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

The early diagnosis and precise treatment of esophageal squamous cell carcinoma (ESCC) hold significant clinical value in improving patient survival rate. Current diagnostic methods for early-stage ESCC primarily rely on invasive procedures and endoscopy, which can cause discomfort and financial burden for patients. Therefore, non-invasive biomarkers with high sensitivity and specificity present a more suitable alternative for early tumor diagnosis. Tumor associated autoantibodies (TAAb), identified as potential biomarkers, have considerable clinical implications for the early diagnosis, treatment monitoring, and prognosis assessment of ESCC. Here in we aim to summarize recent research on ESCC-related autoantibodies, including their background, types and development, analyze the potential of those autoantibodies in clinical diagnosis, treatment monitoring, and prognosis assessment, and also discuss the limitations of existing research and future directions. The goal is to provide a theoretical foundation for the early diagnosis and personalized treatment of ESCC.
Humans ; Autoantibodies/immunology* ; Esophageal Neoplasms/therapy* ; Esophageal Squamous Cell Carcinoma/immunology* ; Biomarkers, Tumor/immunology* ; Prognosis ; Carcinoma, Squamous Cell/diagnosis* ; Animals

Objective To investigate the causal relationship between serum total bile acid (TBA) levels and gastric cancer (GC) using regression discontinuity design (RDD). Methods A total of 1244 GC patients and 1333 healthy controls were included in the study. Demographic characteristics, gallbladder disease history, tumor markers, and serum TBA levels were collected from both groups. Logistic regression was used to construct a risk prediction model to estimate the risk of GC. RDD was employed with serum TBA as the grouping variable and the individual risk of developing GC as the outcome variable. Results The predictive factors in the GC risk prediction model included age, sex, body mass index(BMI), serum TBA, carcinoembryoniv antigen(CEA), alpha fetoprotein(AFP), carbohydrate antigen 199(CA199), and CA125. Serum TBA was identified as an independent risk factor for GC (OR=1.054, 95% CI: 1.030 to 1.079). RDD analysis indicated that when serum TBA levels reached 8 μmol/L, the probability of developing GC increased sharply by 23.7%. The breakpoint remained statistically significant following validity and robustness assessments. Conclusion The study demonstrates a positive causal relationship between serum TBA levels and GC, when the serum TBA level reaches 8 μmol/L, the risk of an individual developing GC increases sharply.
Humans ; Stomach Neoplasms/etiology* ; Male ; Female ; Middle Aged ; Bile Acids and Salts/blood* ; Aged ; Adult ; Risk Factors ; Case-Control Studies ; Biomarkers, Tumor/blood* ; Logistic Models

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

OBJECTIVES: To identify potential plasma lipidomic biomarkers that distinguish non-metastatic medulloblastoma (nmMB) from metastatic medulloblastoma (mMB) in children. METHODS: In this prospective study, 17 children with mMB and 20 matched children with nmMB were enrolled. Plasma samples were analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Lipid metabolites were evaluated for their associations and diagnostic performance. RESULTS: Orthogonal partial least squares discriminant analysis based on lipid profiles clearly separated nmMB from mMB, and 14 differential lipids were identified, including DG(18:2/20:4/0:0) and SM(d18:1/20:0). Receiver operating characteristic analysis showed nine metabolites with area under the curve greater than 0.7. Differential lipids were enriched in sphingolipid, glycerophospholipid, and arachidonic acid metabolism, suggesting an association with the metastatic phenotype. CONCLUSIONS Plasma lipidomics provides a new approach to identify mMB, and the identified lipid metabolites may support early diagnosis and treatment, prognostic assessment, and selection of therapeutic targets for metastatic medulloblastoma.
Humans ; Medulloblastoma/diagnosis* ; Lipidomics ; Child ; Male ; Female ; Child, Preschool ; Cerebellar Neoplasms/blood* ; Biomarkers, Tumor/blood* ; Neoplasm Metastasis ; Prospective Studies ; Adolescent ; Lipids/blood*

In recent years, as a new omics field, metabolomics has been proved to be of great value in the study of the mechanism of occurrence and progression, the screening of new biomarkers and the development of novel therapeutic strategies in many diseases including tumors. In this review, we briefly summarized the research methods and techniques of metabolomics, and focused on the latest research progress of metabolomics in the pathogenesis of hematological malignancies represented by leukemia, lymphoma and multiple myeloma, screening of biomarkers for diagnosis and prognosis, and development of new therapeutic strategies. This article proposes the limitations of metabolomics and future research strategies, and provides a new exploration direction for accurate diagnosis and treatment as well as prognosis evaluation of hematological malignancies.
Humans ; Metabolomics/methods* ; Hematologic Neoplasms/diagnosis* ; Biomarkers, Tumor

BACKGROUND: Epidermal growth factor receptor (EGFR) sensitive mutation is one of the effective targets of targeted therapy for non-small cell lung cancer (NSCLC). However, due to the difficulty of obtaining some primary tissues and the economic factors in some underdeveloped areas, some patients cannot undergo traditional genetic testing. The aim of this study is to establish a machine learning (ML) model using non-invasive peripheral blood markers to explore the biomarkers closely related to EGFR mutation status in NSCLC and evaluate their potential prognostic value. METHODS: 2642 lung cancer patients who visited Jiangsu Cancer Hospital from November 2016 to May 2023 were retrospectively enrolled and finally 175 NSCLC patients with complete follow-up data were included in the study. The ML model was constructed based on peripheral blood indicators and divided into training set and test set according to the ratio of 8:2. Unsupervised learning algorithms were used for clustering blood features and mutual information method for feature selection, and an ensemble learning algorithm based on Shapley value was designed to calculate the contribution of each feature to the model prediction result. The receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the model. RESULTS: Through the feature extraction and contribution analysis of the predictive results of the interpretable ML model based on the Shapley value, the top ten indicators with the highest contribution were: pathological type, phosphorus, eosinophils, monocyte count, activated partial thromboplastin time, potassium, total bilirubin, sodium, eosinophil percentage, and total cholesterol. The area under the curve (AUC) of the model was 0.80. In addition, patients with hyponatremia and squamous cell carcinoma group had a poor prognosis (P<0.05). CONCLUSIONS The interpretable model constructed in this study provides a new approach for the prediction of EGFR mutation status in NSCLC patients, which provides a scientific basis for the diagnosis and treatment of patients who cannot undergo genetic testing.
Humans ; Carcinoma, Non-Small-Cell Lung/diagnosis* ; Machine Learning ; Lung Neoplasms/diagnosis* ; Male ; Female ; Mutation ; Middle Aged ; ErbB Receptors/genetics* ; Prognosis ; Aged ; Retrospective Studies ; Adult ; Biomarkers, Tumor/genetics*

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