Cancers (Apr 2022)

Biological and Clinical Implications of Gene-Expression Profiling in Diffuse Large B-Cell Lymphoma: A Proposal for a Targeted BLYM-777 Consortium Panel as Part of a Multilayered Analytical Approach

  • Fleur A. de Groot,
  • Ruben A. L. de Groen,
  • Anke van den Berg,
  • Patty M. Jansen,
  • King H. Lam,
  • Pim G. N. J. Mutsaers,
  • Carel J. M. van Noesel,
  • Martine E. D. Chamuleau,
  • Wendy B. C. Stevens,
  • Jessica R. Plaça,
  • Rogier Mous,
  • Marie José Kersten,
  • Marjolein M. W. van der Poel,
  • Thomas Tousseyn,
  • F. J. Sherida H. Woei-a-Jin,
  • Arjan Diepstra,
  • Marcel Nijland,
  • Joost S. P. Vermaat

DOI
https://doi.org/10.3390/cancers14081857
Journal volume & issue
Vol. 14, no. 8
p. 1857

Abstract

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Gene-expression profiling (GEP) is used to study the molecular biology of lymphomas. Here, advancing insights from GEP studies in diffuse large B-cell lymphoma (DLBCL) lymphomagenesis are discussed. GEP studies elucidated subtypes based on cell-of-origin principles and profoundly changed the biological understanding of DLBCL with clinical relevance. Studies integrating GEP and next-generation DNA sequencing defined different molecular subtypes of DLBCL entities originating at specific anatomical localizations. With the emergence of high-throughput technologies, the tumor microenvironment (TME) has been recognized as a critical component in DLBCL pathogenesis. TME studies have characterized so-called “lymphoma microenvironments” and “ecotypes”. Despite gained insights, unexplained chemo-refractoriness in DLBCL remains. To further elucidate the complex biology of DLBCL, we propose a novel targeted GEP consortium panel, called BLYM-777. This knowledge-based biology-driven panel includes probes for 777 genes, covering many aspects regarding B-cell lymphomagenesis (f.e., MYC signature, TME, immune surveillance and resistance to CAR T-cell therapy). Regarding lymphomagenesis, upcoming DLBCL studies need to incorporate genomic and transcriptomic approaches with proteomic methods and correlate these multi-omics data with patient characteristics of well-defined and homogeneous cohorts. This multilayered methodology potentially enhances diagnostic classification of DLBCL subtypes, prognostication, and the development of novel targeted therapeutic strategies.

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