Abstract
BACKGROUND: Within the realm of primary brain tumors, specifically glioblastoma (GBM), presents a notable obstacle due to their unfavorable prognosis and differing median survival rates contingent upon tumor grade and subtype. Despite a plethora of research connecting cardiotrophin-1 (CTF1) modifications to a range of illnesses, its correlation with glioma remains uncertain. This study investigated the clinical value of CTF1 in glioma and its potential as a biomarker of the disease. METHODS: Glioma project in The Cancer Genome Atlas (TCGA) database served as the training cohort, and CGGA 325 series in the Chinese Glioma Genome Atlas (CGGA) database served as the external independent validation cohort. First, the difference in the expression level of CTF1 between glioma tissue and normal tissue was analyzed, and the results were verified with the CGGA database. The relationship between CTF1 expression and the prognosis of glioma patients was evaluated using Univariate and Multivariate Cox analysis and the Kaplan-Meier (KM) curve. We used CIBERSOFT to explore the association between CTF1 and immune cell infiltration in GBM, as well as performing gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) analyses. Furthermore, we analyzed the relationship between CTF1 and gene mutations and drug sensitivity. Using Weighted gene co-expression network analysis (WGCNA) analysis, we pinpointed the gene set most correlated with CTF1 and conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) gene enrichment analyses to anticipate the pathways that could be influenced by CTF1. Finally, we constructed a nomogram using a multifactorial regression model to further predict patient prognosis. RESULTS: CTF1 expression was significantly elevated in glioma tissues compared to normal tissues in the TCGA dataset (P<0.001) and was associated with poorer survival in both TCGA and CGGA datasets (P<0.001). Receiver operating characteristic (ROC) analysis demonstrated the diagnostic potential of CTF1, with an area under the curve (AUC) of 0.889 [95% confidence interval (CI): 0.803-0.974] in TCGA and 0.664 (95% CI: 0.599-0.729) in CGGA. High CTF1 levels were correlated with advanced glioma grades, and Cox regression analysis identified CTF1 as an independent risk factor. A nomogram incorporating CTF1 levels, isocitrate dehydrogenase 1 (IDH1) mutation status, O6-methylguanine-DNA methyltransferase (MGMT) methylation status, age, and gender were developed and validated to predict 1- and 2-year survival probabilities. In GBM, drug sensitivity analysis revealed significant associations between CTF1 expression and responsiveness to gemcitabine, dasatinib, and other agents. CTF1 expression was also linked to immune infiltration (monocytes, neutrophils, M0 macrophages) and pathways involved in tumor progression, including IL2_STAT5, P53, and IL6_JAK_STAT3 signaling pathways. CONCLUSIONS: CTF1 could serve as a prognostic marker for glioma. It acts as a predictive indicator and is associated with immune cell infiltration in GBM. These findings provide a foundation for further research into the molecular function of CTF1 and offer new insights for exploring the underlying mechanisms and developing treatments for glioma.