bioRxivCancer BiologyPreprint
RIP140 regulates HES1 oscillatory expression and mitogenic activity in colon cancer cells
N. Sfeir, M. Kajdan, S. Jalaguier, S. Bonnet, C. Teyssier, S. Pyrdziak, R. Yuan, E. Bousquet, A. Maraver, F. Bernex, N. Pirot, F. Boissiere, A. Castet-Nicolas, M. Lapierre, V. Cavailles
Abstract
BackgroundThe transcription factor RIP140 (Receptor Interacting Protein of 140 kDa) regulates intestinal homeostasis and tumorigenesis through the Wnt signaling. In this study, we have investigated its effect on the Notch/HES1 signaling pathway. MethodsThe impact on HES1 expression and activity was evaluated in colorectal cancer (CRC) cell lines and in transgenic mice, invalidated or not for the Rip140 gene in the intestinal epithelium. A tumor microarray and transcriptomic data sets were used to investigate RIP140 and HES1 expression in relation with patient survival. Statistical comparisons were performed with Mann-Whitney or Kruskal-Wallis or Chi2 tests. ResultsIn CRC cells, RIP140 positively regulated HES1 gene expression at the transcriptional level via an RBPJ/NICD-mediated mechanism. In support of these in vitro data, RIP140 and HES1 expression significantly correlated in mouse intestine and in a cohort of CRC samples, analyzed by immunohistochemistry, thus supporting the positive regulation of HES1 gene expression by RIP140. Interestingly, when the Notch pathway is fully activated, RIP140 exerted a strong inhibition of HES1 gene transcription controlled by the level of HES1 itself. Moreover, RIP140 directly interacts with HES1 and reversed its mitogenic activity in human CRC cells. In line with this observation, HES1 levels were associated with a better patient survival only when tumors expressed high levels of RIP140. ConclusionsOur data identify RIP140 as a key regulator of the Notch/HES1 signaling pathway with a dual effect on HES1 gene expression at the transcriptional level and a strong impact on colon cancer cell proliferation.
- organism: mouse
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
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