BACKGROUND: Mutations in the tumor protein 53 (TP53) gene predict a poor prognosis in patients with acute myeloid leukemia (AML). METHODS: Peripheral blood or bone marrow samples from 293 patients with newly diagnosed AML were analyzed with targeted, amplicon-based, next-generation sequencing-based mutation analysis. RESULTS: TP53 mutations were identified in 53 patients (18%; 45 were missense mutations). In 13 of the 53 patients, the most common pattern of amino acid substitution was a substitution of arginine to histidine on different codons. The clinical characteristics, pattern of mutations, response to different therapies, and outcomes of patients with AML-TP53-mutated (n = 53) versus wild-type TP53 (n = 240) were compared. TP53 mutations were significantly more likely in patients who had a complex karyotype; abnormalities of chromosome 5, 7, and 17; and therapy-related AML. Patients who had TP53-mutated AML had significantly lower incidence of mutations in Fms-like tyrosine kinase 3 (FLT3), rat sarcoma (RAS), and nucleophosmin (NPM1) and higher incidence of coexisting MPL mutations compared with those who had wild type TP53. The distribution of TP53 mutations was equal for both age groups (ages <60 years vs ≥60 years). TP53-mutated AML was associated with a lower complete remission rate (41% vs 57%; P = .04), a significantly inferior complete remission duration (at 2 years: 30% vs 55%; P = .001), and overall survival (at 2 years: 9% vs 24%; P ≤ .0001) irrespective of age or the type of treatment received (high-intensity vs low-intensity chemotherapy). CONCLUSIONS: The type of treatment received did not improve outcomes in younger or older patients with TP53-mutated AML. These data suggest that novel therapies are needed to improve the outcome of patients with AML who have TP53 mutations. Cancer 2016;122:3484-3491.
BACKGROUND: Mutations in the tumor protein 53 (TP53) gene predict a poor prognosis in patients with acute myeloid leukemia (AML). METHODS: Peripheral blood or bone marrow samples from 293 patients with newly diagnosed AML were analyzed with targeted, amplicon-based, next-generation sequencing-based mutation analysis. RESULTS:TP53 mutations were identified in 53 patients (18%; 45 were missense mutations). In 13 of the 53 patients, the most common pattern of amino acid substitution was a substitution of arginine to histidine on different codons. The clinical characteristics, pattern of mutations, response to different therapies, and outcomes of patients with AML-TP53-mutated (n = 53) versus wild-type TP53 (n = 240) were compared. TP53 mutations were significantly more likely in patients who had a complex karyotype; abnormalities of chromosome 5, 7, and 17; and therapy-related AML. Patients who had TP53-mutated AML had significantly lower incidence of mutations in Fms-like tyrosine kinase 3 (FLT3), ratsarcoma (RAS), and nucleophosmin (NPM1) and higher incidence of coexisting MPL mutations compared with those who had wild type TP53. The distribution of TP53 mutations was equal for both age groups (ages <60 years vs ≥60 years). TP53-mutated AML was associated with a lower complete remission rate (41% vs 57%; P = .04), a significantly inferior complete remission duration (at 2 years: 30% vs 55%; P = .001), and overall survival (at 2 years: 9% vs 24%; P ≤ .0001) irrespective of age or the type of treatment received (high-intensity vs low-intensity chemotherapy). CONCLUSIONS: The type of treatment received did not improve outcomes in younger or older patients with TP53-mutated AML. These data suggest that novel therapies are needed to improve the outcome of patients with AML who have TP53 mutations. Cancer 2016;122:3484-3491.
Authors: Jan M Middeke; Sylvia Herold; Elke Rücker-Braun; Wolfgang E Berdel; Matthias Stelljes; Martin Kaufmann; Kerstin Schäfer-Eckart; Claudia D Baldus; Reingard Stuhlmann; Anthony D Ho; Hermann Einsele; Wolf Rösler; Hubert Serve; Mathias Hänel; Kristina Sohlbach; Christian Klesse; Brigitte Mohr; Falk Heidenreich; Friedrich Stölzel; Christoph Röllig; Uwe Platzbecker; Gerhard Ehninger; Martin Bornhäuser; Christian Thiede; Johannes Schetelig Journal: Br J Haematol Date: 2016-01-13 Impact factor: 6.998
Authors: Frank G Rücker; Richard F Schlenk; Lars Bullinger; Sabine Kayser; Veronica Teleanu; Helena Kett; Marianne Habdank; Carla-Maria Kugler; Karlheinz Holzmann; Verena I Gaidzik; Peter Paschka; Gerhard Held; Marie von Lilienfeld-Toal; Michael Lübbert; Stefan Fröhling; Thorsten Zenz; Jürgen Krauter; Brigitte Schlegelberger; Arnold Ganser; Peter Lichter; Konstanze Döhner; Hartmut Döhner Journal: Blood Date: 2011-12-20 Impact factor: 22.113
Authors: H Seifert; B Mohr; C Thiede; U Oelschlägel; U Schäkel; T Illmer; S Soucek; G Ehninger; M Schaich Journal: Leukemia Date: 2009-01-08 Impact factor: 11.528
Authors: N Ånensen; S M Hjelle; W Van Belle; I Haaland; E Silden; J-C Bourdon; R Hovland; K Taskén; S Knappskog; P E Lønning; Ø Bruserud; B T Gjertsen Journal: Oncogene Date: 2011-08-22 Impact factor: 9.867
Authors: Stefan O Ciurea; Abhishek Chilkulwar; Rima M Saliba; Julianne Chen; Gabriela Rondon; Keyur P Patel; Haitham Khogeer; Abdul R Shah; Brion V Randolph; Jorge M Ramos Perez; Uday Popat; Chitra M Hosing; Qaiser Bashir; Rohtesh Mehta; Gheath Al-Atrash; Jin Im; Issa F Khouri; Partow Kebriaei; Richard E Champlin Journal: Blood Date: 2018-05-16 Impact factor: 22.113
Authors: Pinkal Desai; Nuria Mencia-Trinchant; Oleksandr Savenkov; Michael S Simon; Gloria Cheang; Sangmin Lee; Michael Samuel; Ellen K Ritchie; Monica L Guzman; Karla V Ballman; Gail J Roboz; Duane C Hassane Journal: Nat Med Date: 2018-07-09 Impact factor: 53.440
Authors: Luis A Carvajal; Daniela Ben Neriah; Adrien Senecal; Lumie Benard; Victor Thiruthuvanathan; Tatyana Yatsenko; Swathi-Rao Narayanagari; Justin C Wheat; Tihomira I Todorova; Kelly Mitchell; Charles Kenworthy; Vincent Guerlavais; D Allen Annis; Boris Bartholdy; Britta Will; Jesus D Anampa; Ioannis Mantzaris; Manuel Aivado; Robert H Singer; Robert A Coleman; Amit Verma; Ulrich Steidl Journal: Sci Transl Med Date: 2018-04-11 Impact factor: 17.956