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Ubiquitinomics revealed disease- and stage-specific patterns relevant for the 3PM approach in human sigmoid colon cancers

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Abstract

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.

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Data availability

All data and materials are provided in this article and supplemental materials, which can be available publicly.

Code availability

All protein and gene accession codes can be available in the Swiss-Prot and GenBank databases.

Abbreviations

AvrA :

virulence factor

ABIN-1 :

ubiquitin-binding protein

ATP :

adenosine triphosphate

BP :

biological process

DEG :

differently expressed genes

DUB :

deubiquitinases

DUP :

differentially ubiquitinated proteins

GO :

Gene Ontology

ISP :

immune system process

KEGG :

Kyoto Encyclopedia of Genes and Genomes

K-ε-GG :

ubiquitinated lysine

LC :

liquid chromatography

MLKL :

mixed lineage kinase domain-like

MS/MS :

tandem mass spectrometry

OS :

overall survival

PHGDH :

phosphoglycerate dehydrogenase

PPI :

protein-protein interaction

PPPM :

predictive, preventive, and personalized medicine

PTM :

post-translational modifications

RIPK3 :

receptor-interacting serine-threonine kinase 3

ROS :

reactive oxygen species

TCGA :

The Cancer Genome Atlas

TH1 :

CD4+T helper 1 cells

TH-17 :

T helper interleukin 17 producing

Treg :

T regulatory cells

UBD :

ubiquitin protein-binding domains

UPS :

ubiquitin proteasome system

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Acknowledgements

The authors acknowledge The Cancer Genome Atlas (TCGA) project organizers as well as all study participants for providing the publicly available TCGA RNA-seq data and clinical data.

Funding

This work was supported by the Shandong Provincial Taishan Scholar Engineering Project Special Funds (to X. Z.), SCIBP-Supported Projects (No. SCIBP2021080005), the Shandong Provincial Natural Science Foundation (ZR2021MH156, ZR2022QH112, ZR2020LZL012), the Shandong First Medical University Talent Introduction Funds (to X. Z.), the Shandong First Medical University High-level Scientific Research Achievement Cultivation Funding Program (to X. Z.), Shandong First Medical University Undergraduate Innovation Research Program (Project No. 2022104391511), China National Nature Scientific Funds (82203592), CSCO-CSPC Cancer Research Fund Project, and the Beijing Science and Technology Innovation Medical Development Foundation (No. KC2021-JX-0186-138).

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Contributions

H. Y., N. L., and L. C. analyzed the data, prepared the figures and tables, and designed and wrote the manuscript. W. J., and L. Z. collected the clinical tissue samples, sample diagnosis, and clinical explanation. Y. Z., J. L., R. C., J. S., L. Y., and X. G. participated in the partial data analysis and experiments. X. Z. conceived the concept; obtained the ubiquitinomics original data; supervised the results; designed, wrote, and critically revised manuscript; and was responsible for its financial supports and the corresponding works. All authors approved the final manuscript.

Corresponding author

Correspondence to Xianquan Zhan.

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All the patients were informed about the purposes of the study and consequently have signed their “consent of the patient.” All investigations conformed to the principles outlined in the Declaration of Helsinki and were performed with permission by Medical Ethics Committee of Shandong First Medical University, and Clinical Medical Research Ethics Committee of China-Japan Friendship Hospital, China.

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Supplementary information

Supplementary figure 1.

The significant signaling pathways of differentially ubiquitinated proteins in sigmoid cancer (PPTX 2470 kb)

Supplementary figure 2.

The overall survival analysis of differentially ubiquitinated proteins in sigmoid cancer (DOCX 1395 kb)

Supplementary Table 1:

Differentially ubiquitinated proteins in sigmoid cancer identified with quantitative ubiquitinomics. K* = ubiquitinated lysine residue (+114.04). M# = oxidated Met residue (+15.99). C# = Carbamidomethylated Cystine residue (+57.02). (+42.01) means protein N-terminal acetylation. Ratio (T/N) = Ratio (tumor/nornal control). Red = increased ubiquitination level. Green = Descreased ubiquitination level. (XLSX 196 kb)

Supplementary Table 2:

The significant pathways of differentially ubiquitinated proteins in sigmoid colon cancer. (XLSX 19 kb)

Supplementary Table 3:

The Biological Process analysis of differentially ubiquitinated proteins in sigmoid cancer. (XLS 189 kb)

Supplementary Table 4:

TheCellularComponent analysis of differentially ubiquitinated proteins in sigmoid cancer. (XLS 137 kb)

Supplementary Table 5:

The MolecularFunction analysis of differentially ubiquitinated proteins in sigmoid cancer. (XLS 106 kb)

Supplementary Table 6:

The Immune System Process analysis of differentially ubiquitinated proteins in sigmoid cancer. (XLS 70 kb)

Supplementary Table 7:

The protein and protein interaction network of the differentially ubiquitinated proteins in sigmoid cancer. (XLSX 29 kb)

Supplementary Table 8:

Clinical characteristic and corresponding gene expression of sigmoid colon cancer based on TCGA database. (XLSX 504 kb)

Supplementary Table 9:

Differentially expressed genes between cancer and normal tissues based on TCGA database according to the differentially ubiquitinated proteins in sigmoid cancer. (XLSX 17 kb)

Supplementary Table 10.

Differentially expressed proteins (DEPs) identified in colorectal cancers compared to controls*. (XLSX 24 kb)

Supplementary Table 11:

The overall survival of the differentially ubiquitinated proteins in sigmoid cancer. (XLSX 34 kb)

Supplementary Table 12:

The drug sensitivity of the identified differentially ubiquitinated proteins in sigmoid cancer. (XLSX 15 kb)

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Yang, H., Li, N., Chen, L. et al. Ubiquitinomics revealed disease- and stage-specific patterns relevant for the 3PM approach in human sigmoid colon cancers. EPMA Journal 14, 503–525 (2023). https://doi.org/10.1007/s13167-023-00328-2

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