Individualizing treatment is key to improve outcome and reduce long-term side-effects in any cancer. In Hodgkin lymphoma (HL), individualization of treatment is hindered by a lack of genomic characterization and technology for sensitive, molecular response assessment.
Sequencing of cell-free (cf)DNA is a powerful strategy to understand an individual cancer genome and can be used to develop assays for extremely sensitive disease monitoring. In HL, a high proportion of cfDNA is tumor-derived making it a highly relevant disease model to study the role of cfDNA sequencing in cancer.
Here, we introduce our targeted cfDNA sequencing platform and present the largest genomic landscape of HL to date, which was entirely derived by cfDNA sequencing. We comprehensively genotype and assess minimal residual disease in 324 samples from 121 patients, presenting an integrated landscape of mutations and copy number variations in HL. In addition, we perform a deep analysis of mutational processes driving HL, investigate the clonal structure of HL and link several genotypes to HL phenotypes and outcome. Finally, we show that minimal residual disease assessment by repeat cfDNA sequencing as early as a week after treatment initiation is feasible and predicts overall treatment response allowing highly improved treatment guidance and relapse prediction. Our study also serves as a blueprint showcasing the utility of our platform for other cancers with similar therapeutic challenges.
Exhaustive circulating tumor DNA sequencing reveals the genomic landscape of Hodgkin lymphoma and facilitates ultrasensitive detection of minimal residual disease