[Show abstract][Hide abstract] ABSTRACT: 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.
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.
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 > or = 4, 2-4, and <2 years before diagnosis, respectively).
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.
Journal of the National Cancer Institute 01/2010; 102(1):26-38. DOI:10.1093/jnci/djp438 · 12.58 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: A group of investigators met at a Specialized Programs of Research Excellence Workshop to discuss key issues in the translation of biomarker discovery to the development of useful laboratory tests for cancer care. Development and approval of several new markers and technologies have provided informative examples that include more specific markers for prostate cancer, more sensitive tests for ovarian cancer, more objective analysis of tissue architecture and an earlier indication of response to treatment in breast cancer. Although there is no clear paradigm for biomarker development, several principles are clear. Marker development should be driven by clinical needs, including early cancer detection, accurate pretreatment staging, and prediction of response to treatment, as well as monitoring disease progression and response to therapy. Development of a national repository that uses carefully preserved, well-annotated tissue specimens will facilitate new marker development. Reference standards will be an essential component of this process. Both hospital-based and commercial laboratories can play a role in developing biomarkers from discovery to test validation. Partnering of academe and industry should occur throughout the process of biomarker development. The National Cancer Institute is in a unique position to bring together academe, industry, and the Food and Drug Administration to (a) define clinical needs for biomarkers by tumor type, (b) establish analytic and clinical paradigms for biomarker development, (c) discuss ways in which markers from different companies might be evaluated in combination, (d) establish computational methods to combine data from multiple biomarkers, (e) share information regarding promising markers developed in National Cancer Institute-supported programs, and (f) exchange data regarding new platforms and techniques that can accelerate marker development.
Clinical Cancer Research 10/2005; 11(17):6103-8. DOI:10.1158/1078-0432.CCR-04-2213 · 8.72 Impact Factor