Predicting a local recurrence after breast-conserving therapy by gene expression profiling

INTRODUCTION: To tailor local treatment in breast cancer patients there is a need for predicting ipsilateral recurrences after breast-conserving therapy. After adequate treatment (excision with free margins and radiotherapy), young age and incompletely excised extensive intraductal component are predictors for local recurrence, but many local recurrences can still not be predicted. Here we have used gene expression profiling by microarray analysis to identify gene expression profiles that can help to predict local recurrence in individual patients. METHODS: By using previously established gene expression profiles with proven value in predicting metastasis-free and overall survival (wound-response signature, 70-gene prognosis profile and hypoxia-induced profile) and training towards an optimal prediction of local recurrences in a training series, we establish a classifier for local recurrence after breast-conserving therapy. RESULTS: Validation of the different gene lists shows that the wound-response signature is able to separate patients with a high (29%) or low (5%) risk of a local recurrence at 10 years (sensitivity 87.5%, specificity 75%). In multivariable analysis the classifier is an independent predictor for local recurrence. CONCLUSION: Our findings indicate that gene expression profiling can identify subgroups of patients at increased risk of developing a local recurrence after breast-conserving therapy

Induction of interferon response in two types of breast cancer cell lines

MDA-MB231 cells were incubated in conditioned media from CCL-171 monoculture, MDA-MB231 monoculture, T47D monoculture, CCL-171/MDA-MB231 co-culture and CCL-171/T47D co-culture. gene expression was determined by quantitative RT-PCR. The gene expression level of GAPDH was used for normalization between the samples. A strong induction of by the supernatant from the CCL-171/MDA-MB231 co-culture can be seen in MDA-MB231. Incubation of T47D cells with conditioned media from CCL-171 monoculture, MDA-MB231 monoculture, T47D monoculture, CCL-171/MDA-MB231 co-culture and CCL-171/T47D co-culture showed that only the CCL-171/MDA-MB231 co-culture supernatant induced gene expression, although to a much lesser extent than in MDA-MB231 cells. Gene expression levels of were determined by quantitative RT-PCR. CCL-171 cells show much higher expression levels when isolated by FACS after co-culture with MDA-MB231 than with T47D cells. Expression levels in tumor cells are shown as controls. The error bars show the standard deviation from the normalized mean.<p><b>Copyright information:</b></p><p>Taken from "Characterization of heterotypic interaction effects to deconvolute global gene expression profiles in cancer"</p><p>http://genomebiology.com/2007/8/9/R191</p><p>Genome Biology 2007;8(9):R191-R191.</p><p>Published online 14 Sep 2007</p><p>PMCID:PMC2375029.</p><p></p

Correlation of the 70 genes signature 38, the wound signature 24, the hypoxia signature 25 and the interferon response score in the NKI dataset

Pairwise scatterplot-matrix of four gene signatures. Pearson correlations are shown in the lower part of each plot.<p><b>Copyright information:</b></p><p>Taken from "Characterization of heterotypic interaction effects to deconvolute global gene expression profiles in cancer"</p><p>http://genomebiology.com/2007/8/9/R191</p><p>Genome Biology 2007;8(9):R191-R191.</p><p>Published online 14 Sep 2007</p><p>PMCID:PMC2375029.</p><p></p

Immunohistochemical staining of STAT1 in a cohort of primary breast cancers: Kaplan-Meier disease-specific survival curve for 353 primary tumors assessed for STAT1

The red curve shows 102 patients bearing tumors with high STAT1 expression whereas the blue curve represents 251 patients with low or absent STAT1 expression. X = censored data.<p><b>Copyright information:</b></p><p>Taken from "Characterization of heterotypic interaction effects to deconvolute global gene expression profiles in cancer"</p><p>http://genomebiology.com/2007/8/9/R191</p><p>Genome Biology 2007;8(9):R191-R191.</p><p>Published online 14 Sep 2007</p><p>PMCID:PMC2375029.</p><p></p

Effect of heterotypic interaction between breast cancer cell line MDA-MB231 and CCL-171 fibroblasts

Biologically independent replicates of the monocultured fibroblast CCL-171, the breast cancer cell line MDA-MB231 and the mixed co-culture of CCL-171 and MDA-MB231 were grown for 48 h at low serum conditions and characterized by DNA microarray hybridization. Hierarchical clustering of a total of 4,333 elements that display a greater than 3-fold variance in expression in more than 3 different experimental samples. Data from individual elements or genes are represented as single rows, and different experiments are shown as columns. Red and green denote expression levels of the samples. The intensity of the color reflects the magnitude of the deviation from baseline. Unsupervised hierarchical clustering of the experiments grouped the biological replicates together. Gene expression varied considerably between fibroblast and MDA-MB231 cultures, as expected for cells of mesenchymal or epithelial origin, respectively. The co-culture profile showed mainly intermediate expression levels. However, the vertical black bar marks a cluster of genes induced in all co-cultures compared to both monocultures, indicating that they are induced by heterotypic interaction. Zooming in on the genes up-regulated in co-culture compared to monocultures reveals that they are associated with the response to interferon.<p><b>Copyright information:</b></p><p>Taken from "Characterization of heterotypic interaction effects to deconvolute global gene expression profiles in cancer"</p><p>http://genomebiology.com/2007/8/9/R191</p><p>Genome Biology 2007;8(9):R191-R191.</p><p>Published online 14 Sep 2007</p><p>PMCID:PMC2375029.</p><p></p

Overview of gene expression changes over multiple co-cultures of breast cancer cell lines and normal breast epithelial cells with fibroblasts

Correlation of the measured co-culture gene expression levels and their estimated expression levels based on the proportional contribution of each cell type determined by a linear regression fit of the monoculture to the co-culture data. Fold change of each gene associated with co-culturing of MDA-MB231 and CCL-171. Genes of the interferon response gene set (Additional data file 1) as determined by SAM are indicated in red. Fold change in expression of the interferon response gene set (Additional data file 1) in co-culture of MCF-7, HMECs and MDA-MB-231 with either the CCL-171 lung fibroblast or the HTB-125 breast fibroblast, showing that CCL-171 and HTB-125 induce a distinct, but very similar response in co-culture with different epithelial cells. Overview of collapsed data from repeat co-culture experiments of eight benign and malignant epithelial cells with three different fibroblasts. Hierarchical clustering of the interaction effects of 3,000 genes in co-cultures of 7 breast cancer cell lines and normal breast epithelial cells with fibroblasts. Red and green denote relative changes in expression associated heterotypic interaction. The magnitude of the relative change is given by color intensity.<p><b>Copyright information:</b></p><p>Taken from "Characterization of heterotypic interaction effects to deconvolute global gene expression profiles in cancer"</p><p>http://genomebiology.com/2007/8/9/R191</p><p>Genome Biology 2007;8(9):R191-R191.</p><p>Published online 14 Sep 2007</p><p>PMCID:PMC2375029.</p><p></p

Predicting a local recurrence after breast-conserving therapy by gene expression profiling.

IntroductionTo tailor local treatment in breast cancer patients there is a need for predicting ipsilateral recurrences after breast-conserving therapy. After adequate treatment (excision with free margins and radiotherapy), young age and incompletely excised extensive intraductal component are predictors for local recurrence, but many local recurrences can still not be predicted. Here we have used gene expression profiling by microarray analysis to identify gene expression profiles that can help to predict local recurrence in individual patients.MethodsBy using previously established gene expression profiles with proven value in predicting metastasis-free and overall survival (wound-response signature, 70-gene prognosis profile and hypoxia-induced profile) and training towards an optimal prediction of local recurrences in a training series, we establish a classifier for local recurrence after breast-conserving therapy.ResultsValidation of the different gene lists shows that the wound-response signature is able to separate patients with a high (29%) or low (5%) risk of a local recurrence at 10 years (sensitivity 87.5%, specificity 75%). In multivariable analysis the classifier is an independent predictor for local recurrence.ConclusionOur findings indicate that gene expression profiling can identify subgroups of patients at increased risk of developing a local recurrence after breast-conserving therapy

A Mouse Mammary Gland Involution mRNA Signature Identifies Biological Pathways Potentially Associated with Breast Cancer Metastasis

Mouse mammary gland involution resembles a wound healing response with suppressed inflammation. Wound healing and inflammation are also associated with tumour development, and a 'wound-healing' gene expression signature can predict metastasis formation and survival. Recent studies have shown that an involuting mammary gland stroma can promote metastasis. It could therefore be hypothesised that gene expression signatures from an involuting mouse mammary gland may provide new insights into the physiological pathways that promote breast cancer progression. Indeed, using the HOPACH clustering method, the human orthologues of genes that were differentially regulated at day 3 of mammary gland involution and showed prolonged expression throughout the first 4 days of involution distinguished breast cancers in the NKI 295 breast cancer dataset with low and high metastatic activity. Most strikingly, genes associated with copper ion homeostasis and with HIF-1 promoter binding sites were the most over-represented, linking this signature to hypoxia. Further, six out of the ten mRNAs with strongest up-regulation in cancers with poor survival code for secreted factors, identifying potential candidates that may be involved in stromal/matrix-enhanced metastasis formation/breast cancer development. This method therefore identified biological processes that occur during mammary gland involution, which may be critical in promoting breast cancer metastasis that could form a basis for future investigation, and supports a role for copper in breast cancer development