Abstract 3252: Circulating tumor DNA (ctDNA) enables enhanced measurable residual disease (MRD) detection and non-invasive clonal profiling in acute myeloid leukemia (AML)
Abstract Introduction: Current MRD detection methods for AML (multiparameter flow cytometry and single-gene assays) are limited by suboptimal sensitivity, narrow coverage for molecular monitoring and clonal resolution, and/or reliance on invasive bone marrow biopsies. To address these issues, we developed AML-CAPP-Seq, a ctDNA-based assay leveraging a customized Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) approach to detect MRD and track clonal evolution. Methods: AML-CAPP-Seq integrates patient-specific hybrid capture panels (based on whole exome sequencing, WES) with a shared panel of 58 recurrently mutated ‘canonical’ AML genes to generate personalized MRD assays. We analyzed > 1000 biological samples from 56 AML patients (median follow-up: 19.5 months) and 21 healthy controls, comparing MRD detection in bone marrow mononuclear cells (BMMCs), peripheral blood mononuclear cells (PBMCs), and cell-free DNA from plasma (PB-ctDNA) and bone marrow (BM-ctDNA) against standard-of-care (SOC) MRD assays. Results: WES identified a median of 32.5 tumor single nucleotide variants (SNVs) per patient, allowing MRD detection in 100% of patients with a detection limit of <0.01% tumor fraction. Use of only canonical AML genes reduced coverage to 84%, while SOC single gene molecular MRD methods were applicable to just 32% of patients. Tumor burden in PB-ctDNA was highly correlated (r > 0.9) with other compartments and showed significantly higher tumor DNA levels at low disease burden states (median 3.8- and 2.9-fold enrichment compared to PBMCs and BMMCs respectively, p < 0.02), particularly in cases of extramedullary involvement. PB-ctDNA detected residual disease in 98.5% of samples with +MRD by SOC marrow-based methods and identified MRD in 47.4% of SOC-negative samples. Of these, 46.8% were from patients who later relapsed, while 50% ultimately reached MRD-negative status after further therapy. In CR1 patients (n = 48), PB-ctDNA identified MRD in 89.3% of those who relapsed, compared to 46.4% by SOC MRD and 35.7% by flow alone. PB-ctDNA MRD robustly predicted relapse-free survival (RFS, HR = 11.9, p = 7e-8) and overall survival (HR = 19.7, p = 5e-9), outperforming SOC methods (HR = 3.4, p = 5e-4 and HR = 5.2, p = 4e-6 respectively). For patients undergoing allogeneic SCT (n = 27), PB-ctDNA MRD clearance before and after SCT predicted RFS (p = 4e-4). Additionally, by monitoring dozens of tumor variants including indels and copy number alternations in a time-resolved fashion, AML-CAPP-Seq allowed detailed tracking of clonal dynamics over time. Conclusions: AML-CAPP-Seq offers ultrasensitive, noninvasive MRD detection in ctDNA superior to SOC methods without need for invasive BM evaluation. Personalized variant tracking ensures universal applicability across AML patients, enabling both MRD monitoring and clonal evolution profiling. Citation Format: Ruwan Gunaratne, Crystal Zhou, Sanjeeth Rajaram, Jesse W. Tai, Sky Kim, Kailee Tanaka, Charu Tiwari, Grace Gao, Mia Carleton, Brian J. Sworder, Gabriel N. Mannis, Michael S. Khodadoust, Ravindra Majeti, David Kurtz, Tian Yi Zhang. Circulating tumor DNA (ctDNA) enables enhanced measurable residual disease (MRD) detection and non-invasive clonal profiling in acute myeloid leukemia (AML) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3252.
Authors
- Crystal Zhou (ORCID: https://orcid.org/0000-0002-0763-0721)
- Charu Tiwari
- Ruwan Gunaratne (ORCID: https://orcid.org/0009-0003-9798-4922)
- Michael S. Khodadoust (ORCID: https://orcid.org/0000-0001-9061-7351)
- Jesse W. Tai (ORCID: https://orcid.org/0000-0001-6556-4171)
- Sky Kim
- Mia Carleton (ORCID: https://orcid.org/0000-0001-9993-9787)
- Brian J. Sworder (ORCID: https://orcid.org/0000-0002-5902-5507)
- David M. Kurtz (ORCID: https://orcid.org/0000-0002-6382-4651)
- Grace Gao (ORCID: https://orcid.org/0000-0002-1807-8637)
- Tian Yi Zhang (ORCID: https://orcid.org/0000-0002-6274-0763)
- Sanjeeth Rajaram (ORCID: https://orcid.org/0000-0002-9336-422X)
- Ravindra Majeti (ORCID: https://orcid.org/0000-0002-5814-0984)
- Kailee Tanaka
- Gabriel N. Mannis
Institutions
- University of California, Irvine (US)
- Stanford University (US)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1158/1538-7445.am2025-3252
- Citations
- 1
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.94