Correlation of clinical data with proteomics profiles in 24 patients with B-cell chronic lymphocytic leukemia.
The development of human cancer is caused by complex molecular perturbations leading to variable clinical behavior often even in single disease entities. To prove that expression profiling on the protein level can be correlated with clinical data we systematically compared in a pilot study the protein expression patterns obtained by 2-dimensional gel electrophoresis with clinical features in human B-cell chronic lymphocytic leukemia (B-CLL), a disease characterized by broad clinical variability. Statistical methods were devised to analyze the spot pattern from 24 patient samples. This analysis allowed the identification of proteins that clearly discriminated between the patient groups with defined chromosomal characteristics or whose expression levels did correlate with clinical parameters such as patient survival. This report demonstrates that the correlation of large-scale protein expression profiles with clinical data can be used to gain new insights into molecular aspects of a disease. The data described here show that B-CLL patient populations with shorter survival times exhibit changed levels of redox enzymes, heat shock protein 27 and protein disulfide isomerase. These molecules may be potentially involved in drug resistance.