Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients

Abstract

Key Points This study describes a method for the comparison of gene expression data of any type of cancer cells with their corresponding normal cells. Our analyses reveal novel disease entities, identify common deregulated transcriptional networks, and predict survival.

Changes in Gene Expression during G-CSF–Induced Emergency Granulopoiesis in Humans

“…Microarray analysis of mRNA transcripts was performed using the same protocols as described for the publicly available microarray data sets provided by Rapin et al (29). RNA from 5,000-200,000 cells was amplified to doublestranded cDNA (wild-type ovation Pico kit; NuGEN, San Carlo, CA), labeled (Encore Biotin Module V2; NuGEN), and hybridized on HG-U133 Plus 2.0 Arrays (Affymetrix, Santa Clara, CA).…”

“…The dataset has been deposited at ArrayExpress accession E-MTAB-4668. We have integrated data from the steady-state granulopoiesis study (29) available at Gene Expression Omnibus database (accession number GSE42519) with our data to examine the effects of G-CSF treatment. The combined data set was subjected to batch effect removal by applying the ComBat function for batch removal, as implemented in the R package surrogate variable analysis in R (64-bit version 3.1.0, 2014-04-10).…”

“…To identify the effects induced by G-CSF on gene expression, we compared cells from normal BM at different stages of maturation, as defined by their expression of differentiation markers (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42519) (29), with cells at the same stage of differentiation obtained from peripheral blood of G-CSF-treated donors (Supplemental Table I). BM from three healthy individuals from the above-mentioned dataset and blood from three healthy G-CSF-treated donors were analyzed separately.…”

Phase I/II study of the hypoxia-activated prodrug PR104 in refractory/relapsed acute myeloid leukemia and acute lymphoblastic leukemia

“…Recent gene expression profiling data confirmed highly distinct hypoxic and proinflammatory gene signatures in AML cells compared to normal hematopoietic stem cells. 5 Hypoxia results in stabilization of the transcription factors hypoxia-inducible factor 1α (HIF-1α) and HIF-2α, which in turn induce a vast array of gene products controlling metabolism, angiogenesis, apoptosis, and cell cycle. 6 In tumors, increased levels of HIF-1α activity are often associated with increased aggressiveness and therapeutic resistance.…”

The Impact of Molecular Genetic in Acute Myeloid Leukemias

“…With this approach we gained knowledge about unique gene expression signatures associated with defined cytogenetics and molecular subgroups of AML [7,8]. The use of gene expression profiling (GEP) has also identified novel sub-types of disease, particularly in CN-AML [9,10] and has been helpful in identifying potential targets of therapy [11,12]. GEP is highly accurate in predicting cytogenetically favorable AML subtypes, such as core-binding factor (CBF-AML) and acute promyelocytic leukemias.…”