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Evaluation of SF3B1 Mutation Screening by High-Resolution Melting Analysis and its Clinical Utility for Myelodysplastic Syndrome with Ring Sideroblasts at the Point of Diagnosis.
Laboratory Medicine 2018 December 27
Background: SF3B1 (splicing factor 3B subunit-1) somatic mutation is specifically detected in myelodysplastic syndrome (MDS) with ring sideroblasts (MDS-RS). We investigated the sensitivity and utility of SF3B1 mutation analysis as a clinical laboratory test.
Method: Detection limit for SF3B1 mutations by high-resolution melting (HRM) analysis was investigated by plasmid mixture. In 67 MDS patients, we examined the association between SF3B1 mutation and prognostic evaluation using the Revised International Prognostic Scoring System and revalidated MDS classifications based on the revised 4th edition of the WHO classification.
Results: HRM analysis enabled mutation detection in the 12.5% SF3B1 mutant alleles. SF3B1 mutation was detected in 9 cases, mostly in the low-risk group. Cases of MDS with ring sideroblasts unrelated to SF3B1 mutation were detected in the high-risk group. Two cases were reclassified as MDS-RS after detecting SF3B1 mutation.
Conclusions: SF3B1 mutation analysis as an initial screening at diagnosis increases the accuracy of prognostic prediction and disease classification.
Method: Detection limit for SF3B1 mutations by high-resolution melting (HRM) analysis was investigated by plasmid mixture. In 67 MDS patients, we examined the association between SF3B1 mutation and prognostic evaluation using the Revised International Prognostic Scoring System and revalidated MDS classifications based on the revised 4th edition of the WHO classification.
Results: HRM analysis enabled mutation detection in the 12.5% SF3B1 mutant alleles. SF3B1 mutation was detected in 9 cases, mostly in the low-risk group. Cases of MDS with ring sideroblasts unrelated to SF3B1 mutation were detected in the high-risk group. Two cases were reclassified as MDS-RS after detecting SF3B1 mutation.
Conclusions: SF3B1 mutation analysis as an initial screening at diagnosis increases the accuracy of prognostic prediction and disease classification.
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