Lei Ji

Axin is a key scaffolding protein responsible for the formation of the β-catenin destruction complex. Stability of Axin protein is regulated by the ubiquitin-proteasome system, and modulation of cellular concentration of Axin protein has a profound effect on Wnt/β-catenin signaling. Although E3s promoting Axin ubiquitination have been identified, the deubiquitinase responsible for Axin deubiquitination and stabilization remains unknown. Here, we identify USP7 as a potent negative regulator of Wnt/β-catenin signaling through CRISPR screens. Genetic ablation or pharmacological inhibition of USP7 robustly increases Wnt/β-catenin signaling in multiple cellular systems. USP7 directly interacts with Axin through its TRAF domain, and promotes deubiquitination and stabilization of Axin. Inhibition of USP7 regulates osteoblast differentiation and adipocyte differentiation through increasing Wnt/β-catenin signaling. Our study reveals a critical mechanism that prevents excessive degradation of Axin and identifies USP7 as a target for sensitizing cells to Wnt/β-catenin signaling.

The Wnt/β-catenin signaling pathway plays essential roles in embryonic development and adult tissue homeostasis. Axin is a concentration-limiting factor responsible for the formation of the β-catenin destruction complex. Wnt signaling itself promotes the degradation of Axin. However, the underlying molecular mechanism and biological relevance of this targeting of Axin have not been elucidated. Here, we identify SIAH1/2 (SIAH) as the E3 ligase mediating Wnt-induced Axin degradation. SIAH proteins promote the ubiquitination and proteasomal degradation of Axin through interacting with a VxP motif in the GSK3-binding domain of Axin, and this function of SIAH is counteracted by GSK3 binding to Axin. Structural analysis reveals that the Axin segment responsible for SIAH binding is also involved in GSK3 binding but adopts distinct conformations in Axin/SIAH and Axin/GSK3 complexes. Knockout of SIAH1 blocks Wnt-induced Axin ubiquitination and attenuates Wnt-induced β-catenin stabilization. Our data suggest that Wnt-induced dissociation of the Axin/GSK3 complex allows SIAH to interact with Axin not associated with GSK3 and promote its degradation and that SIAH-mediated Axin degradation represents an important feed-forward mechanism to achieve sustained Wnt/β-catenin signaling.

Background Local recurrence and distant metastasis are the main causes of death in patients with lung cancer. Multiple studies have described the recurrence or metastasis of lung cancer at the genetic level. However, association between the microbiome of lung cancer tissue and recurrence or metastasis remains to be discovered. Here, we aimed to identify the bacterial biomarkers capable of distinguishing patients with lung cancer from recurrence or metastasis, and how it related to the severity of patients with lung cancer. Methods We applied microbiome pipeline to bacterial communities of 134 non-recurrence and non-metastasis (non-RM) and 174 recurrence or metastasis (RM) samples downloaded from The Cancer Genome Atlas (TCGA). Co-occurrence network was built to explore the bacterial interactions in lung cancer tissue of RM and non-RM. Finally, the Kaplan–Meier survival analysis was used to evaluate the association between bacterial biomarkers and patient survival. Results Compared with non-RM, the bacterial community of RM had lower richness and higher Bray–Curtis dissimilarity index. Interestingly, the co-occurrence network of non-RM was more complex than RM. The top 500 genera in relative abundance obtained an area under the curve (AUC) of 0.72 when discriminating between RM and non-RM. There were significant differences in the relative abundances of Acidovorax , Clostridioides, Succinimonas, and Shewanella , and so on between RM and non-RM. These biomarkers played a role in predicting the survival of lung cancer patients and were significantly associated with lung cancer stage. Conclusion This study provides the first evidence for the prediction of lung cancer recurrence or metastasis by bacteria in lung cancer tissue. Our results highlights that bacterial biomarkers that distinguish RM and non-RM are also associated with patient survival and disease severity.