Biomedical subjects

Namjin Chung

Publications and source records attributed to Namjin Chung.

3 recordsLinked to original sources

PubMed2006

Small interfering RNA screens reveal enhanced cisplatin cytotoxicity in tumor cells having both BRCA network and TP53 disruptions.

RNA interference technology allows the systematic genetic analysis of the molecular alterations in cancer cells and how these alterations affect response to therapies. Here we used small interfering RNA (siRNA) screens to identify genes that enhance the cytotoxicity (enhancers) of established anticancer chemotherapeutics. Hits identified in drug enhancer screens of cisplatin, gemcitabine, and paclitaxel were largely unique to the drug being tested and could be linked to the drug's mechanism of action. Hits identified by screening of a genome-scale siRNA library for cisplatin enhancers in TP53-deficient HeLa cells were significantly enriched for genes with annotated functions in DNA damage repair as well as poorly characterized genes likely having novel functions in this process. We followed up on a subset of the hits from the cisplatin enhancer screen and validated a number of enhancers whose products interact with BRCA1 and/or BRCA2. TP53(+/-) matched-pair cell lines were used to determine if knockdown of BRCA1, BRCA2, or validated hits that associate with BRCA1 and BRCA2 selectively enhances cisplatin cytotoxicity in TP53-deficient cells. Silencing of BRCA1, BRCA2, or BRCA1/2-associated genes enhanced cisplatin cytotoxicity approximately 4- to 7-fold more in TP53-deficient cells than in matched TP53 wild-type cells. Thus, tumor cells having disruptions in BRCA1/2 network genes and TP53 together are more sensitive to cisplatin than cells with either disruption alone.

Antineoplastic Agents↗

PubMed2006

Robust statistical methods for hit selection in RNA interference high-throughput screening experiments.

RNA interference (RNAi) high-throughput screening (HTS) experiments carried out using large (>5000 short interfering [si]RNA) libraries generate a huge amount of data. In order to use these data to identify the most effective siRNAs tested, it is critical to adopt and develop appropriate statistical methods. To address the questions in hit selection of RNAi HTS, we proposed a quartile-based method which is robust to outliers, true hits and nonsymmetrical data. We compared it with the more traditional tests, mean +/- k standard deviation (SD) and median +/- 3 median of absolute deviation (MAD). The results suggested that the quartile-based method selected more hits than mean +/- k SD under the same preset error rate. The number of hits selected by median +/- k MAD was close to that by the quartile-based method. Further analysis suggested that the quartile-based method had the greatest power in detecting true hits, especially weak or moderate true hits. Our investigation also suggested that platewise analysis (determining effective siRNAs on a plate-by-plate basis) can adjust for systematic errors in different plates, while an experimentwise analysis, in which effective siRNAs are identified in an analysis of the entire experiment, cannot. However, experimentwise analysis may detect a cluster of true positive hits placed together in one or several plates, while platewise analysis may not. To display hit selection results, we designed a specific figure called a plate-well series plot. We thus suggest the following strategy for hit selection in RNAi HTS experiments. First, choose the quartile-based method, or median +/- k MAD, for identifying effective siRNAs. Second, perform the chosen method experimentwise on transformed/normalized data, such as percentage inhibition, to check the possibility of hit clusters. If a cluster of selected hits are observed, repeat the analysis based on untransformed data to determine whether the cluster is due to an artifact in the data. If no clusters of hits are observed, select hits by performing platewise analysis on transformed data. Third, adopt the plate-well series plot to visualize both the data and the hit selection results, as well as to check for artifacts.

Cluster Analysis↗

PubMed2004

Sirt1 promotes fat mobilization in white adipocytes by repressing PPAR-gamma.

Calorie restriction extends lifespan in organisms ranging from yeast to mammals. In yeast, the SIR2 gene mediates the life-extending effects of calorie restriction. Here we show that the mammalian SIR2 orthologue, Sirt1 (sirtuin 1), activates a critical component of calorie restriction in mammals; that is, fat mobilization in white adipocytes. Upon food withdrawal Sirt1 protein binds to and represses genes controlled by the fat regulator PPAR-gamma (peroxisome proliferator-activated receptor-gamma), including genes mediating fat storage. Sirt1 represses PPAR-gamma by docking with its cofactors NCoR (nuclear receptor co-repressor) and SMRT (silencing mediator of retinoid and thyroid hormone receptors). Mobilization of fatty acids from white adipocytes upon fasting is compromised in Sirt1+/- mice. Repression of PPAR-gamma by Sirt1 is also evident in 3T3-L1 adipocytes, where overexpression of Sirt1 attenuates adipogenesis, and RNA interference of Sirt1 enhances it. In differentiated fat cells, upregulation of Sirt1 triggers lipolysis and loss of fat. As a reduction in fat is sufficient to extend murine lifespan, our results provide a possible molecular pathway connecting calorie restriction to life extension in mammals.

3T3-L1 Cells↗