DataSheet7_The Systematic Landscape of Nectin Family and Nectin-Like Molecules: Functions and Prognostic Value in Low Grade Glioma.PDF (894.42 kB)
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DataSheet7_The Systematic Landscape of Nectin Family and Nectin-Like Molecules: Functions and Prognostic Value in Low Grade Glioma.PDF

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posted on 01.12.2021, 04:42 authored by Yunhe Han, Cunyi Zou, Chen Zhu, Tianqi Liu, Shuai Shen, Peng Cheng, Wen Cheng, Anhua Wu

Objective: Nectin and nectin-like molecules (Necls) are molecules that are involved in cell–cell adhesion and other vital cellular processes. This study aimed to determine the expression and prognostic value of nectin and Necls in low grade glioma (LGG).

Materials and Methods: Differentially expressed nectin and Necls in LGG samples and the relationship of nectin family and Necls expression with prognosis, clinicopathological parameters, and survival were explored using The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), and Repository of Molecular Brain Neoplasia Data (REMBRANDT) databases. Univariate and multivariate Cox analysis models were performed to construct the prognosis-related gene signature. Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curves and multivariate Cox regression analysis, were utilized to evaluate the prognostic capacity of the four-gene signature. Gene ontology (GO)enrichment analysis and Gene Set Enrichment Analyses (GSEA) were performed to further understand the underlying molecular mechanisms. The Tumor Immune Estimation Resource (TIMER) was used to explore the relationship between the four-gene signature and tumor immune infiltration.

Results: Several nectin and Necls were differentially expressed in LGG. Kaplan–Meier survival analyses and Univariate Cox regression showed patients with high expression of NECTIN2 and PVR and low expression of CADM2 and NECTIN1 had worse prognosis among TCGA, CGGA, and REMBRANDT database. Then, a novel four-gene signature was built for LGG prognosis prediction. ROC curves, KM survival analyses, and multivariate COX regression indicated the new signature was an independent prognostic indicator for overall survival. Finally, GSEA and GO enrichment analyses revealed that immune-related pathways participate in the molecular mechanisms. The risk score had a strong negative correlation with tumor purity and data of TIMER showed different immune cell proportions (macrophage and myeloid dendritic cell) between high- and low-risk groups. Additionally, signature scores were positively related to multiple immune-related biomarkers (IL 2, IL8 and IFNγ).

Conclusion: Our results offer an extensive analysis of nectin and Necls levels and a four-gene model for prognostic prediction in LGG, providing insights for further investigation of CADM2, NECTIN1/2, and PVR as potential clinical and immune targets in LGG.

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