TY - JOUR
T1 - Gene expression profiling of adult acute myeloid leukemia identifies novel biologic clusters for risk classification and outcome prediction
AU - Wilson, Carla S.
AU - Davidson, George S.
AU - Martin, Shawn B.
AU - Andries, Erik
AU - Potter, Jeffrey
AU - Harvey, Richard
AU - Ar, Kerem
AU - Xu, Yuexian
AU - Kopecky, Kenneth J.
AU - Ankerst, Donna P.
AU - Gundacker, Holly
AU - Slovak, Marilyn L.
AU - Mosquera-Caro, Monica
AU - Chen, I. Ming
AU - Stirewalt, Derek L.
AU - Murphy, Maurice
AU - Schultz, Frederick A.
AU - Kang, Huining
AU - Wang, Xuefei
AU - Radich, Jerald P.
AU - Appelbaum, Frederick R.
AU - Atlas, Susan R.
AU - Godwin, John
AU - Willman, Cheryl L.
PY - 2006/7/15
Y1 - 2006/7/15
N2 - To determine whether gene expression profiling could improve risk classification and outcome prediction in older acute myeloid leukemia (AML) patients, expression profiles were obtained in pretreatment leukemic samples from 170 patients whose median age was 65 years. Unsupervised clustering methods were used to classify patients into 6 cluster groups (designated A to F) that varied significantly in rates of resistant disease (RD; P < .001), complete response (CR; P = .023), and disease-free survival (DFS; P = .023). Cluster A (n = 24), dominated by NPM1 mutations (78%), normal karyotypes (75%), and genes associated with signaling and apoptosis, had the best DFS (27%) and overall survival (OS; 25% at 5 years). Patients in clusters B (n = 22) and C (n = 31) had the worst OS (5% and 6%, respectively); cluster B was distinguished by the highest rate of RD (77%) and multidrug resistant gene expression (ABCG2, MDR1). Cluster D was characterized by a "proliferative" gene signature with the highest proportion of detectable cytogenetic abnormalities (76%; including 83% of all favorable and 34% of unfavorable karyotypes). Cluster F (n = 33) was dominated by monocytic leukemias (97% of cases), also showing increased NPM1 mutations (61%). These gene expression signatures provide insights into novel groups of AML not predicted by traditional studies that impact prognosis and potential therapy.
AB - To determine whether gene expression profiling could improve risk classification and outcome prediction in older acute myeloid leukemia (AML) patients, expression profiles were obtained in pretreatment leukemic samples from 170 patients whose median age was 65 years. Unsupervised clustering methods were used to classify patients into 6 cluster groups (designated A to F) that varied significantly in rates of resistant disease (RD; P < .001), complete response (CR; P = .023), and disease-free survival (DFS; P = .023). Cluster A (n = 24), dominated by NPM1 mutations (78%), normal karyotypes (75%), and genes associated with signaling and apoptosis, had the best DFS (27%) and overall survival (OS; 25% at 5 years). Patients in clusters B (n = 22) and C (n = 31) had the worst OS (5% and 6%, respectively); cluster B was distinguished by the highest rate of RD (77%) and multidrug resistant gene expression (ABCG2, MDR1). Cluster D was characterized by a "proliferative" gene signature with the highest proportion of detectable cytogenetic abnormalities (76%; including 83% of all favorable and 34% of unfavorable karyotypes). Cluster F (n = 33) was dominated by monocytic leukemias (97% of cases), also showing increased NPM1 mutations (61%). These gene expression signatures provide insights into novel groups of AML not predicted by traditional studies that impact prognosis and potential therapy.
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U2 - 10.1182/blood-2004-12-4633
DO - 10.1182/blood-2004-12-4633
M3 - Article
C2 - 16597596
AN - SCOPUS:33745957993
SN - 0006-4971
VL - 108
SP - 685
EP - 696
JO - Blood
JF - Blood
IS - 2
ER -