Related Experiment Video
Updated: Nov 25, 2025
Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
Published on: July 22, 2020
DriveWays: a method for identifying possibly overlapping driver pathways in cancer
Ilyes Baali1, Cesim Erten2, Hilal Kazan3
1Electrical and Computer Engineering Graduate Program, Antalya Bilim University, 07190, Antalya, Turkey.
Abstract:
The majority of the previous methods for identifying cancer driver modules output nonoverlapping modules. This assumption is biologically inaccurate as genes can participate in multiple molecular pathways. This is particularly true for cancer-associated genes as many of them are network hubs connecting functionally distinct set of genes. It is important to provide combinatorial optimization problem definitions modeling this biological phenomenon and to suggest efficient algorithms for its solution. We provide a formal definition of the Overlapping Driver Module Identification in Cancer (ODMIC) problem. We show that the problem is NP-hard. We propose a seed-and-extend based heuristic named DriveWays that identifies overlapping cancer driver modules from the graph built from the IntAct PPI network. DriveWays incorporates mutual exclusivity, coverage, and the network connectivity information of the genes. We show that DriveWays outperforms the state-of-the-art methods in recovering well-known cancer driver genes performed on TCGA pan-cancer data. Additionally, DriveWay's output modules show a stronger enrichment for the reference pathways in almost all cases. Overall, we show that enabling modules to overlap improves the recovery of functional pathways filtered with known cancer drivers, which essentially constitute the reference set of cancer-related pathways.
Insights
This study introduces DriveWays, a new method for identifying overlapping cancer driver modules. Overlapping modules better reflect biological complexity and improve the recovery of cancer-related pathways compared to nonoverlapping methods.
Area of Science:
- Computational Biology
- Cancer Genomics
- Systems Biology
Background:
- Previous methods for identifying cancer driver modules often assume nonoverlapping modules, which is biologically inaccurate.
- Genes, especially cancer-associated ones, can participate in multiple molecular pathways and act as network hubs.
Purpose of the Study:
- To formally define the Overlapping Driver Module Identification in Cancer (ODMIC) problem.
- To develop an efficient algorithm for identifying overlapping cancer driver modules.
Main Methods:
- Formal definition of the Overlapping Driver Module Identification in Cancer (ODMIC) problem, proving its NP-hard nature.
- Development of DriveWays, a seed-and-extend heuristic using the IntAct protein-protein interaction network.
- DriveWays incorporates gene mutual exclusivity, coverage, and network connectivity.
Main Results:
- DriveWays outperforms state-of-the-art methods in recovering known cancer driver genes from TCGA pan-cancer data.
- Output modules from DriveWays demonstrate stronger enrichment for reference pathways.
- Enabling module overlap improves the recovery of functional cancer-related pathways.
Conclusions:
- Overlapping module identification is crucial for accurately modeling cancer biology.
- DriveWays provides an effective approach for identifying overlapping cancer driver modules.
- This approach enhances the discovery and understanding of cancer-related pathways.
More Related Videos
03:08Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
10:27Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Related Concept Videos
01:19Interactions Between Signaling Pathways
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
02:53Adaptive Mechanisms in Cancer Cells
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...