CGV: Cancer Genome Viewer, a web service for integrative cancer genome and pharmacogenomic data analysis.

MOTIVATION: Multi-omic profiling data, such as The Cancer Genome Atlas and pharmacogenomic data, facilitate research into cancer mechanisms and drug development. However, it is not easy for researchers to connect, integrate and analyze huge and heterogeneous data, which is a major obstacle to the utilization of cancer genomic data. RESULTS: We developed Cancer Genome Viewer (CGV), a user-friendly web service that provides functions to integrate and visualize cancer genome data and pharmacogenomic data. Users can easily select and customize the samples to be analyzed with the pre-defined selection options for patients' clinic-pathological features from multiple datasets. Using the customized dataset, users can perform subsequent data analyses comprehensively, including gene set analysis, clustering or survival analysis. CGV also provides pre-calculated drug response scores from pharmacogenomic data, which may facilitate the discovery of new cancer targets and therapeutics. AVAILABILITY AND IMPLEMENTATION: CGV web service is implemented with the R Shiny application at http://cgv.sysmed.kr and the source code is freely available at https://git.sysmed.kr/sysmed_public/cgv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comparative RNA-Seq Analysis Revealed Tissue-Specific Splicing Variations during the Generation of the PDX Model.

Tissue-specific gene expression generates fundamental differences in the function of each tissue and affects the characteristics of the tumors that are created as a result. However, it is unclear how much the tissue specificity is conserved during grafting of the primary tumor into an immune-compromised mouse model. Here, we performed a comparative RNA-seq analysis of four different primary-patient derived xenograft (PDX) tumors. The analysis revealed a conserved RNA biotype distribution of primary-PDX pairs, as revealed by previous works. Interestingly, we detected significant changes in the splicing pattern of PDX, which was mainly comprised of skipped exons. This was confirmed by splicing variant-specific RT-PCR analysis. On the other hand, the correlation analysis for the tissue-specific genes indicated overall strong positive correlations between the primary and PDX tumor pairs, with the exception of gastric cancer cases, which showed an inverse correlation. These data propose a tissue-specific change in splicing events during PDX formation as a variable factor that affects primary-PDX integrity.