Gene expression data from bone marrow CD34+ cells of patients with myelodysplastic syndromes (MDS) and healthy controls

We aimed to determine the impact of the common mutations on the transcriptome in myelodysplastic syndromes (MDS). We linked genomic data with gene expression microarray data and we deconvoluted the expression of genes into contributions stemming from each genetic and cytogenetic alteration, providing insights into how driver mutations interfere with the transcriptomic state. We modelled the influence of mutations and expression changes on diagnostic clinical variables as well as survival. 159 patients with MDS patients and 17 healthy controls were included in the study. CD34+ cells were isolated from bone marrow samples obtained from MDS patients and healthy controls. Samples were hybridized to Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays本研究旨在探究常见突变对骨髓增生异常综合征（myelodysplastic syndromes，MDS）转录组的影响。本研究将基因组数据与基因表达微阵列数据进行关联，并通过解卷积分析将基因表达量拆解为各类遗传与细胞遗传学改变的贡献权重，从而揭示驱动突变如何干扰转录组状态。此外，本研究还构建了突变与表达改变对诊断相关临床变量及患者生存期的影响模型。本研究共纳入159例MDS患者及17名健康对照个体，从所有受试者的骨髓样本中分离出CD34阳性细胞（CD34+），并将样本在Affymetrix GeneChip Human Genome U133 Plus 2.0基因芯片上完成杂交反应。

搜集汇总

背景与挑战

背景概述

该数据集包含骨髓CD34+细胞的基因表达数据，来自159名骨髓增生异常综合征（MDS）患者和17名健康对照，使用Affymetrix GeneChip Human Genome U133 Plus 2.0阵列进行表达谱分析。研究旨在探究常见突变对MDS转录组的影响，通过整合基因组和表达数据，分析遗传改变对基因表达的贡献，并建模其对临床变量和生存的影响。