Multilayer network construction and analysis pipeline for gene expression data

Molecular networks are key to understanding the complexity of biological systems. Despite the advances in network construction and analysis techniques, challenges remain in incorporating multidimensional interactions into a hybrid network model and reducing the complexity of large networks into functional modules or influential nodes. Here, we introduce CREAM, a user-friendly application that empowers biologists to construct multilayer networks by integrating gene expression data with various known interactions predicted by experimental and computational techniques, and to identify functional modules and prognostic biomarkers within these networks. When applied to multiple cancer types, CREAM outperforms state-of-the-art module detection methods in identifying biologically relevant modules. Further investigation of colon adenocarcinoma revealed numerous well-known cancer regulators and a promising new therapeutic target, miR-8485. Our in vitro and in vivo experiments demonstrated its inhibitory effects on colon cancer cell proliferation and migration. Overall, CREAM is expected to significantly advance network-based precision medicine research. In order to investigate the regulatory effects of miR-8485 on human colorectal cancer cells, we performed transcriptome sequencing on human colorectal cancer cells HCT116 transfected with miR-8485 mimics and their control group.