Lim, Soon Thye

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.

Abstract Peripheral T-cell lymphomas (PTCLs) are heterogenous T-cell neoplasms often associated with epigenetic dysregulation. We investigated de novo DNA methyltransferase 3A (DNMT3A) mutations in common PTCL entities, including angioimmunoblastic T-cell lymphoma and novel molecular subtypes identified within PTCL–not otherwise specified (PTCL-NOS) designated as PTCL-GATA3 and PTCL-TBX21. DNMT3A-mutated PTCL-TBX21 cases showed inferior overall survival (OS), with DNMT3A-mutated residues skewed toward the methyltransferase domain and dimerization motif (S881–R887). Transcriptional profiling demonstrated significant enrichment of activated CD8+ T-cell cytotoxic gene signatures in the DNMT3A-mutant PTCL-TBX21 cases, which was further validated using immunohistochemistry. Genomewide methylation analysis of DNMT3A-mutant vs wild-type (WT) PTCL-TBX21 cases demonstrated hypomethylation in target genes regulating interferon-γ (IFN-γ), T-cell receptor signaling, and EOMES (eomesodermin), a master transcriptional regulator of cytotoxic effector cells. Similar findings were observed in a murine model of PTCL with Dnmt3a loss (in vivo) and further validated in vitro by ectopic expression of DNMT3A mutants (DNMT3A-R882, -Q886, and -V716, vs WT) in CD8+ T-cell line, resulting in T-cell activation and EOMES upregulation. Furthermore, stable, ectopic expression of the DNMT3A mutants in primary CD3+ T-cell cultures resulted in the preferential outgrowth of CD8+ T cells with DNMT3AR882H mutation. Single-cell RNA sequencing(RNA-seq) analysis of CD3+ T cells revealed differential CD8+ T-cell subset polarization, mirroring findings in DNMT3A-mutated PTCL-TBX21 and validating the cytotoxic and T-cell memory transcriptional programs associated with the DNMT3AR882H mutation. Our findings indicate that DNMT3A mutations define a cytotoxic subset in PTCL-TBX21 with prognostic significance and thus may further refine pathological heterogeneity in PTCL-NOS and suggest alternative treatment strategies for this subset.