Marlene Michelle Dressman

Pharmacogenomic Analysis of Cytogenetic Response in Chronic Myeloid Leukemia Patients Treated with Imatinib

Purpose: To better understand the molecular basis of cytogenetic response in chronic myeloid leukemia patients treated with imatinib, we studied gene expression profiles from a total of 100 patients from a large, multinational Phase III clinical trial (International Randomized Study of IFN-α versus STI571). Experimental Design: Gene expression data for >12,000 genes were generated from whole blood samples collected at baseline (before imatinib treatment) using Affymetrix oligonucleotide microarrays. Cytogenetic response was determined based on the percentage of Ph+ cells from bone marrow following a median of 13 months of treatment. Results: A genomic profile of response was developed using a subset of individuals that exhibited the greatest divergence in cytogenetic response; those with complete response (0% Ph+ cells; n = 53) and those with minimal or no response (>65% Ph+ cells; n = 13). A total of 55 genes was identified that were differentially expressed between these two groups. Using a “leave-one-out” strategy, we identified the optimum 31 genes from this list to use as our genomic profile of response. Using this genomic profile, we were able to distinguish between individuals that achieved major cytogenetic response (0–35% Ph+ cells) and those that did not, with a sensitivity of 93.4% (71 of 76 patients), specificity of 58.3% (14 of 24 patients), positive predictive value of 87.7%, and negative predictive value of 73.7%. Conclusions: Interestingly, many of the genes identified appear to be strongly related to reported mechanisms of BCR-ABL transformation and warrant additional research as potential drug targets. The validity and clinical implications of these results should be explored in future studies.

Signing on to expression profiles

Unique expression patterns of a large number of genes can now define cell specific signatures under a given context. Cell specific signatures will be invaluable to understanding differentiation, cell type specificity and the cellular biology of environmental responses. Expression signatures could greatly enhance drug development by increasing efficacy and decreasing toxicity of therapeutic compounds. We have used (Affymetrix) oligonucleotide microarrays to survey and compare the expression profiles of 7000 human genes from cells of various origins, including lymphocytes, umbilical vein endothelial cells (HUVEC), a breast adenocarcinoma cell line (MCF7) and a glioblastoma cell line (U373MG). Environmental context such as time in culture, state of differentiation, media composition, CO2 content and culture confluency may alter cell signatures. Chemical compound manipulation of cell lines provides one mechanism to dissect function at the gene expression level. For example, extended treatment of endothelial cells with vascular endothelial growth factor (VEGF) results in greater than two-fold changes in expression level of approximately 100 genes, while extended treatment of glioma cell lines with platelet derived growth factor (PDGF) results in greater that two-fold changes in 39 genes. Analysing expression data from multiple cell lines can also be used to identify similarities of expression profiles for all cell lines. We have observed that an average cell type expresses 2335 out of 7000 genes assayed (approxiamately 33%). Sixty-four percent of the 2335 genes are expressed in endothelial, U373MG, and MCF7 cells, with a total of 630 expressed at similar levels in all three cell types despite variation in growth media. Additional cell types are being analyzed to refine the universal and cell-specific signatures.