Introduction to Oncomine Xiayu Stacy Huang

Oncomine is a cancer-specific microarray database and has a web-based data-mining platform aimed at facilitating discovery from genome-wide expression analysis Oncomine was originally developed as an academic tool at the University of Michigan in 2003 and then became a commercial tool in 2006 (Compendia Bioscience). Oncomine is the world’s largest existing human cancer genomic database that covers 674 independent datasets and more than 73,000 samples. What is Oncomine?

Oncomine Platform User Interface

Differential gene expression: What genes are over- or under- expressed in particular cancer types or subtypes? Co-expression: Is my target gene coordinately expressed with other genes that are members of a biological pathway activated in a cancer type? Outlier analysis: What genes might be good biomarkers for cancer subtypes? Comparing (meta-analysis): What gene expression patterns or gene sets are validated across multiple datasets? Concept list: Can patient subtypes be associated with this signature or gene list representing underlying biology? What can Oncomine do?

Free research edition including –Gene expression and DNA copy number data from clinical and cell-line experiments –Lists of DEGs across multiple experiments –Single gene search (differential expression, co-expression, etc) Premium research edition including additional features –Multi-gene search –Expanded analysis types including cancer subtypes, drug sensitivity, clinical outcome analysis, etc. –Export and share results, upload custom concepts, and access commercial-level support Oncomine Editions

Requirements –Internet access –Internet explorer 6.0 or higher, firefox –Java script must be enabled –Oncomine login ( Example questions: –EGFR over-expression in brain cancer? –any genes that are coexpressed with EGFR? –EGFR expression pattern consistent across multiple studies? How to start?

Starting analysis by using search and setting filters Search box Compendia ontology

Determining if EGFR is over-expressed in brain cancer

Meta analysis of EGFR across studies

Finding co-expressed genes with EGFR in brain cancer

By looking at brain and CNS cancer vs. normal analyses, we can conclude EGFR is over-expressed in several independent datasets By doing meta-analysis, we can conclude the expression pattern of EGFR is quite consistent across multiple independent studies By doing coexpression analysis, we can conclude there are some genes that are coexpressed with EGFR and further investigation of these coexpressed genes may be needed Conclusion

Thanks! Any Questions?