CDNA microarray gene expression analysis of B-cell chronic lymphocytic leukemia proposes potential new prognostic markers involved in lymphocyte trafficking.

Human cancer is characterized by complex molecular perturbations leading to variable clinical behavior, often even in single-disease entities. We performed a feasibility study systematically comparing large-scale gene expression profiles with clinical features in human B-cell chronic lymphocytic leukemia (B-CLL). cDNA microarrays were employed to determine the expression levels of 1,024 selected genes in 54 peripheral blood lymphocyte samples obtained from patients with B-CLL. Statistical analyses were applied to correlate the expression profiles with a number of clinical parameters including patient survival and disease staging. We were able to identify genes whose expression levels significantly correlated with patient survival and/or with clinical staging. Most of these genes code either for cell adhesion molecules (L-selectin, integrin-beta2) or for factors inducing cell adhesion molecules (IL-1beta, IL-8, EGR1), suggesting that prognosis of this disease may be related to a defect in lymphocyte trafficking. This report demonstrates the feasibility of a systematic integration of large-scale gene expression profiles with clinical data as a general approach for dissecting human diseases.

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.

Observations on the reproducibility and matching efficiency of two-dimensional electrophoresis gels: consequences for comprehensive data analysis.

Protein expression profiling by proteomics has the potential to be an ideal tool for the description of changes in complex biological systems or in the characterization of a disease. This study analyzes in more quantitative terms how methodological drawbacks of the current technology can hamper the comprehensive analysis of large sets of spot patterns by statistical means. Irreproducibilities in spot intensities due to silver staining and geometric distortions of the spot patterns inherent to the electrophoresis procedure push even the semiautomatic alignment and matching to their limits. This leads to reduced matching efficiencies for identical spots if no additional exhaustive manual matching is performed for every single spot in all gels. As a consequence, only a limited number of spots can be matched in all gels of a large set. The statistical pattern analysis of such data sets will thus not allow the comprehensive description of relevant pattern changes.