Functional Genome-wide Screening Identifies Targets and Pathways Sensitizing Pancreatic Cancer Cells to Dasatinib.

This study is an unbiased genomic screen to obtain functional targets for increased effectiveness of dasatinib in pancreatic cancer. Dasatinib, a multi-targeted tyrosine kinase inhibitor, is used in clinical trials for treatment of pancreatic cancer; however, intrinsic and acquired resistance often occurs. We used a dasatinib-resistant pancreatic cancer cell line SU8686 to screen for synthetic lethality that synergizes with dasatinib using a pooled human shRNA library followed by next generation sequencing. Novel genes were identified which when silenced produced a prominent inhibitory effect with dasatinib against the pancreatic cancer cells. Several of these genes are involved in the regulation of epigenetics, as well as signaling pathways of the FOXO and hedgehog families. Small molecule inhibitors of either histone deacetylases or nuclear exporter had marked inhibitory effect with dasatinib in pancreatic cancers, suggesting their potential therapeutic effectiveness in this deadly cancer.

ScreenSifter: analysis and visualization of RNAi screening data.

BACKGROUND: RNAi screening is a powerful method to study the genetics of intracellular processes in metazoans. Technically, the approach has been largely inspired by techniques and tools developed for compound screening, including those for data analysis. However, by contrast with compounds, RNAi inducing agents can be linked to a large body of gene-centric, publically available data. However, the currently available software applications to analyze RNAi screen data usually lack the ability to visualize associated gene information in an interactive fashion. RESULTS: Here, we present ScreenSifter, an open-source desktop application developed to facilitate storing, statistical analysis and rapid and intuitive biological data mining of RNAi screening datasets. The interface facilitates meta-data acquisition and long-term safe-storage, while the graphical user interface helps the definition of a hit list and the visualization of biological modules among the hits, through Gene Ontology and protein-protein interaction analyses. The application also allows the visualization of screen-to-screen comparisons. CONCLUSIONS: Our software package, ScreenSifter, can accelerate and facilitate screen data analysis and enable discovery by providing unique biological data visualization capabilities.

GBSA: a comprehensive software for analysing whole genome bisulfite sequencing data.

High-throughput sequencing is increasingly being used in combination with bisulfite (BS) assays to study DNA methylation at nucleotide resolution. Although several programmes provide genome-wide alignment of BS-treated reads, the resulting information is not readily interpretable and often requires further bioinformatic steps for meaningful analysis. Current post-alignment BS-sequencing programmes are generally focused on the gene-specific level, a restrictive feature when analysis in the non-coding regions, such as enhancers and intergenic microRNAs, is required. Here, we present Genome Bisulfite Sequencing Analyser (GBSA-http://ctrad-csi.nus.edu.sg/gbsa), a free open-source software capable of analysing whole-genome bisulfite sequencing data with either a gene-centric or gene-independent focus. Through analysis of the largest published data sets to date, we demonstrate GBSA's features in providing sequencing quality assessment, methylation scoring, functional data management and visualization of genomic methylation at nucleotide resolution. Additionally, we show that GBSA's output can be easily integrated with other high-throughput sequencing data, such as RNA-Seq or ChIP-seq, to elucidate the role of methylated intergenic regions in gene regulation. In essence, GBSA allows an investigator to explore not only known loci but also all the genomic regions, for which methylation studies could lead to the discovery of new regulatory mechanisms.