6 research outputs found
Gene expression profi ling of acute myeloid leukemia
Hematopoïese, of de vorming van functionele bloedcellen, is een proces wat
plaats vindt in het beenmerg. Hematopoïetische stamcellen ondergaan cycli van
deling en differentiatie waarin de functionele eindcellen, zoals rode bloedcellen,
bloedplaatjes en witte bloedcellen, worden gevormd. Leukemie is een ziekte waarbij
de stamcellen abnormale processen van deling in combinatie met een stop van de
differentiatie ondergaan, waardoor er de vorming van functionele eindcellen wordt
belemmerd. In het geval van acute myeloïde leukemie (AML) is er een afwijking in
de tak van bloedcelvorming waar onder andere rode bloedcellen, bloedplaatjes en
granulocyten worden gevormd.
De ontsporing van hematopoïetische stamcellen met AML als gevolg wordt
veroorzaakt door abnormaliteiten in het genoom, zoals chromosomale fusies,
deleties en mutaties. De klinische prognose wordt momenteel bepaald aan de hand
van de aan- of afwezigheid van (combinaties van) abnormaliteiten.
Het belangrijkste gevolg van genomische afwijkingen is de abnormale transcriptie
van genen naar mRNA. Met behulpvan gen expressie profilering, door middel
van microarrays, kunnen de transcriptie niveaus van duizenden genen simultaan
worden bepaald. In hoofdstuk 2 is een onderzoek beschreven waarin met gen
expressie profilering is toegepast op 285 beenmerg monsters van de novo AML
patiënten, voor het bepalen van prognose. Verschillende bekende prognostische
groepen, zoals t(8;21) en inv(16) konden worden geidentificeerd, alsmede een
nieuwe prognostisch relevante groep van patiënten met een relatief slechte
prognose (cluster 10).Hoofdstuk 2 laat zien dat gen expressie profilering in staat
is om de huidige technieken voor het bepalen van prognose te vervangen, en
prognose te verbeteren.Roeland George Willehad Verhaak was born in Wijchen, the Netherlands, on
September 29 1976. After fi nishing his VWO education at the Kottenpark College
in Enschede in 1996, he started a curriculum Biomedical Health Sciences at the
Catholic University Nijmegen (KUN, currently Radboud University). As part of
this education, he followed majors in pathobiology and toxicology, and a minor in
computer science. A toxicology internship, titled ‘Mitochondrial toxicity of nuclease
reverse transcriptase inhibitors, was completed at the Department of Pharmacology
and Toxicology of the KUN under supervision of Dr. Roos Masereeuw. A second
intership project, ‘Development of a diagnostic marker of multiple sclerosis’, was
completed at the Department of Biochemistry, under supervision of Dr. Rinie van
Boekel en Prof.dr. W. Van Venrooij. He obtained his Masters–degree in August
2000. After having started a project at the Department of Medical Informatics of
the KUN in October 2000 in which he worked on structuring of temporal data,
he switched to the bioinformatics company Dalicon BV in April 2002. At Dalicon,
he worked as software engineer, with a particular focus at the database system
SRS. In April 2003 he started a PhD-project at the Department of Hematology at
the Erasmus MC in the lab of Prof.dr. Bob Löwenberg, supervised by Dr. Peter
Valk. This work has been described in this thesis. From March 2006 until June 2006,
he was a visiting scientist of the Department of Biostatistics and Computational
Biology of the Dana-Farber Cancer Institute in Boston, supervised by Prof.dr. John
Quackenbush. The author wil continue his academic career at the Broad Institute
in Boston, a research collaboration of MIT, Harvard and its affiliated hospitals, and
the Whitehead Institute
Prognostically useful gene-expression profiles in acute myeloid leukemia
BACKGROUND: In patients with acute myeloid leukemia (AML) a combination of
methods must be used to classify the disease, make therapeutic decisions,
and determine the prognosis. However, this combined approach provides
correct therapeutic and prognostic information in only 50 percent of
cases. METHODS: We determined the gene-expression profiles in samples of
peripheral blood or bone marrow from 285 patients with AML using
Affymetrix U133A GeneChips containing approximately 13,000 unique genes or
expression-signature tags. Data analyses were carried out with Omniviz,
significance analysis of microarrays, and prediction analysis of
microarrays software. Statistical analyses were performed to determine the
prognostic significance of cases of AML with specific molecular
signatures. RESULTS: Unsupervised cluster analyses identified 16 groups of
patients with AML on the basis of molecular signatures. We identified the
genes that defined these clusters and determined the minimal numbers of
genes needed to identify prognostically important clusters with a high
degree of accuracy. The clustering was driven by the presence of
chromosomal lesions (e.g., t(8;21), t(15;17), and inv(16)), particular
genetic mutations (CEBPA), and abnormal oncogene expression (EVI1). We
identified several novel clusters, some consisting of specimens with
normal karyotypes. A unique cluster with a distinctive gene-expression
signature included cases of AML with a poor treatment outcome.
CONCLUSIONS: Gene-expression profiling allows a comprehensive
classification of AML that includes previously identified genetically
defined subgroups and a novel cluster with an adverse prognosis
Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling
We examined the gene expression profiles of two independent cohorts of patients with acute myeloid leukemia [n=247 and n=214 (younger than or equal to 60 years)] to study the applicability of gene expression profiling as a single assay in prediction of acute myeloid leukemia-specific molecular subtypes. The favorable cytogenetic acute myeloid leukemia subtypes, i.e., acute myeloid leukemia with t(8;21), t(15;17) or inv(16), were predicted with maximum accuracy (positive and negative predictive value: 100%). Mutations in NPM1 and CEBPA were predicted less accurately (positive predictive value: 66% and 100%, and negative predictive value: 99% and 97% respectively). Various other characteristic molecular acute myeloid leukemia subtypes, i.e., mutant FLT3 and RAS, abnormalities involving 11q23, -5/5q-, -7/7q-, abnormalities involving 3q (abn3q) and t(9;22), could not be correctly predicted using gene expression profiling. In conclusion, gene expression profiling allows accurate prediction of certain acute myeloid leukemia subtypes, e.g. those characterized by expression of chimeric transcription factors. However, detection of mutations affecting signaling molecules and numerical abnormalities still requires alternative molecular methods
Mutations in nucleophosmin (NPM1) in acute myeloid leukemia (AML): Association with other gene abnormalities and previously established gene expression signatures and their favorable prognostic significance
Mutations in nucleophosmin NPM1 are the most frequent acquired molecular abnormalities in acute myeloid leukemia (AML). We determined the NPM1 mutation status in a clinically and molecularly well-characterized patient cohort of 275 patients with newly diagnosed AML by denaturing high-performance liquid chromatography (dHPLC). We show that NPM1 mutations are significantly underrepresented in patients younger than 35 years. NPM1 mutations positively correlate with AML with high white blood cell counts, normal karyotypes, and fms-like tyrosine kinase-3 gene (FLT3) internal tandem duplication (ITD) mutations. NPM1 mutations associate inversely with the occurrence of CCAAT/enhancer-binding protein-α (CEBPA) and NRAS mutations. With respect to gene expression profiling, we show that AML cases with an NPM1 mutation cluster in specific subtypes of AML with previously established gene expression signatures, are highly associated with a homeobox gene-specific expression signature, and can be predicted with high accuracy. We demonstrate that patients with intermediate cytogenetic risk AML without FLT3 ITD mutations but with NPM1 mutations have a significantly better overall survival (OS) and eventfree survival (EFS) than those without NPM1 mutations. Finally, in multivariable analysis NPM1 mutations express independent favorable prognostic value with regard to OS, EFS, and disease-free survival (DFS)
Sequential gain of mutations in severe congenital neutropenia progressing to acute myeloid leukemia
Severe congenital neutropenia (SCN) is a BM failure syndrome with a high risk of progression to acute myeloid leukemia (AML). The underlying genetic changes involved in SCN evolution to AML are largely unknown. We obtained serial hematopoietic samples from an SCN patient who developed AML 17 years after the initiation of G-CSF treatment. Next-generation sequencing was performed to identify mutations during disease progression. In the AML phase, we found 12 acquired nonsynonymous mutations. Three of these, in CSF3R, LLGL2, and ZC3H18, co-occurred in a subpopulation of progenitor cells already in the early SCN phase. This population expanded over time, whereas clones harboring only CSF3R mutations disappeared from the BM. The other 9 mutations were only apparent in the AML cells and affected known AML-associated genes (RUNX1 and ASXL1) and chromatin remodelers (SUZ12 and EP3