Low-burden TP53 mutations represent frequent genetic events in CLL with an increased risk for treatment initiation

Abstract

TP53 aberrations predict chemoresistance and represent a contraindication for the use of standard chemoimmunotherapy in chronic lymphocytic leukaemia (CLL). Recent next-generation sequencing (NGS)-based studies have identified frequent low-burden TP53 mutations with variant allele frequencies below 10%, but the clinical impact of these low-burden TP53 mutations is still a matter of debate. In this study, we aimed to scrutinise the subclonal architecture and clinical impact of TP53 mutations using a sensitive, NGS-based mutation analysis in a 'real-world' cohort of 901 patients with CLL. In total, 225 TP53 mutations were identified in 17.5% (158/901) of the patients; 48% of these alterations represented high-burden mutations, while 52% were low-burden TP53 mutations. Low-burden mutations as sole alterations were identified in 39% (62/158) of all mutated cases with 82% (51/62) of these being represented by a single low-burden TP53 mutation. Patients harbouring low-burden TP53 mutations had significantly lower time to first treatment compared to patients with wild-type TP53. Our study has expanded the knowledge on the frequency, clonal architecture, and clinical impact of low-burden TP53 mutations. By demonstrating that patients with sole low-burden TP53 variants represent more than one-third of patients with TP53 mutations and have an increased risk for treatment initiation, our findings strengthen the need to redefine the threshold of TP53 variant reporting to below 10% in the routine diagnostic setting.

Keywords: NGS; TP53; chronic lymphocytic leukaemia.

Figure 1

Frequency and distribution of TP53 mutations. (A) TP53 mutation was identified in 17.5% of the patients with the illustrated frequency and distribution of low‐burden and high‐burden mutations. (B–D) The frequency and distribution of TP53 mutations in samples collected at the time of diagnosis, before treatment initiation, and post‐treatment respectively. The first pie chart of each pair (on the left) includes the total number of patients analysed in the respective subgroup, whereas the second pie chart (on the right) includes only patients carrying TP53 mutations in the respective subgroup. M, mutation.

Figure 2

Distribution and type of TP53 mutations along the TP53 gene and protein in the high‐VAF and low‐VAF TP53 mutation context. (A) Mutational distributions along the p53 protein. Each triangle represents an individual TP53 mutation with a colour referring to mutation type. (B) Mutational distributions along the coding sequence of the TP53 gene with pie charts showing the frequency of each mutational type. (C) VAFs of TP53 mutations. Each column represents the VAF of an individual TP53 mutation. DBD, DNA‐binding domain; M, mutation; OD, oligomerisation domain; PRD, proline‐rich domain; TAD, transactivation domain. *Pre‐treatment samples include samples collected at the time of diagnosis.

Figure 3

Frequency and distribution of del(17p) as well as IGHV status in the cohort. (A) Frequency of del(17p) in the high‐VAF and low‐VAF TP53 mutation context. (B) Frequency of del(17p) in the cohort, and in patients harbouring TP53 mutation (D). (C) Frequency of TP53 mutations in patients harbouring del(17p). (E) Distribution of IGHV status among TP53 subgroups. (F–H) The frequency of TP53 mutations among IGHV subgroups.

Figure 4

TFS (A and C) and TTFT (B and D) computed as time (months) from sample collection. p values are represented in the tables below the panels. M, mutated IGHV status; TP53M, TP53 mutation; U, unmutated IGHV status.