ONCOMINE: A Bioinformatics Infrastructure for Cancer Genomics

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Presentation transcript:

ONCOMINE: A Bioinformatics Infrastructure for Cancer Genomics Dan Rhodes Chinnaiyan Laboratory Bioinformatics Program Cancer Biology Training Program Medical Scientist Training Program University of Michigan Medical School

Outline Background ONCOMINE ONCOMINE Data Integration DNA Microarrays and the Cancer Transcriptome ONCOMINE Data collection, normalization & storage Statistical Analysis Visualization of Data and Analysis ONCOMINE Data Integration Therapeutic Targets / Biomarkers Metabolic and Signaling Pathways Known protein-protein Interactions ONCOMINE tutorial

Outline Background ONCOMINE ONCOMINE Data Integration DNA Microarrays and the Cancer Transcriptome ONCOMINE Data collection, normalization & storage Statistical Analysis Visualization of Data and Analysis ONCOMINE Data Integration Therapeutic Targets / Biomarkers Metabolic and Signaling Pathways Known protein-protein Interactions ONCOMINE tutorial

The Cancer Transcriptome

The Cancer Transcriptome

The Cancer Transcriptome

The Cancer Transcriptome

The Cancer Transcriptome

The Cancer Transcriptome

The Cancer Transcriptome

The Cancer Transcriptome

The Cancer Transcriptome

The Cancer Transcriptome

The Cancer Transcriptome 180+ studies profiling human cancer Each profiling 5 – 100+ samples We estimate > 10,000 microarrays 10k chips measuring 20k genes = 200+ million data points

Outline Background ONCOMINE ONCOMINE Data Integration DNA Microarrays and the Cancer Transcriptome ONCOMINE Data collection, normalization & storage Statistical Analysis Visualization of Data and Analysis ONCOMINE Data Integration Therapeutic Targets / Biomarkers Metabolic and Signaling Pathways Known protein-protein Interactions ONCOMINE tutorial

Oncomine oncology + data-mining = oncomine 105 independent datasets (90 analyzed) 7,292 cancer microarrays 79 million gene expression measurements 382 distinct cancer signatures > 5 million tests of differential expression > 5 million tests of gene set enrichment > 5 billion pairwise correlations

Oncomine Database – relational, Oracle 9.2 Statistical computing – R, Perl, Java Front End – Java Server Pages Server – Apache/Tomcat Graphics – Scalable Vector Graphics (SVG)

Data Collection Monthly Pubmed searches (cancer + microarray + transcriptome + tumor + gene expression profiling) Gene Expression Repositories Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo/) ArrayExpress (http://www.ebi.ac.uk/arrayexpress/) Stanford Microarray Database (http://genome-www5.stanford.edu/) Whitehead Cancer Genomics (http://www.broad.mit.edu/cancer/)

Data Normalization Global normalization – same scaling factors applied to all microarray features – mean and variance normalization Affymetrix - Quantile normalization Spotted cDNA - Loess normalization normalize an M vs. A plot

Data Storage Generic data structures to accommodate a variety of data Samples Microarray Features / Genes Normalized Data Statistical Tests Gene Sets

Samples

Samples

Microarray Features / Genes

Normalized Data

Gene Sets

Statistical Tests

Statistical Tests

Outline Background ONCOMINE ONCOMINE Data Integration DNA Microarrays and the Cancer Transcriptome ONCOMINE Data collection, normalization & schema Statistical Analysis Visualization of Data and Analysis ONCOMINE Data Integration Therapeutic Targets / Biomarkers Metabolic and Signaling Pathways Known protein-protein Interactions ONCOMINE tutorial

Differential Expression Analysis Two-sided t-test for each gene: False discovery rate correction for multiple hypothesis testing

R, Oracle, RODBC

Outline Background ONCOMINE ONCOMINE Data Integration DNA Microarrays and the Cancer Transcriptome ONCOMINE Data collection, normalization & storage Statistical Analysis Visualization of Data and Analysis ONCOMINE Data Integration Therapeutic Targets / Biomarkers Metabolic and Signaling Pathways Known protein-protein Interactions ONCOMINE tutorial

Oncomine Tutorial part I Gene Differential Expression Gene Co-Expression Study Differential Expression WWW.ONCOMINE.ORG EMAIL: SHORTCOURSE PASSWORD: MCBI

Outline Background ONCOMINE ONCOMINE Data Integration DNA Microarrays and the Cancer Transcriptome ONCOMINE Data collection, normalization & storage Statistical Analysis Visualization of Data and Analysis ONCOMINE Data Integration Therapeutic Targets / Biomarkers Metabolic and Signaling Pathways Known protein-protein Interactions ONCOMINE tutorial

Therapeutic Targets / Biomarkers Gene Ontology Consortium Biological Process (apoptosis, cell cycle) Cellular Component (cytoplasmic membrane, extracellular) Molecular Function (kinase, phosphatase, protease, etc.) Known Therapeutic Targets NCI Clinical Trials Database Therapeutic Target Database

Therapeutic Target Database 338 proteins with Literature-documented Inhibitor, antagonist, Blocker, etc. http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp

Known Drug Targets Expressed in Bladder Cancer

Secreted proteins highly expressed in Ovarian Cancer

Outline Background ONCOMINE ONCOMINE Data Integration DNA Microarrays and the Cancer Transcriptome ONCOMINE Data collection, normalization & storage Statistical Analysis Visualization of Data and Analysis ONCOMINE Data Integration Therapeutic Targets / Biomarkers Metabolic and Signaling Pathways Known protein-protein Interactions ONCOMINE tutorial

Metabolic & Signaling Pathways KEGG Kyoto Encyclopedia of Genes & Genomes 87 metabolic pathways, 1700 gene assignments Biocarta Signaling pathways reviewed and entered by ‘expert’ biologists 215 signaling pathways, 3700 gene assignments

Pathway enrichment analysis Identify pathways and functional groups of genes deregulated in particular cancer types Enrichment Analysis using Kolmogrov-Smirnov Scanning (Lamb et al)

Kolmogrov-Smirnov Scanning (Lamb et al) 1 2 * 3 4 * 5 6 * 7 * 8 9 10 11 12 13 14 15 16 17 18 * 19 20 (1,2,3,4…,19,20) Vs. (2,4,6,7,18)

Pathway Enrichment Liver vs. other Normal tissues

Pathway Enrichment cont

Pathway enrichment analysis A search for the Biocarta pathways most enriched in a medulloblastoma signature (C2) uncovered involvement of the Ras/Rho pathway

Pathway enrichment analysis cont. A direct link to the Biocarta pathway provides the details (Medulloblastoma genes with red boxes)

Outline Background ONCOMINE ONCOMINE Data Integration DNA Microarrays and the Cancer Transcriptome ONCOMINE Data collection, normalization & storage Statistical Analysis Visualization of Data and Analysis ONCOMINE Data Integration Therapeutic Targets / Biomarkers Metabolic and Signaling Pathways Known protein-protein Interactions ONCOMINE tutorial

Known Protein-Protein Interactions HPRD Human Protein Reference Database Manually curated 20,000+ papers, 15,000+ distinct interactions PKDB Protein Kinase Database Natural Language Processing 60,000+ abstracts suggest interaciton, 16,000 distinct interactions Error prone Co-RIF Locus Link Reference into Function 12,000+ co-RIFs

Human Interactome Map (www.himap.org)

INTERACT

Outline Background ONCOMINE ONCOMINE Data Integration DNA Microarrays and the Cancer Transcriptome ONCOMINE Data collection, normalization & storage Statistical Analysis Visualization of Data and Analysis ONCOMINE Data Integration Therapeutic Targets / Biomarkers Metabolic and Signaling Pathways Known protein-protein Interactions ONCOMINE tutorial

Oncomine Tutorial Part II Gene set filtering to identify therapeutic targets and biomarkers Enrichment Analysis to identify pathways and processes deregulated in cancer Pathway and protein interaction networks deregulated in cancer

Acknowledgements Chinnaiyan Lab Pandey Lab IOB Radhika, Terry, Vasu, Jianjun, Scott, Soory Pandey Lab IOB Shanker, Nandan