Jul 2026· Current Medicinal Chemistry· Vol 33· 0 citations
Medicine
TL;DR
Findings suggest that BRCA1 is not an independent prognostic factor but reflects broader tumor biological processes, particularly DNA repair and redox regulation, and positioning BRCA1 as a key component of tumor biology and a potential target for precision oncology strategies.
Abstract
Objective
This study aims to identify biologically relevant genes associated with DNA repair pathways in gastric cancer (GC) by integrating multi-omics analyses with causal inference approaches.
Methods
Public GC datasets were integrated to identify consensus differentially expressed genes (DEGs). Candidate genes were screened using WGCNA and intersected with DEGs. Key genes were selected via the machine learning algorithm Lasso+plsRglm and validated by the Area Under the Receiver Operating Characteristic Curve (AUC) analysis. The Protein-Protein Interaction (PPI) network determines the hub genes associated with GC. Single-cell RNA sequencing characterized the cell-type-specific gene expression. Kaplan-Meier analysis assessed the prognostic relevance. Immune infiltration was evaluated using CIBERSORT and ESTIMATE algorithms. Mendelian Randomization (MR) examined causal relationships among BRCA1, NADPH, and GC risk. Experimental validation was performed using qRT-PCR and Western blot in GC cell lines and clinical samples.
Results
Five hub genes, i.e., BRCA1, CCNA2, CHEK1, KIF14, and KIF15, predominantly enriched in mesenchymal stem cells and fibroblasts, were identified. BRCA1 was consistently overexpressed in GC and associated with improved survival and enhanced antitumor immune activity. MR analysis suggested indirect associations between BRCA1, NAD(P)H metabolism, and GC risk, without a direct causal effect. Experimental results confirmed significant overexpression of BRCA1 at both mRNA and protein levels in GC.
Discussion
These findings suggest that BRCA1 is not an independent prognostic factor but reflects broader tumor biological processes, particularly DNA repair and redox regulation. Its upregulation likely represents a compensatory response to genomic instability. The identified BRCA1-NAD(P)H axis highlights a potential mechanistic link between DNA repair and metabolic regulation, underscoring its relevance in tumor progression and therapeutic targeting.
Conclusion
This study reveals a regulatory link between DNA repair, redox metabolism and GC progression, positioning BRCA1 as a key component of tumor biology and a potential target for precision oncology strategies.
BACKGROUND
Diffuse large B-cell lymphoma (DLBCL) presents a complex etiology and challenging diagnosis. This study aims to investigate potential pathogenic genes.
METHODS
We identified DLBCL risk genes (DRGs) through expression quantitative trait loci-Mendelian randomization (eQTL-MR). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to explore biological functions. Single-cell RNA sequencing (scRNA-seq) data were analyzed to delineate the subcellular localization. Immune infiltration analyses examined the role of genes in the DLBCL immune microenvironment. Finally, drug sensitivity analyses were performed to predict potentially sensitive drugs.
RESULTS
Following eQTL-MR and prognostic analyses, we identified 15 genes associated with both the pathogenesis and prognosis of DLBCL. These genes were successfully integrated into a risk gene model, achieving an Area Under the Curve (AUC) of 0.787. GO and KEGG enrichment analyses of genes localized significant pathways, including NF-κB signal transduction. ScRNA-seq analysis suggested that DRGs may be linked to the immune microenvironment of DLBCL. Further immune infiltration analysis confirmed the pivotal role of immune infiltration in the malignant progression of DLBCL.
CONCLUSION
This study unveils 15 risk genes as potential pathogenic and therapeutic biomarkers for DLBCL. These findings provide novel insights and targets for understanding the pathogenesis, diagnosis, and treatment of DLBCL.
: 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.
A ferroptosis- and lipid metabolism-related prognostic signature is developed that accurately predicts survival outcomes and immune characteristics in CRC and CRY2 was identified as a critical regulator of tumor growth.
Yu Guo, Yongbo Zou, Min Wang· Annals medicus· 0 citations
Triple-negative breast cancer (TNBC) remains one of the most therapeutically resistant breast cancers and often displays pronounced immune heterogeneity. This study integrates multi-omics datasets to identify candidate biomarkers that may influence TNBC progression and modulate therapeutic response.
Transcriptomic, DNA methylation, microRNA (miRNA), and single nucleotide polymorphism (SNP) datasets from public repositories were analyzed using differential expression and correlation pipelines. Expression, mutation, and regulatory metrics were then integrated to prioritize key genes. Top candidates, including CCND2 and KIF1A, were preliminarily validated using qPCR and Kaplan—Meier plots. CIBERSORT was applied to examine tumor immune cell infiltration and to assess the immune-related expression of candidate genes.
Multi-omics integration highlighted CCND2 and KIF1A as highly ranked candidates associated with TNBC proliferation and cell cycle regulation. Literature and pathway analysis suggested potential involvement of these genes in key oncogenic and immune-related signaling pathways. Preliminary qPCR results supported their differential expression relative to normal breast tissue.
These findings nominate CCND2 and KIF1A as candidate biomarkers and potential therapeutic targets in TNBC. Continued pathway and functional validation will clarify how these genes contribute to tumor progression and may inform precision treatment strategies for TNBC.
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Translational and Interventional Immunology (TI)
Roberto Aguilar, Victor Wang, Shane Deng· Journal of Immunology· 0 citations
Cervical cancer (CC) remains a leading malignancy among women worldwide. Epigenetic and transcriptional dysregulation complicate the identification of causal genes with prognostic and therapeutic relevance. We performed a multi-omics integrative analysis combining summary data-based Mendelian randomization (SMR) using eQTL and pQTL datasets with genome-wide association study (GWAS) summary statistics (ID: ukb-b-8777) to prioritize candidate genes associated with CC. Differential expression analyses were conducted using multiple GEO cohorts, and protein expression was validated by immunohistochemistry (IHC) in clinical specimens. DNA methylation profiling and correlation analyses were performed using GEO and TCGA datasets to investigate epigenetic regulation. Kaplan–Meier and combined expression–methylation survival analyses were used to evaluate prognostic significance. Functional validation was conducted in HeLa cells using wound-healing and CCK-8 assays following FAM3D knockdown or overexpression. RNA sequencing was further performed to explore the downstream molecular pathways regulated by FAM3D. Integrative SMR analysis identified FAM3D as a protective gene for CC. FAM3D expression was significantly reduced in CC tissues and exhibited a progressive decline from normal cervical tissues to cervical intraepithelial neoplasia (CIN) and invasive CC, which was further confirmed by IHC. Promoter hypermethylation of FAM3D (cg26334888) was associated with its transcriptional downregulation and negatively correlated with gene expression. Survival analyses demonstrated that high FAM3D expression (p = 0.016) and low promoter methylation (p = 0.048) were associated with favorable overall survival, while combined expression–methylation analysis further improved prognostic stratification (p = 0.006). Functional assays showed that FAM3D suppressed CC cell proliferation and migration. Transcriptomic profiling revealed that FAM3D restoration induced extensive transcriptional reprogramming and was associated with inflammatory signaling, cytokine-mediated pathways, and extracellular matrix remodeling. Key hub genes identified downstream of FAM3D included CXCL8, MMP1, EREG, and LCN2. FAM3D is a potential tumor suppressor and prognostic biomarker in CC, whose expression is partially regulated by promoter methylation. Integrative multi-omics analyses and functional studies suggest that FAM3D may inhibit CC progression through modulation of inflammatory signaling and extracellular matrix-associated pathways. These findings provide new insights into the molecular mechanisms underlying CC and support the potential clinical utility of FAM3D as a prognostic biomarker and therapeutic target.