Journal of Cell ScienceCancer BiologyPeer-reviewed journal article
PA200 differentially regulates the proteasome and inhibits migration of cancer cells
Ayse Seda YazgiliiD, Georgia A. GiotopoulouiD, Sabine J. BehrendiD, Frauke Koops, Vanessa NeiensiD, Thomas Meul, Linda Zemke, Norbert ReilingiD, Torsten GoldmanniD, Georgios T. StathopoulosiD, Silke MeinersiD
Abstract
Proteasome activator 200 (PA200) is upregulated in non-small cell lung cancer (NSCLC) and linked to poor prognosis. We previously demonstrated that the overexpression of PA200 in NSCLC is associated with immune evasion and reduced responsiveness to immune checkpoint inhibitors. The cell autonomous function of PA200 in cancer growth, however, is not solved. We here demonstrate that deletion of PA200 in two distinct lung cancer cell lines induced cell-specific alterations in proteasome composition and activities with a minor direct impact on overall proteasome activity. Deficiency of PA200 in lung cancer cells did not consistently alter tumor cell growth in vitro and in vivo. However, we observed concerted inhibition of tumor cell migration and invasion with conserved downregulation of the integrin ITGB3 and transcriptional dysregulation of multiple cell adhesion and ECM regulators. Our transcriptome profiling revealed a striking disparity in the transcriptional response to PA200 deletion in the two lung cancer cell lines. Together with our PA200 interactome analysis that uncovered an unexpected cell-dependent profile of PA200-interacting proteins, our data indicate that the function of PA200 is cell-specific and depends on the cellular context. In conclusion, we here demonstrate that PA200 cell-autonomously regulates the invasive capacities of tumor cells thereby potentially promoting lung cancer spread and metastasis formation. This mechanism might add to PA200-related immune evasion and may contribute to the observed poor prognosis of PA200-overexpressing lung cancer patients.
- organism: human
- assay: proteomics
- research focus: cell signaling & trafficking
- approach: statistical model
- Citations
- 3
- FWCI
- 3.43
- Field percentile
- top 9%
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