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EBF1, MYO6 and CALR expression levels predict therapeutic response in diffuse large B-cell lymphomas

  • Autori: Turdo, Alice; Gaggianesi, Miriam; D’Accardo, Caterina; Porcelli, Gaetana; Bella, Sebastiano Di; Cricchio, Dario; Pillitteri, Irene; Porcasi, Rossana; Lo Iacono, Melania; Verona, Francesco; Modica, Chiara; Roozafzay, Narges; Florena, Ada Maria; Stassi, Giorgio; Mancuso, Salvatrice; Todaro, Matilde
  • Anno di pubblicazione: 2023
  • Tipologia: Articolo in rivista
  • OA Link:


Background: Diffuse large B-cell lymphoma (DLBCL) is a hematological malignancy representing one-third of non-Hodgkin’s lymphoma cases. Notwithstanding immunotherapy in combination with chemotherapy (R-CHOP) is an effective therapeutic approach for DLBCL, a subset of patients encounters treatment resistance, leading to low survival rates. Thus, there is an urgent need to identify predictive biomarkers for DLBCL including the elderly population, which represents the fastest-growing segment of the population in Western countries. Methods: Gene expression profiles of n=414 DLBCL biopsies were retrieved from the public dataset GSE10846. Differentially expressed genes (DEGs) (fold change >1.4, p-value <0.05, n=387) have been clustered in responder and non-responder patient cohorts. An enrichment analysis has been performed on the top 30 up-regulated genes of responder and non-responder patients to identify the signatures involved in gene ontology (MSigDB). The more significantly up-regulated DEGs have been validated in our independent collection of formalin-fixed paraffin-embedded (FFPE) biopsy samples of elderly DLBCL patients, treated with R-CHOP as first-line therapy. Results: From the analysis of two independent cohorts of DLBCL patients emerged a gene signature able to predict the response to R-CHOP therapy. In detail, expression levels of EBF1, MYO6, CALR are associated with a significant worse overall survival. Conclusions: These results pave the way for a novel characterization of DLBCL biomarkers, aiding the stratification of responder versus non-responder patients.