Potential Diagnostic Value of Abnormal Pyroptosis Genes Expression in Myelodysplastic Syndromes (MDS): A Primary Observational Cohort Study

Myelodysplastic syndromes (MDS) are determined by ineffective hematopoiesis and bone marrow cytological dysplasia with somatic gene mutations and chromosomal abnormalities. Accumulating evidence has revealed the pivotal role of NLRP3 inflammasome activation and pyroptotic cell death in the pathogenesis of MDS. Although MDS can be diagnosed with a variety of morphologic and cytogenetic tests, most of these tests have limitations or problems in practice.

In the present study, we evaluated the expression of genes that form the inflammasome (NLRP3, ASC, and CASP1) in bone marrow specimens of MDS patients and compared the results with those of other leukemias to evaluate their diagnostic value for MDS.Primary samples of this observational cohort study were collected from aspiration samples of patients with myelodysplastic syndromes (27 cases) and patients with non-myelodysplastic syndrome hematological cancers (45 cases). After RNA extraction and c.DNA synthesis, candidate transcripts and housekeeping transcripts were measured by real-time PCR method (SYBER Green assay). Using Kruskal-Wallis the relative gene expressions were compared and differences with p value less than 0.05 were considered as significant. Discrimination capability, cut-off, and area under curve (AUC) of all markers were analyzed with recessive operation curve (ROC) analysis.

 We found that Caspase-1 and ASC genes expressed at more levels in MDS specimens compared to non-MDS hematological malignancies. A relative average expression of 10.22 with a p-value of 0.001 and 1.86 with p=0.019 was detected for Caspase-1 and ASC, respectively. ROC curve analysis shows an AUC of 0.739 with p=0.0001 for Caspase-1 and an AUC of 0.665 with p=0.0139 for ASC to MDS discrimination.

Our results show that Caspase-1 and ASC gene expression levels can be used as potential biomarkers for MDS diagnosis. Prospective studies with large sample numbers are suggested.