Molecular and Cellular BiologyMolecular BiologyPeer-reviewed journal article
NRF1 and NRF3 complementarily maintain a basal proteasome activity in cancer cells through CPEB3-mediated translational repression
Tsuyoshi WakuiD, Hiroyuki KatayamaiD, Miyako Hiraoka, Atsushi Hatanaka, Nanami Nakamura, Yuya TanakaiD, Natsuko TamuraiD, Akira WatanabeiD, Akira Kobayashi
Abstract
Proteasomes are protease complexes essential for cellular homeostasis, and their activity is crucial for cancer cell growth. However, the mechanism of how proteasome activity is maintained in cancer cells has remained unclear. The CNC family transcription factor NRF1 induces the expression of almost all proteasome-related genes under proteasome inhibition. NRF1 and its phylogenetically closest homolog NRF3 are both highly expressed in several types of cancers, such as colorectal cancer. Herein, we demonstrate that NRF1 and NRF3 complementarily maintain basal proteasome activity in cancer cells. A double knockdown of NRF1 and NRF3 impaired the basal proteasome activity in cancer cells and the cancer cell resistance to a proteasome inhibitor anticancer drug bortezomib by significantly reducing basal expression of seven proteasome-related genes, including PSMB3, PSMB7, PSMC2, PSMD3, PSMG2, PSMG3, and POMP. Interestingly, the molecular basis behind these cellular consequences was that NRF3 repressed NRF1 translation by the gene induction of translational regulator CPEB3, which binds to NRF1-3'UTR and decreases polysome formation on NRF1 mRNA. Consistent results were obtained from clinical analysis, wherein patients with cancer having higher CPEB3/NRF3-expressing tumors exhibit poor prognosis. These results provide the novel regulatory mechanism of basal proteasome activity in cancer cells through an NRF3-CPEB3-NRF1 translational repression axis.
- organism: human
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: protein structure prediction
- research focus: drug response / drug discovery
- approach: statistical model
- Citations
- 53
- FWCI
- 3.16
- Field percentile
- top 6%
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