The influence of BCL2, BAX, and ABCB1 gene expression on prognosis of adult de novo acute myeloid leukemia with normal karyotype patients
Abstract
Background
Deregulation of the apoptotic process underlies the pathogenesis of many cancers, including leukemia, but is also very important for the success of chemotherapy treatment. Therefore, the gene expression profile of main apoptotic factors, such as anti-apoptotic BCL2 (B-cell lymphoma protein 2) and pro-apoptotic BAX (BCL2-associated X), as well as genes involved in the multi-drug resistance (ABCB1), could have significant impact on the prognosis and could be used as targets for specific therapy.
Patients and methods
We analyzed the expression of BCL2, BAX, and ABCB1 in bone-marrow samples collected at diagnosis from 51 adult patients with acute myeloid leukemia with normal karyotype (AML-NK) using real-time polymerase chain reaction method, and examined their prognostic potential.
Results
Increased expression of BCL2 (BCL2+) was associated with the presence of chemoresistance (p = 0.024), while patients with low BAX expression were more prone to relapse (p = 0.047). Analysis of the combined effect of BCL2 and BAX expression showed that 87% of patients with BAX/BCL2low status were resistant to therapy (p = 0.044). High expression of ABCB1 was associated with BCL2+ status (p < 0.001), and with absence FLT3-ITD mutations (p = 0.019).
Conclusions
The present analysis of BCL2, BAX, and ABCB1 gene expression profiles is the first study focusing solely on AML-NK patients. Preliminary results showed that patients with high BCL2 expression are likely to experience resistance to chemotherapy, and may benefit from specific anti-BCL2 treatment. Further investigations conducted on a larger number of patients could elucidate actual prognostic significance of these genes in AML-NK patients.
© 2023 Zlatko Pravdic, Nada Suvajdzic Vukovic, Vladimir Gasic, Irena Marjanovic, Teodora Karan-Djurasevic, Sonja Pavlovic, Natasa Tosic, published by Association of Radiology and Oncology
This work is licensed under the Creative Commons Attribution 4.0 License.