Oncogenic NRAS Primes Primary Acute Myeloid Leukemia Cells for Differentiation

RAS mutations are frequently found among acute myeloid leukemia patients (AML), generating a constitutively active signaling protein changing cellular proliferation, differentiation and apoptosis. We have previously shown that treatment of AML patients with high-dose cytarabine is preferentially beneficial for those harboring oncogenic RAS. On the basis of a murine AML cell culture model, we ascribed this effect to a RAS-driven, p53-dependent induction of differentiation. Hence, in this study we sought to confirm the correlation between RAS status and differentiation of primary blasts obtained from AML patients. The gene expression signature of AML blasts with oncogenic NRAS indeed corresponded to a more mature profile compared to blasts with wildtype RAS, as demonstrated by gene set enrichment analysis (GSEA) and real-time PCR analysis of myeloid ecotropic viral integration site 1 homolog (MEIS1) in a unique cohort of AML patients. In addition, in vitro cell culture experiments with established cell lines and a second set of primary AML cells showed that oncogenic NRAS mutations predisposed cells to cytarabine (AraC) driven differentiation. Taken together, our findings show that AML with inv(16) and NRAS mutation have a differentiation gene signature, supporting the notion that NRAS mutation may predispose leukemic cells to AraC induced differentiation. We therefore suggest that promotion of differentiation pathways by specific genetic alterations could explain the superior treatment outcome after therapy in some AML patient subgroups. Whether a differentiation gene expression status may generally predict for a superior treatment outcome in AML needs to be addressed in future studies.     

A hematopoietic-specific transmembrane protein, Art-1, is possibly regulated by AML1

The functions of AML1 in hematopoietic differentiation are repressed by AML1-mutants including the AML1/ETO chimeric protein, which is seen in t(8;21) acute myeloid leukemia. Erythroid progenitors of the patients with t(8;21) AML expressed AML1/ETO. To investigate the effect of AML1/ETO in erythroid cells, we made a tetracycline-regulated AML1/ETO overexpression system in mouse erythroleukemic (MEL) cells. Enforced AML1/ETO repressed the terminal erythroid differentiation. Furthermore, we performed representational difference analysis using this MEL cell system to clone the downstream targets of AML1 in erythroid cell differentiation. We cloned a novel transmembrane protein, Art-1 (AML1-regulated transmembrane protein 1), which is a member of tetramembrane spanning superfamily. Art-1 expression was restricted in hematopoietic cells. It was upregulated by AML1 and downregulated by AML1/ETO in both erythroid and myeloid cells, and increased during erythroid cell differentiation. Art-1 may play an important role in the differentiation of erythroid cells, possibly as a direct downstream target of AML1.     

The inv(16) cooperates with ARF haploinsufficiency to induce acute myeloid leukemia

The inv(16) is one of the most frequent chromosomal translocations associated with acute myeloid leukemia (AML) and creates a chimeric fusion protein consisting of most of the runt-related X1 co-factor, core binding factor beta fused to the smooth muscle myosin heavy chain MYH11. Expression of the ARF tumor suppressor is regulated by runt-related X1, suggesting that the inv(16) fusion protein (IFP) may repress ARF expression. We established a murine bone marrow transplant model of the inv(16) in which wild type, Arf+/-, and Arf-/- bone marrow were engineered to express the IFP. IFP expression was sufficient to induce a myelomonocytic AML even when expressed in wild type bone marrow, yet removal of only a single allele of Arf greatly accelerated the disease, indicating that Arf is haploinsufficient for the induction of AML in the presence of the inv(16).     

Algebraic dependency models of protein signal transduction networks from time-series data

Signal transduction networks are crucial for inter- and intra-cellular signaling. Signals are often transmitted via covalent modification of protein structure, with phosphorylation/dephosphorylation as the primary example. In this paper, we apply a recently described method of computational algebra to the modeling of signaling networks, based on time-course protein modification data. Computational algebraic techniques are employed to construct next-state functions. A Monte Carlo method is used to approximate the Deegan-Packel Index of Power corresponding to the respective variables. The Deegan-Packel Index of Power is used to conjecture dependencies in the cellular signaling networks. We apply this method to two examples of protein modification time-course data available in the literature. These experiments identified protein carbonylation upon exposure of cells to sub-lethal concentrations of copper. We demonstrate that this method can identify protein dependencies that might correspond to regulatory mechanisms to shut down glycolysis in a reverse, step-wise fashion in response to copper-induced oxidative stress in yeast. These examples show that the computational algebra approach can identify dependencies that may outline signaling networks involved in the response of glycolytic enzymes to the oxidative stress caused by copper.     

c-Jun N-terminal kinase mediates AML1-ETO protein-induced connexin-43 expression

AML1-ETO fusion protein, a product of leukemia-related chromosomal translocation t(8;21), was reported to upregulate expression of connexin-43 (Cx43), a member of gap junction-constituted connexin family. However, its mechanism(s) remains unclear. By bioinformatic analysis, here we showed that there are two putative AML1-binding consensus sequences followed by two activated protein (AP)1 sites in the 5'-flanking region upstream to Cx43 gene. AML1-ETO could directly bind to these two AML1-binding sites in electrophoretic mobility shift assay, but luciferase reporter assay revealed that the AML1 binding sites were not indispensable for Cx43 induction by AML1-ETO protein. Conversely, AP1 sites exerted an important role in this event. In agreement, AML1-ETO overexpression in leukemic U937 cells activated c-Jun N-terminal kinase (JNK), while its specific inhibitor SP600125 effectively abrogated AML1-ETO-induced Cx43 expression, indicating that JNK signaling pathway contributes to AML1-ETO induced Cx43 expression. These results would shed new insights for understanding mechanisms of AML1-ETO-associated leukemogenesis.     

Multidrug resistance determinants in acute myeloid leukemia developed in persons exposed to ionizing radiation due to the Chernobyl accident

The results of multidrug resistance determinants expression analysis on leukemic cells of 56 acute myeloid leukemia (AML) patients by immunophenotyping are presented. Of these, there were 21 persons exposed to ionizing radiation due to the Chemobyl accident with radiation-associated AML and 35 patients with spontaneous leukemia. The aim of this study was to determine if transport proteins (P-glycoprotein, LRP, and MDR1), apoptosis-related proteins (Fas, Bcl-2, Bax, p53, and Bcl-X(L)), and topoisomerase IIalpha expression in AML patients with the history of radiation exposure differed from those in spontaneous AML cases. Leukemic cells in patients with radiation-associated diseases compared to spontaneous AML more often overexpressed antiapoptotic oncoprotein Bcl-2 (12/21 vs. 6/35, p < 0.005) and less often demonstrated expression of Fas receptor (12/21 vs. 30/35, p < 0.05). Moreover, leukemic cells were simultaneously Fas negative and Bcl-2 positive in 4 out of 21 patients exposed to ionizing radiation but none of spontaneous cases had similar phenotype (p < 0.05). Leukemic cells in patients with radiation-associated AML compared to spontaneous cases more often were P-glycoprotein positive (12/20 vs 9/31, p < 0.05). P-glycoprotein overexpression significantly correlated with resistant disease in patients with radiation-associated AML (r = 0.47, p < 0.05), but was not a prognostic variable for the treatment outcome in terms of overall survival. Defects in pathways of drug-induced apoptosis and function of pump, that actively effluxes drugs could contribute significantly to developing drug resistance in radiation-associated AML.     

RCFGL: Rapid Condition adaptive Fused Graphical Lasso and application to modeling brain region co-expression networks

Inferring gene co-expression networks is a useful process for understanding gene regulation and pathway activity. The networks are usually undirected graphs where genes are represented as nodes and an edge represents a significant co-expression relationship. When expression data of multiple (p) genes in multiple (K) conditions (e.g., treatments, tissues, strains) are available, joint estimation of networks harnessing shared information across them can significantly increase the power of analysis. In addition, examining condition-specific patterns of co-expression can provide insights into the underlying cellular processes activated in a particular condition. Condition adaptive fused graphical lasso (CFGL) is an existing method that incorporates condition specificity in a fused graphical lasso (FGL) model for estimating multiple co-expression networks. However, with computational complexity of O(p²K log K), the current implementation of CFGL is prohibitively slow even for a moderate number of genes and can only be used for a maximum of three conditions. In this paper, we propose a faster alternative of CFGL named rapid condition adaptive fused graphical lasso (RCFGL). In RCFGL, we incorporate the condition specificity into another popular model for joint network estimation, known as fused multiple graphical lasso (FMGL). We use a more efficient algorithm in the iterative steps compared to CFGL, enabling faster computation with complexity of O(p²K) and making it easily generalizable for more than three conditions. We also present a novel screening rule to determine if the full network estimation problem can be broken down into estimation of smaller disjoint sub-networks, thereby reducing the complexity further. We demonstrate the computational advantage and superior performance of our method compared to two non-condition adaptive methods, FGL and FMGL, and one condition adaptive method, CFGL in both simulation study and real data analysis. We used RCFGL to jointly estimate the gene co-expression networks in different brain regions (conditions) using a cohort of heterogeneous stock rats. We also provide an accommodating C and Python based package that implements RCFGL.     

Systemic mastocytosis associated with t(8;21)(q22;q22) acute myeloid leukemia

Although KIT mutations are present in 20–25% of cases of t(8;21)(q22;q22) acute myeloid leukemia (AML), concurrent development of systemic mastocytosis (SM) is exceedingly rare. We examined the clinicopathologic features of SM associated with t(8;21)(q22;q22) AML in ten patients (six from our institutions and four from published literature) with t(8;21) AML and SM. In the majority of these cases, a definitive diagnosis of SM was made after chemotherapy, when the mast cell infiltrates were prominent. Deletion 9q was an additional cytogenetic abnormality in four cases. Four of the ten patients failed to achieve remission after standard chemotherapy and seven of the ten patients have died of AML. In the two patients who achieved durable remission after allogeneic hematopoietic stem cell transplant, recipient-derived neoplastic bone marrow mast cells persisted despite leukemic remission. SM associated with t(8;21) AML carries a dismal prognosis; therefore, detection of concurrent SM at diagnosis of t(8;21) AML has important prognostic implications.     

Proteomic Profiling Identifies Distinct Protein Patterns in Acute Myelogenous Leukemia CD34+CD38- Stem-Like Cells

Acute myeloid leukemia (AML) is believed to arise from leukemic stem-like cells (LSC) making understanding the biological differences between LSC and normal stem cells (HSC) or common myeloid progenitors (CMP) crucial to understanding AML biology. To determine if protein expression patterns were different in LSC compared to other AML and CD34+ populations, we measured the expression of 121 proteins by Reverse Phase Protein Arrays (RPPA) in 5 purified fractions from AML marrow and blood samples: Bulk (CD3/CD19 depleted), CD34-, CD34+(CMP), CD34+CD38+ and CD34+CD38-(LSC). LSC protein expression differed markedly from Bulk (n=31 cases, 93/121 proteins) and CD34+ cells (n= 30 cases, 88/121 proteins) with 54 proteins being significantly different (31 higher, 23 lower) in LSC than in either Bulk or CD34+ cells. Sixty-seven proteins differed significantly between CD34+ and Bulk blasts (n=69 cases). Protein expression patterns in LSC and CD34+ differed markedly from normal CD34+ cells. LSC were distinct from CD34+ and Bulk cells by principal component and by protein signaling network analysis which confirmed individual protein analysis. Potential targetable submodules in LSC included the proteins PU.1(SP1), P27, Mcl1, HIF1α, cMET, P53, Yap, and phospho-Stats 1, 5 and 6. Protein expression and activation in LSC differs markedly from other blast populations suggesting that studies of AML biology should be performed in LSC.     

Genetic variation and the mitogen-activated protein kinase (MAPK) signaling pathway

Non-synonymous single nucleotide polymorphisms (nsSNPs) are known to alter protein function, contributing to disease susceptibility. This report explores the nature of nsSNPs in the gene products of the highly conserved mitogen-activated protein kinase (MAPK) signaling pathways already implicated in cancer development. MAPK signaling pathways regulate cellular processes such as proliferation, differentiation, apoptosis, and survival mediated through interconnected signaling cascades. Using the dbSNP database, we have identified 25 nsSNPs in 17 out of 98 MAPK genes studied. Computational algorithms were used to predict whether the amino acid substitutions were evolutionarily tolerated, or affected putative functional units such as phosphorylation sites, protein motifs and domains. This study predicts that 36% of nsSNPs are likely to have functional consequences, based on evolutionary conservation analysis, and 36% based on phosphorylation prediction analysis. All such nsSNPs represent potentially functional and disease-causing/modifying alleles. More interestingly, the epistatic relationships discussed in this report represent potential synergistic/ antagonistic/additive effects of nsSNP combinations found within the same protein, or within members of the same protein complex and cascades. This strategy can effectively determine which nsSNPs potentially alter protein function, and can be utilized to study the genetic architecture and disease association of other biological protein complexes and networks.     

Can systems biology approach help in finding more effective treatment for acute myeloid leukemia?

Acute myeloid leukemia (AML) is a hematological cancer comprising of cancer stem cells (CSCs) that are responsible for the disease progression, drug resistance and post treatment relapses. Advances in genomic technologies have identified AML as a genetically heterogenous disease with dysregulated gene expression networks. Furthermore, observation of intracellular signaling in individual CSCs by mass cytometry has demonstrated the dysregulation of the mitogen associated protein kinase (MAPK) pathways. It has been envisaged that the future treatment for AML would entail upon formulating individualized treatment plans leading to decreased drug related toxicities for patients. However the emerging role of signaling pathways as dynamic molecular switches influencing the cell cycle process, thereby leading to varying stages of cell differentiation, is making community rethink about the current strategies used for the treatment of AML. This commentary will focus on discovering novel biomarkers and identifying new therapeutic targets, to analyze and treat AML, on a platform enabled by systems biology approach.