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Contributors

Phillip M. Galbo Jr.1, Blake Burgher1, Vincent Giamo1, Kiersten M. Miles1, Jesse Luce1, Eunice S. Wang1, Sean T. Glenn1, Carl M. Morrison1

1Roswell Park Comprehensive Cancer Center, Department of Pathology, New York, USA

Introduction

Roswell Park Comprehensive Cancer Center (RPCCC) has been a leader in cancer transplantation for decades and was one of the earliest centres to integrate transplant therapy into routine cancer care. Since initiating its transplant program in 1977, the institution has completed more than 3,450 procedures and has continued to advance techniques aimed at improving patient outcomes and transplant safety. Today, the center performs approximately 160 blood and bone marrow (BM) transplants each year.

Relapse after allogeneic haematopoietic cell transplantation (alloHCT) remains a major challenge in acute myeloid leukaemia (AML), with rates approaching 50% and poor survival outcomes after relapse. These limitations highlight the need for more sensitive measurable residual disease (MRD) detection methods to enable earlier intervention.

At RPCCC MRD is commonly assessed using multiparameter flow cytometry (MFC). Ultrahigh-sensitivity next-generation sequencing (UHS NGS) could offer improved MRD detection. However, there is no clear consensus on optimal timing for MRD monitoring during AML treatment.

In this study, a targeted myeloid MRD panel combined with UHS NGS was used to analyse longitudinal marrow samples from AML patients undergoing alloHCT at RPCCC. The approach demonstrated improved sensitivity for early relapse, showed potential lead-time advantages over MFC, and identified variant-based predictors.

Method

Study design

A total of 166 BM specimens were obtained from the RPCCC biobank where 49 adult patients with AML at multiple time points throughout their treatment course. All patients received induction therapy followed by alloHCT. Of these, 23 patients remained relapse-free for at least five years post-alloHCT (AML no-relapse cohort), whereas 26 patients experienced clinical relapse within two years of transplantation (AML relapse cohort). At the indicated time points, UHS NGS (blue) was performed and compared with standard-of-care MFC (dark green), across the treatment timeline.

Panel design and workflow

Libraries were generated using Oxford Gene Technology’s (OGT) Ultra low MRD NGS Complete Workflow Solution (Figure 2, left panel) together with the SureSeq™ Myeloid MRD Plus NGS Panel (Figure 2, right panel). Sequencing was conducted using 2 x 150 bp reads on an Illumina NextSeq High output® V2 300.

Bioinformatic analysis

The bioinformatics analysis was performed using Interpret NGS Analysis Software v. 4.0.128 (OGT) with a dedicated MRD hotspot monitoring protocol. The de-multiplexed reads were trimmed and aligned to the genome reference GRCh38 which was followed by base-error correction using UMI processing where singleton families were excluded from further analysis. The variant allele frequencies of the SNV/Indel hotspot variants being monitored were subjected to a proprietary background-error modelling statistic to exclude false positives.

Results

Post-induction, pre-alloHCT tumour-informed variant MRD detection is associated with increased relapse risk

Post-alloHCT longitudinal monitoring of tumour-informed variant MRD dynamically correlates with tumour relapse

UHS NGS MRD monitoring provides a lead-time advantage over standard-of-care MFC

Modelling of UHS NGS measurable reside disease threshold for relapse prediction

Discussion

  • Findings support a framework in which routine UHS NGS-based MRD testing is performed at defined post-induction and post-alloHCT intervals.
  • By defining optimal UHS NGS thresholds and clinically actionable time points for testing, our findings support the integration of UHS NGS MRD-guided surveillance into post-transplant management of AML and highlight the potential of UHS NGS to inform earlier intervention strategies aimed at improving patient outcomes.

Conclusions

  • Pre-alloHCT UHS NGS MRD strongly predict relapse risk at VAF thresholds as low as 0.1%.
  • UHS NGS detects relapse with a median lead time advantage of 89 days compared to MFC.
  • Integrated multi-timepoint MRD modelling improves risk stratification the strongest predictive

 

SureSeq: For Research Use Only; Not for Diagnostic Procedures.

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