Hinxton 30 March Reactome Functional Interaction (FI) Network Steve Jupe

Hinxton 30 March Motivation for Pathway and Network Analysis in Cancer “Exclusivity principle” in cancer. once a gene is mutated in a pathway, the selective growth advantage incurred by a second mutated gene in the same pathway is minimal. rare for a single tumor to have multiple genes altered in the same pathway. Analyzing mutated genes in a pathway context. reveals relationships among these genes. facilitates hypothesis generation on roles of these genes in disease phenotype. identifies genes on the affected pathways as therapeutic targets.

Hinxton 30 March Analysis Workflow – Cancer Microarray Experiment: Gene expression profiling of pancreatic tumour (vs normal tissue). Output: list of genes that show significant changes in expression. Downstream analysis: 1.Validation of the top genes sorted by fold-change (or p-value): artificial cut-off, information loss; 2.Manual reviewing and gene classification based on literature, databases and own prior experience: time-consuming and bias; 3.GO annotation and pathway analysis (e.g. Reactome): what biological terms or functional categories are represented in the gene list more often than expected by chance; 4.Network-based analysis. - identify markers not as individual genes but as sub-networks extracted from protein interaction databases and the resulting sub-networks provide novel hypotheses for pathways involved in cancer.

Hinxton 30 March What is the Functional Interaction Network? A reliable interaction network based on manually curated pathways extended with verified interactions Covers almost 50% of human Uniprot proteins A resource for construction of FI sub-networks based on gene sets Tools that: Provide the underlying evidence for FIs Build and analyze network modules of highly-interacting groups Perform functional enrichment to annotate modules Expand the network by finding genes related to the experimental data display source pathway diagrams and overlay with a variety of information sources such as cancer gene index annotations. Method and practical application: A human functional protein interaction network and its application to cancer data analysis, Wu et al Genome BiologyWu et al Genome Biology

Hinxton 30 March Pairwise Problem Input1-Input2, Input1-Catalyst, Input1-Activator, Input1- Inhibitor, Input2-Catalyst, Input2- Activator, Input2-Inhibtior, Catalyst-Activator, Catalyst- Inhibitor, Activator-Inhibitor Reaction Functional Interaction Convert reactions in pathways into pair-wise relationships Functional Interaction: an interaction in which two proteins are involved in the same reaction as input, catalyst, activator and/or inhibitor, or as components in a complex

Hinxton 30 March Reactome Functional Interaction (FI) Network [15%] Wu et al. Genome Biology 2010 Construction of the Reactome FI Network

Hinxton 30 March Coverage after Prediction 10,956 proteins (9,542 genes) 209,988 FIs 5% of network shown here

Hinxton 30 March Reactome Pathway Diagram with FI Overlay

Hinxton 30 March Limitations of web FI overlay Simple viewer – no extra tools Not easy to produce networks Not dynamic – you can’t move the pathway diagram objects

Hinxton 30 March Projecting Experimental Data onto FI Network

Hinxton 30 March A FI Sub-Network Generated from Significant Network Modules based on a TCGA OV Expression Data Set

Hinxton 30 March Cytoscape Cytoscape - open source platform for visualizing complex- networks and integrating these with any type of attribute data. Java-based Plug-in development framework First public release: July 2002, v0.8 Current release: Website:

Hinxton 30 March

Hinxton 30 March Reactome FI Cytoscape Plug-In Cytoscape v2.7.0 or later. Reactome Homepage (see URL below) Menu Bar -> Tools, FI Cytoscape Plugin Save jar file caBigR3.jar into Cytoscape plugins folder, restart.caBigR3.jar Also available as Java Web Start: Cytoscape.jnlpCytoscape.jnlp

Hinxton 30 March FI Network Analysis Pipeline Select gene list (mutated, over- expressed, down-regulated, amplified or deleted genes) Project genes of interest onto Reactome F.I. Network Identify Disease/Cancer Subnetwork Apply Clustering Algorithms Apply Pathway/GO Annotation to each cluster Generate Biological Hypothesis! Predict Disease Gene Function Classify Patients & Samples T2D OvCa GBM Breast Prostate TCGA ICGC

Hinxton 30 March Using the Reactome FIs Plug-in Choose Plugins, Reactome FIs. FI plug-in supports three file formats: Simple gene set: one line per gene. Gene/sample number pair. Contains two required columns, gene and number of samples having gene mutated, and an optional third column listing sample names (delimited by semi-colon ;). NCI MAF (mutation annotation file).

Hinxton 30 March File Formats MSI2 PTPRT PELO SLC18A1 TACC2 FAM148B PRC1 MSTN ATP6V1G2 APOE IMPA2 AGER XPO5 MEST RREB1 BAT1 WIPI1 CATSPERB SSR1 VEGFA EGFL8 Simple Gene ListGene/Sample Number PairsNCI MAF (mutation annotation file)

Hinxton 30 March Loading a file Choose file Choose file format and parameters Click OK

Hinxton 30 March Results Display Constructed network is displayed in the Network View panel using an FI specific visual style

Hinxton 30 March Pop-up menu Right-click an empty space in the network view panel.

Hinxton 30 March Fetch FI annotations Details information on selected FIs. Three edge attributes are created: FI Annotation, FI Direction, and FI Score. Edges display direction attribute values. --> for activating/catalyzing --| for inhibition solid line for complexes or inputs --- for predicted FIs. VizMapper tab, Edge Source Arrow Shape and Edge Target Arrow Shape values give details.

Hinxton 30 March Analyze network functions Pathway or GO term enrichment analysis for the displayed network. Use Data Panel to: Filter enrichment results by FDR value. Check “Hide nodes in not selected rows” to display only nodes in the selected row or rows To analyze an unlinked set of genes choose the "Show genes not linked to others" option when importing data

Hinxton 30 March Cluster FI network Runs spectral partition based network clustering (Newman, 2006) on the displayed FI network.Newman, 2006 Nodes in different network modules will be shown in different colours (max 15 colours).

Hinxton 30 March Analyze module functions Pathway or GO term enrichment analysis on individual network modules. Use filter to remove small network modules Filter by FDR Button selects nodes in the network corresponding to selected row or rows in the Data Panel.

Hinxton 30 March Other features - Query FI source Right-click edge, select "Reactome FI/Query FI Source". If the FI was extracted from a curated pathway the original data source(s) is displayed Double click a row in the table to show details If the FI is predicted the evidence is displayed.

Hinxton 30 March Other features - Fetch FIs for node Select node in the network panel, right click for pop-up menu, select "Reactome FI, Fetch FIs" FI partners for the selected node are displayed in two sections: Partners that are displayed and partners that are not displayed. Select undisplayed partners and click Add

Hinxton 30 March Other features - Show pathway diagram (KEGG) Select a pathway in "Pathways in Network/Modules" tabs, right click, select "Show Pathway Diagram” KEGG pathways - diagram page is opened. Nodes listed in "Nodes" column are highlighted in red.

Hinxton 30 March Other features - Show pathway diagram (Reactome) Reactome pathway diagrams open in a separate window. For human data the manually drawn pathway diagram is displayed. For other species an automated layout is generated. Nodes in the Cytoscape network are highlighted in blue on the diagram Detailed information is viewed using a pop-up menu item "View Instance". Zoom slider bottom of the window. Overview window top-right corner

Hinxton 30 March Cancer Gene Index annotations Cancer Gene Index annotations can be added in two ways: popup menu "Load Cancer Gene Index" when no object is selected (left) popup menu "Fetch Cancer Gene Index" for a selected node (right)

Hinxton 30 March Load Cancer Gene Index This method loads the tree of NCI disease terms in the left panel. Select a disease term in the tree to select all diagram objects that have this annotation or one of its sub-terms.

Hinxton 30 March Fetch Cancer Gene Index This method is for viewing detailed annotations for the selected gene or protein. Annotations are sortable by PubMed ID, Cancer type, status, and several other criteria.

Hinxton 30 March Cancer Gene Survival Analysis Based on a server-side R script that runs either coxph or Kaplan-Meyer survival analysis. Requires appropriate data file (see online). Popup menu “Analyze Module Functions, Survival Analysis...” Results are displayed with a tab "Survival Analysis" (right). You can display multiple analyses. Only Kaplan-Meyer analysis will show a plot file. You can click the file to view the actual plot (far right).

Hinxton 30 March Summary Reactome is a highly reliable, human-curated database of biological pathways and reactions. Expanded the human curated Reactome pathways by importing pathways from other databases and integrating predicted FIs: ~50% coverage. Functional interaction network provides a powerful way to visualize cancer and other disease genes to reveal functional relationships among these genes.

Hinxton 30 March Future Implement multiple network clustering algorithms Currently spectral partition only Future: edge-betweenness, MCL, and hierarchical clustering Integrate with other data types: gene expressions, CNVs… Seamless integration with Reactome pathway diagrams Expand known cancer pathways by using FIs Integrate miRNA/target interactions to study miRNA activities on cancers

Hinxton 30 March Software Demo