AUTHOR=Zhang Meng , Wang Dan , Su Lan , Ma Jingjiao , Wang Sizhen , Cui Meng , Hong Shunming , Guan Bing , Ma Xiaodong TITLE=Activity of Wnt/PCP Regulation Pathway Classifies Patients of Low-Grade Glioma Into Molecularly Distinct Subgroups With Prognostic Difference JOURNAL=Frontiers in Oncology VOLUME=11 YEAR=2021 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.726034 DOI=10.3389/fonc.2021.726034 ISSN=2234-943X ABSTRACT=

Wingless/Int-1 (Wnt) signaling is one of the most well-known oncogenic pathways. Numerous studies have uncovered an aberrant expression of Wnt in cancer and its association with multiple oncogenic processes, such as cell proliferation, epithelial–mesenchymal transition (EMT), and invasiveness. Most previous studies mainly focused on the canonical branch of Wnt signaling pathway, i.e., Wnt/β-catenin signaling. The Wnt/planar cell polarity (PCP) signaling pathway, as the most recently described branch of Wnt signaling, was much less investigated in oncology research. In this study, we thoroughly characterized the activity of the Wnt/PCP regulation pathway in low-grade glioma (LGG) patients. Subtyping based on the expression pattern of the Wnt/PCP regulation pathway revealed three (C1–C3) subgroups with significant survival differences. Each group displayed distinct genomic characteristics. For instance, C1 was enriched with capicua transcriptional repressor (CIC) truncating mutations and 1p19q codel. C2 was characterized with tumor protein p53 (TP53) and ATRX chromatin remodeler (ATRX) inactivating mutations but depletion of telomerase reverse transcriptase (TERT) promoter mutations. C3 showed elevated malignancy reflected from several oncogenic characteristics, such as tumor heterogeneity and cell stemness, and demonstrated the worst survival outcome. In addition, C3 showed elevated macrophage segregation via induction of cytokines that are able to enhance the permeability of the brain–blood barrier (BBB). Lastly, we developed a prognostic model based on the risk score system. Validation indicated that our model can independently predict the prognosis of LGG patients.