ArticleMolecular & cellular proteomics : MCP2009
Discovery and scoring of protein interaction subnetworks discriminative of late stage human colon cancer.
Article in Molecular & cellular proteomics : MCP, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 2 of them syntheses that pooled it.
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63 citing papers in PubMed, 2 syntheses or guidelines pooled it, 111 citations in OpenAlex.
- Finding lost genes in GWAS via integrative-omics analysis reveals novel sub-networks associated with preterm birth.Human molecular genetics · 2016Pooled it
- Searching for consistently reported up- and down-regulated biomarkers in colorectal cancer: a systematic review of proteomic studies.Molecular biology reports · 2012Pooled it
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- Proteinarium: Multi-sample protein-protein interaction analysis and visualization tool.Genomics · 2020Article
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3 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
We used a systems biology approach to identify and score protein interaction subnetworks whose activity patterns are discriminative of late stage human colorectal cancer (CRC) versus control in colonic tissue. We conducted two gel-based proteomics experiments to identify significantly changing proteins between normal and late stage tumor tissues obtained from an adequately sized cohort of human patients. A total of 67 proteins identified by these experiments was used to seed a search for protein-protein interaction subnetworks. A scoring scheme based on mutual information, calculated using gene expression data as a proxy for subnetwork activity, was developed to score the targets in the subnetworks. Based on this scoring, the subnetwork was pruned to identify the specific protein combinations that were significantly discriminative of late stage cancer versus control. These combinations could not be discovered using only proteomics data or by merely clustering the gene expression data. We then analyzed the resultant pruned subnetwork for biological relevance to human CRC. A number of the proteins in these smaller subnetworks have been associated with the progression (CSNK2A2, PLK1, and IGFBP3) or metastatic potential (PDGFRB) of CRC. Others have been recently identified as potential markers of CRC (IFITM1), and the role of others is largely unknown in this disease (CCT3, CCT5, CCT7, and GNA12). The functional interactions represented by these signatures provide new experimental hypotheses that merit follow-on validation for biological significance in this disease. Overall the method outlines a quantitative approach for integrating proteomics data, gene expression data, and the wealth of accumulated legacy experimental data to discover significant protein subnetworks specific to disease.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.