Leukemia (2001) 15, 1721–1728  2001 Nature Publishing Group All rights reserved 0887-6924/01 $15.00 www.nature.com/leu Distinct gene expression profiling in chronic lymphocytic leukemia with 11q23 deletion Y Aalto 1 , W El-Rifai 1,2 , L Vilpo 3 , J Ollila 4 , B Nagy 1,5 , M Vihinen 6 , J Vilpo 3 and S Knuutila 1 1 Department of Medical Genetics, Haartman Institute and Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland; 2 Department of Medicine, University of Virginia Health Systems, VA, USA; 3 Department of Clinical Chemistry, Tampere University Hospital and University of Tampere, Tampere, Finland; 4 Department of Biosciences, Division of Biochemistry, University of Helsinki, Helsinki, Finland; 5 Genetic Laboratory, Faculty of Medicine, Semmelweis University, Budapest, Hungary; and 6 Department of Bioinformatics, Institute of Medical Technology, University of Tampere, Tampere, Finland Chronic lymphocytic leukemia (CLL) is a heterogeneous dis- ease with regard to its clinical course. The limitations of the methods currently available for prognostic assessment in CLL do not allow accurate prediction of the risk of disease pro- gression in individual patients. The recently developed cDNA array technique provides a unique opportunity to study gene expression in various malignancies. To identify new molecular markers for prognostication of CLL patients, we analyzed cDNA arrays by using hierarchical clustering and standard statistic t-test on 34 CLL patients. We found significant expression dif- ferences in 78 genes compared to the reference tonsillar B lym- phocytes. A cluster of genes, LCP1, PARP, BLR1, DEK, NPM, MCL1, SLP76, STAM, HIVEP1, EVI2B, CD25, HTLF, HIVEP2, BCL2, MNDA, PBX3, EBI2, TCF1, CGRP, CD14, IL8, GZMK, GPR17 and CD79B, was associated (P  0.05) with the unfavor- able 11q deletion and also with the unfavorable Binet stages B and C. We present here gene expression profiling that is asso- ciated with CLL patients with the 11q23 deletion. Many of the genes in the cluster have not previously been shown to be related to the initiation or progression of CLL. These novel fin- dings provide fundamental information for further attempts to understand the interaction of the clustered genes in the leuko- mogenesis of CLL in order to better design treatments aimed at specific molecular target(s). Leukemia (2001) 15, 1721–1728. Keywords: chronic lymphocytic leukemia; Binet clinical staging; 11q23 deletion; cDNA array; molecular marker Introduction Chronic lymphocytic leukemia (CLL) is the most common form of leukemia in the Western world. The prognosis for patients with CLL is highly variable. Some patients survive with indolent disease for many years without any treatment and eventually succumb to other diseases. Other patients develop a more aggressive malignancy from which they die. The median survival is approximately 10 years. 1 In order to reduce CLL-related mortality, it is essential to identify patients at risk and prevent progression of their disease. Cytogenetic studies have shown chromosome aberrations in 50–80% of CLL patients and certain genetic changes have been reported repeatedly, such as trisomy 12, deletions in 13q and 14q, and losses in 6q, 11q and 13q. 2–7 Losses in 11q appear to be one of the most common structural chromosome aberrations in CLL and they are associated with both the development of the disease and survival. 3,4,7–9 Despite the relatively large number of patients available for study, little is known about the genes involved in the etiology and progression of CLL. cDNA microarray is a new powerful technology capable of profiling the gene expression patterns of hundreds to thou- Correspondence: S Knuutila, Department of Medical Genetics, Hel- sinki University Central Hospital, PO Box 400 (Haartmaninkatu 3, 4th floor), FIN-00029 HUS, Helsinki, Finland; Fax: +358-9-191.26788 Received 13 June 2001; accepted 19 July 2001 sands of genes in a single experiment. The information obtained from cDNA array analyses provides new diagnostic and prognostic parameters for cancer patients. 10,11 We used this technology to investigate the gene expression profiles of patients at different stages of CLL and to assess the association between the gene expression profile and the clinical behavior of the disease. Materials and methods Patients Peripheral blood specimens were collected from 34 CLL patients referred to the CLL outpatient clinic at the Tampere University Hospital. The selection criterion was a blood lym- phocyte count of 30 × 10 9 or higher. 1 The median age of the patients (nine females and 25 males) was 64.8 years (range 48–79). The patients were diagnosed and staged according to standard clinical, morphological and immunophenotyping criteria and the Binet system. 1,12,13 All patients had a CD19 + /CD5 + /CD23 + immunophenotype. Fifteen patients presented with stage A, 10 with stage B and nine with stage C disease. 1 The clinical data are shown in Table 1. Reference To obtain pure reference material for the expression compari- son, CD19-positive B cells were purified from human adenoid palatine tonsil samples from six healthy children. The B cells were purified using microbeads conjugated to a monoclonal CD19 antibody (Miltenyi Biotec, Bergisch Gladbach, Germany). The proportion of T lymphocytes was less than 5%, indicating that 95% of the isolated cells represented B-lym- phocyte population. RNA isolation Lymphocytic cells were isolated from the patient’s blood using one-step density gradient centrifugation in Ficoll–Paque (Pharmacia Fine Chemicals, Uppsala, Sweden), and the total RNA was extracted using the Trizol Reagent (Gibco BRL, Grand Island, NY, USA). The proportion of monocytes and polyclonal T and B lymphocytes was 1–13%, indicating that 87–99% of the isolated cells represented the leukemic popu- lation. The RNA was then treated with DNase I (Boehringer Mannheim, Mannheim, Germany) for purification, according to the protocol of the Atlas cDNA Expression Array’s user manual (Clontech Laboratories, Palo Alto, CA, USA). The quality and integrity of the RNA were checked using 1% aga-