Leukemia (2003) 17, 1891–1900 & 2003 Nature Publishing Group All rights reserved 0887-6924/03 $25.00 www.nature.com/leu BIO-TECHNICAL METHODS (BTS) Novel potential ALL low-risk markers revealed by gene expression profiling with new high-throughput SSH–CCS–PCR J Qiu1,5, P Gunaratne2,5, LE Peterson3, D Khurana2, N Walsham2, H Loulseged2, RJ Karni1, E Roussel4, RA Gibbs2, JF Margolin1,6 and MC Gingras1,6 1Texas Children’s Cancer Center and Department of Pediatrics; 2Human Genome Sequencing Center, Department of Molecular and Human Genetics; 3Department of Internal Medicine; 1,2,3 are all departments of Baylor College of Medicine, Baylor College of Medicine, Houston, TX, USA; and 4BioTher Corporation, Houston, TX, USA The current systems of risk grouping in pediatric acute t(1;19), BCR-ABL t(9;22), and MLL-AF4 t(4;11).1 These chromo- lymphoblastic leukemia (ALL) fail to predict therapeutic suc- somal modifications and other clinical findings such as age and cess in 10–35% of patients. To identify better predictive markers of clinical behavior in ALL, we have developed an integrated initial white blood cell count (WBC) define pediatric ALL approach for gene expression profiling that couples suppres- subgroups and are used as diagnostic and prognostic markers to sion subtractive hybridization, concatenated cDNA sequencing, assign specific risk-adjusted therapies. For instance, 1.0 to 9.9- and reverse transcriptase real-time quantitative PCR. Using this year-old patients with none of the determinant chromosomal approach, a total of 600 differentially expressed genes were translocation (NDCT) mentioned above but with a WBC higher identified between t(4;11) ALL and pre-B ALL with no determi- than 50 000 cells/ml are associated with higher risk group.2 nant chromosomal translocation. The expression of 67 genes was analyzed in different cytogenetic ALL subgroups and B Hyperdiploid and t(12;21) ALL patients are considered low-risk lymphocytes isolated from healthy donors. Three genes, ALL, are treated with less intensive therapy, and have a better 1,3 BACH1, TP53BPL, and H2B/S, were consistently expressed as event-free survival (EFS) after therapy (480% at 5 years). a significant cluster associated with the low-risk ALL sub- Conversely, hypodiploid, t(1;19), t(9;22), and t(4;11) ALL groups. A total of 42 genes were differentially expressed in ALL patients are considered high-risk ALL, and are treated with vs normal B lymphocytes, with no specific association with any more intensive regimens. These patients, with the exception of particular ALL subgroups. The remaining 22 genes were part of t(1;19), are at a higher risk of relapse and have a much lower EFS a specific expression profile associated with the hyperdiploid, 1,3 t(12;21), or t(4;11) subgroups. Using an unsupervised hierarch- after therapy (o40% after 3–5 years). The t(1;19) patients ical cluster analysis, the discriminating power of these specific have an EFS of 70–80% after 5 years that is more similar to low- expression profiles allowed the clustering of patients according than high-risk ALL.1,3 to their subgroups. These genes could help to understand the The present risk grouping based on clinical, cytogenetic, and difference in treatment response and become therapeutical immunophenotypic criteria fails to predict the 10–35% patients targets to improve ALL clinical outcomes. Leukemia (2003) 17, 1891–1900. doi:10.1038/sj.leu.2403073 who will relapse on current therapies. Such inadequacy might Keywords: acute lymphoblastic leukemia; gene expression be overcome with the identification of molecular prognostic profiling; BACH1; TP53BPL; H2B/S; suppression subtractive markers. To identify such markers, it is necessary to establish hybridization/concatenated cDNA sequencing/reverse transcriptase ALL gene expression profiles. Currently, specific gene expres- real-time quantitative PCR sion profiles have been established with the use of microarrays for B-cell precursor ALL subgroups, T-cell ALL, minimal residual disease, and to distinguish between acute myeloid leukemia (AML) and ALL.4–8 A specific gene expression profile that can Introduction accurately predict relapse is beginning to emerge from these studies.5 However, specific markers that can identify low-risk At least six important chromosomal changes have been ALL and be indicative of an effective response to less intensive identified in pediatric B-cell precursor acute lymphoblastic or toxic therapy have yet to be found. leukemia (ALL). They correspond to hyperdiploid (450) and Gene expression profile characterization can be realized with hypodiploid (o45) chromosomal status, or one of the following different techniques that can be grouped under two broad chromosomal translocations: TEL-AML t(12;21), E2A-PBX1 descriptions: sequencing technologies developed for the analy- sis of global expression pattern and technologies developed for 9–15 Correspondence: Dr M-C Gingras, Texas Children’s Hospital, Feigin the differential profiling of gene expression. However, each Center, 6621 Fannin Street, MC3-3320, Houston, TX 77030, USA; of these techniques has several limitations. Many of the global Fax: +1 832 825 4846 sequencing approaches have the disadvantage of unacceptable 5The first two authors contributed equally to this work 6 amount of redundant sequencing in order to complete the The last two authors shared the direction of this work characterization. Any of the techniques that require plasmid MCG is supported by a Fleming and Davenport Award and a grant from the Elsa U Pardee Foundation. PG, HL, RAG, and JFM are cloning introduce insert size bias. Microarray approaches are supported by an NIH Grant (USPH 5 U01 CA80200). limited by issues related to gene preselection (it is estimated that Received 15 January 2003; accepted 3 June 2003 only 20% of the entire cell transcriptome is presently Gene expression profiling of pediatric ALL J Qiu et al 1892 represented even on the most comprehensive microarray), conjugated to super-paramagnetic MACS MicroBeads and difficulties with quantification, detection of rare transcripts, applied on a positive selection column-type LS. The eluted and issues of amplification bias especially with small clinical CD3ÀCD14À cells were finally incubated with a CD19+ specimens. Therefore, there is a need for the development of antibody conjugated to super-paramagnetic MACS MicroBeads high-throughput techniques that overcome the above disadvan- and applied twice on an LS column. The purity of the CD19+ tages. cell isolation was over 95% as confirmed by FACS analysis. We have developed a novel approach to facilitate gene expression profiling that combines the selective and normal- RNA isolation ization power of suppression subtractive hybridization (SSH), the high-throughput sequencing capability of concatenated The total cellular RNA was extracted utilizing Ultraspec II cDNA sequencing (CCS), and the quantitative analytical power (Biotecx Laboratories, Houston, TX, USA), a commercial version of reverse transcriptase real-time quantitative PCR (RT-RQ-PCR). of the acid-phenol method.16 RNA integrity was checked The SSH–CCS–RT-RQ-PCR approach was developed using on a formaldehyde agarose gel. mRNA was extracted with pediatric t(4;11) and NDCT ALL subgroups as an experimental Oligotex (Qiagen, Santa Clarita, CA, USA). The total and model. We hypothesized that we could characterize rapidly, mRNA extractions were performed as per the manufacturer’s with low RNA requirement, a large set of differentially expressed instructions. genes and identify unknown markers and expression profiles of ALL subgroups. In addition, the potential for discovery was not limited by preselection of specific target genes. RT-RQ-PCR was Suppression subtractive hybridization used to assess the specificity of the SSH–CCS-generated gene expression profiles, and to expand the study to normal B The Diatchenko and co-workers14,15 PCR-based cDNA subtrac- lymphocytes and other ALL subgroups. This approach allowed tion method was performed using the SMART PCR cDNA us to determine specific gene expression profile for t(4;11), synthesis and PCR-Select subtraction kits (Clontech Labora- t(12;21), hyperdiploid ALL subgroups, and identify general and tories, Palo Alto, CA, USA) as described previously.17 The specific low-risk ALL markers. protocol was initiated with 240 ng of mRNA from two t(4;11) ALL patients (patients A and B) and two NDCT ALL patients (patients C and D). The cDNA was then cut into smaller Materials and methods fragments with RsaI to optimize the hybridization process, and a certain proportion of the resulting fragments (tester) were linked Cell isolation to a set of adaptors as per the manufacturer’s instructions17 (Clontech). One set of hybridizations was performed between Human patient samples were collected under an Institutional patients A and C cDNA, and between patients B and D cDNA. Review Board for Human Subject Research (IRB) for Baylor In this hybridization set, patients C and D cDNA was used in College of Medicine and Affiliated Hospitals approved protocol. excess (drivers), resulting in two differentially expressed Two panels of newly diagnosed patients were used in the gene subtracted t(4;11) cDNA pools. A second set of hybridization expression study: a smaller panel of 19 patients for the general was performed using patients A and B cDNA in excess (drivers), analysis and a broader panel of 38 patients for the specific low- resulting in two differentially expressed subtracted NDCT cDNA vs high-risk study (BACH1, TP53BPL, and H2B/S expression pools. The differentially expressed SSH cDNA fragments from analysis). The patients were categorized into one of the each pool were then amplified twice.17 following pre-B ALL subgroups: four and five patients with hyperdiploidy (55–58 chromosomes), six and 15 patients with the translocation t(12;21), four and six patients with the Concatenation translocation t(4;11), one and five patients with the translocation t(9;22), one and four patients with the translocation t(1;19), and The concatenation strategy is illustrated in Figure 1.