Quantitative Gene Expression Analysis of Surrogate Markers for Genetic Risk Groups and Survival in CLL

In CLL, a variety of surrogate markers for individual genetic features, mostly the VH mutation status, were proposed from gene expression analyses. However, their detailed relation to specific genetic subsets such as V3-21 usage, del11q22-q23 (11q−), and del17p13 (17p−), and their prognostic value in relation to established factors is not elucidated yet. Gene expression markers (ADAM29, ATM, CLLU1, DMD, GLO1, HS1, KIAA0977, LPL, MGC9913, PCDH9, PEG10, SEPT10, TCF7, TP53, Vimentin, ZAP-70, ZNF2) were evaluated using real-time quantitative RT-PCR (RQ-PCR) in purified samples of 151 patients. VH sequencing and FISH screening for genomic aberrations were carried out for all cases, survival information was available for 133 cases. Logistic regression was performed to test the predictive value of gene expression for genetic risk groups, Cox proportional hazards statistics for survival analysis. VH mutation status was best assigned by LPL and ZAP70, followed by TCF7, a marker with a characteristic overexpression in VH mutated CLL patients (correct VH prediction in 83%, 83%, and 75% of the patients, respectively). A similar rate of correct VH assignments was achieved in the subgroup of patients with 11q− or 17p− when using these markers (88%, 86%, and 79%, respectively). In contrast to LPL and TCF7, most of the patients with V3-21 usage were recognized as risk patients by ZAP70 independently of the VH status. Therefore, ZAP70 yielded the best results for the overall recognition of patients with a genetic risk constellation (VH unmutated or V3-21 usage or 11q− or 17p−). Comparison of ZAP-70 determination by RQPCR and flow cytometry was performed for 72 patients and revealed 30% of discordant cases. Thereof, the majority was VH unmutated (including several cases with 11q− or 17p−) showing ZAP-70 negativity by FACS and positivity by RQ-PCR. In multivariate analysis of time to first treatment (TFT), ADAM29 was an independent prognostic factor besides the VH status and Binet stage. In overall survival analysis including the gene expression variables only, LPL was the strongest predictor for overall survival. When genetic and clinical factors were added to this analysis, V3-21 usage, 17p−, age, binet stage, and expression of ATM, ADAM29, SEPT10, and TCL1 were identified as significant prognostic factors. In conclusion, novel gene expression markers allow screening for patients at risk but can not fully substitute for the genetic factors, which should therefore at present remain the basis for risk stratification approaches. Some of the novel markers appear to have a prognostic relevance independently of the established factors, which points to relevant biologic and clinical implications demanding further investigation.