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Expression and differential expression analysis of breast cancer patient samples and normal samples

ABSTRACT: Expression and differential expression analysis of breast cancer patient samples and normal samples from breast reduction operations. Fresh frozen tumor biopsies from early breast cancer cases were collected from 920 patients included in the Oslo Micrometastasis (MicMa) Study -- Oslo I from various hospitals between 1995 and 1998 (Naume et al. "Presence of bone marrow micrometastasis is associated with different recurrence risk within molecular subtypes of breast cancer." Mol Oncol 2007, 1: 160-171; Wiedswang et al. "Detection of isolated tumor cells in bone marrow is an independent prognostic factor in breast cancer." J Clin Oncol 2003, 21: 3469-3478.). Breast tissue samples from breast reduction operations were provided from the Colosseum Clinic, Oslo in co-operation with Akershus University Hospital, Lørenskog and are referred to as normal tissue. Expression and differential expression was assessed by using an Agilent custom microarray (244K, nONCOchip). The custom array contains probes for genomic regions that have been found to be differentially expressed (i) throughout cell cycle progression, (ii) in response to the anti-proliferative and pro-apoptotic p53 pathway, and (iii) the anti-apoptotic and pro-proliferative STAT-3 pathway by employing TAS (Kampa et al. "Novel RNAs identified from an in-depth analysis of the transcriptome of human chromosomes 21 and 22". Genome Research, 14:331-42, 2004). In addition, the Agilent custom array (244K) interrogates probes for genomic regions predicted to contain a conserved secondary structure identified by RNAz (Washietl et al. "Fast and reliable prediction of noncoding RNAs." Proc Natl Acad Sci USA. 102:2454-9, 2005.) or Evofold (Pedersen et al. "Identification and classification of conserved RNA secondary structures in the human genome." PLoS Comput Biol. 2:e33, 2006.), as well as known non-coding RNAs from public databases, and the Agilent mRNA probe set 014850. We analyzed 5 to 6 arrays each for breast cancer patient samples and normal samples.

ORGANISM(S): Homo sapiens

SUBMITTER: Reiche Kristin

PROVIDER: S-ECPF-GEOD-50428 | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:Expression and differential expression analysis of breast cancer patient samples and normal samples from breast reduction operations. Fresh frozen tumor biopsies from early breast cancer cases were collected from 920 patients included in the Oslo Micrometastasis (MicMa) Study -- Oslo I from various hospitals between 1995 and 1998 (Naume et al. "Presence of bone marrow micrometastasis is associated with different recurrence risk within molecular subtypes of breast cancer." Mol Oncol 2007, 1: 160-171; Wiedswang et al. "Detection of isolated tumor cells in bone marrow is an independent prognostic factor in breast cancer." J Clin Oncol 2003, 21: 3469-3478.). Breast tissue samples from breast reduction operations were provided from the Colosseum Clinic, Oslo in co-operation with Akershus University Hospital, LM-CM-8renskog and are referred to as normal tissue. Expression and differential expression was assessed by using an Agilent custom microarray (244K, nONCOchip). The custom array contains probes for genomic regions that have been found to be differentially expressed (i) throughout cell cycle progression, (ii) in response to the anti-proliferative and pro-apoptotic p53 pathway, and (iii) the anti-apoptotic and pro-proliferative STAT-3 pathway by employing TAS (Kampa et al. "Novel RNAs identified from an in-depth analysis of the transcriptome of human chromosomes 21 and 22". Genome Research, 14:331-42, 2004). In addition, the Agilent custom array (244K) interrogates probes for genomic regions predicted to contain a conserved secondary structure identified by RNAz (Washietl et al. "Fast and reliable prediction of noncoding RNAs." Proc Natl Acad Sci USA. 102:2454-9, 2005.) or Evofold (Pedersen et al. "Identification and classification of conserved RNA secondary structures in the human genome." PLoS Comput Biol. 2:e33, 2006.), as well as known non-coding RNAs from public databases, and the Agilent mRNA probe set 014850. We analyzed 5 to 6 arrays each for breast cancer patient samples and normal samples.

Project description:PURPOSE:Previous studies of breast tissue gene expression have shown that the extratumoral microenvironment has substantial variability across individuals, some of which can be attributed to epidemiologic factors. To evaluate how mammographic density and breast tissue composition relate to extratumoral microenvironment gene expression, we used data on 121 patients with breast cancer from the population-based Polish Women's Breast Cancer Study. EXPERIMENTAL DESIGN:Breast cancer cases were classified on the basis of a previously reported, biologically defined extratumoral gene expression signature with two subtypes: an Active subtype, which is associated with high expression of genes related to fibrosis and wound response, and an Inactive subtype, which has high expression of cellular adhesion genes. Mammographic density of the contralateral breast was assessed using pretreatment mammograms and a quantitative, reliable computer-assisted thresholding method. Breast tissue composition was evaluated on the basis of digital image analysis of tissue sections. RESULTS:The Inactive extratumoral subtype was associated with significantly higher percentage mammographic density (PD) and dense area (DA) in univariate analysis (PD: P = 0.001; DA: P = 0.049) and in multivariable analyses adjusted for age and body mass index (PD: P = 0.004; DA: P = 0.049). Inactive/higher mammographic density tissue was characterized by a significantly higher percentage of stroma and a significantly lower percentage of adipose tissue, with no significant change in epithelial content. Analysis of published gene expression signatures suggested that Inactive/higher mammographic density tissue expressed increased estrogen response and decreased TGF-? signaling. CONCLUSIONS:By linking novel molecular phenotypes with mammographic density, our results indicate that mammographic density reflects broad transcriptional changes, including changes in both epithelia- and stroma-derived signaling.

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Expression and differential expression analysis of breast cancer patient samples and normal samples

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