[CANCER RESEARCH 63, 6069 – 6075, September 15, 2003] Disease-associated Expression Profiles in Peripheral Blood Mononuclear Cells from Patients with Advanced Renal Cell Carcinoma Natalie C. Twine, Jennifer A. Stover, Bonnie Marshall, Gary Dukart, Manuel Hidalgo, Walter Stadler, Theodore Logan, Janice Dutcher, Gary Hudes, Andrew J. Dorner, Donna K. Slonim, William L. Trepicchio, 1 and Michael E. Burczynski 2 Discovery Medicine [N. C. T., J. A. S., A. J. D., W. L. T., M. E. B.] and Expression Profiling Informatics [D. K. S.], Wyeth Research, Cambridge, Massachusetts 02140; Clinical Research and Development, Wyeth Research, Collegeville, Pennsylvania 19426 [B. M., G. D.]; University of Texas Health Science Center, San Antonio, Texas 78229 [M. H.]; University of Chicago, Chicago, Illinois 60637 [W. S.]; Indiana University, Indianapolis, Indiana 85012 [T. L.]; Our Lady of Mercy Medical Center, New York Medical College, Bronx, New York 10466 [J. D.]; and Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111 [G. H.] ABSTRACT Expression profiling has demonstrated that transcriptomes of primary malignancies differ from those in normal tissue. It is unknown, however, whether there exist “surrogate” transcriptional markers in peripheral blood mononuclear cells (PBMCs) of patients with solid tumors. We identified transcripts expressed differentially between PBMCs from renal cell carcinoma patients and normal subjects, some of which appear to reflect specific immune responses of circulating cells. We also identified small sets of predictor genes distinguishing PBMCs from renal cell car- cinoma patients and normal volunteers with high accuracy. The present findings have important implications for diagnosis and future clinical pharmacogenomic studies of antitumor therapies. INTRODUCTION RCC 3 comprises the majority of all cases of kidney cancer and is one of the 10 most common cancers in industrialized countries (1). The 5-year survival rate for advanced RCC is less than 5% (2). RCC is usually detected by imaging methods, and 30% of apparently nonmetastatic patients undergo relapse after surgery and eventually die of disease (3). Recent expression profiling studies have demon- strated that the transcriptional profiles of primary malignancies are radically altered from the transcriptional profiles of the corresponding normal tissue (for a review see Ref. 4). Specific microarray studies examining RCC tumor transcriptional profiles in detail (5) have identified many classes of genes altered between normal kidney tissue and primary RCC tumors. Despite the progress in expression profiling of primary malignant tissues, it is currently unknown whether in the context of RCC or any other active solid tumor burden there exist correspondingly distinct markers of gene expression in the PBMCs of affected individuals. In the present study, global expression profiles of PBMCs from RCC patients were compared with PBMC profiles from normal volunteers using oligonucleotide arrays for the purpose of identifying surrogate transcriptional markers of disease in the blood of RCC patients. MATERIALS AND METHODS Clinical Parameters and Demographics of Patients and Normal Volun- teers. PBMCs were isolated from peripheral blood of 20 normal volunteers (12 females and 8 males) and 45 RCC patients (18 females and 27 males) participating in a Phase II study. Consent for the pharmacogenomic portion of the clinical study was received, and the project was approved by the local Institutional Review Boards at the participating clinical sites. The RCC tumors were classified at each site as conventional (clear cell) carcinomas (24), granular (1), papillary (3), or mixed subtypes (7). Ten tumors were classified as unknown. RCC patients were primarily of Caucasian descent (44 Cauca- sians and 1 African-American) and had a mean age of 58 years (range, 40 –78). Normal volunteers were of exclusively Caucasian descent, with a mean age of 42 years (range, 29 –58). PBMC Preparation, Isolation of RNA, and Hybridization of Targets to Microarrays. PBMCs from individuals were isolated from whole blood sam- ples (8 ml) collected into cell purification tubes according to the standard procedure. All normal and RCC blood samples were shipped or stored over- night before processing. Total RNA was isolated from PBMC pellets using the RNeasy mini kit (Qiagen, Valencia, CA), and labeled probe for oligonucleotide arrays was prepared using a modification of the procedure described by Lockhart et al. (6). Labeled probes were hybridized to oligonucleotide arrays comprising over 12,600 human sequences (HgU95A, Affymetrix), according to the Affymetrix Expression Analysis Technical Manual (Affymetrix). Gene Expression Data Reduction. Data analysis and absent/present call determination were performed on raw fluorescent intensity values using GENECHIP 3.2 software (Affymetrix). “Present” calls were calculated by GENECHIP 3.2 software by estimating whether a transcript is detected in a sample based on the strength of the signal of the gene compared with back- ground. The “average difference” values for each transcript were normalized to “frequency” values using the scaled frequency normalization method (7), in which the average differences for 11 control cRNAs with known abundance spiked into each hybridization solution were used to generate a global cali- bration curve. This calibration was then used to convert average difference values for all transcripts to frequency estimates, stated in units of parts per million ranging from 1:300,000 (3 ppm) to 1:1,000 (1,000 ppm). Statistical and Clustering Analyses. Unsupervised hierarchical clustering of genes and/or arrays on the basis of similarity of their expression profiles was performed using the procedure of Eisen et al. (8). Nearest neighbor analysis and supervised prediction were performed using Genecluster version 2.0, 4 which has been described previously (9). For hierarchical clustering and nearest neighbor analysis, data were log transformed and normalized to have a mean value of zero and a variance of one. To identify the disease-associated transcripts, a Student’s t test was used to compare normal PBMC expression profiles to renal carcinoma PBMC profiles. Additional Samples from the GeneLogic GX2000 Bioexpress Database and Fold Change Analysis. Expression profiles measured on HgU95 chips of renal carcinoma biopsies (n = 47) and nonmalignant normal kidney tissues (n = 60), WBCs from nondiseased volunteers (n = 4) and WBCs from non-RCC end-stage renal failure patients (n = 9), or unstimulated CD4 T cells in culture (n = 3) and anti-CD3/anti-CD28-stimulated CD4 T cells in culture (n = 3) were accessed from the GX2000 BioExpress database (GeneLogic, Gaithersburg, MD). Data were processed in Affymetrix Micro Array Suite 4 and then normalized using the GeneLogic normalization algorithm. Fold changes were calculated in the GX2000 Fold Change analysis tool, which uses a geometric mean to calculate average changes in the expression of a gene between groups of samples. Received 3/26/03; revised 6/10/03; accepted 6/20/03. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. 1 Present address: Millennium Pharmaceuticals, 75 Sidney Street, Cambridge, MA 02139. 2 To whom requests for reprints should be addressed, at Wyeth Research, 1 Burtt Road, Andover, MA 01810. Phone: (978) 247-1156; Fax: (978) 247-1133; E-mail: mburczynski@ wyeth.com. 3 The abbreviations used are: RCC, renal cell carcinoma; PBMC, peripheral blood mononuclear cell; ppm, parts per million. 4 Internet address: www-genome.wi.mit.edu/cancer/software/genecluster2.html. 6069 on April 7, 2021. © 2003 American Association for Cancer Research. cancerres.aacrjournals.org Downloaded from