Background:Mutations in cohesin complex genes have been described commonly in several types of cancer, with an incidence of 8% in myeloid diseases and myelodysplastic syndromes (MDS), and have been linked to marrow fibrosis by our group in a prior publication (Ramos F et al. Oncotarget 2016). However, their clinical impact is still undetermined.Aims:To identify mutations in cohesin complex genes in MDS patients by next generation sequencing (NGS) and to analyze their implications at clinical level (correlation with clinical characteristics and outcome).Methods:A cohort of 850 myeloid samples was analyzed by targeted deep sequencing (Nextera Rapid Capture Custom Enrichment) using an Illumina ® custom panel of 117 myeloid‐related genes, including cohesin complex genes: STAG1, STAG2, SMC1A, SMC3 and RAD21. A final selection of 324 patients with clinical, biological and follow‐up data were selected.Results:The median age was 75 years (p10‐p90: 57–84); 59% were male. According to the WHO 2008 classification most of the patients had RCMD (40%), and RAEB 1–2 (30%), while 11% had a MDS associated with isolated del(5q), and the remaining subtypes RCUD, RARS, U‐MDS were observed in less than 10% each. Regarding IPSS‐R, the majority of patients had very low (27%) and low (44%) risk, with 85% of the series having normal karyotype or clonal alterations of very good or good risk. The median follow‐up was 2.5 years (range 0.01–15.6) and during this time 50% of patients died and 30% progressed to acute myeloid leukemia (AML).NGS study identified a 9.3% of patients with mutations in cohesin complex genes: STAG2 (6.5%), SMC3 (1.5%) and SMC1A (1.2%). In the global cohort, mutations in cohesin genes were associated with RAEB‐1 and RAEB‐2 subtypes (p = 0.003), intermediate IPSS‐R (p = 0.010), intermediate cytogenetic risk (p = 0.026) and a lower platelet count (p = 0.004). In addition, cohesin‐mutated patients showed a shorter overall survival (3 vs. 5 years, p = 0.06). Moreover, mutations in these genes were associated with a higher rate of progression to AML (p = 0.004) and a shorter time to AML progression (1.5 vs. 9.1 years, p < 0.001).To further study the negative impact of these mutations, analyses were carried out for each IPSS‐R groups, separately. Interestingly, in low IPSS‐R patients, these analyses showed that cohesin mutations were the sole factor significantly associated with an earlier progression to AML (p < 0.001), while hemoglobin, platelet and neutrophil count, blasts in bone marrow and cytogenetic were not related to the outcome (Table 1). In addition, in the multivariate analysis, the presence of cohesin mutations was associated with a shorter overall survival in this subgroup of patients (HR = 0.291 (95% CI, 0.113–0.752); p = 0.011) (Table 2).Summary/Conclusion:Mutations in cohesin complex genes (mainly STAG2) are associated with a worse prognosis due to a higher rate of AML evolution and a shorter time to progression to AML in the global cohort. Of note, mutations in the cohesin complex were associated with a potential prognostic impact in low risk IPSS‐R subgroup. Therefore, analysis of these mutations, especially in this subgroup of patients, should be carried out.image
Myelodysplastic syndromes (MDS) and chronic myelomonocytic leukemia (CMML) 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 serial sequencing studies are still required to define which type of mutations alone or in combination contribute to leukemic transformation. To assess the mutational profiles and mutational dynamics underlying progression from MDS to sAML, a targeted-deep sequencing (TDS) of 117 MDS/AML related-genes was performed in 110 bone marrow serial samples from 50 MDS/CMML patients who evolved to sAML and 5 patients who did not evolved (controls), at two different time-points: at the time of diagnosis and at sAML progression or after a median of 3 year follow-up, respectively. A total of 269 mutations in 57 different genes were identified at second sampling. At diagnosis, all patients, progressing and not progressing (controls), presented similar number of mutations (p=0.15). Moreover, patients evolving to sAML were then divided by FAB/WHO subtypes at diagnosis (CMML, low-risk and high-risk MDS subgroups) and no differences were observed in the number of mutations (p=0.71) and variant allele frequency (VAF) between each group (p=0.63). It should be noted that mutations in the splicing pathway were significantly more frequent in low-risk MDS patients (89% low-risk MDS vs. 56% high risk MDS, p=0.038). However, after progression, those patients who evolved to sAML displayed a statistically significant increase of mutations (p=0.001) at the leukemic phase, while controls did not at the follow-up sample (p=0.88). This higher number of mutations at second sampling in patients who evolved to sAML, independently of their diagnostic subtype, may be indicative of a higher genomic instability during disease evolution. To study the mutational dynamics and what mutations could be important during disease evolution, the VAFs of mutations detected at both time-points in each patient of transformation cohort were compared. We observed that some mutations identified at the sAML stage (163 mutations) were already present at the MDS stage, at clonal or subclonal levels, and were retained during evolution, for example in genes such as SRSF2 and DNMT3A. However, 106 mutations increased in clonal size or were newly acquired. Interestingly, most of mutations in Ras signaling pathway showed a same pattern: they were not present at time of diagnosis and appeared at sAML. In fact, mutations in this pathway were detected in 25 of 50 patients (50%) included in this cohort and in 22 of them (88%) mutations displayed this dynamic. Therefore, in this study, Ras signaling was the most common pathway involved in the progression from MDS to sAML. Of note, 9 of these patients (18% of the whole cohort) presented, independently of diagnosis, a co-occurring cohesin mutation, that was already present at diagnosis and, in most cases, markedly increased in clonal size at sAML. Thus, the combination of mutations in these two pathways could play an important role during disease evolution. In addition, 22 of 50 patients were treated with a disease-modifying agent (18 azacytidine and 4 lenalidomide) before they progressed to sAML, while the remaining 28 patients received no treatment or supportive care and were considered as non-treated. Thus, we studied the effect of disease-modifying therapy on mutational dynamics in this cohort of patients progressing to sAML. In the treated patients, a higher proportion of newly acquired or increasing mutations at sAML in chromatin modifiers was observed, while in non-treated patients most mutations remained stable (61% vs. 28.6%, p=0.013). By contrast, regarding treatment, no differences were detected in the mutational dynamics of cohesin (p=0.56) or Ras pathway (p=1.00). MDS progression to sAML was characterized by a higher genomic instability, independently of MDS subtypes of patients at diagnosis. Ras signaling was the most frequent affected pathway during disease evolution in this cohort and, interestingly, the co-occurrence of Ras signaling and cohesin mutations could play an important role in the progression. Moreover, mutations in chromatin modifiers genes could be related to the evolution of patients who received disease-modifying treatment before progression to sAML. Disclosures Olivier: Celgene: Honoraria; Jassen: Honoraria. Díez-Campelo:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.