Profiling Bladder Cancer Using Targeted Antibody Arrays
2006; Elsevier BV; Volume: 168; Issue: 1 Linguagem: Inglês
10.2353/ajpath.2006.050601
ISSN1525-2191
AutoresMarta Sänchez‐Carbayo, Nicholas D. Socci, Juan José Lozano, Brian B. Haab, Carlos Cordon‐Cardo,
Tópico(s)Monoclonal and Polyclonal Antibodies Research
ResumoBladder cancer is a common malignancy requiring a high degree of surveillance because of the frequent recurrences and the poor clinical outcome of invasive disease. To date, serum biomarkers for bladder cancer lack optimal sensitivity and specificity to assist in diagnosis and disease categorization. Here, we designed antibody arrays for bladder cancer by selecting antibodies against targets differentially expressed in bladder tumors. Serum protein profiles measured by an antibody array containing 254 antibodies discriminated bladder cancer patients from controls (n = 95) with a correct classification rate of 93.7%. A second independent antibody array containing 144 antibodies revealed that protein profiles provide predictive information by stratifying patients with bladder tumors (n = 37) based on their overall survival (P = 0.0479). In addition, serum proteins, such as c-met, that were top ranked at identifying bladder cancer patients were associated with pathological stage, tumor grade, and survival when validated by immunohistochemistry of tissue microarrays containing bladder tumors (n = 173). This study provides experimental evidence for the use of several integrated technologies strengthening the process of biomarker discovery. Serum protein profiles obtained by antibody arrays represent comprehen-sive means for bladder cancer diagnosis and clinical outcome stratification, which could potentially assist in selection of cancer patients who would benefit from early, individualized therapeutic intervention. Bladder cancer is a common malignancy requiring a high degree of surveillance because of the frequent recurrences and the poor clinical outcome of invasive disease. To date, serum biomarkers for bladder cancer lack optimal sensitivity and specificity to assist in diagnosis and disease categorization. Here, we designed antibody arrays for bladder cancer by selecting antibodies against targets differentially expressed in bladder tumors. Serum protein profiles measured by an antibody array containing 254 antibodies discriminated bladder cancer patients from controls (n = 95) with a correct classification rate of 93.7%. A second independent antibody array containing 144 antibodies revealed that protein profiles provide predictive information by stratifying patients with bladder tumors (n = 37) based on their overall survival (P = 0.0479). In addition, serum proteins, such as c-met, that were top ranked at identifying bladder cancer patients were associated with pathological stage, tumor grade, and survival when validated by immunohistochemistry of tissue microarrays containing bladder tumors (n = 173). This study provides experimental evidence for the use of several integrated technologies strengthening the process of biomarker discovery. Serum protein profiles obtained by antibody arrays represent comprehen-sive means for bladder cancer diagnosis and clinical outcome stratification, which could potentially assist in selection of cancer patients who would benefit from early, individualized therapeutic intervention. Bladder cancer is a common malignancy requiring a high surveillance because of the frequent recurrences and the poor clinical outcome when tumors progress into invasive disease. The diagnosis and follow-up of patients with bladder tumors is based on the information provided by cystoscopy in combination with urinary cytology.1Reuter VE Melamed MR The lower urinary tract.in: Sternberg SS Diagnostic Surgical Pathology. Raven Press, New York1989: 1355-1392Google Scholar Noninvasive procedures can assist in early detection, cancer patient surveillance and risk assessment. Availability of cancer biomarkers to be measured in body fluids is critical for the management of these patients. Many tumor markers have been evaluated in body fluids for the detection and monitoring of the disease.2Lotan Y Roehrborn CG Cost-effectiveness of a modified care protocol substituting bladder tumor markers for cystoscopy for the follow-up of patients with transitional cell carcinoma of the bladder, a decision analytical approach.J Urol. 2002; 167: 75-79Abstract Full Text Full Text PDF PubMed Scopus (87) Google Scholar, 3Quek ML Quinn DI Daneshmand S Stein JP Molecular prognostication in bladder cancer—a current perspective.Eur J Cancer. 2003; 39: 1501-1510Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar However, none of the biomarkers evaluated in serum to date has provided sufficient sensitivity and specificity for the early detection of superficial bladder cancer or favorable efficacy for predicting relapses and response to chemotherapy in patients with advanced disease. Thus, the development of alternative serum biomarkers for diagnostic and prognostic stratification is of clinical importance for the management of patients with bladder cancer. The genetic and resulting protein alterations are primary determinants steering neoplastic transformation and tumor progression. The advent of high-throughput DNA microarrays is accelerating the discovery of cancer targets.4Dyrskjot L Thykjaer T Kruhoffer M Jensen JL Marcussen N Hamilton-Dudoit S Wolf H Orntoft TF Identifying distinct classes of bladder carcinoma using microarrays.Nat Genet. 2003; 33: 90-96Crossref PubMed Scopus (428) Google Scholar, 5Thykjaer T Workman C Kruhoffer M Demtroder K Wolf H Andersen LD Frederiksen CM Knudsen S Orntoft TF Identification of gene expression patterns in superficial and invasive human bladder cancer.Cancer Res. 2001; 61: 2492-2499PubMed Google Scholar, 6Sanchez-Carbayo M Socci ND Charytonowicz E Lu M Prystowsky M Childs G Cordon-Cardo C Molecular profiling of bladder cancer using cDNA microarrays, defining histogenesis and biological phenotypes.Cancer Res. 2002; 62: 6973-6980PubMed Google Scholar, 7Sanchez-Carbayo M Socci N Lozano JJ Li W Belbin TJ Prystowsky MB Ortiz AR Childs G Cordon-Cardo C Gene discovery in bladder cancer progression using cDNA microarrays.Am J Pathol. 2003; 163: 505-516Abstract Full Text Full Text PDF PubMed Scopus (162) Google Scholar These targets cannot only assist at characterizing the biology underlining tumorigenesis and progression but can also identify biomarkers for the clinical management of cancer patients. Direct and comparative fluorescent labeling techniques can measure the relative abundance of gene sequences. Moreover, they can also estimate the presence of antigens by antibody solutions printed on derivatized surfaces.8Guschin D Yershov G Zaslavsky A Gemmell A Shick V Proudnikov D Arenkov P Mirzabekov A Manual manufacturing of oligonucleotide DNA, and protein microchips.Anal Biochem. 1997; 250: 203-211Crossref PubMed Scopus (236) Google Scholar, 9Arenkov P Kukhtin A Gemmell A Voloshchuk S Chupeeva V Mirzabekov A Protein microchips, use for immunoassay and enzymatic reactions.Anal Biochem. 2000; 278: 123-131Crossref PubMed Scopus (488) Google Scholar, 10MacBeath G Schreiber SL Printing proteins as microarrays for high-throughput function determination.Science. 2002; 289: 1760-1763Google Scholar, 11Haab BB Dunham MJ Brown PO Protein microarrays for highly parallel detection and quantitation of specific proteins and antibodies in complex solutions.Genome Biol. 2001; 2 (RESEARCH0004.1–4.13)Crossref PubMed Google Scholar Antibody arrays are feasible for clinical applications, such as detecting neoplastic or autoimmune diseases, using tissues and body fluids.11Haab BB Dunham MJ Brown PO Protein microarrays for highly parallel detection and quantitation of specific proteins and antibodies in complex solutions.Genome Biol. 2001; 2 (RESEARCH0004.1–4.13)Crossref PubMed Google Scholar, 12Knezevic V Leethanakul C Bichsel VE Worth JM Prabhu VV Gutkind JS Liotta LA Munson PJ Petricoin III, EF Krizman DB: Proteomic profiling of the cancer microenvironment by antibody arrays.Proteomics. 2001; 1: 1271-1278Crossref PubMed Scopus (285) Google Scholar, 13Huang RP Huang R Fan Y Lin Y Simultaneous detection of multiple cytokines from conditioned media and patient's sera by an antibody-based protein array system.Anal Biochem. 2001; 294: 55-62Crossref PubMed Scopus (220) Google Scholar, 14Schweitzer B Roberts S Grimwade B Shao W Wang M Fu Q Shu Q Laroche I Zhou Z Tchernev VT Christiansen J Velleca M Kingsmore SF Multiplexed protein profiling on microarrays by rolling-circle amplification.Nature Biotechnol. 2002; 20: 359-365Crossref Scopus (499) Google Scholar, 15Robinson WH DiGennaro C Hueber W Haab BB Kamachi M Dean EJ Fournel S Fong D Genovese M Neuman de Vegvar HE Skriner K Hirschberg DL Morris RI Muller S Pruijn GJ van Venrooij WJ Smolen JS Brown PO Steinman L Utz PJ Autoantigen microarrays for multiplex characterization of autoantibody responses.Nat Med. 2002; 8: 295-301Crossref PubMed Scopus (643) Google Scholar, 16Miller JC Zhou H Kwekel J Cavallo R Burke J Butler EB Teh BS Haab BB Antibody microarray profiling of human prostate cancer sera: antibody screening and identification of potential biomarkers.Proteomics. 2003; 3: 56-63Crossref PubMed Scopus (353) Google Scholar The main goal of this study is to test whether targets characteristic of bladder tumors obtained by gene expression analyses, can detect and stratify bladder cancer using specific custom-made antibody arrays on serum specimens of patients with uroepithelial tumors (see experimental design, Figure 1). Tissues from 56 bladder tissues belonging to two patients with superficial bladder cancer (pT1 lesions) and 26 patients with invasive bladder tumors (pT2+) and their corresponding normal urothelium were collected by cystectomy or cystoprostatectomy under institutional review board approval at Memorial Sloan-Kettering Cancer Center. The clinicohistopathological features of these 28 patients with bladder cancer are available as Supplementary Table 1A at http://ajp.amjpathol.org. Macrodissection of OCT-embedded tissue blocks was performed to ensure a minimum of 75% of normal urothelial and tumor cells for each type of specimen, respectively. Total RNA was extracted using TRIzol (Life Technologies, Rockville, MD), and purification with RNeasy columns (Qiagen, Valencia, CA). RNA quality was evaluated based on 260/280 ratios of absorbances and by gel analysis using an Agilent 2100 bioanalyzer (Agilent Technologies, Palo Alto, CA). Complementary DNA of the 56 analyzed specimens was synthesized from 1.5 μg of total RNA using a T7 promoter-tagged oligo-dT primer. RNA target was synthesized by in vitro transcription and labeled with biotinylated nucleotides (Enzo Biochem, Farmingdale, NY). Labeled target was hybridized on GeneChip test 3 arrays (Affymetrix, Santa Clara, CA) to assess the quality of the sample before hybridizing onto the human genome U133A arrays including 22,283 probes representing known genes and expressed sequence tags (Affymetrix), as previously reported.17Sanchez-Carbayo M Saint F Lozano JJ Viale A Cordon-Cardo C Comparison of gene expression profiles in laser-microdissected, nonembedded, and OCT-embedded tumor samples by oligonucleotide microarray analysis.Clin Chem. 2003; 49: 2096-2100Crossref PubMed Scopus (11) Google Scholar Scanned image files were visually inspected for artifacts and analyzed using Affymetrix Microarray Suite 5.0 (MAS 5.0). Expression values of each array were multiplicatively scaled to have an average expression of 500 at least across the central 95% of all genes on the array. Signal was used as the primary measure of expression level, and detection was retained as a complementary measure. Final ranking to obtain genes differentially expressed among paired normal urothelium and bladder tumors was determined using t-test, estimating also the false-positive rates.18Keselman HJ Cribbie R Holland B Controlling the rate of type I error over a large set of statistical tests.Br J Math Stat Psychol. 2002; 55: 27-39Crossref PubMed Scopus (117) Google Scholar Only probes providing P values lower than 0.001 were considered for further analyses related to antibody selection for antibody arrays. Sera were collected from 95 individuals representing 58 controls and 37 patients with bladder cancer. Control specimens were selected to evaluate the specificity of the protein profiles in a variety of healthy, benign urological conditions and other solid and hematological tumors. These included healthy donors (H, n = 18), pregnant women (P, n = 2), patients with benign conditions such as benign prostatic hyperplasia (BPH, n = 8), kidney calculi (KC, n = 3), urinary tract infections (UTI, n = 5), and patients with other malignancies such as prostate (PC, n = 8), breast (BRC, n = 6), colon (CC, n = 2), and ovarian (OC, n = 1) carcinomas, as well as multiple myeloma (MM, n = 3) and lymphoblastic leukemia (LL, n = 2). Clinicopathological features of the 37 patients with bladder cancer are available in Table 1, and information about the diagnosis of the controls in Supplementary Table 1B at http://ajp.amjpathol.org. Review of clinical reports of control individuals revealed that none of them had bladder cancer or industrial exposures. Serum samples belonging to patients with bladder cancer and controls were collected at Memorial Sloan-Kettering Cancer Center and the "Hospital Universitario de Salamanca," Spain, following institutional review board requirements of these institutions.Table 1Clinical Information of the Bladder Cancer Patients Utilized for Serum Profiling Using Custom-Made Antibody ArraysCaseSet 1 IDSet 2 IDStatusTimeAgeSexStageGradeNodeVICISSQ1000-B59669A59705ANED2464MPT2HighNoNoYesNo1001-B59669B59705BNED6.742MPTAHighNoNoNoNo1002-B59668A59706ADOD458FPT3BHighYesYesYesYes1003-B59668B59706BNED20.264MPT3BHighYesNoYesNo1004-B59764A59707ANED11.768MPT1HighNoNoNoNo1008-B59764B59707BNED21.843MPTISHighNoNoYesNo1009-B59763A59708ANED2069MPTISHighNoNoYesNo1011-B59763B59708BNED22.378FPT3BHighNoNoYesYes1012-B59762A59709ANED19.869MPTAHighNoNoNoNo1013-B59762B59709BNED1975MPT1HighNoNoNoNo1014-B59667A59710ANED2273MPT1HighNoNoYesNo1015-B59667B59710BNED1969FPT2HighNoNoYesNo1016-B59666A59711ANED21.266FPT4HighYesYesNoYes1017-B59666B59711BNED2165FPTISHighNoNoYesNo1018-B59665A59712ANED22.261MPTALowNoNoNoNo1019-B59665B59712BNED19.868MPT3BHighNoNoNoNo1020-B59761A59713ANED13.475MPT1HighNoNoNoNo1021-B59761B59713BNED1670FPT1HighYesNoYesNo17161-B59752A57850ADOD #presenting carcinoma in situ, tumor progression, and dying of bladder cancer. The other patient38.271MPTAHighNoNoYesNo17162-B59757A59718ADOD5275MPT1HighNoNoNoNo17168-B59753B59722BDOD8.774FPT3BHighYesYesYesNo17195-B59759B59716BDOD31.749MPT1HighNoNoNoNo17199-B59755B59720BNED25.363MPTISHighNoNoYesNo17208-B59754B59721BDOD38.779MPTISHighNoNoYesYes17224-B59754A59721ADOD6.880MPTISHighYesNoYesYes17229-B59755A59720ANED96.664MPT3AHighNoNoNoNo17230-B59753A59722ANED56.162MPTAHighNoNoNoNo17231-B59756B59719BDOD5.567MPT3BHighNoYesYesYes17237-B59757B59718BDOD *had a high grade Ta, recurred, and died of the disease.3679MPTALowNoNoNoNo17238-B59756A59719ADOD29.253FPTISHighNoNoYesNo17240-B59758B59717BDOD260MPT1HighYesYesYesYes17242-B59758A59717ADOD24.374MPT1HighNoNoYesNo17246-B59759A59716ANED93.667MPTALowNoNoNoNo17251-B59746B59715BNED3670MPTALowNoNoNoNo17267-B59746A59715ADOD9.450MPT4HighYesYesYesYes17270-B59760A59714ANED87.275MPTISLowNoNoYesNo17280-B59760B59714BDOD2452MPTISHighNoNoYesNoThe table includes the identification of the bladder cancer cases in each set of antibody arrays (set 1 ID and set 2 ID), their overall survival status (NED, no evidence of disease; DOD, dead of disease), follow-up time (months), age (years), sex (F, female; M, male), histopathological stage, tumor grade, as well as the presence of lymph node metastases, vascular invasion (VI), carcinoma in situ (CIS), and squamous differentiation (SQ). Two patients with Ta lesions died of disease; one of them# presenting carcinoma in situ, tumor progression, and dying of bladder cancer. The other patient* had a high grade Ta, recurred, and died of the disease. Open table in a new tab The table includes the identification of the bladder cancer cases in each set of antibody arrays (set 1 ID and set 2 ID), their overall survival status (NED, no evidence of disease; DOD, dead of disease), follow-up time (months), age (years), sex (F, female; M, male), histopathological stage, tumor grade, as well as the presence of lymph node metastases, vascular invasion (VI), carcinoma in situ (CIS), and squamous differentiation (SQ). Two patients with Ta lesions died of disease; one of them Antibodies were obtained by purchasing from different companies and as a result of contributions from collaborators. The specific antibodies and suppliers printed on each set of arrays are listed in Supplementary Table 2 at http://ajp.amjpathol.org. Antibodies that were supplied in ascites fluid or antisera were purified using Protein A beads (Affi-Gel Protein A MAPS kit; Bio-Rad, Hercules, CA) according to the manufacturer's protocol. Antibody solutions (10 to 15 μl each) of 100 to 200 μg/ml in 1× phosphate-buffered saline (PBS) were prepared in polypropylene 384-well microtiter plates (Genetix, Boston, MA). The replicate printing pattern was differentially designed in each set of antibody arrays. Antibodies were spotted at least in duplicate in the first printing set of arrays designed for screening purposes and at least in triplicate in the second set of arrays designed for validation purposes. Antibodies against proteins commonly expressed in serum, such as immunoglobulin isotypes, albumin, or C-reactive protein, were used as internal controls. Several antibodies against different epitopes for certain targets were printed onto the microscope slides using a custom-built robotic arrayer. The first set of antibody arrays included 254 antibodies against 183 targets with 768 spots. The selection of the antibodies for the first printing set was based on the top differentially expressed genes between bladder tumors and normal urothelium, given by the U133A expression arrays. Availability of antibodies to differentially expressed transcripts restricted the inclusion of reagents against genes of interest. To compensate for the potential issue of field effect given by the comparison of bladder tumors and paired normal urothelium, other gene profiling analyses were examined as well.6Sanchez-Carbayo M Socci ND Charytonowicz E Lu M Prystowsky M Childs G Cordon-Cardo C Molecular profiling of bladder cancer using cDNA microarrays, defining histogenesis and biological phenotypes.Cancer Res. 2002; 62: 6973-6980PubMed Google Scholar, 7Sanchez-Carbayo M Socci N Lozano JJ Li W Belbin TJ Prystowsky MB Ortiz AR Childs G Cordon-Cardo C Gene discovery in bladder cancer progression using cDNA microarrays.Am J Pathol. 2003; 163: 505-516Abstract Full Text Full Text PDF PubMed Scopus (162) Google Scholar Information regarding the differentially expressed targets given by the U133A gene expression analyses and related antibodies selected for the antibody arrays is provided in Supplementary Table 3 at http://ajp.amjpathol.org. The second set of antibody arrays included 144 antibodies against 114 targets with 366 spots. The selection of these antibodies was based on the presence of signal in the first printing set of arrays in at least 50% of the sera from patients with bladder cancer. Antibodies were printed on nitrocellulose FAST slides (Schleicher & Schuell, Keene, NH) using a robotic arrayer at room temperature with ∼45% humidity. The slides were then incubated in a humidified chamber with saturated NaCl solution overnight at room temperature and then rinsed with PBST 0.5% (1× PBS, 0.5% Tween-20). Block of the slides was performed with 1% bovine serum albumin in PBST 0.5% before rinsing with PBST 0.5% and spinning dry. Sample labeling was performed using a rolling circle amplification protocol, detailed below.14Schweitzer B Roberts S Grimwade B Shao W Wang M Fu Q Shu Q Laroche I Zhou Z Tchernev VT Christiansen J Velleca M Kingsmore SF Multiplexed protein profiling on microarrays by rolling-circle amplification.Nature Biotechnol. 2002; 20: 359-365Crossref Scopus (499) Google Scholar In both sets of antibody arrays experiments, the reference, labeled with Cy5, consisted of two pools containing equal amounts of each of the serum specimens used in each of the printing sets. One aliquot from each of the serum samples was labeled with digoxigenin (Molecular Probes, New Haven, CT), and another aliquot was labeled with biotin (Molecular Probes). Each serum aliquot was diluted 1:20 with 200 mmol/L carbonate buffer at pH 8.3, and a 1/20 vol of 6.7 mmol/L N-hydroxysuccinimide ester-linked biotin or digoxigenin in dimethyl sulfoxide was added. After the reactions proceeded for 2 hours on ice, a 1/20 vol of 1 mol/L Tris-HCl (pH 8.0) was added to each tube to quench the reactions, and the solutions were allowed to sit 20 minutes. The unreacted dye was removed by passing each solution through a size-exclusion chromatography spin column (Bio-Spin P6, Bio-Rad) using 6000 d as the molecular weight cutoff. Digoxigenin-labeled samples were pooled, and equal amounts of the pool were transferred to each of the biotin-labeled samples. Each dye-labeled protein solution was supplemented with nonfat milk to a final concentration of 3%, Tween-20 to a final concentration of 0.1%, and 1× PBS to yield a final serum dilution of 1:100. Each labeled serum sample mix (100 μl) was incubated on a microarray with gentle rocking at room temperature for 2 hours. The microarrays were rinsed briefly in PBST 0.1% to remove the sample, washed three times for 10 minutes each in PBST 0.1%, and dried by centrifugation. The following reagents specific for RCA detection were kindly provided by Molecular Staging, Inc. (New Haven, CT): anti-biotin antibody covalently conjugated to a 22-base oligonucleotide (primer 1), anti-digoxigenin antibody covalently conjugated to a different 28-base oligonucleotide (primer 4.2), 81-base circular DNA (circle 1) with a portion complementary to primer 1, and 80-base circular DNA (circle 4.2) with a portion complementary to primer 4.2. The microarrays were incubated for 1 hour at room temperature with a solution containing 75 nmol/L circle 1, 75 nmol/L circle 4.2, 1.0 μg/ml primer 1-conjugated anti-biotin, and 1.0 μg/ml primer 4.2-conjugated anti-digoxigenin in PBST 0.1% with 1 mmol/L ethylenediaminetetraacetic acid and 5 mg/ml bovine serum albumin. The microarrays were rinsed briefly in PBST 0.1% and washed at room temperature with gentle rocking for 10 minutes in PBST 0.1%. Phi29 DNA polymerase (TempliPhi; Amersham Biosciences Corp, Piscataway, NJ) in 1× Tango buffer (Fermentas, Hanover, MD) solution with 0.1% Tween-20 and 1 mmol/L dNTPs was incubated on the arrays at 37°C for 30 minutes. The microarrays were rinsed briefly in 2× standard saline citrate (SSC)/0.1% Tween-20, washed twice for 5 minutes each at room temperature with gentle rocking in 2× SSC/0.1% Tween-20, and dried by centrifugation. A Cy3-labeled 18-bp oligonucleotide (decorator 1) complementary to the repeating DNA strand from primer 1 and a Cy5-labeled 27-bp oligonucleotide (decorator 4.2) complementary to the repeating DNA strand from primer 4.2 were prepared at 0.2 μmol/L each in 2× SSC with 0.1% Tween-20 and 0.5 mg/ml herring sperm DNA. This solution was incubated on the microarrays for 1 hour at 37°C with gentle rocking. The microarrays were briefly rinsed in 2× SSC/0.1% Tween-20, washed for 10 minutes at room temperature in 2× SSC/0.1% Tween-20, and dried by centrifugation. The slides were spun dry before scanning at 543 nm and 633 nm using a ScanArray microarray scanner (Packard Bioscience, Meriden, CT). GenePix Pro 3.0 (Axon Instruments, Union City, CA) software program was used to quantify the image data. Normalization was performed based on an intensity-dependent algorithm as follows.19Yang YH Dudoit S Luu P Lin DM Peng V Ngai J Speed TP Normalization for cDNA microarray data, a robust composite method addressing single and multiple slide systematic variation.Nucleic Acids Res. 2002; 30: e15Crossref PubMed Scopus (2839) Google Scholar The local background in each color channel was subtracted from the signal at each antibody spot, and spots having obvious defects, no detectable signal by GenePix, or a low net fluorescence in either color channel were removed from the analysis. The ratio of net signal from the sample-specific channel to the net signal from the reference-specific channel was calculated for each antibody spot, and ratios from replicated antibody measurements in the same array were averaged. It is common to plot a red (Cy5) versus green (Cy3) channel scatter plot to examine distribution of intensities; however, we found that transforming to fold change versus average intensity displayed the data in a more easily viewed form. If Ired is the background subtracted red channel intensity, and Igreen is the background subtracted green intensity, then the following variables were created: R = Ired/Igreen and A = √(Ired × Igreen), where R is simply the fold change ratio and A is the average intensity (the geometric mean, which is equivalent to averaging the log intensity). The curvature in the scatter plot indicated a dependence of the ratio R on the overall intensity. This curve is then used to normalize the data: logIred/Igreen->log (Ired/Igreen) − c(A), where c(A) is the fit. This is equivalent to multiplying the green channel intensity (or dividing the red) by an intensity-dependent normalization constant k(A) where log[(k(A)] = c(A). Optimal normalized data should be horizontal and centered. The hierarchical clustering algorithm was used to evaluate the association of protein profiles and individuals under study taking the Pearson correlation (p) as the distance metric (distance = (1 − p)/2) and the average linkage method.20Eisen MB Spellman PT Brown PO Botstein D Cluster analysis and display of genome-wide expression patterns.Proc Natl Acad Sci USA. 1998; 95: 14863-14868Crossref PubMed Scopus (13353) Google Scholar The application of bootstrapping techniques to hierarchical clustering using the R statistical package estimated the robustness of the associations of the relationships among the samples and protein expression patterns.21Felsenstein J Confidence limits on phylogenies, an approach using the bootstrap.Evolution. 1985; 39: 783-791Crossref PubMed Google Scholar Resampling and replacing on the original data are performed to generate replicated datasets. This is done 1000 times, and for each new dataset a clustering tree is generated. A consensus tree is then constructed from the bootstrap trees where at each node the number of times that subgroup appeared in the 1000 trees. The closer this number is to 1000 the more robust that subgroup is. The sensitivity and specificity of antibody arrays was evaluated based on the distribution of patients within the clusters.22Dawson-Saunders B Trapp RG Basic and Clinical Biostatistics. ed 2. Appleton & Lange, Norwalk1994Google Scholar The sensitivity of the antibody arrays was tested on the patients with bladder cancer and the specificity of the antibody arrays was tested on the controls comprising benign and malignant conditions. Cystoscopic evaluation together with the histopathological report was considered as the gold standard for classification of bladder tumors. Inclusion of controls was based on clinical reports. The Wilcoxon test, together with the Bonferroni correction, was applied to rank the most discriminatory antibodies between patients with bladder cancer and controls and between high-risk and low-risk patients with bladder cancer.22Dawson-Saunders B Trapp RG Basic and Clinical Biostatistics. ed 2. Appleton & Lange, Norwalk1994Google Scholar This analysis was done based on the classification given by the hierarchical clustering together with bootstrapping analysis. Additionally, the association of protein profiles with outcome was evaluated using the log-rank test.22Dawson-Saunders B Trapp RG Basic and Clinical Biostatistics. ed 2. Appleton & Lange, Norwalk1994Google Scholar Three different tissue microarrays were constructed in the Division of Molecular Pathology.23Hoos A Cordon-Cardo C Tissue microarray profiling of cancer specimens and cell lines: opportunities and limitations.Lab Invest. 2001; 81: 1331-1338Crossref PubMed Scopus (215) Google Scholar They included a total of 173 primary transitional cell carcinomas (TCCs) of the bladder, belonging to patients recruited at Memorial Sloan-Kettering Cancer Center under institutional review board approved protocols. A total of 40 superficial and 64 invasive TCC tumors were analyzed in the first two microarrays. These tumors corresponded to 24 grade 1, 8 grade 2, and 82 grade 3 lesions. The third tissue microarray comprised 69 bladder primary high-grade TCC cases with annotated follow-up, including two superficial and 67 invasive lesions. Protein expression patterns of c-met were assessed at the microanatomical level on these tissue microarrays by immunohistochemistry using standard avidin-biotin immunoperoxidase procedures. We used a mouse monoclonal antibody against c-met (C-28) from Santa Cruz Biotechnology (Santa Cruz, CA) at 1:50 dilution. The consensus value of the representative cores from each tumor sample arrayed was used for statistical analyses. All TCCs (n = 173) were used for the analysis of association of c-met with histopathological stage and tumor grade, using the nonparametric Wilcoxon-Mann-Whitney and Kruskall-Wallis tests.22Dawson-Saunders B Trapp RG Basic and Clinical Biostatistics. ed 2. Appleton & Lange, Norwalk1994Google Scholar The association of c-met with outcome was evaluated using the 69 TCC cases contained in the third tissue microarray for which follow up was available. The log-rank test was used for this purpose taking the cutoff of 50% expression.24Cheng HL Trink B Tzai TS Liu HS Cha
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