Background Sex is a major source of diversity among patients and a sex-informed approach is becoming a new paradigm in precision medicine.We aimed to describe sex diversity in myelodysplastic syndromes in terms of disease genotype, phenotype, and clinical outcome.Moreover, we sought to incorporate sex information into the clinical decision-making process as a fundamental component of patient individuality. MethodsIn this multicentre, observational cohort study, we retrospectively analysed 13 284 patients aged 18 years or older with a diagnosis of myelodysplastic syndrome according to 2016 WHO criteria included in the EuroMDS network (n=2025), International Working Group for Prognosis in MDS (IWG-PM; n=2387), the Spanish Group of Myelodysplastic Syndromes registry (GESMD; n=7687), or the Düsseldorf MDS registry (n=1185).Recruitment periods for these cohorts were between 1990 and 2016.The correlation between sex and genomic features was analysed in the EuroMDS cohort and validated in the IWG-PM cohort.The effect of sex on clinical outcome, with overall survival as the main endpoint, was analysed in the EuroMDS population and validated in the other three cohorts.Finally, novel prognostic models incorporating sex and genomic information were built and validated, and compared to the widely used revised International Prognostic Scoring System (IPSS-R).This study is registered with ClinicalTrials.gov,NCT04889729.Findings The study included 7792 (58•7%) men and 5492 (41•3%) women.10 906 (82•1%) patients were White, and race was not reported for 2378 (17•9%) patients.Sex biases were observed at the single-gene level with mutations in seven genes enriched in men (ASXL1, SRSF2, and ZRSR2 p<0•0001 in both cohorts; DDX41 not available in the EuroMDS cohort vs p=0•0062 in the IWG-PM cohort; IDH2 p<0•0001 in EuroMDS vs p=0•042 in IWG-PM; TET2 p=0•031 vs p=0•035; U2AF1 p=0•033 vs p<0•0001) and mutations in two genes were enriched in women (DNMT3A p<0•0001 in EuroMDS vs p=0•011 in IWG-PM; TP53 p=0•030 vs p=0•037).Additionally, sex biases were observed in co-mutational pathways of founding genomic lesions (splicing-related genes, predominantly in men, p<0•0001 in both the EuroMDS and IWG-PM cohorts), in DNA methylation (predominantly in men, p=0•046 in EuroMDS vs p<0•0001 in IWG-PM), and TP53 mutational pathways (predominantly in women, p=0•0073 in EuroMDS vs p<0•0001 in IWG-PM).In the retrospective EuroMDS cohort, men had worse median overall survival (81•3 months, 95% CI 70•4-95•0 in men vs 123•5 months, 104•5-127•5 in women; hazard ratio [HR] 1•40, 95% CI 1•26-1•52; p<0•0001).This result was confirmed in the prospective validation cohorts (median overall survival was 54•7 months, 95% CI 52•4-59•1 in men vs 74•4 months, 69•3-81•2 in women; HR 1•30, 95% CI 1•23-1•35; p<0•0001 in the GEMSD MDS registry; 40•0 months, 95% CI 33•4-43•7 in men vs 54•2 months, 38•6-63•8 in women; HR 1•23, 95% CI 1•08-1•36; p<0•0001 in the Dusseldorf MDS registry).We developed new personalised prognostic tools that included sex information (the sex-informed prognostic scoring system and the sex-informed genomic scoring system).Sex maintained independent prognostic power in all prognostic systems; the highest performance was observed in the model that included both sex and genomic information.A five-to-five mapping between the IPSS-R and new score categories resulted in the re-stratification of 871 (43•0%) of 2025 patients from the EuroMDS cohort and 1003 (42•0%) of 2387 patients from the IWG-PM cohort by using the sex-informed prognostic scoring system, and of 1134 (56•0%) patients from the EuroMDS cohort and 1265 (53•0%) patients from the IWG-PM cohort by using the sex-informed genomic scoring system.We created a web portal that enables outcome predictions based on a sexinformed personalised approach.Interpretation Our results suggest that a sex-informed approach can improve the personalised decision making process in patients with myelodysplastic syndromes and should be considered in the design of clinical trials including low-risk patients.
Chronic myeloid leukemia (CML) is characterized by the constitutive tyrosine kinase activity of the oncoprotein BCR-ABL1 in myeloid progenitor cells that activates multiple signal transduction pathways leading to the leukemic phenotype. The tyrosine-kinase inhibitor (TKI) nilotinib inhibits the tyrosine kinase activity of BCR-ABL1 in CML patients. Despite the success of nilotinib treatment in patients with chronic-phase (CP) CML, a population of Philadelphia-positive (Ph+) quiescent stem cells escapes the drug activity and can lead to drug resistance. The molecular mechanism by which these quiescent cells remain insensitive is poorly understood. The aim of this study was to compare the gene expression profiling (GEP) of bone marrow (BM) CD34+/lin- cells from CP-CML patients at diagnosis and after 12 months of nilotinib treatment by microarray, in order to identify gene expression changes and the dysregulation of pathways due to nilotinib action. We selected BM CD34+/lin- cells from 78 CP-CML patients at diagnosis and after 12 months of first-line nilotinib therapy and microarray analysis was performed. GEP bioinformatic analyses identified 2,959 differently expressed probes and functional clustering determined some significantly enriched pathways between diagnosis and 12 months of nilotinib treatment. Among these pathways, we observed the under expression of 26 genes encoding proteins belonging to the cell cycle after 12 months of nilotinib treatment which led to the up-regulation of chromosome replication, cell proliferation, DNA replication, and DNA damage checkpoint at diagnosis. We demonstrated the under expression of the ATP-binding cassette (ABC) transporters ABCC4, ABCC5, and ABCD3 encoding proteins which pumped drugs out of the cells after 12 months of nilotinib. Moreover, GEP data demonstrated the deregulation of genes involved in the JAK-STAT signaling pathway. The down-regulation of JAK2, IL7, STAM, PIK3CA, PTPN11, RAF1, and SOS1 key genes after 12 months of nilotinib could demonstrate the up-regulation of cell cycle, proliferation and differentiation via MAPK and PI3K-AKT signaling pathways at diagnosis.
