ALBERT

Description: The diagnosis of myelodysplastic syndrome (MDS) currently relies primarily on the morphologic assessment of the patient's bone marrow and peripheral blood cells. Moreover, prognostic scoring systems rely on observer-dependent assessments of blast percentage and dysplasia. Gene expression profiling could enhance current diagnostic and prognostic systems by providing a set of standardized, objective gene signatures. Within the Microarray Innovations in LEukemia study, a diagnostic classification model was investigated to distinguish the distinct subclasses of pediatric and adult leukemia, as well as MDS. Overall, the accuracy of the diagnostic classification model for subtyping leukemia was approximately 93%, but this was not reflected for the MDS samples giving only approximately 50% accuracy. Discordant samples of MDS were classified either into acute myeloid leukemia (AML) or “none-of-the-targets” (neither leukemia nor MDS) categories. To clarify the discordant results, all submitted 174 MDS samples were externally reviewed, although this did not improve the molecular classification results. However, a significant correlation was noted between the AML and “none-of-the-targets” categories and prognosis, leading to a prognostic classification model to predict for time-dependent probability of leukemic transformation. The prognostic classification model accurately discriminated patients with a rapid transformation to AML within 18 months from those with more indolent disease.

Description: Microarray analysis can identify differentially expressed genes associated with distinct clinical and therapeutically relevant classes of both pediatric and adult leukemias. Recently, the MILE (Microarray Innovations in Leukemia) research study program has been launched in 10 centers: 7 from the European Leukemia Network (ELN, WP13) and 3 from the US. In this study, which will include 4,000 patients, the clinical accuracy of gene expression profiles of 16 acute and chronic leukemia subclasses, MDS, and non-leukemia as control will be assessed as compared to current routine diagnostic workup. Each center is trained on an identical microarray protocol and uses the same laboratory equipment, kits, and reagents for target preparation (Affymetrix HG-U133 Plus 2.0). First, the intra- and inter-laboratory comparability was investigated using 2 different cell line samples, MCF-7 and HEPG2, with different amounts of starting material (1 μg and 5 μg input for cDNA synthesis). Also, each center prepared in parallel total RNA and processed replicate samples from three leukemia pts (AML with t(8;21), CML, and CLL). We found a high reproducibility among the different centers: unsupervised analyses accordingly group the two different cell lines distinct from the three types of leukemia samples. In hierarchical clustering and principal component analysis the non-leukemia samples are clearly distinct from the leukemia samples and no clustering of the individual centers can be seen. Remarkably, for the replicates of the leukemia samples the squared correlation coefficients of gene expression range between 0.975 and 0.997 for CML, between 0.975 and 0.998 for CLL, and between 0.970 and 0.999 for the AML with t(8;21). Secondly, the samples were analyzed by a classification algorithm. The algorithm was trained on a database that contains gene expression profiles of 〉1,600 leukemia patients and cell lines and can distinguish 16 different classes of leukemia, MDS, and non-leukemia. Several methods are used to form linear classifiers for all 18 * (18 – 1)/2 = 153 class pairs. The average cross-validation accuracy is 91% or higher. Miscalls are predominantly seen in the distinction between MDS and AML with normal karyotype. The accuracy of resubstitution (application of the classifier to the data forming the classifier) is 100%. For the new data accurate predictions for the non-leukemia cell lines, AML with t(8;21), and CLL were observed. Interestingly, the CML in blast crisis is predicted as AML with other abnormalities. This may be due to the fact that the classifier was trained on CML in chronic phase only. In conclusion, for the first time an international multi-center research study demonstrates a very high reproducibility of microarray analyses performed at different centers for the same leukemia samples. This lays the foundation for an international clinical research initiative evaluating the application of microarrays in the diagnosis and classification of hematological malignancies.

Description: During the years of 2005 to 2008, the MILE (Microarray Innovations in LEukemia) study research program was performed in 11 laboratories across three continents: 7 from the European Leukemia Network (ELN, WP13), 3 from the US and 1 in Singapore. The first stage was designed as biomarker discovery phase to generate whole-genome gene expression profiles (GEP) from recognized categories of clinically relevant leukemias and myelodysplastic syndromes (MDS). These were C1: mature B-ALL with t(8;14), C2: pro-B-ALL with t(11q23)/MLL, C3: c-ALL/pre-B-ALL with t(9;22), C4: T-ALL, C5: ALL with t(12;21), C6: ALL with t(1;19), C7: ALL with hyperdiploid karyotype, C8: c-ALL/pre-B-ALL without specific genetic abnormalities, C9: AML with t(8;21), C10: AML with t(15;17), C11: AML with inv(16)/t(16;16), C12: AML with t(11q23)/MLL, C13: AML with normal karyotype or other abnormalities, C14: AML with complex aberrant karyotype, C15: CLL, C16: CML, C17: MDS, and C18: non-leukemic and healthy bone marrow samples as controls and were compared to conventional diagnostic assays (“Gold Standard”). Data from the completed MILE Stage I included 2143 retrospectively collected adult and pediatric samples tested with HG-U133 Plus 2.0 microarrays (Affymetrix). In total only 47 analyses (2.1%) failed technical quality criteria. Cross-validation accuracy (average of three 30-fold cross-validations) of the final 2096 MILE Stage I samples was 92.1% concordant with the center-specific “Gold Standard” diagnosis (average call rate 99.4%). In nine classes the sensitivity was ≥94.3%: C2, C3, C4, C5, C9, C10, C11, C15, and C16. Lower sensitivities were observed for C7, C8, C14, and C17; which can largely be explained by the biological heterogeneity and non-standardized “Gold Standard” definitions for these entities. Yet, it is notable that all these classes showed specificities above 98.1%. In order to assess the clinical utility of microarray-based diagnostics a prospective Stage II was subsequently performed using a customized microarray representing 1480 probe sets. Overall, 1156 high quality GEP have been generated in MILE Stage II and represent an independent and blinded test set for the algorithms developed. A focused classification scheme aimed at accurately addressing only acute leukemias resulted in a 95.5% median sensitivity and a 99.5% median specificity for the 14 classes included in the classifier (C1 – C14, n=696). Lower accuracies were observed for the interface of C7–C8 in ALL, as well as C12 and C14 in AML. Interestingly, during the process of discrepant results analyses, it was observed that for 7.5% (n=52) of acute leukemias microarray results were correctly diagnosing samples as compared to the initial “Gold Standard” diagnoses entered into the study database, either because of erroneous entries into case report forms (24%) or subsequent re-testing of left-over material following the suggested diagnosis from the microarray (76%). In addition, predicted accuracies for CLL, CML and MDS in Stage II were 99.2%, 95.2%, and 81.5%, respectively. In conclusion, the MILE research study confirms in a final cohort of 3252 patients that microarrays accurately classify acute and chronic leukemia samples into known diagnostic and prognostic sub-categories. This final report underlines that the standardized method of gene expression profiling with low technical failure rate and simplified standard operating procedures may improve current “Gold Standards” as an adjunct to conventional diagnostic algorithms and potentially offers a reliable diagnostic/prognostic tool for many patients who don’t have access to a state-of-the-art “Gold Standard” workup. Our gene expression database, intended to be submitted to the public domain, will further contribute to research that aims to elucidate the molecular understanding of leukemias.

Description: The MILE (Microarray Innovations in LEukemia) study has previously shown that gene expression signatures associated with initial leukaemia classifier (LCver7) give an overall cross-validation accuracy of 〉95% for distinct sub-classes of pediatric and adult leukemias. However, only 50% of the 174 MDS samples in the whole-genome microarray analysis (Stage 1) of the MILE study were correctly identified; the remainder showed AML-like or non-leukemia-like gene profiles. An external morphological review (DB & HL) according to FAB and WHO criteria, of the 174 slides was performed independently (blind) which resulted in 6 samples being reclassified as AML and 4 non-leukemia cases excluded from the study. A recently improved, hierarchical based algorithm correctly identified 100% of the confirmed MDS cases. In this study, using LCver7, the confirmed 164 samples had 50% MDS classifications (Class 17), 23.8% non-leukemia classifications (Class 18), and 22.6% AML classifications (Classes 13 or 14) with the remaining 3.7% having a classification tie between 2 or 3 Classes (due to low confidence). No 5q- syndrome patients had an AML call, whilst 68.3% of RAEB2 patients had an AML classification and none were Class 18. Similarly, 95.6% of Low IPSS patients were classified as Class 17 or 18, whilst all patients (n=5) with High IPSS had an AML call. The classification was independent of blast cells: 10.2% of Class 18 calls had 〉5% blasts; 28.2% of AML-like cases had

Description: The t(11;17)(q23;q21) translocation is associated with a retinoic acid (RA)–insensitive form of acute promyelocytic leukemia (APL), involving the production of reciprocal fusion proteins, promyelocytic leukemia zinc finger–retinoic acid receptor α (PLZF-RARα) and RARα-PLZF. Using a combination of chromatin immunoprecipitation promotor arrays (ChIP-chip) and gene expression profiling, we identify novel, direct target genes of PLZF-RARα that tend to be repressed in APL compared with other myeloid leukemias, supporting the role of PLZF-RARα as an aberrant repressor in APL. In primary murine hematopoietic progenitors, PLZF-RARα promotes cell growth, and represses Dusp6 and Cdkn2d, while inducing c-Myc expression, consistent with its role in leukemogenesis. PLZF-RARα binds to a region of the c-MYC promoter overlapping a functional PLZF site and antagonizes PLZF-mediated repression, suggesting that PLZF-RARα may act as a dominant-negative version of PLZF by affecting the regulation of shared targets. RA induced the differentiation of PLZF-RARα–transformed murine hematopoietic cells and reduced the frequency of clonogenic progenitors, concomitant with c-Myc down-regulation. Surviving RA-treated cells retained the ability to be replated and this was associated with sustained c-Myc expression and repression of Dusp6, suggesting a role for these genes in maintaining a self-renewal pathway triggered by PLZF-RARα.

Description: Abstract 3619 Erythropoietin (Epo) and its receptor (EpoR) play vital roles in regulating red blood cell production. However, aberrant over-expression of EpoR has been reported in a wide range of tumours and hematological malignancies, particularly acute lymphoblastic leukemia (ALL) with the chromosomal translocation TEL-AML1 (ETV6/RUNX1). Around 25% of B-cell ALLs contain this chromosomal translocation which is associated with a favourable, prognosis but the role of EpoR is unknown. We have investigated whether methylation, transcription factors or miRNA regulation are implicated in the mechanism of the specific EpoR up-regulation associated with the TEL-AML1 rearrangement using two human B precursor cell line models. The pre-B REH cell line is TEL-AML1 positive whereas the pre-B NALM-6 cell line is TEL-AML1 negative; in addition the erythroleukemia cell line UT-7, which constitutively over- expresses EpoR was used as a positive control. Sequencing confirmed that the EpoR in these cell lines was wild type. Quantitative RT-PCR (RQ-PCR) of EpoR mRNA levels showed ~25 fold higher expression in REH cells compared to NALM-6 cells, verified by western blot analysis. RQ-PCR analysis of 20 pediatric ALL patient samples confirmed a 14-fold up-regulation (p

Description: Abstract 224 During hematopoiesis, all-trans-retinoic acid (ATRA), a natural derivative of vitamin A, has been shown to induce both myelomonocytic progenitor/stem cell differentiation and self-renewal. Although these opposing effects are likely to be partly due to developmental differences, it has been shown that pro- and anti-differentiation effects of ATRA are mediated by distinct retinoic acid receptor isotypes (RARα and RARγ, respectively). With the exception of acute promyelocytic leukemia (APL), ATRA treatment as a single agent has not been successful in other types of acute myeloid leukemia (AML). We have previously hypothesized that one of the underlying reasons for poor response of non-APL AML to ATRA (pan-RAR agonist) is aberrant expression and/or activities of RAR isotypes favoring RARγ and cell growth versus differentiation. Consistently, we have reported that expression of RARα isoforms, particularly ATRA-inducible RARα2, are down-regulated in AML (Blood. 2008; 111:2374). Epigenetic analysis of patient samples revealed that relative to normal CD33+ cells, the loss of RARα2 in AML is associated with a diminution in levels of histone histone H3 lysine 4 dimethylation (H3K4me2) on the ATRA-responsive RARA2 promoter (a modification associated with transcriptional activation). Interestingly, the H3K4me1/me2 demethylase LSD1/KDM1 (AOF2) is highly expressed in AML patients (www.proteinatlas.org). A number of small molecules that target this enzyme (LSD1i) are in development and, collectively, these data predict that the use of LSD1i will facilitate induction of expression of genes that are required for differentiation of AML cells. In this study we used tranylcypromine (TCP, a monoamine oxidase used as an antidepressant and anxiolytic agent in the clinical treatment of mood and anxiety disorders, respectively), which functions a time-dependent, mechanism-based inhibitor of LSD1. Here we show that TCP unlocked the ATRA-driven therapeutic differentiation response in non-APL AML cell lines including the TEX cell line, which is derived from primitive human cord blood cells immortalized by expression of the TLS-ERG oncogene. TEX cells are 〉90% CD34+, respond poorly to ATRA and mimic features of primary human AML and leukemia initiating cells (Leukemia. 2005; 19:1794). Consistent with this, ATRA/TCP treatment increased differentiation in primary patient samples. ATRA alone had in general only small effects in primary AML samples and TCP showed minimal activity in most cases. Furthermore, shRNA-mediated knockdown of LSD1 confirmed a critical role for this enzyme in blocking the ATRA response in AML cells. The effects of ATRA/TCP on AML cell maturation were paralleled by enhanced induction of genes associated with myelomonocytic differentiation, including direct ATRA targets. LSD1i treatment did not lead to an increase in genome-wide H3K4me2, but did increase H3K4 dimethylation of myelomonocytic differentiation-associated genes. Importantly, treatment with ATRA/TCP dramatically diminished the clonogenic capacity of AML cells in vitro and engraftment of cells derived from AML patients in vivo, suggesting that ATRA/TCP may also target leukemic stem cells. These data strongly suggest that LSD1 may, at least in part, contribute to AML pathogenesis by inhibiting the normal function of ATRA in myelomonocytic development and pave the way for effective differentiation therapy of AML. Disclosures: No relevant conflicts of interest to declare.

Description: The RUNX1 gene (aka AML1 on chromosome 21) encodes the alpha component of the Core Binding Factor (CBF) complex. This heterodimeric transcription factor is central to haematopoietic development and has been shown to be involved in the regulation of a number of haematopoietic-specific genes including IL-3, MPO and GM-CSF. RUNX1 is one of the most frequently disrupted genes in acute myeloid leukaemia (AML); and is particularly associated with chromosomal translocations. The t(8;21) encodes the RUNX1-RUNX1T1 (aka AML1-ETO) fusion protein which promotes self-renewal of haematopoietic cells and also inhibits their subsequent differentiation. Leukaemias expressing this abnormality are generally associated with a good prognosis in terms of complete remission, relapse risk and overall survival compared with other subtypes and tends to respond favourably to chemotherapeutic agents. However it is not currently known why patients expressing the t(8;21) have a good prognosis. It has been suggested that in AML patients expressing RUNX1-RUNX1T1, the fusion gene may promote the expression of p-glycoprotein (encoded by MDR-1) in mediating drug resistance. We therefore tested this hypothesis directly by expressing the RUNX1-RUNX1T1 fusion as a single abnormality in human haematopoietic cell subsets and performed Affymetrix microarray analysis to determine whether this fusion had any effect on the transcription of MDR genes. Using this approach we generated independent replicate sets of data from control and RUNX1-RUNX1T1 matched CD34+ cultures as well as matched sets constituting granulocytic (CD14lo, CD36lo, CD15hi) and monocytic (CD14hi) unilineage populations (isolated from day 6 cultures by immunomagnetic sorting). cRNA was prepared from each sample and hybridised to Affymetrix human 133A oligonucleotide arrays which allowed the simultaneous analysis of 6 MDR family gene members. In each of these populations, the expression of MDR genes was not significantly different from controls. We could therefore find no evidence that RUNX1-RUNX1T1 expression directly influences MDR gene expression as a single abnormality. We next addressed the issue of whether the t(8;21) abnormality directly influences the susceptibility to chemotherapeutic agents. We therefore assessed the sensitivity of CD34+ cells expressing RUNX1-RUNX1T1 to a number drugs commonly used to treat AML (Daunorubicin, Cytarabine, Fludarabine, Idarubicin or Etoposide) in comparison with matched controls. Remarkably, none of these agents differentially affected the growth of RUNX1-RUNX1T1 transduced cells. Since treatment of AML commonly involves multiple drugs, we also determined the effect of combining two or more of these chemotherapeutic agents. Again, we observed little difference in the in vitro growth response of RUNX1-RUNX1T1 expressing cells compared to controls. Taken together, these data suggest that expression of RUNX1-RUNX1T1 itself has no effect on the intrinsic susceptibility to cytotoxic chemicals. This raises the alternative hypothesis that RUNX1-RUNX1T1 moderates the influence of secondary abnormalities which are required for RUNX1-RUNX1T1 expressing cells to undergo leukaemic transformation.

Description: Abstract 1704 Gene expression profiling studies have been performed in MDS to better characterize these diseases. However, the molecular pathogenesis of low-risk MDS is not yet fully understood. Furthermore, the transcriptional activity is dependent on many factors including epigenetic modifications. Therefore the integration of genome-wide epigenetic regulatory marks along with gene expression levels would provide additional information regarding the biological characteristics of low-risk MDS. A total of 83 low-risk MDS patients and 36 age-matched controls were included in the study. A cohort of 18 patients with low-risk MDS and seven controls were included in a simultaneous integrative study of methylation and expression, while the whole series was used as a control group of expression data. Both the RNA and the DNA were isolated from BM mononucleate cells and hybridised with the Human Genome Expression Array (U133 Plus) from Affymetrix and MCAM Array from University Health Network (Canada), respectively. For analysis and interpretation of the hybridisation results, the R/Bioconductor program, DAVID bioinformatic resource, the web-delivered bioinformatics tool set Ingenuity Pathway Analysis and Metacore Analytical Suite were used. The results generated by expression and methylation microarrays were confirmed using Q- PCR and pyrosequencing, respectively. A total of 817 differentially methylated genes were identified as being present in low-risk MDS (p〈 0.10); hyper-methylated genes (n=457) were more frequent than hypo-methylated genes (n=360). In addition, mRNA expression profiling identified 1005 genes that significantly differed between low-risk MDS and control group. Integrative analysis of the epigenetic and expression profiles revealed that 66.7% of the hyper-methylated genes were under-expressed in low-risk MDS cases. The most represented categories were regulation of apoptosis, gene expression, immune response and RNA process. BCL2, ETS1, IL27RA and DICER1, all of them hyper-methylated and down-expressed, were the most significant genes related to these functions. 1. Regarding apoptosis and BCL2, an over-expression of BCL2L11 and MYC were found in low-risk MDS. In contrast, BAX and CUX1 were under-expressed with respect to the control group. In addition, SYK gene was also hyper-methylated and under-expressed. 2. Promoter region analysis demonstrated that ETS1 transcription factor was involved in the regulation of 83 target genes included in the down-regulation signature of the low-risk MDS patients. The most significant functions of these target genes revealed that the cell-to-cell signaling and interaction pathway were prominently affected. In addition, apoptosis was identified as the function with the most number of down-regulated target genes. Therefore, the overall apoptosis pathway could be affected in low-risk MDS patients in two ways: methylation and decreased expression of BCL2 with the deregulation of related genes, as well as methylation and decreased expression of the ETS1 transcription factor with the deregulation of the apoptosis-related targets. 3. Regarding immune response, the study showed that besides IL27RA, another nine interleukins and interleukin receptors were under-expressed in the same cohort of patients: IL16, IL32, IL1RAP, IL2RB, IL6R, IL7R, IL10RA, IL10RB and IL13RA1. Three of them (IL16, IL1RAP and IL10RB) had direct genetic interactions with IL27RA. 4. Finally, the identification of DICER1 as a gene significantly altered by methylation and expression in low-risk MDS prompted us to measure the 183 miRNAs expression. A general down-regulation of miRNAs was observed in low-risk MDS cases respect to the control group (p=0.039). Our integrative analysis revealed that aberrant epigenetic regulation is a hallmark of low-risk MDS patients and could play a central role in these diseases. Furthermore, we highlight candidate DNA methylation changes associated with low-risk MDS patients. Disclosures: No relevant conflicts of interest to declare.