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The Glycosyltransferase XYLT1 Activates NF-κB Signaling to Promote Metastasis of Early-Stage Lung Adenocarcinoma.

Cancer research2025-02-24PubMed
Total: 88.5Innovation: 9Impact: 9Rigor: 9Citation: 8

Summary

XYLT1 is upregulated in metastatic recurrent early-stage lung adenocarcinoma and promotes metastasis by enabling sGAG conjugation of IκBα, enhancing its proteasomal degradation and activating NF-κB signaling. The study links proteoglycan modification to a canonical inflammatory pathway as a driver of metastasis, offering biomarker and therapeutic target opportunities.

Key Findings

  • XYLT1 is upregulated in metastatic recurrent lesions of early-stage lung adenocarcinoma and associates with poor prognosis.
  • XYLT1 activates NF-κB signaling by promoting sGAG-conjugated IκBα and its proteasomal degradation via enhanced IKK interaction.
  • In vitro and in vivo models demonstrate that XYLT1 augments lung adenocarcinoma cell survival and metastasis.
  • Proteoglycan modification-mediated NF-κB activation is identified as a driver of metastatic recurrence.

Clinical Implications

XYLT1 and sGAG-conjugated IκBα could serve as biomarkers for early metastatic risk stratification and as targets to disrupt NF-κB activation in adjuvant settings.

Why It Matters

This work uncovers a previously unrecognized proteoglycan-dependent mechanism directly activating NF-κB to drive metastasis in early-stage lung adenocarcinoma, with clear translational implications.

Limitations

  • Preclinical models require prospective clinical validation to establish predictive utility
  • Potential context specificity; tumor heterogeneity and off-target effects of pathway modulation were not addressed

Future Directions

Validate XYLT1/sGAG-IκBα as biomarkers in prospective cohorts; develop inhibitors targeting XYLT1 or the sGAG-IκBα-IKK axis; explore synergy with adjuvant therapies.

Study Information

Study Type
Basic/Mechanistic
Research Domain
Pathophysiology
Evidence Level
IV - Preclinical mechanistic study with in vitro and in vivo models and clinical correlation
Study Design
OTHER