Deciphering the Genomics of Aggressive non-Hodgkin Lymphoma

Background To unravel the biological basis of aggressive non-Hodgkin lymphomas (aNHL), we and others have performed large mutational profiling studies. These reveal considerable genetic heterogeneity and identify hundreds of recurrent genetic alterations. These mutations are not independently distributed, allowing cases to be clustered into predicted genomic subtypes.

Gene expression and survival differences support the concept that these subtypes represent biologically distinct diseases, suggesting optimal treatment may differ between subtypes. There is no shortage of novel, therapeutic agents in development for lymphoma. However, it remains far from clear how these should be targeted to molecular subtypes or individual patients.

The large number of theoretical drug combinations, combined with the complex genetic heterogeneity makes it impossible to address these questions by empiric testing in clinical trials.

Therefore, we require better preclinical experimental systems to model the effects of mutational repertoires and enable their interrogation.

My group has developed a novel experimental system that allows the creation of mutation-customised models of lymphoma, and provides the ability to study many hundreds of mutational combinations simultaneously.

Aims 1) Dissect the GNA13 pathway as a potential therapeutic target in aNHL. 2) Perform comprehensive, combinatorial mutant open reading frame (mORF) screening of 1,000 recurrent mutations in human GC B cells ex vivo and in vivo. 3) Combine genetic perturbation and single cell transcriptional profiling of mORF-transduced single cells with a systems biology model to condense genetic heterogeneity into targetable oncogenic pathways. 4) Develop a highly sensitive plasma DNA sequencing assay to capture the evolution of genetic heterogeneity during lymphoma treatment.

Methods We will capitalise on a system we developed for ex vivo expansion of primary human B cells in a co-culture designed to mimic the germinal centre microenvironment.

Genetic manipulation of lymphoma driver genes allows us to generate immortalised cultures and “synthetic” in vivo models that closely recapitulate aNHL. This will be combined with a lymphoma-specific mutant ORF library and single cell sequencing technologies.

How research will be used By understanding how genetic alterations co-operate to drive lymphoma and how mutational profiles evolve during therapy, our results will: 1) Elucidate the molecular basis of recently described genomic subtypes 2) Propose therapeutic stratification for future trials 3) Identify the pathways that should be optimally targeted for individual disease subtypes 4) Determine how we should assess response to treatment at the subclonal level.

Results will therefore guide the design and interpretation of the next generation of lymphoma clinical trials.