Abstract
The course of chronic lymphocytic leukemia (CLL) is variable. In aggressive disease, the CLL cells usually express an unmutated immunoglobulin heavy-chain variable-region gene (IgVH) and the 70-kD zeta-associated protein (ZAP-70), whereas in indolent disease, the CLL cells usually express mutated IgVH but lack expression of ZAP-70. The reasons for the differences in clinical characteristics are unknown. Examination of microarray data has shown that these two subtypes of CLL share a common gene-expression pattern, suggesting that they constitute a single entity. However, the microarray data have also revealed some important differences between the two types of CLL in the expression of a small number of genes. While mRNA expression profiling by microarray is a useful and convenient way for signature gene recognition, systematic proteomic analysis may be more relevant to understanding the pathophysiology of disease. To our knowledge, few studies have performed systematic proteomic profiling on CLL and none have tried to identify proteins that are differentially expressed among patients with differing outcomes. We have applied multidimensional LC-ESI-tandem mass spectrometry to identify proteins that are differentially expressed between aggressive (5 ZAP-70 pos/IgVH unmutated) and indolent (5 ZAP-70 neg/IgVH mutated) purified B cell samples. A total of more than 3,000 proteins were identified in our proteomic analysis. We observed a positive correlation in expression of protein and mRNA of three genes (ZAP-70, gravin, and dystrophin); these genes were consistently associated with disease progression in CLL as reported by microarray analyses. This indicates that the proteomic data is of high quality. We also compared the proteomic and transcriptomic patterns between these two groups. In general, the correlation between mRNA and protein expression was poor. To identify the genes that appear coordinately regulated at the mRNA and protein level, we examined the mRNA expression pattern of about 200 proteins that were differentially expressed in our proteomic data between aggressive and indolent CLL. We found 37 genes were differentially regulated post-transcriptionally, perhaps through the influence of microRNA or protein stability. In addition, we found 117 genes to be differentially expressed in microarray but not proteomic analysis. This result raises the question of how reliable mRNA expression levels reflect the biological activity of protein function. In conclusion, we have identified a number of candidate proteins that are differentially expressed in CLL of distinctive clinical outcomes by comparing high quality proteomic and transcriptomic data. These proteins might serve as biomarkers or therapeutic targets. We also found genes that might be differentially regulated in CLL post-transcriptionally. Further studies of how these genes are regulated will advance our knowledge of CLL pathogenesis.
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