Abstract Introduction: Early relapse limits durable remissions in multiple myeloma (MM). Cell-free DNA (cfDNA) fragment patterns capture tumor burden and nucleosome positioning. We tested whether a fragmentomics signature trained at MRD time points stratifies progression-free survival (PFS) when applied to pretreatment plasma. Methods: We performed 30-40× whole-genome sequencing of plasma cfDNA from 43 newly diagnosed MM patients, with 65 additional MRD timepoint samples from 41 of those patients (post-ASCT n=30; 1-year maintenance n=30; other maintenance n=5) across eight Canadian sites (TFRIM4 and IMMAGINE studies) and one U.S. site (Mayo SPORE). MRD testing used multiparameter flow cytometry for all follow-up samples (n=65) and clonoSEQ in a subset (n=31). Logistic and elastic-net models were trained at MRD timepoints on fragmentomics features (short-fragment burden; a combined model integrating fragment-length distributions with inferred nucleosome positioning at MM-specific chromatin accessibility regions Ordoñez et al., Genome Res. 2020). A decision threshold was fixed by the Youden index during training and applied unchanged to diagnosis samples. PFS was analyzed by Kaplan-Meier, log-rank, and Cox models. Results: After a median follow-up of 49.1 months, 16 of 43 patients (37%) progressed. Using the prespecified locked threshold, patients classified as MRD+ by the proportion-of-short-fragments model had significantly shorter PFS than MRD- patients (HR = 5.12; 95% CI 1.16-22.57; log-rank p = 0.016), with median PFS of 49.2 months for MRD+ cases versus not reached for the MRD- group. Fixed-horizon PFS favored MRD- samples at 24/36/48 months (100/94/87% vs 85/81/53% for MRD+). A combined model integrating weighted fragment lengths with inferred nucleosome positioning also separated outcomes (log-rank p=0.054); the Cox HR was not estimable because no MRD- patients relapsed. At 24, 36, and 48 months, baseline MRD positivity by the short-fragment model identified 100%, 83%, and 86% of patients who relapsed within those intervals (specificity 44%, 43%, and 52%), while the combined model detected all early relapses across the same horizons (specificity 15-21%), indicating consistently high sensitivity but modest specificity for predicting early progression. Conclusions: A cfDNA fragmentomics signature trained at MRD time points stratified PFS when applied to diagnostic plasma, identifying patients at risk of early relapse. Short-fragment burden was most discriminative, and a combined model with nucleosome positioning recapitulated it with higher sensitivity, albeit lower specificity. These data support cfDNA fragmentomics as a practical liquid-biopsy risk biomarker in MM and suggest higher signals may proxy aggressive disease with greater tumor shedding and chromatin disorganization. Future work will validate findings in larger cohorts and integrate cytogenetic and immune features. Citation Format: Dor David Abelman, Jenna Eagles, Aimee Wong, Saumil Shah, Jeffrey Bruce, Stephanie Pedersen, David S. Scott, Cecilia Bonolo de Campos, Signy Chow, Darrell White, Irwindeed Sandhu, Kevin Song, Esteban Braggio, Shaji Kunnathu Kumar, Alli Murugesan, Tony Reiman, A. Keith Stewart, Suzanne Trudel, Trevor J. Pugh. Baseline cfDNA fragmentomics identifies multiple myeloma patients at risk of early progression abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2597.
Abelman et al. (Fri,) studied this question.