Gruber AML WGS - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001006442 | EGA |
REPOSITORIES: EGA
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Project description:WXS files for paper titled "Integrative Analysis of Pediatric Acute Leukemia Identifies Acute Myeloid/T-Lymphoblastic Leukemia Subtype that Spans a T Lineage and Myeloid Continuum with Distinct Prognoses"
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Project description:RNASeq files for paper titled "Integrative Analysis of Pediatric Acute Leukemia Identifies Acute Myeloid/T-Lymphoblastic Leukemia Subtype that Spans a T Lineage and Myeloid Continuum with Distinct Prognoses"
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Project description:This SuperSeries is composed of the following subset Series: GSE30745: Expression data from murine acute myeloid leukemia (AML) cells following shRNA-mediated suppression of Myb GSE30746: Expression data from murine Tet-off MLL-AF9/Ras acute myeloid leukemia cell lines following withdrawal of MLL-AF9 Refer to individual Series
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Project description:The paper describes a model of acute myeloid leukaemia.
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This model is described in the article:
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
Abstract:
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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2019-08-19 | BIOMD0000000798 | BioModels
Project description:Mixed phenotype acute leukemia (MPAL) also known as acute leukemia of ambiguous lineage (ALAL), is characterized by leukemic blasts with both lymphoid and myeloid cell surface markers. Here, we use SC multiomic profiling on newly diagnosed MPAL samples to characterize the immunophenotypic, genetic, and transcriptional landscapes of MPAL. This profiling allows us to definitively contradict the paradigm of MPAL as a disease on a continuum with myeloid and lymphoid lineage acute leukemias, and instead identifies MPAL as a distinct, stem-like disease that, unlike other leukemias, cannot be defined by genetics alone. We further describe a stem cell gene expression signature for MPAL that can predict patient survival. These results broaden our understanding of MPAL biology and suggest a path toward novel risk stratification for MPAL. Importantly, these findings have potential to direct treatment and, hopefully, ultimately improve the prognosis of this disease.
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Project description:Mixed phenotype acute leukemia (MPAL) also known as acute leukemia of ambiguous lineage (ALAL), is characterized by leukemic blasts with both lymphoid and myeloid cell surface markers. Here, we use SC multiomic profiling on newly diagnosed MPAL samples to characterize the immunophenotypic, genetic, and transcriptional landscapes of MPAL. This profiling allows us to definitively contradict the paradigm of MPAL as a disease on a continuum with myeloid and lymphoid lineage acute leukemias, and instead identifies MPAL as a distinct, stem-like disease that, unlike other leukemias, cannot be defined by genetics alone. We further describe a stem cell gene expression signature for MPAL that can predict patient survival. These results broaden our understanding of MPAL biology and suggest a path toward novel risk stratification for MPAL. Importantly, these findings have potential to direct treatment and, hopefully, ultimately improve the prognosis of this disease.
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Project description:Mixed phenotype acute leukemia (MPAL) also known as acute leukemia of ambiguous lineage (ALAL), is characterized by leukemic blasts with both lymphoid and myeloid cell surface markers. Here, we use SC multiomic profiling on newly diagnosed MPAL samples to characterize the immunophenotypic, genetic, and transcriptional landscapes of MPAL. This profiling allows us to definitively contradict the paradigm of MPAL as a disease on a continuum with myeloid and lymphoid lineage acute leukemias, and instead identifies MPAL as a distinct, stem-like disease that, unlike other leukemias, cannot be defined by genetics alone. We further describe a stem cell gene expression signature for MPAL that can predict patient survival. These results broaden our understanding of MPAL biology and suggest a path toward novel risk stratification for MPAL. Importantly, these findings have potential to direct treatment and, hopefully, ultimately improve the prognosis of this disease.
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