High-risk molecular features may eclipse genomic complexity in predicting chronic lymphocytic leukemia outcomes; UK clinical trial insights

Parker, H., Carr, L., Norris, K., Nilsson-Takeuchi, A., Stevens, B., Amarasinghe, H., Kadalayil, Latha, Else, M., Clifford, Ruth, Pettitt, A., Munir, T., Schuh, A., Walewska, R., Baird, D. M. ORCID: https://orcid.org/0000-0001-8408-5467, Oscier, D. G., Pepper, C., Bryant, D., Gibson, J. and Strefford, J. C. 2026. High-risk molecular features may eclipse genomic complexity in predicting chronic lymphocytic leukemia outcomes; UK clinical trial insights. Leukemia Item availability restricted.

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Abstract

High genomic complexity (HGC) is linked to poor prognosis in CLL, but its independent prognostic value remains uncertain amid emerging biomarkers. We analysed copy number alterations (CNA) in 495 untreated patients from (immuno)chemotherapy trials (CLL4, ADMIRE, ARCTIC), incorporating IGHV status, telomere length (TL), targeted sequencing, and DNA-methylation subtypes. Patients harboured low (LGC, 2 CNAs; n=334), intermediate (IGC, 3–4 CNAs; n=97), or high (HGC, 5 CNAs; n=64) genomic complexity. HGC associated with U-CLL (81%, p<0.001), TP53-aberration (36%, p<0.001), short TL (TL-S; 61%, p<0.05), del13q (50%, p<0.001) and del11q (22%, p<0.05). IGC was enriched biallelic ATM disruption and BIRC3 deletions (p<0.001). Trisomy 12 and NOTCH1 mutations were enriched in LGC (p<0.001). HGC associated with shorter progression-free and overall survival in univariate models but only remained independent for OS in CLL4 (HR=1.61, p=0.02). Independent prognostic factors included TP53 aberration, U-CLL, TL-S and n-CLL. Of 64 HGC patients, 23 had TP53-aberration; 92% of TP53 wild-type cases had other high-risk features (TL-S, U-CLL, or n-CLL). HGC may reflect a convergence of high-risk features rather than represent an independent biomarker. The interplay of telomere attrition, IGHV status, and DNA methylation subtype necessitates further validation in targeted therapy cohorts to enhance risk assessment in prognostic models.

Item Type:	Article
Status:	In Press
Schools:	Schools > Medicine
Publisher:	Nature Publishing Group
ISSN:	0887-6924
Date of First Compliant Deposit:	30 January 2026
Date of Acceptance:	30 January 2026
Last Modified:	30 Jan 2026 16:55
URI:	https://orca.cardiff.ac.uk/id/eprint/184286

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