Mutational Landscape and Clinical Impact of SPEN Mutations in Patients with Chronic Lymphocytic Leukemia
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background/Objectives: NOTCH1 is frequently mutated in chronic lymphocytic leukemia (CLL) and is a marker of poor prognosis. In addition to NOTCH1, mutations in the NOTCH1 regulatory pathway including SPEN have been described in a limited number of CLL cases and others have suggested that these mutations are also associated with adverse patient outcomes Methods: In this study, 1617 CLL cases were assessed using targeted sequencing and a 29-gene panel and the results were correlated with prognosis. Results: SPEN mutations were detected in 48 (2.9%) CLL patients: 92.4% were deleterious (frameshift or truncating nonsense mutations) and the remaining (7.6%) were missense. Compared with SPEN wild type CLL patients, SPEN mutated patients had a statistically higher frequency of IGHV unmutated status (79.5% vs. 57.8%, p = 0.004), CD38 positivity (73.3% vs. 52.4%, p = 0.01), ZAP70 positivity (77.3% vs. 58.3%, p = 0.01) and trisomy 12 (43.5% vs. 13.7%, p < 0.001). The most common gene mutations co-occurring with SPEN mutations were as follows: NOTCH1 (43.7%), TP53 (22.9%), BIRC3 (12.5%), SF3B1 (10.4%), XPO1 (8.3%), MUC2 (6.2%), ATM (4.2%), FBXW7 (4.2%), and BTK (4.2%). Patients with SPEN mutated CLL had a significantly shorter time-to-first treatment compared to CLL patients with wild type SPEN (2.5 vs. 4.07 years, p = 0.01). The finding of shorter time-to-first treatment in SPEN mutated CLL patients was not maintained in a multivariable analysis. IGHV unmutated status, TP53 disruption, and trisomy 12 remained independently predictive of a shorter time-to-first treatment in a multivariable analysis. Conclusions: These data show that SPEN mutations in CLL are associated with adverse prognostic impact and should be included in sequencing assays performed for the prognostic workup of CLL patients.
Source: Cancers
Authors: Priyatharsini Nirmalanantham, Andrés E. Quesada, Anindita Ghosh, Pei Lin, Chi Y. Ok, Richard K. Yang, Hong Fang, Sofia Garces, Rashmi Kanagal-Shamanna, Sanam Loghavi, Mark J. Routbort, Cameron Cheng Yin, Wang Wei, Sarah Pasyar, Roland Bassett, Siba El Hussein, Nitin Jain, Jan Burger, William G. Wierda, Sa Wang, Carlos Bueso-Ramos, Keyur P. Patel, Leonard Jeffrey Medeiros, Fatima Zahra Jelloul
Language: English
Subfield: Genetics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,499
OpenAlex ID: W4415987251