Unsupervised hierarchical clustering of pancreatic adenocarcinoma dataset from TCGA defines a mucin expression profile that impacts overall survival

19Citations
Citations of this article
18Readers
Mendeley users who have this article in their library.

Abstract

Mucins are commonly associated with pancreatic ductal adenocarcinoma (PDAC) that is a deadly disease because of the lack of early diagnosis and efficient therapies. There are 22 mucin genes encoding large O-glycoproteins divided into two major subgroups: membrane-bound and secreted mucins. We investigated mucin expression and their impact on patient survival in the PDAC dataset from The Cancer Genome Atlas (PAAD-TCGA). We observed a statistically significant increased messenger RNA (mRNA) relative level of most of the membrane-bound mucins (MUC1/3A/4/12/13/16/17/20), secreted mucins (MUC5AC/5B), and atypical mucins (MUC14/18) compared to normal pancreas. We show that MUC1/4/5B/14/17/20/21 mRNA levels are associated with poorer survival in the high-expression group compared to the low-expression group. Using unsupervised clustering analysis of mucin gene expression patterns, we identified two major clusters of patients. Cluster #1 harbors a higher expression of MUC15 and atypical MUC14/MUC18, whereas cluster #2 is characterized by a global overexpression of membrane-bound mucins (MUC1/4/16/17/20/21). Cluster #2 is associated with shorter overall survival. The patient stratification appears to be independent of usual clinical features (tumor stage, differentiation grade, lymph node invasion) suggesting that the pattern of membrane-bound mucin expression could be a new prognostic marker for PDAC patients.

Cite

CITATION STYLE

APA

Jonckheere, N., Auwercx, J., Bachir, E. H., Coppin, L., Boukrout, N., Vincent, A., … Seuningen, I. V. (2020). Unsupervised hierarchical clustering of pancreatic adenocarcinoma dataset from TCGA defines a mucin expression profile that impacts overall survival. Cancers, 12(11), 1–17. https://doi.org/10.3390/cancers12113309

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free