Minimal Residual Disease in Acute Myeloid Leukemia Using a Difference from Normal Approach Is Predictive of Outcome
Authors: Kakirde Chinmayee , Kodgule Rohan , Raval Goutham , Talole Sanjay , Kadechkar Shraddha , Chatterjee Gaurav , Yajamanam Badrinath , Ghoghale Sitaram , Deshpande Nilesh , Amare Kadam Pratibha , Menon Hari , Sengar Manju , Khattry Navin , Jain Hasmukh , Bagal Bhausaheb , Tembhare Prashant , Gujral Sumeet , Patkar Nikhil 
Published: October 2019

Introduction: One of the mainstays of chemotherapy in acute myeloid leukemia (AML), other than acute promyelocytic leukemia, is induction with a goal to achieve morphological complete remission (CR) as evident by less than 5% blasts. Post remission strategies then focus on either consolidation chemotherapy or allogeneic bone marrow transplantation (aBMT). However, not all patients by this remission criterion achieve long term remission and a subset of patients relapse. This relapse originates from further expansion chemoresistant clones. Detection of minimal residual disease (MRD) following chemotherapy, early in the course of treatment, is highly predictive of outcome and offers a window of opportunity to intensify treatment and prevent relapse. Here, we describe assessment of immunophenotypic MRD using a 10-colour two tube assay and a "difference from normal" approach.

Methods: We accrued 100 consecutive patients of adult (>18 years) AML, other than with t(15;17), over a 14 month period after obtaining informed consent. All patients received "3+7" induction therapy with daunorubicin and cytarabine. If patients were in morphological CR at end of induction, they either received 3 courses of 12-18 gm/m2 high dose cytarabine (HiDAC) or aBMT if feasible.MRD testing was done at two time points, post induction and post 1st Cycle HiDac using a two tube 10 colour assay. (CD15, CD13, CD19, CD34, CD56, CD7, CD45, CD11b, HLA-DR, CD117, CD14, CD123, CD64, CD33, CD36 & CD38). A minimum of one million events were acquired per tube on a Navios flow cytometer. Identical panel was used at MRD time points as well as on the diagnostic sample. Analysis of MRD was done using Kaluza 1.3 by a difference from normal approach that focused on the development of progenitors to monocytes. Conventional karyotyping and FISH was done as per standard recommendations and patients were classified into favorable, intermediate and poor cytogenetic risk. The presence of FLT3-ITD, NPM1 and CEBPAmutations was detected by a fragment length analysis based assay. Overall survival (OS) was calculated from start of induction therapy to time of last follow up or death. Relapse free survival (RFS) was calculated after achieving of 1st remission (CR) till relapse or death or last follow up if in CR. Results of the MRD assays, cytogenetic and molecular risk groups were analyzed for their impact on OS and DFS.

Results: A total of 100 AML patients were treated and followed up over a 14 month period. Based on cytogenetics, 36.7% were classified as favorable risk whereas 54.1% and 9.2% were intermediate and poor risk respectively. FLT3-ITD, NPM1 and CEBPA mutations were harbored by 9%, 19% and 8% of patients respectively. The OS was 63% and RFS was 50% with a median follow up of 6 months. Of these, 24 had induction death and 17 had refractory disease. Post induction MRD was assessed in 70 patients of which 25 (35.7%) had detectable residual disease (range 0.02-55%, median:1.5%). Post consolidation MRD was assessed in 49 patients of which 14 (28.6%) were MRD positive (range 0.002-7.7%, median: 0.03%). Favorable risk cytogenetics was predictive of better RFS (p=0.007) but not OS. FLT3-ITD positive status was associated with worse OS (p=0.01) but not RFS. Patients harboring MRD at the end of induction were associated with worse OS (p=0.08) & RFS (p=0.04), whereas post consolidation positive MRD status was strongly associated with inferior RFS (p=0.04).

Conclusion: Our data is in agreement with other studies that determination of immunophenotypic MRD is extremely important in predicting outcome. AML MRD is a very useful guide for guiding post remission strategies in AML and should be incorporated into routine treatment algorithms.

Acknowledgments: Dr Nikhil Patkar is supported by the Wellcome Trust - DBT / India Alliance through an Intermediate Fellowship for Clinicians and Public Health Researchers. This research is supported through an India Alliance grant (IA/CPHI/14/1/501485).

Disclosures

Patkar: Wellcome Trust-DBT India Alliance: Research Funding.