Lambert C. J. Dorssers

Molecular Classification of Tamoxifen-Resistant Breast Carcinomas by Gene Expression Profiling

PURPOSE To discover a set of markers predictive for the type of response to endocrine therapy with the antiestrogen tamoxifen using gene expression profiling. PATIENTS AND METHODS The study was performed on 112 estrogen receptor-positive primary breast carcinomas from patients with advanced disease and clearly defined types of response (ie, 52 patients with objective response v 60 patients with progressive disease) from start of first-line treatment with tamoxifen. Main clinical end points are the effects of therapy on tumor size and time until tumor progression (progression-free survival [PFS]). RNA isolated from tumor samples was amplified and hybridized to 18,000 human cDNA microarrays. RESULTS Using a training set of 46 breast tumors, 81 genes were found to be differentially expressed (P < or = .05) between tamoxifen-responsive and -resistant tumors. These genes were involved in estrogen action, apoptosis, extracellular matrix formation, and immune response. From the 81 genes, a predictive signature of 44 genes was extracted and validated on an independent set of 66 tumors. This 44-gene signature is significantly superior (odds ratio, 3.16; 95% CI, 1.10 to 9.11; P = .03) to traditional predictive factors in univariate analysis and also significantly related with a longer PFS in univariate (hazard ratio, 0.54; 95% CI, 0.31 to 0.94; P = .03) as well as in multivariate analyses (P = .03). CONCLUSION Our data show that gene expression profiling can be used to discriminate between breast cancer patients with progressive disease and objective response to tamoxifen. Additional studies are needed to confirm if the predictive signature might allow identification of individual patients who could benefit from other (adjuvant) endocrine therapies.

Bcar1/p130Cas Protein and Primary Breast Cancer: Prognosis and Response to Tamoxifen Treatment

Background: The product of the Bcar1/p130Cas (breast cancer resistance/p130Crk-associated substrate) gene causes resistance to antiestrogen drugs in human breast cancer cells in vitro. To investigate its role in clinical breast cancer, we determined the levels of Bcar1/p130Cas protein in a large series of primary breast carcinomas. Methods: We measured Bcar1/p130Cas protein in cytosol extracts from 937 primary breast carcinomas by western blot analysis. The levels of Bcar1/p130Cas protein were tested for associations and trends against clinicopathologic and patient characteristics, the lengths of relapse-free survival and overall survival (n = 775), and the efficacy of first-line treatment with tamoxifen for recurrent or metastatic disease (n = 268). Results: Bcar1/ p130Cas levels in primary tumors were associated with age/ menopausal status and the levels of estrogen receptor and progesterone receptor. In univariate survival analysis, higher Bcar1/p130Cas levels were associated with poor relapse-free survival and overall survival (both two-sided P = .04; log-rank test for trend). In multivariate analysis, a high level of Bcar1/p130Cas was independently associated with poor relapse-free survival and overall survival. The response to tamoxifen therapy in patients with recurrent disease was reduced in patients with primary tumors that expressed high

Anni 2.0: a multipurpose text-mining tool for the life sciences

Anni 2.0 is an online tool (http://biosemantics.org/anni/) to aid the biomedical researcher with a broad range of information needs. Anni provides an ontology-based interface to MEDLINE and retrieves documents and associations for several classes of biomedical concepts, including genes, drugs and diseases, with established text-mining technology. In this article we illustrate Annis usability by applying the tool to two use cases: interpretation of a set of differentially expressed genes, and literature-based knowledge discovery.

Tamoxifen resistance in breast cancer: elucidating mechanisms.

Tamoxifen has been used for the systemic treatment of patients with breast cancer for nearly three decades. Treatment success is primarily dependent on the presence of the estrogen receptor (ER) in the breast carcinoma. While about half of patients with advanced ER-positive disease immediately fail to respond to tamoxifen, in the responding patients the disease ultimately progresses to a resistant phenotype.The possible causes for intrinsic and acquired resistance have been attributed to the pharmacology of tamoxifen, alterations in the structure and function of the ER, the interactions with the tumour environment and genetic alterations in the tumour cells. So far no prominent mechanism leading to resistance has been identified.The recent results of a functional screen for breast cancer antiestrogen resistance (BCAR) genes responsible for development of tamoxifen resistance in human breast cancer cells are reviewed. Individual BCAR genes can transform estrogen-dependent breast cancer cells into estrogen-independent and tamoxifen-resistant cells in vitro. Furthermore, high levels of BCAR1/p130Cas protein in ER-positive primary breast tumours are associated with intrinsic resistance to tamoxifen treatment. These results indicate a prominent role for alternative growth control pathways independent of ER signalling in intrinsic tamoxifen resistance of ER-positive breast carcinomas.Deciphering the differentiation characteristics of normal and malignant breast epithelial cells with respect to proliferation control and regulation of cell death (apoptosis) is essential for understanding therapy response and development of resistance of breast carcinoma.

Identification of BCAR3 by a random search for genes involved in antiestrogen resistance of human breast cancer cells.

The antiestrogen tamoxifen is important in the treatment of hormone‐dependent breast cancer, although development of resistance is inevitable. To unravel the molecular mechanisms of antiestrogen resistance, a search for involved genes was initiated. Retrovirus‐mediated insertional mutagenesis was applied to human ZR‐75‐1 breast cancer cells. Infected cells were subjected to tamoxifen selection and a panel of resistant cell clones was established. Screening for a common integration site resulted in the identification of a novel gene designated BCAR3. Transfer of this locus by cell fusion or transfection of the BCAR3 cDNA to ZR75‐1 and MCF‐7 cells induces antiestrogen resistance. BCAR3 represents a putative SH2 domain‐containing protein and is partly homologous to the cell division cycle protein CDC48.

Relevance of Breast Cancer Antiestrogen Resistance Genes in Human Breast Cancer Progression and Tamoxifen Resistance

PURPOSE We have previously identified a set of breast cancer antiestrogen resistance (BCAR) genes causing estrogen independence and tamoxifen resistance in vitro using a functional genetic screen. Here, we explored whether these BCAR genes provide predictive value for tamoxifen resistance and prognostic information for tumor aggressiveness in breast cancer patients. PATIENTS AND METHODS mRNA levels of 10 BCAR genes (AKT1, AKT2, BCAR1, BCAR3, EGFR, ERBB2, GRB7, SRC, TLE3, and TRERF1) were measured in estrogen receptor-positive breast tumors using quantitative reverse-transcriptase polymerase chain reaction. Normalized mRNA levels were evaluated for association with progression-free survival (PFS) in 242 patients receiving tamoxifen as first-line monotherapy for recurrent disease, and with distant metastasis-free survival (MFS) in 413 lymph node-negative (LNN) primary breast cancer patients who did not receive systemic adjuvant therapy. RESULTS Concerning tamoxifen resistance, BCAR3, ERBB2, GRB7, and TLE3 mRNA levels were predictive for PFS, independent of traditional predictive factors. By combining GRB7 (or ERBB2) and TLE3 mRNA levels, patients could be classified in three subgroups with distinct PFS. For the evaluation of tumor aggressiveness, AKT2, EGFR, and TRERF1 mRNA levels were all significantly associated with MFS, independent of traditional prognostic factors. Using the combined AKT2 and EGFR mRNA status, four prognostic groups were identified with different MFS outcomes. CONCLUSION The majority of BCAR genes, which were revealed to confer tamoxifen resistance and estrogen independence in vitro by functional screening, have clinical relevance, and associate with tamoxifen resistance and/or tumor aggressiveness in breast cancer patients.

Venn Mapping: clustering of heterologous microarray data based on the number of co-occurring differentially expressed genes

MOTIVATION To evaluate microarray data, clustering is widely used to group biological samples or genes. However, problems arise when comparing heterologous databases. As the clustering algorithm searches for similarities between experiments, it will most likely first separate the data sets, masking relationships that exist between samples from different databases. RESULTS We developed a program, Venn Mapper, to calculate the statistical significance of the number of co-occurring differentially expressed genes in any of the two experiments. For proof of principle, we analysed a heterologous data set of 170 microarrays including breast and prostate cancer microarray analyses. Significant overlap was found in an unsupervised analysis between metastasized prostate cancer and metastasized breast cancer and BRCA mutated breast cancer. A comparison between single microarray data and the averaged breast and prostate data sets was also evaluated. This analysis suggests that genes expressed higher in stromal cells are also implicated in metastatic prostate cancer and BRCA mutated breast cancer. The Venn Mapper program identifies overlaps between samples from heterologous data sets and directly extracts the genes responsible for the overlap. From this information novel biological hypotheses may be addressed. AVAILABILITY Venn Mapper is freely available on http://www.erasmusmc.nl/gatcplatform. SUPPLEMENTARY INFORMATION http://www.erasmusmc.nl/gatcplatform/vennmapper.html.

Functional screen for genes responsible for tamoxifen resistance in human breast cancer cells

Antiestrogens, such as tamoxifen, are widely used for endocrine treatment of estrogen receptor–positive breast cancer. However, as breast cancer progresses, development of tamoxifen resistance is inevitable. The mechanisms underlying this resistance are not well understood. To identify genes involved in tamoxifen resistance, we have developed a rapid screening method. To alter the tamoxifen-sensitive phenotype of human ZR-75-1 breast cancer cells into a tamoxifen-resistant phenotype, the cells were infected with retroviral cDNA libraries derived from human placenta, human brain, and mouse embryo. Subsequently, the cells were selected for proliferation in the presence of 4-hydroxy-tamoxifen (OH-TAM) and integrated cDNAs were identified by sequence similarity searches. From 155 OH-TAM-resistant cell colonies, a total of 25 candidate genes were isolated. Seven of these genes were identified in multiple cell colonies and thus cause antiestrogen resistance. The epidermal growth factor receptor, platelet-derived growth factor receptor-α, platelet-derived growth factor receptor-β, colony-stimulating factor 1 receptor, neuregulin1, and fibroblast growth factor 17 that we have identified have been described as key regulators in the mitogen-activated protein kinase pathway. Therefore, this pathway could be a valuable target in the treatment of patients with breast cancer resistant to endocrine treatment. In addition, the putative gene LOC400500, predicted by in silico analysis, was identified. We showed that ectopic expression of this gene, designated as breast cancer antiestrogen resistance 4 (BCAR4), caused OH-TAM resistance and anchorage-independent cell growth in ZR-75-1 cells and that the intact open reading frame was required for its function. We conclude that retroviral transfer of cDNA libraries into human breast cancer cells is an efficient method for identifying genes involved in tamoxifen resistance. (Mol Cancer Res 2006;4(6):379–86)

Co-occurrence based meta-analysis of scientific texts: retrieving biological relationships between genes

MOTIVATION The advent of high-throughput experiments in molecular biology creates a need for methods to efficiently extract and use information for large numbers of genes. Recently, the associative concept space (ACS) has been developed for the representation of information extracted from biomedical literature. The ACS is a Euclidean space in which thesaurus concepts are positioned and the distances between concepts indicates their relatedness. The ACS uses co-occurrence of concepts as a source of information. In this paper we evaluate how well the system can retrieve functionally related genes and we compare its performance with a simple gene co-occurrence method. RESULTS To assess the performance of the ACS we composed a test set of five groups of functionally related genes. With the ACS good scores were obtained for four of the five groups. When compared to the gene co-occurrence method, the ACS is capable of revealing more functional biological relations and can achieve results with less literature available per gene. Hierarchical clustering was performed on the ACS output, as a potential aid to users, and was found to provide useful clusters. Our results suggest that the algorithm can be of value for researchers studying large numbers of genes. AVAILABILITY The ACS program is available upon request from the authors.

Fibroblast growth factor receptor 4 predicts failure on tamoxifen therapy in patients with recurrent breast cancer

Tamoxifen treatment of estrogen-dependent breast cancer ultimately loses its effectiveness due to the development of resistance. From a functional screen for identifying genes responsible for tamoxifen resistance in human ZR-75-1 breast cancer cells, fibroblast growth factor (FGF) 17 was recovered. The aim of this exploratory study was to assess the predictive value of FGF17 and the receptors FGFR1-4 for the type of response to tamoxifen treatment (clinical benefit) and the duration of progression-free survival (PFS) in patients with recurrent breast cancer. mRNA levels of FGF17 and FGFR1-4 were quantified by real-time reverse transcriptase PCR in 285 estrogen receptor-positive breast carcinomas with clinical follow-up. All patients had recurrent disease and were treated with tamoxifen as first-line systemic therapy for local or distant relapse. FGF17 and FGFR1-3 mRNA levels had no significant predictive value for this group of patients. However, high FGFR4 mRNA levels analyzed as a continuous log-transformed variable predicted poor clinical benefit (odds ratio=1.22; P=0.009) and shorter PFS (hazard ratio=1.18; P<0.001). In addition, in multivariable analysis, the predictive value of FGFR4 was independent from the traditional predictive factors. Our analyses show that FGFR4 may play a role in the biological response of the tumor to tamoxifen treatment. In addition, as altered expression of FGF17 causes tamoxifen resistance in vitro, the FGF signaling pathway could be a valuable target in the treatment of breast cancer patients resistant to endocrine treatment.