ArticleJournal of proteome research2016
Integrative Omics Analysis Reveals Post-Transcriptionally Enhanced Protective Host Response in Colorectal Cancers with Microsatellite Instability.
Article in Journal of proteome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Microbial Pathogenesis in the Era of Spatial Omics.Infection and immunity · 2023Review
- Proteomic Analysis of Protective Effects of Dl-3-n-Butylphthalide against mpp + -Induced Toxicity via downregulating P53 pathway in N2A Cells.Proteome science · 2023Article
- Article
- Quantitative Proteomics of All 14 Renal Tubule Segments in Rat.Journal of the American Society of Nephrology : JASN · 2020Article
- Article
- Article
- A comparison of graph- and kernel-based -omics data integration algorithms for classifying complex traits.BMC bioinformatics · 2017Article
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Authors and funding
2 authors.
Funding
Abstract
Microsatellite instability (MSI) is a frequent and clinically relevant molecular phenotype in colorectal cancer. MSI cancers have favorable survival compared with microsatellite stable cancers (MSS), possibly due to the pronounced tumor-infiltrating lymphocytes observed in MSI cancers. Consistent with the strong immune response that MSI cancers trigger in the host, previous transcriptome expression studies have identified mRNA signatures characteristic of immune response in MSI cancers. However, proteomics features of MSI cancers and the extent to which the mRNA signatures are reflected at the protein level remain largely unknown. Here, we performed a comprehensive comparison of global proteomics profiles between MSI and MSS colorectal cancers in The Cancer Genome Atlas (TCGA) cohort. We found that protein signatures of MSI are also associated with increased immunogenicity. To reliably quantify post-transcription regulation in MSI cancers, we developed a resampling-based regression method by integrative modeling of transcriptomics and proteomics data sets. Compared with the popular simple method, which detects post-transcriptional regulation by either identifying genes differentially expressed at the mRNA level but not at the protein level or vice versa, our method provided a quantitative, more sensitive, and accurate way to identify genes subject to differential post-transcriptional regulation. With this method, we demonstrated that post-transcriptional regulation, coordinating protein expression with key players, initiates de novo and enhances protective host response in MSI cancers.
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