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Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Annotating cancer variants and anti-cancer therapeutics in reactome
Marija Milacic1, Robin Haw, Karen Rothfels
1Informatics and Bio-computing Platform, Ontario Institute for Cancer Research, Toronto, ON, M5G0A3, Canada. robin.haw@oicr.on.ca.
Abstract:
Reactome describes biological pathways as chemical reactions that closely mirror the actual physical interactions that occur in the cell. Recent extensions of our data model accommodate the annotation of cancer and other disease processes. First, we have extended our class of protein modifications to accommodate annotation of changes in amino acid sequence and the formation of fusion proteins to describe the proteins involved in disease processes. Second, we have added a disease attribute to reaction, pathway, and physical entity classes that uses disease ontology terms. To support the graphical representation of "cancer" pathways, we have adapted our Pathway Browser to display disease variants and events in a way that allows comparison with the wild type pathway, and shows connections between perturbations in cancer and other biological pathways. The curation of pathways associated with cancer, coupled with our efforts to create other disease-specific pathways, will interoperate with our existing pathway and network analysis tools. Using the Epidermal Growth Factor Receptor (EGFR) signaling pathway as an example, we show how Reactome annotates and presents the altered biological behavior of EGFR variants due to their altered kinase and ligand-binding properties, and the mode of action and specificity of anti-cancer therapeutics.
Insights
Reactome now annotates cancer pathways by extending its data model to include disease attributes and protein modifications. This enables visualization of cancer variants and comparison with normal pathways for therapeutic insights.
Area of Science:
- Biochemistry
- Molecular Biology
- Bioinformatics
Background:
- Reactome models biological pathways as chemical reactions mirroring cellular interactions.
- Existing Reactome data structures require extension to incorporate disease-specific information, particularly for cancer.
Purpose of the Study:
- To extend the Reactome data model for annotating cancer and other disease processes.
- To enhance pathway visualization and analysis tools for disease variants.
Main Methods:
- Extended the protein modification class to include amino acid sequence changes and fusion proteins relevant to disease.
- Added a disease attribute to reaction, pathway, and physical entity classes, utilizing disease ontology terms.
- Adapted the Pathway Browser for graphical representation and comparison of disease variants with wild-type pathways.
Main Results:
- The extended Reactome model now accommodates annotation of disease-related protein alterations.
- Disease attributes integrated into Reactome allow for specific tracking of disease pathways.
- The Pathway Browser visualizes cancer pathway variants, their connections to other pathways, and therapeutic interventions.
Conclusions:
- Reactome's data model extensions facilitate comprehensive annotation of cancer pathways.
- These enhancements enable interoperability with existing pathway and network analysis tools.
- The updated Reactome system provides insights into altered biological behavior in diseases like cancer, aiding therapeutic development.
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