296 research outputs found
Identifying Cancer Specific Metabolic Signatures Using Constraint-Based Models
Cancer metabolism differs remarkably from the metabolism of healthy surrounding tissues, and it is extremely heterogeneous across cancer types. While these metabolic differences provide promising avenues for cancer treatments, much work remains to be done in understanding how metabolism is rewired in malignant tissues. To that end, constraint-based models provide a powerful computational tool for the study of metabolism at the genome scale. To generate meaningful predictions, however, these generalized human models must first be tailored for specific cell or tissue sub-types. Here we first present two improved algorithms for (1) the generation of these context-specific metabolic models based on omics data, and (2) Monte-Carlo sampling of the metabolic model ux space. By applying these methods to generate and analyze context-specific metabolic models of diverse solid cancer cell line data, and primary leukemia pediatric patient biopsies, we demonstrate how the methodology presented in this study can generate insights into the rewiring differences across solid tumors and blood cancers
Targeted therapy in acute myeloid leukemia:current status and new insights from a proteomic perspective
Introduction: The biological heterogeneity of acute myeloid leukemia (AML) complicates personalized medicine. Individual prognosis is typically based on the presence of chromosomal and genetic lesions. Nevertheless, these classifications often lack a priori information about response to therapy. Since the protein expression landscape reflects the functional activity state of cells, we hypothesize that analyzing this can be used for the identification of protein activity markers to provide better risk stratification as well as may provide targeted therapeutic guidance in AML. Areas covered: Herein, we review recently new adopted drugs in the treatment for AML and discuss how quantitative proteomic techniques may contribute to better therapeutic selection in AML. Expert commentary: The net functional state of the cell is defined by the activity of protein within all the pathways that are active in the cell. Recognition of the proteomic profile of the leukemic blast could, therefore, complement current classification systems by providing a better a priori description of what pathways are important within a cell as a guide to the selection of therapy for the patient
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Accurate detection of uniparental disomy and microdeletions by SNP array analysis in myelodysplastic syndromes with normal cytogenetics.
Progress in the management of patients with myelodysplastic syndromes (MDS) has been hampered by the inability to detect cytogenetic abnormalities in 40-60% of cases. We prospectively analyzed matched pairs of bone marrow and buccal cell (normal) DNA samples from 51 MDS patients by single nucleotide polymorphism (SNP) arrays, and identified somatically acquired clonal genomic abnormalities in 21 patients (41%). Among the 33 patients with normal bone marrow cell karyotypes, 5 (15%) had clonal, somatically acquired aberrations by SNP array analysis, including 4 with segmental uniparental disomies (UPD) and 1 with three separate microdeletions. Each abnormality was detected more readily in CD34+ cells than in unselected bone marrow cells. Paired analysis of bone marrow and buccal cell DNA from each patient was necessary to distinguish true clonal genomic abnormalities from inherited copy number variations and regions with apparent loss of heterozygosity. UPDs affecting chromosome 7q were identified in two patients who had a rapidly deteriorating clinical course despite a low-risk International Prognostic Scoring System score. Further studies of larger numbers of patients will be needed to determine whether 7q UPD detected by SNP array analysis will identify higher risk MDS patients at diagnosis, analogous to those with 7q cytogenetic abnormalities
Therapeutic targeting of the MEK/MAPK signal transduction module in acute myeloid leukemia
: The mitogen-activated protein kinase (MAPK) pathway regulates growth and survival of many cell types, and its constitutive activation has been implicated in the pathogenesis of a variety of malignancies. In this study we demonstrate that small-molecule MEK inhibitors (PD98059 and PD184352) profoundly impair cell growth and survival of acute myeloid leukemia (AML) cell lines and primary samples with constitutive MAPK activation. These agents abrogate the clonogenicity of leukemic cells but have minimal effects on normal hematopoietic progenitors. MEK blockade also results in sensitization to spontaneous and drug-induced apoptosis. At a molecular level, these effects correlate with modulation of the expression of cyclin-dependent kinase inhibitors (p27(Kip1) and p21(Waf1/CIP1)) and antiapoptotic proteins of the inhibitor of apoptosis proteins (IAP) and Bcl-2 families. Interruption of constitutive MEK/MAPK signaling therefore represents a promising therapeutic strategy in AML
DNA Damage Response-Related Proteins Are Prognostic for Outcome in Both Adult and Pediatric Acute Myelogenous Leukemia Patients: Samples from Adults and from Children Enrolled in a Children\u27s Oncology Group Study
The survival of malignant leukemic cells is dependent on DNA damage repair (DDR) signaling. Reverse Phase Protein Array (RPPA) data sets were assembled using diagnostic samples from 810 adult and 500 pediatric acute myelogenous leukemia (AML) patients and were probed with 412 and 296 strictly validated antibodies, respectively, including those detecting the expression of proteins directly involved in DDR. Unbiased hierarchical clustering identified strong recurrent DDR protein expression patterns in both adult and pediatric AML. Globally, DDR expression was associated with gene mutational statuses and was prognostic for outcomes including overall survival (OS), relapse rate, and remission duration (RD). In adult patients, seven DDR proteins were individually prognostic for either RD or OS. When DDR proteins were analyzed together with DDR-related proteins operating in diverse cellular signaling pathways, these expanded groupings were also highly prognostic for OS. Analysis of patients treated with either conventional chemotherapy or venetoclax combined with a hypomethylating agent revealed protein clusters that differentially predicted favorable from unfavorable prognoses within each therapy cohort. Collectively, this investigation provides insight into variable DDR pathway activation in AML and may help direct future individualized DDR-targeted therapies in AML patients
Epidermal growth factor receptor is expressed and active in a subset of acute myeloid leukemia
The epidermal growth factor receptor (EGFR) inhibitor erlotinib has been shown to induce complete remission of acute myeloid leukemia (AML) in two patients with concurrent lung cancer and raised attention for a role of EGFR in AML whereas a recent phase II clinical study with gefitinib in AML demonstrated a negative result on the outcome. However, from several studies, EGFR expression in AML is poorly defined and the role of EGFR in AML remains unclear. Herein, we report the results of EGFR expression in AML of large cohorts of adult and pediatric AML patients with the data of total protein and phosphorylation levels of EGFR. Our data conclude that there is the expression of EGFR at the protein level in a subset of AML, which was identified to be functionally active in similar to 15 % of AML patients. This suggests that future studies need to be conducted with a subset of AML patients characterized by high EGFR expression
Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia
BackgroundAcute leukemia is an epigenetically heterogeneous disease. The intensity of treatment is currently guided by cytogenetic and molecular genetic risk classifications; however these incompletely predict outcomes, requiring additional information for more accurate outcome predictions. We aimed to identify potential prognostic implications of epigenetic modification of histone proteins, with a focus on H3K4 and H3K27 methylation marks in relation to mutations in chromatin, splicing and transcriptional regulators in adult-onset acute lymphoblastic and myeloid leukemia.ResultsHistone 3 lysine 4 di- and trimethylation (H3K4me2, H3K4me3) and lysine 27 trimethylation (H3K27me3) mark expression was evaluated in 241 acute myeloid leukemia (AML), 114 B-cell acute lymphoblastic leukemia (B-ALL) and 14T-cell ALL (T-ALL) patient samples at time of diagnosis using reverse phase protein array. Expression levels of the marks were significantly lower in AML than in B and T-ALL in both bone marrow and peripheral blood, as well as compared to normal CD34+ cells. In AML, greater loss of H3K27me3 was associated with increased proliferative potential and shorter overall survival in the whole patient population, as well as in subsets with DNA methylation mutations. To study the prognostic impact of H3K27me3 in the context of cytogenetic aberrations and mutations, multivariate analysis was performed and identified lower H3K27me3 level as an independent unfavorable prognostic factor in all, as well as in TP53 mutated patients. AML with decreased H3K27me3 demonstrated an upregulated anti-apoptotic phenotype. In ALL, the relative quantity of histone methylation expression correlated with response to tyrosine kinase inhibitor in patients who carried the Philadelphia cytogenetic aberration and prior smoking behavior.ConclusionThis study shows that proteomic profiling of epigenetic modifications has clinical implications in acute leukemia and supports the idea that epigenetic patterns contribute to a more accurate picture of the leukemic state that complements cytogenetic and molecular genetic subgrouping. A combination of these variables may offer more accurate outcome prediction and we suggest that histone methylation mark measurement at time of diagnosis might be a suitable method to improve patient outcome prediction and subsequent treatment intensity stratification in selected subgroups
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Metabolic gatekeeper function of B-lymphoid transcription factors.
B-lymphoid transcription factors, such as PAX5 and IKZF1, are critical for early B-cell development, yet lesions of the genes encoding these transcription factors occur in over 80% of cases of pre-B-cell acute lymphoblastic leukaemia (ALL). The importance of these lesions in ALL has, until now, remained unclear. Here, by combining studies using chromatin immunoprecipitation with sequencing and RNA sequencing, we identify a novel B-lymphoid program for transcriptional repression of glucose and energy supply. Our metabolic analyses revealed that PAX5 and IKZF1 enforce a state of chronic energy deprivation, resulting in constitutive activation of the energy-stress sensor AMPK. Dominant-negative mutants of PAX5 and IKZF1, however, relieved this glucose and energy restriction. In a transgenic pre-B ALL mouse model, the heterozygous deletion of Pax5 increased glucose uptake and ATP levels by more than 25-fold. Reconstitution of PAX5 and IKZF1 in samples from patients with pre-B ALL restored a non-permissive state and induced energy crisis and cell death. A CRISPR/Cas9-based screen of PAX5 and IKZF1 transcriptional targets identified the products of NR3C1 (encoding the glucocorticoid receptor), TXNIP (encoding a glucose-feedback sensor) and CNR2 (encoding a cannabinoid receptor) as central effectors of B-lymphoid restriction of glucose and energy supply. Notably, transport-independent lipophilic methyl-conjugates of pyruvate and tricarboxylic acid cycle metabolites bypassed the gatekeeper function of PAX5 and IKZF1 and readily enabled leukaemic transformation. Conversely, pharmacological TXNIP and CNR2 agonists and a small-molecule AMPK inhibitor strongly synergized with glucocorticoids, identifying TXNIP, CNR2 and AMPK as potential therapeutic targets. Furthermore, our results provide a mechanistic explanation for the empirical finding that glucocorticoids are effective in the treatment of B-lymphoid but not myeloid malignancies. Thus, B-lymphoid transcription factors function as metabolic gatekeepers by limiting the amount of cellular ATP to levels that are insufficient for malignant transformation
IDENTIFYING CANCER SPECIFIC METABOLIC SIGNATURES USING CONSTRAINT-BASED MODELS
Cancer metabolism differs remarkably from the metabolism of healthy surrounding tissues, and it is extremely heterogeneous across cancer types. While these metabolic differences provide promising avenues for cancer treatments, much work remains to be done in understanding how metabolism is rewired in malignant tissues. To that end, constraint-based models provide a powerful computational tool for the study of metabolism at the genome scale. To generate meaningful predictions, however, these generalized human models must first be tailored for specific cell or tissue sub-types. Here we first present two improved algorithms for (1) the generation of these context-specific metabolic models based on omics data, and (2) Monte-Carlo sampling of the metabolic model flux space. By applying these methods to generate and analyze context-specific metabolic models of diverse solid cancer cell line data, and primary leukemia pediatric patient biopsies, we demonstrate how the methodology presented in this study can generate insights into the rewiring differences across solid tumors and blood cancers
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