The influence of Wilms' tumor 1 gene expression level on prognosis and risk stratification of acute promyelocytic leukemia patients. (12th December 2019)

• Record Type: Journal Article
• Authors: Mitrovic, Mirjana; Kostic, Tatjana; Virijevic, Marijana; Karan‐Djurasevic, Teodora; Suvajdzic Vukovic, Nada; Pavlovic, Sonja; Tosic, Natasa
• Is Part Of: International journal of laboratory hematology. Volume 42:Number 1(2020:Feb.)
• Page Start: 82
• Page End: 87
• Publication Date: 2019-12-12
• Subjects: acute promyelocytic leukemia -- minimal residual disease -- prognosis -- WT1 gene expression; Hematology -- Periodicals; Blood -- Diseases -- Periodicals; Hematology -- Periodicals; 616.15005
• DOI: 10.1111/ijlh.13144
• Languages: English
• ISSNs: 1751-5521

Abstract

Abstract: Introduction: Patients with acute promyelocytic leukemia (APL) are characterized by the highest expression of Wilms' tumor 1 ( WT1 ) gene compared with other subtypes of acute myeloid leukemia, and yet this molecular marker is almost never used for risk stratification and in therapy response monitoring. Methods: Quantitative assessment of Wilms' tumor 1 ( WT1 ) gene transcripts was performed using real‐time PCR method. The bone marrow samples were collected at the time of diagnosis for 47 APL patients, and for 31/47 patients during follow‐up/relapse of the disease (129 samples in total). We examined how this molecular marker can be used for prognosis and minimal residual disease (MRD) monitoring. Results: Increased WT1 expression was found in 34% of patients. WT1 high status was an independent unfavorable factor for early death occurrence and was associated with shorter overall survival (OS). Assessment of log reduction value of WT1 expression in paired diagnosis/complete remission samples did not reveal its impact on relapse rate, disease‐free survival, and OS. Also, measurement of WT1 expression level at different time points during therapy was not a reliable method for MRD monitoring. Conclusion: Increased expression of WT1 gene detected in high proportion of APL patients could be considered as a marker for more precise risk stratification models in an attempt to further improve treatment and outcome of APL patients.