About: Gene Expression-Based Classification As an Independent Predictor of Clinical Outcome in Juvenile Myelomonocytic Leukemia     Goto   Sponge   NotDistinct   Permalink

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Description
  • Purpose Juvenile myelomonocytic leukemia (JMML) is a rare early childhood myelodysplastic/myeloproliferative disorder characterized by an aggressive clinical course. Age and hemoglobin F percentage at diagnosis have been reported to predict both survival and outcome after hematopoietic stem cell transplantation (HSCT). However, no genetic markers with prognostic relevance have been identified so far. We applied gene expression based classification to JMML samples in order to identify prognostic categories related to clinical outcome. Patients and Methods Samples of 44 patients with JMML were available for microarray gene expression analysis. A diagnostic classification (DC) model developed for leukemia and myelodysplastic syndrome classification was used to classify the specimens and identify prognostically relevant categories. Statistical analysis was performed to determine the prognostic value of the classification and the genes identifying prognostic categories were further analyzed through R software. Results The samples could be divided into two major groups: 20 specimens were classified as acute myeloid leukemia (AML) -like and 20 samples as nonAML-like. Four patients could not be assigned to a unique class. The 10-year probability of survival after diagnosis of AML-like and nonAML-like patients was significantly different (7% v 74%; P=.0005). Similarly, the 10-year event-free survival after HSCT was 6% for AML-like and 63% for nonAML-like patients (P=.0010). Conclusion Gene expression based classification identifies two groups of patients with JMML with distinct prognosis outperforming all known clinical parameters in terms of prognostic relevance. Gene expression based classification could thus be prospectively used to guide clinical/therapeutic decisions.
  • Purpose Juvenile myelomonocytic leukemia (JMML) is a rare early childhood myelodysplastic/myeloproliferative disorder characterized by an aggressive clinical course. Age and hemoglobin F percentage at diagnosis have been reported to predict both survival and outcome after hematopoietic stem cell transplantation (HSCT). However, no genetic markers with prognostic relevance have been identified so far. We applied gene expression based classification to JMML samples in order to identify prognostic categories related to clinical outcome. Patients and Methods Samples of 44 patients with JMML were available for microarray gene expression analysis. A diagnostic classification (DC) model developed for leukemia and myelodysplastic syndrome classification was used to classify the specimens and identify prognostically relevant categories. Statistical analysis was performed to determine the prognostic value of the classification and the genes identifying prognostic categories were further analyzed through R software. Results The samples could be divided into two major groups: 20 specimens were classified as acute myeloid leukemia (AML) -like and 20 samples as nonAML-like. Four patients could not be assigned to a unique class. The 10-year probability of survival after diagnosis of AML-like and nonAML-like patients was significantly different (7% v 74%; P=.0005). Similarly, the 10-year event-free survival after HSCT was 6% for AML-like and 63% for nonAML-like patients (P=.0010). Conclusion Gene expression based classification identifies two groups of patients with JMML with distinct prognosis outperforming all known clinical parameters in terms of prognostic relevance. Gene expression based classification could thus be prospectively used to guide clinical/therapeutic decisions. (en)
Title
  • Gene Expression-Based Classification As an Independent Predictor of Clinical Outcome in Juvenile Myelomonocytic Leukemia
  • Gene Expression-Based Classification As an Independent Predictor of Clinical Outcome in Juvenile Myelomonocytic Leukemia (en)
skos:prefLabel
  • Gene Expression-Based Classification As an Independent Predictor of Clinical Outcome in Juvenile Myelomonocytic Leukemia
  • Gene Expression-Based Classification As an Independent Predictor of Clinical Outcome in Juvenile Myelomonocytic Leukemia (en)
skos:notation
  • RIV/00064203:_____/10:10209998!RIV14-MZ0-00064203
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • I
http://linked.open...iv/cisloPeriodika
  • 11
http://linked.open...vai/riv/dodaniDat
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http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 260309
http://linked.open...ai/riv/idVysledku
  • RIV/00064203:_____/10:10209998
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • jmml; survival; children; progenitors; discovery; ras mutations; myeloid-leukemia; molecular classification; stem-cell transplantation; pediatric myelodysplastic syndromes (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • US - Spojené státy americké
http://linked.open...ontrolniKodProRIV
  • [22A71F9FF0D3]
http://linked.open...i/riv/nazevZdroje
  • Journal of Clinical Oncology
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 28
http://linked.open...iv/tvurceVysledku
  • Starý, Jan
  • Locatelli, Franco
  • Hasle, Henrik
  • Basso, Giuseppe
  • Bresolin, Silvia
  • Flotho, Christian
  • Kronnie, Geertruy Te
  • Niemeyer, Charlotte M.
  • Sainati, Laura
  • Trentin, Luca
  • Zangrando, Andrea
  • Zecca, Marco
  • de Moerloose, Barbara
http://linked.open...ain/vavai/riv/wos
  • 000276457800017
issn
  • 0732-183X
number of pages
http://bibframe.org/vocab/doi
  • 10.1200/JCO.2009.24.4426
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