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Novel insights into Hodgkin lymphoma biology by single cell analysis.

Tomohiro AokiChristian Steidl
Published in: Blood (2022)
The emergence and rapid development of single cell technologies marks a paradigm shift in cancer research. Various technology implementations represent powerful tools to understand cellular heterogeneity, identify minor cell populations that were previously hard to detect and define, and to make inferences about cell-to-cell interactions at single cell resolution. Applied to lymphoma, recent advances in single cell RNA sequencing have broadened opportunities to delineate previously underappreciated heterogeneity of malignant cell differentiation states and presumed cell of origin, and to describe the composition and cellular subsets in the ecosystem of the tumor microenvironment (TME). Clinical deployment of an expanding armamentarium of immunotherapy options that rely on targets and immune cell interactions in the TME, emphasizes the requirement for a deeper understanding of immune biology in lymphoma. In particular, classic Hodgkin lymphoma (CHL) can serve as a study paradigm due to its unique TME, featuring infrequent tumor cells among numerous non-malignant immune cells with significant inter- and intra-patient variability. Synergistic to advances in single cell sequencing, multiplexed imaging techniques have added a new dimension to describing cellular crosstalk in various lymphoma entities. Here, we comprehensively review recent progress utilizing novel single cell technologies with an emphasis on TME biology of CHL as an application field. The described technologies, that are applicable to peripheral blood, fresh tissues and formalin-fixed samples, hold the promise to accelerate biomarker discovery for novel immunotherapeutic approaches, and to serve as future assay platforms for biomarker-informed treatment selection including immunotherapies.
Keyphrases
  • single cell
  • rna seq
  • high throughput
  • hodgkin lymphoma
  • peripheral blood
  • diffuse large b cell lymphoma
  • gene expression
  • stem cells
  • machine learning
  • climate change
  • high resolution
  • case report
  • single molecule