title: Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients.
abstract: Gene expression profiling has been used extensively to characterize cancer, identify novel subtypes, and improve patient stratification. However, it has largely failed to identify transcriptional programs that differ between cancer and corresponding normal cells and has not been efficient in identifying expression changes fundamental to disease etiology. Here we present a method that facilitates the comparison of any cancer sample to its nearest normal cellular counterpart, using acute myeloid leukemia (AML) as a model. We first generated a gene expression-based landscape of the normal hematopoietic hierarchy, using expression profiles from normal stem/progenitor cells, and next mapped the AML patient samples to this landscape. This allowed us to identify the closest normal counterpart of individual AML samples and determine gene expression changes between cancer and normal. We find the cancer vs normal method (CvN method) to be superior to conventional methods in stratifying AML patients with aberrant karyotype and in identifying common aberrant transcriptional programs with potential importance for AML etiology. Moreover, the CvN method uncovered a novel poor-outcome subtype of normal-karyotype AML, which allowed for the generation of a highly prognostic survival signature. Collectively, our CvN method holds great potential as a tool for the analysis of gene expression profiles of cancer patients.
authors.affiliation: The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Rapin
authors.forename: Frederik Otzen
authors.initials: FO
authors.lastname: Bagger
authors.forename: Johan
authors.initials: J
authors.lastname: Jendholm
authors.forename: Helena
authors.initials: H
authors.lastname: Mora-Jensen
authors.forename: Anders
authors.initials: A
authors.lastname: Krogh
authors.forename: Alexander
authors.initials: A
authors.lastname: Kohlmann
authors.forename: Christian
authors.initials: C
authors.lastname: Thiede
authors.forename: Niels
authors.initials: N
authors.lastname: Borregaard
authors.forename: Lars
authors.initials: L
authors.lastname: Bullinger
authors.forename: Ole
authors.initials: O
authors.lastname: Winther
authors.forename: Kim
authors.initials: K
authors.lastname: Theilgaard-Mönch
authors.forename: Bo T
authors.initials: BT
authors.lastname: Porse
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics*; D015153:Blotting, Western; D016022:Case-Control Studies; D005500:Follow-Up Studies; D020869:Gene Expression Profiling; D006412:Hematopoietic Stem Cells / Q000378:metabolism*; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000235:genetics* / Q000473:pathology; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D012333:RNA, Messenger / Q000235:genetics; D060888:Real-Time Polymerase Chain Reaction; D020133:Reverse Transcriptase Polymerase Chain Reaction; D015996:Survival Rate
chemical_list: D014408:Biomarkers, Tumor; D012333:RNA, Messenger