CONTOURv2

CONTOURv2 employs a log-linear model to analyze dysregulation of protein complexes in cancer by integrating protein-interaction (PPI) datasets with gene-expression data to identify transcription factor (TF) regulation and altered complex expression.

Key Features:

• Protein Complex Analysis: Identifies and analyzes changes in protein complex expression across cancer conditions to provide an integrated view of multi-gene contributions to disease states.
• Integration with Large-Scale Datasets: Integrates protein-interaction (PPI) datasets with gene-expression data to detect significant changes in complex expression across conditions.
• Log-Linear Modeling: Employs a log-linear model to relate changes in complex expression to differential regulation by transcription factors (TFs), elucidating cooperative and counteractive TF interactions.
• Case Study Findings: Applied analyses to pancreatic and familial breast tumors, revealing altered complexes involved in DNA damage repair and the cell cycle and patterns of decreases and compensatory increases in complex expression.

Scientific Applications:

• Mechanistic insight in cancer: Highlights dynamic regulation of protein complexes and their transcriptional control in tumorigenesis.
• Identification of aberrant complexes and TF regulators: Enables detection of complexes and transcription factors involved in compensatory processes and altered cellular functions such as genome stability maintenance and cell proliferation.
• Application to tumor types: Provides analyses specific to pancreatic and familial breast tumors to reveal complex-level dysregulation relevant to cancer initiation and progression.

Methodology:

Integration of protein-interaction (PPI) datasets with gene-expression data, identification and analysis of changes in protein complex expression across conditions, and application of a log-linear model to relate complex expression changes to differential transcription factor (TF) regulation.