Contributions
Abstract: S878
Type: Oral Presentation
Presentation during EHA23: On Saturday, June 16, 2018 from 16:30 - 16:45
Location: Room A7
Background
Myelodysplastic syndromes (MDS) are hematological disorders at high risk of progression to acute myeloid leukemia (sAML). Previous high-throughput sequencing studies have provided insight into the mutational dynamics and clonal evolution underlying disease progression. However, large longitudinal sequencing genomic studies are still required to define which mutations or combinations of them are important in disease progression.
Aims
To study the mutational profiles and mutational dynamics underlying progression from MDS to sAML.
Methods
A total of 846 samples of myeloid malignancies, divided in 3 cohorts, were examined: 1) a discovery cohort consisting of 94 serially collected samples from 47 MDS/CMML patients evolving to sAML that were studied two different time-points: at the time of diagnosis (disease presentation) and at sAML progression (disease evolution); 2) a control cohort consisting of 10 samples from 5 MDS/CMML patients who did not progress to sAML (median follow-up of 3 years); and 3) a validation cohort comprising 742 myeloid malignancies samples.
Sequencing studies were performed by a combination of whole-exome sequencing (WES) and targeted-deep sequencing (TDS). WES was carried out, as first screening, on 40 diagnosis/progression-matched samples of the discovery cohort, and driver mutations were identified, after variant calling by a standardized bioinformatics pipeline, by using the novel tool “Cancer Genome Interpreter”. Secondly, TDS was performed on these 40 samples of the initial discovery cohort, in order to validate WES results, and in additional 806 samples from all of the cohort (including 66 extra serial samples), using a custom MDS/AML-related capture enrichment panel (Illumina ®) of 117 genes.
Results
As a first result, all patients, progressing (discovery cohort) and not progressing (control cohort), presented similar number of mutations at diagnosis (p=0.15). However, patients who evolved to sAML displayed a statistically significant increase of mutations after progression (p=0.001) while control cohort did not during follow-up time (p= 0.88). Thus, this greater number of mutations at second sampling may be indicative of a higher genomic instability during disease evolution.
Then, to study the mutational dynamics during disease progression (discovery cohort), we compared the variant allele frequencies (VAFs) of mutations detected at both time-points in each patient. We identified 4 different clonal dynamics: mutations that were initially present but increased (type-1) such as STAG2 mutations; decreased (type-2); were newly acquired (type-3) such as NRAS/KRAS and FLT3 mutations; or persisted with similar allelic burden (type-4) at sAML stage, namely SRSF2, TET2 and DNMT3A mutations.
Interestingly, 13% of patients (6/47) included in this cohort showed co-occurrence of type-1 STAG2 and type-3 Ras signaling mutations indicating this mutational combination could play an important role during disease progression. To confirm this hypothesis, we searched this combination in all patients of the validation cohort and we found that was present in 8 patients, and 7 of them were MDS patients who finally progressed to sAML.
Conclusion
Progression from MDS to sAML could be explained by different mutational processes, as well as by the occurrence of unique and complex changes in the clonal architecture of the disease during the evolution. Co-occurrence of STAG2 and Ras signaling mutations could play an important role during disease progression.
Nº306242-NGS-PTL; FEHH 2015-2016 (MA); GRS 1349/A/16; GRS 1179/A/15.
Session topic: 9. Myelodysplastic syndromes – Biology & Translational Research
Keyword(s): MDS/AML, Myelodysplasia, Progression
Abstract: S878
Type: Oral Presentation
Presentation during EHA23: On Saturday, June 16, 2018 from 16:30 - 16:45
Location: Room A7
Background
Myelodysplastic syndromes (MDS) are hematological disorders at high risk of progression to acute myeloid leukemia (sAML). Previous high-throughput sequencing studies have provided insight into the mutational dynamics and clonal evolution underlying disease progression. However, large longitudinal sequencing genomic studies are still required to define which mutations or combinations of them are important in disease progression.
Aims
To study the mutational profiles and mutational dynamics underlying progression from MDS to sAML.
Methods
A total of 846 samples of myeloid malignancies, divided in 3 cohorts, were examined: 1) a discovery cohort consisting of 94 serially collected samples from 47 MDS/CMML patients evolving to sAML that were studied two different time-points: at the time of diagnosis (disease presentation) and at sAML progression (disease evolution); 2) a control cohort consisting of 10 samples from 5 MDS/CMML patients who did not progress to sAML (median follow-up of 3 years); and 3) a validation cohort comprising 742 myeloid malignancies samples.
Sequencing studies were performed by a combination of whole-exome sequencing (WES) and targeted-deep sequencing (TDS). WES was carried out, as first screening, on 40 diagnosis/progression-matched samples of the discovery cohort, and driver mutations were identified, after variant calling by a standardized bioinformatics pipeline, by using the novel tool “Cancer Genome Interpreter”. Secondly, TDS was performed on these 40 samples of the initial discovery cohort, in order to validate WES results, and in additional 806 samples from all of the cohort (including 66 extra serial samples), using a custom MDS/AML-related capture enrichment panel (Illumina ®) of 117 genes.
Results
As a first result, all patients, progressing (discovery cohort) and not progressing (control cohort), presented similar number of mutations at diagnosis (p=0.15). However, patients who evolved to sAML displayed a statistically significant increase of mutations after progression (p=0.001) while control cohort did not during follow-up time (p= 0.88). Thus, this greater number of mutations at second sampling may be indicative of a higher genomic instability during disease evolution.
Then, to study the mutational dynamics during disease progression (discovery cohort), we compared the variant allele frequencies (VAFs) of mutations detected at both time-points in each patient. We identified 4 different clonal dynamics: mutations that were initially present but increased (type-1) such as STAG2 mutations; decreased (type-2); were newly acquired (type-3) such as NRAS/KRAS and FLT3 mutations; or persisted with similar allelic burden (type-4) at sAML stage, namely SRSF2, TET2 and DNMT3A mutations.
Interestingly, 13% of patients (6/47) included in this cohort showed co-occurrence of type-1 STAG2 and type-3 Ras signaling mutations indicating this mutational combination could play an important role during disease progression. To confirm this hypothesis, we searched this combination in all patients of the validation cohort and we found that was present in 8 patients, and 7 of them were MDS patients who finally progressed to sAML.
Conclusion
Progression from MDS to sAML could be explained by different mutational processes, as well as by the occurrence of unique and complex changes in the clonal architecture of the disease during the evolution. Co-occurrence of STAG2 and Ras signaling mutations could play an important role during disease progression.
Nº306242-NGS-PTL; FEHH 2015-2016 (MA); GRS 1349/A/16; GRS 1179/A/15.
Session topic: 9. Myelodysplastic syndromes – Biology & Translational Research
Keyword(s): MDS/AML, Myelodysplasia, Progression