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

## TL;DR

This study shows that deletion of chromosome 11q, not ATM mutations, is a key predictor of early disease progression in chronic lymphocytic leukemia.

## Contribution

The study clarifies that del(11q) is a stronger prognostic biomarker than ATM mutations in CLL.

## Key findings

- ATM mutations co-occur with del(11q) in 45.5% of cases.
- Multivariable analysis shows del(11q) is an independent predictor of shorter time-to-treatment in CLL.
- Isolated ATM mutations are rare and not strongly prognostic.

## 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.