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NF-κB-dependent Luciferase Activation and Quantification of Gene Expression in Salmonella Infected Tissue Culture Cells
Published on: January 12, 2020
Non-Canonical NF-κB Signaling Stratifies LGG into Subtypes with Distinct Molecular and Cellular Characteristic and
Minhua Lin1, Tianxiang Huang2, Xuan Wang1
1Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China.
Introduction:
NF-κB signaling is involved in a wide range of biological processes including cell proliferation, cell survival and immunity. Meanwhile, as one of the major oncogenic pathways, its upregulation has been observed in many cancer types. Compared with canonical NF-κB signaling, its non-canonical branch was much less studied in cancerous context.
Methods:
In this study, we leveraged multi-omics data across multiple platforms to investigate the activity of non-canonical NF-κB signaling in low-grade glioma (LGG) and explore its connection with molecular characteristics of LGG.
Results:
We found that non-canonical NF-κB signaling could classify LGG patients into subgroups with significant survival difference. Non-canonical NF-κB-low group enriched with oligodendroglioma featured by CIC mutations and 1p19q co-deletion. On the another hand, LGG in non-canonical NF-κB-high group showed high frequency of EGFR mutations but relatively low frequency of IDH mutations. In addition, LGG in this group reflected immunosuppressive environment characterized by high level of cytotoxic T cell exhaustion and macrophage M2 infiltration. More comprehensive evaluation implied that LGG in non-canonical NF-κB-high group reflected significantly higher immunogenicity. Through a series of feature selection technique, we developed a model that can predict the prognosis of LGG patients in a cost-effective way.
Conclusion:
Our analysis demonstrated the prognostic value of non-canonical NF-κB signaling in LGG. The survival difference between non-canonical NF-κB stratified groups may be explained by their distinct molecular characteristics as well as cellular context. Our prognostic model may help in offering better therapeutic strategy and clinical management.
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