E-GEOD-46873 - Dual targeting of MYC and CYCLON by BET bromodomain inhibition optimizes Rituximab response in lymphoma
Released on 1 June 2013, last updated on 13 May 2014
Immuno-chemotherapy regimens elicit high response rates in B-cell non-Hodgkin lymphoma but heterogeneity in response duration is observed, with some patients achieving cure and others showing refractory disease or relapse. Using a transcriptome-powered targeted proteomics screen, we discovered a gene regulatory circuit involving the nuclear factor CYCLON which characterizes aggressive disease and resistance to the anti-CD20 monoclonal antibody, Rituximab, in high-risk B-cell lymphoma. CYCLON knockdown was found to inhibit the aggressivity of MYC-overexpressing tumors in mice and to modulate gene expression programs of biological relevance to lymphoma. Furthermore, CYCLON knockdown increased the sensitivity of human lymphoma B cells to Rituximab in vitro and in vivo. Strikingly, this effect could be mimicked by in vitro treatment of lymphoma B cells with a small molecule inhibitor for BET bromodomain proteins (JQ1). In summary, this work has identified CYCLON as a new MYC cooperating factor that drives aggressive tumor growth and Rituximab resistance in lymphoma. This resistance mechanism is amenable to next-generation epigenetic therapy by BET bromodomain inhibition, thereby providing a new combination therapy rationale for high-risk lymphoma. We have identified CYCLON has a nuclear factor involved in tumor progression and treatment resistance in aggressive lymphoma. In order to get further insights into the molecular mechanisms related to the expression of this factor, we used Raji cells to compared gene expression profiles of control and CYCLON knock-down cell lines. Stable cell lines have been established using lentiviral transduction of Raji Burkitt lymphoma B cells with either a control (non-targeting) shRNA sequence or CYCLON shRNA constructs under puromycin selection. Non-transduced cells were also analyzed as a control. 4 replicates were analyzed for each conditions.
transcription profiling by array
Anouk Emadali, Mary Callanan, Saadi Khochbin, Sophie Rousseaux