α-1,2-Mannosidase MAN1C1 Inhibits Proliferation and Invasion of Clear Cell Renal Cell Carcinoma

Integrated glycoproteomic characterization of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC), a common form of RCC, is responsible for the high mortality rate of kidney cancer. Dysregulations of glycoproteins have been shown to associate with ccRCC. However, the molecular mechanism has not been well characterized. Here, a comprehensive glycoproteomic analysis is conducted using 103 tumors and 80 paired normal adjacent tissues. Altered glycosylation enzymes and corresponding protein glycosylation are observed, while two of the major ccRCC mutations, BAP1 and PBRM1, show distinct glycosylation profiles. Additionally, inter-tumor heterogeneity and cross-correlation between glycosylation and phosphorylation are observed. The relation of glycoproteomic features to genomic, transcriptomic, proteomic, and phosphoproteomic changes shows the role of glycosylation in ccRCC development with potential for therapeutic interventions. This study reports a large-scale tandem mass tag (TMT)-based quantitative glycoproteomic analysis of ccRCC that can serve as a valuable resource for the community.

Cuproptosis-related gene FDX1 as a prognostic biomarker for kidney renal clear cell carcinoma correlates with immune checkpoints and immune cell infiltration

Background: Kidney renal clear cell carcinoma (KIRC) is not sensitive to radiotherapy and chemotherapy, and only some KIRC patients can benefit from immunotherapy and targeted therapy. Cuproptosis is a new mechanism of cell death, which is closely related to tumor progression, prognosis and immunity. The identification of prognostic markers related to cuproptosis in KIRC may provide targets for treatment and improve the prognosis of KIRC patients. Methods: Ten cuproptosis-related genes were analyzed for differential expression in KIRC-TCGA and a prognostic model was constructed. Nomogram diagnostic model was used to screen independent prognostic molecules. The screened molecules were verified in multiple datasets (GSE36895 and GSE53757), and in KIRC tumor tissues by RT-PCR and immunohistochemistry (IHC). Clinical correlation of cuproptosis-related independent prognostic molecules was analyzed. According to the molecular expression, the two groups were divided into high and low expression groups, and the differences of immune checkpoint and tumor infiltrating lymphocytes (TILs) between the two groups were compared by EPIC algorithm. The potential Immune checkpoint blocking (ICB) response of high and low expression groups was predicted by the "TIDE" algorithm. Results: FDX1 and DLAT were protective factors, while CDKN2A was a risk factor. FDX1 was an independent prognostic molecule by Nomogram, and low expressed in tumor tissues compared with adjacent tissues (p < 0.05). FDX1 was positively correlated with CD274, HAVCR2, PDCD1LG2, and negatively correlated with CTLA4, LAG3, and PDCD1. The TIDE score of low-FDX1 group was higher than that of high-FDX1 group. The abundance of CD4⁺ T cells, CD8⁺ T cells and Endothelial cells in FDX1-low group was lower than that in FDX1-high group (p < 0.05). Conclusion: FDX1, as a key cuproptosis-related gene, was also an independent prognostic molecule of KIRC. FDX1 might become an interesting biomarker and potential therapeutic target for KIRC.

Glycosylation in Renal Cell Carcinoma: Mechanisms and Clinical Implications

Renal cell carcinoma (RCC) is one of the most prevalent malignant tumors of the urinary system, accounting for around 2% of all cancer diagnoses and deaths worldwide. Clear cell RCC (ccRCC) is the most prevalent and aggressive histology with an unfavorable prognosis and inadequate treatment. Patients' progression-free survival is considerably improved by surgery; however, 30% of patients develop metastases following surgery. Identifying novel targets and molecular markers for RCC prognostic detection is crucial for more accurate clinical diagnosis and therapy. Glycosylation is a critical post-translational modification (PMT) for cancer cell growth, migration, and invasion, involving the transfer of glycosyl moieties to specific amino acid residues in proteins to form glycosidic bonds through the activity of glycosyltransferases. Most cancers, including RCC, undergo glycosylation changes such as branching, sialylation, and fucosylation. In this review, we discuss the latest findings on the significance of aberrant glycans in the initiation, development, and progression of RCC. The potential biomarkers of altered glycans for the diagnosis and their implications in RCC have been further highlighted.

Molecular Characterization, Tumor Microenvironment Association, and Drug Susceptibility of DNA Methylation-Driven Genes in Renal Cell Carcinoma

Accumulating evidence suggests that DNA methylation has essential roles in the development of renal cell carcinoma (RCC). Aberrant DNA methylation acts as a vital role in RCC progression through regulating the gene expression, yet little is known about the role of methylation and its association with prognosis in RCC. The purpose of this study is to explore the DNA methylation-driven genes for establishing prognostic-related molecular clusters and providing a basis for survival prediction. In this study, 5,198 differentially expressed genes (DEGs) and 270 DNA methylation-driven genes were selected to obtain 146 differentially expressed DNA methylation-driven genes (DEMDGs). Two clusters were distinguished by consensus clustering using 146 DEMDGs. We further evaluated the immune status of two clusters and selected 106 DEGs in cluster 1. Cluster-based immune status analysis and functional enrichment analysis of 106 DEGs provide new insights for the development of RCC. To predict the prognosis of patients with RCC, a prognostic model based on eight DEMDGs was constructed. The patients were divided into high-risk groups and low-risk groups based on their risk scores. The predictive nomogram and the web-based survival rate calculator (http://127.0.0.1:3496) were built to validate the predictive accuracy of the prognostic model. Gene set enrichment analysis was performed to annotate the signaling pathways in which the genes are enriched. The correlation of the risk score with clinical features, immune status, and drug susceptibility was also evaluated. These results suggested that the prognostic model might be a promising prognostic tool for RCC and might facilitate the management of patients with RCC.

Integrative Analysis of Epigenome and Transcriptome Data Reveals Aberrantly Methylated Promoters and Enhancers in Hepatocellular Carcinoma

DNA methylation is a key transcription regulator, whose aberration was ubiquitous and important in most cancers including hepatocellular carcinoma (HCC). Whole-genome bisulfite sequencing (WGBS) was conducted for comparison of DNA methylation in tumor and adjacent tissues from 33 HCC patients, accompanying RNA-seq to determine differentially methylated region-associated, differentially expressed genes (DMR-DEGs), which were independently replicated in the TCGA-LIHC cohort and experimentally validated via 5-aza-2-deoxycytidine (5-azadC) demethylation. A total of 9,867,700 CpG sites showed significantly differential methylation in HCC. Integrations of mRNA-seq, histone ChIP-seq, and WGBS data identified 611 high-confidence DMR-DEGs. Enrichment analysis demonstrated activation of multiple molecular pathways related to cell cycle and DNA repair, accompanying repression of several critical metabolism pathways such as tyrosine and monocarboxylic acid metabolism. In TCGA-LIHC, we replicated about 53% of identified DMR-DEGs and highlighted the prognostic significance of combinations of methylation and expression of nine DMR-DEGs, which were more efficient prognostic biomarkers than considering either type of data alone. Finally, we validated 22/23 (95.7%) DMR-DEGs in 5-azadC-treated LO2 and/or HepG2 cells. In conclusion, integration of epigenome and transcriptome data depicted activation of multiple pivotal cell cycle-related pathways and repression of several metabolic pathways triggered by aberrant DNA methylation of promoters and enhancers in HCC.

Trends in oligomannosylation and α1,2-mannosidase expression in human cancers

Aberrant protein glycosylation is a prominent cancer feature. While many tumour-associated glycoepitopes have been reported, advances in glycoanalytics continue to uncover new associations between glycosylation and cancer. Guided by a comprehensive literature survey suggesting that oligomannosylation (Man_5–9 GlcNAc₂) is a widespread and often regulated glycosignature in human cancers, we here revisit a valuable compilation of nearly 500 porous graphitized carbon LC-MS/MS N-glycomics datasets acquired across 11 human cancer types to systematically test for oligomannose-cancer associations. Firstly, the quantitative glycomics data obtained across 34 cancerous cell lines demonstrated that oligomannosylation is a pan-cancer feature spanning in a wide abundance range. In keeping with literature, our quantitative glycomics data of tumour and matching control tissues and new MALDI-MS imaging data of tissue microarrays showed a strong cancer-associated elevation of oligomannosylation in both basal cell (p = 1.78 × 10^–12) and squamous cell (p = 1.23 × 10^–11) skin cancer and colorectal cancer (p = 8.0 × 10^–4). The glycomics data also indicated that some cancer types including gastric and liver cancer exhibit unchanged or reduced oligomannose levels, observations also supported by literature and MALDI-MS imaging data. Finally, expression data from public cancer repositories indicated that several α1,2-mannosidases are regulated in tumour tissues suggesting that these glycan-processing enzymes may contribute to the cancer-associated modulation of oligomannosylation. This omics-centric study has compiled robust glycomics and enzyme expression data revealing interesting molecular trends that open avenues to better understand the role of oligomannosylation in human cancers.

The plasma exosomal miR-1180-3p serves as a novel potential diagnostic marker for cutaneous melanoma

Background

Exosomes are a promising tool in disease detection because they are noninvasive, cost-effective, sensitive and stable in body fluids. MicroRNAs (miRNAs) are the main exosomal component and participate in tumor development. However, the exosomal miRNA profile among Asian melanoma patients remains unclear.

Methods

Exosomal miRNAs from the plasma of melanoma patients (n = 20) and healthy individuals (n = 20) were isolated and subjected to small RNA sequencing. Real-time PCR was performed to identify the differential miRNAs and to determine the diagnostic efficiency. Proliferation, scratch and Transwell assays were performed to detect the biological behavior of melanoma cells.

Results

Exosomal miRNA profiling revealed decreased miR-1180-3p expression as a potential diagnostic marker of melanoma. The validation group of melanoma patients (n = 28) and controls (n = 28) confirmed the diagnostic efficiency of miR-1180-3p. The level of miR-1180-3p in melanoma cells was lower than that in melanocytes. Accordingly, the level of miR-1180-3p was negatively associated with the proliferation, migration and invasion of melanoma cells. Functional analysis and target gene prediction found that ST3GAL4 was a potential target and highly expressed in melanoma tissues and was negatively regulated by miR-1180-3p. Knockdown of ST3GAL4 hindered the malignant phenotype of melanoma cells.

Conclusions

This study indicates that reduced exosomal miR-1180-3p in melanoma patient plasma is a promising diagnostic marker and provides novel insight into melanoma development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02164-8.

Identification of serum biomarkers to predict pemetrexed/platinum chemotherapy efficacy for advanced lung adenocarcinoma patients by data-independent acquisition (DIA) mass spectrometry analysis with parallel reaction monitoring (PRM) verification

Background

Pemetrexed/platinum chemotherapy has been the standard chemotherapy regimen for lung adenocarcinoma patients, but the efficacy varies considerably.

Methods

To discover new serum biomarkers to predict the efficacy of pemetrexed/platinum chemotherapy, we analyzed 20 serum samples from advanced lung adenocarcinoma patients who received pemetrexed/platinum chemotherapy with the data-independent acquisition (DIA) quantitative mass spectrometry (MS).

Results

The 20 patients were categorized as “good response” [12 patients achieving partial response (PR)] and “poor response” [8 patients with progressive disease (PD)] groups. Altogether 23 significantly different expressed proteins were identified, which had relative ratios higher than 1.2 or lower than –0.83, with 7 proteins having an area under the curve (AUC) above 0.8. To further validate the DIA results, we used the parallel reaction monitoring (PRM) method to examine 16 candidate serum biomarkers in the study cohort of 20 patients and another cohort of 22 advanced lung adenocarcinoma patients (16 PR and 6 PD). Quantitative validation using PRM correlated well with the DIA results, and 10 promising proteins exhibited a similar up- or downregulation. It is worth noting that glutathione peroxidase 3 (GPX3) exhibits significant upregulation in the poor response group compared with the good response group, which was validated by both DIA and PRM methods.

Conclusions

Our study confirmed that combined DIA MS and PRM approaches were effective in identifying serum predictive biomarkers for advanced lung adenocarcinoma patients. Further studies are needed to explore the potential biological mechanism underlying these biomarkers.

Golgi α1,2-mannosidase I induces clustering and compartmentalization of CD147 during epithelial cell migration

CD147 is a widely expressed matrix metalloproteinase inducer involved in the regulation of cell migration. The high glycosylation and ability to undergo oligomerization have been linked to CD147 function, yet there is limited understanding on the molecular mechanisms behind these processes. The current study demonstrates that the expression of Golgi α1,2-mannosidase I is key to maintaining the cell surface organization of CD147 during cell migration. Using an in vitro model of stratified human corneal epithelial wound healing, we show that CD147 is clustered within lateral plasma membranes at the leading edge of adjacent migrating cells. This localization correlates with a surge in matrix metalloproteinase activity and an increase in the expression of α1,2-mannosidase subtype IC (MAN1C1). Global inhibition of α1,2-mannosidase I activity with deoxymannojirimycin markedly attenuates the glycosylation of CD147 and disrupts its surface distribution at the leading edge, concomitantly reducing the expression of matrix metalloproteinase-9. Likewise, treatment with deoxymannojirimycin or siRNA-mediated knockdown of MAN1C1 impairs the ability of the carbohydrate-binding protein galectin-3 to stimulate CD147 clustering in unwounded cells. We conclude that the mannose-trimming activity of α1,2-mannosidase I coordinates the clustering and compartmentalization of CD147 that follows an epithelial injury.

Identification of DNA methylation patterns and biomarkers for clear-cell renal cell carcinoma by multi-omics data analysis

Background

Tumorigenesis is highly heterogeneous, and using clinicopathological signatures only is not enough to effectively distinguish clear cell renal cell carcinoma (ccRCC) and improve risk stratification of patients. DNA methylation (DNAm) with the stability and reversibility often occurs in the early stage of tumorigenesis. Disorders of transcription and metabolism are also an important molecular mechanisms of tumorigenesis. Therefore, it is necessary to identify effective biomarkers involved in tumorigenesis through multi-omics analysis, and these biomarkers also provide new potential therapeutic targets.

Method

The discovery stage involved 160 pairs of ccRCC and matched normal tissues for investigation of DNAm and biomarkers as well as 318 cases of ccRCC including clinical signatures. Correlation analysis of epigenetic, transcriptomic and metabolomic data revealed the connection and discordance among multi-omics and the deregulated functional modules. Diagnostic or prognostic biomarkers were obtained by the correlation analysis, the Least Absolute Shrinkage and Selection Operator (LASSO) and the LASSO-Cox methods. Two classifiers were established based on random forest (RF) and LASSO-Cox algorithms in training datasets. Seven independent datasets were used to evaluate robustness and universality. The molecular biological function of biomarkers were investigated using DAVID and GeneMANIA.

Results

Based on multi-omics analysis, the epigenetic measurements uniquely identified DNAm dysregulation of cellular mechanisms resulting in transcriptomic alterations, including cell proliferation, immune response and inflammation. Combination of the gene co-expression network and metabolic network identified 134 CpG sites (CpGs) as potential biomarkers. Based on the LASSO and RF algorithms, five CpGs were obtained to build a diagnostic classifierwith better classification performance (AUC > 99%). A eight-CpG-based prognostic classifier was obtained to improve risk stratification (hazard ratio (HR) > 4; log-rank test, p-value < 0.01). Based on independent datasets and seven additional cancers, the diagnostic and prognostic classifiers also had better robustness and stability. The molecular biological function of genes with abnormal methylation were significantly associated with glycolysis/gluconeogenesis and signal transduction.

Conclusion

The present study provides a comprehensive analysis of ccRCC using multi-omics data. These findings indicated that multi-omics analysis could identify some novel epigenetic factors, which were the most important causes of advanced cancer and poor clinical prognosis. Diagnostic and prognostic biomarkers were identified, which provided a promising avenue to develop effective therapies for ccRCC.

A potential role of TLR2 in xenograft rejection of porcine iliac endothelial cells: An in vitro study

BACKGROUND

Porcine vascular endothelial cells are a major participant in xenograft rejection. The Toll-like receptor 2 (TLR2) pathway plays an important role in both innate and adaptive immunity. The specific role of TLR2 in the response to a xenograft has not been reported. Whether the TLR2 pathway in pig vascular endothelial cells is involved in acute rejection needs to be investigated, and the mechanism is explored.

METHODS

We used a modified antibody-dependent complement-mediated cytotoxicity (ADCC) assay to conduct in vitro experiments. In porcine iliac artery endothelial cells (PIECs), siRNA was used to knock down the expression of TLR2, CXCL8, and CCL2. The effect of human serum or inactivated human serum on the expression of TLR2 was analyzed by real-time PCR and Western blotting, and transwell assays were used to assess the chemotactic efficiency of PIECs on human monocyte-macrophages (THP-1 cells) and human neutrophils. The downstream signaling pathways activated by human serum were detected by Western blotting, and the regulation of proinflammatory chemokines and cytokines by TLR2 signaling was assessed by real-time PCR and ELISA.

RESULTS

TLR2 was significantly upregulated in PIECs after exposure to human serum, and porcine proinflammatory chemokines, CXCL8 and CCL2, were induced, at least partially, in a TLR2-dependent pattern; the upregulated chemokines participated in the chemotaxis of human neutrophils and THP-1 cells across the species barrier.

CONCLUSIONS

(i) TLR2 is significantly upregulated in PIECs by human serum, (ii) the elevated TLR2 participates in the chemotaxis of inflammatory cells through the secretion of chemokine CCL2 and CXCL8, and (iii) blockade of TLR2 would be beneficial for xenograft survival.