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. 2025 Jul;39(7):1650-1660.
doi: 10.1038/s41375-025-02615-5. Epub 2025 Apr 24.

ATM aberrations in chronic lymphocytic leukemia: del(11q) rather than ATM mutations is an adverse-prognostic biomarker

Affiliations

ATM aberrations in chronic lymphocytic leukemia: del(11q) rather than ATM mutations is an adverse-prognostic biomarker

Birna Thorvaldsdottir et al. Leukemia. 2025 Jul.

Abstract

Despite the well-established adverse impact of del(11q) in chronic lymphocytic leukemia (CLL), the prognostic significance of somatic ATM mutations remains uncertain. We evaluated the effects of ATM aberrations (del(11q) and/or ATM mutations) on time-to-first-treatment (TTFT) in 3631 untreated patients with CLL, in the context of IGHV gene mutational status and mutations in nine CLL-related genes. ATM mutations were present in 246 cases (6.8%), frequently co-occurring with del(11q) (112/246 cases, 45.5%). ATM-mutated patients displayed a different spectrum of genetic abnormalities when comparing IGHV-mutated (M-CLL) and unmutated (U-CLL) cases: M-CLL was enriched for SF3B1 and NFKBIE mutations, whereas U-CLL showed mutual exclusivity with trisomy 12 and TP53 mutations. Isolated ATM mutations were rare, affecting 1.2% of Binet A patients and <1% of M-CLL cases. While univariable analysis revealed shorter TTFT for Binet A patients with any ATM aberration compared to ATM-wildtype, multivariable analysis identified only del(11q), trisomy 12, SF3B1, and EGR2 mutations as independent prognosticators of shorter TTFT among Binet A patients and within M-CLL and U-CLL subgroups. These findings highlight del(11q), and not ATM mutations, as a key biomarker of increased risk of early progression and need for therapy, particularly in otherwise indolent M-CLL, providing insights into risk-stratification and therapeutic decision-making.

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Conflict of interest statement

Competing interests: PG: Honoraria/advisory board: AbbVie, Acerta/AstraZeneca, Adaptive, ArQule/MSD, BeiGene, CelGene/Juno, Gilead, Janssen, Loxo/Lilly, Sunesis. Research funding: AbbVie, Gilead, Janssen, Novartis, Sunesis; LS: advisory board AbbVie, AstraZeneca, Janssen; RR: honoraria/advisory board: AbbVie, AstraZeneca, Illumina, Janssen, Lilly and Roche; KS: honoraria/advisory board: AbbVie, Acerta/AstraZeneca, Gilead, Janssen. Research funding: AbbVie, Gilead, Janssen; PB: honoraria from Abbvie, Gilead and Janssen. Research funding from Gilead; GG: Advisory Board/Speaker’s bureau: Abbvie, AstraZeneca, Beigene, Hikma, Incyte, Johnson & Johnson, Lilly; LB: honoraria/advisory board: Abbvie, Amgen, Astellas, BMS/Celgene, Daiichi Sankyo, Gilead, Hexal, Janssen, Jazz Pharmaceuticals, Menarini, Novartis, Pfizer, Sanofi, Seattle Genetics. Research funding: Bayer, Jazz Pharmaceuticals; GMR: honoraria from Abbvie, AstraZeneca, Gilead and Janssen. Research funding from Gilead; CB: Honoraria/advisory board: AstraZeneca and Eli Lilly. CUN received research grants and/or honoraria from Abbvie, AstraZeneca, Janssen, Genmab, Beigene, Octapharma, MSD, Lilly, Synamics, CSL Behring, Takeda, Nofo Nordisk Foundation. The other authors declare no competing financial interests

Figures

Fig. 1
Fig. 1. Classification of reported ATM variants.
A Hierarchical flowchart used to assign ATM variants to putative ‘germline/neutral’ or ’somatic/mutated’ categories. B Distribution of variant allele frequencies (VAFs) for ATM variants in each flowchart category, bar chart shows the proportion del(11q) positive cases for each category. C Distribution of VAFs for all variants assigned as ‘germline/neutral’ and ‘somatic/mutated’. D Graphical representation of amino acid changes and frequencies for all ATM variants in the cohort. Putative somatic variants are displayed above and putative germline/predicted neutral variants are shown below. *Confirmed germline by sequencing in published datasets [30, 31] and in unpublished data. **Four ATM variants, each observed in multiple patients and variably classified as either germline/neutral or somatic/mutated depending on the final step of the classification system, were reviewed and reassigned to a single classification category (Supplementary Table S2).
Fig. 2
Fig. 2. Overview of recurrent genetic aberrations in the entire cohort and ATM-mutated cases.
A Overview of all 3631 CLL cases included in the study, sorted by frequency of mutations in 10 recurrently mutated genes. B Oncoplot showing detected mutations in recurrently mutated genes, IGHV somatic hypermutation status and chromosomal aberrations in 246 ATM-mutated cases. C Co-occurrence of recurrent gene mutations and chromosomal aberrations in the entire cohort. Odds ratios (OR) and BH-adjusted p values derived from two-sided Fisher exact tests. OR 0–1 indicates a trend towards mutual exclusivity, OR > 1 indicates a trend towards co-occurrence. U-CLL, CLL with unmutated IGHV genes, M-CLL, CLL with mutated IGHV genes.
Fig. 3
Fig. 3. Overview of detected recurrent genetic abnormalities in U-CLL and M-CLL.
A Oncoplot and (B) co-occurrence plot displaying recurrently mutated genes and chromosomal aberrations in 1502 U-CLL cases. C Oncoplot and (D) co-occurrence plot with recurrently mutated genes and chromosomal aberrations in 1900 M-CLL cases. Odds ratios (OR) and BH-adjusted p values derived from two-sided Fisher exact tests. OR 0–1 indicates a trend towards mutual exclusivity, OR > 1 indicates a trend towards co-occurrence. U-CLL CLL with unmutated IGHV genes, M-CLL CLL with mutated IGHV genes.
Fig. 4
Fig. 4. Clinical impact of ATM aberrations in Binet A CLL patients.
Kaplan-Meier survival analysis using TTFT subdivided by (A) ATM aberration; somatic ATM mutation only, del(11q) only and combined ATM mutation and del(11q), (B) type of ATM mutation; frameshift/nonsense, missense/inframe indels with del(11q) displayed separately, and (C) comparing one versus multiple ATM mutations with del(11q) displayed separately.
Fig. 5
Fig. 5. Clinical impact of ATM aberrations in Binet A CLL patients stratified by IGHV somatic hypermutation status.
Kaplan-Meier survival analysis using TTFT in Binet stage A in (A) U-CLL and (B) M-CLL patients. Pairwise comparisons were performed using the Cox–Mantel log-rank test. C Multivariable analysis using TTFT in Binet stage A CLL patients with U-CLL and M-CLL. U-CLL, CLL with unmutated IGHV genes, M-CLL, CLL with mutated IGHV genes. CI95, 95% confidence interval; * indicates a p value < 0.05, ** p < 0.01, and *** p < 0.001.

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