Association between the CEBPA and c-MYC genes expression levels and acute myeloid leukemia pathogenesis and development.
Krygier AdrianSzmajda-Krygier DagmaraAleksandra Sałagacka-KubiakKrzysztof JamroziakŻebrowska-Nawrocka MartaEwa BalcerczakPublished in: Medical oncology (Northwood, London, England) (2020)
CEBPA and c-MYC genes belong to TF and play an essential role in hematologic malignancies development. Furthermore, these genes also co-regulate with RUNX1 and lead to bone marrow differentiation and may contribute to the leukemic transformation. Understanding the function and full characteristics of selected genes in the group of patients with AML can be helpful in assessing prognosis, and their usefulness as prognostic factors can be revealed. The aim of the study was to evaluate CEBPA and c-MYC mRNA expression level and to seek their association with demographical and clinical features of AML patients such as: age, gender, FAB classification, mortality or leukemia cell karyotype. Obtained results were also correlated with the expression level of the RUNX gene family. To assess of relative gene expression level the qPCR method was used. The expression levels of CEBPA and c-MYC gene varied among patients. Neither CEBPA nor c-MYC expression levels differed significantly between women and men (p=0.8325 and p=0.1698, respectively). No statistically significant correlation between age at the time of diagnosis and expression of CEBPA (p=0.4314) or c-MYC (p=0.9524) was stated. There were no significant associations between relative CEBPA (p=0.4247) or c-MYC (p=0.4655) expression level and FAB subtype and mortality among the enrolled patients (p=0.5858 and p=0.8437, respectively). However, it was observed that c-MYC and RUNX1 expression levels were significantly positively correlated (rS=0.328, p=0.0411). Overall, AML pathogenesis involves a complex interaction among CEBPA, c-MYC and RUNX family genes.
Keyphrases
- acute myeloid leukemia
- poor prognosis
- prognostic factors
- gene expression
- bone marrow
- genome wide
- transcription factor
- binding protein
- newly diagnosed
- genome wide identification
- dna methylation
- type diabetes
- mesenchymal stem cells
- mental health
- cardiovascular events
- pregnant women
- stem cells
- coronary artery disease
- metabolic syndrome
- deep learning
- chronic kidney disease
- insulin resistance
- single cell
- middle aged
- pregnancy outcomes