Abstract 70: A role for the chromatin remodeling protein CHD3 in ovarian cancer therapy response

Carboplatin and cisplatin are chemotherapeutic agents that are used extensively for treating epithelial ovarian cancer. These drugs can be highly effective, yet tumors are frequently refractory to treatment or become resistant upon tumor relapse. Epigenetic silencing, particularly at promoter regions of genes regulates important cell function and has been associated with all stages of tumor formation and progression and may contribute to therapy response. We analyzed the epigenome of 50 primary ovarian tumors and 12 normal ovarian samples using an array based method previously developed in our lab and associated Affymetrix U133 expression data. We then identified gene candidates that segregate patients based on platinum sensitivity and patient survival. These candidates were then pooled into a genome-wide RNAi-based screen where we validated a gene encoding a chromatin remodeling protein, CHD3, a member of the Mi-2 NuRD complex, and show that it is linked to chemoresistance. CHD3 is silenced through an epigenetic mechanism in both ovarian cancer cell lines and primary ovarian tumors. When ovarian cancer cell lines that are transcriptionally silenced for CHD3 are challenged with carboplatin they display a striking slow growth phenotype as well as increased resistance to the chemotherapy drugs carboplatin and cisplatin. Taken together, we provide the first evidence for a role for CHD3 as an important mediator of chemoresistance in ovarian cancer. Furthermore, CHD3 might represent a response predictor and potential therapeutic target for predicting chemoresistance in this disease

Scintillation Counters for the D0 Muon Upgrade

We present the results of an upgrade to the D0 muon system. Scintillating counters have been added to the existing central D0 muon system to provide rejection for cosmic ray muons and out-of-time background, and to provide additional fast timing information for muons in an upgraded Tevatron. Performance and results from the 1994-1996 Tevatron run are presented.Comment: 30 pages, 25 postscript figure

Evaluation and comparison of clustering algorithms in analyzing ES cell gene expression data

Many clustering algorithms have been used to analyze microarray gene expression data. Given embryonic stem cell gene expression data, we applied several indices to evaluate the performance of clustering algorithms, including hierarchical clustering, k-means, PAM and SOM. The indices were homogeneity and separation scores, silhouette width, redundant score (based on redundant genes), and WADP (testing the robustness of clustering results after small perturbation). The results showed that the ES cell dataset posed a challenge for cluster analysis in that the clusters generated by different methods were only partially consistent. Using this data set, we were able to evaluate the advantages and weaknesses of algorithms with respect to both internal and external quality measures. This study may provide a guideline on how to select suitable clustering algorithms and it may help raise relevant issues in the extraction of meaningful biological information from microarray expression data. Keywords cluster analysis; gene expression; microarray; mouse embryonic stem cel