Evaluation of serum protein profiling by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry for the detection of prostate cancer: I. Assessment of platform reproducibility.

BACKGROUND Protein expression profiling for differences indicative of early cancer has promise for improving diagnostics. This report describes the first stage of a National Cancer Institute/Early Detection Research Network-sponsored multiinstitutional evaluation and validation of this approach for detection of prostate cancer. METHODS Two sequential experimental phases were conducted to establish interlaboratory calibration and standardization of the surface-enhanced laser desorption (SELDI) instrumental and assay platform output. We first established whether the output from multiple calibrated Protein Biosystem II SELDI-ionization time-of-flight mass spectrometry (TOF-MS) instruments demonstrated acceptable interlaboratory reproducibility. This was determined by measuring mass accuracy, resolution, signal-to-noise ratio, and normalized intensity of three m/z "peaks" present in a standard pooled serum sample. We next evaluated the ability of the calibrated and standardized instrumentation to accurately differentiate between selected cases of prostate cancer and control by use of an algorithm developed from data derived from a single site 2 years earlier. RESULTS When the described standard operating procedures were established at all laboratory sites, the across-laboratory measurements revealed a CV for mass accuracy of 0.1%, signal-to-noise ratio of approximately 40%, and normalized intensity of 15-36% for the three pooled serum peaks. This was comparable to the intralaboratory measurements of the same peaks. The instrument systems were then challenged with sera from a selected group of 14 cases and 14 controls. The classification agreement between each site and the established decision algorithm were examined by use of both raw peak intensity boosting and ranked peak intensity boosting. All six sites achieved perfect blinded classification for all samples when boosted alignment of raw intensities was used. Four of six sites achieved perfect blinded classification with ranked intensities, with one site passing the criteria of 26 of 28 correct and one site failing with 19 of 28 correct. CONCLUSIONS These results demonstrate that "between-laboratory" reproducibility of SELDI-TOF-MS serum profiling approaches that of "within-laboratory" reproducibility as determined by measuring discrete m/z peaks over time and across laboratories.

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

[2]  O John Semmes,et al.  Normal, benign, preneoplastic, and malignant prostate cells have distinct protein expression profiles resolved by surface enhanced laser desorption/ionization mass spectrometry. , 2002, Clinical cancer research : an official journal of the American Association for Cancer Research.

[3]  Jeffrey S. Morris,et al.  Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments , 2004, Bioinform..

[4]  M S Pepe,et al.  Phases of biomarker development for early detection of cancer. , 2001, Journal of the National Cancer Institute.

[5]  G. Wright,et al.  Development of a novel proteomic approach for the detection of transitional cell carcinoma of the bladder in urine. , 2001, The American journal of pathology.

[6]  Kaushik Ghosh,et al.  A New Method of Predicting US and State‐Level Cancer Mortality Counts for the Current Calendar Year , 2004, CA: a cancer journal for clinicians.

[7]  D. Ransohoff Rules of evidence for cancer molecular-marker discovery and validation , 2004, Nature Reviews Cancer.

[8]  A. Jemal,et al.  Cancer Statistics, 2004 , 2004, CA: a cancer journal for clinicians.

[9]  Ruth Etzioni,et al.  Early detection: The case for early detection , 2003, Nature Reviews Cancer.

[10]  E. Petricoin,et al.  Serum proteomic patterns for detection of prostate cancer. , 2002, Journal of the National Cancer Institute.

[11]  K. Kozak,et al.  Identification of biomarkers for ovarian cancer using strong anion-exchange ProteinChips: Potential use in diagnosis and prognosis , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[12]  D. Seligson,et al.  Clinical Chemistry , 1965, Bulletin de la Societe de chimie biologique.

[13]  Sudhir Srivastava,et al.  The early detection research network surface-enhanced laser desorption and ionization prostate cancer detection study: A study in biomarker validation in genitourinary oncology. , 2004, Urologic oncology.

[14]  J. Crowley,et al.  Prevalence of prostate cancer among men with a prostate-specific antigen level < or =4.0 ng per milliliter. , 2004, The New England journal of medicine.

[15]  C. Paweletz,et al.  New approaches to proteomic analysis of breast cancer , 2001, Proteomics.

[16]  P. Schellhammer,et al.  Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men. , 2002, Cancer research.

[17]  X. Xiao,et al.  Development of Proteomic Patterns for Detecting Lung Cancer , 2004, Disease markers.

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

[19]  L. Liotta,et al.  Proteomic Patterns of Nipple Aspirate Fluids Obtained by SELDI-TOF: Potential for New Biomarkers to Aid in the Diagnosis of Breast Cancer , 2002, Disease markers.

[20]  D. McCarthy,et al.  Serum Protein Expression Profiling for Cancer Detection: Validation of a SELDI-Based Approach for Prostate Cancer , 2004, Disease markers.

[21]  E. Diamandis Re: diagnostic potential of serum proteomic patterns in prostate cancer. , 2004, The Journal of urology.

[22]  J. Potter,et al.  A data-analytic strategy for protein biomarker discovery: profiling of high-dimensional proteomic data for cancer detection. , 2003, Biostatistics.

[23]  William E Grizzle,et al.  Clarification in the point/counterpoint discussion related to surface-enhanced laser desorption/ionization time-of-flight mass spectrometric identification of patients with adenocarcinomas of the prostate. , 2004, Clinical chemistry.

[24]  Bao-Ling Adam,et al.  Diagnostic potential of serum proteomic patterns in prostate cancer. , 2003, The Journal of urology.

[25]  A. Vlahou,et al.  A novel approach toward development of a rapid blood test for breast cancer. , 2003, Clinical breast cancer.

[26]  Y. Yasui,et al.  An Automated Peak Identification/Calibration Procedure for High-Dimensional Protein Measures From Mass Spectrometers , 2003, Journal of biomedicine & biotechnology.

[27]  J. Moul,et al.  Diagnostic potential of prostate-specific antigen expressing epithelial cells in blood of prostate cancer patients. , 2003, Clinical cancer research : an official journal of the American Association for Cancer Research.

[28]  H. Kumar Re: histological changes of minimally invasive procedures for the treatment of benign prostatic hyperplasia and prostate cancer: clinical implications. , 2004, The Journal of urology.

[29]  T. Zhukov,et al.  Discovery of distinct protein profiles specific for lung tumors and pre-malignant lung lesions by SELDI mass spectrometry. , 2003, Lung cancer.

[30]  Min Zhan,et al.  A data review and re-assessment of ovarian cancer serum proteomic profiling , 2003, BMC Bioinformatics.

[31]  P. Schellhammer,et al.  Boosted decision tree analysis of surface-enhanced laser desorption/ionization mass spectral serum profiles discriminates prostate cancer from noncancer patients. , 2002, Clinical chemistry.

[32]  T. Yip,et al.  Comprehensive proteomic profiling identifies serum proteomic signatures for detection of hepatocellular carcinoma and its subtypes. , 2003, Clinical chemistry.

[33]  D. R. Lewis,et al.  Cancer survival and incidence from the Surveillance, Epidemiology, and End Results (SEER) program. , 2003, The oncologist.

[34]  O John Semmes,et al.  Serum Protein Profiles to Identify Head and Neck Cancer , 2004, Clinical Cancer Research.

[35]  K. Lillemoe,et al.  Identification of hepatocarcinoma-intestine-pancreas/pancreatitis-associated protein I as a biomarker for pancreatic ductal adenocarcinoma by protein biochip technology. , 2002, Cancer research.

[36]  Erika Check,et al.  Proteomics and cancer: Running before we can walk? , 2004, Nature.

[37]  B. Adam,et al.  Identification of patients with head and neck cancer using serum protein profiles. , 2004, Archives of otolaryngology--head & neck surgery.

[38]  E. Diamandis Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems. , 2004, Journal of the National Cancer Institute.

[39]  D. Chan,et al.  Serum Diagnosis of Pancreatic Adenocarcinoma Using Surface-Enhanced Laser Desorption and Ionization Mass Spectrometry , 2004, Clinical Cancer Research.

[40]  T. Kang,et al.  Pattern analysis of serum proteome distinguishes renal cell carcinoma from other urologic diseases and healthy persons , 2003, Proteomics.