bims-fragic Biomed News
on Fragmentomics
Issue of 2026–06–07
two papers selected by
Laura Mannarino, Humanitas Research



  1. J R Soc Interface. 2026 Jun 03. pii: 20250349. [Epub ahead of print]23(239):
      Cell-free DNA (cfDNA) is a promising biomarker for cancer detection. However, the sources of elevated cfDNA in patients with early-stage cancer, and the mechanisms by which cfDNA is shed into, and subsequently cleared from the circulation are still poorly understood. Using a rich dataset of cfDNA in healthy individuals and early-stage cancer patients, we find a multiplicative increase in cfDNA concentration in the presence of cancer. This increase is cancer type-specific, ranging from an approximately 1.3-fold increase in lung cancer to an approximately 12-fold increase in liver cancer, and does not originate from the tumour, but from healthy tissue. Employing an additional dataset reporting the tissue of origin of cfDNA, we observe a significant increase in the correlation between cfDNA originating from leukocytes and from non-leukocyte sources in cancer patients. Introducing a mathematical model for cfDNA dynamics, we find that the observed correlation can be explained by a saturation mechanism in cfDNA clearance. Saturation in clearance implies that smaller increases in cfDNA shedding may lead to proportionally larger increases in cfDNA levels. Our findings quantify cfDNA dynamics in patients with cancer, with implications for improving the accuracy of liquid biopsies for early cancer detection.
    Keywords:  cell-free DNA; early cancer detection; liquid biopsy
    DOI:  https://doi.org/10.1098/rsif.2025.0349
  2. NPJ Precis Oncol. 2026 Jun 03.
      Diagnosing lymphoma traditionally relies on invasive tissue biopsies, which can yield insufficient material for histopathological evaluation and carry a risk of complications. Minimally invasive assessment of cell-free DNA (cfDNA) in plasma offers a promising alternative for lymphoma detection that could aid the rapid evaluation of malignant vs. benign lymphadenopathy. Here, we examine the methylome of plasma samples from 165 lymphoma patients and 47 controls using cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq). Differential methylation analysis of a discovery cohort (142 out of 212 samples) revealed 13,897 hypermethylated genomic regions in lymphoma cases, which were subsequently used for classification using regularized binomial generalized linear models. In a validation cohort (70 samples), we identified lymphomas with an accuracy of 0.89, positive predictive value (PPV) of 0.90 and negative predictive value (NPV) of 0.87. cfDNA methylation scores were significantly associated with orthogonal measures of cfDNA tumor burden, stage, and clinical outcomes. Our results highlight the feasibility of cfDNA methylation profiling as a sensitive and minimally invasive method for detecting lymphoma.
    DOI:  https://doi.org/10.1038/s41698-026-01533-8