Transcription profiling by array of blood and bone marrow samples obtained from patients suffering from acute myeloid leukemia (AML, subtype M1 and M2)
ABSTRACT: Acute myeloid leukemia (AML) is the most common and severe acute leukemia in adults. It is a heterogeneous disease where the subset of molecularly different types, presenting various morphological features and differentiation stage, can be distinguished. Genomic research of leukemias is conducted since 1999 and large cohort studies shown that particular genetic alterations correspond with specific gene expression signatures. However, not always they provide clinically relevant information. The most unknown group is cytogenetically normal acute myeloid leukemia (CN-AML, 40-49% of all AML cases). The aim of our experiment was to determine selected gene expression profiles in CN-AML, using small, boutique microarray. The array contained 933 oligonucleotide probes, mainly complementary to acute myeloid leukemia markers, genes involved in leukemic transformation and myeloid cell proliferation, differentiation and maturation. Our test dataset included 40 hybridizations: 24 corresponding with blood and bone marrow samples collected from 12 patients with AML M1 or M2 FAB subtype and 16 corresponding with healthy control samples. Total RNA was extracted from the mononuclear cell fractions, reversibly transcribed to cDNA and labeled with Alexa 647 dye. The common reference was RNA isolated from HL-60 cell culture, labeled with Alexa 555 dye.
International journal of molecular medicine 20130715 3
DNA microarrays, which are among the most popular genomic tools, are widely applied in biology and medicine. Boutique arrays, which are small, spotted, dedicated microarrays, constitute an inexpensive alternative to whole-genome screening methods. The data extracted from each microarray-based experiment must be transformed and processed prior to further analysis to eliminate any technical bias. The normalization of the data is the most crucial step of microarray data pre-processing and this proc ...[more]
Project description:Acute myeloid leukemia (AML) is the most common and severe acute leukemia diagnosed in adults. Although it is one of the most studied cancers, this is the first study of Polish population of AML patients. The data were collected with the use of home-made boutique array. The additional advantage is pre-selection of patients - our sample set includes only two AML FAB subtypes with the highest content of immature myeloid cells: M1 (11 samples) and M2 (22 samples). From the majority of patients two sources of material were used for mononuclear cell separation and RNA extraction: bone marrow and peripheral blood. 15 samples from healthy volunteers were used as a control.
Project description:LC-MS/MS was used to profile total phosphotyrosine phosphatase in acute myeloid leukemia (AML) in order to find potential biomarkers, drug targets, signatures for AML classification, and its relationship with total phosphotyrosine amount in the samples.
Project description:Acute myeloid leukemia (AML) is a heterogeneous disease in respect of molecular aberrations and prognosis. We used gene expression profiling of 562 patients treated in the German AMLCG 1999 trial to develop a gene signature that predicts survival in AML. Analysis of 562 samples (140 HGU-133plus2; 422 HGU-133A; 422 HGU-133B) from adult patients with acute myeloid leukemia (AML).
Project description:The paper describes a model of acute myeloid leukaemia.
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Optimal control of acute myeloid leukaemia
Jesse A. Sharp, Alexander P Browning, Tarunendu Mapder, Kevin Burrage, Matthew J Simpson
Journal of Theoretical Biology 470 (2019) 30–42
Acute myeloid leukaemia (AML) is a blood cancer affecting haematopoietic stem cells. AML is routinely treated with chemotherapy, and so it is of great interest to develop optimal chemotherapy treatment strategies. In this work, we incorporate an immune response into a stem cell model of AML, since we find that previous models lacking an immune response are inappropriate for deriving optimal control strategies. Using optimal control theory, we produce continuous controls and bang-bang controls, corre- sponding to a range of objectives and parameter choices. Through example calculations, we provide a practical approach to applying optimal control using Pontryagin’s Maximum Principle. In particular, we describe and explore factors that have a profound influence on numerical convergence. We find that the convergence behaviour is sensitive to the method of control updating, the nature of the control, and to the relative weighting of terms in the objective function. All codes we use to implement optimal control are made available.
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Project description:We evaluated different in-solution and filter-aided sample preparation (FASP) proteomic workflows, and different enrichment strategies of phosphorylated peptides on acute myeloid leukemia (AML) patient samples. We also studied the effect of liquid nitrogen storage on the proteome and phosphoproteome of four AML patients.