Integration of transcriptional and mutational data simplifies the stratification of peripheral T‐cell lymphoma. Issue 6 (19th March 2019)

• Record Type: Journal Article
• Authors: Maura, Francesco; Agnelli, Luca; Leongamornlert, Daniel; Bolli, Niccolò; Chan, Wing C.; Dodero, Anna; Carniti, Cristiana; Heavican, Tayla B.; Pellegrinelli, Alessio; Pruneri, Giancarlo; Butler, Adam; Bhosle, Shriram G.; Chiappella, Annalisa; Di Rocco, Alice; Zinzani, Pier Luigi; Zaja, Francesco; Piva, Roberto; Inghirami, Giorgio; Wang, Wenyi; Palomero, Teresa; Iqbal, Javeed; Neri, Antonino; Campbell, Peter J.; Corradini, Paolo
• Is Part Of: American journal of hematology. Volume 94:Issue 6(2019:Jun.)
• Page Start: 628
• Page End: 634
• Publication Date: 2019-03-19
• Subjects: Hematology -- Periodicals; 616.15
• DOI: 10.1002/ajh.25450
• Languages: English
• ISSNs: 0361-8609

Abstract

Abstract: The histological diagnosis of peripheral T‐cell lymphoma (PTCL) can represent a challenge, particularly in the case of closely related entities such as angioimmunoblastic T‐lymphoma (AITL), PTCL‐not otherwise specified (PTCL‐NOS), and ALK‐negative anaplastic large‐cell lymphoma (ALCL). Although gene expression profiling and next generations sequencing have been proven to define specific features recurrently associated with distinct entities, genomic‐based stratifications have not yet led to definitive diagnostic criteria and/or entered into the routine clinical practice. Herein, to improve the current molecular classification between AITL and PTCL‐NOS, we analyzed the transcriptional profiles from 503 PTCLs stratified according to their molecular configuration and integrated them with genomic data of recurrently mutated genes ( RHOA G17V, TET2, IDH2 R172, and DNMT3A ) in 53 cases (39 AITLs and 14 PTCL‐NOSs) included in the series. Our analysis unraveled that the mutational status of RHOA G17V, TET2, and DNMT3A poorly correlated, individually, with peculiar transcriptional fingerprints. Conversely, in IDH2 R172 samples a strong transcriptional signature was identified that could act as a surrogate for mutational status. The integrated analysis of clinical, mutational, and molecular data led to a simplified 19‐gene signature that retains high accuracy in differentiating the main nodal PTCL entities. The expression levels of those genes were confirmed in an independent cohort profiled by RNA‐sequencing.