Gene Expression Signatures for the Accurate Diagnosis of Peripheral T-Cell Lymphoma Entities in the Routine Clinical Practice

Abstract

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.

Classification and challenges in the histopathological diagnosis of peripheral T-cell lymphomas, emphasis on the WHO-HAEM5 updates

“…ICOS and PD-1 are expressed in most cases. However, ICOS is expressed in 43-52% of the PTCL-NOS cases, and PD-1 is expressed in approximately 60% of PTCL-NOS cases (67,68) and apart from other peripheral T-cell lymphomas, including ALCL and PTCL-NOS (69). However, recent studies show that a subset of PTCL-TFH cases features gene expression profiles closer to the PTCL-NOS group (69).…”

“…However, ICOS is expressed in 43-52% of the PTCL-NOS cases, and PD-1 is expressed in approximately 60% of PTCL-NOS cases (67,68) and apart from other peripheral T-cell lymphomas, including ALCL and PTCL-NOS (69). However, recent studies show that a subset of PTCL-TFH cases features gene expression profiles closer to the PTCL-NOS group (69). To emphasize that this group of neoplasms constitutes a spectrum with morphological plasticity, this family of neoplasms has been designated nodal T-follicular helper lymphomas (nTFH) in the updated WHO-HAEM5.…”

“…The morphological features can transition between T-FH subtypes over subsequent biopsies or transform into PTCL-NOS. The genetic profile includes similar frequencies of mutations in DNMT3A , RHOA , and TET2 ( 61 , 69 , 70 ), and IDH2 mutations are predominantly detected in AITL. The gene expression profiles are similar, and these groups of neoplasms cluster in proximity and apart from other peripheral T-cell lymphomas, including ALCL and PTCL-NOS ( 69 ).…”

“…The genetic profile includes similar frequencies of mutations in DNMT3A , RHOA , and TET2 ( 61 , 69 , 70 ), and IDH2 mutations are predominantly detected in AITL. The gene expression profiles are similar, and these groups of neoplasms cluster in proximity and apart from other peripheral T-cell lymphomas, including ALCL and PTCL-NOS ( 69 ). However, recent studies show that a subset of PTCL-TFH cases features gene expression profiles closer to the PTCL-NOS group ( 69 ).…”

Emerging predictive biomarkers for novel therapeutics in peripheral T-cell and natural killer/T-cell lymphoma

“…Despite years of study, the diagnosis of specific T cell lymphoma remains challenging due to numerous overlying similarities, often requiring a consolidated review of clinical, laboratory, and immunohistological findings and expert analysis for categorization. Modern technological options such as the utility of gene expression signatures via transcriptomic analysis have also been studied as novel means of increasing the accuracy of diagnosing each subtype of PTCL, including further substratification of PTCL-NOS into its GATA3-or TBX21-expressing subgroups (36). This…”