Literature DB >> 28096087

Diffuse large B-cell lymphoma genotyping on the liquid biopsy.

Davide Rossi1,2, Fary Diop1, Elisa Spaccarotella1, Sara Monti1, Manuela Zanni1, Silvia Rasi1, Clara Deambrogi1, Valeria Spina1,2, Alessio Bruscaggin1,2, Chiara Favini1, Roberto Serra3, Antonio Ramponi4, Renzo Boldorini4, Robin Foà5, Gianluca Gaidano1.   

Abstract

Accessible and real-time genotyping for diagnostic, prognostic, or treatment purposes is increasingly impelling in diffuse large B-cell lymphoma (DLBCL). Cell-free DNA (cfDNA) is shed into the blood by tumor cells undergoing apoptosis and can be used as source of tumor DNA for the identification of DLBCL mutations, clonal evolution, and genetic mechanisms of resistance. In this study, we aimed at tracking the basal DLBCL genetic profile and its modification upon treatment using plasma cfDNA. Ultra-deep targeted next generation sequencing of pretreatment plasma cfDNA from DLBCL patients correctly discovered DLBCL-associated mutations that were represented in >20% of the alleles of the tumor biopsy with >90% sensitivity and ∼100% specificity. Plasma cfDNA genotyping also allowed for the recovery of mutations that were undetectable in the tissue biopsy, conceivably because, due to spatial tumor heterogeneity, they were restricted to clones that were anatomically distant from the biopsy site. Longitudinal analysis of plasma samples collected under rituximab-cyclophosphamide-doxorubicin-vincristine-prednisone (R-CHOP) chemotherapy showed a rapid clearance of DLBCL mutations from cfDNA among responding patients. Conversely, among patients who were resistant to R-CHOP, basal DLBCL mutations did not disappear from cfDNA. In addition, among treatment-resistant patients, new mutations were acquired in cfDNA that marked resistant clones selected during the clonal evolution. These results demonstrate that cfDNA genotyping of DLBCL is as accurate as genotyping of the diagnostic biopsy to detect clonally represented somatic tumor mutations and is a real-time and noninvasive approach to tracking clonal evolution and the emergence of treatment-resistant clones.
© 2017 by The American Society of Hematology.

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Year:  2017        PMID: 28096087     DOI: 10.1182/blood-2016-05-719641

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


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