0000000000087662

AUTHOR

Nancy Mah

0000-0002-1240-8076

showing 4 related works from this author

Evaluating Cell Identity from Transcription Profiles

2018

SummaryInduced pluripotent stem cells (iPS) and direct lineage programming offer promising autologous and patient-specific sources of cells for personalized drug-testing and cell-based therapy. Before these engineered cells can be widely used, it is important to evaluate how well the engineered cell types resemble their intended target cell types. We have developed a method to generate CellScore, a cell identity score that can be used to evaluate the success of an engineered cell type in relation to both its initial and desired target cell type, which are used as references. Of 20 cell transitions tested, the most successful transitions were the iPS cells (CellScore > 0.9), while other t…

0303 health sciences03 medical and health sciencesCell typemedicine.anatomical_structureTranscription (biology)030302 biochemistry & molecular biologyCellmedicineBiologyInduced pluripotent stem cellCell identity030304 developmental biologyCell biology
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Myeloid leukemia with transdifferentiation plasticity developing from T-cell progenitors

2016

Unfavorable patient survival coincides with lineage plasticity observed in human acute leukemias. These cases are assumed to arise from hematopoietic stem cells, which have stable multipotent differentiation potential. However, here we report that plasticity in leukemia can result from instable lineage identity states inherited from differentiating progenitor cells. Using mice with enhanced c-Myc expression, we show, at the single-cell level, that T-lymphoid progenitors retain broad malignant lineage potential with a high capacity to differentiate into myeloid leukemia. These T-cell-derived myeloid blasts retain expression of a defined set of T-cell transcription factors, creating a lymphoi…

0301 basic medicineMyeloidBone Marrow CellsBiologyGeneral Biochemistry Genetics and Molecular Biology03 medical and health scienceshemic and lymphatic diseasesmedicineCell LineageProgenitor cellMolecular BiologyGeneral Immunology and MicrobiologyGeneral NeuroscienceTransdifferentiationMyeloid leukemiaCell DifferentiationArticlesmedicine.diseaseHematopoietic Stem CellsHaematopoiesisLeukemia030104 developmental biologymedicine.anatomical_structureImmunologyCancer researchLymphoid Progenitor CellsStem cell
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RNA Sequencing of Human Peripheral Blood Cells Indicates Upregulation of Immune-Related Genes in Huntington's Disease

2020

Huntington's disease (HD) is an autosomal dominantly inherited neurodegenerative disorder caused by a trinucleotide repeat expansion in the Huntingtin gene. As disease-modifying therapies for HD are being developed, peripheral blood cells may be used to indicate disease progression and to monitor treatment response. In order to investigate whether gene expression changes can be found in the blood of individuals with HD that distinguish them from healthy controls, we performed transcriptome analysis by next-generation sequencing (RNA-seq). We detected a gene expression signature consistent with dysregulation of immune-related functions and inflammatory response in peripheral blood from HD ca…

inflammationHuntington's diseaseRNA-Seqdifferential gene expressiondisease markerslcsh:Neurology. Diseases of the nervous systemlcsh:RC346-429Frontiers in Neurology
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Detection of condition-specific marker genes from RNA-seq data with MGFR

2019

The identification of condition-specific genes is key to advancing our understanding of cell fate decisions and disease development. Differential gene expression analysis (DGEA) has been the standard tool for this task. However, the amount of samples that modern transcriptomic technologies allow us to study, makes DGEA a daunting task. On the other hand, experiments with low numbers of replicates lack the statistical power to detect differentially expressed genes. We have previously developed MGFM, a tool for marker gene detection from microarrays, that is particularly useful in the latter case. Here, we have adapted the algorithm behind MGFM to detect markers in RNA-seq data. MGFR groups s…

Bioinformaticslcsh:MedicineRNA-SeqComputational biologyMarker genesCell fate determinationBiologyMarker geneGeneral Biochemistry Genetics and Molecular BiologyTranscriptomeBioconductor03 medical and health sciences0302 clinical medicineGene expressionSingle cellRNA-SeqTranscriptomicsGene030304 developmental biology0303 health sciencesGeneral Neurosciencelcsh:RCell-type specificityGenomicsGeneral MedicineTissue specificity030220 oncology & carcinogenesisGene expressionR-packageDNA microarrayGeneral Agricultural and Biological SciencesPeerJ
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