ITEM METADATA RECORD
Title: Integrated molecular profiles of invasive breast tumors and ductal carcinoma in situ (DCIS) reveal differential vascular and interleukin signaling
Authors: Kristensen, Vessela N *
Vaske, Charles J *
Ursini-Siegel, Josie
Van Loo, Peter
Nordgard, Silje H
Sachidanandam, Ravi
Sørlie, Therese
Wärnberg, Fredrik
Haakensen, Vilde D
Helland, Åslaug
Naume, Bjørn
Perou, Charles M
Haussler, David
Troyanskaya, Olga G
Børresen-Dale, Anne-Lise # ×
Issue Date: Feb-2012
Publisher: National Academy of Sciences
Series Title: Proceedings of the National Academy of Sciences of the United States of America vol:109 issue:8 pages:2802-7
Article number: 10.1073/pnas.1108781108
Abstract: We use an integrated approach to understand breast cancer heterogeneity by modeling mRNA, copy number alterations, microRNAs, and methylation in a pathway context utilizing the pathway recognition algorithm using data integration on genomic models (PARADIGM). We demonstrate that combining mRNA expression and DNA copy number classified the patients in groups that provide the best predictive value with respect to prognosis and identified key molecular and stromal signatures. A chronic inflammatory signature, which promotes the development and/or progression of various epithelial tumors, is uniformly present in all breast cancers. We further demonstrate that within the adaptive immune lineage, the strongest predictor of good outcome is the acquisition of a gene signature that favors a high T-helper 1 (Th1)/cytotoxic T-lymphocyte response at the expense of Th2-driven humoral immunity. Patients who have breast cancer with a basal HER2-negative molecular profile (PDGM2) are characterized by high expression of protumorigenic Th2/humoral-related genes (24-38%) and a low Th1/Th2 ratio. The luminal molecular subtypes are again differentiated by low or high FOXM1 and ERBB4 signaling. We show that the interleukin signaling profiles observed in invasive cancers are absent or weakly expressed in healthy tissue but already prominent in ductal carcinoma in situ, together with ECM and cell-cell adhesion regulating pathways. The most prominent difference between low and high mammographic density in healthy breast tissue by PARADIGM was that of STAT4 signaling. In conclusion, by means of a pathway-based modeling methodology (PARADIGM) integrating different layers of molecular data from whole-tumor samples, we demonstrate that we can stratify immune signatures that predict patient survival.
URI: 
ISSN: 0027-8424
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Human Genome Laboratory
* (joint) first author
× corresponding author
# (joint) last author

Files in This Item:
File Description Status SizeFormat
Kristensen2012.pdf Published 1217KbAdobe PDFView/Open Request a copy

These files are only available to some KU Leuven Association staff members

 




All items in Lirias are protected by copyright, with all rights reserved.

© Web of science