Peripheral T-cell lymphoma: molecular profiling distinguishes subclasses, recognizes the tumor architecture and identifies prognostic markers. (October 2021)

• Record Type: Journal Article
• Authors: Rodriguez-Moreno, Marta; Tomás-Roca, Laura; Alonso-Alonso, Ruth; Manso-Alonso, Rebeca; Cereceda, Laura; Borregón, Jennifer; Villaescusa, Teresa; Córdoba, Raúl; Sánchez-Beato, Margarita; Fernández-Miranda, Ismael; Betancor, Isabel; Bárcena, Carmen; García, Juan Fernando; Mollejo, Manuela; García-Cosio, Monica; Martín-Acosta, Paloma; Climent, Fina; Caballero, Dolores; Mondéjar, Rufino; Kessler, Linda; Scholz, Catherine; Gualberto, Antonio; Rodríguez-Pinilla, Socorro María; Piris, Miguel Ángel
• Is Part Of: European journal of cancer. Volume 156(2021)Supplement 1
• Page Start: S43
• Page End: S44
• Publication Date: 2021-10
• Subjects: PTCL -- prognostic markers -- microenvironment -- nanostring; Cancer -- Periodicals; Neoplasms -- Periodicals; Cancer -- Périodiques; Cancer; Tumors; Electronic journals; Periodicals; Electronic journals; 616.994
• DOI: 10.1016/S0959-8049(21)00707-3
• Languages: English
• ISSNs: 0959-8049

Abstract

Abstract : Introduction: Peripheral T-cell lymphomas (PTCLs) are aggressive tumours with unfavourable prognosis, with around 30% OS after 5 years. Histological and molecular studies have revealed a striking degree of heterogeneity, with three major PTCL subtypes defined. Consistent diagnosis and prognostication are still difficult to achieve, because of the difficulty of reproducing results, and the dearth of clinically applicable prognostic biological markers. Methods: We have analyzed a series of 105 PTCL cases (66 angioimmunoblastic T-cell lymphoma, AITL; 21 PTCL-not otherwise specified, PTCL-NOS; and 18 PTCL-with T follicular helper phenotype, PTCL-TFH) patients using a customized NanoString platform that includes 208 genes associated with T-cell differentiation, oncogenes and tumor suppressor genes, deregulated pathways and stromal cell subpopulations. Specifically, the platform includes genes expressed by the multiple cell types present in PTCL specimens, together with normal T-cell populations. These are used to try and enable the deconvolution of the T-cell lymphoma microenvironment, and thereby develop an integrated perspective on the cell composition of PTCL tumor specimens. Results: A comparative analysis of the various histological types of PTCL (AITL, PTCL-NOS and PTCL-TFH) showed specific sets of genes to be associated with each of the diagnoses, including TFH markers, cytotoxic markers and genes whose expression was a surrogate for specific cellular subpopulations, including follicular dendritic cells, mast cells and genes belonging to specific cell-survival pathways (NF-κB). Unsupervised analysis of the expression of the genes here studied revealed clusters of co-regulated genes that identified the main cell components of the tumor. The analysis did not reveal any differences in survival probability associated with the histological sub-classification, but did identify specific genes and gene sets whose expression was associated with changes in survival probability for each of the PTCL subtypes, independently of the clinical variables included in the International Prognostic Index (IPI). These included a B-cell gene set in cases of AITL, the expression of proliferation markers in PTCL-NOS, and the expression of cytotoxic markers in cases with a diagnosis of PTCL-TFH. For each PTCL lymphoma type, a multivariate analysis identified genes that allow the series of cases to be stratified into different risk groups. This was validated for AITL in an independent series of 54 additional cases. Conclusions: In summary, our study supports the current division of PTCL into these three categories (AITL, PTCL-NOS and PTCL-TFH), identifies gene sets potentially useful for this classification and recognizes the expression of B-cell genes as an IPI-independent prognostic factor for AITL subtype.