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Biomarker discovery using a comparative omics approach in a mouse model developing heterogeneous mammary cancer subtypes
Author(s) -
Pennings Jeroen L.A.,
Van Dycke Kirsten C.G.,
van Oostrom Conny T.M.,
Kuiper Raoul V.,
Rodenburg Wendy,
de Vries Annemieke
Publication year - 2012
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201100497
Subject(s) - breast cancer , proteomics , biomarker discovery , cancer , human protein atlas , biomarker , biology , proteome , computational biology , transcriptome , gene , cancer research , bioinformatics , gene expression , protein expression , genetics
Identification of biomarkers for early breast cancer detection in blood is a challenging task, since breast cancer is a heterogeneous disease with a wide range of tumor subtypes. This is envisioned to result in differences in serum protein levels. The p53 R270H/+ WAPC re mouse model is unique in that these mice spontaneously develop both ER − and ER + tumors, in proportions comparable to humans. Therefore, these mice provide a well‐suited model system to identify human relevant biomarkers for early breast cancer detection that are additionally specific for different tumor subtypes. Mammary gland tumors were obtained from p53 R270H/+ WAPC re mice and cellular origin, ER , and HER 2 status were characterized. We compared gene expression profiles for tumors with different characteristics versus control tissue, and determined genes differentially expressed across tumor subtypes. By using literature data (Gene Ontology, UniProt, and Human Plasma Proteome), we further identified protein candidate biomarkers for blood‐based detection of breast cancer. Functional overrepresentation analysis (using Gene Ontology, MS ig DB , B io GPS , Cancer G ene S ig DB , and proteomics literature data) showed enrichment for several processes relevant for human breast cancer. Finally, Human Protein Atlas data were used to obtain a prioritized list of 16 potential biomarkers that should facilitate further studies on blood‐based breast cancer detection in humans.