Nascent Proteome and Glycoproteome Reveal the Inhibition Role of ALG1 in Hepatocellular Carcinoma Cell Migration

COP9 signalosome complex is a prognostic biomarker and corresponds with immune infiltration in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is among the most common deadly tumors but still lacks specific biomarkers for diagnosis, prognosis, and treatment guidance. The COP9 signalosome (COPS) is an essential regulator of the ubiquitin conjugation pathway upregulated in various cancers. We evaluated the contributions of COPS subunits to HCC tumorigenesis and their utility for prognosis. We comprehensively evaluated the tumor expression pattern and tumorigenic functions of COPS subunits using The Cancer Genome Atlas (TCGA), The Human Protein Atlas and immunohistochemistry. Kaplan-Meier, Cox regression, ROC curve, and nomogram analyses were used to assess the predictive values of COPS subunits for clinical outcome. Expression levels of COPS subunits were significantly upregulated in HCC tissues, which predicted shorter overall survival (OS). Further, Cox regression analysis identified COPS5, COPS7B, and COPS9 as independent prognostic biomarkers for OS. High mutation rates were also found in COPS subunits. Functional network analysis indicated that COPS and neighboring genes regulate 'protein neddylation', 'protein deneddylation', and 'protein ubiquitination'. The COPS PPI included strong interactions with p53, CUL1/2/3/4, and JUN. Moreover, the correlations between COPS subunit expression levels and tumor immune cell infiltration rates were examined using TIMER, TISIDB, ssGSEA, and ESTIMATE packages. COPS subunits expression levels were positively correlated with specific tumor immune cell infiltration rates, immunoregulator expression levels, and microsatellite instability in HCC. Finally, knockout of COPS6 and COPS9 in HCC cells reduced while overexpression enhanced proliferation rate and metastasis capacity. Our study revealed that COPS potential biomarker for unfavorable HCC prognosis and indicators of immune infiltration, tumorigenicity, and metastasis.

Proteomic characterization identifies clinically relevant subgroups of soft tissue sarcoma

Soft tissue sarcoma is a broad family of mesenchymal malignancies exhibiting remarkable histological diversity. We portray the proteomic landscape of 272 soft tissue sarcomas representing 12 major subtypes. Hierarchical classification finds the similarity of proteomic features between angiosarcoma and epithelial sarcoma, and elevated expression of SHC1 in AS and ES is correlated with poor prognosis. Moreover, proteomic clustering classifies patients of soft tissue sarcoma into 3 proteomic clusters with diverse driven pathways and clinical outcomes. In the proteomic cluster featured with the high cell proliferation rate, APEX1 and NPM1 are found to promote cell proliferation and drive the progression of cancer cells. The classification based on immune signatures defines three immune subtypes with distinctive tumor microenvironments. Further analysis illustrates the potential association between immune evasion markers (PD-L1 and CD80) and tumor metastasis in soft tissue sarcoma. Overall, this analysis uncovers sarcoma-type-specific changes in proteins, providing insights about relationships of soft tissue sarcoma.

High-throughput intact Glycopeptide quantification strategy with targeted-MS (HTiGQs-target) reveals site-specific IgG N-glycopeptides as biomarkers for hepatic disorder diagnosis and staging

Liver disease is one of the leading causes of global mortality, and identifying biomarkers for diagnosing the progression of liver diseases is crucial for improving its outcomes. Targeted mass spectrometry technology is a powerful tool with unique advantages for verifying biomarker candidates and clinical applications. It is particularly useful in validating protein biomarkers with post-translational modifications, eliminating the need for site-specific antibodies. Especially, targeted mass spectrometry technique is particularly critical for translation of glycoproteins into clinical applications as there are no site-specific antibodies for N-glycosylation. Nevertheless, its limitation in analyzing only one sample per run has become apparent when dealing with a large number of clinical samples. Herein, we developed a high-throughput intact N-glycopeptides quantification strategy with targeted-MS (HTiGQs-Target), which allows the validation of 20 samples per run with an average analysis time of only 3 min per sample. We applied HTiGQs-Target in a cohort of 461 serum samples (including 120 healthy controls (HC), 127 chronic hepatitis B (CHB) cases, 106 liver cirrhosis (LC) cases, and 108 hepatocellular carcinomas (HCC) cases) and found that a panel of 10 IgG N-glycopeptides have strong clinical utility in evaluating the severity of the liver disease.

The Prognostic Significance of the TEAD4 in Hepatocellular Carcinoma

Background

Abnormal expression of genes causes tumorigenesis, tumor progression, and poor prognosis in hepatocellular carcinoma (HCC). Therefore, the aims of this study were to explore the transcription enhancer domain factor 4 (TEAD4) in patients with liver cancer and its relationship with prognosis.

Methods

HTSeq-FPKM data and corresponding clinical data of HCC patients were obtained from The Cancer Genome Atlas (TCGA). Difference in TEAD4 expression between normal and tumor and the correlation with clinical characteristics were analyzed by the chi-squared test based on UALCAN. HepG2 cell lines were used to study the effect of TEAD4 on HCC cell lines. The expression and clinical significance of TEAD4 in HCC were detected in clinical cases.

Results

The transcription and post-transcription levels of TEAD4 were higher in HCC tumors than normal illustrated different expressed transcription of TEAD4 in gender, nodal metastasis status, tumor grades, and individual cancer stages. The high TEAD4 expression was significantly associated with tumor grades. The high expression of TEAD4 was significantly correlated to shorter 2-5 years overall survival. Inhibition of TEAD4 expression in HepG2 cells resulted in significantly decreased cell proliferation and invasion.

Conclusion

TEAD4 was identified as an independent prognostic factor, and inhibition of TEAD4 expression in HepG2 cells resulted in significantly decreased cell proliferation and invasion.

Discovery of age-related early-stage glycated proteins based on deep quantitative serum glycated proteome analysis

Aging is a pressing global health issue that is linked to various diseases, such as diabetes and Alzheimer's disease. It is well known that glycation plays a pathological role in the aging process and age-related diseases. Thus, it is of great significance to discover protein glycation at an early stage for monitoring and intervention in the aging process. However, the endogenous age-related early-stage glycated proteome remains insufficiently profiled. To address this research gap, our study focuses on assessing glycated proteomics profiles in the serum of mice. We employ a robust and quantitative strategy previously developed by our team, to analyze endogenous glycated proteome in serum samples of 4 age groups of mice (10 weeks, 16 weeks, 48 weeks and 80 weeks). In total, 2959 endogenous glycated peptides corresponding to 296 serum proteins are identified from 48 runs of serum samples from 16 mice across the four age groups. By comparing these glycated peptides between adjacent age groups, we discover 49 glycated peptides from 35 proteins that show significant upregulation between the 48-week and 80-week age groups. Furthermore, we identify 10 glycated proteins (or protein groups) that are significantly upregulated only between the 48-week and 80-week age groups, including lecithin-cholesterol acyltransferase (LCAT) and apolipoprotein A-II (Apo A-II). These novel findings provide unique signatures for understanding the aging process and age-related diseases. By shedding light on the early-stage glycated proteome, our study contributes valuable insights that may have implications for future interventions and therapeutic approaches.

Unsupervised Machine Learning of MRI Radiomics Features Identifies Two Distinct Subgroups with Different Liver Function Reserve and Risks of Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma

OBJECTIVE

To identify subgroups of patients with hepatocellular carcinoma (HCC) with different liver function reserves using an unsupervised machine-learning approach on the radiomics features from preoperative gadoxetic-acid-enhanced MRIs and to evaluate their association with the risk of post-hepatectomy liver failure (PHLF).

METHODS

Clinical data from 276 consecutive HCC patients who underwent liver resections between January 2017 and March 2019 were retrospectively collected. Radiomics features were extracted from the non-tumorous liver tissue at the gadoxetic-acid-enhanced hepatobiliary phase MRI. The reproducible and non-redundant features were selected for consensus clustering analysis to detect distinct subgroups. After that, clinical variables were compared between the identified subgroups to evaluate the clustering efficacy. The liver function reserve of the subgroups was compared and the correlations between the subgroups and PHLF, postoperative complications, and length of hospital stay were evaluated.

RESULTS

A total of 107 radiomics features were extracted and 37 were selected for unsupervised clustering analysis, which identified two distinct subgroups (138 patients in each subgroup). Compared with subgroup 1, subgroup 2 had significantly more patients with older age, albumin-bilirubin grades 2 and 3, a higher indocyanine green retention rate, and a lower indocyanine green plasma disappearance rate (all p < 0.05). Subgroup 2 was also associated with a higher risk of PHLF, postoperative complications, and longer hospital stays (>18 days) than that of subgroup 1, with an odds ratio of 2.83 (95% CI: 1.58-5.23), 2.41(95% CI: 1.15-5.35), and 2.14 (95% CI: 1.32-3.47), respectively. The odds ratio of our method was similar to the albumin-bilirubin grade for postoperative complications and length of hospital stay (2.41 vs. 2.29 and 2.14 vs. 2.16, respectively), but was inferior for PHLF (2.83 vs. 4.55).

CONCLUSIONS

Based on the radiomics features of gadoxetic-acid-enhanced MRI, unsupervised clustering analysis identified two distinct subgroups with different liver function reserves and risks of PHLF in HCC patients. Future studies are required to validate our findings.