Ott, German

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.

SummaryMantle cell lymphoma (MCL) is still considered incurable and the course of the disease is highly variable. Established risk factors include the Mantle Cell Lymphoma International Prognostic Index (MIPI) and the quantification of the proliferation rate of the tumour cells, e.g. by Ki‐67 immunohistochemistry. In this study, we aimed to validate the prognostic value of the gene expression‐based MCL35 proliferation assay in patient cohorts from randomized trials of the European Mantle Cell Lymphoma Network. Using this assay, we analysed the gene expression proliferation signature in routine diagnostic lymph node specimens from MCL Younger and MCL Elderly trial patients, and the calculated MCL35 score was used to assign MCL patients to low (61%), standard (27%) or high (12%) risk groups with significantly different outcomes. We confirm here in our prospective clinical trial cohort of MCL patients, that the MCL35 assay is strongly prognostic, providing additional information to the Ki‐67 index and the MIPI. Thus, this robust assay may assist in making treatment decisions or in devising risk‐adapted prospective clinical trials in the future.