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Updated: Jan 10, 2026
06:52
Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
Published on: July 22, 2020
6.9K
Data-driven universal insights into tumorigenesis via hallmark networks.
Jiahe Wang1, Yan Wu1, Yuke Hou1
1Institute of Operations Research and Information Engineering, Beijing University of Technology, Beijing, China.
NPJ Systems Biology and Applications
|November 19, 2025
Summary
Cancer
Area of Science:
- Systems Biology
- Genomics
- Cancer Research
Background:
- Cancers involve complex regulatory network changes beyond single genes.
- Existing models struggle to capture the full spectrum of cancer development.
Purpose of the Study:
- To develop a whole genomic data-driven framework to model cancer development.
- To analyze dynamic changes in cancer hallmarks using gene regulatory networks.
Main Methods:
- Constructed a coarse-grained gene regulatory network of cancer hallmarks.
- Simulated tumorigenesis using stochastic differential equations.
- Analyzed network topology changes preceding hallmark shifts.
Main Results:
- Network topology reconfiguration precedes hallmark level shifts, indicating early malignancy.
- "Tissue Invasion and Metastasis" hallmark shows the largest normal-to-cancer difference.
- "Reprogramming Energy Metabolism" hallmark shows the least difference across 15 cancer types.
Conclusions:
- Cancer evolution is a systemic process.
- Network-based systems biology offers insights into tumorigenesis transitions.
- Early detection of malignancy is possible through network analysis.
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