Published October 28, 2019 | Version v1
Journal article Open

Measurable residual disease monitoring for patients with acute myeloid leukemia following hematopoietic cell transplantation using error corrected hybrid capture next generation sequencing

Description

Improved systems for detection of measurable residual disease (MRD) in acute myeloid leukemia (AML) are urgently needed, however attempts to utilize broad-scale next-generation sequencing (NGS) panels to perform multi-gene surveillance in AML post-induction have been stymied by persistent premalignant mutation-bearing clones. We hypothesized that this technology may be more suitable for evaluation of fully engrafted patients following hematopoietic cell transplantation (HCT). To address this question, we developed a hybrid-capture NGS panel utilizing unique molecular identifiers (UMIs) to detect variants at 0.1% VAF or below across 22 genes frequently mutated in myeloid disorders and applied it to a retrospective sample set of blood and bone marrow DNA samples previously evaluated as negative for disease via standard-of-care short tandem repeat (STR)-based engraftment testing and hematopathology analysis in our laboratory. Of 30 patients who demonstrated trackable mutations in the 22 genes at eventual relapse by standard NGS analysis, we were able to definitively detect relapse-associated mutations in 18/30 (60%) at previously disease-negative timepoints collected 20–100 days prior to relapse date. MRD was detected in both bone marrow (15/28, 53.6%) and peripheral blood samples (9/18, 50%), while showing excellent technical specificity in our sample set. We also confirmed the disappearance of all MRD signal with increasing time prior to relapse (>100 days), indicating true clinical specificity, even using genes commonly associated with clonal hematopoiesis of indeterminate potential (CHIP). This study highlights the efficacy of a highly sensitive, NGS panel-based approach to early detection of relapse in AML and supports the clinical validity of extending MRD analysis across many genes in the post-transplant setting.

Data availability

Data cannot be shared publicly because of human subject clinical data. Data are available from the University of Chicago IRB office for researchers who meet the criteria for access to confidential data. For original data, please contact the Director of Regulatory Compliance for Human Subjects at the Office of Clinical Research, Millie Maleckar (mmalecka@bsd.uchicago.edu). The data set should be identified as Segal_MRA dataset.

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Additional details

Identifiers

DOI
10.1371/journal.pone.0224097
Other
oai:uchicago.tind.io:6275

Funding

AbbVie (United States)
UChicago collaboration grant

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Family Medicine, Genetics, Genomics, and Systems Biology, Pathology
Center(s) or Institute(s)
Center for Research Informatics