TP53 Mutations with Low Variant Allele Frequency Predict Short Survival in Chronic Lymphocytic Leukemia.

PURPOSE: In chronic lymphocytic leukemia (CLL), TP53 mutations are associated with reduced survival and resistance to standard chemoimmunotherapy (CIT). Nevertheless, the clinical impact of subclonal TP53 mutations below 10% to 15% variant allele frequency (VAF) remains unclear. EXPERIMENTAL DESIGN: Using a training/validation approach, we retrospectively analyzed the clinical and biological features of TP53 mutations above (high-VAF) or below (low-VAF) the previously reported 10.0% VAF threshold, as determined by deep next-generation sequencing. Clinical impact of low-VAF TP53 mutations was also confirmed in a cohort (n = 251) of CLL treated with fludarabine-cyclophosphamide-rituximab (FCR) or FCR-like regimens from two UK trials. RESULTS: In the training cohort, 97 of 684 patients bore 152 TP53 mutations, while in the validation cohort, 71 of 536 patients had 109 TP53 mutations. In both cohorts, patients with the TP53 mutation experienced significantly shorter overall survival (OS) than TP53 wild-type patients, regardless of the TP53 mutation VAF. By combining TP53 mutation and 17p13.1 deletion (del17p) data in the total cohort (n = 1,220), 113 cases were TP53 mutated only (73/113 with low-VAF mutations), 55 del17p/TP53 mutated (3/55 with low-VAF mutations), 20 del17p only, and 1,032 (84.6%) TP53 wild-type. A model including low-VAF cases outperformed the canonical model, which considered only high-VAF cases (c-indices 0.643 vs. 0.603, P < 0.0001), and improved the prognostic risk stratification of CLL International Prognostic Index. Clinical results were confirmed in CIT-treated cases (n = 552) from the retrospective cohort, and the UK trials cohort. CONCLUSIONS: TP53 mutations affected OS regardless of VAF. This finding can be used to update the definition of TP53 mutated CLL for clinical purposes.

CD49d promotes disease progression in chronic lymphocytic leukemia: new insights from CD49d bimodal expression.

CD49d is a remarkable prognostic biomarker of chronic lymphocytic leukemia (CLL). The cutoff value for the extensively validated 30% of positive CLL cells is able to separate CLL patients into 2 subgroups with different prognoses, but it does not consider the pattern of CD49d expression. In the present study, we analyzed a cohort of 1630 CLL samples and identified the presence of ∼20% of CLL cases (n = 313) characterized by a bimodal expression of CD49d, that is, concomitant presence of a CD49d+ subpopulation and a CD49d- subpopulation. At variance with the highly stable CD49d expression observed in CLL patients with a homogeneous pattern of CD49d expression, CD49d bimodal CLL showed a higher level of variability in sequential samples, and an increase in the CD49d+ subpopulation over time after therapy. The CD49d+ subpopulation from CD49d bimodal CLL displayed higher levels of proliferation compared with the CD49d- cells; and was more highly represented in the bone marrow compared with peripheral blood (PB), and in PB CLL subsets expressing the CXCR4dim/CD5bright phenotype, known to be enriched in proliferative cells. From a clinical standpoint, CLL patients with CD49d bimodal expression, regardless of whether the CD49d+ subpopulation exceeded the 30% cutoff or not, experienced clinical behavior similar to CD49d+ CLL, both in chemoimmunotherapy (n = 1522) and in ibrutinib (n = 158) settings. Altogether, these results suggest that CD49d can drive disease progression in CLL, and that the pattern of CD49d expression should also be considered to improve the prognostic impact of this biomarker in CLL.

Cluster analysis of immunophenotypic data: the example of chronic lymphocytic leukemia.

Studies of gene expression profiling have been successfully used for the identification of molecules to be employed as potential prognosticators. In analogy with gene expression profiling, we have previously proposed an original method to identify the immunophenotypic signature of chronic lymphocytic leukemia (CLL) subsets with different prognosis, named surface-antigen expression profiling. According to this method, expression data for surface markers can be successfully analyzed by data mining tools identical to those employed in gene expression profiling studies, including unsupervised and supervised algorithms, with the aim to identify the immunophenotypic signature of CLL subsets with different prognosis. By employing an identical approach for investigating the reactivity of a wide panel of monoclonal antibodies provided by the "Ninth International Workshop on Leukocyte Differentiation Antigens", we were able to identify some of them (i.e. TCL1, CCR7, FCRL2, FCRL3, and CD150) as additional potential markers with prognostic relevance in CLL. These suggestions need to be confirmed: (i) in a new set of clinically characterized CLL cases; (ii) in combination with other prognostic markers in the context of comprehensive scoring systems for clinical outcome prediction.