Glioma IL13Rα2 Is Associated with Mesenchymal Signature Gene Expression and Poor Patient Prognosis

Christine E Brown, Charles D Warden, Renate Starr, Xutao Deng, Behnam Badie, Yate-Ching Yuan, Stephen J Forman and Michael E Barish

PLOS ONE, 2013, vol. 8, issue 10, 1-

Abstract: A major challenge for successful immunotherapy against glioma is the identification and characterization of validated targets. We have taken a bioinformatics approach towards understanding the biological context of IL-13 receptor α2 (IL13Rα2) expression in brain tumors, and its functional significance for patient survival. Querying multiple gene expression databases, we show that IL13Rα2 expression increases with glioma malignancy grade, and expression for high-grade tumors is bimodal, with approximately 58% of WHO grade IV gliomas over-expressing this receptor. By several measures, IL13Rα2 expression in patient samples and low-passage primary glioma lines most consistently correlates with the expression of signature genes defining mesenchymal subclass tumors and negatively correlates with proneural signature genes as defined by two studies. Positive associations were also noted with proliferative signature genes, whereas no consistent associations were found with either classical or neural signature genes. Probing the potential functional consequences of this mesenchymal association through IPA analysis suggests that IL13Rα2 expression is associated with activation of proinflammatory and immune pathways characteristic of mesenchymal subclass tumors. In addition, survival analyses indicate that IL13Rα2 over-expression is associated with poor patient prognosis, a single gene correlation ranking IL13Rα2 in the top ~1% of total gene expression probes with regard to survival association with WHO IV gliomas. This study better defines the functional consequences of IL13Rα2 expression by demonstrating association with mesenchymal signature gene expression and poor patient prognosis. It thus highlights the utility of IL13Rα2 as a therapeutic target, and helps define patient populations most likely to respond to immunotherapy in present and future clinical trials.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0077769 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 77769&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0077769

DOI: 10.1371/journal.pone.0077769

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().