Objective: The patients with sigmoid colorectal cancer commonly show high mortality and poor prognosis. Increasing evidence has demonstrated that the ubiquitinated proteins and ubiquitination-mediated molecular pathways influence the growth and aggressiveness of colorectal cancer. It emphasizes the scientific merits of quantitative ubiquitinomics in human sigmoid colon cancer. We hypothesize that the ubiquitinome and ubiquitination-mediated pathway networks significantly differ in sigmoid colon cancers compared to controls, which offers the promise for in-depth insight into molecular mechanisms, discovery of effective therapeutic targets, and construction of reliable biomarkers in the framework of predictive, preventive, and personalized medicine (PPPM; 3P medicine).
Methods: The first ubiquitinome analysis was performed with anti-K-ε-GG antibody beads (PTMScan ubiquitin remnant motif [K-ε-GG])-based label-free quantitative proteomics and bioinformatics to identify and quantify ubiquitination profiling between sigmoid colon cancer tissues and para-carcinoma tissues. A total of 100 human sigmoid colon cancer samples that included complete clinical information and the corresponding gene expression data were obtained from The Cancer Genome Atlas (TCGA). Ubiquitination was the main way of protein degradation; the relationships between differentially ubiquitinated proteins (DUPs) and their differently expressed genes (DEGs) and between DUPs and their differentially expressed proteins (DEPs) were analyzed between cancer tissues and control tissues. The overall survival of those DUPs was obtained with Kaplan-Meier method.
Results: A total of 1249 ubiquitinated sites within 608 DUPs were identified in human sigmoid colon cancer tissues. KEGG pathway network analysis of these DUPs revealed 35 statistically significant signaling pathways, such as salmonella infection, glycolysis/gluconeogenesis, and ferroptosis. Gene Ontology (GO) analysis of 608 DUPs revealed that protein ubiquitination was involved in 98 biological processes, 64 cellular components, 51 molecule functions, and 26 immune system processes. Protein-protein interaction (PPI) network of 608 DUPs revealed multiple high-combined scores and co-expressed DUPs. The relationship analysis between DUPs and their DEGs found 4 types of relationship models, including DUP-up (increased ubiquitination level) and DEG-up (increased gene expression), DUP-up and DEG-down (decreased gene expression), DUP-down (decreased ubiquitination level) and DEG-up, and DUP-down and DEG-down. The relationship analysis between DUPs and their DEPs found 4 types of relationship models, including DUP-up and DEP-up (increased protein expression), DUP-up and DEP-down (decreased protein expression), DUP-down and DEP-up, and DUP-down and DEP-down. Survival analysis found 46 overall survival-related DUPs in sigmoid colon cancer, and the drug sensitivity of overall survival-related DUPs were identified.
Conclusion: The study provided the first differentially ubiquitinated proteomic profiling, ubiquitination-involved signaling pathway network changes, and the relationship models between protein ubiquitination and its gene expression and between protein ubiquitination and its protein expression, in human sigmoid colon cancer. It offers the promise for deep insights into molecular mechanisms of sigmoid colon cancer, and discovery of effective therapeutic targets and biomarkers for patient stratification, predictive diagnosis, prognostic assessment, and personalized treatment in the context of 3P medicine.
Supplementary information: The online version contains supplementary material available at 10.1007/s13167-023-00328-2.
Keywords: 3P medical approach; Health policy; Individual outcomes; Patient stratification; Personalized treatment; Predictive diagnosis; Predictive preventive personalized medicine (PPPM); Prognostic assessment; Sigmoid colon cancer; Ubiquitination; Ubiquitinomics.
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