Fig 1.
Bioinformatics framework for knowledge integration and construction of knowledge map.
Fig 2.
Beta-catenin biological network.
The network depicts connections among beta-catenin (CTNNB1) PTM enzymes, interacting proteins, and transcription factors co-activated beta-catenin and their targets.
Fig 3.
Functional enrichment of GO Biological Process terms for the beta-catenin network.
Enriched terms were grouped into functional clusters. The most highly enriched terms for the top ten clusters are shown in the treemap, represented as different colored blocks. For each term, box size reflects the p-value of the term enrichment.
Fig 4.
Beta-catenin sub-network for transcriptional feedback analysis.
(A) Workflow for identifying beta-catenin transcriptional targets that affect beta-catenin transcriptional activity, thereby participating in positive and/or negative feedback loops. (B) Sub-network of beta-catenin interacting proteins whose expression is regulated by a transcription factor co-activated by beta-catenin (“target-interactors”). Node fill color indicates the effect of the interacting proteins on beta-catenin transcriptional activity. Nodes with heavy borders represent genes for which there is experimental evidence of transcriptional regulation by beta-catenin.
Fig 5.
Regulation of beta-catenin activity by kinase signaling.
(A) Workflow for exploring effects of CDK5 on beta-catenin transcriptional activity. (B) Sub-network of CDK5 substrates (blue nodes) in the beta-catenin network (Step 1 of workflow) (C) Sub-network of CDK5 substrates selected for further study (Step 2 of workflow). Pathways through which CDK5 kinase activity affects beta-catenin (CTNNB1) phosphorylation state and transcriptional activity are shown.
Fig 6.
Beta-catenin sequence map of most frequently mutated sites in cancer.
PTM sites, PTM enzyme binding sites, and frequencies of cancer-associated mutations at individual sites are indicated. (B) Beta-catenin proteoforms phosphorylated on combinations of the four N-terminal phosphorylation sites Ser-33, Ser-37, Thr-41, and Ser-45 and their functional annotation.
Fig 7.
Mutation patterns of beta-catenin across cancer types.
(A) Hierarchical clustering of cancer tissues based on their pattern of mutations in the six most frequently mutated beta-catenin residues in cancer: Asp-32, Ser-33, Gly-34, Ser-37, Thr-41, and Ser-45. (Band C) Frequencies of the various possible amino acid substitutions at beta-catenin residues Ile-35 (B) and His-36 (C) observed in cancer samples. Amino acids are color coded and grouped in the pie charts according to the chemical nature of their side chains.