Integration of DNA copy number alterations and prognostic gene expression signatures in breast cancer patients.

Purpose: Several prognostic gene expression profiles have been identified in breast cancer. In spite of this progress in prognostic classification, the underlying mechanisms that drive these gene expression patterns remain unknown. Specific genomic alterations, such as copy number alterations, are an important factor in tumor development and progression and are also associated with changes in gene expression.

Local recurrence after breast-conserving therapy in relation to gene expression patterns in a large series of patients.

Purpose: The majority of patients with early-stage breast cancer are treated with breast-conserving therapy (BCT). Several clinical risk factors are associated with local recurrence (LR) after BCT but are unable to explain all instances of LR after BCT. Here, gene expression microarrays are used to identify novel risk factors for LR after BCT.

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.

An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer.

Individualization of cancer management requires prognostic markers and therapy-predictive markers. Prognostic markers assess risk of disease progression independent of therapy, whereas therapy-predictive markers identify patients whose disease is sensitive or resistant to treatment. We show that an experimentally derived IFN-related DNA damage resistance signature (IRDS) is associated with resistance to chemotherapy and/or radiation across different cancer cell lines.

Combining biological gene expression signatures in predicting outcome in breast cancer: An alternative to supervised classification.

Introduction: Gene expression profiling has been extensively used to predict outcome in breast cancer patients. We have previously reported on biological hypothesis-driven analysis of gene expression profiling data and we wished to extend this approach through the combinations of various gene signatures to improve the prediction of outcome in breast cancer.

Methods: We have used gene expression data (25.

Using microarray analysis as a prognostic and predictive tool in oncology: focus on breast cancer and normal tissue toxicity.

Microarray analysis makes it possible to study the expression levels of tens of thousands of genes in one single experiment and is widely available for research purposes. Gene expression profiling is currently being used in many research projects aimed at identifying gene expression signatures in malignant tumors associated with prognosis and response to therapy. An important goal of such research is to develop gene expression-based diagnostic tests that can be used to guide therapy in cancer patients.

Revealing targeted therapy for human cancer by gene module maps.

A major goal of cancer research is to match specific therapies to molecular targets in cancer. Genome-scale expression profiling has identified new subtypes of cancer based on consistent patterns of variation in gene expression, leading to improved prognostic predictions. However, how these new genetic subtypes of cancers should be treated is unknown.

Gene expression programs of human smooth muscle cells: tissue-specific differentiation and prognostic significance in breast cancers.

Smooth muscle is present in a wide variety of anatomical locations, such as blood vessels, various visceral organs, and hair follicles. Contraction of smooth muscle is central to functions as diverse as peristalsis, urination, respiration, and the maintenance of vascular tone. Despite the varied physiological roles of smooth muscle cells (SMCs), we possess only a limited knowledge of the heterogeneity underlying their functional and anatomic specializations.

Characterization of heterotypic interaction effects in vitro to deconvolute global gene expression profiles in cancer.

Background: Perturbations in cell-cell interactions are a key feature of cancer. However, little is known about the systematic effects of cell-cell interaction on global gene expression in cancer.

Results: We used an ex vivo model to simulate tumor-stroma interaction by systematically co-cultivating breast cancer cells with stromal fibroblasts and determined associated gene expression changes with cDNA microarrays.

Impact of supervised gene signatures of early hypoxia on patient survival.

Background And Purpose: Hypoxia is a common feature of solid tumors associated with therapy resistance, increased malignancy and poor prognosis. Several approaches have been developed with the hope of identifying patients harboring hypoxic tumors including the use of microarray based gene signatures. However, studies to date have largely ignored the strong time dependency of hypoxia-regulated gene expression.

Gene expression signatures to predict the development of metastasis in breast cancer.

Understanding and preventing the development of distant metastases is the most important aim in research and treatment of malignant tumors, including breast cancer. In patients with primary breast cancer without lymph node metastases who are under 50 years of age, approximately 25% will develop distant metastases after 5 years. When treated with adjuvant chemotherapy, this can be reduced to approximately 18%.

The macrophage-stimulating protein pathway promotes metastasis in a mouse model for breast cancer and predicts poor prognosis in humans.

A better understanding of tumor metastasis requires development of animal models that authentically reproduce the metastatic process. By modifying an existing mouse model of breast cancer, we discovered that macrophage-stimulating protein promoted breast tumor growth and metastasis to several organs. A special feature of our findings was the occurrence of osteolytic bone metastases, which are prominent in human breast cancer.

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.

Concordance among gene-expression-based predictors for breast cancer.

Background: Gene-expression-profiling studies of primary breast tumors performed by different laboratories have resulted in the identification of a number of distinct prognostic profiles, or gene sets, with little overlap in terms of gene identity.

Methods: To compare the predictions derived from these gene sets for individual samples, we obtained a single data set of 295 samples and applied five gene-expression-based models: intrinsic subtypes, 70-gene profile, wound response, recurrence score, and the two-gene ratio (for patients who had been treated with tamoxifen).

Results: We found that most models had high rates of concordance in their outcome predictions for the individual samples.

Genetic regulators of large-scale transcriptional signatures in cancer.

Gene expression signatures encompassing dozens to hundreds of genes have been associated with many important parameters of cancer, but mechanisms of their control are largely unknown. Here we present a method based on genetic linkage that can prospectively identify functional regulators driving large-scale transcriptional signatures in cancer. Using this method we show that the wound response signature, a poor-prognosis expression pattern of 512 genes in breast cancer, is induced by coordinate amplifications of MYC and CSN5 (also known as JAB1 or COPS5).

Gene expression programs in response to hypoxia: cell type specificity and prognostic significance in human cancers.

Background: Inadequate oxygen (hypoxia) triggers a multifaceted cellular response that has important roles in normal physiology and in many human diseases. A transcription factor, hypoxia-inducible factor (HIF), plays a central role in the hypoxia response; its activity is regulated by the oxygen-dependent degradation of the HIF-1alpha protein. Despite the ubiquity and importance of hypoxia responses, little is known about the variation in the global transcriptional response to hypoxia among different cell types or how this variation might relate to tissue- and cell-specific diseases.

Determination of stromal signatures in breast carcinoma.

Many soft tissue tumors recapitulate features of normal connective tissue. We hypothesize that different types of fibroblastic tumors are representative of different populations of fibroblastic cells or different activation states of these cells. We examined two tumors with fibroblastic features, solitary fibrous tumor (SFT) and desmoid-type fibromatosis (DTF), by DNA microarray analysis and found that they have very different expression profiles, including significant differences in their patterns of expression of extracellular matrix genes and growth factors.

Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival.

Based on the hypothesis that features of the molecular program of normal wound healing might play an important role in cancer metastasis, we previously identified consistent features in the transcriptional response of normal fibroblasts to serum, and used this "wound-response signature" to reveal links between wound healing and cancer progression in a variety of common epithelial tumors. Here, in a consecutive series of 295 early breast cancer patients, we show that both overall survival and distant metastasis-free survival are markedly diminished in patients whose tumors expressed this wound-response signature compared to tumors that did not express this signature. A gene expression centroid of the wound-response signature provides a basis for prospectively assigning a prognostic score that can be scaled to suit different clinical purposes.