Chronic lymphocytic leukemia (CLL) is a heterogeneous disease where a significant proportion of patients will develop an aggressive disease. Today, the mutational status of the immunoglobulin heavy variable (IGHV) genes is one of the strongest prognostic markers in CLL, where unmutated IGHV genes correlate with poor outcome. In addition, IGHV3-21 gene usage is associated with poor prognosis independent of mutational status. Recently, several genes were shown to be differently expressed between IGHV mutated and unmutated CLL and were suggested as prognostic markers. The aim of this thesis was to examine the applicability of these RNA-based prognostic markers in CLL. In papers I and II, the prognostic significance of LPL and TCL1A mRNA expression in CLL was investigated in 140 and 144 patients, respectively. High expression was found to be associated with inferior clinical outcome for both markers. However, CLL cases with mutated IGHV3-21 genes displayed low levels of LPL expression, indicating that LPL cannot identify this poor-risk patient group. In contrast, high TCL1A expression was detected in all IGHV3-21 cases. To elucidate the functionality of LPL in CLL, LPL lipase activity was measured in 33 cases. The lipase activity was found to be invariably low, implying an alternative function for LPL in CLL. In paper III, a comprehensive analysis of five RNA-based markers (LPL, TCL1A, ZAP70, CLLU1 and MCL1) was performed in 252 CLL patients. All RNA-based markers except MCL1 predicted clinical outcome, with LPL being the strongest. Moreover, LPL expression independently predicted overall survival when adjusted for established markers. All of the RNA-based markers added additional prognostic information to established markers, e.g. high LPL expression predicted an inferior outcome in patients with mutated IGHV genes or good-risk cytogenetics. For clinical application, over time stability of prognostic markers is crucial. In paper IV, the expression of LPL, TCL1A, ZAP70 and MCL1 was investigated in samples taken at diagnosis and at a follow-up of seven years in 104 CLL patients. LPL was found to be the most stable marker, displaying high correlation between the sequential samples, whereas ZAP70 and MCL1 varied significantly. TCL1A expression increased at follow-up, which may indicate disease progression as TCL1A promotes cell survival. In summary, this thesis highlights the applicability of RNA-based markers in CLL prognostication, both as single markers or in combination with established markers. In particular, LPL was shown to be the strongest RNA-based marker in terms of prognostic strength and stability.

The clinical course of chronic lymphocytic leukemia (CLL) is highly heterogeneous, which has prompted the search for biomarkers that can predict prognosis in this disease. The IGHV gene mutation status and certain genomic aberrations have been identified as reliable prognostic markers of clinical outcome for this disorder. However, the search for more feasible prognostic markers in CLL is still being pursued. Recently, certain single nucleotide polymorphisms (SNPs) in the GNAS1, BCL2 and MDM2 genes and the RNA expression levels of the LPL, ZAP70, TCL1, CLLU1 and MCL1 genes were suggested as novel prognostic markers in CLL. In papers I-III, we performed genotyping analyses of the GNAS1 T393C, BCL2 -938C>A and MDM2 SNP309 polymorphisms in 268-418 CLL patients and related the genotypes with clinical data. Association studies between the polymorphisms and established prognostic markers (i.e. IGHV mutation status, genomic aberrations, CD38 expression) were also performed. Our studies did not find any significant relationship between these SNPs with either clinical outcome or other known prognostic markers in CLL. In paper IV, we measured the RNA expression levels of LPL, ZAP70, TCL1, CLLU1 and MCL1 in 252 CLL cases and correlated these levels with clinical outcome. Here, we verified that high expression of all these RNA-based markers, except MCL1, were associated with an unfavourable prognosis. We also confirmed a close relationship between IGHV mutation status and the RNA-based markers, especially for LPL and CLLU1 expression. Among the RNA-based markers, multivariate analysis revealed LPL expression as the strongest independent prognostic marker for overall survival and time to treatment. Furthermore, the RNA-based markers could add further prognostic information to established markers in subgroups of patients, with LPL expression status giving the most significant results. In summary, data from papers I-III could not verify the GNAS1 T393C, BCL2 -938C>A and MDM2 SNP309 polymorphisms as prognostic markers in CLL. Future SNP markers must hence be confirmed in large, independent cohorts before being proposed as prognostic marker in CLL. In paper IV, we conclude that LPL expression appears to be the strongest among the RNA-based markers for CLL prognostication. Further efforts to standardize LPL quantification are required before it can be applied in the clinical laboratory to predict clinical outcome in this disease.