BACKGROUND:To explore the prognostic value and immunomodulatory role of CTNNB1 in pancreatic ductal adenocarcinoma (PDAC), so as to provide evidence for the diagnosis and individualized treatment of PDAC. METHODS:Next-generation sequencing (NGS) was performed to detect 425 cancer-associated genes in PDAC specimens and matched normal pancreatic tissues. Integrative transcriptome analysis based on TCGA, GTEx, and multiple GEO datasets was conducted to identify the differential expression of CTNNB1 between PDAC and normal pancreatic tissues. The Human Protein Atlas (HPA, https://www.proteinatlas.org/) database was used to verify the protein expression and subcellular localization of CTNNB1 in normal pancreatic tissues and pancreatic ductal adenocarcinoma (PDAC) tissues. Single-cell RNA-sequencing and spatial transcriptomic data were further supplemented to delineate its cellular expression landscape. Forest plot, Kaplan-Meier survival analysis, and ROC curve analysis were applied to evaluate the correlations between CTNNB1 expression and prognostic and to verify its prognostic accuracy. The prognostic reliability was further validated using the independent cohort GSE57495. Immune cell infiltration and immune regulatory factors were quantified via TIMER, EPIC, MCPcounter, CIBERSORT, and xCell algorithms, and TMEscore was calculated to predict the responsiveness to immune checkpoint blockade (ICB). Pharmacogenomic datasets including GDSC1, GDSC2, PRISM, and CTRP were utilized to screen optimal candidate drugs for CTNNB1-high PDAC patients. RESULTS:CTNNB1 was significantly overexpressed in PDAC compared with normal pancreatic tissues. HPA immunohistochemistry confirmed CTNNB1 shifts from membranous to cytoplasmic localization in PDAC, indicating activated Wnt signaling and concordant dysregulation at mRNA and protein levels. CTNNB1 protein was mainly localized in malignant epithelial cells of PDAC, with elevated expression also observed in partial immune cell subsets by single-cell sequencing and spatial transcriptome assessment. Upregulated CTNNB1 was significantly linked to unfavorable clinical prognosis in PDAC. ROC analysis verified its good diagnostic efficiency for distinguishing PDAC from peritumoral tissues with favorable sensitivity and specificity. CTNNB1 expression was closely correlated with multiple immune biomarker molecules and ICB therapeutic efficacy; patients with low CTNNB1 expression tended to be more responsive to ICB treatment. Pharmacological prediction revealed that PDAC patients with high CTNNB1 expression exhibited enhanced sensitivity to clofibrate and several other small-molecule compounds. CONCLUSION:CTNNB1 may be remarkably effective as a suitable biomarker for the prognosis prediction of PDAC patients and is closely related to the tumor immune microenvironment. Such an association could provide novel thoughts for the therapy tactics and mechanistic studies toward PDAC.
PURPOSE:This study aims to investigate whether matrix metalloproteinases (MMPs) are associated with the risk of metabolic syndrome (MetS) and its components. METHODS:We conducted a two-sample Mendelian randomization (MR) study by using 9 types of MMPs as exposures and MetS and its components (waist circumference, essential hypertension, fasting blood glucose [FBG], high-density lipoprotein [HDL] cholesterol, and triglycerides) as outcomes. The genome-wide association study summary data of exposure and outcome were both obtained from publicly published research. Four MR analytical methods, including inverse variance weighted, MR-Egger, weighted median, and weighted mode, were applied to analyze the causality between exposure and outcome, in which IVW was employed as the primary analytical method. MR-Egger, Cochran's Q, leave-one-out (LOO), and MR pleiotropy residual sum and outlier (MR-PRESSO) were used to assess the reliability of the results of the MR analysis. RESULTS:Genetically determined MMP12 showed significant negative associations to the risk of essential hypertension (OR = 0.996, 95% CI: 0.993-0.998, p = 0.001). Results that were analyzed with the MR-Egger, weighted median, and weight mode were consistent with those analyzed with IVW. Although MMP12 may have a suggestive protective effect on FBG levels (OR = 0.993, 95% CI: 0.986-1, p = 0.049), this finding may be affected by potential horizontal pleiotropy and requires further validation. No causal associations were identified between other MMPs and the risk of MetS or its components. CONCLUSIONS:This MR analysis provides evidence of causal links between MMP12 and the risk of essential hypertension, indicating that MMP12 might inform early risk stratification for specific cardiometabolic components (e.g., essential hypertension), rather than serving as a diagnostic biomarker for the composite metabolic syndrome.
BACKGROUND:Epstein-Barr virus-associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer, but reliable biomarkers linking EBV-related biology, prognosis, and microenvironmental remodeling remain limited. METHODS:Differentially expressed genes associated with EBVaGC were identified from TCGA and GEO datasets. Weighted gene co-expression network analysis and machine learning were used to screen core genes. Functional enrichment, diagnostic and prognostic modeling, immune infiltration analysis, single-cell transcriptomic analysis of a public scRNA-seq dataset, cell-cell communication analysis, drug sensitivity prediction, external cohort validation, and RT-qPCR validation in gastric cancer cell lines were subsequently performed. RESULTS:Five core genes (ASPA, CHODL, GNG7, P2RY14, and PI16) were identified. The combined classifier showed high apparent diagnostic performance in the discovery datasets (AUC = 1.000 in the EBV cohort and 0.981 in TCGA-STAD) and retained value in GSE27342 (AUC = 0.771). RT-qPCR confirmed differential expression of these genes between a gastric epithelial cell line and a gastric cancer cell line, providing general tumor-versus-normal experimental support rather than EBV-specific validation. A five-gene risk signature stratified overall survival, with 1-, 2-, and 3-year AUCs of 0.634, 0.645, and 0.622, which improved to 0.716, 0.768, and 0.693 after integration with age and stage. Single-cell analysis localized the strongest signature signal to fibroblasts and B cells and revealed enhanced MIF-, PTN-, and TNFSF13B-related communication in tumors. High-risk tumors showed higher predicted IC50 values for paclitaxel and 5-fluorouracil. CONCLUSION:We identified a five-gene signature with strong diagnostic value and biologically meaningful prognostic relevance in EBVaGC, highlighting fibroblast- and B-cell-associated microenvironmental programs in aggressive disease.
OBJECTIVE:To detect the expression level of cell division cycle 20 homolog (CDC20) in clear cell renal cell carcinoma (ccRCC) and to study the biological function of CDC20 in ccRCC. METHODS:CDC20 expression levels and clinical significance of ccRCC were determined using the Cancer Genome Atlas (TCGA) database. We detected the expression level of CDC20 in ccRCC with the help of immunohistochemistry (IHC). The effect of CDC20 on the proliferation of renal cancer cells was investigated using EDU and CCK-8 proliferation assays. We used wound healing assays and Transwell assays to determine the effects of CDC20 on renal cancer cell migration and invasion and Wnt signaling pathway agonists in recovery experiments. The mechanism of CDC20 in ccRCC was detected using western blotting. Finally, the effect of CDC20 on renal cancer cells was verified in vivo in a nude mouse xenograft model. RESULTS:Bioinformatics analysis found that CDC20 was upregulated in ccRCC, and its high expression was associated with poor prognosis in kidney renal cell carcinoma (KIRC) patients. In addition, we detected high expression of CDC20 in KIRC tissues, consistent with the results of bioinformatics analysis. Besides, knockdown of CDC20 can inhibit the biological functions of renal cancer cells. The recovery experiment proved that the biological function of the originally inhibited renal cancer cells was restored. In vivo, low expression of CDC20 can inhibit tumor growth. CONCLUSIONS:As CDC20 is highly expressed in KIRC tissues, it can be used as both a therapeutic target and a prognostic marker.
BACKGROUND:The significance of M2 macrophages in cancer is well established, yet their specific role and the regulatory molecules involved in colorectal cancer remain unclear. METHODS:Using publicly available single-cell RNA-seq data from four colorectal cancer datasets (EMTAB8107, GSE139555, GSE146771, and GSE166555), we evaluated macrophage proportions and their functional enrichment. Immune cell infiltration was quantified by CIBERSORT, quanTIseq, and xCell on TCGA-COAD bulk transcriptomes, with immune correlations adjusted for tumor purity. GSEA was performed with MSigDB v7.4 gene sets (Hallmark, GO, KEGG). Prognostic models were built using Kaplan-Meier and multivariate Cox regression. In vitro, CCBE1 was silenced in SW480 and HCT116 cells; proliferation was measured by CCK-8, colony formation, and EdU assays, and migration/invasion were measured by transwell assays. M2 polarization was assessed by flow cytometry. RESULTS:Macrophages represented a substantial fraction (20%-35% across datasets) of the tumor microenvironment and were associated with upregulated coagulation and KRAS signaling. Consensus M2 macrophage infiltration was linked to 91 upregulated genes, among which CCBE1 emerged as an independent prognostic risk factor (multivariate Cox: HR = 1.305 [95% CI: 1.039-1.639], p < 0.05). CCBE1 was overexpressed in colorectal cancer cell lines compared to NCM460. Silencing CCBE1 significantly suppressed cell proliferation, migration, and invasion. Moreover, the conditioned medium from CCBE1-knockdown cancer cells decreased the proportion of CD206+ M2 macrophages and upregulated M1 markers while downregulating M2 markers, indicating that CCBE1 promotes M2 polarization. CONCLUSIONS:CCBE1 is an oncogenic driver in colorectal cancer that independently predicts poor survival and functionally enhances tumor cell proliferation, invasion, and M2 macrophage polarization. Targeting CCBE1 may represent a potential therapeutic strategy for colorectal cancer.
