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Network-based method for detecting dysregulated pathways in glioblastoma cancer

Hao Wu1, Jihua Dong2, Jicheng Wei3

  • 1College of Information Engineering, Northwest A&F University, Yangling 712100, Shaanxi, People's Republic of China. haowu@nwsuaf.edu.cn.

IET Systems Biology
|January 17, 2018
PubMed

Insights

This study identifies two key molecular pathways in glioblastoma (a brain cancer) by analyzing gene mutations and expression. These pathways, involving epidermal growth factor receptor and TP53, are linked to distinct glioblastoma subtypes, aiding in diagnosis and targeted therapies.

Area of Science:

  • Cancer Biology
  • Molecular Mechanisms
  • Genomics

Background:

  • Understanding cancer's molecular mechanisms is crucial for precise diagnosis and treatment.
  • Detecting dysregulated pathways offers insights into cancer mechanisms and potential drug targets.

Purpose of the Study:

  • To present a network-based method for detecting dysregulated pathways in glioblastoma using gene mutation and expression data.
  • To identify molecular pathways associated with different glioblastoma subtypes.

Main Methods:

  • Constructed a gene network integrating gene mutation mutual exclusivity and expression changes.
  • Utilized the CFinder clustering algorithm to detect complete subgraphs.
  • Merged gene sets based on overlapping scores to identify dysregulated pathways.

Main Results:

  • Identified two significant dysregulated pathways in glioblastoma.
  • One pathway, centered around the epidermal growth factor receptor, is associated with primary glioblastoma.
  • Another pathway, involving TP53, is linked to secondary glioblastoma.

Conclusions:

  • The identified pathways provide insights into the molecular basis of glioblastoma subtypes.
  • These findings can contribute to the development of targeted therapies and improved diagnostic strategies for glioblastoma.

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