CrossHub

CrossHub integrates TF binding evidence, miRNA target data, co-expression, and methylation correlations across TCGA to analyze gene expression regulation mechanisms in cancer.

Key Features:

• Two-Way Identification of TF-Gene Interactions: Identifies transcription factor–gene interactions using ENCODE ChIP-Seq binding evidence or Jaspar predictions combined with co-expression analysis from TCGA.
• mRNA-miRNA Pair Identification: Detects mRNA–miRNA pairs by integrating predicted or validated binding sites from TargetScan, mirSVR, PicTar, DIANA microT, and miRTarBase with strong negative expression correlations in TCGA.
• Expression-Methylation Correlation Analysis: Performs correlation analyses between gene expression and methylation to pinpoint hypermethylated CpG sites or regions that significantly impact gene expression.
• Comprehensive Molecular Portraits: Integrates TF–gene interactions, miRNA interference, and promoter/enhancer methylation to outline molecular portraits and identify the three most prevalent sources of expression regulation: methylation, miRNA interference, and TF-mediated activation or repression.

Scientific Applications:

• Cancer regulatory network analysis: Elucidates interactions among TFs, miRNAs, and methylation patterns across tumor types within TCGA to map regulatory networks.
• Biomarker and therapeutic target identification: Supports identification of potential biomarkers and therapeutic targets by linking regulatory mechanisms to gene expression changes in cancer.

Methodology:

Integrates ENCODE ChIP-Seq binding evidence and Jaspar predictions, miRNA target predictions/validations (TargetScan, mirSVR, PicTar, DIANA microT, miRTarBase), co-expression analysis of TCGA expression data, and expression–methylation correlation studies.