molecular profiling improves classification and prognostication of nodal peripheral tcell lymphomas results of a phase iii diagnostic accuracy study purpose the differential diagnosis among the commonest peripheral tcell lymphomas ptcls ie ptcl not otherwise specified nos angioimmunoblastic tcell lymphoma aitl and anaplastic largecell lymphoma alcl is difficult with the morphologic and phenotypic features largely overlapping we performed a phase iii diagnostic accuracy study to test the ability of gene expression profiles geps index test to identify ptcl subtypemethods we studied 244 ptcls including 158 ptcls nos 63 aitls and 23 alknegative alcls the gepbased classification method was established on a support vector machine algorithm and the reference standard was an expert pathologic diagnosis according to who classificationresults first we identified molecular signatures molecular classifier mc discriminating either aitl and alknegative alcl from ptcl nos in a training set of note the mc was developed in formalinfixed paraffinembedded ffpe samples and validated in both ffpe and frozen tissues second we found that the overall accuracy of the mc was remarkable 98 to 77 for aitl and 98 to 93 for alknegative alcl in test and validation sets of patient cases respectively furthermore we found that the mc significantly improved the prognostic stratification of patients with ptcl particularly it enhanced the distinction of alknegative alcl from ptcl nos especially from some cd30 ptcl nos with uncertain morphology finally mc discriminated some tfollicular helper tfh ptcl nos from aitl providing further evidence that a group of ptcls nos shares a tfh derivation with but is distinct from aitlconclusion our findings support the usage of an mc as additional tool in the diagnostic workup of nodal ptcl