Loss of connectivity in cancer co-expression networks

Area of Science:

• Genomics
• Systems Biology
• Cancer Research

Background:

• Differential gene expression identifies biomarkers but misses alterations affecting gene function or protein activity.
• Oncogenic mutations and post-translational modifications can alter gene networks without changing expression levels.
• Studying co-expressed gene networks provides complementary information to differential expression analysis.

Purpose of the Study:

• To investigate the rewiring of co-expressed gene networks in cancer.
• To identify genes with differentiated co-expression patterns between normal and tumor tissues.
• To complement differential expression analysis with network connectivity insights.

Main Methods:

• Analysis of 339 mRNAomes across five cancer types.
• Identification of differentially connected genes between normal and tumor phenotypes.
• Integration of differential expression and differential connectivity analyses.

Main Results:

• Loss of connectivity is a common topological feature in cancer gene networks.
• Novel candidate cancer genes were identified through network analysis.
• Integrated analysis improved pathway enrichment, revealing new cancer-related biological systems.

Conclusions:

• Network connectivity analysis is crucial for understanding cancer beyond gene expression levels.
• Altered gene network topology is a hallmark of cancer.
• Combining differential expression and connectivity offers a more comprehensive view of cancer gene functions and interactions.