The prognostic value of circulating myeloblasts in patients with myelodysplastic syndromes

IDH2 regulates U2AF1 expression and hydroxymethylation in MDS patients

The expression of some genes regulated by their DNA methylation is involved in pathogenesis and disease progression of myelodysplastic syndrome (MDS), which is characterised by abnormal differentiation and development of myeloid cells. Therefore, it is significant for us to work on investigating what factors regulate U2AF1 expression and hydroxymethylation in MDS patients. However, the members of TET protein family can change 5-methylcytosine (5mC) into 5-hydroxymethylcytosine5-methyl cytosine (5hmC). In general, 5mC and 5hmC levels maintain dynamic equilibrium, and their imbalance is associated with the onset and progression of some tumors. In this study, the expression and 5mC and 5hmC levels of U2AF1 gene decreased significantly after the treatment by decitabine in Mutz-1 cells. The decreased degree of 5hmC is far greater than that of 5mC. IDH2 expression decreased significantly followed by U2AF1 5hmC levels. However, the expression of other hydroxymethylation-related genes such as IDH1, TET1 and TET2 also decreased, but the difference did not achieve significance. Compared with IDH2 or U2AF1 wild-type MDS patients, U2AF1 expression and 5hmC level in patients with these two gene mutations were both significantly reduced.

Navigating Myelodysplastic and Myelodysplastic/Myeloproliferative Overlap Syndromes

Myelodysplastic syndromes (MDS) and MDS/myeloproliferative neoplasms (MPNs) are clonal diseases that differ in morphologic diagnostic criteria but share some common disease phenotypes that include cytopenias, propensity to acute myeloid leukemia evolution, and a substantially shortened patient survival. MDS/MPNs share many clinical and molecular features with MDS, including frequent mutations involving epigenetic modifier and/or spliceosome genes. Although the current 2016 World Health Organization classification incorporates some genetic features in its diagnostic criteria for MDS and MDS/MPNs, recent accumulation of data has underscored the importance of the mutation profiles on both disease classification and prognosis. Machine-learning algorithms have identified distinct molecular genetic signatures that help refine prognosis and notable associations of these genetic signatures with morphologic and clinical features. Combined geno-clinical models that incorporate mutation data seem to surpass the current prognostic schemes. Future MDS classification and prognostication schema will be based on the portfolio of genetic aberrations and traditional features, such as blast count and clinical factors. Arriving at these systems will require studies on large patient cohorts that incorporate advanced computational analysis. The current treatment algorithm in MDS is based on patient risk as derived from existing prognostic and disease classes. Luspatercept is newly approved for patients with MDS and ring sideroblasts who are transfusion dependent after erythropoietic-stimulating agent failure. Other agents that address red blood cell transfusion dependence in patients with lower-risk MDS and the failure of hypomethylating agents in higher-risk disease are in advanced testing. Finally, a plethora of novel targeted agents and immune checkpoint inhibitors are being evaluated in combination with a hypomethylating agent backbone to augment the depth and duration of response and, we hope, improve overall survival.

Comorbidity Networks in Cardiovascular Diseases

Background: Cardiovascular diseases are the leading causes of mortality worldwide. One reason behind this lethality lies in the fact that often cardiovascular illnesses develop into systemic failure due to the multiple connections to organismal metabolism. This in turn is associated with co-morbidities and multimorbidity. The prevalence of coexisting diseases and the relationship between the molecular origins adds to the complexity of the management of cardiovascular diseases and thus requires a profound knowledge of the genetic interaction of diseases. Objective: In order to develop a deeper understanding of this phenomenon, we examined the patterns of comorbidity as well as their genetic interaction of the diseases (or the lack of evidence of it) in a large set of cases diagnosed with cardiovascular conditions at the national reference hospital for cardiovascular diseases in Mexico. Methods: We performed a cross-sectional study of the National Institute of Cardiology. Socioeconomic information, principal diagnosis that led to the hospitalization and other conditions identified by an ICD-10 code were obtained for 34,099 discharged cases. With this information a cardiovascular comorbidity networks were built both for the full database and for ten 10-years age brackets. The associated cardiovascular comorbidities modules were found. Data mining was performed in the comprehensive ClinVar database with the disease names (as extracted from ICD-10 codes) to establish (when possible) connections between the genetic associations of the genetic interaction of diseases. The rationale is that some comorbidities may have a stronger genetic origin, whereas for others, the environment and other factors may be stronger. Results: We found that comorbidity networks are highly centralized in prevalent diseases, such as cardiac arrhythmias, heart failure, chronic kidney disease, hypertension, and ischemic diseases. Said comorbidity networks are actually modular on their connectivity. Modules recapitulate physiopathological commonalities, e.g., ischemic diseases clustering together. This is also the case of chronic systemic diseases, of congenital malformations and others. The genetic and environmental commonalities behind some of the relations in these modules were also found by resorting to clinical genetics databases and functional pathway enrichment studies. Conclusions: This methodology, hence may allow the clinician to look up for non-evident comorbidities whose knowledge will lead to improve therapeutically designs. By continued and consistent analysis of these types of patterns, we envisaged that it may be possible to acquire, strong clinical and basic insights that may further our advance toward a better understanding of cardiovascular diseases as a whole. Hopefully these may in turn lead to further development of better, integrated therapeutic strategies.

Gender disparity in the survival of patients with primary myelodysplastic syndrome

Several prognostic scoring systems have been developed to assess prognosis in myelodysplastic syndrome (MDS). However, currently there are no systems that list gender as a prognostic factor. We queried a National Cancer Institute database to investigate the prognostic influence of gender on the survival of patients with MDS. We first identified 34,681 qualified patients diagnosed with MDS from 2001-2014 in the Surveillance, Epidemiology, and End Results (SEER) database, and then analyzed the characteristics of these patients using chi-squared tests. The Kaplan-Meier method and the multivariate Cox regression model were used to examine whether gender disparity in the survival of patients with MDS existed. We found that male patients had higher incidence rate of MDS (55.3% vs 44.7%, P<0.001) and a significant survival disadvantage (27.6% vs 33.6%, P<0.001) compared to female patients. Moreover, the less favorable survival rate of male MDS patients was associated with the age at diagnosis, race, marital status at diagnosis and the histological subtypes including refractory anemia (RA), refractory cytopenia with multilineage dysplasia (RCMD), myelodysplastic associated with isolated del 5q (MDS 5q-), myelodysplastic/myeloproliferative neoplasm (MDS/MPN) and not otherwise specified (NOS). In conclusion, gender can be considered as an independent prognostic factor for the overall survival of patients with MDS.

A novel complete blood count-based score to screen for myelodysplastic syndrome in cytopenic patients

The diagnosis of myelodysplastic syndromes (MDS) is often challenging, time- and resource-consuming. A thorough analysis of complete blood count (CBC) parameters could, however, help to screen for MDS among other causes of cytopenia. To test this hypothesis, 109 newly-diagnosed MDS patients and 399 cytopenic patients older than 50 years with confirmed absence of MDS were enrolled in a prospective study. Multiparametric analysis highlighted three CBC parameters that were significantly different between the two cohorts: mean corpuscular volume, absolute neutrophil count and median neutrophil complexity and width of dispersion of the events measured (Ne-WX), which were used to define an MDS-CBC score. This score enables the prediction of MDS with 86% sensitivity and 88% specificity. The MDS-CBC score excluded MDS in 89% of cytopenic controls. Moreover, high score values at MDS diagnosis significantly correlated with decreased event-free (P = 0·02) and overall survival (P = 0·01). The power of this score was confirmed in an independent validation cohort (MDS n = 34, cytopenic controls n = 28). The MDS-CBC score is an easy and fast tool to exclude or suspect MDS in unselected patients with cytopenia of unknown reasons at the time of analysis, by prompting blood smear examination. It may thus improve allocation of further MDS-specific work-up in patients with cytopenia at the time of CBC assessment.