Received on September 29, 2006
Accepted on March 27, 2007

Proteomics and Protein Markers

A Novel, High-Throughput Workflow for Discovery and Identification of Serum Carrier Protein-Bound Peptide Biomarker Candidates in Ovarian Cancer Samples

¹ PerkinElmer Life and Analytical Sciences, Wellesley, MA
² Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA
³ Clinical Proteomics Reference Laboratory, Gaithersburg, MD
⁴ Department of Pathology, Division of Translational Pathology, University of Texas Southwestern Medical Center, Dallas, TX
⁵ Nonlinear Dynamics, Cuthbert House, All Saints, Newcastle upon Tyne, United Kingdom
⁶ Harvard Partners, Cambridge, MA

^* To whom correspondence should be addressed. E-mail: mary.lopez{at}perkinelmer.com.

Background: Most cases of ovarian cancer are detected at later stages when the 5-year survival is |mf15\%, but 5-year survival approaches 90\% when the cancer is detected early (stage I), To use mass spectrometry (MS) of serum proteins for early detection, a seamless workflow is needed that provides an opportunity for rapid profiling along with direct identification of the underpinning ions.

Methods: We used carrier protein-bound affinity enrichment of serum samples directly coupled with MALDI orthagonal time-of-flight MS profiling to rapidly search for potential ion signatures that contained discriminatory power. These ions were subsequently directly subjected to tandem MS for sequence identification.

Results: We discovered several biomarker panels that enabled differentiation of stage I ovarian cancer from unaffected (age-matched) patients with no evidence of ovarian cancer, with positive results in >93% of samples from patients with disease-negative results and in 97% of disease-free controls. The carrier protein-based approach identified additional protein fragments, many from low-abundance proteins or proteins not previously seen in serum.

Conclusions: This workflow system using a highly reproducible, high-resolution MALDI-TOF platform enables rapid enrichment and profiling of large numbers of clinical samples for discovery of ion signatures and integration of direct sequencing and identification of the ions without need for additional offline, time-consuming purification strategies.