Reinhold Schäfer

Caveolin-1 Is Down-Regulated in Human Ovarian Carcinoma and Acts as a Candidate Tumor Suppressor Gene

To identify novel markers differentially expressed in ovarian cancer versus normal ovary, we hybridized microarrays with cDNAs derived from normal human ovaries and advanced stage ovarian carcinomas. This analysis revealed down-regulation of the caveolin-1 gene (CAV1) in ovarian carcinoma samples. Suppression of CAV1 in ovarian carcinomas was confirmed using a tumor tissue array consisting of 68 cDNA pools from different matched human tumor and normal tissues. Immunohistochemistry demonstrated expression of caveolin-1 in normal and benign ovarian epithelial cells, but loss of expression in serous ovarian carcinomas. In low-grade carcinomas, redistribution of caveolin-1 from a membrane-associated pattern observed in normal epithelium to a cytoplasmic localization pattern was observed. No expression of caveolin-1 was detectable in four of six ovarian carcinoma cell lines investigated. In SKOV-3 and ES-2 carcinoma cells, which express high levels of the caveolin-1 protein, phosphorylation of the 22-kd caveolin-1 isoform was detected. Inhibition of both DNA methylation and histone deacetylation using 5-aza-2deoxycytidine and Trichostatin A, respectively, relieves down-regulation of caveolin-1 in OAW42 and OVCAR-3 cells which is in part mediated by direct regulation at the mRNA level. Expression of CAV1 in the ovarian carcinoma cell line OVCAR-3, resulted in suppression of tumor cell survival in vitro, suggesting that the CAV1 gene is likely to act as a tumor suppressor gene in human ovarian epithelium.

Prediction of doxorubicin sensitivity in breast tumors based on gene expression profiles of drug-resistant cell lines correlates with patient survival

Up to date clinical tests for predicting cancer chemotherapy response are not available and individual markers have shown little predictive value. We hypothesized that gene expression patterns attributable to chemotherapy-resistant cells can predict response and cancer prognosis. We contrasted the expression profiles of 13 different human tumor cell lines of gastric (EPG85–257), pancreatic (EPP85–181), colon (HT29) and breast (MCF7 and MDA-MB-231) origin and their counterparts resistant to the topoisomerase inhibitors daunorubicin, doxorubicin or mitoxantrone. We interrogated cDNA arrays with 43u2009000 cDNA clones (∼30u2009000 unique genes) to study the expression pattern of these cell lines. We divided gene expression profiles into two sets: we compared the expression patterns of the daunorubicin/doxorubicin-resistant cell lines and the mitoxantrone-resistant cell lines independently to the parental cell lines. For identifying predictive genes, the Prediction Analysis for Mircorarrays algorithm was used. The analysis revealed 79 genes best correlated with doxorubicin resistance and 70 genes with mitoxantrone resistance. In an independent classification experiment, we applied our model of resistance for predicting the sensitivity of 44 previously characterized breast cancer samples. The patient group characterized by the gene expression profile similar to those of doxorubicin-sensitive cell lines exhibited longer survival (49.7±26.1 months, n=21, P=0.034) than the resistant group (32.9±18.7 months, n=23). The application of gene expression signatures derived from doxorubicin-resistant and -sensitive cell lines allowed to predict effectively clinical survival after doxorubicin monotherapy. Our approach demonstrates the significance of in vitro experiments in the development of new strategies for cancer response prediction.

Systematic identification and molecular characterization of genes differentially expressed in breast and ovarian cancer

The identification of novel disease‐associated genes in gynaecological tumours has important implications for understanding the process of tumourigenesis and the development of novel treatment regimens. cDNA libraries from disease tissues may represent a valuable source to identify such genes. Recently, a bio‐informatic procedure based on an ‘electronic Northern’ approach was established to screen expressed sequence tag (EST) libraries for genes differentially expressed in tumour and normal tissues, and identified 450 candidate genes differentially expressed in breast and ovarian cancer. In this report, the validation of an initial set of 40 candidate genes, which were selected due to their localization in chromosomal regions frequently altered in gynaecological tumours, is described. Differential expression of 29 of these genes, including three uncharacterized novel genes, was confirmed by applying cancer profiling arrays with 106 matched pairs of tumour/normal cDNAs and quantitative reverse transcription‐polymerase chain reaction (RT‐PCR) on 60 clinical specimens. The majority of these differentially expressed genes have not been described previously in the context of breast and ovarian cancer, and may constitute novel diagnostic markers for these tumour entities. Copyright

Reactive oxygen species as mediators of the transformed phenotype

Reactive oxygen species (ROS) are known to be involved in different pro‐ and anticarcinogenic mechanisms. However, their influence on the maintenance of the transformed phenotype has not been studied so far. Here we show that the anchorage‐independent growth of transformed murine fibroblasts is inhibited by antioxidants and radical scavengers in a concentration‐dependent and reversible manner. These agents also reduce TGF‐β‐dependent stimulation of colony formation in soft agar, pointing to their specific interference with TGF‐β‐triggered signal chains involved in the maintenance of the transformed state.Int. J. Cancer 70:587–589