Relationship between immunophenotyping and X-inactive specific transcript gene in acute myeloid leukemia

Abstract Context Acute myeloid leukemia (AML) is an aggressive malignancy of the bone marrow presenting significant challenges in clinical management because its molecular cause is not fully understood. Clarifying the intricate connection between X-inactive specific transcript ( XIST ) and the development of tumors poses a significant challenge. Consequently, gaining a thorough comprehension of the varied functions of XIST in cancer biology will establish the foundation for its application as a diagnostic, prognostic indicator, and a potential target for therapeutic interventions in cancer treatment within clinical settings. Aims To detect the XIST gene by fluorescence in situ hybridization in AML patients and to study the association between its deletion and the immunophenotypic panel of acute leukemia and also to evaluate its role as a predictor of AML patient outcomes. Settings and design A cross-sectional study. Patients and methods The study was carried out on 65 patients diagnosed with AML after bone marrow aspirate and immunophenotyping. We detected the XIST gene by fluorescence in situ hybridization. Statistical analysis used Data were verified, coded by the researcher, and analyzed using IBM-SPSS 24.0 (IBM-SPSS Inc.). Results XIST deletion was detected in six (9.2%) cases and extra X chromosome in one (1.5%) case. Five of the six XIST gene-deleted cases had monocytic differentiation. All XIST gene-deleted cases expressed HLA-DR. However, when compared with nondeleted XIST cases the difference did not reach a significant level. Conclusions The XIST gene was deleted in some AML patients. This deletion was associated more with AML with monocytic differentiation. All XIST gene deletion cases showed an expression of HLA-DR. The outcome of the patients revealed that all the patients who had XIST gene deletion died early after diagnosis. This may raise the possibility that its deletion might be associated with more advanced risk stratification in those patients.