Computational Analysis of Cohesin Complex Genes and their Role in the Pathogenesis of AML

Abstract

Objective: Anomalies in the cohesion complex contribute to the pathogenesis of myeloid malignancies by affecting the self-renewal capacity of hematopoietic and progenitor stem cells, but the underlying mechanisms of this phenotype are not fully understood. Therefore, this study aims to shed light on the relationship between AML pathogenesis and the cohesion complex by comprehensively determining the mutations and expression profiles in the genes constituting the cohesion complex and investigating the effect of expression on survival using bioinformatics databases and tools. Methods: A total of 96 different mutations were identified in 13 genes. Out of these 96 mutations, 26 were classified as pathogenic/oncogenic. The expression levels of STAG1, REC8, MAU2, CDCA5, and PDS5B were significantly higher in the patient group compared to the healthy group (p< .01). Survival analysis based on low and high gene expression profiles revealed that increased REC8 expression was significantly associated with survival (p= .024), which is considered a prognostic marker. In STRING analysis, it was determined that hub proteins interact with acetyltransferases ESCO1 and ESCO2 involved in sister chromatid cohesion, with TERF1, a component of the telomere nucleoprotein complex, and with PDS5A and BRCA2, which are functionally related to genetic stability and genetic recombination, respectively. Results: An increase in language outcomes, particularly in repetition, was observed following the treatments. It was also found that therapy gains were more robust following bihemispheric stimulation of the posterior temporal sites compared to the inferior frontal targets. Conclusion: Overall, none of the target genes except the mutated REC8 showed a significant and independent effect on the clinical outcome defined as overall survival. However, we have identified the diversity of genetic alterations in individual cohesin subunits through comprehensive molecular analysis. The results may be beneficial in the development of targeted drug therapies and personalized medicine approaches.