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Gene expression profiling in T-cell acute lymphoblastic leukemia.

Adolfo A Ferrando1, A Thomas Look

  • 1Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA.

Seminars in Hematology
|October 29, 2003
PubMed
Summary

Gene expression profiling reveals distinct molecular subtypes of T-cell acute lymphoblastic leukemia (T-ALL). Identifying HOX11-positive T-ALL indicates a good prognosis, aiding in risk-stratified therapy for better patient outcomes.

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Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • T-cell acute lymphoblastic leukemia (T-ALL) poses significant treatment challenges due to unpredictable prognosis based on clinical features.
  • Microarray gene expression analysis has uncovered biological heterogeneity and clinically relevant molecular subtypes within T-ALL.
  • Five distinct molecular pathways involving oncogene activation (HOX11, HOX11L2, TAL1, LMO1/2, LYL1, LMO2, MLL-ENL) have been identified in T-ALL.

Purpose of the Study:

  • To elucidate the molecular heterogeneity of T-cell acute lymphoblastic leukemia (T-ALL) through gene expression profiling.
  • To identify molecular subtypes that correlate with prognosis and inform risk-specific therapeutic strategies.
  • To explore the potential for targeted therapies based on identified molecular pathways in T-ALL.

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Main Methods:

  • Microarray gene expression analysis of T-cell leukemic lymphoblasts.
  • Identification of molecular pathways involving oncogene activation.
  • Application of supervised learning approaches to microarray data for high-risk case identification.

Main Results:

  • Gene expression studies revealed oncogene activation (HOX11, TAL1, LYL1, LMO1, LMO2) in a significant fraction of T-ALL cases.
  • Overexpression of the HOX11 gene, observed in 5-10% of childhood and 30% of adult T-ALL, is associated with an excellent prognosis.
  • TAL1- and LYL1-positive T-ALL cases are largely associated with high risk of early treatment failure.
  • Supervised learning identified gene expression signatures capable of distinguishing high-risk T-ALL cases.

Conclusions:

  • Molecular subtyping of T-ALL via gene expression profiling is crucial for accurate prognosis and treatment stratification.
  • HOX11-positive T-ALL patients demonstrate favorable outcomes with current chemotherapy regimens.
  • Further analysis of gene expression signatures is needed to identify high-risk T-ALL patients for intensified therapies, such as myeloablative regimens with stem cell rescue.
  • Understanding T-ALL molecular pathways holds promise for developing novel, targeted therapeutic strategies.