Institute of Information Science, Academia Sinica

As an increasing number of cancer omics data become available, there is a growing need to integrate these data with the biological networks to reveal cancer mechanisms. Nevertheless, three open issues remain challenging. First, the human interactome is still incomplete. Second, the network is too complicated to directly use it for analyzing the cell behaviors and cancer mechanisms. Third, the static network cannot reflect the variations in human cells. For example, alterations in membrane proteins (MPs) and their regulated pathways have been established as cancer hallmarks; however, the analysis of MP-interacting proteins and downstream pathways across human malignancies is still an unmet need. In support of this pursuit, we develop a systematically integrated method to generate a resource of cancer membrane protein-regulated networks (CaMPNets) [1], containing 64,125 new PPIs for 1,964 MPs, using expression profiles from 5,922 tumors with overall survival outcomes across 15 human cancers. CaMPNets can reveal the cancer-wide atlas of MPs and their regulated pathways, with significant implications for facilitating the identification of gene set-based prognostic biomarkers as well as therapeutic targets and agents. Based on CaMPNets resource, we identify CHRNA9 with 12 PPIs (e.g., ERBB2) can be a therapeutic target and find its anti-metastasis agent for treatment in nicotine-induced breast cancer.