Abstract
Extracellular matrix protein 2 (ECM2), which regulates cell proliferation and differentiation, has recently been reported as a prognostic indicator for multiple cancers, but its value in lower grade glioma (LGG) remains unknown. In this study, LGG transcriptomic data of 503 cases in The Cancer Genome Atlas (TCGA) database and 403 cases in The Chinese Glioma Genome Atlas (CGGA) database were collected to analyze ECM2 expression patterns and the relationship with clinical characteristics, prognosis, enriched signaling pathways, and immune-related markers. In addition, a total of 12 laboratory samples were used for experimental validation. Wilcoxon or Kruskal-Wallis tests demonstrated highly expressed ECM2 in LGG was positively associated with malignant histological features and molecular features such as recurrent LGG and isocitrate dehydrogenase (IDH) wild-type. Also, Kaplan-Meier (KM) curves proved high ECM2 expression could predict shorter overall survival in LGG patients, as multivariate analysis and meta-analysis claimed ECM2 was a deleterious factor for LGG prognosis. In addition, the enrichment of immune-related pathways for ECM2, for instance JAK-STAT pathway, was obtained by Gene Set Enrichment Analysis (GSEA) analysis. Furthermore, positive relationships between ECM2 expression with immune cells infiltration and cancer-associated fibroblasts (CAFs), iconic markers (CD163), and immune checkpoints (CD274, encoding PD-L1) were proved by Pearson correlation analysis. Finally, laboratory experiments of RT-qPCR and immunohistochemistry showed high expression of ECM2, as well as CD163 and PD-L1 in LGG samples. This study identifies ECM2, for the first time, as a subtype marker and prognostic indicator for LGG. ECM2 could also provide a reliable guarantee for further personalized therapy, synergizing with tumor immunity, to break through the current limitations and thus reinvigorating immunotherapy for LGG. AVAILABILITY OF DATA AND MATERIALS: Raw data from all public databases involved in this study are stored in the online repository (chengMD2022/ECM2 (github.com)).