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Molecular Minimal Residual Disease Detection Shows Further Promise in Acute Myeloid Leukemia


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Andrew Dunbar, MD

Andrew Dunbar, MD

Martin Tallman, MD

Martin Tallman, MD

Extended next-generation sequencing genomic profiling in acute myeloid leukemia (AML) has revealed remarkable heterogeneity and molecular complexity of the disease and provided critical insights into the genetic mechanisms underpinning of preleukemic and leukemic pathogenesis.1,2 Despite significant advances in AML treatment in the postgenomic era, the relapse rate remains high, and therapeutic options in this setting are generally limited to clinical trials, often with variable efficacy. When AML does relapse, it is generally thought to arise as a result of residual leukemic cells not successfully eradicated by high-intensity induction chemotherapy and subsequent postremission treatment. Additional prognostication strategies are needed to more accurately predict for relapse in AML and allow for improved individualization of postremission therapy.

Minimal residual disease, or the persistence of leukemic cells after induction chemotherapy occurring below the level of detection of traditional histology/light microscopy, is increasingly recognized as a powerful tool in predicting relapse.3 Currently employed methods for identifying minimal residual disease include multiparametric flow cytometry and targeted, gene-specific, quantitative polymerase chain reaction (PCR)—techniques capable of detecting residual abnormal cells at levels 10 to 100,000 times deeper than that of current histopathologic analysis. In acute lymphoblastic leukemia, minimal residual disease detection has become incorporated into prognostication schema and is regularly used to guide treatment. Over the past decade, seminal studies in AML have also established similar associations between minimal residual disease and relapse rate4-7; however, standardized monitoring has yet to be routinely integrated into clinical practice (although recently published comprehensive guidelines by the European LeukemiaNet aim to change this).8 Furthermore, despite the regular use of extended next-generation sequencing profiling at the time of diagnosis for AML, few large-cohort series had explored this assay prospectively as a tool for minimal residual disease assessment.

Correlation Between Mutations and Outcomes

In the March 29, 2018, issue of The New England Journal of Medicine, Dr. Jongen-Lavrencic and colleagues from the Erasmus MC Cancer Institute in the Netherlands describe their systematic evaluation of extended next-generation sequencing as a tool for minimal residual disease detection and its correlation with clinical outcomes in AML9; the study is reviewed in this issue of The ASCO Post. The primary study endpoint was relapse risk, with secondary endpoints of relapse-free survival and overall survival, with 4-year overall follow-up. Sensitivity of the next-generation sequencing panel to detect individual mutations varied based on the depth of coverage at specific loci.

Remarkably, approximately half of all 430 patients for whom molecular profiling was available had residual detectable mutations at the time of minimal residual disease assessment.
— ANDREW DUNBAR, MD, AND MARTIN TALLMAN, MD

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Remarkably, approximately half (51.4%) of all 430 patients for whom molecular profiling was available had residual detectable mutations at the time of minimal residual disease assessment. The presence of any mutation after induction chemotherapy correlated significantly with 4-year relapse risk (48.2% vs 32.4%, P = .03). Interestingly, mutations detectable after chemotherapy were those most often implicated in age-related clonal hematopoiesis, specifically DNMT3A, TET2, and ASXL1 (so-called DTA mutations)—persisting at variant allele frequencies of up to 47%, highlighting the relative durability of these clonal cell populations despite exposure to high-intensity chemotherapy. However, persistence of a DTA mutation was not associated with increased relapse rate or worsened outcome, regardless of allele burden. Rather, it was the presence of all other mutations (“non-DTA mutations”) that correlated closely with relapse: in patients in whom a non-DTA mutation persisted after induction chemotherapy (whether co-occurring with a DTA mutation or not), the 4-year relapse risk was significantly greater compared with those who tested negative for a non-DTA mutation (55.4% vs 31.9%, hazard ratio [HR] = 2.14, P < .001). This translated into significant reductions in relapse-free survival (36.6% vs 58.1%, HR = 1.92, P < .001) and overall survival (41.9% vs 66.1%, HR = 2.06, P < .001).

Notably, the most striking effect was seen when next-generation sequencing profiling was integrated with multiparametric flow cytometry. High concordance of minimal residual disease positivity was observed between both assays (69%), and relapse risk was remarkably high if detectable minimal residual disease was positive in both panels (73.3%) versus negative in both panels (26.7%). These data, and others,10 lend further support to integrated approaches combining multiparametric flow and extended next-generation sequencing testing with other established prognostic indicators for improved relapse prediction modeling in AML.

Age-Related Clonal Hematopoiesis

In addition to its major contributions in regard to minimal residual disease monitoring in AML, this work also serves to highlight the emerging importance of age-related clonal hematopoiesis11-13 and the risk of “DTA mutations” in the development of overt myeloid disease. Not only were DTA mutations prevalent in leukemic cells at the time of diagnosis, they also persisted at high allele frequencies despite exposure to intensive chemotherapy, presumably as a result of treatment resistance and clonal selection after eradication of leukemic cells. Although not associated with relapse within the follow-up in this study, the long-term consequences of these residual preleukemic clonal cell populations and any potential effect on late reemergence of leukemia or development of secondary myeloid malignancy remain unclear.

The work by Dr. Jongen-Lavrencic and colleagues adds to the growing body of evidence supporting the role of minimal residual disease monitoring in the prognostication and management of AML.
— ANDREW DUNBAR, MD, AND MARTIN TALLMAN, MD

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Additional translational studies exploring the genetic and epigenetic mechanisms conferring clonal advantage to these cells are needed to better elucidate how they survive and expand in response to injury and how they might be better targeted with epigenetic therapies. Similarly, prospective monitoring of patients with incidentally found clonal hematopoiesis (either before or after the development of myeloid disease) will help to define its ideal management, from mitigating the risk of potential malignancy to preventing other systemic sequelae with which it might be associated, including known cardiovascular disease.14

Closing Thoughts

In sum,the work by Dr. Jongen-Lavrencic and colleagues adds to the growing body of evidence supporting the role of minimal residual disease monitoring in the prognostication and management of AML. As minimal residual disease monitoring becomes increasingly commonplace, and methods are further refined to cultivate standardization across institutions, so too will prospective, randomized trials hopefully validate minimal residual disease as a clinical decision-making tool in AML.

DISCLOSURE: Dr. Dunbar reported no conflicts of interest. Dr. Tallman has a consulting or advisory role with Daiichi-Sankyo and Orsnenix; has received research support from ARO, ADC Therapeutics, Orsenix, and Cellerant; and has received honoraria or reimbursement for travel/accommodation expenses from the University of Pittsburgh, Eastern Virginia Medical School, St. Vincent’s Hospital, Emirates Haematology Conference, Hartford Hospital, International Educational Forum, Norvartis, Mayo Clinic, George Washington University, American Society of Hematology, Rush University Medical Center, Lynn Cancer Institute, Indy Hematology Education, Acute Leukemia Forum, Agrupacion Mexicana para el Estudio de la Hematologia, The France Foundation, Rambam Health Care, Chinese Medical Association, European School of Haematology, Medscape, TRM Oncology, National Comprehensive Cancer Network, Lankenau Medical Center, and the Hospital for Sick Children.

REFERENCES

1. Patel JP, Gönen M, Figueroa ME, et al: Prognostic relevance of integrated genetic profiling in acute myeloid leukemia. N Engl J Med 366:1079-1089, 2012.

2. Papaemmanuil E, Gerstung M, Bullinger L, et al: Genomic classification and prognosis in acute myeloid leukemia. N Engl J Med 374:2209-2221, 2016.

3. Hourigan CS, Karp JE: Minimal residual disease in acute myeloid leukaemia. Nat Rev Clin Oncol 10:460-471, 2013.

4. Ivey A, Hills RK, Simpson MA, et al: Assessment of minimal residual disease in standard-risk AML. N Engl J Med 374:422-433, 2016.

5. Krönke J, Schlenk RF, Jensen KO, et al: Monitoring of minimal residual disease in NPM1-mutated acute myeloid leukemia. J Clin Oncol 29:2709-2716, 2011.

6. Klco JM, Miller CA, Griffith M, et al: Association between mutation clearance after induction therapy and outcomes in acute myeloid leukemia. JAMA 314:811-822, 2015.

7. Hirsch P, Tang R, Abermil N, et al: Precision and prognostic value of clone-specific minimal residual disease in acute myeloid leukemia. Haematologica 102:1227-1237, 2017.

8. Schuurhuis GJ, Heuser M, Freeman S, et al: Minimal/measurable residual disease in AML: A consensus document from European LeukemiaNet Working Party. Blood 131:1275-1291, 2018.

9. Jongen-Lavrencic M, Grob T, Hanekamp D, et al: Molecular minimal residual disease in acute myeloid leukemia. N Engl J Med 378:1189-1199, 2018.

10. Getta BM, Devlin SM, Levine RL, et al: Multicolor flow cytometry and multigene next-generation sequencing are complementary and highly predictive for relapse in acute myeloid leukemia after allogeneic transplantation. Biol Blood Marrow Transplant 23:1064-1071, 2017.

11. Jaiswal S, Fontanillas P, Flannick J, et al: Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med 371:2488-2498, 2014.

12. Genovese G, Kähler AK, Handsaker RE, et al: Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N Engl J Med 371:2477-2487, 2014.

13. Steensma DP, Bejar R, Jaiswal S, et al: Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes. Blood 126:9-16, 2015.

14. Jaiswal S, Natarajan P, Silver AJ, et al: Clonal hematopoiesis and risk of atherosclerotic cardiovascular disease. N Engl J Med 377:111-121, 2017.


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