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TP53 mutations in de novo acute myeloid leukemia patients: longitudinal follow-ups show the mutation is stable during disease evolution.

Hou HA, Chou WC, Kuo YY, Liu CY, Lin LI, Tseng MH, Chiang YC, Liu MC, Liu CW, Tang JL, Yao M, Li CC, Huang SY, Ko BS, Hsu SC, Chen CY, Lin CT, Wu SJ, Tsay W, Chen YC, Tien HF - Blood Cancer J (2015)

Bottom Line: TP53 mutations were closely associated with older age, lower white blood cell (WBC) and platelet counts, FAB M6 subtype, unfavorable-risk cytogenetics and CK, but negatively associated with NPM1 mutation, FLT3/ITD and DNMT3A mutation.Sequential study of 420 samples showed that TP53 mutations were stable during AML evolution, whereas the mutation was acquired only in 1 of the 126 TP53 wild-type patients when therapy-related AML originated from different clone emerged.In conclusion, TP53 mutations are associated with distinct clinic-biological features and poor prognosis in de novo AML patients and are rather stable during disease progression.

View Article: PubMed Central - PubMed

Affiliation: Division of Hematology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.

ABSTRACT
The TP53 mutation is frequently detected in acute myeloid leukemia (AML) patients with complex karyotype (CK), but the stability of this mutation during the clinical course remains unclear. In this study, TP53 mutations were identified in 7% of 500 patients with de novo AML and 58.8% of patients with CK. TP53 mutations were closely associated with older age, lower white blood cell (WBC) and platelet counts, FAB M6 subtype, unfavorable-risk cytogenetics and CK, but negatively associated with NPM1 mutation, FLT3/ITD and DNMT3A mutation. Multivariate analysis demonstrated that TP53 mutation was an independent poor prognostic factor for overall survival and disease-free survival among the total cohort and the subgroup of patients with CK. A scoring system incorporating TP53 mutation and nine other prognostic factors, including age, WBC counts, cytogenetics and gene mutations, into survival analysis proved to be very useful to stratify AML patients. Sequential study of 420 samples showed that TP53 mutations were stable during AML evolution, whereas the mutation was acquired only in 1 of the 126 TP53 wild-type patients when therapy-related AML originated from different clone emerged. In conclusion, TP53 mutations are associated with distinct clinic-biological features and poor prognosis in de novo AML patients and are rather stable during disease progression.

No MeSH data available.


Related in: MedlinePlus

Kaplan–Meier survival curves for OS (a) and DFS (b) in AML patients based on scoring system (P<0.001 for both OS and DFS). AML patients were grouped according to scoring system based on TP53 mutation and 9 other prognostic markers (CEBPAdouble-mutation, NPM1/FLT3-ITD, IDH2, TP53, WT1, RUNX1 and DNMT3A mutations, age and WBC counts at diagnosis). A score of −1 was assigned for each parameter associated with a favorable outcome (CEBPAdouble mutation, IDH2 mutation and NPM1+/FLT3-ITD-), whereas a score of +1 was assigned for each factor associated with an adverse outcome (TP53, WT1, RUNX1 and DNMT3A mutations, older age and higher WBC counts at diagnosis). The karyotypes were stratified into three groups (unfavorable: +2, intermediate: +1 and favorable: 0). The algebraic summation of these scores of each patient was the final score. The 12 patients without chromosome data were not included in the analysis.
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fig3: Kaplan–Meier survival curves for OS (a) and DFS (b) in AML patients based on scoring system (P<0.001 for both OS and DFS). AML patients were grouped according to scoring system based on TP53 mutation and 9 other prognostic markers (CEBPAdouble-mutation, NPM1/FLT3-ITD, IDH2, TP53, WT1, RUNX1 and DNMT3A mutations, age and WBC counts at diagnosis). A score of −1 was assigned for each parameter associated with a favorable outcome (CEBPAdouble mutation, IDH2 mutation and NPM1+/FLT3-ITD-), whereas a score of +1 was assigned for each factor associated with an adverse outcome (TP53, WT1, RUNX1 and DNMT3A mutations, older age and higher WBC counts at diagnosis). The karyotypes were stratified into three groups (unfavorable: +2, intermediate: +1 and favorable: 0). The algebraic summation of these scores of each patient was the final score. The 12 patients without chromosome data were not included in the analysis.

Mentions: To better stratify the AML patients into different risk groups, a scoring system incorporating 10 prognostic markers, including age, WBC counts, cytogenetics at diagnosis, NPM1/FLT3-ITD and mutations of CEBPA, IDH2, TP53, DNMT3A, RUNX1 and WT1, into survival analysis was formulated based on the results of our Cox proportional hazards model. A score of −1 was assigned for each parameter associated with a favorable outcome (CEBPAdouble mutation, IDH2 mutation and NPM1+/FLT3-ITD-), whereas a score of +1 for each factor associated with an adverse outcome (TP53, DNMT3A, WT1 and RUNX1 mutations, older age and higher WBC counts at diagnosis). The karyotypes were stratified into three groups (unfavorable: +2, intermediate: +1 and favorable: 0). The algebraic summation of these scores of each patient was the final score. This score system divided the AML patients into five groups with different clinical outcomes (P<0.001 for both OS and DFS, Figure 3).


TP53 mutations in de novo acute myeloid leukemia patients: longitudinal follow-ups show the mutation is stable during disease evolution.

Hou HA, Chou WC, Kuo YY, Liu CY, Lin LI, Tseng MH, Chiang YC, Liu MC, Liu CW, Tang JL, Yao M, Li CC, Huang SY, Ko BS, Hsu SC, Chen CY, Lin CT, Wu SJ, Tsay W, Chen YC, Tien HF - Blood Cancer J (2015)

Kaplan–Meier survival curves for OS (a) and DFS (b) in AML patients based on scoring system (P<0.001 for both OS and DFS). AML patients were grouped according to scoring system based on TP53 mutation and 9 other prognostic markers (CEBPAdouble-mutation, NPM1/FLT3-ITD, IDH2, TP53, WT1, RUNX1 and DNMT3A mutations, age and WBC counts at diagnosis). A score of −1 was assigned for each parameter associated with a favorable outcome (CEBPAdouble mutation, IDH2 mutation and NPM1+/FLT3-ITD-), whereas a score of +1 was assigned for each factor associated with an adverse outcome (TP53, WT1, RUNX1 and DNMT3A mutations, older age and higher WBC counts at diagnosis). The karyotypes were stratified into three groups (unfavorable: +2, intermediate: +1 and favorable: 0). The algebraic summation of these scores of each patient was the final score. The 12 patients without chromosome data were not included in the analysis.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4526785&req=5

fig3: Kaplan–Meier survival curves for OS (a) and DFS (b) in AML patients based on scoring system (P<0.001 for both OS and DFS). AML patients were grouped according to scoring system based on TP53 mutation and 9 other prognostic markers (CEBPAdouble-mutation, NPM1/FLT3-ITD, IDH2, TP53, WT1, RUNX1 and DNMT3A mutations, age and WBC counts at diagnosis). A score of −1 was assigned for each parameter associated with a favorable outcome (CEBPAdouble mutation, IDH2 mutation and NPM1+/FLT3-ITD-), whereas a score of +1 was assigned for each factor associated with an adverse outcome (TP53, WT1, RUNX1 and DNMT3A mutations, older age and higher WBC counts at diagnosis). The karyotypes were stratified into three groups (unfavorable: +2, intermediate: +1 and favorable: 0). The algebraic summation of these scores of each patient was the final score. The 12 patients without chromosome data were not included in the analysis.
Mentions: To better stratify the AML patients into different risk groups, a scoring system incorporating 10 prognostic markers, including age, WBC counts, cytogenetics at diagnosis, NPM1/FLT3-ITD and mutations of CEBPA, IDH2, TP53, DNMT3A, RUNX1 and WT1, into survival analysis was formulated based on the results of our Cox proportional hazards model. A score of −1 was assigned for each parameter associated with a favorable outcome (CEBPAdouble mutation, IDH2 mutation and NPM1+/FLT3-ITD-), whereas a score of +1 for each factor associated with an adverse outcome (TP53, DNMT3A, WT1 and RUNX1 mutations, older age and higher WBC counts at diagnosis). The karyotypes were stratified into three groups (unfavorable: +2, intermediate: +1 and favorable: 0). The algebraic summation of these scores of each patient was the final score. This score system divided the AML patients into five groups with different clinical outcomes (P<0.001 for both OS and DFS, Figure 3).

Bottom Line: TP53 mutations were closely associated with older age, lower white blood cell (WBC) and platelet counts, FAB M6 subtype, unfavorable-risk cytogenetics and CK, but negatively associated with NPM1 mutation, FLT3/ITD and DNMT3A mutation.Sequential study of 420 samples showed that TP53 mutations were stable during AML evolution, whereas the mutation was acquired only in 1 of the 126 TP53 wild-type patients when therapy-related AML originated from different clone emerged.In conclusion, TP53 mutations are associated with distinct clinic-biological features and poor prognosis in de novo AML patients and are rather stable during disease progression.

View Article: PubMed Central - PubMed

Affiliation: Division of Hematology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.

ABSTRACT
The TP53 mutation is frequently detected in acute myeloid leukemia (AML) patients with complex karyotype (CK), but the stability of this mutation during the clinical course remains unclear. In this study, TP53 mutations were identified in 7% of 500 patients with de novo AML and 58.8% of patients with CK. TP53 mutations were closely associated with older age, lower white blood cell (WBC) and platelet counts, FAB M6 subtype, unfavorable-risk cytogenetics and CK, but negatively associated with NPM1 mutation, FLT3/ITD and DNMT3A mutation. Multivariate analysis demonstrated that TP53 mutation was an independent poor prognostic factor for overall survival and disease-free survival among the total cohort and the subgroup of patients with CK. A scoring system incorporating TP53 mutation and nine other prognostic factors, including age, WBC counts, cytogenetics and gene mutations, into survival analysis proved to be very useful to stratify AML patients. Sequential study of 420 samples showed that TP53 mutations were stable during AML evolution, whereas the mutation was acquired only in 1 of the 126 TP53 wild-type patients when therapy-related AML originated from different clone emerged. In conclusion, TP53 mutations are associated with distinct clinic-biological features and poor prognosis in de novo AML patients and are rather stable during disease progression.

No MeSH data available.


Related in: MedlinePlus