cBioPortal Tutorial #7:

Pathways

Explore genomics data in the context of pathways

Last update: February 15, 2021

Tutorial Objectives

• Motivate viewing cancer genomics data in context of pathways
• Locate cBioPortal Pathways tabs in Results or Patient views
• Introduce pathway view components
• Detail pathway view toolbar operations
• Save as static images
• Perform layout
• Expand query genes [Results view only]
• Edit pathway with PathwayMapper editor [Results view only]
• Get help on notation
• Walk through different pathway ranking options [Results view only]
• List technology behind the component

Motivation for Pathways View

• Genomic alterations in cancer often affect a relatively small number of signaling pathways involved in cell proliferation, cell growth, apoptosis and DNA repair, among others [1]
• The Cancer Genome Atlas (TCGA), an effort to comprehensively characterize genomic alterations in more than 20 tumor types, produced a number of publications with hand-drawn pathways summarizing such alterations [2]
• Pathways tabs in cBioPortal overlay alteration data from your study or patient of interest on TCGA pathways while highlighting your genes of interest.
• The Pathways tab is available in Results view and Patient view

[1] Bahceci et al. “PathwayMapper: a collaborative visual web editor for cancer pathways and genomic data”, Bioinformatics, 2017

[2] The Cancer Genome Atlas Program

Pathways Tab in Results View

• One may be interested in viewing genetic alterations in a particular study in the context of pathways
• Start with Results view in TP53 and MDM2/4 alterations in “Glioblastoma (TCGA, Nature 2008)” as an example

Not sure how to run a query to get to Results View? Review Tutorial #2: Single Study Query

Link to this page

Pathways Tab in Results View

Toolbar for pathway operations

Pathway with alteration frequencies of selected genetic profiles of the chosen study overlaid

TCGA pathways table, sorted by score using current ranking scheme

Pathways tab

Link to this page

Toggle between pathways defined by TCGA PanCancer Atlas (default), or all TCGA publications

Ranking options

Results Pathways View

Resulting pathway tab from example query “TP53 and MDM2/4 alterations in GBM”

Query genes of interest are shown with thicker borders

TCGA pathway ranking highest with default ranking scheme is shown

Name of TCGA pathway currently shown

Link to this page

Overview window (useful for navigating large pathways)

Pan-zoom controls

Toolbar for pathway operations

More information about notation used can be found here

Results Pathways View Toolbar

Buttons on the toolbar provide useful operations

Perform incremental layout, respecting current positions

Link to this page

Add selected genes to query

Add all valid genes in this pathway to query

Edit pathway with PathwayMapper editor

Save current pathway as SVG

Save current pathway as PNG

Quick help with a link to detailed documentation

Results Pathways Table & Ranking Options

Genes in current pathway matching those in query genes

TCGA pathway currently selected / shown

Link to this page

Match count vs percentage: whether we should score pathways by the number of genes matched or by the percentage of genes matched

Score of each TCGA pathway using current ranking scheme

Consider alteration frequency: whether we should take each matching gene with a count of 1 or with a weight of its alteration frequency in scoring

Search pathway by name

Toggle between pathways defined by TCGA PanCancer Atlas (default), or all TCGA publications

Results Pathways View Ranking Options

Link to this page

• When a query gene is in a particular pathway, we consider it “matching”.
• Example:
• Query genes: TP53, MDM2, MDM4
• Pathway: BRCA-2012-TP53-pathway (see on the right)

BRCA-2012-TP53-pathway

• Match count vs percentage:
• Count the query genes matching and rank pathways based on this count. The score in our example is 3 as all three genes are in the pathway.
• Take the ratio of query genes matching to total number of genes in the pathway. The score in our example is 3 / 6 = 50%.
• Consider alteration frequency:
• When checked, each matching gene will not contribute to the score as 1 unit but with its alteration frequency of that gene. The score in our example is 35.2+14.3+6.6 = 56.1.

Pathways Tab in Patient View

• One may be interested in viewing following types of genetic alterations of a patient in the context of pathways

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• Start with “Patient view of an endometrial cancer case (TCGA, Nature 2013)” as an example

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Not sure how to get to patient view? Review Tutorial #3: Patient View

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Link to this page

Patient Pathways View

Pathway with genetic alterations of the patient

TCGA pathways table, where altered pathways are shown before non-altered ones by default

Pathways tab

Link to this page

Toolbar for pathway operations

More information about notation used can be found here

Patient Pathways View

Link to this page

Mouse over to see alteration details

Pathways tab from example “Patient view of an endometrial cancer case”

Altered genes are shown with thicker borders

Pan-zoom controls

Name of TCGA pathway currently shown

Patient Pathways View

Buttons on the toolbar provide useful operations

Link to this page

Pathways tabs in cBioPortal were built using a viewer only edition of PathwayMapper, which in turn was based on Cytoscape.js, a fully featured graph library in pure JavaScript.

Questions?

Check out our other tutorials

or email us at: cbioportal@googlegroups.com