Minhua Lin1, Tianxiang Huang2, Xuan Wang1, Xuenan Li3, Jingjiao Ma3, Lan Su3, Jun Wu2. 1. Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China. 2. Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China. 3. Beijing Genetron Health, Co. Ltd, Beijing, 102206, People's Republic of China.
Abstract
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.
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.
Authors: Mark Ayers; Jared Lunceford; Michael Nebozhyn; Erin Murphy; Andrey Loboda; David R Kaufman; Andrew Albright; Jonathan D Cheng; S Peter Kang; Veena Shankaran; Sarina A Piha-Paul; Jennifer Yearley; Tanguy Y Seiwert; Antoni Ribas; Terrill K McClanahan Journal: J Clin Invest Date: 2017-06-26 Impact factor: 14.808
Authors: Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov Journal: Proc Natl Acad Sci U S A Date: 2005-09-30 Impact factor: 11.205
Authors: Michael Weller; Roger Stupp; Monika E Hegi; Martin van den Bent; Joerg C Tonn; Marc Sanson; Wolfgang Wick; Guido Reifenberger Journal: Neuro Oncol Date: 2012-09 Impact factor: 12.300
Authors: Julien Fourcade; Zhaojun Sun; Mourad Benallaoua; Philippe Guillaume; Immanuel F Luescher; Cindy Sander; John M Kirkwood; Vijay Kuchroo; Hassane M Zarour Journal: J Exp Med Date: 2010-09-06 Impact factor: 14.307
Authors: Chiara Porta; Monica Rimoldi; Geert Raes; Lea Brys; Pietro Ghezzi; Diana Di Liberto; Francesco Dieli; Serena Ghisletti; Gioacchino Natoli; Patrick De Baetselier; Alberto Mantovani; Antonio Sica Journal: Proc Natl Acad Sci U S A Date: 2009-08-17 Impact factor: 11.205
Authors: Shuiping Tu; Govind Bhagat; Guanglin Cui; Shigeo Takaishi; Evelyn A Kurt-Jones; Barry Rickman; Kelly S Betz; Melitta Penz-Oesterreicher; Olle Bjorkdahl; James G Fox; Timothy C Wang Journal: Cancer Cell Date: 2008-11-04 Impact factor: 31.743
Authors: Emily L Hopewell; Weipeng Zhao; William J Fulp; Crystina C Bronk; Alexis S Lopez; Michael Massengill; Scott Antonia; Esteban Celis; Eric B Haura; Steven A Enkemann; Dung-Tsa Chen; Amer A Beg Journal: J Clin Invest Date: 2013-05-01 Impact factor: 14.808