Proteomic analyses reveal divergent ubiquitylation patterns in hepatocellula carcinoma cell lines with different metastasis potential

High-throughput Proteomics-Guided Biomarker Discovery of Hepatocellular Carcinoma

Liver cancer stands as the fifth leading cause of cancer-related deaths globally. Hepatocellular carcinoma (HCC) comprises approximately 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients qualify for curative therapy, primarily due to the absence of reliable tools for early detection and prognosis of HCC. This underscores the critical need for molecular biomarkers for HCC management. Since proteins reflect disease status directly, proteomics has been utilized in biomarker developments for HCC. In particular, proteomics coupled with liquid chromatography-mass spectrometer (LC-MS) methods facilitate the process of discovering biomarker candidates for diagnosis, prognosis, and therapeutic strategies. In this work, we investigated LC-MS-based proteomics methods through recent reference reviews, with a particular focus on sample preparation and LC-MS methods appropriate for the discovery of HCC biomarkers and their clinical applications. We classified proteomics studies of HCC according to sample types, and we examined the coverage of protein biomarker candidates based on LC-MS methods in relation to study scales and goals. Comprehensively, we proposed protein biomarker candidates categorized by sample types and biomarker types for appropriate clinical use. In this review, we summarized recent LC-MS-based proteomics studies on HCC and proposed potential protein biomarkers. Our findings are expected to expand the understanding of HCC pathogenesis and enhance the efficiency of HCC diagnosis and prognosis, thereby contributing to improved patient outcomes.

qPTM: an updated database for PTM dynamics in human, mouse, rat and yeast

Post-translational modifications (PTMs) are critical molecular mechanisms that regulate protein functions temporally and spatially in various organisms. Since most PTMs are dynamically regulated, quantifying PTM events under different states is crucial for understanding biological processes and diseases. With the rapid development of high-throughput proteomics technologies, massive quantitative PTM proteome datasets have been generated. Thus, a comprehensive one-stop data resource for surfing big data will benefit the community. Here, we updated our previous phosphorylation dynamics database qPhos to the qPTM (http://qptm.omicsbio.info). In qPTM, 11 482 553 quantification events among six types of PTMs, including phosphorylation, acetylation, glycosylation, methylation, SUMOylation and ubiquitylation in four different organisms were collected and integrated, and the matched proteome datasets were included if available. The raw mass spectrometry based false discovery rate control and the recurrences of identifications among datasets were integrated into a scoring system to assess the reliability of the PTM sites. Browse and search functions were improved to facilitate users in swiftly and accurately acquiring specific information. The results page was revised with more abundant annotations, and time-course dynamics data were visualized in trend lines. We expected the qPTM database to be a much more powerful and comprehensive data repository for the PTM research community.

The Analysis of the Ubiquitylomic Responses to Streptococcus agalactiae Infection in Bovine Mammary Gland Epithelial Cells

Purpose

Streptococcus agalactiae is one of the primary pathogens responsible for subclinical mastitis, a significant economic burden for dairy farms. An essential component of the immune response to infection is ubiquitination, which plays important roles in the complex interactions between the pathogen and host.

Materials and Methods

In the present study, quantitative ubiquitylomics was performed to profile changes in the global ubiquitinome of bovine mammary gland epithelial cells (BMECs) infected with S. agalactiae.

Results

The most notable changes in the BMEC ubiquitinome were related to the adherens junction, ribosome, and tight junction pathways. Ubiquitination of CTNNB1, EGFR, ITGB1, CTNNA1, CTNNA2, CDH1, YES1, and SLC9A3R1 appears to be fundamental for regulating multiple cellular processes in BMECs in response to S. agalactiae infection. In addition, broad ubiquitination of various effectors and outer membrane proteins was observed. Ubiquitinated proteins in S. agalactiae-infected BMECs were associated with regulating cell junctions in the host, with potential implications for susceptibility to infection.

Conclusion

The preliminary findings suggest that extensive ubiquitination of CTNNB1, CDH1 and SLC9A3R1 and proteins closely related to cell junctions might play an important role in mastitis progression in dairy cows. The results provide evidence that ubiquitin modification of certain proteins in S. agalactiae-infected BMECs could be a promising therapeutic strategy for reducing mammary gland injury and mastitis.

XRCC5 downregulated by TRIM25 is susceptible for lens epithelial cell apoptosis

Exposure of the lens to UVB can lead to oxidative stress, which would result in age-related cataract (ARC) formation. In this study, we investigate the regulatory mechanism of tripartite motif containing 25 (TRIM25) in ARC. The protein level of TRIM25 was elevated in ARC specimens and UVB-exposed SRA01/04 cells. Bioinformatic analysis indicated that X-ray repair cross complementing 5 (XRCC5) might interact with TRIM25, and the interaction was validated via immunoprecipitation. TRIM25 interacted with XRCC5 and ubiquitinated it for degradation. Further studies showed that XRCC5 overexpression notably repressed UVB-induced apoptosis, while XRCC5 knockdown promoted apoptosis. Of note, ubiquitination of XRCC5 mediated by TRIM25 overexpression facilitated apoptosis. Attenuation of XRCC5 ubiquitination by mutant with substitution of lysine residues with arginine residues rescued its anti-apoptosis effect. Moreover, we observed that TRIM25-mediated XRCC5 degradation was reversed by proteasome inhibitor MG-132 or lysosome inhibitor 3-MA. In conclusion, TRIM25 mediates ubiquitination of XRCC5 to regulate the function and degradation of XRCC5, suggesting that interventions targeting TRIM25 might be a promising therapeutic strategy for ARC.

Potential Biomarkers for Liver Cancer Diagnosis Based on Multi-Omics Strategy

Liver cancer is the fourth leading cause of cancer-related death worldwide. Hepatocellular carcinoma (HCC) accounts for about 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients are eligible for curative therapy mainly due to the lack of early-detection strategies, highlighting the significance of reliable and accurate biomarkers. The integration of multi-omics became an important tool for biomarker screening and unique alterations in tumor-associated genes, transcripts, proteins, post-translational modifications and metabolites have been observed. We here summarized the novel biomarkers for HCC diagnosis based on multi-omics technology as well as the clinical significance of these potential biomarkers in the early detection of HCC.

The role of the ubiquitin-proteasome pathway in skin cancer development: 26S proteasome-activated NF-κB signal transduction

The Ubiquitin-Proteasome System plays a central role in signal transduction associated with stress, in the skin in particular by the control of NF-κB pathways. Under normal conditions, the inhibitory protein IκB is phosphorylated by kinases, then ubiquitinated and ends up at the proteasome to be degraded. The present short review discusses recent progress in the inhibition of NF-κB activation by proteasome inhibitors prevents the degradation of protein IκB, which accumulates in the cytosol, and there by the activation of NF-κB. Moreover, would not only limit the expression of adhesion molecules and cytokines involved in metastatic processes, but also increase the sensitivity of cancer cells to apoptosis. Considering this fact, the activity of NF-κB is regulated by the phosphorylation and proteasome-dependent degradation of its inhibitor Iκb. In this scenario, the use of a proteasome inhibitor might be an effective strategy in the treatment of skin cancer with constitutive activation of NF-κB.

Quantitative ubiquitylomics reveals the ubiquitination regulation landscape in oral adenoid cystic carcinoma

Adenoid cystic carcinoma (ACC) is an extremely rare salivary gland tumor with a poor prognosis and needs attention on molecular mechanisms. Protein ubiquitination is an evolutionarily conserved post-translational modification (PTM) for substrates degradation and controls diverse cellular functions. The broad cellular function of ubiquitination network holds great promise to detect potential targets and identify respective receptors. Novel technologies are discovered for in-depth research and characterization of the precise and dynamic regulation of ubiquitylomics in multiple cellular processes during cancer initiation, progression and treatment. In the present study, 4D label-free quantitative techniques of ubiquitination proteomics were used and we identified a total of 4152 ubiquitination sites in 1993 proteins. We also performed a systematic bioinformatics analysis for differential modified proteins and peptides containing quantitative information through the comparation between oral ACC (OACC) tumor with adjacent normal tissues, as well as the identification of eight protein clusters with motif analysis. Our findings offered an important reference of potential biomarkers and effective therapeutic targets for ACC.

Integrative proteomics reveals the role of E3 ubiquitin ligase SYVN1 in hepatocellular carcinoma metastasis

Background

Tumor metastasis is a major factor for poor prognosis of hepatocellular carcinoma (HCC), but the relationship between ubiquitination and metastasis need to be studied more systematically. We analyzed the ubiquitinome of HCC in this study to have a more comprehensive insight into human HCC metastasis.

Methods

The protein ubiquitination levels in 15 HCC specimens with vascular invasion and 15 without vascular invasion were detected by ubiquitinome. Proteins with significantly different ubiquitination levels between HCCs with and without vascular invasion were used to predict E3 ubiquitin ligases associated with tumor metastasis. The topological network of protein substrates and corresponding E3 ubiquitin ligases was constructed to identify the key E3 ubiquitin ligase. Besides, the growth, migration and invasion ability of LM3 and HUH7 hepatoma cell lines with and without SYVN1 expression interference were measured by cell proliferation assay, subcutaneous tumor assay, umphal vein endothelium tube formation assay, transwell migration and invasion assays. Finally, the interacting proteins of SYVN1 were screened and verified by protein interaction omics, immunofluorescence, and immunoprecipitation. Ubiquitin levels of related protein substrates in LM3 and HUH7 cells were compared in negative control, SYVN1 knockdown, and SYVN1 overexpression groups.

Results

In this study, our whole‐cell proteomic dataset and ubiquitinomic dataset contained approximately 5600 proteins and 12,000 ubiquitinated sites. We discovered increased ubiquitinated sites with shorter ubiquitin chains during the progression of HCC metastasis. In addition, proteomic and ubiquitinomic analyses revealed that high expression of E3 ubiquitin‐protein ligase SYVN1 is related with tumor metastasis. Furthermore, we found that SYVN1 interacted with heat shock protein 90 (HSP90) and impacted the ubiquitination of eukaryotic elongation factor 2 kinase (EEF2K).

Conclusions

The ubiquitination profiles of HCC with and without vascular invasion were significantly different. SYVN1 was the most important E3 ubiquitin‐protein ligase responsible for this phenomenon, and it was related with tumor metastasis and growth. Therefore, SYVN1 might be a potential therapeutic target for HCC.

Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine

Hepatocellular carcinoma (HCC) is the most common primary cancer of the liver with high morbidity and mortality rates worldwide. Since 1963, when alpha-fetoprotein (AFP) was discovered as a first HCC serum biomarker, several other protein biomarkers have been identified and introduced into clinical practice. However, insufficient specificity and sensitivity of these biomarkers dictate the necessity of novel biomarker discovery. Remarkable advancements in integrated multiomics technologies for the identification of gene expression and protein or metabolite distribution patterns can facilitate rising to this challenge. Current multiomics technologies lead to the accumulation of a huge amount of data, which requires clustering and finding correlations between various datasets and developing predictive models for data filtering, pre-processing, and reducing dimensionality. Artificial intelligence (AI) technologies have an enormous potential to overcome accelerated data growth, complexity, and heterogeneity within and across data sources. Our review focuses on the recent progress in integrative proteomic profiling strategies and their usage in combination with machine learning and deep learning technologies for the discovery of novel biomarker candidates for HCC early diagnosis and prognosis. We discuss conventional and promising proteomic biomarkers of HCC such as AFP, lens culinaris agglutinin (LCA)-reactive L3 glycoform of AFP (AFP-L3), des-gamma-carboxyprothrombin (DCP), osteopontin (OPN), glypican-3 (GPC3), dickkopf-1 (DKK1), midkine (MDK), and squamous cell carcinoma antigen (SCCA) and highlight their functional significance including the involvement in cell signaling such as Wnt/β-catenin, PI3K/Akt, integrin αvβ3/NF-κB/HIF-1α, JAK/STAT3 and MAPK/ERK-mediated pathways dysregulated in HCC. We show that currently available computational platforms for big data analysis and AI technologies can both enhance proteomic profiling and improve imaging techniques to enhance the translational application of proteomics data into precision medicine.