AUTHOR=Wang Lin-jian , Lv Peipei , Lou Yongli TITLE=A Novel TAF-Related Signature Based on ECM Remodeling Genes Predicts Glioma Prognosis JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.862723 DOI=10.3389/fonc.2022.862723 ISSN=2234-943X ABSTRACT=
The composition and abundance of immune and stromal cells in the tumor microenvironment (TME) dramatically affect prognosis. Infiltration of immunosuppressive tumor-associated fibroblasts (TAFs) is a hallmark of glioma. However, the mechanisms regulating TAF infiltration and the prognostic value of TAF-related genes in glioma remain unclear. In this study, we analyzed TAF infiltration by Estimating the Proportion of Immune and Cancer cells (EPIC) algorithm based on multiple glioma databases, including Glioblastoma and low-grade glioma merged cohort from The Cancer Genome Atlas (TCGA GBMLGG) cohort, the Chinese Glioma Genome Atlas (CGGA) #325 cohort, and the CGGA #693 cohort. TAF infiltration was increased in glioblastoma (GBM), and elevated TAF infiltration predicted poorer survival in gliomas. Gene enrichment analyses revealed that differentially expressed genes (DEGs) between low-grade glioma (LGG) and GBM were significantly enriched in the extracellular matrix (ECM) remodeling-related signaling, which may contribute to immune escape and resistance to immune checkpoint blockers (ICBs). To identify co-expression modules and candidate hub genes that may be associated with TAF infiltration, we performed weighted correlation network analysis (WGCNA) of DEGs. Afterward, univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analyses were performed to screen the positive prognostic hub genes. Finally, a high-efficacy prediction signature was constructed based on the expression of