Reproducing the molecular subclassification of peripheral T-cell lymphoma-NOS by immunohistochemistry

Blood. 2019 Dec 12;134(24):2159-2170. doi: 10.1182/blood.2019000779.

Abstract

Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of mature T-cell malignancies; approximately one-third of cases are designated as PTCL-not otherwise specified (PTCL-NOS). Using gene-expression profiling (GEP), we have previously defined 2 major molecular subtypes of PTCL-NOS, PTCL-GATA3 and PTCL-TBX21, which have distinct biological differences in oncogenic pathways and prognosis. In the current study, we generated an immunohistochemistry (IHC) algorithm to identify the 2 subtypes in paraffin tissue using antibodies to key transcriptional factors (GATA3 and TBX21) and their target proteins (CCR4 and CXCR3). In a training cohort of 49 cases of PTCL-NOS with corresponding GEP data, the 2 subtypes identified by the IHC algorithm matched the GEP results with high sensitivity (85%) and showed a significant difference in overall survival (OS) (P = .03). The IHC algorithm classification showed high interobserver reproducibility among pathologists and was validated in a second PTCL-NOS cohort (n = 124), where a significant difference in OS between the PTCL-GATA3 and PTCL-TBX21 subtypes was confirmed (P = .003). In multivariate analysis, a high International Prognostic Index score (3-5) and the PTCL-GATA3 subtype identified by IHC were independent adverse predictors of OS (P = .0015). Additionally, the 2 IHC-defined subtypes were significantly associated with distinct morphological features (P < .001), and there was a significant enrichment of an activated CD8+ cytotoxic phenotype in the PTCL-TBX21 subtype (P = .03). The IHC algorithm will aid in identifying the 2 subtypes in clinical practice, which will aid the future clinical management of patients and facilitate risk stratification in clinical trials.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Algorithms
  • Biomarkers, Tumor*
  • Computational Biology / methods
  • Female
  • Gene Expression Profiling
  • Humans
  • Immunohistochemistry
  • Immunophenotyping
  • Lymphoma, T-Cell, Peripheral / diagnosis*
  • Lymphoma, T-Cell, Peripheral / etiology*
  • Lymphoma, T-Cell, Peripheral / metabolism
  • Male
  • Middle Aged
  • Neoplasm Staging
  • Prognosis
  • Reproducibility of Results

Substances

  • Biomarkers, Tumor