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Updated: May 26, 2025

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
Published on: December 28, 2015
The mutational landscape and its longitudinal dynamics in relapsed and refractory classic Hodgkin lymphoma
Hanno Witte1,2,3, Axel Künstner4,5,6, Thomas Hahn4,7,8
1University Cancer Center Schleswig-Holstein, University Hospital of Schleswig-Holstein, Campus Lübeck, 23538, Lübeck, Germany. hanno.witte@uni-ulm.de.
Abstract:
In classic Hodgkin-lymphoma (cHL), only a few cases recur, and only a limited fraction of patients is primary-refractory to standard-polychemotherapy. Underlying genomic features of unfavorable clinical courses remain sparsely characterized. Here, we investigated the genomic characteristics of primary-refractory/relapsed cHL in contrast with responders. Therefore, ultra-deep next-generation panel-sequencing was performed on a total of 59 FFPE-samples (20 responders, 26 relapsed (rHL: 11 initial-diagnosis, 15 relapse) and 13 primary-refractory (prHL: 8 initial-diagnosis, 5 progression) from 44 cHL-patients applying a hybrid-capture approach. We compared samples associated with distinct disease courses concerning their oncogenic drivers, mutational signatures, and perturbed pathways. Compared to responders, mutations in genes such as PMS2, PDGFRB, KAT6A, EPHB1, and HGF were detected more frequently in prHL/rHL. Additionally, we observed that in rHL or prHL, BARD1-mutations occur, whereas ETV1, NF1, and MET-mutations were eliminated through clonal selection. A significant enrichment of non-synonymous variants was detected in prHL compared to responders and a significant selection process in favor of NOTCH-pathway mutations driving rHL or prHL was observed. However, our analysis revealed a negative selection process for non-synonymous variants affecting the hippo-pathway. This study delineates distinct mutational signatures between responders and rHL/prHL, whilst illustrating longitudinal dynamics in mutational profiles using paired samples. Further, several exploitable therapeutic vulnerabilities for rHL and prHL were identified.
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