Mutational Landscape and Tumor Burden Assessed by Cell-free DNA in Diffuse Large B-Cell Lymphoma in a Population-Based Study
- 15 January 2021
- journal article
- research article
- Published by American Association for Cancer Research (AACR) in Clinical Cancer Research
- Vol. 27 (2), 513-521
- https://doi.org/10.1158/1078-0432.ccr-20-2558
Abstract
Purpose: We analyzed the utility of cfDNA in a prospective population-based cohort to determine the mutational profile, assess tumor burden, and estimate its impact in response rate and outcome in patients with DLBCL. Experimental Design: One-hundred patients were diagnosed with DLBCL during the study period. Mutational status of 112 genes was studied in cfDNA by targeted next-generation sequencing. Paired formalin-fixed paraffin-embedded samples and volumetric PET/CT were assessed when available. Results: Appropriate cfDNA to perform the analyses was obtained in 79/100 cases. At least one mutation could be detected in 69/79 cases (87%). The sensitivity of cfDNA to detect the mutations was 68% (95% CI: 56.2-78.7). The mutational landscape found in cfDNA samples was highly consistent with that shown in the tissue and allowed genetic classification in 43% of the cases. A higher amount of ctDNA significantly correlated with clinical parameters related to tumor burden (elevated LDH and β2-microglobulin serum levels, advanced stage, and high-risk IPI) and total metabolic tumor volume assessed by PET/CT. In patients treated with curative intent, high ctDNA levels (>2.5 log hGE/mL) were associated with lower complete response (65% vs. 96%, Pvs. 85%, P=0.038) and overall survival (73% vs. 100%, P=0.007) at 2 years, although it did not maintain prognostic value in multivariate analyses. Conclusions: In a population-based prospective DLBCL series, cfDNA resulted an alternative source to estimate tumor burden and to determine the tumor mutational profile and genetic classification, which have prognostic implications and may contribute to a future tailored treatment.Other Versions
Funding Information
- Ministerio de Ciencia e Innovación European Regional Development Fund (PI16/00420, PI19/00887)
- Ministerio de Ciencia e Innovación European Regional Development Fund (RTI2018-094274-B-I00, SAF2016-81860-REDT)
- CIBERONC (CB16/12/00334, CB16/12/00225)
- Generalitat de Catalunya (SLT002/16/00374)
- Canadian Institutes of Health Research (825835)
- Ministerio de Ciencia e Innovación (BES-2016-076372)
- Generalitat de Catalunya (PERIS IPFE SLT006/17/301)
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