Integrative analysis of the cancer genome atlas and cancer cell lines encyclopedia large-scale genomic databases: MUC4/MUC16/MUC20 signature is associated with poor survival in human carcinomas

癌症基因组图谱和癌细胞系百科全书大型基因组数据库的整合分析:MUC4/MUC16/MUC20 特征与人类癌的不良生存率相关

阅读:1

Abstract

BACKGROUND: MUC4 is a membrane-bound mucin that promotes carcinogenetic progression and is often proposed as a promising biomarker for various carcinomas. In this manuscript, we analyzed large scale genomic datasets in order to evaluate MUC4 expression, identify genes that are correlated with MUC4 and propose new signatures as a prognostic marker of epithelial cancers. METHODS: Using cBioportal or SurvExpress tools, we studied MUC4 expression in large-scale genomic public datasets of human cancer (the cancer genome atlas, TCGA) and cancer cell line encyclopedia (CCLE). RESULTS: We identified 187 co-expressed genes for which the expression is correlated with MUC4 expression. Gene ontology analysis showed they are notably involved in cell adhesion, cell-cell junctions, glycosylation and cell signaling. In addition, we showed that MUC4 expression is correlated with MUC16 and MUC20, two other membrane-bound mucins. We showed that MUC4 expression is associated with a poorer overall survival in TCGA cancers with different localizations including pancreatic cancer, bladder cancer, colon cancer, lung adenocarcinoma, lung squamous adenocarcinoma, skin cancer and stomach cancer. We showed that the combination of MUC4, MUC16 and MUC20 signature is associated with statistically significant reduced overall survival and increased hazard ratio in pancreatic, colon and stomach cancer. CONCLUSIONS: Altogether, this study provides the link between (i) MUC4 expression and clinical outcome in cancer and (ii) MUC4 expression and correlated genes involved in cell adhesion, cell-cell junctions, glycosylation and cell signaling. We propose the MUC4/MUC16/MUC20(high) signature as a marker of poor prognostic for pancreatic, colon and stomach cancers.

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。