Improving treatment of Hodgkin Lymphoma with molecular risk classification and highly sensitive residual disease monitoring by circulating cell-free DNA sequencing

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Hodgkin lymphoma (HL) is a B cell-derived, hematological malignancy. A remarkable feature of HL is that the pathognomonic, malignant Hodgkin and Reed-Sternberg (HRS) cells make up only 1-10% of the tumor tissue while the rest is composed of a complex microenvironment supporting tumor growth. This paucity of HRS cells in the tumor biopsy has made understanding the genetic drivers of HL with traditional approaches difficult.Two challenges define the current medical need in HL. First, aggressive, multi-agent chemotherapy treatment leads to severe early and late toxicities. Second, in about 20-30% of patients the first treatment attempt is not successful and the patients ultimately relapse and often die. Currently, treatment stratification is based purely on clinical risk factors; a molecular risk classification based on presence or absence of genetic features is currently lacking. Thus, to improve treatment outcome and reduce both early and late toxicities, we need to identify molecularly defined subgroups of HL and individualize treatment.Cell-free DNA in the circulation of cancer patients is released from apoptotic cells and contains circulating tumor-derived DNA (ctDNA) in cancer patients reflecting the genetics of the tumor.In two separate projects, we were able to show that ctDNA can be successfully used to detect tumor-associated mutations and copy number alterations in HL. One of these projects is the DFG previous project that we plan to extend with this application. In this project we performed whole-exome sequencing using ctDNA in 166 HLs. The other project is an independent project of our group in which we developed a platform to genotype HL based on a targeted ctDNA sequencing panel. In this study we also developed an approach to detect minimal residual disease (MRD) in HL patients in follow-up samples during and after treatment. A manuscript presenting the results of this project is published as a preprint (Sobesky et al., medRxiv 2021) and currently under review. Our overarching aim for this extension is to develop a molecular risk classification to improve prognostication in HL. Furthermore, we will expand on this with a dynamic risk model including depth of early molecular response to treatment using the MRD assay developed by us. In detail, the following aims will be addressed: (1) We will identify molecular signatures detectable by liquid biopsy that are associated with a favorable or adverse prognosis in newly diagnosed HL, (2) we will validate this signature in a separate cohort of relapsed and refractory HL and (3) we will refine these response signatures by dynamic risk profiling including early minimal residual disease assessment.Altogether, the extension project is likely to deliver a molecular risk classification of HL while at the same time exploring dynamic risk modelling during HL treatment as a potential future paradigm shift in HL treatment.