Multi-omics dataset to decipher the complexity of drug resistance in diffuse large B-cell lymphoma
SCIENTIFIC REPORTS
Authors: Fornecker, Luc-Matthieu; Muller, Leslie; Bertrand, Frederic; Paul, Nicodeme; Pichot, Angelique; Herbrecht, Raoul; Chenard, Marie-Pierre; Mauvieux, Laurent; Vallat, Laurent; Bahram, Seiamak; Cianferani, Sarah; Carapito, Raphael; Carapito, Christine
Abstract
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.
The distinct gene expression profiles of chronic lymphocytic leukemia and multiple myeloma suggest different anti-apoptotic mechanisms but predict only some differences in phenotype
LEUKEMIA RESEARCH
Authors: Zent, CS; Zhan, FG; Schichman, SA; Bumm, KHW; Lin, P; Chen, JB; Shaughnessy, JD
Abstract
We compared gene expression in purified tumor cells from untreated patients with chronic lymphocytic (CLL) (n = 24) and newly diagnosed multiple myeloma (MM) (n = 29) using the Affymetrix HuGeneFL microarray with probes for approximately 6800 genes. Hierarchical clustering analysis showed that CLL and MM have distinct expression profiles (class prediction). Gene and protein expression (measured by flow cytometry) correlated well for CD19, CD20, CD23, and CD138 in CLL and MM, but not for immunoglobulin light chain, CD38 and CD79b in CLL, or CD45 and CD52 in MM. CLL and MM differentially expressed 18% of 130 apoptosis related genes, suggesting differences in mechanisms of cell survival. Published by Elsevier Science Ltd.