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.

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W e present a laboratory-based prognostic calculator (designated CRO score) to risk stratify treatment-free survival in early stage (Rai 0) chronic lymphocytic leukemia (CLL) developed using a training-validation model in a series of 1,879 cases from Italy, the United Kingdom and the United States. By means of regression analysis, we identified five prognostic variables with weighting as follows: deletion of the short arm of chromosome 17 and unmutated immunoglobulin heavy chain gene status, 2 points; deletion of the long arm of chromosome 11, trisomy of chromosome 12, and white blood cell count >32.0x10 3 /microliter, 1 point. Low-, intermediate-and high-risk categories were established by recursive partitioning in a training cohort of 478 cases, and then validated in four independent cohorts of 144 / 395 / 540 / 322 cases, as well as in the composite validation cohort. Concordance indices were 0.75 in the training cohort and ranged from 0.63 to 0.74 in the four validation cohorts (0.69 in the composite validation cohort). These findings advocate potential application of our novel prognostic calculator to better stratify early-stage CLL, and aid case selection in risk-adapted treatment for early disease. Furthermore, they support immunocytogenetic analysis in Rai 0 CLL being performed at the time of diagnosis to aid prognosis and treatment, particularly in today's chemofree era.

Chronic lymphocytic leukemia (CLL) is a heterogeneous disease with a variable clinical course. Novel biomarkers discovered over the past 20 years have revolutionized the way clinicians approach prognostication and treatment especially in the chemotherapy-free era. Herein, we review the best established prognostic and predictive biomarkers in the setting of chemoimmunotherapy (CIT) and novel targeted therapy. We propose that TP53 disruption (defined as either TP53 mutation or chromosome 17p deletion), unmutated immunoglobulin heavy chain variable region gene status (UM IGHV), NOTCH1 mutation, and CD49d expression are the strongest prognosticators of disease progression and overall survival in the field of novel biomarkers including recurrent gene mutations. We also highlight the predictive role of TP53 disruption, UM IGHV, and NOTCH1 mutation in the setting of CIT and TP53 disruption and CD49d expression in the setting of novel targeted therapy employing B-cell receptor (BCR) and B-cell lymphoma-2 (BCL2) inhibition. Finally, we discuss future directions in the field of biomarker development to identify those with relapsed/refractory disease at risk for progression despite treatment with novel therapies.