The alkylating agent Busulfan (Bu) is commonly used in the pre-transplant conditioning regimen for patients with acute myeloid leukemia (AML). Relapse after transplant is in part due to resistance to Bu. Our study was aimed at identifying a genomic signature that could predict resistance to Bu in AML cells.

In order to obtain a list of candidate genes which may correlate with increasing resistance to Bu we performed a linear regression analysis controlled for cancer type on NCI60 Stanford cDNA data and GI50 values. This produced a list of 111 genes correlating with increasing Busulfan GI50 (p<0.01, FDR<50%). The ability of these 111 genes to predict GI50 was subsequently tested based upon their expression in a second independent gene expression platform (Affymetrix U133 plus 2.0). This analysis yielded 6 genes (KCNH2, CD74, CD53, HCLS1, ERC2 and HLA-DQB2) predicting higher GI50 values (p<0.05). We then tested the ability of these genes to predict Bu GI50 in a panel of 6 AML cell lines (K562, HL60, HL60-MX1, KG1, THP1 and NB4). To obtain GI50 values on AML cell lines we treated the cells with doses of Bu ranging from 0-200mcg/ml. At 24 hours, cells were washed and resuspended in fresh medium. Proliferation of cells was measured by standard 3H-thymidine uptake assay at 48 hours. Sigmoidal dose response curves and GI50 values were then calculated. GI50 values varied from 13.9 - 70.4 micromoles/ml. RNA quantitation for the 6 identified genes was performed using the Quantigene assay (Panomics, Santa Clara, CA). Expression was normalized to control gene levels (RPLP0). Two genes (ERC2 and HLA-DQB2) showed low or undetectable expression and were excluded from further analysis. Logistic regression analysis showed that a combined overexpression of any 2 of the remaining 4 genes was significantly associated with increasing resistance to Bu GI50 in AML cells (p=0.006). Of the 6 cell lines tested, the 2 most resistant (THP1 and K562) both displayed this pattern of gene overexpression.

To our knowledge, this is the first attempt to obtain a list of genomic biomarkers to predict Bu resistance in AML using a genome wide approach. This data provides a rationale for validation of these 4 genes in a clinical dataset with the potential future application of predicting relapse after Bu based high dose therapy.


No relevant conflicts of interest to declare.

Author notes


Asterisk with author names denotes non-ASH members.