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Cell Cycle and Immune-Related Processes Are Significantly Bone Marrow Transplantation (2008) 41, 1047–1057 & 2008 Nature Publishing Group All rights reserved 0268-3369/08 $30.00 www.nature.com/bmt ORIGINAL ARTICLE Cell cycle and immune-related processes are significantly altered in chronic GVHD SJ Oh1,2,8, SB Cho1,3,8,, S-H Park1, CZ Piao1, SM Kwon1, I Kim1,4, SS Yoon4, BK Kim4, EK Park1,5, JJ Kang6, S-J Yang6, WJ Lee7, C-H Yoo7, S Hwang7, SH Kim7, JH Kim1,3 and S Park1,4 1Diagnostic DNA Chip Center, Seoul National University College of Medicine, Seoul, Korea; 2Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea; 3Seoul National University Biomedical Informatics, Seoul, Korea; 4Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea; 5Department of Internal Medicine, Chung-ang University College of Medicine, Seoul, Korea; 6Macrogen Inc., Seoul, Korea and 7Digital Genomics Inc., Seoul, Korea Currently, the pathogenesis of chronic GVHDis unclear. Introduction To elucidate the molecular characteristics underlying chronic GVHD, we analyzed the gene expression profiles Chronic GVHD, which is one of the most serious of 21 mononuclear cell samples from allogeneic hemato- complications of allogeneic hematopoietic stem cell trans- poietic stem cell transplantation (HSCT) recipients. Self plantation (HSCT), occurs in 20B70% of patients who organizing map (SOM) clustering showed that the entire survive for 100 days or more following the procedure.1 The expression profiles of chronic GVHDsamples were clearly pathologic characteristics of chronic GVHD include different from those of the non-GVHDsamples, and immune dysregulation, immunodeficiency and impaired significance analysis of microarray (SAM) demonstrated organ function,2 and its treatment consists of the adminis- that 120 genes, including PTDSS1, VAV1 and CD3D, tration of immunosuppressive medications for approxi- were up-regulated, and 5 genes, including calnexin, were mately 1–3 years.1 The high mortality associated with down-regulated in GVHDpatients. Gene ontology chronic GVHD makes it one of the major causes of death annotation revealed that these genes are related to the in stem cell transplant recipients.3 However, the patho- phosphorous metabolism and lipid biosynthesis. Quanti- genesis of chronic GVHD is still not well understood.4 tative real time polymerase chain reaction (qRT-PCR) Although the true pathophysiologic mechanism of experiments validated the up-regulation of PTDSS1, GVHD has not yet been fully clarified, alloreactive T cells VAV1 and CD3D in separate samples. Pathway-wise are thought to initiate chronic GVHD.2,5,6 Furthermore, global test revealed that differential gene expression in humoral immunity-related phenomena, such as B cell cell cycle and T cell immune-associated pathways were dysfunction, a high prevalence of anti-nuclear auto- significant between GVHDpatients and non-GVHD antibodies, and clinical manifestations of autoimmune patients. Seventeen classifier genes selected using a diseases are also observed in chronic GVHD patients.7–9 PAM (prediction analysis of microarray) algorithm Although these findings have been supported by individual showed favorable performance (prediction accuracy studies, it has been difficult to perform a comprehensive 0.85) for identifying patients with chronic GVHD. In ¼ study to examine these phenomena systematically. conclusion, we identified differentially expressed genes Therefore, in this study, we performed a microarray survey and pathways in chronic GVHDpatients using microarray of peripheral blood samples obtained from chronic GVHD analysis, and we also selected diagnostic genes predicting patients to elucidate the molecular characteristics under- chronic GVHDstatus. lying the pathogenesis of GVHD. Bone Marrow Transplantation (2008) 41, 1047–1057; In the post-genomic era, microarray analysis plays a key doi:10.1038/bmt.2008.37; published online 10 March 2008 role in the evaluation of whole genome mRNA expression. Keywords: chronic GVHD; microarray; cell cycle; Due to its high throughput capacity, microarray experi- immune process ments have yielded a large amount of previously unknown findings, and they are commonly used to identify diagnostic or prognostic biomarkers. For example, Golub et al.10 identified diagnostic markers for distinguishing AML and Correspondence: Dr S Park, Department of Internal Medicine, Seoul ALL, as well as subgroups of ALL patients who had National University College of Medicine, 28 Chongno-gu, Yungon different cell lineages using only data obtained by dong, Seoul 110-744, Republic of Korea. conducting microarray analyses. Furthermore, analysis of E-mail: [email protected] 8These authors contributed equally to this work. gene expression profiles using microarray data have also Received 28 September 2007; revised 18 December 2007; accepted 20 identified global gene expression regulatory relation- December 2007; published online 10 March 2008 ships,11,12 and may provide novel and holistic views Cell cycle and immune alteration in chronic GVHD SJ Oh et al 1048 regarding the molecular markers and mechanisms under- Table 1 Summary of patients characteristics (non-GVHD; 10, lying pathologic processes. In this study, we evaluated GVHD; 11) peripheral blood samples obtained from 21 HSCT Clinical variables Total number recipients using an oligonucleotide microarray that contained 20 142 probes to assess immunologic perturba- Total number of patients 21 tion and other abnormal biologic processes associated with Sex, No. (%) chronic GVHD. We also evaluated the results of the M 14 (66.7) microarray analysis to determine if the gene expression F 7 (33.7) profile could be used as a diagnostic tool for patients with chronic GVHD. Patient age Median (range), years 42 (22–64) Primary disease AML 9 (42.9) Materials and methods AA 5 (23.8) CML 2 (9.5) Sample population MDS 2 (9.5) MM 1 (4.8) A total of 21 patients (median age; 42 years, range; 22–64 NHL 1 (4.8) years) who received allogeneic HSCT between May 1991 RCC 1 (4.8) and June 2005 at the Seoul National University Hospital, Seoul, Korea were evaluated using gene expression Acute GVHD analysis. The characteristics of the GVHD and non-GVHD Yes 8 (38.1) No 13 (57.9) patients are shown in Table 1. All patients had received HSCT from HLA (human leukocyte antigen)-matched Conditioning regimen sibling donors with the exception of 2 patients whose HLA Myeolablative 12 (57.2) were mismatched in one A locus. All patients were in Non-myeloablative 9 (42.9) complete remission and in the complete chimerism state. Days after HSCT that last sample was collected Eleven of the 21 patients developed chronic GVHD, Median (range), months 43 (5–92) including one who received partially mismatched trans- plantation. Protocols for all cases in this study were Abbreviations: AA ¼ aplastic anemia; MDS ¼ myelodysplastic syndrome; approved by the Institutional Review Board at the Seoul MM ¼ multiple myeloma; NHL ¼ non-Hodgkin’s lymphoma; RCC ¼ renal National University Hospital, and informed consent was cell carcinoma. obtained from all patients. resulted in a fragmented target with a size range between 100 and 200 bases. Target preparation Two micrograms of total RNA were extracted from Array hybridization mononuclear cells of peripheral blood and added to a Ten micrograms of fragmented target cRNA in 260 mlof reaction mix with a final volume of 12 ml that contained hybridization solution was used for hybridization with each T7-(dT) oligonucleotide primer. The mixture was 24 UniSet Human 20 K I Bioarray (Amersham Biosciences, incubated for 10 min at 70 1C and then chilled on ice. Little Chalfont, Bucks, UK). The hybridization solution While the mixture was on ice, 2 mlof10Â first-strand was heated to 90 1C for 5 min to denature the cRNA, and buffer, 4 mlof5mM dNTP mix, 1 ml of RNase inhibitor then chilled on ice for 5 min. Next, the sample was vortexed (40 U/ml) and 1 ml of Superscript II RNase H– reverse for 5 s at maximum speed, and 250 ml was injected into the transcriptase (200 U/ml) was added to give a final volume of inlet port of the hybridization chamber, which was then 20 ml. The mixture was then incubated for 2 h in a 42 1C placed in a 12-slide shaker tray. The hybridization chamber water bath. Next, second-strand cDNA was synthesized in ports were then sealed with 1 cm sealing strips (Amersham a final volume of 100 ml in a mixture containing 10 mlof Biosciences), and the shaker tray containing the slides was 10 Â second-strand buffer, 4 mlof5mM dNTP mix, 2 mlof loaded into a shaking incubator. The slides were then DNA polymerase mix (20 U/ml) and 1 mlofRNaseH(2U/ml) incubated for 18 h at 37 1C while shaking at 300 r.p.m. for 2 h at 16 1C. The cDNA was then purified using a Qiagen QIAquick purification kit, dried down, and resuspended in IVT reaction mix that contained 4 mlof10Â reaction buffer, Post-hybridization processing using Cy5-streptavidin 4 mlof75mM ATP, 4 mlof75mM GTP, 4 mlof75mM CTP, The 12-slide holder was removed from the shaking 3 mlof75mM UTP, 7.5 mlof10mM Biotin 11-UTP and 4 mlof incubator and the hybridization chamber was then enzyme mix with a final volume of 40 ml. The reaction mix removed from each slide. Next, each slide was briefly was then incubated for 14 h at 37 1C and the cRNA target rinsed in TNT buffer (0.075 M Tris-HCl pH 7.6, 0.1125 M was purified using an RNeasy kit (Qiagen, Hilden, Germany). NaCl, 0.0375% Tween 20) at room temperature, and then The cRNA yield was quantified by measuring the UV washed in TNT buffer at 42 1C for 60 min. The signal was absorbance at 260 nm, and then fragmented into 40 mM then developed using a 1:500 dilution of Cy5-streptavidin Tris–acetate (TrisOAc, pH 7.9), 100 mM KOAc and (Amersham Bioscience) for 30 min at room temperature.
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