| 1. |
- Kristensen, Vessela N, et al.
(author)
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Genetic variation in putative regulatory loci controlling gene expression in breast cancer
- 2006
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 103:20, s. 7735-7740
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Journal article (other academic/artistic)abstract
- Candidate single-nucleotide polymorphisms (SNPs) were analyzed for associations to an unselected whole genome pool of tumor mRNA transcripts in 50 unrelated patients with breast cancer. SNPs were selected from 203 candidate genes of the reactive oxygen species pathway. We describe a general statistical framework for the simultaneous analysis of gene expression data and SNP genotype data measured for the same cohort, which revealed significant associations between subsets of SNPs and transcripts, shedding light on the underlying biology. We identified SNPs in EGF, IL1A, MAPK8, XPC, SOD2, and ALOX12 that are associated with the expression patterns of a significant number of transcripts, indicating the presence of regulatory SNPs in these genes. SNPs were found to act in trans in a total of 115 genes. SNPs in 43 of these 115 genes were found to act both in cis and in trans. Finally, subsets of SNPs that share significantly many common associations with a set of transcripts (biclusters) were identified. The subsets of transcripts that are significantly associated with the same set of SNPs or to a single SNP were shown to be functionally coherent in Gene Ontology and pathway analyses and coexpressed in other independent data sets, suggesting that many of the observed associations are within the same functional pathways. To our knowledge, this article is the first study to correlate SNP genotype data in the germ line with somatic gene expression data in breast tumors. It provides the statistical framework for further genotype expression correlation studies in cancer data sets.
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| 2. |
- Kristensen, Vessela N, et al.
(author)
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Integrated molecular profiles of invasive breast tumors and ductal carcinoma in situ (DCIS) reveal differential vascular and interleukin signaling
- 2012
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In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 109:8, s. 2802-2807
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Journal article (peer-reviewed)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.
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| 3. |
- Nordgard, Silje H, et al.
(author)
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Genome-wide analysis identifies 16q deletion associated with survival, molecular subtypes, mRNA expression, and germline haplotypes in breast cancer patients
- 2008
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In: Genes, Chromosomes and Cancer. - : Wiley. - 1045-2257 .- 1098-2264. ; 47:8, s. 680-696
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Journal article (peer-reviewed)abstract
- Breast carcinomas are characterized by DNA copy number alterations (CNAs) with biological and clinical significance. This explorative study integrated CNA, expression, and germline genotype data of 112 early-stage breast cancer patients. Recurrent CNAs differed substantially between tumor subtypes classified according to expression pattern. Deletion of 16q was overrepresented in Luminal A, and a predictor of good prognosis, both overall and for the nonluminal A subgroups. The deleted region most significantly associated with survival mapped to 16q22.2, harboring the genes TXNL4B and DXH38, whose expression was strongly correlated with the deletion. The area most frequently deleted resided on 16q23.1, 3.5 MB downstream of the area most significantly associated with survival, and included the tumor suppressor gene ADAMTS18 and the cell recognition gene CNTNAP4. Whole-genome association analysis identified germline single nucleotide polymorphisms (SNPs) and their corresponding haplotypes, residing on several different chromosomes, to be associated with deletion of 16q. The genes where these SNPs reside encode proteins involved in the extracellular matrix (CHST3 and SPOCK2), in regulation of the cell cycle (JMY, PTPRN2, and Cwf19L2) and chromosome stability (KPNB1).
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