Elevated insulin-like growth factor 2 mRNA binding protein 1 levels predict a poor prognosis in patients with breast carcinoma using an integrated multi-omics data analysis

利用整合多组学数据分析发现,胰岛素样生长因子2 mRNA结合蛋白1水平升高可预测乳腺癌患者预后不良。

阅读:1

Abstract

Background: Insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1) controls the cytoplasmic fate of certain mRNAs and is hypothesized to predict a poor patient prognosis in several malignant tumors. However, the prognostic relevance of IGF2BP1 in breast cancer remains debatable. Methods: We interrogated large publicly available datasets from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and cBioportal databases to analyze the genetic alterations in the expression levels of IGF2BP1 in patients with invasive breast carcinoma (BRCA), and to discern the prognostic value of IGF2BP1 in BRCA. We applied Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genome (KEGG), and gene set enrichment analysis (GSEA) to uncover a functional association between IGF2BP1 and BRCA using differentially expressed genes (DEGs), and we screened genes and proteins related to BRCA. Results: We determined that both genetic alterations in IGF2BP1 (approximately 10%) and an increase in IGF2BP1 mRNA levels were related to certain cancer subtypes and an unfavorable prognosis in BRCA patients, and we then established an OS nomogram upon our multivariate regression model. The DEGs and IGF2BP1-correlated genes/proteins that implied the involvement of cornification, keratinization, drug/xenobiotic metabolism by cytochrome P450, chemical carcinogenesis, cell interactions, and cell adhesion to the extracellular matrix (ECM) pathways with respect to the prognostic relevance of IGF2BP1. Conclusion: In summary, our results indicated that both genetic alterations in IGF2BP1 and increased levels of IGF2BP1 mRNA and protein predict a poor patient prognosis in BRCA patients.

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。