Abstract
Introduction:
Clearance of detected somatic mutations at complete response by next-generation sequencing is a prognostic marker for survival in patients with acute myeloid leukemia (AML). However, the impact of allelic burden and persistence of clonal hematopoiesis of indeterminate potential (CHIP)-associated mutations on survival remains unclear. The aim of this study is to evaluate the prognostic impact of allelic burden of CHIP mutations at diagnosis, and their persistence within 6 months of therapy.
Methods:
From February 1, 2012 to May 26, 2016, we reviewed 562 patients with newly diagnosed AML. Next-generation sequencing was performed on the bone marrow samples to detect the presence of CHIP-associated mutations defined as DNMT3A, TET2, ASXL1, JAK2 and TP53. Overall survival (OS) was defined as time period from the diagnosis of AML to the date of last follow-up or death. Univariate (UVA) and multivariate Cox proportional hazard regression (MVA) were performed to identify prognostic factors for OS with p value cutoff of 0.020 for the selection of variables for MVA. Landmark analysis at 6 months was performed for the evaluation of the impact of clearance of CHIP, FLT3-ITD, FLT3D835, and NPM1 mutations.
Results:
We identified 378 patients (74%) with AML with CHIP mutations; 134 patients (26%) with AML without CHIP mutations. The overall median follow-up of 23 months (range, 0.1-49.0). The median age at diagnosis was 70 years (range, 17-92) and 66 years (range, 20-87) in CHIP AML and non-CHIP AML, respectively (p =0.001). Of 371 patients and 127 patients evaluable for cytogenetic in CHIP AML and non-CHIP AML, 124 (33%) and 25 patients (20%) had complex karyotype, respectively (p= 0.004). Of 378 patients with CHIP AML, 183 patients (48%) had TET2 mutations; 113 (30%), TP53; 110 (29%), ASXL1; 109 (29%), DNMT3A; JAK2, 46 (12%). Of 378 patients, single CHIP mutations was observed in 225 patients (60%); double, 33 (9%); triple, 28 (7%); quadruple, 1 (0%). Concurrent FLT3-ITD mutations was detected in 47 patients (13%) and 12 patients (9%) in CHIP AML and non-CHIP AML, respectively (p= 0.287); FLT3-D835, 22 (6%) and 8 (6%), respectively (p= 0.932); NPM1 mutations, 62 (17%) and 13 (10%), respectively (p= 0.057). Of 183 patients with TET2-mutated AML, the median TET2 variant allele frequency (VAF) was 42.9% (range, 2.26-95.32); of 113 with TP53-mutated AML, the median TP53 VAF, 45.9% (range, 1.15-93.74); of 109 with ASXL1-mutated AML, the median ASXL1 VAF was 34.5% (range, 1.17-58.62); of 109 with DNMT3A-mutated AML, the median DNMT3A VAF was 41.8% (range, 1.02-91.66); of 46 with JAK2-mutated AML, the median JAK2 VAF was 54.4% (range, 1.49-98.52). Overall, the median OS was 12 months and 11 months in CHIP AML and non-CHIP AML, respectively (p= 0.564); 16 months and 5 months in TET2-mutated AML and non-TET2-mutated AML, respectively (p <0.001); 4 months and 13 months in TP53-mutated and non-TP53-mutated AML, respectively (p< 0.001); 17 months and 11 months in DNMT3A-mutated and non-DNMT3A-mutated AML, respectively (p= 0.072); 16 months and 11 months in ASXL1-mutated AML and non-ASXL1-mutated AML, respectively (p= 0.067); 11 months and 12 months in JAK2-murated and non-JAK2-mutated AML, respectively (p= 0.123). The presence and number of CHIP mutations were not a prognostic factor for OS by univariate analysis (p=0.565; hazard ratio [HR], 0.929; 95% confidence interval [CI], 0.722-1.194: p= 0.408; hazard ratio, 1.058; 95% confidence interval, 0.926-1.208, respectively). MVA Cox regression identified age (p< 0.001; HR, 1.036; 95% CI, 1.024-1.048), TP53 VAF (p= 0.007; HR, 1.009; 95% CI, 1.002-1.016), NPM1 VAF (p=0.006; HR, 0.980; 95% CI, 0.967-0.994), and complex karyotype (p<0.001; HR, 1.869; 95% CI, 1.332-2.622) as independent prognostic factors for OS. Of 33 patients with CHIP AML who were evaluated for the clearance of VAF by next generation sequencing , landmark analysis at 6 months showed median OS of not reached and 20.3 months in patients with and without CHIP-mutation clearance, respectively (p=0.310).
Conclusion:
The VAF of TP53 and NPM1 mutations by next generation sequencing can further stratify patients with newly diagnosed AML. Approximately, each increment of TP53 and NPM1 VAF by 1% is independently associated with 1% higher risk of death, and 2% lower risk of death, respectively. The presence of CHIP mutations except TP53 does not affect outcome.
Disclosures
Sasaki: Otsuka Pharmaceutical: Honoraria. Short:Takeda Oncology: Consultancy. Ravandi:Macrogenix: Honoraria, Research Funding; Seattle Genetics: Research Funding; Sunesis: Honoraria; Xencor: Research Funding; Jazz: Honoraria; Seattle Genetics: Research Funding; Abbvie: Research Funding; Macrogenix: Honoraria, Research Funding; Bristol-Myers Squibb: Research Funding; Orsenix: Honoraria; Abbvie: Research Funding; Jazz: Honoraria; Xencor: Research Funding; Orsenix: Honoraria; Sunesis: Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Astellas Pharmaceuticals: Consultancy, Honoraria. Kadia:BMS: Research Funding; Abbvie: Consultancy; Takeda: Consultancy; Jazz: Consultancy, Research Funding; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Celgene: Research Funding; Novartis: Consultancy; Amgen: Consultancy, Research Funding; BMS: Research Funding; Jazz: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy; Abbvie: Consultancy; Celgene: Research Funding. DiNardo:Karyopharm: Honoraria; Agios: Consultancy; Celgene: Honoraria; Medimmune: Honoraria; Bayer: Honoraria; Abbvie: Honoraria. Cortes:Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Astellas Pharma: Consultancy, Research Funding; Arog: Research Funding.
Analysis and Optimal Design for Association Studies Using Next-Generation Sequencing With Case-Control Pools
