Objective To investigate the differential expression of related proteins in interosseous muscle tissue between patients with familial amyotrophic lateral sclerosis（FALS） and normal individuals in a family using the isobaric tags for relative and absolute quantitation （iTRAQ） technique， to identify the pathogenic proteins for this family， and to provide a basis for treatment. Methods Interosseous muscle tissue samples were collected from all subjects in this family， and the iTRAQ technique was used to perform qualitative and quantitative analyses for all proteins and obtain the expression profile of proteins in the disease group and the normal group. The bioinformatics methods were used to identify the proteins associated with the onset of FALS. A gene ontology（GO）analysis was performed for cell components， and a classification analysis was performed for related proteins. Results A total of 453 proteins were identified by mass spectrometry. The GO analysis obtained 14 differentially expressed proteins between the disease group and the normal group （P<0.05）， and compared with the normal group，the disease group had the low expression of 5 proteins （Ratio<1） and the high expression of 9 proteins （Ratio>1）. Conclusion This study identifies 8 proteins that are highly associated with FALS， i.e.， tripartite motif-containing protein 72， NADH dehydrogenase [ubiquinone] 1 beta subcomplex subunit 1， annexin A1， decorin， glutathione peroxidase 3， collagen alpha-1 （Ⅻ） chain， collagen alpha-2 （Ⅰ） chain， and collagen type I alpha 1 isoform CRA-a. There are 6 proteins that might be associated with FALS， i.e.，26 S protease regulatory subunit 8， laminin subunit alpha-2，prolargin， fibrillin-1， myosin-8， and dermatopontin.
Proteomics

OBJECTIVE: To explore the serological characteristics and bioinformatics analysis results of 4 blood donors with RHCE*cE(281C, 282T) variant allele. METHODS: A total of 4 non-related blood donors with RHCE*cE (281C, 282T) variant allele (donors 1-4) were selected as the study objects. They donated blood at Shenzhen Blood Center from January 2022 to June 2023. The 4 blood donors were all Han. And 5 mL elbow venous blood was collected from these 4 blood donors. Regular serological assaying with 4 kinds of monoclonal antibody reagents was used for determination of the RhCcEe type. The nucleotide sequences of all 10 exons and adjacent flanking intron regions of RHCE gene in these 4 donors were analyzed by Sanger sequencing, and the full-length haplotype analysis of RHCE gene was performed by using the single-molecule real-time sequencing (SMRT) third-generation technology. DeepTMHMM software was used to analyze the structure of protein transmembrane region of wild type and variant RhCcEe protein and predict the location of amino acid substitution. The effects of mutations on RhCcEe protein function were analyzed using PolyPhen-2, SIFT and Mutation Taster bioinformatics software. Robetta and Swiss-PdbViewer v4.1.0 were used for modeling the tertiary structures of RhCcEe to analyze the difference between wild type and variant RhCcEe protein. The mutation was rated according to the standards and guidelines for the classification of genetic variants of the American College of Medical Genetics and Genomics (ACMG). This study has been approved by the Medical Ethics Committee of Shenzhen Blood Center (Approval No. SZBCMEC-2022-024). RESULTS: The RhCcEe phenotypes of the 4 blood donors were CCEweake by serological assaying. The RhE antigen were weakly expressed form 0 to 3+. The analysis of RHCE gene sequence indicated that all the 4 donors with RHCE*cE (281C, 282T) allele. The mutation caused the substitution of a single amino acid in the RhCcEe protein (p.Leu94 Pro) and the amino acid substitution was located in the transmembrane α3 chain resulted in significant changes in the 3D structure of the extracellular region of RhCcEe protein. The substitution was predicted to be "Probably damaging", "Damaging" and "Polymorphism" by PolyPhen-2, SIFT and Mutation Taster bioinformatics software. According to the guidelines of ACMG, the variant was rated to be likely pathogenic. CONCLUSION The RHCE*cE (281C, 282T) variant allele was first found in the Han Chinese population. The serological data of this allele were enriched. It provides an important guarantee for the safety of blood transfusion. Bioinformatics analysis provided evidences for further study of the structure and functions of RhCcEe protein.
Humans ; Blood Donors ; Computational Biology/methods* ; Alleles ; Rh-Hr Blood-Group System/genetics* ; Male ; Female ; Adult ; Exons

The International System for Human Cytogenomic Nomenclature (ISCN) is a standardized international nomenclature system established by the International Standing Committee on Human Cytogenomic Nomenclature (ISCN SC). It is designed for describing chromosomal or genomic abnormalities detected by commonly used genetic and genomic techniques including but not limited to karyotyping, fluorescence in situ hybridization, microarray, genome mapping, various region-specific assays, and high-throughput sequencing. With a history spanning over six decades, the ISCN was revised by the ISCN SC in 2024 and officially published in September 2024. This article provides a summary for the updates introduced in the 2024 edition of the International System for Human Cytogenomic Nomenclature.
Humans ; Terminology as Topic ; Genomics ; Genome, Human/genetics*

OBJECTIVES: To identify potential molecular targets of quercetin in the treatment of clear cell renal carcinoma (ccRCC). METHODS: The therapeutic targets of quercetin were screened from multiple databases by network pharmacology analysis, and the targets significantly correlated with ccRCC were screened from 4907 plasma proteins using a Mendelian randomization method. The drug-disease network model was constructed to screen the potential key targets. The functions of these targets were evaluated via bioinformatics analysis, and the screened targets were verified in cultured ccRCC cells. RESULTS: Network pharmacology analysis combined with Mendelian randomization identified TP53 (OR=3.325, 95% CI: 1.805-6.124, P=0.0001), ARF4 (OR=0.173, 95% CI: 0.065-0.456, P=0.0003), and DPP4 (OR=0.463, 95% CI: 0.302-0.711, P=0.0004) as the core targets in quercetin treatment of ccRCC. Bioinformatics analysis showed that TP53 was highly expressed in ccRCC, and patients with high TP53 expressions had worse survival outcomes. Molecular docking studies showed that the binding energy between quercetin and TP53 was -5.83 kcal/mol. In cultured 786-O cells, CCK-8 assay and wound healing assay showed that treatment with quercetin significantly inhibited cell proliferation and migration. Quercetin treatment also strongly suppressed the expression of TP53 at both the mRNA and protein levels in 786-O cells as shown by RT-qPCR and Western blotting. CONCLUSIONS TP53 may be the key target of quercetin in the treatment of ccRCC, which sheds light on potential molecular mechanism that mediate the therapeutic effect of quercetin.
Humans ; Quercetin/pharmacology* ; Carcinoma, Renal Cell/genetics* ; Cell Proliferation/drug effects* ; Kidney Neoplasms/genetics* ; Cell Movement/drug effects* ; Tumor Suppressor Protein p53/metabolism* ; Cell Line, Tumor ; Computational Biology

OBJECTIVES: To explore the role of oxidative stress and immune infiltration in rheumatoid arthritis (RA). METHODS: RA datasets GSE55235 (10 RA vs 10 normal samples) and GSE55457 (13 RA vs 10 normal samples) from the GEO database were merged as the test set to identify the differentially expressed genes (DEGs) in RA using R. The DEGs were intersected with oxidative stress-related genes to obtain oxidative stress-associated DEGs. KEGG and GO enrichment analyses of the DEGs were performed, and the RA-related pathways and biological processes were analyzed using GSEA. A protein-protein interaction (PPI) network was constructed using STRING and Cytoscape, and the top 10 key genes were obtained using the Degree algorithm. The validation dataset GSE1919 from GEO database was used for ROC analysis of the key genes to obtain the core genes, and their correlations with infiltrating immune cells were analyzed using CIBERSORT. The results were verified by RT-qPCR for detecting expression levels of the core genes in RA and normal joint samples. RESULTS: We identified 89 oxidative stress-associated DEGs. Enrichment analysis suggested that these DEGs were involved in the biological processes including oxidative stress, chemical stress response, reactive oxygen species response, and lipopolysaccharide response. ROC analysis showed that the 5 core genes (STAT1, MMP9, MYC, CCL5, and JUN) all had AUC values >0.7, indicating their high diagnostic sensitivity and specificity for RA. These genes were closely correlated with immune cells, particularly T cells. RT-qPCR confirmed significant differential expressions of the core genes between RA and normal samples. CONCLUSIONS Oxidative stress and diverse immune responses are features of RA, and the immune responses contribute to activation of oxidative stress. The identified core genes can potential serve as new diagnostic markers for RA.
Arthritis, Rheumatoid/genetics* ; Oxidative Stress/genetics* ; Humans ; Computational Biology ; Protein Interaction Maps ; Gene Expression Profiling ; Gene Regulatory Networks

OBJECTIVES: To explore the potential of pyrroline-5-carboxylate reductase 1 (PYCR1) as a pan-cancer biomarker and investigate its expression, function, and clinical significance in bladder cancer (BLCA). METHODS: Bioinformatics analysis was conducted to evaluate the associations of PYCR1 with prognosis, immune microenvironment remodeling, tumor mutation burden (TMB), and microsatellite instability (MSI) in cancer patients. Using the TCGA-BLCA dataset, univariate and multivariate regression analyses were performed to assess the potential of PYCR1 as an independent prognostic risk factor for BLCA, and a clinical decision model was constructed. The IMvigor210 cohort was utilized to evaluate the potential of PYCR1 for independently predicting the efficacy of immunotherapy. The pRRophetic was employed to screen candidate chemotherapeutic agents for treating BLCA with high PYCR1 expression. The CMap-XSum algorithm and molecular docking techniques were used to explore and validate small molecule inhibitors of PYCR1. RESULTS: A high expression of PYCR1 was significantly associated with poor prognosis, immune cell infiltration, TMB and MSI in various tumors (r>0.3). PYCR1 was overexpressed in BLCA, and high PYCR1 expression was closely related to poor prognosis in BLCA patients (HR: 1.14, 95% CI: 1.02-1.68, P=0.006). The IC₅₀ of the anti-cancer drugs cetuximab, 5-fluorouracil, and doxorubicin increased significantly in BLCA cell lines with high PYCR1 expressions (P<0.0001). CONCLUSIONS High PYCR1 expression is an independent risk factor for poor prognosis in BLCA patients and can serve as a significant indicator for clinical decision-making as well as a marker for predicting sensitivity to chemotherapeutic agents and the efficacy of immunotherapy.
Humans ; Urinary Bladder Neoplasms/genetics* ; Immunotherapy ; Prognosis ; Pyrroline Carboxylate Reductases/metabolism* ; Biomarkers, Tumor/genetics* ; delta-1-Pyrroline-5-Carboxylate Reductase ; Microsatellite Instability ; Tumor Microenvironment ; Mutation ; Computational Biology ; Molecular Docking Simulation

OBJECTIVES: To explore the therapeutic mechanism of Arctium lappa extract for treatment of Post-Viral Pneumonia Pulmonary Fibrosis (PPF). METHODS: The chemical constituents of Arctium lappa extracts were identified using UHPLC-Q-TOF-MS/MS. Mouse models of pulmonary fibrosis established by tracheal instillation of bleomycin were treated with Arctium lappa extract, and body weight changes were recorded and lung tissue pathology was examined using HE and Masson staining. Metabolomics analysis was used to identify the differential metabolites and the associated metabolic pathways in the treated mice. The common targets of viral pneumonia and pulmonary fibrosis were acquired from the publicly available databases, and the core targets and active constituents were screened using the protein-protein interaction (PPI) network, GO and KEGG enrichment analyses, and molecular docking, and a "gene-metabolite" regulatory network was constructed. The expressions of the core targets were detected in the lung tissues of the treated mice using Western blotting. RESULTS: Fifty-three chemical constituents were identified from Arctium lappa extract. In the mouse models of pulmonary fibrosis, treatment with Arctium lappa extract significantly improved weight loss and ameliorated lung inflammation and fibrosis. The differential metabolites in the treated mice were enriched in energy metabolism pathways involving citrate cycle, pentose phosphate pathway, glycolysis, tryptophan metabolism, glutamate metabolism and glutathione metabolism, which regulated the production of energy metabolism intermediates. Twenty-three key active compounds (mostly lignans and phenolic acids) and 82 core targets were screened, which were associated with the non-canonical Smad signaling pathways (including PI3K/AKT, HIF-1, MAPK, and Foxo) that participated in the regulation of energy metabolism. Arctium lappa extract also regulated the expressions of epithelial-mesenchymal transition (EMT)‑related proteins (fibronectin, vimentim, and Snail, etc.) and inhibited MAPK signaling pathway activation. CONCLUSIONS Preliminary findings suggest that Arctium lappa treats fibrosis by regulating metabolism to inhibit EMT and involves the modulation of non-canonical Smad signaling pathways, such as MAPK providing theoretical support for its clinical application and further research in treating PPF.
Arctium/chemistry* ; Animals ; Pulmonary Fibrosis/metabolism* ; Mice ; Metabolomics ; Network Pharmacology ; Plant Extracts/pharmacology* ; Signal Transduction ; Drugs, Chinese Herbal/pharmacology* ; Molecular Docking Simulation

OBJECTIVES: To establish a prognostic model for primary liver cancer (PLC) using bioinformatics methods. METHODS: Based on the data from 404 patients in the Cancer Genome Atlas (TCGA) database, we constructed a prognostic model integrating the differentially expressed genes, anoikis, and immune-related genes (DAIs) using univariate Cox regression and the LASSO-Cox approach. The predictive ability of the model was evaluated using Kaplan-Meier method and receiver-operating characteristic curves, and a nomogram was developed to facilitate its clinical applications. Gene set enrichment analysis (GSEA) was performed to explore the associated pathways and relationship between the DAIs and the tumor immune microenvironment, and the half-maximal inhibitory concentration (IC₅₀) of liver cancer drugs was calculated using the "pRRophetic" R package. We also detected the expression of SEMA7A in paired tumor and adjacent tissues from liver cancer patients. RESULTS: We constructed and validated a prognostic model based on 7 DAIs (NR4A3, SEMA7A, IL11, AR, BIRC5, EGF, and SPP1), and obtained consistent results in both the TCGA training cohort and GEO validation cohort (GSE14520), where the patients in the low-risk group were characterized by more favorable clinical outcomes and immune status. By integrating this prognostic signature with clinical information, a composite nomogram was generated. Somatic mutation analysis showed that TTN, TP53, and CTNNB1 mutations accounted for the largest proportion of total mutations, and the patients in the low-risk-low-TMB group had higher survival rate. Drug sensitivity analysis revealed differences in sensitivity to chemotherapeutic agents between high- and low-risk groups and between TP53 mutations and non-mutations. In clinical tissue specimens, SEMA7A expression was significantly higher in liver cancer tissues than in the adjacent tissues. CONCLUSIONS We established a new prognostic model based on DAIs for predicting clinical outcomes and therapeutic response of patients with primary liver cancer.
Humans ; Liver Neoplasms/diagnosis* ; Prognosis ; Anoikis ; Nomograms ; Computational Biology ; Tumor Microenvironment ; Semaphorins/metabolism*

OBJECTIVES: To investigate the impact of hepatitis B virus (HBV) infection on oral microbiota and metabolites in patients with metabolic dysfunction-associated fatty liver disease (MAFLD) and the underlying mechanisms. METHODS: This prospective study was conducted in 47 MAFLD patients complicated with chronic hepatitis B (CHB) and 48 MAFLD patients without CHB enrolled from November, 2023 to January, 2024. Fasting tongue coating samples were collected from the patients for analyzing microbial community structures and metabolites using high-throughput 16S rDNA sequencing and non-targeted metabolomics techniques, and their associations with clinical indicators and biological pathways were explored using correlation analysis and functional annotation. RESULTS: The levels of fasting blood glucose, total cholesterol (TC), gamma-glutamyl transferase (GGT), and severity of fatty liver were all significantly lower in MAFLD+CHB group than in MAFLD group. Microbiota analysis showed that the abundances of Patescibacteria (at the phylum level), Hydrogenophaga, and Absconditabacteriales (at the genus level) were significantly increased, while the abundance of Megasphaera was decreased in MAFLD+CHB group. The differential microbiota were significantly correlated with TC, GGT and low-density lipoprotein (r=-0.68‒0.75). Metabolomics analysis revealed that 469 metabolites (including lipids and amino acids) were upregulated and 2306 (including organic oxygen-containing compounds and phenylpropanoids) were downregulated in MAFLD+CHB group, for which KEGG enrichment analysis suggested abnormal activation of the linoleic acid metabolism and glycerophospholipid metabolism pathways. Correlation analysis between microbiota and metabolites indicated that Patescibacteria and Megasphaera, which were positively correlated with lipid metabolites and negatively with fatty acid metabolites, respectively, jointly affected glycolipid metabolism and oxidative stress pathways. CONCLUSIONS Compared to patients with MAFLD alone, MAFLD patients with concurrent chronic HBV infection showed lower levels in some lipid metabolism indicators and the degree of hepatic steatosis, accompanied by alterations in oral microbiota structure and metabolic profiles. The precise mechanisms involved require further investigation to be fully elucidated.
Humans ; Lipid Metabolism ; Prospective Studies ; Microbiota ; Hepatitis B, Chronic/microbiology* ; Male ; Female ; Adult ; Fatty Liver/microbiology* ; Middle Aged ; Mouth/microbiology* ; Metabolomics

OBJECTIVES: To analyze the molecular mechanism of Xixian Pills for treatment of rheumatoid arthritis (RA). METHODS: Forty-eight rats were randomized into 6 groups (n=8), including a normal control group, a collagen-induced arthritis (CIA) model group, 3 Xixian Pills treatment (200, 400 and 800 mg/kg) groups, and a Tripterygium glycosides tablet (TGT) treatment group. In the latter 4 groups, the rats were treated with daily gavage of Xixian Pills or TGT 2 weeks after CIA modeling for 3 consecutive weeks. The differentially expressed proteins in high-dose Xixian Pills group and the model group compared with the normal control group were screened based on the tandem mass spectrometry tag (TMT) technology, and the core targets and signaling pathways were analyzed. The immune cell infiltration and gene expression data were analyzed using ggplot2 and tidyverse packages, and the correlation coefficients between the core targets and the immune cells were calculated. RESULTS: The CIA rats showed significantly increased serum levels of TNF-α and IL-6 and lowered serum IL-10 level. Treatments with high- and medium-dose Xixian Pills and TGT all significantly reduced serum TNF‑α and IL-6 and increased IL-10 levels in CIA rats. Proteomic analysis identified 160 differential proteins between the model group and high-dose Xixian Pills group, and the core targets included CCL5, STAT1, GZMB and IL7R. The areas under the ROC curve of CCL5 and STAT1 were both greater than 0.9. Immunohistochemical and immunofluorescence staining revealed increased levels of CCL5 and STAT1 in the ankle joints of CIA rats, which were significantly decreased after treatment with Xixian Pills. CONCLUSIONS Treatment with Xixian Pills offers protection of the joints in CIA rats possibly by inhibiting joint inflammation via regulating protein expressions of CCL5 and STAT1.
Animals ; Drugs, Chinese Herbal/pharmacology* ; Rats ; Arthritis, Rheumatoid/metabolism* ; Proteomics ; Tripterygium/chemistry* ; Arthritis, Experimental/metabolism* ; Tumor Necrosis Factor-alpha/blood* ; Interleukin-10/blood* ; Interleukin-6/blood* ; Male ; Rats, Sprague-Dawley ; Signal Transduction