In this panel, you can explore the oncogenic protein-protein interactions (oncoPPI) for input genes across selected cancer datasets. Some gene signature lists are provided.

The resource data is derived from mutation enrichment screen result published by Xiong et al. They includes significance tests of somatic mutation enrichment in protein-protein interaction (PPI) interfaces across 33 TCGA cancer types based on PIONEER deep-learning framework, PDB and Interactome3D.

See the original paper for details.
Xiong et al. A structurally informed human protein-protein interactome reveals proteome-wide perturbations caused by disease mutations. Nat Biotechnol. 2024. [DOI] [PubMed]

Parameters:

• Gene: Input a gene/isoform or multiple genes of interest.
• TCGA Tumor/Selected Datasets: Select cancer types of interest in the "TCGA Tumor" field and click "add" to build dataset list in the "Selected Datasets" field. Also, manual input of cancer types split by comma (e.g. COAD Tumor,READ Tumor) is also acceptable. The interaction analysis is based on the datasets list.

Notes:

• This module focuses on PPIs significantly enriched with somatic mutations in their interfaces (oncoPPI) in TCGA cancer types.
• Data is integrated from PIONEER predictions, PDB structures, and Interactome3D homologous models.
• When searching for a single gene, the displayed network graph highlights the top 10 nodes with the lowest FDR related to the target gene within the selected datasets and interaction patterns.
• When searching for multiple genes, the displayed network graph the top 10 nodes with the highest degrees connected to the target genes within the selected datasets and interaction patterns.