Analysis reveals that genomic complexity significantly predicts poorer outcomes in CLL, indicating the need for further validation of biomarkers and therapies.
High genomic complexity is linked to poor prognosis in chronic lymphocytic leukaemia (CLL), but its independent prognostic value remains uncertain amid emerging biomarkers. We analysed copy number alterations (CNA) in 495 treatment-naïve patients from three randomized trials (CLL4, ADMIRE, ARCTIC), incorporating IGHV status, telomere length (TL), targeted sequencing, and DNA-methylation subtypes. Patients harboured low (LGC, 0-2 CNAs; n=334), intermediate (IGC, 3-4 CNAs; n=97), or high (HGC, >5 CNAs; n=64) genomic complexity. U-CLL (81%, p<0.001) and short TL (61%, p<0.05) were enriched in HGC, and TL inversely correlated with CNA burden (τ=-0.147, p<0.001). 62% of HGC patients were n-CLL. TP53 dysfunction was associated with HGC (36%, p<0.001). Trisomy 12 and NOTCH1 mutations, were enriched in LGC (p<0.001). HGC predicted shorter progression-free and overall survival in all univariate models but only remained independently prognostic for OS only in CLL4 (HR=1.61, p=0.02). Of 64 HGC patients, 23 had TP53 dysfunction; 92% of TP53 wild-type cases had other high-risk features (TL-S, U-CLL, or n-CLL). HGC is associated with adverse outcomes but may reflect underlying biological risk rather than serve as an independent biomarker. Its interplay with telomere attrition, immunogenetics, and epigenetic subtype warrants further validation in targeted therapy-treated cohorts.
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Parker et al. (2025) studied this question.
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