Multi-omics dataset to decipher the complexity of drug resistance in diffuse large B-cell lymphoma.
Fiche publication
Date publication
janvier 2019
Journal
Scientific reports
Auteurs
Membres identifiés du Cancéropôle Est :
Pr BAHRAM Siamak, Pr CHENARD Marie-Pierre, Dr CIANFERANI Sarah, Pr HERBRECHT Raoul, Pr MAUVIEUX Laurent, Dr VALLAT Laurent, Dr CARAPITO Christine, Dr CARAPITO Raphaël, Pr FORNECKER Luc-Matthieu
Tous les auteurs :
Fornecker LM, Muller L, Bertrand F, Paul N, Pichot A, Herbrecht R, Chenard MP, Mauvieux L, Vallat L, Bahram S, Cianférani S, Carapito R, Carapito C
Lien Pubmed
Résumé
The prognosis of patients with relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) remains unsatisfactory and, despite major advances in genomic studies, the biological mechanisms underlying chemoresistance are still poorly understood. We conducted for the first time a large-scale differential multi-omics investigation on DLBCL patient's samples in order to identify new biomarkers that could early identify patients at risk of R/R disease and to identify new targets that could determine chemorefractoriness. We compared a well-characterized cohort of R/R versus chemosensitive DLBCL patients by combining label-free quantitative proteomics and targeted RNA sequencing performed on the same tissues samples. The cross-section of both data levels allowed extracting a sub-list of 22 transcripts/proteins pairs whose expression levels significantly differed between the two groups of patients. In particular, we identified significant targets related to tumor metabolism (Hexokinase 3), microenvironment (IDO1, CXCL13), cancer cells proliferation, migration and invasion (S100 proteins) or BCR signaling pathway (CD79B). Overall, this study revealed several extremely promising biomarker candidates related to DLBCL chemorefractoriness and highlighted some new potential therapeutic drug targets. The complete datasets have been made publically available and should constitute a valuable resource for the future research.
Référence
Sci Rep. 2019 Jan 29;9(1):895