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Updated: Oct 1, 2025

Identification of EGFR and RAS Inhibitors using Caenorhabditis elegans
Published on: October 5, 2020
Reconstruction and analysis of a large-scale binary Ras-effector signaling network
Simona Catozzi1,2, Camille Ternet1,2, Alize Gourrege1,2
1Systems Biology Ireland, School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland.
Background:
Ras is a key cellular signaling hub that controls numerous cell fates via multiple downstream effector pathways. While pathways downstream of effectors such as Raf, PI3K and RalGDS are extensively described in the literature, how other effectors signal downstream of Ras is often still enigmatic.
Methods:
A comprehensive and unbiased Ras-effector network was reconstructed downstream of 43 effector proteins (converging onto 12 effector classes) using public pathway and protein-protein interaction (PPI) databases. The output is an oriented graph of pairwise interactions defining a 3-layer signaling network downstream of Ras. The 2290 proteins comprising the network were studied for their implication in signaling crosstalk and feedbacks, their subcellular localizations, and their cellular functions.
Results:
The final Ras-effector network consists of 2290 proteins that are connected via 19,080 binary PPIs, increasingly distributed across the downstream layers, with 441 PPIs in layer 1, 1660 in layer 2, and 16,979 in layer 3. We identified a high level of crosstalk among proteins of the 12 effector classes. A class-specific Ras sub-network was generated in CellDesigner (.xml file) and a functional enrichment analysis thereof shows that 58% of the processes have previously been associated to a respective effector pathway, with the remaining providing insights into novel and unexplored functions of specific effector pathways.
Conclusions:
Our large-scale and cell general Ras-effector network is a crucial steppingstone towards defining the network boundaries. It constitutes a 'reference interactome' and can be contextualized for specific conditions, e.g. different cell types or biopsy material obtained from cancer patients. Further, it can serve as a basis for elucidating systems properties, such as input-output relationships, crosstalk, and pathway redundancy. Video Abstract.
Insights
This study maps the Ras-effector network, revealing extensive crosstalk and novel functions. The comprehensive interactome serves as a foundation for understanding Ras signaling in various cellular contexts and diseases like cancer.
Area of Science:
- Cellular signaling and molecular networks
- Systems biology and bioinformatics
Background:
- Ras is a central regulator of cell fate, controlling multiple downstream pathways.
- While some Ras effector pathways are well-studied, many remain poorly understood.
Purpose of the Study:
- To construct a comprehensive and unbiased Ras-effector network.
- To analyze signaling crosstalk, feedbacks, localization, and functions within the network.
Main Methods:
- Reconstruction of a Ras-effector network using public pathway and protein-protein interaction (PPI) databases.
- Analysis of 43 effector proteins and 12 effector classes, resulting in a 3-layer signaling network.
- Generation of class-specific subnetworks and functional enrichment analysis.
Main Results:
- The network comprises 2290 proteins and 19,080 PPIs, with interactions increasing in downstream layers.
- Significant crosstalk was identified among the 12 effector classes.
- Functional enrichment revealed known and novel functions for specific effector pathways.
Conclusions:
- The developed Ras-effector network is a reference interactome for defining network boundaries.
- It can be contextualized for specific cell types or cancer patient data.
- The network provides a basis for studying systems properties like crosstalk and pathway redundancy.
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