Abstract

Recent molecular studies have indicated the varied oncogenic pathways resulting in the subtypes of peripheral T-cell lymphoma, not otherwise specified (PTCL, NOS), which affect prognosis and may have predictive value. To evaluate the immunohistochemistry (IHC) algorithm (Amador et al.) for the subtyping of PTCL, NOS and ascertain their relevance with correlation to the clinicopathological profile. This 7-year (2015-2021) ambispective study included 43 patients with diagnoses of PTCL, NOS from the archives of the Department of Pathology (AIIMS, New Delhi). IHC for transcription factors GATA3 (>50% immunopositivity considered positive) and TBX21 (>20%) and their target proteins CCR4 (>50%) and CXCR3 (>20%) was performed followed by subtyping by two pathologists. Detailed clinicopathological correlation was done. The association between the subtypes and clinical factors (demographics, performance status, organomegaly, IPI/PIT score, stage, marrow involvement), histologic features (monomorphous/polymorphous population), and survival (overall and progression-free survival) was analyzed. With the application of the algorithm by Amador et al., the cases were categorized into the subtypes GATA3 (18), TBX21 (13), and unclassifiable (7). There was no significant association observed with the clinical parameters of the subtypes. Though an increased proportion of TBX21-subgroup cases showed a polymorphous population compared to the GATA3 subgroup with monomorphous population, no significant P-value was found. Two of the Lennert lymphomas were categorized in the GATA3 subgroup. On multivariate analysis, no significant difference was present for overall survival (P-value=0.149) and progression-free survival (P-value=0.066) amongst the IHC-defined subtypes; the trends suggest that the GATA3 subgroup has worse overall and progression-free survival. The IHC-derived subtypes of GATA3 and TBX21 may have a role in prognostication and may guide further therapeutics aiding in better patient management of this aggressive group of lymphomas. The algorithm is reproducible, however some of the cases may be left unclassifiable and require further work up and gene expression profiling. The results trend toward the GATA3 subgroup having a monomorphous population with a worse overall prognosis, requiring a larger sample size for validation. The application of this algorithm in routine practice can help in risk stratification of the patients. Thanks to Science-Engineering-Research-Board and AIIMS-Research section (SERB-EEQ/2016/402, AIIMS-A-653).

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