The clinical implication and prognostic impact of dynamic genetic evolution in myelodysplastic syndrome

Introduction Myelodysplastic syndrome (MDS) is a heterogeneous group of clonal bone marrow (BM) disorders. It is characterized by ineffective hematopoiesis leading to BM failure and a high risk of progression to acute leukemia. The classification of MDS is according to either the French-American-British Cooperative Group Criteria developed in 1982 or the World Health Organization criteria in 2001, 2008, and 2016. Several prognostic markers, including the age, BM blast percentage, hemoglobin level, white blood cell and platelet counts, and cytogenetics, have been proposed. The International prognostic scoring (IPSS) and revised international prognostic scoring system (IPSS-R) both have great predictive values for probability of leukemia transformation and overall survival. However, there are still some patients with similar IPSS or IPSS-R scores but with discrete prognosis. Recently, many gene mutations have been detected in MDS patients and some of them have prognostic implications. The myeloid research team at the National Taiwan University Hospital (NTUH) has found that integration of monosomal karyotype to IPSS-R can better risk-stratify MDS patients into different groups. Besides, several gene mutations detected at diagnosis by Sanger sequencing have been found to correlate well with clinical and biological features and be either stable or unstable during clinical evolution. However comprehensive mutation analysis of a large-cohort of MDS patients by next generation sequencing in serial studies are still lacking. Specific aims The aims of this study were to investigate the dynamic clonal architecture by mutation analyses of paired samples obtained at diagnosis and subsequent disease progression during follow-ups using targeted next generation sequencing. Furthermore, we speculated if the evolution profile has any prognostic impact. Methods Totally, 150 de novo MDS patients diagnosed according to the 2016 WHO classification at the NTUH were recruited in this study. Among them, 70 patients had disease progression: 23 patients progressed to high risk MDS and 47 progressed to AML. The DNA extracted from BM mononuclear cells was amplified by polymerase chain reaction and then analyzed by targeted next generation sequencing for gene mutations. The mutation patterns obtained at diagnosis and disease progression from the same patient were compared. The findings were correlated with clinical features, treatment response, and clinical outcome. Result For clinical characteristics, such as laboratory data at diagnosis or cytogenetic risk stratification base on IPSS, patients with or without disease progression were comparable. The most prevalent gene mutations at both diagnosis and progression were similar, including ASXL1 (34.3% and 35.7%, at diagnosis and at progression, respectively), RUNX1 (22.9% and 27.1%), SRSF2 (18.6% and 18.6%), U2AF1 (18.6% and 20.0%), STAG2 (15.7% and 17.1%), and DNMT3A mutations (15.7% and 12.9%). The most common acquisition of genetic evolution was the one involving chromosome 8 (16.1%), followed by NRAS (15.8%), and RUNX1 mutations (14.0%). Among the 70 patients with disease progression, 48 (68.6%) patients had genetic evolution: 15 (21.4%) patients had only cytogenetic evolution, 18 (25.7%) had only mutation shift, and 15 (21.4%) had both cytogenetic evolution and mutation shift. The patients with disease progression had a higher frequency of mutation shift (either acquisition or loss) than those with stable disease (47.1% vs. 30.0%, P=0.043). The gene mutation numbers had no association with the disease status at diagnosis, but at progression, patients with acute myeloid leukemia (AML) had more gene mutation numbers than those with high risk MDS. Progression to AML rather than to high risk MDS, and presence of cytogenetic evolution or genetic evolution predicted poorer overall survival (OS) after progression, irrespective of the original disease status. Intriguingly, patients with cohesin mutations acquired at progression had a significant better OS than those with the mutations at diagnosis. The patients with genetic evolution did not benefit from hematopoietic stem cell transplantation. We used SciClone to analyze the clonal architecture of gene mutations at diagnosis and at disease progression, and identified two clusters of gene mutations. Cluster 1 gene mutations [DNMT3A, NRAS, RUNX1, WT1, IDH2, splicing factors (including SRSF2, SF3B1, and U2AF1), and TET2 mutations] tended to have increasing VAF or be acquired at progression. On the other hand, cluster 2 gene mutations (ASXL1, SETBP1, STAG2, BCOR, and TP53 mutations) tended to be stationary, decreasing, or lost at disease progression. At diagnosis, the cluster 1 gene mutations were significantly more prevalent in secondary AML but the cluster 2 gene mutations were more likely to present in high risk MDS status. Two cluster 2 gene mutations, TP53 and SETBP1, were associated with very poor and poor-risk cytogenetics. We risk-stratified patients into three groups at diagnosis: the group 1 patients with cluster 1 ± cluster 2 gene mutations, the group 2 patients with only cluster 2 gene mutations, and the group 3 patients with neither cluster 1 nor cluster 2 gene mutations. The group 1 patients had significantly more good-risk cytogenetics; on the contrary, the group 2 patients harbored significantly more very poor-risk cytogenetics. For OS, the group 3 patients had the longest OS, followed by the group 1 and group 2 patients. Conclusion In conclusion, more than half of MDS patients experienced genetic evolution during disease progression and the presence of the genetic evolution had poor prognostic impact, not remediated by HSCT. It is necessary to develop new treatment strategy, such as target or immunotherapy, for patients with genetic evolution.