Phase I dose-escalation study to determine the safety, pharmacokinetics and pharmacodynamics of brivanib alaninate in combination with full-dose cetuximab in patients with advanced gastrointestinal malignancies who have failed prior therapy.

Background: The objectives of this phase I study were to determine the safety, pharmacokinetics (PK), pharmacodynamics and efficacy of brivanib combined with full-dose cetuximab in patients with advanced gastrointestinal malignancies.

Methods: Patients with advanced gastrointestinal malignancies who had failed prior therapies received brivanib (320, 600 or 800 mg daily) plus cetuximab (400 mg m(-2) loading dose then 250 mg m(-2) weekly). Assessments included adverse events, PK, tumour response, 2[18F]fluoro-2-deoxyglucose positron-emitting tomography and K-Ras mutation analyses.

A phase I study to determine the safety, pharmacokinetics and pharmacodynamics of a dual VEGFR and FGFR inhibitor, brivanib, in patients with advanced or metastatic solid tumors.

Background: This study was designed to determine the safety, pharmacokinetics (PK) and pharmacodynamics (PD) of brivanib in patients with advanced/metastatic solid tumors.

Patients And Methods: Ninety patients enrolled in this two-part, phase I open-label study of oral brivanib alaninate. The primary objectives of this study were (in part A) dose-limiting toxicity, maximum tolerated dose (MTD) and the lowest biologically active dose level and (in part B) the optimal dose/dose range.

From nanotechnology to nanomedicine: applications to cancer research.

Scientific advances have significantly improved the practice of medicine by providing objective and quantitative means for exploring the human body and disease states. These innovative technologies have already profoundly improved disease detection, imaging, treatment and patient follow-up. Today's analytical limits are at the nanoscale level (one-billionth of a meter) enabling a detailed exploration at the level of DNA, RNA, proteins and metabolites which are in fact nano-objects.

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.

The impact of inter-observer variation in pathological assessment of node-negative breast cancer on clinical risk assessment and patient selection for adjuvant systemic treatment.

Background: It is well known that there is considerable inter-observer variability in assessment of the pathological parameters that are used to select node-negative breast cancer patients for adjuvant systemic treatment. There are only limited data available as to in how many patients this leads to differences in treatment decisions.

Methods: Clinical and pathological data of 694 patients <61 years with primary unilateral T1-4N0M0 breast cancer were analysed.

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.

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.

Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types.

Tumour proliferation is one of the main biological phenotypes limiting cure in oncology. Extensive research is being performed to unravel the key players in this process. To exploit the potential of published gene expression data, creation of a signature for proliferation can provide valuable information on tumour status, prognosis and prediction.

Validation of 70-gene prognosis signature in node-negative breast cancer.

Purpose: The 70-gene prognosis signature (van't Veer et al., Nature 415(6871):530-536, 2002) may improve the selection of lymph node-negative breast cancer patients for adjuvant systemic therapy. Optimal validation of prognostic classifiers is of great importance and we therefore wished to evaluate the prognostic value of the 70-gene prognosis signature in a series of relatively recently diagnosed lymph node negative breast cancer patients.

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.

The chemokine receptor CXCR6 and its ligand CXCL16 are expressed in carcinomas and inhibit proliferation.

The chemokine receptor CXCR6 and its ligand CXCL16 are involved in inflammation. Thus far, they were known to be expressed mainly by T cells and macrophages, respectively. However, we detected both in all of 170 human primary mammary carcinomas and at similar levels in all 8 human mammary carcinoma cell lines tested by microarray analysis.

Molecular profiles of progesterone receptor loss in human breast tumors.

Background: Patient prognosis and response to endocrine therapy in breast cancer correlate with protein expression of both estrogen receptor (ER) and progesterone receptor (PR), with poorer outcome in patients with ER+/PR- compared to ER+/PR+ tumors.

Methods: To better understand the underlying biology of ER+/PR- tumors, we examined RNA expression (n > 1000 tumors) and DNA copy number profiles from five previously published studies of human breast cancers with clinically assigned hormone receptor status (ER+/PR+, ER+/PR-, and ER-/PR-).

Results: We identified an expression "signature" of genes with either elevated or diminished RNA levels specifically in ER+/PR+ compared to ER-/PR- and ER+/PR- tumors.

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 profiling to predict outcome after chemoradiation in head and neck cancer.

Purpose: The goal of the present study was to improve prediction of outcome after chemoradiation in advanced head and neck cancer using gene expression analysis.

Materials And Methods: We collected 92 biopsies from untreated head and neck cancer patients subsequently given cisplatin-based chemoradiation (RADPLAT) for advanced squamous cell carcinomas (HNSCC). After RNA extraction and labeling, we performed dye swap experiments using 35k oligo-microarrays.

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.

Lung metastasis genes couple breast tumor size and metastatic spread.

The association between large tumor size and metastatic risk in a majority of clinical cancers has led to questions as to whether these observations are causally related or whether one is simply a marker for the other. This is partly due to an uncertainty about how metastasis-promoting gene expression changes can arise in primary tumors. We investigated this question through the analysis of a previously defined "lung metastasis gene-expression signature" (LMS) that mediates experimental breast cancer metastasis selectively to the lung and is expressed by primary human breast cancer with a high risk for developing lung metastasis.

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.