A Reference Profile of N-Glycosylation for Human Kidney and the Identification of Cell-Cell Interactions between Parietal Epithelial Cells and Capillary Endothelial Cells by Single-Cell Glycosylation-Sequencing.

BACKGROUND: N-glycosylation is one of the most common posttranslational modifications in humans, and these alterations are associated with kidney diseases. METHODS: A novel technological approach, single-cell N-acetyllactosamine sequencing (scLacNAc-seq), was applied to simultaneously detect N-glycosylation expression and the transcriptome at single-cell resolution in three human kidney tissues from zero-time biopsy. Cell clusters, glycation abundance in each cell cluster, functional enrichment analysis, cell-cell crosstalk, and pseudotime analysis were applied. RESULTS: Using scLacNAc-seq, 24,247 cells and 22 cell clusters were identified, and N-glycan abundance in each cell was obtained. Transcriptome analysis revealed a close connection between capillary endothelial cells (CapECs) and parietal epithelial cells (PECs). PECs and CapECs communicate with each other through several pairs of ligand receptors (e.g., TGFB1-EGFR, GRN-EGFR, TIMP1-FGFR2, VEGFB-FLT1, ANGPT2-TEK, and GRN-TNFRSF1A). Finally, a regulatory network of cell-cell crosstalk between PECs and CapECs was constructed, which is involved in cell development. CONCLUSIONS: We here, for the first time, constructed the glycosylation profile of 22 cell clusters in the human kidney from zero-time biopsy. Moreover, cell-cell communication between PECs and CapECs through the ligand-receptor system may play a crucial regulatory role in cell proliferation.

Multi-omics data-based analysis characterizes molecular alterations of the vesicle genes in human colorectal cancer.

The role of vesicular genes in the development of colorectal cancer (CRC) is crucial. Analyzing alterations in these genes at multi-omics can aid in understanding the molecular pathways behind colorectal carcinogenesis and identifying potential treatment targets. However, studies on the overall alteration of vesicular genes in CRC are still lacking. In this study, we aimed to investigate the relationship between vesicle genetic alterations and CRC progression. To achieve this, we analyzed molecular alterations in CRC vesicle genes at eight levels, including mRNA, protein, and epigenetic levels. Additionally, we examined CRC overall survival-related genes that were obtained from a public database. Our analysis of chromatin structural variants, DNA methylation, chromatin accessibility, and proteins (including phosphorylation, ubiquitination, and malonylation), along with RNA-seq data from the TCGA database, revealed multiple levels of alterations in CRC vesicle genes in the collected tissue samples. We progressively examined the alterations of vesicle genes in mRNA and protein levels in CRC and discovered the hub genes. Further investigation identified the probable essential transcription factors. This study contributes to a thorough knowledge of the connection between vesicle gene alterations at multiple levels and the development of CRC and offers a theoretical framework for the identification of novel treatment targets.

Analysis of proteome and post-translational modifications of 2-hydroxyisobutyrylation reveals the glycolysis pathway in oral adenoid cystic carcinoma.

PURPOSE: Oral adenoid cystic carcinoma (OACC) has high rates of both local-regional recurrence and distant metastasis. The objective of this study is to investigate the impact of Khib on OACC and its potential as a targeted therapeutic intervention. EXPERIMENTAL DESIGN: We investigated the DEPs (differentially expressed proteins) and DHMPs between OACC-T and OACC-N using LC-MS/MS-based quantitative proteomics and using several bioinformatics methods, including GO enrichment analysis, KEGG pathway analysis, subcellular localization prediction, MEA (motif enrichment analysis), and PPI (protein-protein interaction networks) to illustrate how Khib modification interfere with OACC evolution. RESULTS: Compared OACC-tumor samples (OACC-T) with the adjacent normal samples (OACC-N), there were 3243 of the DEPs and 2011 Khib sites were identified on 764 proteins (DHMPs). DEPs and DHMPs were strongly associated to glycolysis pathway. GAPDH of K254, ENO of K228, and PGK1 of K323 were modified by Khib in OACC-T. Khib may increase the catalytic efficiency to promote glycolysis pathway and favor OACC progression. CONCLUSIONS AND CLINICAL RELEVANCE: Khib may play a significant role in the mechanism of OACC progression by influencing the enzyme activity of the glycolysis pathway. These findings may provide new therapeutic options of OACC.

Corrigendum to "The novel putative methyltransferase METTL7A as one prognostic biomarker potentially associated with immune infiltration in human renal cancer".

[This corrects the article DOI: 10.1016/j.heliyon.2023.e15371.].

The novel putative methyltransferase METTL7A as one prognostic biomarker potentially associated with immune infiltration in human renal cancer.

Among urological cancers, renal cancer has the highest fatality rate. In a previous pan-cancer study of the METTL family, we observed a stronger association between the METTL family members and the risk of renal cancer compared to other cancers. Among these members, METTL7A, a potential methyltransferase, was identified as a protective factor, although its role and mechanism in renal cancer remain unclear. In this study, we utilized public databases to examine the expression of METTL7A in renal cancer tissues and normal tissues and found that METTL7A expression was much lower in renal cancer tissues. We also noticed a link between low METTL7A expression and poor prognosis for patients. According to the results of our functional enrichment analysis, METTL7A may have a role in immunological functions in renal cancer. METTL7A expression was strongly linked with the degrees of immune cell infiltration and expression of numerous immunological components. METTL7A had significantly different effects on the survival times of renal cancer patients with high or low immune infiltration. Our findings suggest that METTL7A may be used as both a prognostic biomarker and an immunological target for kidney cancer. In conclusion, our study sheds light on the importance of METTL7A in renal cancer and emphasizes the potential of targeting METTL7A as a novel therapeutic strategy for kidney cancer.

Serum metabolomics analysis reveals metabolite profile and key biomarkers of idiopathic membranous nephropathy.

Background: Idiopathic membranous nephropathy (IMN) is an organ-specific autoimmune disease with multiple and complex pathogenic mechanisms. Currently, renal biopsy is considered the gold standard for diagnosing membranous nephropathy. However, there were limitations to the renal puncture biopsy, such as the relatively high cost, longer time consuming, and the risk of invasive procedures. We investigated the profile of serum metabolites in IMN patients based on the UHPLC-QE-MS metabolomics technique for exploring the potential disease biomarkers and clinical implementation. Methods: In our research, we collected serum samples from healthy control (n = 15) and IMN patients (n = 25) to perform metabolomics analysis based on the UHPLC-QE-MS technique. Result: We identified 215 differentially expressed metabolites (DEMs) between the IMN and healthy control (HC) groups. Furthermore, these DEMs were significantly identified in histidine metabolism, arginine and proline metabolism, pyrimidine metabolism, purine metabolism, and steroid hormone biosynthesis. Several key DEMs were significantly correlated with the level of clinical parameters, such as serum albumin, IgG, UTP, and cholesterol. Among them, dehydroepiandrosterone sulfate (DHEAS) was considered the reliable diagnostic biomarker in the IMN group. There was an increased abundance of actinobacteria, phylum proteobacteria, and class gammaproteobacterial in IMN patients for host-microbiome origin analysis. Conclusion: Our study revealed the profiles of DEMs from the IMN and HC groups. The result demonstrated that there were disorders of amino acids, nucleotides, and steroids hormones metabolism in IMN patients. The down-regulation of DHEAS may be associated with the imbalance of the immune environment in IMN patients. In host-microbiome origin analysis, the gut microbiota and metabolite disturbances were present in IMN patients.

Anthocyanin improves kidney function in diabetic kidney disease by regulating amino acid metabolism.

BACKGROUND: Diabetic kidney disease (DKD) is among the most important causes for chronic kidney disease. Anthocyanins (ANT) are polyphenolic compounds present in various food and play an important role in ameliorating hyperglycemia and insulin sensitivity. However, the effects of ANT in DKD are still poorly understood. This study aimed to investigate the effect of ANT (cyanidin-3-O-glucoside [C3G]) on the renal function of DKD, and whether the anti-DKD effect of ANT is related to metabolic pathways. METHODS: To explore the role of ANT in DKD, we performed the examination of blood glucose, renal function, and histopathology. As for the mechanism, we designed the label-free quantification proteomics and nontargeted metabolomics analysis for kidney and serum. Subsequently, we revealed the anti-DKD effect of ANT through the bioinformatic analysis. RESULTS: We showed that the fasting blood glucose level (- 6.1 mmol/L, P = 0.037), perimeter of glomerular lesions (- 24.1 µm, P = 0.030), fibrosis score of glomerular (- 8.8%, P = 0.002), and kidney function (Cystatin C: - 701.4 pg/mL, P = 0.043; urine creatinine: - 701.4 mmol/L, P = 0.032) were significantly alleviated in DKD mice after ANT treatment compared to untreated in the 20th week. Further, proteins and metabolites in the kidneys of DKD mice were observed to be dramatically altered due to changes in amino acid metabolism with ANT treatment; mainly, taurine and hypotaurine metabolism pathway was upregulated (P = 0.0001, t value = 5.97). Furthermore, upregulated tryptophan metabolism (P < 0.0001, t value = 5.94) and tyrosine metabolism (P = 0.0037, t value = 2.91) pathways had effects on serum of DKD mice as responsed ANT regulating. CONCLUSIONS: Our results suggested that prevention of the progression of DKD by ANT could be related to the regulation of amino acid metabolism. The use of dietary ANT may be one of the dietary strategies to prevent and treat DKD.

NFE2L3 as a Potential Functional Gene Regulating Immune Microenvironment in Human Kidney Cancer.

With the increasing incidence and mortality of renal cancer, it is pressing to find new biomarkers and drug targets for diagnosis and treatment. However, as one negative upstream regulator of p53, the prognostic and immunological role of NFE2L3 in renal cancer is still barely known. We investigated the expression, prognostic value, and relevant pathways of NFE2L3 using the datasets from public databases, including The Cancer Genome Atlas Program (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and UALCAN. Furthermore, we analyzed the relationship between NFE2L3 expression and the immune microenvironment using distinct methods. We found that NFE2L3 was higher expressed in kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP) tissues than adjacent normal tissues. Additionally, we identified NFE2L3 as one survival-related factor for KIRC and KIRP. The enrichment analyses revealed that NFE2L3 was associated with a variety of immune-relevant pathways in KIRC and related to the infiltration ratios of 17 types of immune cells in KIRC patients. Ultimately, we demonstrated nine significantly enriched mutations, such as TP53 and MET, in NFE2L3-expression-changing groups. The elevated expression of NFE2L3 in renal cancerous tissues versus normal tissues is associated with poor outcomes in patients. Besides, NFE2L3 has a role in the regulation of the immune microenvironment in renal cancer patients. The findings of our study provide a potential prognostic biomarker and a new drug target for renal cancer.

Spatial metabolomics on liver cirrhosis to hepatocellular carcinoma progression.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the deadliest cancers and is mainly developed from chronic liver diseases such as hepatitis-B infection-associated liver cirrhosis (LC). The progression from LC to HCC makes the detection of diagnostic biomarkers to be challenging. Hence, there have been constant efforts to improve on identifying the critical and predictive changes accompanying the disease progression. METHODS: In this study, we looked to using the mass spectrometry mediated spatial metabolomics technique to simultaneous examine hundreds of metabolites in an untargeted fashion. Additionally, metabolic profiles were compared between six subregions within the HCC tissue to collect spatial information. RESULTS: Through those metabolites, altered metabolic pathways in LC and HCC were identified. Specifically, the amino acid metabolisms and the glycerophospholipid metabolisms experienced the most changes. Many of the altered metabolites and metabolic pathways were able to be connected through the urea cycle. CONCLUSIONS: The identification of the key metabolites and pathways can expand our knowledge on HCC metabolic reprogramming and help us exam potential biomarkers for earlier detection of the malignant disease progression.

Integrated computer analysis and a self-built Chinese cohort study identified GSTM2 as one survival-relevant gene in human colon cancer potentially regulating immune microenvironment.

According to a recent report by GLOBOCAN, colorectal cancer is the third most common and second most deadly cancer in 2020. In our previous proteomic study, we found that the expression of GSTM2 in colon tissues was significantly lower than that in para-cancer tissues, and its lower expression was associated with reduced overall survival rate of patients, suggesting that this gene might play a role in the occurrence of colon cancer. As a member of the detoxifying enzyme family, GSTM2 is likely to play an important role in the initiation of tumors. Whereas, the functions of GSTM2 in colon cancer are barely known. In this study, using the RNA-Seq datasets of colon cancer patients from public database (ntumor = 457, nnormal = 41), we confirmed the reduced expression of GSTM2 and its prognostic value in colon cancer. Furthermore, we used our own Chinese cohort (ntumor = 100, nnormal = 72) verified the lower GSTM2 expression in colon cancer, and also its effects on patient prognosis. Subsequently, we uncovered two potential reasons for the lower expression of GSTM2 in colon cancer tissues, including the deep deletion of GSTM2 on genome, and the up-regulation of RAD21 or SP1. Moreover, we disclosed that GSTM2 might be involved in several immune-related pathways in colon cancer, such as chemokine signaling and leukocyte transendothelial migration. Finally, we revealed that the GSTM2 expression was closely related to the immune-related scores of colon cancer and the infiltration ratios of various immune cells, suggesting that GSTM2 might regulate the development of colon cancer by modulating immune microenvironment. In conclusion, we uncovered the prognostic value of GSTM2 based on the public data and our own data, revealed its potential regulatory role in tumor immune microenvironment, and disclosed the probable reasons for its lower expression in colon cancer. The findings of our study provide a potential prognostic biomarker and drug target for clinical diagnosis and treatment of colon cancer.

Comprehensive characterization of ubiquitinome of human colorectal cancer and identification of potential survival-related ubiquitination.

BACKGROUND: According to the Global Cancer Statistics in 2020, the incidence and mortality of colorectal cancer (CRC) rank third and second among all tumors. The disturbance of ubiquitination plays an important role in the initiation and development of CRC, but the ubiquitinome of CRC cells and the survival-relevant ubiquitination are poorly understood. METHODS: The ubiquitinome of CRC patients (n = 6) was characterized using our own data sets of proteomic and ubiquitin-proteomic examinations. Then, the probable survival-relevant ubiquitination was searched based on the analyses of data sets from public databases. RESULTS: For the ubiquitinomic examination, we identified 1690 quantifiable sites and 870 quantifiable proteins. We found that the highly-ubiquitinated proteins (n ≥ 10) were specifically involved in the biological processes such as G-protein coupling, glycoprotein coupling, and antigen presentation. Also, we depicted five motif sequences frequently recognized by ubiquitin. Subsequently, we revealed that the ubiquitination content of 1172 proteins were up-regulated and 1700 proteins were down-regulated in CRC cells versus normal adjacent cells. We demonstrated that the differentially ubiquitinated proteins were relevant to the pathways including metabolism, immune regulation, and telomere maintenance. Then, integrated with the proteomic datasets from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) (n = 98), we revealed that the increased ubiquitination of FOCAD at Lys583 and Lys587 was potentially associated with patient survival. Finally, we depicted the mutation map of FOCAD and elucidated its potential functions on RNA localization and translation in CRC. CONCLUSIONS: The findings of this study described the ubiquitinome of CRC cells and identified abnormal ubiquitination(s) potentially affecting the patient survival, thereby offering new probable opportunities for clinical treatment.

A comprehensive investigation discovered the novel methyltransferase METTL24 as one presumably prognostic gene for kidney renal clear cell carcinoma potentially modulating tumor immune microenvironment.

Background: Recently, an increasing number of studies have uncovered the aberrant expression of methyltransferase-like family (METTL) plays an important role in tumorigenesis, such as METTL3 (an m6A writer). In our recent work, we discovered METTL24 expression was highly associated with the hazard ratio (HR) of kidney renal clear cell carcinoma (KIRC) compared to other tumors, implying a special function of METTL24 in KIRC carcinogenesis. Until now, the functions and mechanisms of METTL24 in KIRC have remained mostly unknown. Methods: The mRNA expression of METTL24 in KIRC was analyzed using the TIMER 2.0, GEPIA, and UALCAN databases. The immunohistochemical assay was performed to validate METTL24 expression in our self-built Chinese cohort (n tumor = 88, n normal = 85). The gene set enrichment analysis (GSEA) was used to investigate the biological processes in which METTL24 might be engaged. The Spearman analysis was used to evaluate the expression correlations between METTL24 and a range of immunological variables, and the effects of METTL24 on the infiltration levels of multiple immune cells were explored using TCGA data. The upstream transcription factors of METTL24 were screened through a multi-omics analysis. Results: METTL24 expression in KIRC tissues was significantly decreased compared to normal adjacent kidney tissues, which was associated with the lower survival rate of KIRC patients. METTL24 potentially participated in the immune-relevant biological processes such as cytokine binding, NF-kappa B binding, MHC protein complex, and interleukin-12 action. Besides, METTL24 expression was linked to a number of immune checkpoints, cytokines, chemokines, and chemokine receptors, and also correlated with the infiltration levels of 10 types of immune cells in KIRC. Meanwhile, METTL24 expression differently affected the overall survival rates (OS) of KIRC patients with high or low levels of immune infiltration. Finally, CTCF and EP300 were discovered to be the probable transcription factors of METTL24 in KIRC. Conclusion: This study revealed that METTL24 might serve as a prognostic marker in KIRC and as one immune-relevant target for clinical treatment.

Identification and Characterization of Genes Related to the Prognosis of Hepatocellular Carcinoma Based on Single-Cell Sequencing.

The heterogeneity of hepatocellular carcinoma (HCC) highlights the importance of precision therapy. In recent years, single-cell RNA sequencing has been used to reveal the expression of genes at the single-cell level and comprehensively study cell heterogeneity. This study combined big data analytics and single-cell data mining to study the influence of genes on HCC prognosis. The cells and genes closely related to the HCC were screened through single-cell RNA sequencing (71,915 cells, including 34,414 tumor cells) and big data analysis. Comprehensive bioinformatics analysis of the key genes of HCC was conducted for molecular classification and multi-dimensional correlation analyses, and a prognostic model for HCC was established. Finally, the correlation between the prognostic model and clinicopathological features was analyzed. 16,880 specific cells, screened from the single-cell expression profile matrix, were divided into 20 sub-clusters. Cell typing revealed that 97% of these cells corresponded to HCC cell lines, demonstrating the high specificity of cells derived from single-cell sequencing. 2,038 genes with high variability were obtained. The 371 HCC samples were divided into two molecular clusters. Cluster 1 (C1) was associated with tumorigenesis, high immune score, immunotherapy targets (PD-L1 and CYLA-4), high pathological stage, and poor prognosis. Cluster 2 (C2) was related to metabolic and immune function, low immune score, low pathological stage, and good prognosis. Seven differentially expressed genes (CYP3A4, NR1I2, CYP2C9, TTR, APOC3, CYP1A2, and AFP) identified between the two molecular clusters were used to construct a prognostic model. We further validated the correlation between the seven key genes and clinical features, and the established prognostic model could effectively predict HCC prognosis. Our study identified seven key genes related to HCC that were used to construct a prognostic model through single-cell sequencing and big data analytics. This study provides new insights for further research on clinical targets of HCC and new biomarkers for clinical application.

Comparing DESI-MSI and MALDI-MSI Mediated Spatial Metabolomics and Their Applications in Cancer Studies.

Metabolic heterogeneity of cancer contributes significantly to its poor treatment outcomes and prognosis. As a result, studies continue to focus on identifying new biomarkers and metabolic vulnerabilities, both of which depend on the understanding of altered metabolism in cancer. In the recent decades, the rise of mass spectrometry imaging (MSI) enables the in situ detection of large numbers of small molecules in tissues. Therefore, researchers look to using MSI-mediated spatial metabolomics to further study the altered metabolites in cancer patients. In this review, we examined the two most commonly used spatial metabolomics techniques, MALDI-MSI and DESI-MSI, and some recent highlights of their applications in cancer studies. We also described AFADESI-MSI as a recent variation from the DESI-MSI and compare it with the two major techniques. Specifically, we discussed spatial metabolomics results in four types of heterogeneous malignancies, including breast cancer, esophageal cancer, glioblastoma and lung cancer. Multiple studies have effectively classified cancer tissue subtypes using altered metabolites information. In addition, distribution trends of key metabolites such as fatty acids, high-energy phosphate compounds, and antioxidants were identified. Therefore, while the visualization of finer distribution details requires further improvement of MSI techniques, past studies have suggested spatial metabolomics to be a promising direction to study the complexity of cancer pathophysiology.

Multi-platform-based characterization of ferroptosis in human colorectal cancer.

Ferroptosis is a type of programmed cell death potentially playing an important role in colorectal cancer (CRC) development. However, comprehensive investigations toward ferroptosis in human CRC are lacking. Here, we performed multiple investigations on cancer and para-cancer tissues. We demonstrated that the changes of structural variation and chromatin accessibility in CRC were more associated with the altered mRNA expression of ferroptosis-related genes (FRGs), and the expression of CDKN2A, GPX4, ALOXE3, and LINC00336 was related to the overall survival rates. Subsequently, we revealed that CYBB and YAP1 were potentially the hub genes, and that HSF1 and STAT2 were potentially FRGs' upstream transcription factors. Finally, we depicted the crosstalk between ferroptosis and necrosis, autophagy, and apoptosis. Based on multi-dimensional analyses, we characterized ferroptosis, probable core genes, and the upstream regulators in human CRC. The findings here may improve our understanding of ferroptosis in CRC and provide new opportunities for clinical diagnosis and treatment.