Contributions
Abstract: PB1389
Type: Publication Only
Session title: Acute myeloid leukemia - Biology & Translational Research
Background
Actual prognostic factors for predicting therapy response in patients with acute myeloid leukemia (AML) are formed on the basis of detected cytogenetic and molecular genetic abnormalities, as well as initial clinical data, including the patient's age, the number of leukocytes in peripheral blood, and the level of blasts in the bone marrow. However, the therapy response is often influenced by the presence of primary resistance of tumor cells to cytotoxic drugs. Assessment of the combined impact of these factors on the therapy response of leukemia patients can be done by the forming of the multivariate predictive models.
Aims
The aim of this work was to assess the risk of development and progression of drugresistance in patientswith acute myeloidleukemia based on thepatients’ age, MDR1 gene expression, sensitivity of tumor cells to cytostatic drugs, cytogenetic and molecular genetic abnormalities detected initially at diagnosis before treatment start.
Methods
The study included 53 patients withAML.Leukemic cells were collected from peripheral blood and bone marrow of patients. Assessment of multidrug resistance in tumor cells of leukemia patients was performed using real-time RT-qPCR) and WST1-test. RT-qPCR was used to evaluate the expression of the MDR1 gene. WST1-test was used to evaluate the sensitivity of tumor cells to chemotherapeutic drugs in vitro. The correlation analysis was performed using Spearmen’s correlation coefficient (r).All statistical analyses were done with software MS Excel, OriginPro 7.5, Statistica 10.0.
Results
The average age of the patients was 51.2±14.5 years.In the group of AML patients who receivedanthracycline-based therapy, reliable correlations for response to therapy (p <0.05) with the following indicatorswere obtained: age (r = 0.55), sensitivity to daunorubicin (r = 0.72), karyotype of tumor cells (r = 0.6), standard risk stratification by genetics (r = 0.7), total sensitivity to cytotoxic drugs (r = 0.61), standard prognosis stratification by cytogenetic/molecular markers and clinical characteristics(r = 0.55). There was also direct correlation between response to therapy and the level of MDR1 gene expression (r = 1.0), however, due to the small sample size the differences were statistically insignificant, p> 0.05. Based on this data, a new prognostic scale was developed –all patients were divided into 3 prognostic groups: low risk group, intermediate risk group and high risk group.
Conclusion
Thus, the prognostic factors influencing the therapy response of AML patients were analyzed. The most prognostic values were detected for the following variables: the sensitivity of tumor cells to cytostatic drugs, the level of MDR1 gene expression, the karyotype of tumor cells, the age of patients, and the presence of cytogenetic abnormalities in tumor cells. Our prognostic scale allows to predictthe patient’s response to the planned treatment protocol before the therapystart , which enables a personalized approach to the selection of patient management strategy.
Keyword(s): Acute myeloid leukemia, Drug resistance, Drug sensitivity, MDR1
Abstract: PB1389
Type: Publication Only
Session title: Acute myeloid leukemia - Biology & Translational Research
Background
Actual prognostic factors for predicting therapy response in patients with acute myeloid leukemia (AML) are formed on the basis of detected cytogenetic and molecular genetic abnormalities, as well as initial clinical data, including the patient's age, the number of leukocytes in peripheral blood, and the level of blasts in the bone marrow. However, the therapy response is often influenced by the presence of primary resistance of tumor cells to cytotoxic drugs. Assessment of the combined impact of these factors on the therapy response of leukemia patients can be done by the forming of the multivariate predictive models.
Aims
The aim of this work was to assess the risk of development and progression of drugresistance in patientswith acute myeloidleukemia based on thepatients’ age, MDR1 gene expression, sensitivity of tumor cells to cytostatic drugs, cytogenetic and molecular genetic abnormalities detected initially at diagnosis before treatment start.
Methods
The study included 53 patients withAML.Leukemic cells were collected from peripheral blood and bone marrow of patients. Assessment of multidrug resistance in tumor cells of leukemia patients was performed using real-time RT-qPCR) and WST1-test. RT-qPCR was used to evaluate the expression of the MDR1 gene. WST1-test was used to evaluate the sensitivity of tumor cells to chemotherapeutic drugs in vitro. The correlation analysis was performed using Spearmen’s correlation coefficient (r).All statistical analyses were done with software MS Excel, OriginPro 7.5, Statistica 10.0.
Results
The average age of the patients was 51.2±14.5 years.In the group of AML patients who receivedanthracycline-based therapy, reliable correlations for response to therapy (p <0.05) with the following indicatorswere obtained: age (r = 0.55), sensitivity to daunorubicin (r = 0.72), karyotype of tumor cells (r = 0.6), standard risk stratification by genetics (r = 0.7), total sensitivity to cytotoxic drugs (r = 0.61), standard prognosis stratification by cytogenetic/molecular markers and clinical characteristics(r = 0.55). There was also direct correlation between response to therapy and the level of MDR1 gene expression (r = 1.0), however, due to the small sample size the differences were statistically insignificant, p> 0.05. Based on this data, a new prognostic scale was developed –all patients were divided into 3 prognostic groups: low risk group, intermediate risk group and high risk group.
Conclusion
Thus, the prognostic factors influencing the therapy response of AML patients were analyzed. The most prognostic values were detected for the following variables: the sensitivity of tumor cells to cytostatic drugs, the level of MDR1 gene expression, the karyotype of tumor cells, the age of patients, and the presence of cytogenetic abnormalities in tumor cells. Our prognostic scale allows to predictthe patient’s response to the planned treatment protocol before the therapystart , which enables a personalized approach to the selection of patient management strategy.
Keyword(s): Acute myeloid leukemia, Drug resistance, Drug sensitivity, MDR1