Contributions
Abstract: PB2082
Type: Publication Only
Background
Somatic mutations are one of the major factors driving the pathogenesis of myelodysplastic syndromes (MDS) and are closely associated with clinical phenotype. The iron-chelator deferasirox (DFX) has been shown to induce hematologic response (HR) in about 10% of patients with MDS, with a yet unknown mechanism.
Aims
Our aim was to evaluate the role of somatic mutations in critical genes as predictors of hematologic response to DFX.
Methods
Sixty diagnostic bone marrow samples from 19 patients responsive and 41 resistant to DFX were tested in this study. Thirty genes known to be frequently mutated in haematological malignancies were screened for somatic mutations in 15 patients (7 responsive and 8 resistant) using NGS based on the commercial Myeloid Solution by SOPHiA GENETICS (SOPHiA GENETICS, Saint-Sulpice, Switzerland). The resulting captured libraries were further processed on a HiSeq® sequencing platform (Illumina, San Diego, California). Generated FASTQ sequencing files were then uploaded to SOPHiA DDM® platform (SOPHiA GENETICS, Saint-Sulpice, Switzerland). An additional cohort of 45 patients was screened for mutations in the hot-spot regions of spliceosome machinery enzymes (SF3B1, SRSF2, U2AF1) and epigenetic regulators (IDH1, IDH2 and DNMT3A), using Sanger sequencing.
Results
Using NGS, we identified 53 mutations with a variant allele frequency (VAF) ≥ 1%, with at least 1 mutation in 14 of 15 patients (93.3%). The median number of mutations per patient was 3.53 (range, 0-6). As reported in figure 1a, the most commonly mutated genes were: ASXL1 in 9 of 15 pts (60%) and RUNX1, DNMT3A, SF3B1 and TET2 in 4 of 15 pts (27%). In this analysis, none of the single gene was predictive of HR to Deferasirox treatment, while mutation frequency in general was lower in responders, as compared to resistant patients (mean 2.4 vs mean 4.5 mutations/patient, respectively; p=0.0232).
When extending the mutational screening to further 45 patients by Sanger sequencing, we identified SF3B1 as the most commonly mutated gene. Although the cumulative frequency of SF3B1 mutations in the entire cohort of patients (23/60 pts, 38.3%) appeared to be higher in resistant as compared to responsive patients (17/41, 41.5%, vs 6/19, 31.6%), the difference did not reach statistical significance.
Conclusion
Our preliminary data show that mutational screening performed by NGS of lower-risk MDS may have a role in predicting hematologic response to Deferasirox treatment, whereas the sole presence of SF3B1 mutations is not associated to hematologic response.
Session topic: 9. Myelodysplastic syndromes – Biology & Translational Research
Keyword(s): iron chelation, MDS, mutation analysis
Abstract: PB2082
Type: Publication Only
Background
Somatic mutations are one of the major factors driving the pathogenesis of myelodysplastic syndromes (MDS) and are closely associated with clinical phenotype. The iron-chelator deferasirox (DFX) has been shown to induce hematologic response (HR) in about 10% of patients with MDS, with a yet unknown mechanism.
Aims
Our aim was to evaluate the role of somatic mutations in critical genes as predictors of hematologic response to DFX.
Methods
Sixty diagnostic bone marrow samples from 19 patients responsive and 41 resistant to DFX were tested in this study. Thirty genes known to be frequently mutated in haematological malignancies were screened for somatic mutations in 15 patients (7 responsive and 8 resistant) using NGS based on the commercial Myeloid Solution by SOPHiA GENETICS (SOPHiA GENETICS, Saint-Sulpice, Switzerland). The resulting captured libraries were further processed on a HiSeq® sequencing platform (Illumina, San Diego, California). Generated FASTQ sequencing files were then uploaded to SOPHiA DDM® platform (SOPHiA GENETICS, Saint-Sulpice, Switzerland). An additional cohort of 45 patients was screened for mutations in the hot-spot regions of spliceosome machinery enzymes (SF3B1, SRSF2, U2AF1) and epigenetic regulators (IDH1, IDH2 and DNMT3A), using Sanger sequencing.
Results
Using NGS, we identified 53 mutations with a variant allele frequency (VAF) ≥ 1%, with at least 1 mutation in 14 of 15 patients (93.3%). The median number of mutations per patient was 3.53 (range, 0-6). As reported in figure 1a, the most commonly mutated genes were: ASXL1 in 9 of 15 pts (60%) and RUNX1, DNMT3A, SF3B1 and TET2 in 4 of 15 pts (27%). In this analysis, none of the single gene was predictive of HR to Deferasirox treatment, while mutation frequency in general was lower in responders, as compared to resistant patients (mean 2.4 vs mean 4.5 mutations/patient, respectively; p=0.0232).
When extending the mutational screening to further 45 patients by Sanger sequencing, we identified SF3B1 as the most commonly mutated gene. Although the cumulative frequency of SF3B1 mutations in the entire cohort of patients (23/60 pts, 38.3%) appeared to be higher in resistant as compared to responsive patients (17/41, 41.5%, vs 6/19, 31.6%), the difference did not reach statistical significance.
Conclusion
Our preliminary data show that mutational screening performed by NGS of lower-risk MDS may have a role in predicting hematologic response to Deferasirox treatment, whereas the sole presence of SF3B1 mutations is not associated to hematologic response.
Session topic: 9. Myelodysplastic syndromes – Biology & Translational Research
Keyword(s): iron chelation, MDS, mutation analysis