Preliminary study of gene expression profile associated with risk classification of childhood patients with acute lymphoblastic leukemia / 中华血液学杂志

ABSTRACT

<p><b>OBJECTIVE</b>To explore genes associated with risk classification of childhood acute lymphoblastic leukemia (ALL) by gene chip technology.</p><p><b>METHODS</b>Group A and B were both composed of three newly diagnosed ALL cases with standard risk. After re-evaluation, group B was relegated to high-risk. The control group was composed of three idiopathic thrombocytopenic purpura (ITP) patients. The gene expression profiles of group A and B were studied by Illumina Human-6 Beadchip. Eighty-two ALL patients were selected as the experimental group and 21 with normal bone marrow as control group for real-time quantitative RT-PCR (RQ-PCR).</p><p><b>RESULTS</b>(1) There were 19 genes expressed differently between group B and A, including 14 up-regulated as ABCC4 and BCL11A, 5 down-regulated genes as TOP2A. (2) ABCC4 and BCL11A were validated by RQ-PCR and their expression level was higher in the high risk group than in the standard risk group (P < 0.05). The gene expression level in the group A and B was higher than that in the normal control group (P < 0.01). TOP2A was also validated by RQ-PCR and its expression level in the high risk group was lower than that in the standard risk group (P < 0.05). The gene expression level in the groups A and B was lower than that in the normal control group and the difference was statistically significance (P < 0.01). (3) There was a significant difference in the expression level of ABCC4 between the remission and unremission patients (P < 0.05). There was no significant difference in the expression level of BCL11A between different clinical indicators (P > 0.05). There was significant difference in the expression level of TOP2A between remission and prednisone good responder groups (P < 0.05).</p><p><b>CONCLUSIONS</b>Fourteen genes studied were involved in the pathogenesis and drug resistance mechanism in childhood ALL patients. Investigation of gene expression profile will be helpful for predicting drug resistance, prognosis, early intervention and target therapy in childhood ALL.</p>