Glycosylation is an important modification of membrane proteins that results in functional changes in many cellular activities, from cell-cell recognition to regulatory signaling. Fucosyltransferase 8 (FUT8) is the sole enzyme responsible for core fucosylation, and aberrant fucosylation by dysregulated expression of fucosyltransferases is responsible for the growth of various types of carcinomas. However, the function of FUT8 in the progress of osteosarcoma (OS) has not been reported. In this study, we found that FUT8 is expressed at lower levels in patients with OS and in human OS cell lines such as MNNG/HOS, U2OS, and 143B, suggesting that attenuated expression of FUT8 is involved in the growth and progression of OS. Mechanistically, FUT8 affects the survival strategy of OS by modifying core-fucosylation levels of TNF receptors (TNFRs). Lower fucosylation of TNFRs activates the non-canonical NF-κB signaling pathway, and in turn, decreases mitochondria-dependent apoptosis in OS cells. Together, our results point to FUT8 being a negative regulator of OS that enhances OS-cell apoptosis and suggests a novel therapeutic strategy for treating OS.
Highlights
Preoperative CT images of GCTBs have value in prognostic prediction.
Certain features of GCTBs on CT images are related to local recurrence.
Our models’ predictions for GCTB patients accepting extensive curettage are good.
Background
Extended curettage has increasingly become the preferred treatment for giant cell tumour of bone (GCTB), but the high recurrence rate after curettage poses a major challenge for orthopaedic surgeons. Computed tomography (CT) is valuable in the evaluation of GCTB. Our aim was to identify specific features of GCTB around the knee in pre-operative CT images that might have prognostic value for local recurrence.
Methods
We retrospectively analyzed data from 124 patients with primary GCTB around the knee who underwent extended curettage from 2010 through 2019. We collected demographic, clinical, and therapeutic data along with several CT-derived tumour characteristics. CT-derived tumor characteristics included tumour size, the distance between the tumour edge and articular surface (DTA), and destruction of posterior cortical bone (DPC). Akaike information criterion (AIC) was used to select which variables to enter into multivariate logistic regression models and to determine significant factors affecting recurrence.
Results
The total recurrence rate was 21.0% (26/124), and the average follow-up time was 69.5 ± 31.2 months (24–127 months). Age, DTA (< 2 mm), and DPC were significantly related to recurrence, as determined by multivariate logistic regression. The C-index of the final model was 0.79 (95% CI: 0.71 to 0.88), representing a good model for predicting recurrence.
Conclusion
Identifying certain features of GCTB around the knee on CT has prognostic value for patients treated with extended curettage. A three-factor model predicts tumour recurrence well after extended curettage.
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