Chan, Wing C

Peripheral T cell lymphoma (PTCL) is a heterogeneous group of postthymic T cell neoplasms, with ~40% classified as PTCL–not otherwise specified (PTCL-NOS). PTCL-GATA3, a molecularly defined subtype, associated with T helper 2 (T H 2)–like differentiation and poor prognosis, has frequent co-occurrence of TP53 loss/mutation and heterozygous PTEN loss. CD4+ T cell conditional mouse models with Trp53 mutation/deletion and Pten loss demonstrated mature T cell lymphomas (mTCLs) with T H 2-like transcriptomic and immunophenotypic profiles. Molecular studies revealed that codeletion of Trp53/Pten induced T cell receptor and Janus kinase–signal transducer and activator of transcription signaling, promoting T H 2 differentiation while inhibiting T H 1 differentiation. These findings were validated by CRISPR editing of TP53/PTEN loss in human CD4+ T cells and mechanistically evaluated the p53 binding region in intron-3 of GATA3, resulting in transcriptional repression. Transcriptomic profiles of m-TCLs recapitulated human-PTCL-GATA3 transcriptome and distinguished PTCL-NOS subtypes. Preclinical assessment of m-TCLs with PI3Kγ/δ inhibitors significantly improved survival, supporting a therapeutic approach for the p53-aberrant PTCL-GATA3.

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.

PURPOSE Peripheral T-cell lymphoma (PTCL) includes heterogeneous clinicopathologic entities with numerous diagnostic and treatment challenges. We previously defined robust transcriptomic signatures that distinguish common PTCL entities and identified two novel biologic and prognostic PTCL-not otherwise specified subtypes (PTCL-TBX21 and PTCL-GATA3). We aimed to consolidate a gene expression–based subclassification using formalin-fixed, paraffin-embedded (FFPE) tissues to improve the accuracy and precision in PTCL diagnosis. MATERIALS AND METHODS We assembled a well-characterized PTCL training cohort (n = 105) with gene expression profiling data to derive a diagnostic signature using fresh-frozen tissue on the HG-U133plus2.0 platform (Affymetrix, Inc, Santa Clara, CA) subsequently validated using matched FFPE tissues in a digital gene expression profiling platform (nCounter, NanoString Technologies, Inc, Seattle, WA). Statistical filtering approaches were applied to refine the transcriptomic signatures and then validated in another PTCL cohort (n = 140) with rigorous pathology review and ancillary assays. RESULTS In the training cohort, the refined transcriptomic classifier in FFPE tissues showed high sensitivity (> 80%), specificity (> 95%), and accuracy (> 94%) for PTCL subclassification compared with the fresh-frozen–derived diagnostic model and showed high reproducibility between three independent laboratories. In the validation cohort, the transcriptional classifier matched the pathology diagnosis rendered by three expert hematopathologists in 85% (n = 119) of the cases, showed borderline association with the molecular signatures in 6% (n = 8), and disagreed in 8% (n = 11). The classifier improved the pathology diagnosis in two cases, validated by clinical findings. Of the 11 cases with disagreements, four had a molecular classification that may provide an improvement over pathology diagnosis on the basis of overall transcriptomic and morphological features. The molecular subclassification provided a comprehensive molecular characterization of PTCL subtypes, including viral etiologic factors and translocation partners. CONCLUSION We developed a novel transcriptomic approach for PTCL subclassification that facilitates translation into clinical practice with higher precision and uniformity than conventional pathology diagnosis.