[Frontiers in Bioscience 11, 977-982, January 1, 2006]

Genes differentially expressed in responsive and refractory acute leukemia

Qing Wei 1, Yao Li 1, Li Chen 2, Liying Zhang 1, Xianmin He 3, Xuping Fu 1, Kang Ying 1, Jianfeng Huang 3, Qin Chen 3, Yi Xie 1, and Yumin Mao 1

1 State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University, Shanghai 200433, P.R. China,2 Hematology Department, Changhai Hospital, The Second Military Medical University, Shanghai 200433 China, and 3 Shanghai BioStar Genechip Institute, Shanghai 200092, P.R. China

TABLE OF CONTENTS

1. Abstract
2. Introduction
3. Methods and materials
3.1. RNA isolation
3.2. Construction of microarrays and probe preparations
3.3. Hybridization
3.4. Detection and Analysis
4. Results and Discussion
4.1. Genes differentially expressed in acute leukemia
4.2. Genes differentially expressed in refractory versus responsive acute leukemia
5. Acknowledgement
6. References

1. ABSTRACT

DNA microarray in 22 patients with acute leukemia revealed genes which were differentially expressed. Ribosomal protein SA (RPSA), minichromosome maintenance deficient 2 (MCM2) and heterogeneous nuclear ribonucleoprotein A1 (HNRPA1) were significantly upregulated (p<0.05, t test) in refractory patients, suggesting that they may play a role in refractoriness in acute leukemia and could be biomarkers of prognosis.

2. INTRODUCTION

Understanding complex biological processes, such as disease initiation and progression at the molecular level, has become an exciting area in biomedicine. Alterations in gene expression patterns accompanying different stages of growth, disease onset, cell cycle progression, responses to environmental stimuli, provide important clues about these complex processes. Identifying stereotypical expression patterns may allow elucidation of the mechanisms that underlie cancer and provide important molecular markers for diagnostic purposes.

Further progress in the management of acute leukemia (AL) is currently limited by our incomplete understanding of the molecular pathways involved in leukemia pathogenesis and by the lack of useful prognostic markers for most patients. cDNA microarray technology (1,2), which allows the simultaneous analysis at gene expression levels for thousands of transcripts, has significantly accelerated the rate of progress in our understanding of the molecular basis of AL. Currently, considerable findings have been made by applying cDNA microarray to leukemia molecular classification, diagnosis and prognosis. For instance, leukemia classification can be based solely on microarray gene expression monitoring (3); lipoprotein lipase (LPL) and a disintegrin and metalloproteinase domain 29 (ADAM29) gene expression is a strong prognostic indicator in chronic lymphocytic leukemia (4); some of the biological pathways affected by farnesyl protein transferase inhibitors (FTI) treatment may provide a proof of principle for identifying candidate genes that might be used as surrogate biomarkers of drug activity (5).

However, most of these experiments did not describe the holistic effects and inter-regulation of those differentially expressed genes in the disease progression, but only focused on certain genes or pathways related to leukemogenesis, classification, prognosis and drug-induced changes according to clinical materials and statistical methods. Through this investigation, we aimed to find the key genes related to leukemogenesis and to refractoriness which could potentially serve as biomarkers.

3. MATERIALS AND METHODS

3.1. RNA isolation

The acute leukemia patient and normal specimens used in this study were provided by Changhai Hospital at the Second Military Medical University. Institutional approval was obtained for all specimens. Bone marrows from 22 patients diagnosed with de novo AL were obtained as well as normal bone marrow from 20 voluntary donors with no history of AL that were used as reference samples. Tissue samples were ground into a fine powder in a 10 cm ceramic mortar (RNase-free) and then were homogenized in TRIzol (Biostar, Shanghai, China). After centrifugation, the supernatant was separated from the organic phase and was extracted in an equal volume of chloroform. The aqueous phase was then precipitated by an equal volume of isopropanol at 4�C, centrifuged to pellet the RNA and dissolved in Milli-Q H2O.

3.2. Construction of microarrays and probe preparations

The construction of the microarrays used in this study (12800 chip) was carried out following Brown's method (6). The 12800 microarrays consisted of 12,800 sequences including full-length and partial cDNAs representing known, novel, and control genes provided by United Gene Holdings. All the sequences were verified. The known genes were selected from the NCBI Unigene set and cloned into a plasmid vector. The novel genes were obtained through systematic full-length cloning efforts carried out at United Gene Holding. The control spots of non-human origin in the 12800 chip included the rice U2 RNA gene (8 spots), the hepatitis c virus (HCV) coat protein gene (8 spots), and spotting solution alone without DNA (32 spots). The cDNA inserts were amplified by use of the polymerase chain reaction (PCR) using universal primers to plasmid vector sequences and were then purified (7). All PCR products were examined by agarose gel electrophoresis to ensure the quality and the identity of the amplified clones as expected. Then the amplified PCR products were dissolved in a buffer containing 3� SSC solution. The solution with amplified PCR products were spotted onto silylated slides (CEL Associates, Houston, TX., USA) using a Cartesian PixSys 7500 motion control robot (Cartesian Technologies, Irvine, CA., USA) fitted with ChipMaker Micro-Spotting Technology (TeleChem International, Sunnyvale, CA., USA). The glass slides were then hydrated for 2 hrs in 70% humidity, dried for 0.5 hrs at room temperature, and UV crosslinked (65 mj/cm). They were further processed at room temperature by soaking in 0.2% sodium dodecyl sulfate (SDS) for 10 min, distilled H2O for 10 min, and 0.2% sodium borohydride (NaBH4) for 10 min. The slides were dried again and ready for use. The fluorescent cDNA probes were prepared through reverse transcription of the isolated mRNAs and then purified according to the methods of Schena et al (1,2). The RNA samples from normal bone marrows were labeled with Cy3-dUTP and those from leukemia patients with Cy5-dUTP.

3.3. Hybridization

The probe was dissolved in 20 �l of Hybridization Solution [5X SSC (0.75M NaCl and 0.075M sodium citrate), 0.4% SDS, 50% formamide]. Microarrays were pre-hybridized with a hybridization solution containing 0.5 mg/ml denatured salmon sperm DNA at 42�C for 6 hrs. Fluorescent probe mixtures were denatured at 95�C for 5 minutes, and then applied onto the pre-hybridized chip under a cover glass. Chips were hybridized at 42�C for 15-17 hours. Next, the hybridized chips were each washed at 60�C for 10 min in solutions of 2X SSC and 0.2% SDS, 0.1X SSC and 0.2% SDS, and 0.1X SSC, then dried at room temperature.

3.4. Detection and Analysis

The chips were scanned with a ScanArray 4000 (GSI Lumonics, Bellerica, MA) at two wavelengths, 635nm and 532 nm, to detect emission from both Cy5 and Cy3 respectively. The acquired images were analyzed using GenePix Pro 3.0 software. The intensities of each spot at the two wavelengths represent the quantity of Cy3-dUTP and Cy5-dUTP. Ratios of Cy5 to Cy3 were computed using the GenePix Pro 3.0 median of ratio method. Overall intensities were normalized using the corresponding GenePix default normalization factor. All spots flagged "Bad" or "Not Found" by GenePix software were removed from the final data. Only genes with raw intensity values for both Cy3 and Cy5 of >200 counts were chosen for differential analysis. Genes were identified as differentially expressed if the ratio was >2 or <0.5, or the absolute value of base 2 logarithm of the ratio was >1.

4. RESULTS AND DISCUSSION

Samples from sixteen males and 6 females, from ages 15 to 86, were used in this study (AML M1 1 case, AML M2 4 cases, AML M3 5 cases, AML M4 1 case, AML M5 3 cases, AML M6 3 cases, ALL L2 5 cases). The information regarding these specimens is provided in table 1. The tumor sample gene expression was compared to the normal references (i.e. no history of acute leukemia) and the ratio of these samples was converted into a log scale with base 2. Supplement raw data can be downloaded at http://www.chinagenenet.com/weiqing/.

4.1. Genes differentially expressed in acute leukemia

A patient was defined to be refractory according to the standard proposed in the 2nd National Refractory Leukemia Conference (Fuzhou, China, Oct, 1999). In summary, a patient was regarded as refractory if he or she (a) was an AML subtype and did not show complete remission (CR) after 2 courses of classical inducement, or (b) was an ALL subtype and did not show CR 4 or 5 weeks after classical inducement, or (c) had a relapse within 6 months after the first CR, or (d) had a relapse 6 months after the first CR and failed in classical inducement, or (e) had more than one relapse.

We found 114 genes which were differentially expressed in 9 samples with an accordance rate of over 80%, including 51 downregulated genes and 63 upregulated genes. Explored by Onto-express software (8), the distribution of these 114 genes in gene ontology (GO) terms is shown in figure 1, of which the three largest known components are the intracellular, the binding and the metabolism groups. The expression of 32 key genes, was consistently changed in more than 15 samples, or were differentially regulated between responsive and refractory patients (p<0.05) (Table 2, Figure 2). All these genes were first reported in acute leukemia except MCM2, HNRPA1, RTN4, MAPK14, ANXA2 and NUP214.

S100 calcium binding protein A11 (S100A11), which has not been reported in leukemia yet, was downregulated in all 22 patients. The protein encoded by S100A11 gene is a member of the S100 family and contains 2 EF-hand calcium-binding motifs. S100 proteins are localized in the cytoplasm and/or nucleus of a wide range of cells, and involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation. Downregulation of S100C expression is associated with increasing tumor aggressiveness and poor prognosis in bladder cancer patients (9).

4.2. Genes differentially expressed in refractory versus responsive acute leukemia

RPSA has not been previously reported in acute leukemia. RPSA regulates laminins, a family of extracellular matrix glycoproteins and the major noncollagenous constituent of basement membranes. Laminins have been implicated in a wide variety of biological processes including cell adhesion, differentiation, migration, signaling, neurite outgrowth, metastasis and multi-drug resistance. It has been observed that the level of the laminin receptor transcript is higher in colon carcinoma tissue and lung cancer cell line than that of their normal counterparts. Also, there is a correlation between the upregulation of this polypeptide in cancer cells and their invasive and metastatic phenotype (10-13). In our experiments, RPSA was upregulated, especially in refractory patients, with a significant difference (p<0.01, t test). CDKN2D, CLU, MAPK14, B2M, TXNIP and SAT induce differentiation or apoptosis and are involved in proliferation (14-19).. MCM2 is a biomarker of proliferation in human malignant fibrous histiocytoma (MFH), and its expression is ubiquitous in proliferating cells, regardless of the expression of p53 (20). This gene was differentially expressed in refractory patients and others with a significant level (p=0.0225). FBLN1 can inhibit proliferation by inhibiting secreted form of amyloid precursor protein (sAPP) (21), but it was downregulated in 90% of the samples, especially in refractory patients (p=0.0396). HNRPA1, which was reported to be upregulated in many tumors and have the function of inhibiting apoptosis (22), was markedly upregulated in refractory patients (p=0.0065). TNFSF1B, CTSD and ANXA2, which are involved in cell proliferation (23-25), were downregulated. Protein kinase C delta (PRKCD) which inhibits the expression of glutamine synthetase (26) and inhibits EI24 (27) and promote apoptosis (28-29)

Taken together, high density cDNA microarray, showed changes in expression profile of genes implicated in proliferation and differentiation and apoptosis. RPSA, MCM2, HNRPA1 may play important roles in refractoriness of acute leukemia and potentially can be used as biomarkers for prognosis of acute leukemia.

5. ACKNOWLEDGEMENT

This research was supported by a grant 2002AA2Z2002 from the National High Technology Research and Development Program of China (863 Program). Qing Wei and Yao Li contributed equally to this paper

6. REFERENCES

1. Schena M, D. Shalon, R.W. Davis & P.O. Brown: Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467-470 (1995)

2. Schena M, D. Shalon, R. Heller, A. Chai, P.O. Brown & R.W. Davis: Parallel human genome analysis: microarray-based expression monitoring of 1000 genes. PNAS 93, 10614-10619 (1996)

3. Golub T.R, D.K. Slonim, P. Tamayo, C. Huard, M. Gaasenbeek, J.P. Mesirov, H. Coller, M.L. Loh, J.R. Downing, M.A. Caligiuri, C.D. Bloomfield & E.S. Lander: Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531-537 (1999)

4. Oppezzo P, Y. Vasconcelos, C. Settegrana, D. Jeannel, F. Vuillier, M. Legarff-Tavernier, E. Yuriko Kimura, S. Bechet, G. Dumas, M. Brissard, H. Merle-Beral, M. Yamamoto, G. Dighiero & F. Davi: The LPL/ADAM29 expression ratio is a novel prognosis indicator in chronic lymphocytic leukemia. Blood 106, 650-657 (2005)

5. Raponi M, R.T. Belly, J.E. Karp, J.E. Lancet, D. Atkins & Y. Wang: Microarray analysis reveals genetic pathways modulated by tipifarnib in acute myeloid leukemia. BMC Cancer 4, 56 (2004)

6. Brown P: In: http://cmgm.stanford.edu/pbrown/protocols/index.html (2000)

7. Sambrook J & D.W. Russell: Using PCR to amplify DNA in vitro. In: Molecular Cloning: A Laboratory Manual, 3rd ed. Eds: Cold Spring Harbor Laboratory Press, NY (2001)

8. Intelligent systems and bioinformatics laboratory [homepage on the Internet] Computer Science Department, Wayne State University Available from: http://vortex.cs.wayne.edu/Projects.html#Onto-Express

9. Memon A.A, B.S. Sorensen, P. Meldgaard, L. Fokdal, T. Thykjaer & E. Nexo: Down-regulation of S100C is associated with bladder cancer progression and poor survival. Clin Cancer Res 11, 606-611 (2005)

10. Diggle C.P, S. Cruickshank, J.D. Olsburgh, S. Pellegrin, B. Smith, R.E. Banks, P.J. Selby, M.A. Knowles, J. Southgate & P. Harnden: Identification of genes up-regulated in urothelial tumors: the 67-kd laminin receptor and tumor-associated trypsin inhibitor. Am J Pathol 163, 493-504 (2003)

11. Satoh K, K. Narumi, T. Sakai, T. Abe, T. Kikuchi, K. Matsushima, S. Sindoh & M. Motomiya: Cloning of 67-kDa laminin receptor cDNA and gene expression in normal and malignant cell lines of the human lung. Cancer Lett 62, 199-203 (1992)

12. Clausse N, P. Jackers, P. Jares, B. Joris, M.E. Sobel & V. Castronovo: Identification of the active gene coding for the metastasis-associated 37LRP/p40 multifunctional protein. DNA Cell Biol 15, 1009-1023 (1996)

13. Shi Y, H. Zhai, X. Wang, H. Wu, X. Ning, Y. Han, D. Zhang, B. Xiao, K. Wu & D. Fan: Multidrug-resistance-associated protein MGr1-Ag is identical to the human 37-kDa laminin receptor precursor. Cell Mol Life Sci 59, 1577-1583 (2002)

14. Tanaka H, I. Matsumura, K. Nakajima, H. Daino, J. Sonoyama, H. Yoshida, K. Oritani, T. Machii, M. Yamamoto, T. Hirano & Y. Kanakura: GATA-1 blocks IL-6-induced macrophage differentiation and apoptosis through the sustained expression of cyclin D1 and bcl-2 in a murine myeloid cell line M1. Blood 95, 1264-1273 (2000)

15. Wellbrock C, C. Weisser, E. Geissinger, J. Troppmair & M. Schartl: Activation of p59(Fyn) leads to melanocyte dedifferentiation by influencing MKP-1-regulated mitogen-activated protein kinase signaling. J Biol Chem 277, 6443-6454 (2002)

16. Morita K, M. Saitoh, K. Tobiume, H. Matsuura, S. Enomoto, H. Nishitoh & H. Ichijo: Negative feedback regulation of ASK1 by protein phosphatase 5 (PP5) in response to oxidative stress. EMBO J 20, 6028-6036 (2001)

17. Fagan L.F. Jr, F.V. Aguirre, U. Deligonul & M.J. Kern: Pseudodissection: negative contrast streaming from collateral flow branch mimicking coronary arterial dissection. Cathet Cardiovasc Diagn 18, 15-17 (1989)

18. Wang Y, G.W. De Keulenaer & R.T. Lee: Vitamin D(3)-up-regulated protein-1 is a stress-responsive gene that regulates cardiomyocyte viability through interaction with thioredoxin. J Biol Chem 277, 26496-26500 (2002)

19. Vujcic S, M. Halmekyto, P. Diegelman, G. Gan, D.L. Kramer, J. Janne & C.W. Porter: Effects of conditional overexpression of spermidine/spermine N1-acetyltransferase on polyamine pool dynamics, cell growth, and sensitivity to polyamine analogs. J Biol Chem 275, 38319-38328 (2000)

20. Osaki M, M. Osaki, H. Yamashita, K. Shomori, H. Yoshida & H. Ito: Expression of minichromosome maintenance-2 in human malignant fibrous histiocytomas: Correlations with Ki-67 and P53 expression, and apoptosis. Int J Mol Med 10, 161-168 (2002)

21. Ohsawa I, C. Takamura & S. Kohsaka: Fibulin-1 binds the amino-terminal head of beta-amyloid precursor protein and modulates its physiological function. J Neurochem 76, 1411-1420 (2001)

22. Patry C, L. Bouchard, P. Labrecque, D. Gendron, B. Lemieux, J. Toutant, E. Lapointe, R. Wellinger & B. Chabot: Small interfering RNA-mediated reduction in heterogeneous nuclear ribonucleoparticule A1/A2 proteins induces apoptosis in human cancer cells but not in normal mortal cell lines. Cancer Res 63, 7679-7688 (2003)

23. Kalb A, H. Bluethmann, M.W. Moore & W. Lesslauer: Tumor necrosis factor receptors (Tnfr) in mouse fibroblasts deficient in Tnfr1 or Tnfr2 are signaling competent and activate the mitogen-activated protein kinase pathway with differential kinetics. J Biol Chem 271, 28097-28104 (1996)

24. Leto G, N. Gebbia, L. Rausa & F.M. Tumminello: Cathepsin D in the malignant progression of neoplastic diseases. Anticancer Res 12, 235-240 (1992)

25. Tanaka T, S. Akatsuka, M. Ozeki, T. Shirase, H. Hiai & S. Toyokuni: Redox regulation of annexin 2 and its implications for oxidative stress-induced renal carcinogenesis and metastasis. Oncogene 23, 3980-3989 (2004)

26. Brodie C, K. Bogi, P. Acs, P.S. Lorenzo, L. Baskin & P.M. Blumberg: Protein kinase C delta (PKCdelta) inhibits the expression of glutamine synthetase in glial cells via the PKCdelta regulatory domain and its tyrosine phosphorylation. J Biol Chem 273, 30713-30718 (1998)

27. Matassa A.A, L. Carpenter, T.J. Biden, M.J. Humphries & M.E. Reyland: PKCdelta is required for mitochondrial-dependent apoptosis in salivary epithelial cells. J Biol Chem 276, 29719-29728 (2001)

28. Gu Z, C. Flemington, T. Chittenden & G.P. Zambetti: ei24, a p53 response gene involved in growth suppression and apoptosis. Mol Cell Biol 20, 233-240 (2000)

29. Kramer K, E.O. Harrington, Q. Lu, R. Bellas, J. Newton, K.L. Sheahan & S. Rounds: Isoprenylcysteine carboxyl methyltransferase activity modulates endothelial cell apoptosis. Mol Biol Cell 14, 848-857 (2003)

Abbreviations: RPSA: Ribosomal protein SA; MCM2: minichromosome maintenance deficient 2; HNRPA1: heterogeneous nuclear ribonucleoprotein A1; AL: acute leukemia; LPL: lipoprotein lipase; HCV: hepatitis c virus; PCR: polymerase chain reaction; CR: complete remission; ADAM29: a disintegrin and metalloproteinase domain 29; FTI: farnesyl protein transferase inhibitors; GO: gene ontology; S100A11: S100 calcium binding protein A11; MFH: malignant fibrous histiocytoma; sAPP: secreted form of amyloid precursor protein; PRKCD: Protein kinase C delta; RTN4: reticulon 4; MAPK14: mitogen-activated protein kinase 14; ANXA2: annexin A2; NUP214: nucleoporin 214kDa; CDKN2D: cyclin-dependent kinase inhibitor 2D; CLU: clusterin; B2M: beta-2-microglobulin; TXNIP: thioredoxin interacting protein; SAT: spermidine/spermine N1-acetyltransferase; TNFSF1B: tumor necrosis factor receptor superfamily, member 1B; CTSD: cathepsin D; EI24: etoposide induced 2.4 mRNA

Key words: leukemia, cDNA microarray, responsive, refractory

Send correspondence to: Yumin Mao, State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University, Shanghai 200433, P.R. China, Tel: +86-21-65989936, Fax: +86-21-65633919, E-mail: ymmao@fudan.edu.cn