Splicing factor 3B subunit 1A (SF3B1) mutations in lymphoid malignancies.

e23315 Background: Advancements in genetic profiling are paving the way to personalized medicine by identification of mutations across all tumor types, helping optimize therapeutic outcomes. Splicing Factor 3B subunit 1A (SF3B1), plays a significant role in preventing aberrant splicing that can lead to a distinct subtype of Myelodysplastic syndrome (MDS). While its role is partially explored in Chronic Lymphocytic Leukemia (CLL) and certain solid tumors, it remains unknown in lymphoma. Methods: We conducted a retrospective analysis using AACR GENIE v17.0 from cBioPortal, selecting patients with Chronic lymphocytic leukemia and lymphoma by their subtypes. The analysis was limited to a single distinct sample per patient to avoid duplication. The study assessed the frequency and characteristics of SF3B1 mutations in this group. Results: A preliminary analysis identified 6,767 patients and 8,816 samples. Among these, 5,104 consisted of one sample per patient, which were analyzed to determine the prevalence of the SF3B1 mutation. 3.57 % (n = 182/5104) samples harbored somatic SF3B1 mutation. 202 mutations were identified in these samples of which 134 were driver mutations and 68 were Variants of Unknown Significance (VUS). All driver mutations and 57/68 of VUS were missense mutations. The rest of the VUS were inframe (4), splice (5) and fusion (2) mutations. Sub categorization by tumor type showed mutation in 5.26% of Non-Hodgkin Lymphoma (NHL), 4.5% of Mature B cell neoplasm, 1.51% of mature T and NK cell neoplasm, 1.35% Hodgkin lymphoma, < 1% in T and B lymphoblastic leukemia/lymphoma. Conclusions: This study highlights significant prevalence of driver SF3B1 mutations outside of its traditionally recognized association with myeloid neoplasms. It has been partially explored in CLL, where it may contribute to poor outcomes. However, further research is needed to better understand its impact on survival and its potential as a therapeutic target in other lymphomas, such as NHL. A potential limitation of our study is that NGS-based tests typically use genomic DNA derived from bulk mononuclear cells, making it challenging to determine whether the sequenced cells belong to the myeloid or lymphoid lineage. Future studies should focus on analyzing SF3B1 mutations in sorted lymphocytic populations to provide greater clarity Reference: The AACR Project GENIE Consortium. AACR Project GENIE: Powering Precision Medicine Through An International Consortium, Cancer Discov. 2017 Aug;7(8):818-831 v 17.0-public. Neoplasm type SF3B1 mutation % Non-Hodgkin Lymphoma 5.26% Mature B cell neoplasm 4.50% Mature T and NK cell neoplasm 1.51% Hodgkin lymphoma 1.35% T and B lymphoblastic leukemia/lymphoma <1%

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Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.e23315
Primary Topic
RNA Research and Splicing
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article
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article

Splicing factor 3B subunit 1A (SF3B1) mutations in lymphoid malignancies.

Judy Grover, Aditi Arora, Akriti Gupta Jain, Abhay Singh et al.
Journal of Clinical Oncology
RNA Research and Splicing
article

Splicing factor 3B subunit 1A (SF3B1) mutations in lymphoid malignancies.

Judy Grover, Aditi Arora, Akriti Gupta Jain, Abhay Singh, Sandra Mazzoni, Ying Ni, Kirti Arora, Rahul Chowdhary
article en

Abstract

e23315 Background: Advancements in genetic profiling are paving the way to personalized medicine by identification of mutations across all tumor types, helping optimize therapeutic outcomes. Splicing Factor 3B subunit 1A (SF3B1), plays a significant role in preventing aberrant splicing that can lead to a distinct subtype of Myelodysplastic syndrome (MDS). While its role is partially explored in Chronic Lymphocytic Leukemia (CLL) and certain solid tumors, it remains unknown in lymphoma. Methods: We conducted a retrospective analysis using AACR GENIE v17.0 from cBioPortal, selecting patients with Chronic lymphocytic leukemia and lymphoma by their subtypes. The analysis was limited to a single distinct sample per patient to avoid duplication. The study assessed the frequency and characteristics of SF3B1 mutations in this group. Results: A preliminary analysis identified 6,767 patients and 8,816 samples. Among these, 5,104 consisted of one sample per patient, which were analyzed to determine the prevalence of the SF3B1 mutation. 3.57 % (n = 182/5104) samples harbored somatic SF3B1 mutation. 202 mutations were identified in these samples of which 134 were driver mutations and 68 were Variants of Unknown Significance (VUS). All driver mutations and 57/68 of VUS were missense mutations. The rest of the VUS were inframe (4), splice (5) and fusion (2) mutations. Sub categorization by tumor type showed mutation in 5.26% of Non-Hodgkin Lymphoma (NHL), 4.5% of Mature B cell neoplasm, 1.51% of mature T and NK cell neoplasm, 1.35% Hodgkin lymphoma, < 1% in T and B lymphoblastic leukemia/lymphoma. Conclusions: This study highlights significant prevalence of driver SF3B1 mutations outside of its traditionally recognized association with myeloid neoplasms. It has been partially explored in CLL, where it may contribute to poor outcomes. However, further research is needed to better understand its impact on survival and its potential as a therapeutic target in other lymphomas, such as NHL. A potential limitation of our study is that NGS-based tests typically use genomic DNA derived from bulk mononuclear cells, making it challenging to determine whether the sequenced cells belong to the myeloid or lymphoid lineage. Future studies should focus on analyzing SF3B1 mutations in sorted lymphocytic populations to provide greater clarity Reference: The AACR Project GENIE Consortium. AACR Project GENIE: Powering Precision Medicine Through An International Consortium, Cancer Discov. 2017 Aug;7(8):818-831 v 17.0-public. Neoplasm type SF3B1 mutation % Non-Hodgkin Lymphoma 5.26% Mature B cell neoplasm 4.50% Mature T and NK cell neoplasm 1.51% Hodgkin lymphoma 1.35% T and B lymphoblastic leukemia/lymphoma <1%

Journal of Clinical OncologyVol. 43(16_suppl)
Cleveland Clinic (US), Pandit Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences (IN), Kolkata Municipal Corporation (IN), Punjab Institute of Medical Sciences (IN), Cleveland Clinic Akron General (US)
Openalex Percentile: Top 89%
RNA Research and Splicing
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