Integrated analysis reveals critical genomic regions in prostate tumor microenvironment associated with clinicopathologic phenotypes - Abstract
We sought to integrate global genomic structural and expressional alterations in prostate cancer epithelium and stroma and their association with clinicopathologic features.
EXPERIMENTAL DESIGN: We conducted a genome-wide LOH/allelic imbalance (AI) scan of DNA from epithelium and stroma of 116 prostate cancers. LOH/AI hot or cold spots were defined as the markers with significantly higher or lower LOH/AI frequencies compared with the average frequency for markers along the same chromosome. These data were then integrated with publicly available transcriptome data sets and our experimentally derived data. Immunohistochemistry on an independent series was used for validation.
RESULTS: Overall, we identified 43 LOH/AI hot/cold spots, 17 in epithelium and stroma (P < 0.001), 18 only in epithelium (P < 0.001), and eight only in stroma (P < 0.001). Hierarchical clustering of expression data supervised by genes within LOH/AI hot/cold spots in both epithelium and stroma accurately separated samples into normal epithelium, primary cancer, and metastatic cancer groups, which could not be achieved with data from only epithelium. Importantly, our experimental expression data of the genes within the LOH/AI hot/cold spots in stroma accurately clustered normal stroma from cancer stroma. We also identified 15 LOH/AI markers that were associated with Gleason score, which were validated functionally in each compartment by transcriptome data. Independent immunohistochemical validation of STIM2 within a stromal significant LOH marker (identified as associated with Gleason grade) confirmed its downregulation in the transition from moderate to high Gleason grade.
CONCLUSIONS: Compartment-specific genomic and transcriptomic alterations accurately distinguish clinical and pathologic outcomes, suggesting new biomarkers for prognosis and targeted therapeutics.
Written by:
Ashida S, Orloff MS, Bebek G, Zhang L, Zheng P, Peehl DM, Eng C. Are you the author?
Genomic Medicine Institute, Section of Statistical Genetics and Bioinformatics, Department of Quantitative Health Sciences, Lerner Research Institute; Taussig Cancer Institute; Stanley Shalom Zielony Institute for Nursing Excellence, Cleveland Clinic; Center for Proteomics and Bioinformatics, Department of Genetics, CASE Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland; Department of Pathology, The Ohio State University, Columbus, Ohio; Division of Immunotherapy, Department of Surgery, and Program of Molecular Medicine, Comprehensive Cancer Center, University of Michigan Medical Center, Ann Arbor, Michigan; and Department of Urology, Stanford University School of Medicine, Stanford, California.
Reference: Clin Cancer Res. 2012 Mar 15;18(6):1578-1587. Epub 2012 Jan 24.
PubMed Abstract
PMID: 22275508
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