A transcriptional classifier of formalin-fixed, paraffin-embedded (FFPE) tissue from patients with peripheral T-cell lymphoma (PTCL) provides molecular characterization and improved pathologic diagnosis, according to the results of a study published in the Journal of Clinical Oncology.
“The diagnosis of PTCL is one of the most challenging among lymphoma and more often results in an inconclusive, inconsistent, or incorrect diagnosis,” the authors wrote in their report.
A previous study developed transcriptomic signatures that identified different PTCL subtypes and 2 novel subtypes that are typically classified as part of the PTCL-not otherwise specified (NOS) umbrella. The aim of this study was to develop a gene expression-based subclassification for improved PTCL diagnosis.
The study evaluated data from FFPE tissue specimens of 105 patients in a PTCL training cohort with prior gene expression profiling data. Data from a separate 140 patients with PTCL were used to validate the transcriptomic signatures.
The transcriptomic classifier demonstrated high sensitivity of greater than 80%, specificity of greater than 95%, and accuracy greater than 94% in the training cohort compared with a fresh-frozen-derived diagnostic model. The results of the transcriptomic classifier was reproducible between 3 independent laboratories.
The overall concordance between 3 independent, expert hematopathologists was 91% (95% CI, 0.85-0.95), in which the pathology diagnosis matched the results of the transcriptional classifier in the validation cohort. The concordance in the training and validation cohorts was 83% and 74%, respectively, for AITL, 83% and 90% for ALCL, 100% and 83% for ATLL. For PTCL-NOS, the overall concordance with an immunohistochemistry algorithm was 80% and the concordance for the novel subgroups, PTCL-GATA3 or PTCL-TBX21, was 87% in the training cohort.
In 2 cases, the transcriptional classifier improved the pathology diagnosis, as confirmed by clinical findings.
The authors concluded that “We developed a novel transcriptomic approach for PTCL subclassification that facilitates translation into clinical practice with higher precision and uniformity than conventional pathology diagnosis.”
Disclosures: This study was supported in part by Allos Therapeutics and Spectrum Pharmaceuticals. Please see the original reference for a full list of disclosures.
Amador C, Bouska A, Wright G, et al. Gene expression signatures for the accurate diagnosis of peripheral T-cell lymphoma entities in the routine clinical practice. J Clin Oncol. Published online July 15, 2022. doi: 10.1200/JCO.21.02707