Humans ; Ovarian Neoplasms/metabolism* ; Female ; Biomarkers, Tumor/metabolism* ; Mutation

Humans ; Biomarkers, Tumor/metabolism* ; Claudins/analysis* ; Consensus ; Immunohistochemistry/methods* ; Stomach Neoplasms/diagnosis*

Humans ; Ovarian Neoplasms/drug therapy* ; Folate Receptor 1/metabolism* ; Female ; Immunohistochemistry/standards* ; Consensus ; Biomarkers, Tumor/metabolism* ; Fallopian Tube Neoplasms/pathology*

Objective To explore the clinical and immunological significance of CCDC97 in hepatocellular carcinoma (HCC). Methods Clinical data and RNA sequencing results from HCC patients were retrieved from TCGA and ICGC databases. Bioinformatics analysis and in vitro experiments were performed to investigate the role of CCDC97 in HCC. Results The expression level of CCDC97 was elevated in HCC patients and HCC cells, closely associated with pathological features and prognosis. CCDC97 was identified as a novel prognostic biomarker. It is linked to the spliceosome pathway, which is significantly active in tumors and potentially promotes carcinogenesis. CCDC97 is also highly expressed in various immune cells and is associated with microenvironment. Furthermore, knocking down CCDC97 in vitro suppressed cell migration, invasion, and proliferation. Conclusion CCDC97 plays a critical role in HCC progression and the immune microenvironment, making it a potential target for prognosis and therapeutic intervention.
Humans ; Carcinoma, Hepatocellular/metabolism* ; Liver Neoplasms/metabolism* ; Tumor Microenvironment/genetics* ; Cell Movement/genetics* ; Cell Proliferation ; Prognosis ; Cell Line, Tumor ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/genetics* ; Male

Objective To investigate the clinical relevance and diagnostic or prognostic value of ST3β-galactoside α-2, 3-sialyltransferase 1 (ST3GAL1) in glioma and to confirm its role in promoting malignant phenotypes. Methods Using data from The Cancer Genome Atlas (TCGA) database, we analyzed the correlation between ST3GAL1 expression levels in glioma and clinical parameters to evaluate its diagnostic and prognostic value. The impact of ST3GAL1 on malignant phenotypes of glioma cells-including proliferation, cell cycle progression, apoptosis, and invasion was further validated through ST3GAL1 knockdown experiments. Results The expression level of ST3GAL1 was significantly higher in glioma tissues compared to healthy brain tissues and showed a strong correlation with clinical characteristics of glioma patients. Survival analysis and receiver operating characteristic (ROC) curve demonstrated that ST3GAL1 could serve as a potential diagnostic and prognostic biomarker for glioma. Knockdown of ST3GAL1 suppressed proliferation, invasion, and migration capabilities of glioma cell lines, and induced G1-phase cell cycle arrest. Conclusion ST3GAL1 promotes malignant phenotypes in glioma and plays a critical role in its malignant progression, suggesting its potential as a biomarker for glioma diagnosis and prognosis.
Humans ; Sialyltransferases/metabolism* ; Glioma/diagnosis* ; Cell Proliferation/genetics* ; Cell Line, Tumor ; Brain Neoplasms/enzymology* ; beta-Galactoside alpha-2,3-Sialyltransferase ; Disease Progression ; Prognosis ; Cell Movement/genetics* ; Apoptosis/genetics* ; Male ; Female ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/metabolism* ; Middle Aged

Objective TXN is a thioredoxin (TXN) that participates in many redox reactions and plays a crucial role in various signaling pathways. However, the role of TXN in many cancers is still unclear. The objective of this study is to investigate and visualize the diagnostic, prognostic, and immunological implications of TXN expression across various cancer types. Methods The clinical data were downloaded from the cancer genome mapping project(TCGA) database to analyze the expression level of TXN in pan cancer, and the expression level was preliminarily verified by human protein mapping (HPA)(https://www.proteinatlas.org/)database. The ESTIMATE algorithm and CIBERSORT algorithm were applied to calculate the correlation between TXN expression and immune cell infiltration. The correlation between TXN and microsatellite instability (MSI) and tumor mutation burden (TMB) was analyzed using Spearman method. Gene Set Enrichment Analysis (GSEA) is used for gene biology functional analysis and sensitivity analysis of genes to pan cancer therapeutic drugs. Results TXN is highly expressed in most malignant tumors. The high expression of TXN is associated with overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression free interval (PFI) in various cancers. Moreover, TXN expression is associated with TMB, MSI, tumor microenvironment, chemotherapy sensitivity and so on. Conclusion TXN may become a potential prognostic biomarker in pan cancer, providing strong theoretical basis for future tumor diagnosis and prognosis judgment. The retinoic acid-inducible gene-I (RIG-I)-like receptor signaling pathway, Toll-like receptor (TLR) signaling pathway, and nucleotide binding oligomerization domain (NOD)-like receptor signaling pathway may be crucial pathways through which TXN influences tumor immunity.
Humans ; Prognosis ; Neoplasms/diagnosis* ; Thioredoxins/metabolism* ; Microsatellite Instability ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/genetics* ; Mutation ; Tumor Microenvironment

BACKGROUND: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. Lung squamous cell carcinoma (LUSC) is an important pathological subtype of NSCLC. The complex immune escape mechanism limits the effectiveness of immunotherapy. Ficolin-3 (FCN3) is a crucial immunomodulatory molecule that regulates immune escape by remodeling the tumor microenvironment. However, the role of FCN3 in LUSC remains unclear. This study employed bioinformatics methods to analyze LUSC samples from The Cancer Genome Atlas (TCGA) database. The aim of this study was to explore the potential biological functions and prognostic significance of FCN3 in LUSC. METHODS: A pan-cancer analysis characterized the expression patterns and prognostic value of FCN3 across various cancer types. Simultaneously, the expression patterns of FCN3 in LUSC samples from the TCGA database and its relationship with prognosis were analyzed. The Nomogram model and somatic mutation analysis, differential expression analysis, correlation analysis, as well as Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were constructed to explore the potential mechanisms of FCN3. Additionally, immune infiltration analysis, immune escape score (TIDE), and correlation analysis of immune-related molecules were used to reveal the regulatory role of high FCN3 levels on immunity in LUSC. Furthermore, the correlation between FCN3 expression characteristics and drug sensitivity was evaluated. Finally, in vitro experiments verified the expression characteristics of FCN3 in LUSC. RESULTS: The expression level of FCN3 in LUSC tissues was significantly lower than that in normal tissues. Patients with high FCN3 expression in LUSC had a poorer prognosis compared to those with low expression. Different expression levels of FCN3 were associated with the abundance of immune cell infiltration and immune cell dysfunction. It was also linked to the expression of immune checkpoints, immune stimulatory molecules, major histocompatibility complex (MHC) class molecules, and chemotherapy drug sensitivity. CONCLUSIONS High expression of FCN3 in LUSC is associated with poor prognosis and is linked to immune cell infiltration, immune-related pathways, and immune-related molecules. FCN3 may be a potential prognostic marker and a new target for immunotherapy in LUSC.
Humans ; Lung Neoplasms/immunology* ; Immunotherapy ; Biomarkers, Tumor/metabolism* ; Prognosis ; Lectins/metabolism* ; Carcinoma, Squamous Cell/immunology* ; Ficolins ; Gene Expression Regulation, Neoplastic

BACKGROUND: Lung cancer is one of the leading causes of cancer-related mortality worldwide, with above 80% of cases be non-small cell lung cancer (NSCLC), among which lung squamous cell carcinoma (LUSC) occupies a significant proportion. Although comprehensive cancer therapies have considerably improved the overall survival of patients, patients with advanced LUSC have a poorer prognosis. Therefore, there is a need for a biomarker to predict the progress of advanced LUSC in order to improve prognosis through early diagnosis. Previous studies have shown that miRNAs are differentially expressed in lung cancer tissues and play roles as potential oncogenes or tumor suppressors. The aim of this study is to identify differentially expressed miRNAs between early-stage and advanced-stage LUSC, and to establish a set of miRNAs that can predict the progress of advanced LUSC. METHODS: Clinical data and miRNA-related data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Bioinformatic methods were applied to analyze the data. Receiver operating characteristic (ROC) curves were plotted, and various online tools were used to predict target genes, with subsequent analysis of the potential biological mechanisms of these genes. RESULTS: A total of 58 differentially expressed miRNAs were identified between the experiment group and the control group. Seven miRNAs were selected for potential construction of a miRNA biomarker through LASSO regression, and based on the area under the curve (AUC) values of each miRNA, four of these miRNAs (miR-377-3p, miR-4779, miR-6803-5p, miR-3960) were ultimately chosen as biomarkers for predicting advanced LUSC. The AUC under the ROC curve for the combined four miRNAs was 0.865. Enrichment analysis showed that these target genes were involved in several pathways, including cancer-related pathways, mitogen-activated protein kinase (MAPK) signaling pathway, serine/threonine kinase, and tyrosine kinase signaling pathways. CONCLUSIONS The combined use of miR-377-3p, miR-4779, miR-6803-5p and miR-3960 provides a good predictive ability for the progress of advanced LUSC patients, with an AUC of 0.865.
Humans ; MicroRNAs/metabolism* ; Lung Neoplasms/metabolism* ; Biomarkers, Tumor/metabolism* ; Carcinoma, Squamous Cell/pathology* ; Gene Expression Regulation, Neoplastic ; Male ; Female ; Prognosis ; ROC Curve ; Middle Aged

Lung cancer, particularly non-small cell lung cancer (NSCLC), is a leading cause of cancer-related mortality worldwide. In recent years, metabolomics has emerged as a key systems biology approach for analyzing small-molecule metabolites in cells, tissues and organisms. It provides new strategies for early diagnosis and metabolic profiling. Additionally, metabolomics plays a crucial role in studying resistance mechanisms in lung cancer. Tumor cell metabolic reprogramming is a key driving factor in the initiation and progression of lung cancer. Metabolomics studies have revealed how lung cancer cells regulate critical pathways such as energy metabolism, lipid metabolism, and amino acid metabolism to adapt to the demands of rapid proliferation and invasive metastasis. This review summarizes the latest advances in metabolomics research in lung cancer, focusing on the characteristics of metabolic reprogramming, the identification of potential metabolic biomarkers, and the prospects of metabolomics in early diagnosis and the elucidation of resistance mechanisms in lung cancer.
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Humans ; Metabolomics/methods* ; Lung Neoplasms/pathology* ; Animals ; Biomarkers, Tumor/metabolism*

OBJECTIVE: To explore the function of LIM and calponin homology domains 1 (LIMCH1) in the development and progression of oral squamous cell carcinoma (OSCC), along with their potential clinical applications. METHODS: By utilizing transcriptome sequencing data from two groups of oral squamous cell carcinoma patients, along with bioinformatics analytical techniques such as Gene Ontology (GO) and gene co-expression networks, we identified genes that might play a pivotal role in the pathogenesis of oral squamous cell carcinoma. We employed real-time quantitative PCR and Western blotting to validate the expression patterns of these genes across twelve patient tissue samples. Furthermore, we conducted CCK-8 assays, flow cytometry analyses, and scratch wound healing assays to assess the impact of key genes on the biological behaviors of both the Cal27 oral squamous cell carcinoma cell line and the potentially malignant DOK oral lesion cell line. Additionally, we examined correlations between these key genes and clinical disease parameters in 214 oral squamous cell carcinoma patients using The Cancer Genome Atlas (TCGA) data; gene set enrichment analysis (GSEA) analysis results were also incorporated to enhance our findings from real-time quantitative PCR and Western blotting regarding potential mechanisms underlying the action of these key genes. RESULTS: The integrated analysis of sequencing data and bioinformatics revealed that LIMCH1 exhibited significantly reduced mRNA (P < 0.001) and protein levels (P < 0.01) in the oral squamous cell carcinoma tissues compared with normal control tissues. In the Cal27 cells, the low LIMCH1 level group demonstrated a larger wound healing area within 24 hours than the control group (P < 0.01), enhanced proliferation capacity over 72 hours relative to the control group (P < 0.01), and an increased apoptosis rate within 24 hours compared with the high expression group (P < 0.05). However, no significant differences were observed between the low and high level groups in DOK cells. Furthermore, it was determined that low LIMCH1 level correlated with poor prognosis in the patients (P=0.013) and a higher lymph node metastasis rate (P < 0.05). Investigations into the potential mechanisms of action indicated that LIMCH1 did not influence the onset or progression of oral squamous cell carcinoma via the epithelial-mesenchymal transition pathway. CONCLUSION LIMCH1 level may function as a promising biomarker to aid in the prognostic assessment of oral squamous cell carcinoma; however, its precise mechanistic role requires further investigation.
Humans ; Mouth Neoplasms/metabolism* ; Prognosis ; Carcinoma, Squamous Cell/metabolism* ; Biomarkers, Tumor/metabolism* ; LIM Domain Proteins/metabolism* ; Cell Line, Tumor ; Cell Proliferation ; Male ; Female