Networks for Cancer Genomics Analysis

This page provides direct download to several interaction networks that may be useful in Cancer Genomics Analysis.

Networks are derived from Pathway Commons.

Binary or Pairwise Interaction Networks

Binary or pairwise interaction networks consist of gene nodes and edge interactions only, and do not represent the full semantic complexity of biological pathways. They can, however, be useful for many different types of network analyses in cancer genomics.

  • Binary or pairwise interaction network consisting of interactions derived from HPRD, NCI-Nature Pathway Interaction Database, Reactome, and the MSKCC Cancer Cell Map. The network was constructed as described in Cerami et al., but has since been updated to reflect current data in Pathway Commons.

Integrated Network

  • Pathway Commons also provides pairwise interaction networks for individual data sources. They can be downloaded in the Simple Interaction Format (SIF), described in the Pathway Commons README:

BioGrid HumanCyc IMID IntAct MetaCyc MINT

BioPax Networks

BioPax is a standard language that aims to enable integration, exchange, visualization and analysis of biological pathway data. Unlike the pairwise interactions above, BioPAX is able to represent the rich biological complexity of multiple types of biological pathways, including metabolic pathways, molecular interactions, signaling pathways (including molecular states and generics), gene regulation and genetic interactions.

All data from the NCI-Nature Pathway Interaction Database, Reactome, and the MSKCC Cancer Cell Map can be downloaded in BioPAX format:

NCI-Nature PID Reactome MSKCC Cell Map

Additional downloads in BioPAX format are available from Pathway Commons.

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Data Sets

The Portal contains data for 20958 tumor samples from 89 cancer studies. [Details.]

Example Queries

RAS/RAF alterations in colorectal cancer

BRCA1 and BRCA2 mutations in ovarian cancer

POLE hotspot mutations in endometrial cancer

Protein changes in PTEN-altered ovarian cancer samples

TP53 and MDM2/4 alterations in GBM

PTEN mutations in GBM in text format

BRAF V600E mutations across cancer types

Patient view of an endometrial cancer case

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– Associate Professor, University of Virginia