STAT1 as a potential diagnostic biomarker for gastric cancer

Integrative analysis identifies candidate biomarkers for bladder cancer: evidence from genomic and clinical validation

Investigation and validation of prognostic features associated with transient receptor potential channel genes in gastric cancer

Background An increasing body of evidence suggests an association between transient receptor potential (TRP) channel s and cancer development; however, a systematic evaluation of the combined prognostic value of TRP channel-related genes (TRGs) in gastric cancer (GC) has not been conducted. Methods Data were obtained from The Cancer Genome Atlas Stomach Adenocarcinoma, GSE84433, and TRGs. Prognostic genes related to TRP channels and GC were screened, and a risk model was constructed. Functional analysis, immune correlation analysis, and molecular regulatory network construction were performed to identify mechanisms associated with GC prognosis. Finally, the expression of prognostic genes was preliminarily assessed in clinical samples using reverse transcription quantitative polymerase chain reaction (RT-qPCR) for exploratory validation. Results Seven genes associated with GC prognosis (5-hydroxytryptamine 2C receptor (HTR2C), MAGEA11, MAGEA3, aspartoacylase (ASPA), GAD1, Hedgehog-interacting protein (HHIP), and AHNAK) were identified. A risk model constructed from these genes demonstrated potential prognostic value for patient outcomes. A close association was observed between these genes and the differential abundance of immune cells. The strongest negative correlation was observed between AHNAK and T follicular helper cells. In addition, the prognostic genes were significantly negatively correlated with CD274, which is an immune checkpoint gene. Moreover, complex regulatory relationships among prognostic genes were observed in the regulatory network. Computational analysis predicted regulatory interactions, such as the regulation of AHNAK by EPB41L4A-AS1 and ERICD via hsa-miR-106a-5p. Finally, quantitative reverse transcription polymerase chain reaction (RT-qPCR) analysis revealed that the expression pattern of MAGEA11 was consistent with that observed in public databases. Conclusions Seven prognostic genes (HTR2C, MAGEA11, MAGEA3, ASPA, GAD1, HHIP, and AHNAK) related to TRP channels were identified in GC. These findings provide insight into potential prognostic mechanisms and a basis for further studies on their roles in GC biology.

Seven-gene biomarkers reveal prognostic and immune signatures in lung adenocarcinoma.

BACKGROUND Reliable prognostic biomarkers for lung adenocarcinoma (LUAD) remain limited because of inter-cohort heterogeneity across transcriptomic studies. This study aimed to identify survival-related gene signatures associated with immune characteristics in LUAD. METHODS Three independent Gene Expression Omnibus (GEO) datasets were analyzed separately to identify consistently dysregulated genes in LUAD. Functional enrichment, protein-protein interaction network, survival, receiver operating characteristic (ROC) curve analysis, principal component analysis (PCA), expression validation, and immune infiltration analyses were performed. RESULTS A total of 68 overlapping differentially expressed genes were identified. Functional enrichment analysis showed that these genes were mainly involved in vascular-related biological processes. Network and survival analyses identified seven significantly downregulated genes, including AGER, CAV1, EDNRB, ROBO4, EMCN, TEK, and PTPRB, which were associated with overall survival in LUAD. ROC analysis showed favorable diagnostic performance across the three GEO datasets, with area under the curve (AUC) values ranging from 0.873 to 1.000. In the larger datasets, AUCs ranged from 0.932 to 0.952 in GSE19188 and from 0.873 to 0.949 in GSE30219, with corresponding 95% CI ranges of 0.870-1.000 and 0.710-1.000, respectively. PCA further supported separation between LUAD and normal samples. Immune infiltration analysis showed associations between the seven-gene signature, tumor purity, and multiple immune cell populations. CONCLUSIONS A seven-gene vascular-related signature was associated with prognosis and immune infiltration patterns in LUAD. These findings may support future biomarker development and studies of tumor microenvironment remodeling in LUAD.

Establishment and evaluation of novel prognostic biomarkers based on systemic coagulation-inflammation index and related genes in breast cancer

Background Coagulation and inflammation play crucial roles in the initiation and progression of cancer, and they exhibit a synergistic effect. However, a hematological biomarker and risk model based on coagulation and inflammatory have not yet been established in breast cancer. Methods This study retrospectively analyzed 749 breast cancer patients at our institution. We established a coagulation-inflammation-related genes (CIRGs) risk model using the TCGA-BRCA dataset as the training set and GEO datasets (GSE20685, GSE21653) as the testing sets. Immunohistochemical staining was performed on tumor tissues to validate protein-level expression of key genes. Additionally, single-cell RNA sequencing (scRNA-seq) was applied to investigate the expression of the CIRGs and explore intercellular communication differences. Results All enrolled cases were stratified by median systemic coagulation-inflammation index (SCI) into high- and low-SCI groups. The low-SCI group had longer disease-free survival and overall survival than the high-SCI group, with higher SCI levels noted in triple-negative breast cancer (TNBC). SCI exhibited a linear correlation with survival outcomes and superior survival predictive performance compared to the platelet-to-lymphocyte ratio. LASSO regression selected 21 prognosis-related CIRGs to construct a prognostic model, which showed robust predictive efficacy across three datasets. Tumor microenvironment analysis indicated that the high-risk group was associated with immune suppression. Drug sensitivity analysis identified 6 potential candidate drugs for low- and high-risk groups. Four hub genes (ABCA1, IL1R1, SERPINE1, and HPN) were identified among CIRGs, showing strong correlations with tumor stage and prognosis. scRNA-seq analysis revealed high expression of the CIRGs in myeloid, endothelial, and epithelial cells, with higher AUCell scores of the CIRGs in TNBC. Significant intercellular communication differences were observed between the two risk groups, especially in fibroblast/endothelial cell-to-T/B cell signaling pathways. Conclusion This study deeply explores the roles and clinical significance of coagulation and inflammation in breast cancer. The hematological indicator SCI and the CIRGs risk model can serve as reliable biomarkers for breast cancer personalized treatment.

Seven-Gene Signature and Immune Microenvironment as Determinants of Survival Rate in Colorectal Carcinoma

: Backgrounds: Colorectal cancer (CRC) prognosis remains difficult due to molecular heterogeneity and interaction between tumor cells and the immune microenvironment. This study aimed to identify transcriptomic and immune-cell patterns associated with overall survival (OS) and to develop an integrated prognostic model to improve risk stratification. Methods: RNA-sequencing was performed on 131 primary CRC samples and matched normal tissues. Differentially expressed genes (DEGs) were identified and functionally characterized through gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein–protein interaction (PPI) network analysis. Immune-cell composition was estimated using CIBERSORTx deconvolution and evaluated for its association with OS. Prognostic DEGs were screened using univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) analysis to construct a risk score. The model was validated in the Cancer Genome Atlas Database (TCGA)-COAD (colon cancer) and READ (rectal cancer) cohorts. A nomogram integrating molecular and clinicopathological variables were generated. Results: A total of 5589 DEGs were identified between CRC and normal tissues, enriched in pathways related to cell cycle, Tumor Protein P53 (TP53), WNT Family Member (WNT), Janus kinase/signal transducer and activator of transcription 3 (JAK/STAT), calcium signaling, metabolism, and immune regulation. PPI analysis highlighted ten upregulated hub genes involved in mitotic spindle formation and chromosomal stability. Immune infiltration analysys indicated that higher proportions of plasma cells ( p = 6.9 × 10 − 4 ), naïve B cells ( p = 0.019), resting CD4 + memory T cells ( p = 0.02), M0 macrophages ( p = 0.0077), and activated dendritic cells ( p = 1.89 × 10 − 5 ) were associated with improved OS, whereas monocytes ( p = 0.012), neutrophils ( p = 0.041), activated mast cells ( p = 0.0066), and M2 macrophages ( p = 0.014) were linked to poorer survival. A seven-gene signature including aspartate beta-hydroxylase (ASPH), bradykinin receptor B1 (BDKRB1), calcium voltage-gated channel auxiliary subunit beta 1 (CACNB1), C-C motif chemokine receptor 8 (CCR8), cyclic nucleotide gated channel subunit alpha 3 (CNGA3), microtubule associated protein 1A (MAP1A) and oxytocin receptor (OXTR) stratified patients into high-and low-risk groups with significant OS differences. The model demonstrated strong predictive performance (AUC: 0.84 at 1 year) and was validated in TCGA cohorts. Multivariate analysis confirmed the risk score as an independent prognostic factor. The integrated nomogram accurately predicted 1, 3-, and 5-year survival (C-index = 0.757; 95% CI 0.724–0.791). Conclusions: We developed and validated a seven-gene immune-related prognostic signature that, combined with clinicopathological parameters, provides a robust tool for individualized survival prediction and may guide precision management in CRC patients.

Integrated Analysis of Multiple Databases Identifies Tissue Inhibitor of Metalloproteinase 1 Expression and Its Association with the Immune Microenvironment in Colorectal Cancer

Background: In recent decades, the incidence of colorectal cancer (CRC) has been rising worldwide. CRC ranks second in cancer-related mortality. The identification of reliable biomarkers for early diagnosis and prognosis prediction, along with a deeper understanding of the underlying molecular events, holds substantial promise for improving patient outcomes. The tissue inhibitor of the metalloproteinase 1 (TIMP1) gene is overexpressed in various gastrointestinal malignancies and contributes to tumor progression. However, its role in regulating the CRC tumor immune microenvironment (TIME) and its potential as a clinically actionable prognostic biomarker remain unclear. Methods: To probe how TIMP1 acts as a prognosis-related candidate biomarker in colorectal carcinoma, TCGA-derived datasets were adopted to conduct Kaplan–Meier survival assessment. We also investigated the connection between the expression abundance of TIMP1 and the infiltration of immune populations and intratumoral lymphocytes; furthermore, immune checkpoint-related genes were systematically assessed across multiple tumor types via the TISIDB and TIMER2.0 platforms, with particular emphasis on CRC. We adopted the ESTIMATE scoring system to figure out how TIMP1 gene expression correlates with the phenotypic properties of the colorectal-cancer TIME. We relied on the limma toolkit for the screening of differential transcripts from high-TIMP1 and low-TIMP1 cohorts. Enrichment assessments covering Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes entries were then carried out to predict the potential biological pathways associated with TIMP1. We constructed the protein–protein interaction map for TIMP1-interacting partners via the STRING repository. To further explore TIMP1-correlated genes, we performed Venn diagram intersection analysis combined with Spearman’s correlation test. Finally, quantitative reverse-transcription PCR was then implemented to detect TIMP1 messenger-RNA abundance inside the RKO colorectal carcinoma cell line as well as normal colonic epithelial CCD-18Co cells, which offered in vitro experimental verification for our bioinformatic outcomes. Results: According to outcome data, TIMP1 transcripts were markedly up-regulated in CRC specimens and cell lines relative to normal samples. Elevated TIMP1 expression served as a poor-prognosis indicator for overall survival (hazard ratio [HR] = 0.43, 95% confidence interval [CI] = 0.29–0.64, p < 0.001) and disease-specific survival (HR = 0.39, 95% CI = 0.22–0.68, p = 0.001) among colorectal-carcinoma patients. TIMP1-high and TIMP1-low groups exhibited notable differences in immune cell infiltration (CD8+ T, macrophage, mast, neutrophil, B, monocyte, dendritic, and CD4+ T cells). TIMP1 expression was also significantly correlated with tumor-infiltrating lymphocytes, key immune checkpoint genes (e.g., CD274 [PD-L1] and CTLA4), and immunomodulatory chemokines (e.g., CCL3 and CCL5). Twelve TIMP1-interacting DEGs were selected: COL5A1, FN1, PRG4, and a cluster of nine MMPs (MMP1/2/3/7/8/9/11/13/14), all of which showed significant positive correlations with TIMP1 (r = 0.31–0.63, all p < 0.001). Conclusions: TIMP1 expression correlates with features of the tumor immune microenvironment and extracellular matrix remodeling in CRC, suggesting that TIMP1 shows potential as a candidate biomarker. However, its potential as a therapeutic target warrants further experimental investigation.