Urinary biomarker profiling in transitional cell carcinoma

Urinary biomarkers or profiles that allow noninvasive detection of recurrent transitional cell carcinoma (TCC) of the bladder are urgently needed. We obtained duplicate proteomic (SELDI) profiles from 227 subjects (118 TCC, 77 healthy controls and 32 controls with benign urological conditions) and used linear mixed effects models to identify peaks that are differentially expressed between TCC and controls and within TCC subgroups. A Random Forest classifier was trained on 130 profiles to develop an algorithm to predict the presence of TCC in a randomly selected initial test set (n = 54) and an independent validation set (n = 43) several months later. Twenty two peaks were differentially expressed between all TCC and controls (p < 10−7). However potential confounding effects of age, sex and analytical run were identified. In an age‐matched sub‐set, 23 peaks were differentially expressed between TCC and combined benign and healthy controls at the 0.005 significance level. Using the Random Forest classifier, TCC was predicted with 71.7% sensitivity and 62.5% specificity in the initial set and with 78.3% sensitivity and 65.0% specificity in the validation set after 6 months, compared with controls. Several peaks of importance were also identified in the linear mixed effects model. We conclude that SELDI profiling of urine samples can identify patients with TCC with comparable sensitivities and specificities to current tumor marker tests. This is the first time that reproducibility has been demonstrated on an independent test set analyzed several months later. Identification of the relevant peaks may facilitate multiplex marker assay development for detection of recurrent disease. © 2006 Wiley‐Liss, Inc.

[1]  A. Lopez‐Beltran,et al.  Non-invasive urothelial neoplasms: according to the most recent WHO classification. , 2004, European urology.

[2]  M. Soloway,et al.  Current bladder tumor tests: does their projected utility fulfill clinical necessity? , 2001, The Journal of urology.

[3]  Richard A. Szucs,et al.  TNM Classification of Malignant Tumors. 5th ed , 1998 .

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

[5]  Douglas M. Bates,et al.  LINEAR AND NONLINEAR MIXED-EFFECTS MODELS , 1998 .

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

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

[8]  D. Shackley,et al.  The community‐based morbidity of flexible cystoscopy , 2002, BJU international.

[9]  O John Semmes,et al.  Protein profiling of urine in the diagnosis of bladder cancer , 2005, Nature Clinical Practice Urology.

[10]  Jean-Charles Sanchez,et al.  Proteomics: new perspectives, new biomedical opportunities , 2000, The Lancet.

[11]  G. Izmirlian,et al.  Application of the Random Forest Classification Algorithm to a SELDI‐TOF Proteomics Study in the Setting of a Cancer Prevention Trial , 2004, Annals of the New York Academy of Sciences.

[12]  James M. Kozlowski,et al.  NCCN Urothelial Cancer Practice Guidelines , 1998 .

[13]  J. Barrett,et al.  Influences of blood sample processing on low-molecular-weight proteome identified by surface-enhanced laser desorption/ionization mass spectrometry. , 2005, Clinical chemistry.

[14]  D. Driesch,et al.  ProteinChip technology reveals distinctive protein expression profiles in the urine of bladder cancer patients. , 2005, European urology.

[15]  Alex Pothen,et al.  Computational protein biomarker prediction: a case study for prostate cancer , 2004, BMC Bioinformatics.

[16]  A. Bateman,et al.  The levels and biologic action of the human neutrophil granule peptide HP-1 in lung tumors , 1992, Peptides.

[17]  Jeffrey S. Morris,et al.  The importance of experimental design in proteomic mass spectrometry experiments: some cautionary tales. , 2005, Briefings in functional genomics & proteomics.

[18]  Stephen Alexander,et al.  Proteomic Analysis to Identify Breast Cancer Biomarkers in Nipple Aspirate Fluid , 2004, Clinical Cancer Research.

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

[20]  Marije Deutekom,et al.  Tumor markers in the diagnosis of primary bladder cancer. A systematic review. , 2003, The Journal of urology.

[21]  S. Weinberger,et al.  Recent advancements in surface‐enhanced laser desorption/ionization‐time of flight‐mass spectrometry , 2000, Electrophoresis.

[22]  K. Rodland.  Proteomics and cancer diagnosis: the potential of mass spectrometry. , 2004, Clinical biochemistry.

[23]  M. Deeg,et al.  Human α-Defensins HNPs-1, -2, and -3 in Renal Cell Carcinoma : Influences on Tumor Cell Proliferation , 2002 .

[24]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[25]  S. Loening,et al.  Superficial bladder cancer: progression and recurrence. , 1983, The Journal of urology.

[26]  Ming Xu,et al.  Using tree analysis pattern and SELDI-TOF-MS to discriminate transitional cell carcinoma of the bladder cancer from noncancer patients. , 2005, European urology.

[27]  Bill C. White,et al.  Proteomic patterns of tumour subsets in non-small-cell lung cancer , 2003, The Lancet.

[28]  P. Nickerson,et al.  Urine protein profiling with surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry. , 2004, Kidney international.

[29]  M. Guan,et al.  Tree analysis of mass spectral urine profiles discriminates transitional cell carcinoma of the bladder from noncancer patient. , 2004, Clinical biochemistry.

[30]  B. Liu,et al.  Sensitivity and specificity of NMP-22, telomerase, and BTA in the detection of human bladder cancer. , 1999, Urology.

[31]  T. Ratliff.  Urine markers for bladder cancer surveillance: a systematic review. , 2005, The Journal of urology.

[32]  Yi-ding Chen,et al.  World Journal of Gastroenterology , 2022 .

[33]  Robert Tibshirani,et al.  The Use of Plasma Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry Proteomic Patterns for Detection of Head and Neck Squamous Cell Cancers , 2004, Clinical Cancer Research.

[34]  N. Dubrawsky.  Cancer statistics , 1989, CA: a cancer journal for clinicians.

[35]  Shin-Yoon Kim,et al.  Establishment of a near‐standard two‐dimensional human urine proteomic map , 2004, Proteomics.

[36]  C. Roehrborn,et al.  Sensitivity and specificity of commonly available bladder tumor markers versus cytology: results of a comprehensive literature review and meta-analyses. , 2003, Urology.

[37]  D. Chan,et al.  Bioinformatics strategies for proteomic profiling. , 2004, Clinical biochemistry.

[38]  P. Selby,et al.  Proteomic profiling of urinary proteins in renal cancer by surface enhanced laser desorption ionization and neural-network analysis: identification of key issues affecting potential clinical utility. , 2003, Cancer research.

[39]  A Pollack,et al.  NCCN urothelial cancer practice guidelines. National Comprehensive Cancer Network. , 1998, Oncology.

[40]  S. Daneshmand,et al.  New molecular markers for bladder cancer detection , 2004, Current opinion in urology.

[41]  S. Wilczynski,et al.  The accuracy of urinary cytology in daily practice , 1999, Cancer.

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

[43]  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.

[44]  Claus W Heizmann,et al.  Analysis of minor hemoglobins by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. , 2005, Clinical chemistry.

[45]  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.

[46]  B. Konety,et al.  Urine based markers of urological malignancy. , 2002, The Journal of urology.