Targeted Next-Generation Sequencing of TP53, BIRC3, NOTCH1, SF3B1, and ATM Identifies a Significant Proportion of Lower-Risk Chronic Lymphocytic Leukemia with Unfavorable Prognostic Indicators

Introduction

The clinical course of chronic lymphocytic leukemia (CLL) is heterogeneous, ranging from indolent disease with essentially normal life expectancy to rapidly progressive disease with significantly decreased survival. Traditional risk stratification is dependent in large part on cytogenetic analysis by fluorescence in situ hybridization (FISH), with del(13q) as a sole abnormality associated with a favorable prognosis, trisomy 12 or normal cytogenetics associated with an intermediate prognosis, and del(11q) or del(17p) associated with an unfavorable prognosis.¹ In the last few years, recurrent mutations in key genes including TP53, BIRC3, NOTCH1, SF3B1, and ATM have also been identified as unfavorable prognostic indicators in CLL.^2-4 In a study by Rossi et al, integration of mutations and cytogenetic abnormalities was found to significantly improve the accuracy of survival prediction in CLL beyond that of FISH alone.² The aim of this study is to evaluate the frequency of these unfavorable mutations in an unselected cohort of CLL patients seen in the community setting, and to determine the percentage of lower-risk patients with a worse than expected prognosis who may potentially benefit from earlier and/or novel therapy.

Methods

An unselected cohort of 633 CLL patients seen in the community setting was included in this study. Demographic data included a mean age of 69 years, male to female ratio of 1.8:1, and mean WBC count of 48 g/dL. DNA sequences of key exons in TP53, BIRC3, NOTCH1, SF3B1, and ATM were determined from peripheral blood or bone marrow aspirates using a clinically validated next-generation sequencing (NGS) assay with a 5% lower limit of detection for single nucleotide variants. Results were compared between duplicate samples and annotated using software that queried databases containing known somatic mutations and germline variants. FISH analysis utilized probes specific for 11q22.3 (ATM), chromosome 12, 13q14.3/13q34, and 17p13.1 (TP53). CLL diagnoses were confirmed by flow cytometry, with FISH for t(11;14)(IGH-CCND1) also performed to exclude mantle cell lymphoma. The percentage of CLL cells by flow cytometry ranged from 18-98%, with a mean of 69%.

Results

Cytogenetic abnormalities were detected in 85% of CLL patients in this study, with del(13q) the most frequent (65%), followed by trisomy 12 (19%), del(11q) (17%), and del(17p) (10%). Mutations in any one of the 5 genes were detected in 37% of patients, with TP53 mutation the most frequent (12%), followed by mutations in NOTCH1 (11%), SF3B1 (10%), ATM (7%), and BIRC3 (3%). TP53 disruption as a whole was found in 14% of patients, consisting of del(17p) only (2%), TP53 mutation only (5%), and biallelic TP53 disruption (7%). ATM disruption as a whole was found in 21% of patients, consisting of del(11q) only (14%), ATM mutation only (4%), and biallelic ATM disruption (4%). Lower-risk patients, as defined by FISH showing either isolated del(13q), trisomy 12, or normal results, comprised 75% of patients, with 29% showing one or more unfavorable mutation: NOTCH1 (12%), SF3B1 (8%), TP53 (6%), ATM (4%), and BIRC3 (3%).

Conclusions

Mutations in TP53, BIRC3, NOTCH1, SF3B1, and ATM have previously been shown to be indicators of unfavorable prognosis in CLL. Using a clinically validated NGS assay, 37% of the CLL patients in our cohort were shown to have a mutation in any one of the 5 genes. In patients with lower-risk disease as defined by FISH, 29% showed one or more unfavorable mutation, including 6% with a TP53 mutation. Mutational profiling using NGS can thus help identify a significant proportion of lower-risk CLL patients with a worse than expected prognosis who may potentially benefit from earlier and/or novel therapy.

References

1. Dohner H, et al. N Engl J Med 2000;343:1910-1916

2. Rossi D, et al. Blood 2013;121:1403-1412

3. Austen B, et al. J Clin Oncol 2007;25:5448-5457

4. Skowronska A, et al. J Clin Oncol 2012;30:4524-32