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Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling.

ABSTRACT: 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.

SUBMITTER: Verhaak RG

PROVIDER: S-EPMC2625407 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature

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Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling.

Verhaak Roel G W RG Wouters Bas J BJ Erpelinck Claudia A J CA Abbas Saman S Beverloo H Berna HB Lugthart Sanne S Löwenberg Bob B Delwel Ruud R Valk Peter J M PJ

Haematologica 20081006 1

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 v ...[more]

PMID: 18838472

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Project description:BACKGROUND:Pediatric acute myeloid leukemia is a heterogeneous disease characterized by non-random genetic aberrations related to outcome. The genetic subtype is currently detected by different diagnostic procedures which differ in success rate and/or specificity. DESIGN AND METHODS:We examined the potential of gene expression profiles to classify pediatric acute myeloid leukemia. Gene expression microarray data of 237 children with acute myeloid leukemia were collected and a double-loop cross validation approach was used to generate a subtype-predictive gene expression profile in the discovery cohort (n=157) which was then tested for its true predictive value in the independent validation cohort (n=80). The classifier consisted of 75 probe sets, representing the top 15 discriminating probe sets for MLL-rearranged, t(8;21)(q22;q22), inv(16)(p13q22), t(15;17)(q21;q22) and t(7;12)(q36;p13)-positive acute myeloid leukemia. RESULTS:These cytogenetic subtypes represent approximately 40% of cases of pediatric acute myeloid leukemia and were predicted with 92% and 99% accuracy in the discovery and independent validation cohort, respectively. However, for NPM1, CEBPA, MLL(-PTD), FLT3(-ITD), KIT, PTPN11 and N/K-RAS gene expression signatures had limited predictive value. This may be caused by a limited frequency of these mutations and by underlying cytogenetics. This latter is exemplified by the fact that different gene expression signatures were discovered for FLT3-ITD in patients with normal cytogenetics and in those with t(15;17)(q21;q22)-positive acute myeloid leukemia, which pointed to HOXB-upregulation being specific for FLT3-ITD(+) cytogenetically normal acute myeloid leukemia. CONCLUSIONS:In conclusion, gene expression profiling correctly predicted the most prevalent cytogenetic subtypes of pediatric acute myeloid leukemia with high accuracy. In clinical practice, this gene expression signature may replace multiple diagnostic tests for approximately 40% of pediatric acute myeloid leukemia cases whereas only for the remaining cases (predicted as 'acute myeloid leukemia-other') are additional tests indicated. Moreover, the discriminative genes reveal new insights into the biology of acute myeloid leukemia subtypes that warrants follow-up as potential targets for new therapies.

Project description:Acute myeloid leukemia (AML) is an infrequent disease, and it is associated with high morbidity and mortality. It harbors a unique configuration of cytogenetic abnormalities and molecular mutations that can be detected using microscopic and molecular methods respectively. These genetic tests are core elements of diagnosis and prognostication in high-income countries. They are routinely incorporated in clinical decision making, allowing for the individualization of therapy. However, these tests are largely inaccessible to most patients in Kenya and therefore no data has been reported on this group of patients. The main purpose of this study is to describe the cytogenetic and molecular abnormalities of acute myeloid leukemia patients seen at the hemato-oncology unit of Kenyatta National Hospital. A cross-sectional descriptive study was carried out over a 3-month period on ten patients with a diagnosis of AML. Social demographics and clinical data were collected through a study proforma. A peripheral blood sample was collected for conventional metaphase G-banding technique and next generation sequencing. Particularly, targeted DNA sequencing (Illumina myeloid panel) and whole exome sequencing (WES) were performed. Cytogenetic analysis failed in 10/10 cases. Targeted sequencing was successfully obtained in 8 cases, whereas WES in 7. Cytogenetic studies yielded no results. There were 20 mutations detected across 10 commonly mutated genes. All patients had at least one clinically relevant mutation. Based on ELN criteria, NGS identified three patients with high-risk mutations, affecting TP53 (n = 2) and RUNX1 (n = 1). One patient was classified as favorable (PML-RARA) while 4 were standard risk. However, WT1 mutations associated with unfavorable prognosis were recorded in additional 2 cases. WES showed concordant results with targeted sequencing while unveiling more mutations that warrant further attention. In conclusion, we provide the first molecular profiling study of AML patients in Kenya including application of advanced next generation sequencing technologies, highlighting current limitations of AML diagnostics and treatment while confirming the relevance of NGS in AML characterization.

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Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling.

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Prediction of molecular subtypes in acute myeloid leukemia based on gene expression profiling.

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