A novel, high-throughput workflow for discovery and identification of serum carrier protein-bound peptide biomarker candidates in ovarian cancer samples.

BACKGROUND Most cases of ovarian cancer are detected at later stages when the 5-year survival is approximately 15%, 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 TOF 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.

[1]  E. Diamandis Peptidomics for cancer diagnosis: present and future. , 2006, Journal of proteome research.

[2]  P. Pandolfi,et al.  A CK2-Dependent Mechanism for Degradation of the PML Tumor Suppressor , 2006, Cell.

[3]  G. Whiteley Proteomic patterns for cancer diagnosis--promise and challenges. , 2006, Molecular bioSystems.

[4]  D. Chan,et al.  Proteomics: a new diagnostic frontier. , 2006, Clinical chemistry.

[5]  G. Hortin The MALDI-TOF mass spectrometric view of the plasma proteome and peptidome. , 2006, Clinical chemistry.

[6]  S. Bhoola,et al.  Diagnosis and Management of Epithelial Ovarian Cancer , 2006, Obstetrics and gynecology.

[7]  F. Rickles Mechanisms of Cancer-Induced Thrombosis in Cancer , 2006, Pathophysiology of Haemostasis and Thrombosis.

[8]  E. Petricoin,et al.  Serum peptidome for cancer detection: spinning biologic trash into diagnostic gold. , 2005, The Journal of clinical investigation.

[9]  A. Olshen,et al.  Differential exoprotease activities confer tumor-specific serum peptidome patterns. , 2005, The Journal of clinical investigation.

[10]  I. Brewis The human plasma proteome , 2006 .

[11]  Peng-Hui Wang,et al.  Altered mRNA expressions of sialyltransferases in ovarian cancers. , 2005, Gynecologic oncology.

[12]  Kym Faull,et al.  Characterization of serum biomarkers for detection of early stage ovarian cancer , 2005, Proteomics.

[13]  Thomas Lengauer,et al.  ROCR: visualizing classifier performance in R , 2005, Bioinform..

[14]  David A Bennett,et al.  High-resolution serum proteomic profiling of Alzheimer disease samples reveals disease-specific, carrier-protein-bound mass signatures. , 2005, Clinical chemistry.

[15]  E. Petricoin,et al.  Analysis of albumin-associated peptides and proteins from ovarian cancer patients. , 2005, Clinical chemistry.

[16]  Shan Gao,et al.  Identification of differential genes in ovarian cancer using representational difference analysis of cDNA. , 2005, Chinese medical sciences journal = Chung-kuo i hsueh k'o hsueh tsa chih.

[17]  K A Baggerly,et al.  New tumor markers: CA125 and beyond , 2005, International Journal of Gynecologic Cancer.

[18]  Annette M. Molinaro,et al.  Prediction error estimation: a comparison of resampling methods , 2005, Bioinform..

[19]  E. Kohn,et al.  Ovarian cancer in the proteomics era: diagnosis, prognosis, and therapeutics targets , 2005, International Journal of Gynecologic Cancer.

[20]  S. Olewniczak,et al.  Concentration of histamine in serum and tissues of the primary ductal breast cancers in women. , 2005, Breast.

[21]  K. Coombes,et al.  Direct tandem mass spectrometry reveals limitations in protein profiling experiments for plasma biomarker discovery. , 2005, Journal of proteome research.

[22]  Hao Yu,et al.  Discovering patterns to extract protein-protein interactions from the literature: Part II , 2005, Bioinform..

[23]  M. Hung,et al.  Signaling intricacies take center stage in cancer cells. , 2005, Cancer research.

[24]  T. Colgan,et al.  Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and cICAT with multidimensional liquid chromatography and tandem mass spectrometry. , 2005, Journal of proteome research.

[25]  T. Reynolds,et al.  The role of CA125 in clinical practice , 2005, Journal of Clinical Pathology.

[26]  Emanuel F Petricoin,et al.  Importance of communication between producers and consumers of publicly available experimental data. , 2005, Journal of the National Cancer Institute.

[27]  Jeffrey S. Morris,et al.  Signal in noise: evaluating reported reproducibility of serum proteomic tests for ovarian cancer. , 2005, Journal of the National Cancer Institute.

[28]  R. Bast,et al.  Three Biomarkers Identified from Serum Proteomic Analysis for the Detection of Early Stage Ovarian Cancer , 2004, Cancer Research.

[29]  J. Yates,et al.  A model for random sampling and estimation of relative protein abundance in shotgun proteomics. , 2004, Analytical chemistry.

[30]  E. Petricoin,et al.  An investigation into the human serum “interactome” , 2004, Electrophoresis.

[31]  T. Veenstra,et al.  The Human Plasma Proteome , 2004, Molecular & Cellular Proteomics.

[32]  Emanuel F Petricoin,et al.  Serum proteomics in cancer diagnosis and management. , 2004, Annual review of medicine.

[33]  Emanuel F. Petricoin,et al.  Biomarker Amplification by Serum Carrier Protein Binding , 2004, Disease markers.

[34]  T. Veenstra,et al.  Characterization of the Low Molecular Weight Human Serum Proteome*S , 2003, Molecular & Cellular Proteomics.

[35]  E. Diamandis Point: Proteomic patterns in biological fluids: do they represent the future of cancer diagnostics? , 2003, Clinical chemistry.

[36]  Fang Wang,et al.  The human serum proteome: Display of nearly 3700 chromatographically separated protein spots on two‐dimensional electrophoresis gels and identification of 325 distinct proteins , 2003, Proteomics.

[37]  R. Bast,et al.  Status of tumor markers in ovarian cancer screening. , 2003, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[38]  Young Y. Wang,et al.  A simple affinity spin tube filter method for removing high‐abundant common proteins or enriching low‐abundant biomarkers for serum proteomic analysis , 2003, Proteomics.

[39]  B. Doğan,et al.  Expression of keratin K2e in cutaneous and oral lesions: association with keratinocyte activation, proliferation, and keratinization. , 2003, The American journal of pathology.

[40]  Ronald J. Moore,et al.  Toward a Human Blood Serum Proteome , 2002, Molecular & Cellular Proteomics.

[41]  D. Chan,et al.  Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. , 2002, Clinical chemistry.

[42]  E. Petricoin,et al.  Clinical potential of proteomics in the diagnosis of ovarian cancer , 2002, Expert review of molecular diagnostics.

[43]  E. Petricoin,et al.  Use of proteomic patterns in serum to identify ovarian cancer , 2002, The Lancet.

[44]  S Hanash,et al.  Proteomics in early detection of cancer. , 2001, Clinical chemistry.

[45]  J. Yates,et al.  Large-scale analysis of the yeast proteome by multidimensional protein identification technology , 2001, Nature Biotechnology.

[46]  R. Tibshirani,et al.  Flexible Discriminant Analysis by Optimal Scoring , 1994 .