An integrated bioinformatic investigation of focal adhesion-related genes in glioma followed by preliminary validation of COL1A2 in tumorigenesis

对胶质瘤中粘着斑相关基因进行综合生物信息学研究,并初步验证 COL1A2 在肿瘤发生中的作用

阅读:9
作者:Guojun Yao, Ling Deng, Xinquan Long, Yufan Zhou, Xiang Zhou

Abstract

Focal adhesions (FAs) allow cells to contact the extracellular matrix, helping to maintain tension and enabling signal transmission in cell migration, differentiation, and apoptosis. In addition, FAs are associated with changes in the tumor microenvironment (TME) that lead to malignant progression and drug resistance in tumors. However, there are still few studies on the comprehensive analysis of focal adhesion-related genes (FARGs) in glioma. Expression data and clinical information of glioma samples were downloaded from public databases. Two distinct molecular subtypes were identified based on FARGs using an unsupervised consensus clustering algorithm. A scoring system consisting of nine FARGs was constructed using integrated LASSO regression and multivariate Cox regression. It not only has outstanding prognostic value but also can guide immunotherapy of glioma patients, which was verified in TCGA, CGGA, GSE16011, and IMvigor210 cohorts. The results of bioinformatics analysis, immunohistochemistry staining, and western blotting all revealed that the expression of COL1A2 was up-regulated in glioblastoma and related to poor prognosis outcomes in patients from public datasets. COL1A2 promotes the proliferation, migration, and invasion of glioblastoma cells. A positive correlation between COL1A2 and CD8 was determined in GBM specimens from eight patients. Moreover, the results of cell co-cultured assay showed that COL1A2 participated in the killing of GBM cells by Jurkat cells. Our study indicates that the FARGs have prominent application value in the identification of molecular subtypes and prediction of survival outcomes in glioma patients. Bioinformatics analysis and experimental verification provide a direction for further research on FARGs.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。