Different spectra of recurrent gene mutations in subsets of chronic lymphocytic leukemia harboring stereotyped B-cell receptors

Abstract

We report on markedly different frequencies of genetic lesions within subsets of chronic lymphocytic leukemia patients carrying mutated or unmutated stereotyped B-cell receptor immunoglobulins in the largest cohort (n=565) studied for this purpose. By combining data on recurrent gene mutations (BIRC3, MYD88, NOTCH1, SF3B1 and TP53) and cytogenetic aberrations, we reveal a subset-biased acquisition of gene mutations. More specifically, the frequency of NOTCH1 mutations was found to be enriched in subsets expressing unmutated immunoglobulin genes, i.e. #1, #6, #8 and #59 (22-34%), often in association with trisomy 12, and was significantly different (P<0.001) to the frequency observed in subset #2 (4%, aggressive disease, variable somatic hypermutation status) and subset #4 (1%, indolent disease, mutated immunoglobulin genes). Interestingly, subsets harboring a high frequency of NOTCH1 mutations were found to carry few (if any) SF3B1 mutations. This starkly contrasts with subsets #2 and #3 where, despite their immunogenetic differences, SF3B1 mutations occurred in 45% and 46% of cases, respectively. In addition, mutations within TP53, whilst enriched in subset #1 (16%), were rare in subsets #2 and #8 (both 2%), despite all being clinically aggressive. All subsets were negative for MYD88 mutations, whereas BIRC3 mutations were infrequent. Collectively, this striking bias and skewed distribution of mutations and cytogenetic aberrations within specific chronic lymphocytic leukemia subsets implies that the mechanisms underlying clinical aggressiveness are not uniform, but rather support the existence of distinct genetic pathways of clonal evolution governed by a particular stereotyped B-cell receptor selecting a certain molecular lesion(s).

Figure 1.

Recurrent gene mutations in stereotyped CLL subsets. The distribution of mutations within NOTCH1, SF3B1 and TP53 varied considerably between the major stereotyped subsets included in the present study. All cases were devoid of MYD88 mutations and BIRC3 mutations were rare, with no clear bias to any subset (this data is not shown in the graph). M-CLL: mutated IGHV gene; U-CLL: unmutated IGHV gene.

Figure 2.

SF3B1 mutations in subsets #2 and #3. (A) Distribution of SF3B1 mutations in subsets #2 and #3. Overall, 45% (72/161) of subset #2 and 46% (12/26) of subset #3 cases were found to carry mutations within SF3B1. While the majority of subset #2 cases (69/72; 96%) carried a single SF3B1 mutation, 3 cases had 2 mutations within SF3B1 (2/3 cases carried the p.K700E change, with one case carrying both p.K700E and p.G742D). Although the most frequent amino acid change in both subsets involved a lysine to glutamic acid substitution at codon 700 (exon 15), representing 57% (43/75) and 33% (4/12) of all SF3B1 mutations in subsets #2 and #3, respectively, the overall distribution of mutations varied. To elaborate, in subset #3, all remaining SF3B1 mutations (excluding p.K700E) occur within exon 14. This is in contrast to the SF3B1 mutational profile in subset #2 where only 17% of mutations are found within exon 14 and where two particular substitutions account for 96% and 88% of the alterations observed in exon 15 and exon 16 (p.K700E and p.G742D, respectively). *indicates that more than one amino acid change occurred at this codon (detailed in Online Supplementary Table S8). (B) Prognostic implications of SF3B1 mutations within subset #2 on overall survival (OS) and time to first treatment (TTFT). (Binet A cases).

Figure 3.

Main biological associations within subset #1. (A) Concurrent mutations within subset #1. Only cases for which the mutational status of all 3 genes (NOTCH1, SF3B1 and TP53) was available were included in the figure (n=135). Fifty-seven cases had a mutation in at least one of the gene hotspots whereas 78 cases were wild-type for these genes. (B) Spectrum of mutations and genomic aberrations within subset #1. Despite a high frequency of NOTCH1 mutations, a large proportion (58%) of subset #1 cases carried no mutations within the 5 genes analyzed. Specifically, considering the subset #1 cases lacking any recurrent gene mutations, 35% also lacked any recurrent genetic aberrations. Collectively, this resulted in the absence of any recurrent gene mutation or cytogenetic aberration in approximately 20% of subset #1 cases, thereby implying that additional mechanisms must account for the clinically aggressive nature of this subset. Only cases for which the mutational status of all 3 genes (NOTCH1, SF3B1 and TP53) was available were included in the figure (n=135). *indicates that none of the known recurrent genomic aberrations were present; NOTCH1^mut: mutation in NOTCH1 only; TP53^mut: mutation in TP53 only; SF3B1^mut: mutation in SF3B1 only. Concurrent^mut refers to the presence of mutations in more than one of the genes analyzed. Absolute numbers and percentages are provided in brackets. For del(17p), 2/53 correspond to the 4% indicated in the figure. (C) The frequency of NOTCH1 mutations in subset #1 cases varies depending on specific IGHV gene usage. Only the top 3 utilized IGHV genes within subset #1 patients in our cohort were included in the graph, collectively accounting for 73% (99/136) subset #1 cases. Mutations within NOTCH1 were found to be particularly frequent in subset #1 cases expressing IGHV1-2*02 (17/39; 44%).