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Meriranta L, Alkodsi A, Pasanen A, et al. Molecular features encoded in the ctDNA reveal heterogeneity and predict outcome in high-risk aggressive B-cell lymphoma. Blood. 2021;doi: 10.1182/blood.2021012852.
Meriranta, L., Alkodsi, A., Pasanen, A., Lepistö, M., Mapar, P., Blaker, Y. N., Jørgensen, J. M., Karjalainen-Lindsberg, M. L., Fiskvik, I., Mikalsen, L. T. G., Autio, M., Björkholm, M., Jerkeman, M., Fluge, �. �., Brown, P., Jyrkkiö, S., Holte, H., Pitkänen, E., Ellonen, P., & Leppa, S. (2021). Molecular features encoded in the ctDNA reveal heterogeneity and predict outcome in high-risk aggressive B-cell lymphoma. Blood, . https://doi.org/10.1182/blood.2021012852
Meriranta, Leo, et al. "Molecular features encoded in the ctDNA reveal heterogeneity and predict outcome in high-risk aggressive B-cell lymphoma." Blood vol. (2021). doi: https://doi.org/10.1182/blood.2021012852
Meriranta L, Alkodsi A, Pasanen A, Lepistö M, Mapar P, Blaker YN, Jørgensen JM, Karjalainen-Lindsberg ML, Fiskvik I, Mikalsen LTG, Autio M, Björkholm M, Jerkeman M, Fluge Ø, Brown P, Jyrkkiö S, Holte H, Pitkänen E, Ellonen P, Leppa S. Molecular features encoded in the ctDNA reveal heterogeneity and predict outcome in high-risk aggressive B-cell lymphoma. Blood. 2021 Dec 21; doi: 10.1182/blood.2021012852. Epub 2021 Dec 21. PMID: 34932792.
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Blood. 2021 Dec 21; doi: 10.1182/blood.2021012852. Epub 2021 Dec 21.

Molecular features encoded in the ctDNA reveal heterogeneity and predict outcome in high-risk aggressive B-cell lymphoma.

Blood

Leo Meriranta, Amjad Alkodsi, Annika Pasanen, Maija Lepistö, Parisa Mapar, Yngvild Nuvin Blaker, Judit Meszaros Jørgensen, Marja-Liisa Karjalainen-Lindsberg, Idun Fiskvik, Lars Tore Gyland Mikalsen, Matias Autio, Magnus Björkholm, Mats Jerkeman, Øystein Fluge, Peter Brown, Sirkku Jyrkkiö, Harald Holte, Esa Pitkänen, Pekka Ellonen, Sirpa Leppa

Affiliations

  1. Helsinki university, Helsinki, Finland.
  2. University of Helsinki and iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland.
  3. University of Helsinki, Finland.
  4. Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science HILIFE, Helsinki, Finland.
  5. University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science HILIFE, Helsinki, Finland.
  6. Oslo University Hospital, Oslo, Norway.
  7. Aarhus University Hospital, Aarhus, Denmark.
  8. Helsinki University Central Hospital, Helsinki, Finland.
  9. Oslo University Hospital, oslo, Norway.
  10. Oslo University Hospital, and Oslo Metropolitan University, Oslo, Norway.
  11. University of Helsinki, Helsinki, Finland.
  12. Clinical Medicine Unit, Stockholm, Sweden.
  13. Skane University Hospital and Lund University, Lund, Sweden.
  14. Haukeland University Hospital, Bergen, Norway.
  15. Rigshospitalet, Copenhagen, Denmark.
  16. Turku University Hospital, Turku, Finland.
  17. Institute for molecular medicine Finland, Helsinki, Finland.
  18. University of Helsinki, Helsinki University Hospital Comprehensive Cancer Centre and iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland.

PMID: 34932792 DOI: 10.1182/blood.2021012852

Abstract

Inadequate molecular and clinical stratification of the patients with high-risk diffuse large B-cell lymphoma (DLBCL) is a clinical challenge hampering the establishment of personalized therapeutic options. We studied the translational significance of liquid biopsy in a uniformly treated trial cohort. Pretreatment circulating tumor DNA (ctDNA) revealed hidden clinical and biological heterogeneity, and high ctDNA burden determined increased risk of relapse and death independently of conventional risk factors. Genomic dissection of pretreatment ctDNA revealed translationally relevant phenotypic, molecular, and prognostic information that extended beyond diagnostic tissue biopsies. During therapy, chemorefractory lymphomas exhibited diverging ctDNA kinetics, whereas end-of-therapy negativity for minimal residual disease characterized cured patients and resolved clinical enigmas, including false residual PET positivity. Furthermore, we discovered fragmentation disparities in the cell-free DNA that characterize lymphoma-derived ctDNA and, as a proof-of-concept for their clinical application, utilized machine learning to show that end-of-therapy fragmentation patterns predict outcome. Altogether, we have discovered novel molecular determinants in the liquid biopsy that can non-invasively guide treatment decisions.

Copyright © 2021 American Society of Hematology.

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