Gene expression profiling of adult acute myeloid leukemia identifies novel biologic clusters for risk classification and outcome prediction

Carla S. Wilson, George S. Davidson, Shawn B. Martin, Erik Andries, Jeffrey Potter, Richard Harvey, Kerem Ar, Yuexian Xu, Kenneth J. Kopecky, Donna P Ankerst, Holly Gundacker, Marilyn L. Slovak, Monica Mosquera-Caro, I. Ming Chen, Derek L. Stirewalt, Maurice Murphy, Frederick A. Schultz, Huining Kang, Xuefei Wang, Jerald P. RadichFrederick R. Appelbaum, Susan R. Atlas, John Godwin, Cheryl L. Willman

Research output: Contribution to journalArticle

135 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)685-696
Number of pages12
JournalBlood
Volume108
Issue number2
DOIs
StatePublished - Jul 15 2006
Externally publishedYes

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Gene Expression Profiling
Acute Myeloid Leukemia
Gene expression
Genes
Karyotype
Mutation
Transcriptome
Chromosome Aberrations
Apoptosis
Disease-Free Survival
Cluster Analysis
Leukemia
Gene Expression
Survival
Therapeutics

ASJC Scopus subject areas

  • Hematology

Cite this

Wilson, C. S., Davidson, G. S., Martin, S. B., Andries, E., Potter, J., Harvey, R., ... Willman, C. L. (2006). Gene expression profiling of adult acute myeloid leukemia identifies novel biologic clusters for risk classification and outcome prediction. Blood, 108(2), 685-696. https://doi.org/10.1182/blood-2004-12-4633

Gene expression profiling of adult acute myeloid leukemia identifies novel biologic clusters for risk classification and outcome prediction. / Wilson, Carla S.; Davidson, George S.; Martin, Shawn B.; Andries, Erik; Potter, Jeffrey; Harvey, Richard; Ar, Kerem; Xu, Yuexian; Kopecky, Kenneth J.; Ankerst, Donna P; Gundacker, Holly; Slovak, Marilyn L.; Mosquera-Caro, Monica; Chen, I. Ming; Stirewalt, Derek L.; Murphy, Maurice; Schultz, Frederick A.; Kang, Huining; Wang, Xuefei; Radich, Jerald P.; Appelbaum, Frederick R.; Atlas, Susan R.; Godwin, John; Willman, Cheryl L.

In: Blood, Vol. 108, No. 2, 15.07.2006, p. 685-696.

Research output: Contribution to journalArticle

Wilson, CS, Davidson, GS, Martin, SB, Andries, E, Potter, J, Harvey, R, Ar, K, Xu, Y, Kopecky, KJ, Ankerst, DP, Gundacker, H, Slovak, ML, Mosquera-Caro, M, Chen, IM, Stirewalt, DL, Murphy, M, Schultz, FA, Kang, H, Wang, X, Radich, JP, Appelbaum, FR, Atlas, SR, Godwin, J & Willman, CL 2006, 'Gene expression profiling of adult acute myeloid leukemia identifies novel biologic clusters for risk classification and outcome prediction', Blood, vol. 108, no. 2, pp. 685-696. https://doi.org/10.1182/blood-2004-12-4633
Wilson, Carla S. ; Davidson, George S. ; Martin, Shawn B. ; Andries, Erik ; Potter, Jeffrey ; Harvey, Richard ; Ar, Kerem ; Xu, Yuexian ; Kopecky, Kenneth J. ; Ankerst, Donna P ; Gundacker, Holly ; Slovak, Marilyn L. ; Mosquera-Caro, Monica ; Chen, I. Ming ; Stirewalt, Derek L. ; Murphy, Maurice ; Schultz, Frederick A. ; Kang, Huining ; Wang, Xuefei ; Radich, Jerald P. ; Appelbaum, Frederick R. ; Atlas, Susan R. ; Godwin, John ; Willman, Cheryl L. / Gene expression profiling of adult acute myeloid leukemia identifies novel biologic clusters for risk classification and outcome prediction. In: Blood. 2006 ; Vol. 108, No. 2. pp. 685-696.
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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.

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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.

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