1. Academic Validation
  2. Peripheral T-cell lymphoma: molecular profiling recognizes subclasses and identifies prognostic markers

Peripheral T-cell lymphoma: molecular profiling recognizes subclasses and identifies prognostic markers

  • Blood Adv. 2021 Dec 28;5(24):5588-5598. doi: 10.1182/bloodadvances.2021005171.
Marta Rodríguez 1 2 Ruth Alonso-Alonso 1 2 Laura Tomás-Roca 1 Socorro M Rodríguez-Pinilla 1 2 Rebeca Manso-Alonso 1 Laura Cereceda 1 2 Jennifer Borregón 1 Teresa Villaescusa 3 Raúl Córdoba 2 3 Margarita Sánchez-Beato 2 4 Ismael Fernández-Miranda 4 Isabel Betancor 1 Carmen Bárcena 5 Juan F García 2 6 Manuela Mollejo 2 7 Mónica García-Cosio 2 8 Paloma Martin-Acosta 2 9 Fina Climent 10 Dolores Caballero 11 Lorena de la Fuente 12 13 Pablo Mínguez 12 13 14 Linda Kessler 15 Catherine Scholz 15 Antonio Gualberto 15 Rufino Mondéjar 2 16 Miguel A Piris 1 2
Affiliations

Affiliations

  • 1 Pathology Department, Instituto de Investigación Sanitaria Fundación Jiménez Díaz, Madrid, Spain.
  • 2 Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), ISCIII, Madrid, Spain.
  • 3 Lymphoma Unit, Department of Hematology, Fundación Jiménez Díaz University Hospital, Health Research Institute IIS-FJD, Madrid, Spain.
  • 4 Lymphoma Research Group, Medical Oncology Department, Instituto de Investigación Sanitaria Puerta de Hierro-Segovia de Arana, Madrid, Spain.
  • 5 Pathology Department, Hospital Universitario 12 de Octubre, Madrid, Spain.
  • 6 Pathology Department, Hospital MD Anderson Cancer Center, Madrid, Spain.
  • 7 Pathology Department, Hospital Virgen de la Salud, Toledo, Spain.
  • 8 Pathology Department, Hospital Universitario Ramón y Cajal, Madrid, Spain.
  • 9 Pathology Department, Hospital Universitario Puerta de Hierro-Segovia de Arana, Madrid, Spain.
  • 10 Pathology Department, Hospital Universitari de Bellvitge, IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain.
  • 11 Haematology Department, Hospitalario Universitario de Salamanca (HUS/IBSAL), Salamanca, Spain.
  • 12 Bioinformatics Unit, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
  • 13 Department of Genetics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain.
  • 14 Center for Biomedical Network Research on Rare Diseases (CIBERER), ISCIII, Madrid, Spain.
  • 15 Kura Oncology Inc., San Diego, CA; and.
  • 16 UGC Laboratorios, Hospital Universitario de Puerto Real, Cádiz, Spain.
Abstract

Peripheral T-cell lymphoma (PTCL) is a clinically aggressive disease, with a poor response to therapy and a low overall survival rate of approximately 30% after 5 years. We have analyzed a series of 105 cases with a diagnosis of PTCL using a customized NanoString platform (NanoString Technologies, Seattle, WA) that includes 208 genes associated with T-cell differentiation, oncogenes and tumor suppressor genes, deregulated pathways, and stromal cell subpopulations. A comparative analysis of the various histological types of PTCL (angioimmunoblastic T-cell lymphoma [AITL]; PTCL with T follicular helper [TFH] phenotype; PTCL not otherwise specified [NOS]) showed that specific sets of genes were associated with each of the diagnoses. These included TFH markers, cytotoxic markers, and genes whose expression was a surrogate for specific cellular subpopulations, including follicular dendritic cells, mast cells, and genes belonging to precise survival (NF-κB) and other pathways. Furthermore, the mutational profile was analyzed using a custom panel that targeted 62 genes in 76 cases distributed in AITL, PTCL-TFH, and PTCL-NOS. The main differences among the 3 nodal PTCL classes involved the RHOAG17V mutations (P < .0001), which were approximately twice as frequent in AITL (34.09%) as in PTCL-TFH (16.66%) cases but were not detected in PTCL-NOS. A multivariate analysis identified gene sets that allowed the series of cases to be stratified into different risk groups. This study supports and validates the current division of PTCL into these 3 categories, identifies sets of markers that can be used for a more precise diagnosis, and recognizes the expression of B-cell genes as an IPI-independent prognostic factor for AITL.

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