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Genomic profiling for clinical decision making in lymphoid neoplasms

  • Laurence de Leval
  • , Ash A. Alizadeh
  • , P. Leif Bergsagel
  • , Elias Campo
  • , Andrew Davies
  • , Ahmet Dogan
  • , Jude Fitzgibbon
  • , Steven M. Horwitz
  • , Ari M. Melnick
  • , William G. Morice
  • , Ryan D. Morin
  • , Bertrand Nadel
  • , Stefano A. Pileri
  • , Richard Rosenquist
  • , Davide Rossi
  • , Itziar Salaverria
  • , Christian Steidl
  • , Steven P. Treon
  • , Andrew D. Zelenetz
  • , Ranjana H. Advani
  • Carl E. Allen, Stephen M. Ansell, Wing C. Chan, James R. Cook, Lucy B. Cook, Francesco d'Amore, Stefan Dirnhofer, Martin Dreyling, Kieron Dunleavy, Andrew L. Feldman, Falko Fend, Philippe Gaulard, Paolo Ghia, John G. Gribben, Olivier Hermine, Daniel J. Hodson, Eric D. Hsi, Giorgio Inghirami, Elaine S. Jaffe, Kennosuke Karube, Keisuke Kataoka, Wolfram Klapper, Won Seog Kim, Rebecca L. King, Young H. Ko, Ann S. LaCasce, Georg Lenz, José I. Martin-Subero, Miguel A. Piris, Stefania Pittaluga, Laura Pasqualucci, Leticia Quintanilla-Martinez, Scott J. Rodig, Andreas Rosenwald, Gilles A. Salles, Jesus San-Miguel, Kerry J. Savage, Laurie H. Sehn, Gianpietro Semenzato, Louis M. Staudt, Steven H. Swerdlow, Constantine S. Tam, Judith Trotman, Julie M. Vose, Oliver Weigert, Wyndham H. Wilson, Jane N. Winter, Catherine J. Wu, Pier L. Zinzani, Emanuele Zucca, Adam Bagg, David W. Scott
  • University of Lausanne
  • Stanford University
  • Mayo Clinic Scottsdale-Phoenix, Arizona
  • University of Barcelona
  • University of Southampton
  • Memorial Sloan-Kettering Cancer Center
  • Queen Mary University of London
  • Cornell University
  • Mayo Clinic Rochester, MN
  • Simon Fraser University
  • Provincial Health Services Authority
  • Aix Marseille University
  • IRCCS Istituto Europeo di Oncologia - Milano
  • Karolinska Institutet
  • Università della Svizzera italiana
  • August Pi i Sunyer Biomedical Research Institute
  • University of British Columbia
  • Dana-Farber Cancer Institute
  • Baylor College of Medicine
  • City of Hope National Med Center
  • Cleveland Clinic Foundation
  • Imperial College London
  • Aarhus University
  • University of Basel
  • Ludwig Maximilian University of Munich
  • Georgetown University
  • University of Tübingen
  • Hôpital Henri Mondor
  • University Paris-Est-Créteil
  • Vita-Salute San Raffaele University
  • Université Paris Cité
  • University of Cambridge
  • Wake Forest University
  • National Institutes of Health
  • Nagoya University
  • National Cancer Center Research Institute
  • Keio University
  • University Hospital Schleswig-Holstein
  • Sungkyunkwan University
  • Cheju Halla General Hospital
  • University of Münster
  • Fundacion Jimenez Diaz University Hospital
  • Columbia University
  • Brigham and Women’s Hospital
  • University of Würzburg
  • University of Navarra
  • University of Padua and Veneto Institute of Molecular Medicine
  • University of Pittsburgh
  • Alfred Health
  • Concord Repatriation General Hospital
  • University of Nebraska Medical Center
  • Northwestern University
  • University Hospital S. Orsola
  • University of Pennsylvania

Research output: Contribution to journal › Article › peer-review

Abstract

With the introduction of large-scale molecular profiling methods and high-throughput sequencing technologies, the genomic features of most lymphoid neoplasms have been characterized at an unprecedented scale. Although the principles for the classification and diagnosis of these disorders, founded on a multidimensional definition of disease entities, have been consolidated over the past 25 years, novel genomic data have markedly enhanced our understanding of lymphomagenesis and enriched the description of disease entities at the molecular level. Yet, the current diagnosis of lymphoid tumors is largely based on morphological assessment and immunophenotyping, with only few entities being defined by genomic criteria. This paper, which accompanies the International Consensus Classification of mature lymphoid neoplasms, will address how established assays and newly developed technologies for molecular testing already complement clinical diagnoses and provide a novel lens on disease classification. More specifically, their contributions to diagnosis refinement, risk stratification, and therapy prediction will be considered for the main categories of lymphoid neoplasms. The potential of whole-genome sequencing, circulating tumor DNA analyses, single-cell analyses, and epigenetic profiling will be discussed because these will likely become important future tools for implementing precision medicine approaches in clinical decision making for patients with lymphoid malignancies.

Original languageEnglish
Pages (from-to)2193-2227
Number of pages35
JournalBlood
Volume140
Issue number21
DOIs
StatePublished - 24 Nov 2022
Externally publishedYes

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