Gene expression profile related to prognosis of acute myeloid leukemia

Min Ha Park, Sun A. Cho, Kyung Hyun Yoo, Moon Hee Yang, Ji Young Ahn, Hyo Soo Lee, Kyoung Eun Lee, Yeung Chul Mun, Dae Ho Cho, Chu Myong Seong, Jong Hoon Park

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Acute myeloid leukemia (AML) is a heterogeneous group of diseases with respect to biology and clinical course. Through genome-wide scanning, we can have an improvement of the diagnosis and assay system of AML. Microarray was performed for the identification of acute myeloid leukemia prognosis. We divided patients into two groups (good prognosis group, GPG and poor prognosis group, PPG) based on differences in the individual reactions to treatment. Gene expression profiles were analyzed using microarray. Among genes up-regulated at least two-fold and down-regulated at least 0.5-fold in HL-60, we chose three up-regulated genes (PPP2CA, ME3, and CCDN2) and three down-regulated genes (GLO1, ANXA2, and BMI1) and confirmed the expression of these six genes by RT-PCR. We created a leukemia-specific subclass microarray, based on the gene expression profiles. Clinical samples from the bone marrow of four patients were hybridized on this microarray. Among the genes selected by the microarray technology, NB4, silenced TRIB3 and overexpressed XRN2 were not differentiated in spite of treatment with ATRA. This indicates that XRN2 and TRIB3 play an important role in cell differentiation. These data provided an expression profile for the diagnosis and prognosis of AML patients and identified candidate genes that might allow the prognosis of AML through the relative comparison of the expression level of genes between GPG and PPG.

Original languageEnglish
Pages (from-to)1395-1402
Number of pages8
JournalOncology Reports
Volume18
Issue number6
DOIs
StatePublished - Dec 2007

Keywords

  • Acute myeloid leukemia
  • Microarry
  • Prognosis

Fingerprint

Dive into the research topics of 'Gene expression profile related to prognosis of acute myeloid leukemia'. Together they form a unique fingerprint.

Cite this