OBJECTIVE: To evaluate the anti-hepatocellular carcinoma (HCC) activity of total alkaloids from Gelsemium elegans Benth. (TAG) in vivo and in vitro and to elucidate their potential mechanisms of action through transcriptomic analysis. METHODS: TAG extraction was conducted, and the primary components were quantified using high-performance liquid chromatography (HPLC). The effects of TAG (100, 150, and 200 µg/mL) on various tumor cells, including SMMC-7721, HepG2, H22, CAL27, MCF7, HT29, and HCT116, were assessed. Effects of TAG on HCC proliferation and apoptosis were detected by colony formation assays and cell stainings. Caspase-3, Bcl-2, and Bax protein levels were detected by Western blotting. In vivo, a tumor xenograft model was developed using H22 cells. Totally 40 Kunming mice were randomly assigned to model, cyclophosphamide (20 mg/kg), TAG low-dose (TAG-L, 0.5 mg/kg), and TAG high-dose (TAG-H, 1 mg/kg) groups, with 10 mice in each group. Tumor volume, body weight, and tumor weight were recorded and compared during 14-day treatment. Immune organ index were calculated. Tissue changes were oberseved by hematoxylin and eosin staining and immunohistochemistry. Additionally, transcriptomic and metabolomic analyses, as well as quatitative real-time polymerase chain reaction (RT-qPCR), were performed to detect mRNA and metabolite expressions. RESULTS: HPLC successfully identified the components of TAG extraction. Live cell imaging and analysis, along with cell viability assays, demonstrated that TAG inhibited the proliferation of SMMC-7721, HepG2, H22, CAL27, MCF7, HT29, and HCT116 cells. Colony formation assays, Hoechst 33258 staining, Rhodamine 123 staining, and Western blotting revealed that TAG not only inhibited HCC proliferation but also promoted apoptosis (P<0.05). In vivo experiments showed that TAG inhibited the growth of solid tumors in HCC in mice (P<0.05). Transcriptomic analysis and RT-qPCR indicated that the inhibition of HCC by TAG was associated with the regulation of the key gene CXCL13. CONCLUSION TAG inhibits HCC both in vivo and in vitro, with its inhibitory effect linked to the regulation of the key gene CXCL13.
Animals ; Apoptosis/drug effects* ; Liver Neoplasms/genetics* ; Carcinoma, Hepatocellular/genetics* ; Humans ; Alkaloids/therapeutic use* ; Gelsemium/chemistry* ; Cell Line, Tumor ; Cell Proliferation/drug effects* ; Mice ; Xenograft Model Antitumor Assays

OBJECTIVES: To explore the underlying pharmacological mechanisms and its potential effects of Chinese medicine herbal formula Sini Powder (SNP) on hepatocellular carcinoma (HCC). METHODS: The active components of SNP and their in vivo distribution were identified using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Construction of component-target-disease networks, protein-protein interaction network, Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and molecular docking were employed to analyze the active components and anti-HCC mechanisms of SNP. Cell viability assay and wound healing assay were utilized to confirm the effect of SNP-containing serum (2.5%, 5.0%, 10%, 20%, and 40%), isoprenaline or propranolol (both 10, 100, and 1,000 µ mol/L) on proliferation and migration of HepG 2 or Huh7 cells. Meanwhile, the effect of isoprenaline or propranolol on the β 2 adrenergic receptor (ADRB2) mRNA expression on HepG2 cells were measured by real-time quantitative reverse transcription (RT-qPCR). Mice with subcutaneous tumors were either subjected to chronic restraint stress (CRS) followed by SNP administration (364 mg/mL) or directly treated with SNP (364 mg/mL). These two parallel experiments were performed to validate the effects of SNP on stress responses. Stress-related proteins and hormones were quantified using RT-qPCR, enzyme-linked immunosorbent assay, and immunohistochemistry. Metagenomic sequencing was performed to confirm the influence of SNP on the gut microbiota in the tumor-bearing CRS mice. RESULTS: The distribution of the 12 active components of SNP was confirmed in various tissues and feces. Network pharmacology analysis confirmed the anti-HCC effects of the 5 active components. The potential anti-HCC mechanisms of SNP may involve the epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase Src (SRC) and signal transducer and activator of transcription 3 (STAT3) pathways. SNP-containing serum inhibited the proliferation of HepG2 and Huh7 cells at concentrations of 2.5% and 5.0%, respectively, after 24 h of treatment. Furthermore, SNP suppressed tumor progression in tumor-bearing mice exposed to CRS. SNP treatment also downregulated the expressions of stress-related proteins and pro-inflammatory cytokines, primarily by modulating the gut microbiota. Specifically, the abundance of Alistipes and Prevotella, which belong to the phylum Bacteroidetes, increased in the SNP-treated group, whereas Lachnospira, in the phylum Firmicutes, decreased. CONCLUSION SNP can combat HCC by alleviating stress responses through the regulation of gut microbiota.
Animals ; Gastrointestinal Microbiome/drug effects* ; Liver Neoplasms/microbiology* ; Carcinoma, Hepatocellular/microbiology* ; Humans ; Drugs, Chinese Herbal/therapeutic use* ; Powders ; Cell Proliferation/drug effects* ; Mice ; Molecular Docking Simulation ; Cell Line, Tumor ; Hep G2 Cells ; Receptors, Adrenergic, beta-2/genetics* ; Stress, Physiological/drug effects* ; Cell Movement/drug effects* ; Male ; Protein Interaction Maps/drug effects* ; Cell Survival/drug effects* ; Proto-Oncogene Mas

OBJECTIVES: Esophageal squamous cell carcinoma (ESCC) is characterized by complex pathogenesis and poor prognosis. In recent years, epithelial-mesenchymal transition (EMT) in tumor initiation and progression has attracted increasing attention. Enhancer of zeste homolog 2 (EZH2), which is aberrantly expressed in various tumors, may be closely related to the EMT process. This study aims to examine the expression and correlation of EZH2 and EMT markers in ESCC cells and tissues, evaluate the effects of EZH2 knockdown on ESCC cell proliferation, invasion, and migration, and explore how EZH2 contributes to the malignant biological behavior of ESCC. METHODS: Bioinformatics analyses were used to assess EZH2 expression levels in ESCC. Small interfering RNA was used to knock down EZH2 in ESCC cell lines EC109 and EC9706. Cell proliferation, invasion, and migration were evaluated using cell counting kit-8 (CCK-8), wound healing, and Transwell assays. Protein and mRNA expression levels of EZH2, E-cadherin (E-cad), and vimentin (Vim) were detected by Western blotting and real time fluorogenic quantitative PCR (RT-qPCR), respectively. Immunohistochemical (IHC) staining was performed on 70 ESCC tissue samples and 40 paired adjacent normal tissues collected from the First Affiliated Hospital of Shihezi University between 2010 and 2016 to assess the expression of EZH2, E-cad, and Vim, and to analyze their associations with clinicopathological feature and patient prognosis. RESULTS: Bioinformatics analysis showed that EZH2 was highly expressed in ESCC (P<0.001), and high EZH2 expression was associated with worse prognosis (P<0.001). CCK-8, wound healing, and Transwell assays demonstrated that EZH2 knockdown significantly suppressed the proliferation, invasion, and migration of ESCC cells (P<0.001). In addition, Vim expression was significantly reduced, while E-cad expression was significantly increased at both protein and mRNA levels in EZH2-silenced cells (all P<0.05). IHC staining analysis revealed higher expression of EZH2 and Vim and lower expression of E-cad in ESCC tissues compared to adjacent normal tissues. Kaplan-Meier survival analysis showed that low expression of EZH2 and Vim and high expression of E-cad were associated with longer survival (all P<0.05). CONCLUSIONS EZH2 promotes malignant biological behavior in ESCC by mediating EMT. Elevated EZH2 expression is associated with poor prognosis in ESCC patients.
Humans ; Enhancer of Zeste Homolog 2 Protein/physiology* ; Esophageal Squamous Cell Carcinoma/pathology* ; Epithelial-Mesenchymal Transition/genetics* ; Esophageal Neoplasms/metabolism* ; Cell Proliferation ; Cell Line, Tumor ; Cell Movement ; Cadherins/genetics* ; Vimentin/genetics* ; Male ; Female ; Middle Aged ; Neoplasm Invasiveness ; Prognosis ; RNA, Small Interfering/genetics* ; Gene Expression Regulation, Neoplastic

OBJECTIVES: Hepatocellular carcinoma is one of the most common primary malignant tumors with the third highest mortality rate worldwide. This study aims to identify key genes associated with hepatocellular carcinoma prognosis using the Gene Expression Omnibus (GEO) database and provide a theoretical basis for discovering novel prognostic biomarkers for hepatocellular carcinoma. METHODS: Hepatocellular carcinoma-related datasets were retrieved from the GEO database. Differentially expressed genes (DEGs) were identified using the GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and key genes were identified using Cytoscape software. The University of Alabama at Birmingham Cancer Data Analysis Resource (UALCAN) was used to analyze the expression levels of key genes in normal and hepatocellular carcinoma tissues, as well as their associations with pathological grade, clinical stage, and patient survival. The Human Protein Atlas (THPA) was used to further validate the impact of key genes on overall survival. Expression levels of key genes in the blood of hepatocellular carcinoma patients were evaluated using the expression atlas of blood-based biomarkers in the early diagnosis of cancers (BBCancer). RESULTS: A total of 78 DEGs were identified from the GEO database. GO and KEGG analyses indicated that these genes may contribute to hepatocellular carcinoma progression by promoting cell division and regulating protein kinase activity. Sixteen key genes were screened via Cytoscape and validated using UALCAN and THPA. These genes were overexpressed in hepatocellular carcinoma tissues and were associated with disease progression and poor prognosis. Finally, BBCancer analysis showed that ASPM and NCAPG were also elevated in the blood of hepatocellular carcinoma patients. CONCLUSIONS This study identified 16 key genes as potential prognostic biomarkers for hepatocellular carcinoma, among which ASPM and NCAPG may serve as promising blood-based markers for hepatocellular carcinoma.
Humans ; Carcinoma, Hepatocellular/mortality* ; Liver Neoplasms/pathology* ; Prognosis ; Computational Biology/methods* ; Protein Interaction Maps/genetics* ; Biomarkers, Tumor/genetics* ; Gene Expression Regulation, Neoplastic ; Gene Expression Profiling ; Gene Ontology ; Databases, Genetic

Currently, research on N⁶-methyladenine (m⁶A) is extensive in the field of oncology, while studies involving m⁶A and skin diseases remain relatively limited. Based on existing reports, we searched PubMed and Web of Science for literature related to m⁶A and dermatological conditions. Analysis of citation counts and journal impact factors revealed a significant upward trend in the volume of m⁶A-related research. Term frequency analysis of titles and abstracts indicated that studies mainly focus on skin tumors and inflammatory or immune-related skin diseases, particularly melanoma, psoriasis, and skin development. Transcriptomic data from the Gene Expression Omnibus (GEO) were analyzed, revealing differential expression of m⁶A-related genes in 4 types of skin tumors (including squamous cell carcinoma and basal cell carcinoma) as well as in inflammatory skin diseases such as psoriasis and atopic dermatitis, and potential mechanisms of action were also explored. Findings suggest that m⁶A modifications exhibit heterogeneity between neoplastic and non-neoplastic skin diseases. However, the regulatory mechanisms of m⁶A dynamic modifications on key genes involved in dermatological disorders remain unclear and warrant further investigation.
Humans ; Skin Neoplasms/metabolism* ; Skin Diseases/metabolism* ; Adenosine/genetics* ; Psoriasis/genetics* ; Carcinoma, Squamous Cell/genetics* ; Carcinoma, Basal Cell/genetics* ; Melanoma/genetics*

OBJECTIVES: Non-small cell lung cancer (NSCLC) is associated with poor prognosis, with 30% of patients diagnosed at an advanced stage. Mutations in the EGFR and KRAS genes are important prognostic factors for NSCLC, and targeted therapies can significantly improve survival in these patients. Although tissue biopsy remains the gold standard for detecting gene mutations, it has limitations, including invasiveness, sampling errors due to tumor heterogeneity, and poor reproducibility. This study aims to develop machine learning models based on radiomic features to predict EGFR and KRAS gene mutation status in NSCLC patients, thereby providing a reference for precision oncology. METHODS: Imaging and mutation data from eligible NSCLC patients were obtained from the publicly available Lung-PET-CT-Dx dataset in The Cancer Imaging Archive (TCIA). A three-dimensional-convolutional neural network (3D-CNN) was used to extract imaging features from the regions of interest (ROI). The LightGBM algorithm was employed to build classification models for predicting EGFR and KRAS gene mutation status. Model performance was evaluated using 5-fold cross-validation, with receiver operator characteristic (ROC) curves, area under the curve (AUC), accuracy, sensitivity, and specificity used for validation. RESULTS: The models effectively predicted EGFR and KRAS mutations in NSCLC patients, achieving an AUC of 0.95 for EGFR mutations and 0.90 for KRAS. The models also demonstrated high accuracy (EGFR 89.66%; KRAS 87.10%), sensitivity (EGFR 93.33%; KRAS 87.50%), and specificity (EGFR 85.71%; KRAS 86.67%). CONCLUSIONS A radiogenomics-machine learning predictive model can serve as a non-invasive tool for anticipating EGFR and KRAS gene mutation status in NSCLC patients.
Humans ; Carcinoma, Non-Small-Cell Lung/diagnostic imaging* ; Lung Neoplasms/diagnostic imaging* ; Mutation ; Proto-Oncogene Proteins p21(ras)/genetics* ; ErbB Receptors/genetics* ; Machine Learning ; Positron Emission Tomography Computed Tomography ; Female ; Male ; Neural Networks, Computer ; Middle Aged ; Aged

Nasopharyngeal carcinoma（NPC） is a distinct type of head and neck cancer closely associated with Epstein-Barr virus（EBV） infection and exhibits significant geographic variations in its incidence. Despite recent advancements in radiotherapy techniques and precision medicine for NPC, the overall survival rate remains unsatisfactory due to tumor metastasis, recurrence, and drug resistance. Single-cell RNA sequencing（scRNA-seq） is an emerging technology that allows for the analysis of gene expression at single-cell resolution, providing a clearer understanding of tumor cell subpopulations, the evolutionary trajectory of tumor cells, and the functional roles and interactions of cells within the tumor microenvironment. This provides new ideas for the development of precision medicine in NPC. Here, we review the applications of scRNA-seq in exploring the mechanisms of NPC pathogenesis, tumor heterogeneity, the tumor microenvironment, drug resistance, and therapeutic response.
Humans ; Nasopharyngeal Neoplasms/genetics* ; Tumor Microenvironment ; Nasopharyngeal Carcinoma ; Single-Cell Analysis ; Sequence Analysis, RNA ; Precision Medicine ; Drug Resistance, Neoplasm ; Epstein-Barr Virus Infections ; Herpesvirus 4, Human ; Single-Cell Gene Expression Analysis

Objective:Proteins are closely associated with the development, progression, and immunotherapy of head and neck squamous cell carcinoma（HNSCC）. However, few clinical models utilize proteomics to predict prognosis and immunotherapy efficacy. In this study, we developed a protein prognostic model（PPM） to stratify survival outcomes and differential immunotherapy responses in HNSCC patients. Methods:Based on proteomic profiling, we constructed a PPM comprising 11 protein markers. Patients were classified into high-and low-risk groups according to PPM scores. The prognostic value of risk scores was evaluated using Cox regression analysis, and predictive accuracy was assessed via time-dependent receiver operating characteristic（ROC） curves. Additionally, we analyzed treatment responses to PD1/CTLA4 immunotherapy in PD1-or CTLA4-positive patients across risk groups. Results:Cox regression confirmed the risk score as an independent prognostic factor（HR=1.161, 95%CI 1.112-1.213, P<0.001）, with high-risk patients exhibiting significantly poorer survival than low-risk counterparts. The model demonstrated robust predictive accuracy, with 1-year and 3-year time-dependent ROC areas under the curve（AUC） of 0.713 and 0.707, respectively. In PD1/CTLA4-positive subgroups, low-risk patients showed superior immunotherapy responses compared to high-risk patients. Conclusion:The PPM can provide reliable prognostic stratification and preliminary guidance for immunotherapy in HNSCC. However, further clinical studies and basic experiments are needed for further verification.
Humans ; Immunotherapy ; Squamous Cell Carcinoma of Head and Neck/therapy* ; Prognosis ; Head and Neck Neoplasms/genetics* ; Proteome ; Proteomics ; Gene Expression Profiling ; Transcriptome ; CTLA-4 Antigen ; Programmed Cell Death 1 Receptor ; Male ; Female ; Middle Aged

OBJECTIVES: To investigate the clinical significance of SLC1A5 overexpression in pan-cancer and its mechanism for promoting hepatocellular carcinoma (HCC) progression. METHODS: We analyzed the correlation of SLC1A5 expression with clinical stage, lymph node metastasis and prognosis in pan-cancer using TCGA and ICGC datasets and explored its association with immune cell infiltration using EPIC, CIBERSORT, and TIMER algorithms. In HCC cell lines, the effects of lentivirus-mediated SLC1A5 overexpression or RNA interference on cell proliferation were examined using CCK-8 assay, and the growth of HCC cell xenografts overexpressing SLC1A5 was observed in nude mice. The effects of SLC1A5 overexpression or silencing in HCC cells on macrophage polarization were evaluated in a cell co-culture system. RESULTS: SLC1A5 was mainly localized on cell membrane and was highly expressed in most cancers in association with clinical stage, lymph node metastasis and poor prognosis. SLC1A5 expression was positively correlated with immunity score in 13 cancer types, especially in low-grade glioma (LGG), LIHC and thyroid cancer. SLC1A5 was positively correlated with macrophage infiltration level in LGG and LIHC but negatively correlated with macrophage infiltration in 5 cancers including lung squamous carcinoma, pancreatic carcinoma, and gastric carcinoma. Patients with SLC1A5 overexpression and high level of M2 macrophage infiltration had the worst survival outcomes. SLC1A5 was correlated with immunosuppression-related genes, cytokines, and cytokine receptors, which was the most obvious in LGG and LIHC. SLC1A5 was highly expressed in different HCC cell lines, and its overexpression promoted HCC cell proliferation both in vitro and in nude mice. In the cell co-culture experiment, SLC1A5 was positively correlated with the molecular markers of M2 polarization of macrophages, and its overexpression strongly promoted M2 polarization of the macrophages and inhibited T cell secretion of IFN-γ. CONCLUSIONS SLC1A5 expression level is correlated with clinical stage, lymph node metastasis, prognosis, and immune cell infiltration in most cancers, and its overexpression promotes HCC progression by inhibiting T-cell function via promoting M2 polarization of macrophages.
Humans ; Carcinoma, Hepatocellular/metabolism* ; Liver Neoplasms/metabolism* ; Animals ; Macrophages/cytology* ; Disease Progression ; Cell Line, Tumor ; Mice ; Amino Acid Transport System ASC/genetics* ; Cell Proliferation ; Lymphatic Metastasis ; Mice, Nude ; Prognosis ; Minor Histocompatibility Antigens

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