE4 was found to perform better than TVU as a second-line screen, confirming 27 of 39 cancers with increasing CA125 serum levels compared with 17 cancers confirmed by TVU (P = .03). Serum HE4 levels were found to increase with age and smoking status, suggesting that a longitudinal algorithm might improve its performance.

Use of yeast-secreted in vivo biotinylated recombinant antibodies (biobodies) in bead–based ELISA

Purpose: To measure circulating antigens, sandwich ELISA assays require two complementary affinity reagents. Mouse monoclonal antibodies (mAb) and polyclonal antibodies (pAb) are commonly used, but because their production is lengthy and costly, recombinant antibodies are emerging as an attractive alternative. Experimental Design: We developed a new class of recombinant antibodies called biobodies (Bb) and compared them to mAb for use in serodiagnosis. Bbs were secreted biotinylated in vivo by diploid yeast and used as affinity reagents after Ni purification. Bead-based assays for HE4 and mesothelin were developed using Bbs in combination with pAbs (Bb/pAb assays). To assess precision, reproducibility studies were done using four runs of 16 replicates at six analyte levels for each marker. Pearson correlations and receiver-operator characteristic analyses were done in 214 patient serum samples to directly compare the Bb/pAb assays to mAb assays. Diagnostic performance of the Bb/pAb assay was further assessed in an expanded set of 336 ovarian cancer cases and controls. Results: On average across analyte levels, Bb/pAb assays yielded within-run and between-run coefficients of variations of 11.7 and 23.8, respectively, for HE4 and 14.0 and 14.5, respectively, for mesothelin. In the subset (n = 214), Pearson correlations of 0.95 for HE4 and 0.92 for mesothelin were observed between mAb and Bb/pAb assays. The area under the curves for the mAb and Bb/pAb assays were not significantly different for HE4 (0.88 and 0.84, respectively; P = 0.20) or mesothelin (0.74 and 0.72, respectively; P = 0.38). Conclusion: Yeast-secreted Bbs can be used reliably in cost-effective yet highly sensitive bead–based assays for use in large validation studies.

Identifying abundant immunotherapy and other targets in solid tumors integrating RNA-seq and mass spectrometry proteomics data sets

RNA-seq and mass-spectrometry proteomics combined with growing data repositories have greatly increased the capacity to identify candidate proteins or protein sequence variants that share properties of ideal therapy targets, which include being abundant in cancer cells, absent or rare in adult organs (especially vital organs), and shared by many patient tumors. RNA-seq and fixed content arrays can identify genes that are overexpressed or misexpressed in cancer. RNA-seq is uniquely suited to identifying cancer-specific sequence variants. We review factors relevant for determining whether products of genes that are abundant or differentially abundant in RNA-seq are concordant or discordant with proteins that are identified as abundant or differentially abundant in mass-spectrometry proteomics assays.

Correction: Evaluating Serum Markers for Hormone Receptor-Negative Breast Cancer.

The third author’s name is listed incorrectly. The correct name is Maria D. Giraldez. The correct citation is: Schummer M, Thorpe J, Giraldez MD, Bergan L, Tewari M, Urban N (2015) Evaluating Serum Markers for Hormone Receptor-Negative Breast Cancer. PLoS ONE 10(11): e0142911. doi:10.1371/journal.pone.0142911