ALBERT

Description: MicroRNAs (miRNAs) are postulated to be important regulators in cancers. Here, we report a genome-wide miRNA expression analysis in 52 acute myeloid leukemia (AML) samples with common translocations, including t(8;21)/AML1(RUNX1)-ETO(RUNX1T1), inv(16)/CBFB-MYH11, t(15;17)/PML-RARA, andMLLrearrangements. Distinct miRNA expression patterns were observed for t(15;17),MLLrearrangements, and core-binding factor (CBF) AMLs including both t(8;21) and inv(16) samples. Expression signatures of a minimum of two (i.e., miR-126/126*), three (i.e., miR-224, miR-368, and miR-382), and seven (miR-17–5p and miR-20a, plus the aforementioned five) miRNAs could accurately discriminate CBF, t(15;17), andMLL-rearrangement AMLs, respectively, from each other. We further showed that the elevated expression of miR-126/126* in CBF AMLs was associated with promoter demethylation but not with amplification or mutation of the genomic locus. Our gain- and loss-of-function experiments showed that miR-126/126* inhibited apoptosis and increased the viability of AML cells and enhanced the colony-forming ability of mouse normal bone marrow progenitor cells alone and particularly, in cooperation withAML1-ETO, likely through targeting Polo-like kinase 2 (PLK2), a tumor suppressor. Our results demonstrate that specific alterations in miRNA expression distinguish AMLs with common translocations and imply that the deregulation of specific miRNAs may play a role in the development of leukemia with these associated genetic rearrangements.

Description: More than 40 proteins have been identified as partners of MLL in acute leukemia. The partner proteins are categorized based on their subcellular localization into either the nucleus or cytoplasm. Recent studies have proposed that the mechanism of transformation of MLL-cytoplasmic protein fusion products is mediated by the oligomerization ability of partner proteins. Gephyrin, which is involved in synaptic anchoring of glycine receptor and certain GABAA receptor subtypes, is a rare partner of MLL in patients with AML. Using an in vivo cross linking assay, we confirmed the dimerization activity of a domain within the MoeA-N domain of Gephyrin, which is located at amino acids 456–476. However, we found that this domain was dispensable for immortalization in the methylcellulose colony-forming assay, indicating that the presence of a dimerization domain was not sufficient for transformation. We also observed that the Tubulin binding domain, which is located at amino acids 322–376, was also dispensable. To evaluate which domain of Gephyrin is critical for the immortalization activity of MLL-Gephyrin, we performed a colony-forming assay in methylcellulose and found that both the MoeA-N (amino acids 354–528) and the MoeA-C (amino acids 691–769) domains of Gephyrin are essential for immortalization. In addition, we observed that a MLL- Gephyrin (444–476) deletion mutant formed dimers using the in vivo cross linking assay. To explore the possibility that both MoeA-N and MoeA-C domains are associated with dimer formation of MLL- Gephyrin, we performed co-immunoprecipitation experiments with three fragments of Gephyrin, MoeA-N, MoCF (amino acids 532–690) and MoeA-C. Our data showed that both the MoeA-N and MoeA-C domains interacted with the MoCF domain of Gephyrin. Taken together, these findings show that Gephyrin has multiple dimerization domains, and that the interaction that links the MoeA-N, MoeA-C, and MoCF domains is critical for the immortalization activity of the MLL- Gephyrin fusion protein. Our data indicate that complex patterns of dimerization exist among MLL partners and suggest that specific types of dimerization domains might be critical for MLL-associated transforming activity.

Description: Chromosome translocations are among the most common genetic abnormalities in human leukemia. Their abnormally expressed genes identify specific markers for their clinical diagnosis. Important biological properties are often conserved across species. However, although genetically engineered mouse leukemia models are well-established, few systematic studies have validated the genes that exhibit similar abnormal expression patterns in both human and mouse leukemia models. MLL-ELL and MLL-ENL fusion genes resulting from t(11;19)(q23;p13.1) and t(11;19)(q23;p13.3), respectively, are frequently involved in human acute leukemia, and in retrovirus-mediated mouse leukemia models. We used the SAGE technique to compare gene expression profiles between MLL-ELL or MLL-ENL myeloid leukemia progenitor cells and normal myeloid progenitor cells in both human and mouse. We analyzed four patient samples (two with each fusion) and two retrovirally-induced mouse leukemias containing either MLL-ELL or MLL-ENL fusions, and a leukemia cell line with an MLL-ELL fusion. 484,303 SAGE tags were identified from the nine samples, yielding 103,899 unique tags in human and 60,993 in mouse samples. We identified 40 candidate genes that appear to be abnormally expressed in both human and murine MLL-ELL leukemias (2 up- and 38 down-regulated), and 72 in both human and murine MLL-ENL leukemias (23 up and 49 down). 25 candidate genes are down-regulated in both types of leukemias, and many of them can bind with and/or regulate other candidate genes in the candidate list. For example, LCN2 can bind directly with and positively regulate MMP9; MMP9 and TMSB4X may positively regulate FOS; FOS and JUNB can bind directly and positively regulate each other. JUNB may inhibit proliferation and promote apoptosis, and it was reported that inactivation of JunB in LT-HSC leads to MPD while its inactivation in committed myeloid progenitors also predisposes to leukemia evolution. LCN2 may also positively regulate apoptosis. Meanwhile, some important candidate genes are observed only in one type of leukemia. For example, both PXN and ARHGEF1 are down-regulated only in MLL-ELL leukemias. PXN can bind directly with ARHGEF1, and the latter may inhibit proliferation. Similarly, MYB is significantly upregulated only in MLL-ENL leukemias, which was reported to play a role in MLL-ENL-mediated transformation. Taken together, some common pathways may exist in the development of both types of leukemias, whereas each may also have their own pathway. The deregulation of the important candidate genes may contribute to leukemogenesis through inhibiting apoptosis while promoting proliferation of hematopoietic cells. We have validated the expression patterns of the candidate genes, and are studying the functions and pathways of the validated candidate genes. Our studies will provide important insights into the complex functional pathways related to MLL rearrangements in the development of acute myeloid leukemia, which may lead to more effective therapy for these leukemias.

Description: Chromosome rearrangements involving the mixed-lineage leukemia gene (MLL) create MLL-fusion proteins, which could drive both acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). The lineage decision of MLL-fusion leukemia is influenced by the fusion partner and microenvironment. To investigate the interplay of fusion proteins and microenvironment in lineage choice, we transplanted human hematopoietic stem and progenitor cells (HSPCs) expressing MLL-AF9 or MLL-Af4 into immunodeficient NSGS mice, which strongly promote myeloid development. Cells expressing MLL-AF9 efficiently developed AML in NSGS mice. In contrast, MLL-Af4 cells, which were fully oncogenic under lymphoid conditions present in NSG mice, displayed compromised transformation capacity in a myeloid microenvironment. MLL-Af4 activated a self-renewal program in a lineage-dependent manner, showing the leukemogenic activity of MLL-Af4 was interlinked with lymphoid lineage commitment. The C-terminal homology domain (CHD) of Af4 was sufficient to confer this linkage. Although the MLL-CHD fusion protein failed to immortalize HSPCs in myeloid conditions in vitro, it could successfully induce ALL in NSG mice. Our data suggest that defective self-renewal ability and leukemogenesis of MLL-Af4 myeloid cells could contribute to the strong B-cell ALL association of MLL-AF4 leukemia observed in the clinic.

Description: Chromosome rearrangements involving the Mixed Lineage Leukemia (MLL) gene on chromosome 11q23 account for 15-20% of acute lymphoid leukemia (ALL) and confer poor prognosis. Such rearrangements generate the MLL-fusion proteins, in which the N-terminus of the MLL protein mediating chromatin interactions is fused with one of more than 70 different partner proteins. Proteins that are frequently involved in MLL translocations, including AF4, ENL, AF9 and AF10, were identified as components of the super elongation complex (SEC) or DOT1L complex (an H3K79 histone methyltransferase). Based on these observations, a consensus model of MLL-fusion leukemogenesis has been proposed, which suggests that all fusion proteins bind to the targets of wildtype MLL and lead to the aberrant transcriptional elongation and H3K79 methylation via the recruitment of SEC or DOT1L complex and thus the uncontrolled activation of the target genes. Therefore, regardless of the nature of fusion partners, all MLL-fusion proteins work in a similar fashion by dysregulating the same pathways. Our group has successfully established xenograft models of MLL-AF4 and MLL-AF9 B-ALL using human CD34+ hematopoietic stem and progenitor cells transduced with FLAG-tagged MLL-Af4 or MLL-AF9, which faithfully recapitulate the clinical features of the disease. We generated MLL-Af4 and -AF9 ALL using matched units of human CD34+ cells to directly test the consensus model. Interestingly, although having the same genetic background, the immunophenotype of the two ALL are unique, with CD34 expressed only in MLL-Af4 but not -AF9 cells. The transcriptomes of the two ALL were analyzed by RNAseq and dysregulated genes were defined by comparison with the transcriptome of normal pro-B cells (p≤0.05, fold-change≥2). Strikingly, only 40% of MLL-Af4-regulated genes overlap with those of MLL-AF9. This transcriptome heterogeneity is mirrored in clinical samples, where the gene signature generated from our model leukemia can be utilized to accurately classify patient samples in unsupervised hierarchical clustering analysis, with MLL-AF4 patient samples readily distinguishable from MLL-AF9 samples. To identify the mechanisms accounting for this heterogeneity, we performed ChIP-seq analysis using anti-FLAG antibody to compare the chromatin occupancy of MLL-Af4 and MLL-AF9 in our model ALL cells. The MLL-Af4 ChIP-seq signal displayed a clear correlation with those of published MLL-AF4 ChIP-seq datasets from patient-derived cell lines, in the range of 70-90%, highlighting the faithfulness of our model. Surprisingly, MLL-Af4 shows a distinct genome-wide distribution compared to MLL-AF9, with only 20% of MLL-Af4 peaks and 35% of MLL-AF9 peaks overlapping. In contrast to MLL-Af4 which predominantly binds to promoter regions, MLL-AF9 has a relatively greater enrichment at intra- and inter-genic regions. Intriguingly, MLL-AF9 tends to bind at repetitive sequences in introns, suggesting these repetitive sequences may serve as regulatory elements for gene expression. Integration with RNAseq data reveals a significant association between differentially-expressed MLL-Af4 and -AF9 targets and specific chromatin binding of different MLL-fusion proteins. This data demonstrates that chromatin binding is not solely controlled by the MLL portion of the fusion protein and that differential target recognition of different fusion proteins is one molecular mechanism driving gene expression heterogeneity. To test whether distinct co-factor recruitment by MLL-fusions adds another layer regulating gene expression heterogeneity beyond DNA binding, we purified the core complexes of MLL-Af4 and -AF9 from ALL cells by anti-FLAG immunoprecipitation and analyzed by mass spectrometry. These experiments identified both common and fusion-specific interacting proteins. MLL-Af4 showed a higher affinity with SEC component EAF2 but a lower affinity with DOT1L compared to MLL-AF9, suggesting that MLL-fusions have distinct associations with complex components which may achieve differential gene regulation. In summary, our data question the consensus model of MLL-fusion leukemia and emphasize that MLL-fusion ALL is a heterogeneous disease. These findings have important implications for therapy development as each MLL-fusion leukemia could have its own Achilles' heel and customized therapy may need to be introduced for each type of disease. Disclosures No relevant conflicts of interest to declare.

Description: The Mixed Lineage Leukemia (MLL) gene on chromosome 11q23 is fused by reciprocal translocation to a diverse group of partner genes that drive both acute myeloid and acute lymphoid leukemia (AML and ALL). As a result of the t(4;11)(q21;q23), MLL fuses to AF4 (also referred to as AFF1), one of the most common MLL fusion partner proteins. Unlike several other MLL fusions that are frequently identified in AML, for example MLL-AF9 caused by t(9;11)(p22;q23), MLL-AF4 is almost exclusively associated with B-cell ALL with a pro-B immunophenotype. It is the most frequent MLL fusion in ALL and accounts for 10-15% of ALL cases. Patients with t(4;11) have a poor prognosis compared with other cytogenetically defined subsets. Although many MLL-fusion leukemia models have successfully been established, it has not been possible to generate a t(4;11) pro-B leukemia model that accurately recapitulates the human disease, hampering research into the molecular mechanisms that underlie the development of this subtype of leukemia. Here we present a faithful human cell based model of t(4;11) pro-B-ALL that fully recapitulates the immunophenotypic and molecular aspects of the human disease. Transduced with a modified MLL-AF4 fusion gene, human hematopoietic CD34+ cells successfully initiate ALL in a xenograft system with high penetrance. The leukemia cells have a CD19+CD34+ pro-B immunophenotype and are CD10(-), a common feature in MLL-AF4 patients. The effect of the oncogene is species-specific, as retroviral transduction and transplantation of murine hematopoietic cells with MLL-AF4 results in only AML using either lymphoid or myeloid conditions. An MLL-AF4 specific gene signature derived from patients is significantly enriched in our model cells, as shown by RNAseq, and the model samples group tightly with MLL-AF4 patients, even when compared with other MLL-fusions in unsupervised hierarchical clustering analysis. Interestingly, using gene profiles of normal pro-B and pre-B cells as reference, our MLL-AF4 leukemia cells show strong enrichment for pro-B genes, while instead, pre-B but not pro-B genes are overrepresented in our MLL-AF9 B-ALL leukemia cells. This differential developmental stage blockage of MLL-fusions is also reflected in patient samples. More strikingly, in accordance with the distinct lineage bias of MLL-fusions observed in the clinic, human cells expressing MLL-AF4 have a strong predilection for the lymphoid lineage and a demonstrated resistance to reprogramming in response to myeloid signals compared to human cells expressing MLL-AF9. This difference in lineage predisposition of MLL-AF4 compared to MLL-AF9 can be attributed to differential effects on lineage-specific gene expression. Under myeloid-priming conditions, phenotypically (CD33+CD19-) and morphologically myeloid MLL-AF4 cells are still able to initiate pro-B ALL in immunodeficient mice, while only AML is generated by MLL-AF9 myeloid cells. Accordingly, an active lymphoid molecular program with lower expression of critical myeloid genes is observed in MLL-AF4 myeloid cells compared to MLL-AF9 myeloid cells. Interestingly, we find that the polycomb gene BMI1, which was reported to be critical to prevent lymphoid priming in normal hematopoiesis, is expressed at significantly lower levels in MLL-AF4 than in MLL-AF9 myeloid cells. Strikingly, this decreased BMI1 expression is evident in primary B-ALL patient samples as well, with MLL-AF9 B-ALL samples demonstrating increased BMI1 relative to MLL-AF4. Reintroduction of BMI1 into MLL-AF4 cells enables AML generation with variable penetrance, while control vector transduced cells always result in B-ALL. Our results demonstrate that lineage fate in response to MLL-fusion protein expression involves a complex interplay of oncogene, intra- and extra-cellular microenvironmental cues. In addition, our data clearly demonstrate the species specificity associated with the t(4;11) oncogene and highlight the limitations of using murine cells in human disease modeling. The model provides a valuable tool to unravel the pathogenesis of MLL-AF4 leukemogenesis. Disclosures Thirman: AbbVie: Research Funding; Pharmacyclics: Research Funding; Gilead: Research Funding.

Description: Chromosome translocations are among the most common genetic abnormalities in human leukemia. The mixed lineage leukemia (MLL) gene was identified as a common target of chromosomal translocations associated with human acute leukemias; it is located on human chromosome 11 band q23 and on mouse chromosome 9. More than 50 different loci are rearranged in11q23 leukemias involving MLL, resulting in either acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL). In general, MLL rearrangements are associated with a poor prognosis. MLL-ELL and MLL-ENL resulting from t(11;19)(q23;p13.1) and t(11;19)(q23;p13.3) respectively are two common examples of these rearrangements. These two fusions are frequently involved in human AML, while MLL-ENL is also involved in human ALL. There is a common observation that important biological properties are often conserved across species. Cross-species sequence comparison has been widely used to infer gene function, but it is becoming apparent that sequence similarity is not always proportional to functional similarity. To determine the function of a gene precisely, therefore, we need to investigate not only its sequence characteristics but also its expression characteristics. Model organisms have contributed substantially to our understanding of the etiology of human disease and the development of new treatment methodologies. However, although genetically engineered mouse leukemia models have been established for many years, there are few systematic studies to identify and study the genes that exhibit similar abnormal expression patterns in both human leukemia and mouse leukemia model cells. To perform an interspecies gene expression comparative study in leukemia, we used the serial analysis of gene expression (SAGE) technique to examine gene expression profiles between MLL-ELL or MLL-ENL myeloid leukemia progenitor cells and normal myeloid progenitor cells in both humans and mice. We obtained 484,303 total SAGE tags for the nine samples and a total of 103,899 unique SAGE tags from five human and 60,993 from four mouse samples. We identified 88 genes that appeared to be significantly deregulated (32 up- and 56 down-regulated) in both human and murine MLL-ELL and/or MLL-ENL leukemia. Fifty-seven genes have not been reported previously. A large-scale quantitative real-time PCR (qPCR) assay was performed to validate the candidate genes, and 84% (36/43) of the tested SAGE candidate genes were confirmed. The most up-regulated genes include several HOX genes (e.g., HOX A5, HOXA9 and HOXA10) and a HOX cofactor MEIS1; their overexpression is a hallmark of MLL-rearrangement leukemia. The top down-regulated genes include LTF, LCN2, MMP9, S100A8, S100A9, PADI4, TGFBI and CYBB. Remarkably, up-regulated genes have a much higher percentage of enrichment in Gene Ontology (GO) terms related to gene expression and transcription, whereas down-regulated genes are more enriched in GO terms related to apoptosis, signal transduction and response. Thus, the up-regulation of genes responsible for gene expression and transcription but down-regulation of genes responsible for apoptosis, signal transduction and response, can promote cell proliferation and inhibit apoptosis, and thereby contribute to the development of leukemia. We showed that the CpG islands of several significantly down-regulated genes including LIF, TGFBI and G0S2 are hypermethylated. We also examined the expression of microRNAs from the mir-17–92 cluster, which are overexpressed in human MLL-rearrangement leukemias, and showed that seven individual microRNAs (i.e., miR-17-5p, miR-17-3p, miR-18a, miR-19a, miR-20a, miR-19b and miR-92) within this cluster are also overexpressed in mouse MLL-rearrangement leukemia cells. Nineteen putative targets (i.e., APP, RASSF2, SH3BP5, DBN1, ELK3, FLT1, GNAI1, HIF1A, ITGA6, MN1, POU4F1, RB1, RGL1, RNF167, SASH1, SLC24A3, TNFRSF21, WWP1 and YES1) of these microRNAs were reported and/or confirmed by our qPCR to be down-regulated in MLL-rearrangement leukemias. We further confirmed both APP and RASSF2 as direct targets of miR-17 through luciferase reporter and mutagenesis assay. The identification and validation of gene expression changes in MLL-rearrangement human and murine leukemia provides important insights into the genetic pathways that are important for MLL fusion-induced leukemogenesis.

Description: Acute myeloid leukemia (AML) is the most common type of acute leukemia in adults. It is estimated that 13,410 cases will be diagnosed and 8,990 will die of AML in the United States in 2007 (http://seer.cancer.gov). AML is a genetically diverse hematopoietic malignancy with variable response to treatment. Expression profiling of protein-coding genes using DNA microarray in AML has resulted in inconsistent data from different laboratories. Therefore, further validation of these observations in large cohorts and in independent studies is definitely required before clinical application becomes feasible. Recently, Golub and colleagues described a new, bead-based flow cytometric microRNA (miRNAs, miRs) expression profiling method that could successfully classify tumors. MiRNAs are endogenous ∼22 nucleotide non-coding RNAs, which can function as oncogenes and tumor suppressors. To provide new insights into the complex genetic alterations in leukemogenesis and to identify novel markers for diagnosis and treatment of AML, we performed a genome-wide analysis of miRNA expression profiles using the bead-based method on 54 AML samples with common translocations including t(15;17), t(8;21), inv(16), and 11q23 rearrangement, along with normal controls. In both unsupervised and supervised hierarchical cluster analyses, we observed that t(15;17) samples grouped together as one cluster, as do the 11q23 rearrangement samples. Interestingly, t(8;21) and inv(16), both CBF (core-binding factor) AMLs, grouped together as a unique cluster. Forty-one miRNAs exhibited significantly differential expression between different subtypes of AMLs, and/or between AMLs and normal controls. Notably, expression signature of a minimal number of two, three, and seven miRNAs could be used for class prediction of CBF, t(15;17), and 11q23 rearrangement AMLs, respectively, with an overall diagnostic accuracy of 94–96%. We further showed that overexpression of the two discriminatory miRNAs in CBF AML is associated with epigenetic regulation, rather than DNA copy number amplification. Moreover, several important target genes of these discriminatory miRNAs have also been validated. We are currently exploring the role of these discriminatory miRNAs and their critical target genes in the development of AML using in vitro and in vivo models. This work will enhance our understanding of the biological role of these miRNAs and their targets in leukemogenesis.

Description: The t(4;11)(q21;q23) translocation is a hallmark of infant acute lymphoblastic leukemia (ALL), which results in the fusion of the MLL gene on chromosome 11 and the AF4 gene on chromosome 4. MLL-AF4 fusion is the most common consequence of chromosomal translocations in infant leukemia and is associated with a poor prognosis. To identify leukemia-related genes, we used the SAGE technique to compare gene expression profiles between two MLL-AF4 patient samples and one normal sample (CD19+ progenitor B cells; 216,464 tags in total). We identified 61 candidate genes that appear to be abnormally expressed in the leukemia samples (29 up- and 32 down-regulated). Remarkably, we found that many candidate genes appear to play important role in the development of B cells. In addition, many candidate genes can bind with and/or regulate other candidates in the candidate gene list. For example, SYK, BTK and BLNK can bind directly and regulate each other. SYK can also bind directly with TNFRSF1B. In addition, EBF may positively regulate BLK, while BLK can bind directly with BTK. All six of these genes are significantly down-regulated in MLL-AF4 leukemia samples. BTK, SYK and BLK are tyrosine kinases. BTK (B-cell progenitor tyrosine kinase) is a key regulator in B-lymphocyte differentiation and activation. BLK (B-lymphocyte-specific tyrosine kinase) is expressed only in B lymphocytes, and controls pre-B cell development. SYK (spleen tyrosine kinase) is widely expressed in hematopoietic cells, which can phosphorylate BLNK (B-cell linker protein). BLNK represents a central linker protein that bridges the B-cell receptor-associated kinases and may regulate B-cell function and development. EBF (early B-cell factor) is a tissue-specific and differentiation stage-specific DNA-binding protein, and mice lacking Ebf are unable develop B lymphoid cells. TNFRSF1B is strongly expressed on stimulated T and B lymphocytes. Moreover, previous studies indicate that BTK, BLK, SYK, BLNK and TNFRSF1B can positively regulate apoptosis, while BTK can also positively regulate differentiation. Thus, their down-regulation may inhibit apoptosis and differentiation, and thereby contribute to leukemogenesis. In contrast, GNA12, a transforming oncogene which can enhance proliferation and transformation and can bind directly with BTK, is significantly up-regulated in MLL-AF4 leukemia cells. Its up-regulation may also be important to leukemogenesis. Taken together, the deregulation of the important candidate genes may contribute to leukemogenesis through inhibiting apoptosis and differentiation while promoting proliferation of hematopoietic cells. We have validated the expression patterns of the candidate genes with real-time quantitative RT-PCR and are studying the functions and pathways of the validated candidate genes using RNAi and retrovirus transduction over-expression methods. In addition, we will also establish knock-in or knock-out mouse models for the most promising functional candidate genes to see the effect on the development of leukemia. Our studies will provide important insights into the complex functional pathways related to MLL rearrangements in the development of acute lymphoblastic leukemia, which may lead to more effective therapy for these leukemias.