Hereditas最新文献

Background: Pituitary tumor-transforming gene 1 (PTTG1) has been implicated in multiple malignancies; however, its precise role and regulatory mechanism in gastric cancer remain unclear. This study aimed to determine how PTTG1 regulates cell proliferation, migration, and epithelial-mesenchymal transition (EMT) through the TGF-β/Smad signaling pathway in gastric cancer.

Methods: PTTG1 expression in gastric cancer was evaluated using The Cancer Genome Atlas (TCGA) datasets and subsequently validated by western blotting in gastric cancer cell lines. To investigate the biological functions of PTTG1, functional assays including CCK8, colony formation, and Transwell migration and invasion assays were performed following PTTG1 knockdown in SGC-7901 and HGC-27 cells. The effects on EMT were further examined by assessing EMT-related markers by western blotting. Tumorigenic and metastatic potential in vivo was determined using a nude mouse xenograft model. The regulatory influence of PTTG1 on the TGF-β/Smad pathway was analyzed by measuring the expression levels of TGF-β, Smad2, Smad3, and their phosphorylated forms.

Results: PTTG1 expression was significantly upregulated in gastric cancer tissues compared with normal gastric mucosa according to TCGA data and validation in cell lines. Silencing PTTG1 in SGC-7901 and HGC-27 cells markedly inhibited proliferation and colony formation (p < 0.01), and suppressed migration and invasion (p < 0.01). Western blotting revealed increased E-cadherin and reduced N-cadherin, α-SMA, and Vimentin expression after PTTG1 knockdown. In vivo, xenograft tumor growth was significantly reduced in nude mice injected with si-PTTG1 cells compared with controls (n = 6 per group; p < 0.05). Mechanistically, PTTG1 depletion attenuated TGF-β, phosphorylated Smad2, and phosphorylated Smad3 levels, indicating inhibition of the TGF-β/Smad pathway.

Conclusion: PTTG1 promotes gastric cancer progression by activating the TGF-β/Smad axis to enhance cell proliferation, invasion, and EMT. These findings highlight PTTG1 as a potential diagnostic biomarker and therapeutic target in gastric cancer.

Background: Atherosclerosis (AS) is a leading cause of cardiovascular-related death worldwide. The role and regulatory mechanism of GAS6-AS2 in AS remain unclear.

Aim: To investigate the diagnostic/prognostic value of GAS6-AS2 in AS and clarify its molecular mechanism.

Methods: 107 AS patients and 105 healthy controls were included. The levels of GAS6-AS2, miR-138-5p, and mRNA were measured using RT-qPCR. ROC curve, K-M survival analysis, and Cox regression were performed to evaluate the diagnostic and prognostic value of GAS6-AS2. Bioinformatics prediction and dual-luciferase reporter assay were performed to verify the regulatory axis. Ox-LDL-induced VSMCs were used to construct an AS cell model. The biological functions were assessed using CCK-8, SA-β-Gal, and ELISA.

Results: GAS6-AS2 expression was significantly increased in AS patients and in VSMCs treated with ox-LDL, and it showed high diagnostic accuracy and risk prediction for patients with AS. Knockdown of GAS6-AS2 reduced SA-β-Gal-positive cells, downregulated the expression of senescence-related genes and proteins (p16, p21, p53), and decreased the levels of inflammatory factors (IL-6, IL-1β) in ox-LDL-induced VSMCs. Mechanistically, GAS6-AS2 directly bound to miR-138-5p and inhibited its expression, while miR-138-5p targeted AKT1 to suppress its expression. Rescue experiments confirmed that the GAS6-AS2/miR-138-5p/AKT1 axis mediated ox-LDL-induced VSMC senescence and inflammation.

Conclusions: GAS6-AS2 is a potential diagnostic and prognostic biomarker for AS. It regulates ox-LDL-induced VSMC senescence and inflammatory response through the sponging of miR-138-5p to upregulate AKT1, providing a novel molecular target for AS treatment.

Lung cancer is the leading cause of cancer-related deaths globally. Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancer cases, and drug resistance severely undermines treatment efficacy. This review summarizes recent advances in elucidating NSCLC drug-resistance mechanisms using multi-omics integration. Multi-omics integration systematically reveals the molecular networks of drug resistance, identifies key biomarkers and targets, and facilitates the screening of high-priority candidates for drug development through experimental validation. Small-molecule inhibitors targeting drug-resistant proteins and multi-omics-guided combination therapies offer strategies to reverse resistance. Future directions involve developing simultaneous multi-omics detection technologies, leveraging artificial intelligence for intelligent data analysis, establishing standardized frameworks for data sharing, and implementing personalized medicine based on multi-omics to improve patient prognosis.

Background: The primary renal complication of diabetes mellitus is diabetic kidney disease (DKD). The precise pathogenic mechanisms of DKD remain poorly elucidated. The aim of this study was to identify potential energy metabolism-related genes associated with DKD.

Methods: The GSE30529 and GSE30528 datasets were retrieved from the Gene Expression Omnibus, and energy metabolism-related genes were obtained from the GeneCards database. Differentially expressed genes (DEGs) between DKD and control groups were analyzed. The biological functions and signaling pathways of these DEGs were evaluated using Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). The diagnostic performance of hub genes for DKD was assessed using receiver operating characteristic (ROC) curve analysis. Expression levels of five significant energy metabolism-related genes were validated through immunohistochemistry. The Nephroseq V5 tool was used to evaluate gene expression in DKD and to determine correlations between gene expression and renal function in patients with DKD.

Results: A total of 17 energy metabolism-related DEGs were identified. Five hub genes-ALB, IGF1, CD36, LPL, and UCP2-were identified. Among these, CD36 and LPL demonstrated relatively high diagnostic accuracy for DKD. The findings suggest that CD36, IGF1, LPL, and UCP2 may serve as potential biomarkers for DKD.

Conclusions: The genes CD36, IGF1, LPL, and UCP2 represent potential energy metabolism-related biomarkers with possible applications in the diagnosis and treatment of DKD.

Background: Colorectal cancer (CRC) is characterized by a complex pathogenesis and substantial heterogeneity in prognosis.

Objective: This study aims to elucidate the clinical significance of miR-1908-5p in CRC, as well as its association with clinicopathological parameters and patient prognosis.

Method: miR-1908-5p expression in tumor tissues was quantified by RT-qPCR. Survival outcomes were assessed using the Kaplan-Meier method. The chi-square (χ²) test and Cox regression analysis were employed to evaluate clinicopathological correlations and prognostic value.miR-1908-5p was compared between NCM460 and CRC lines (HT-29, HCT116), overexpressed, and functionally tested by CCK-8 and Transwell assays. TargetScan and luciferase assay verified the targeting of SCAMP4 3'-UTR. qPCR and Pearson analysis defined their correlation in CRC.

Results: miR-1908-5p is downregulated in CRC tumors versus adjacent normal mucosal tissues. Low expression predicts poor prognosis and is associated with reduced survival rates in colorectal cancer, correlating with advanced TNM stage and elevated serum CA19-9 levels. CRC lines (HT-29 and HCT116) show reduced miR-1908-5p compared to NCM460. miR-1908-5p mimic suppresses proliferation, migration, and invasion. TargetScan-predicted binding to SCAMP4 3'-UTR was validated by dual-luciferase reporter assay. miR-1908-5p overexpression lowers SCAMP4, which is overexpressed in tumor tissues and exhibits an inverse correlation with miR-1908-5p.

Conclusion: miR-1908-5p is downregulated in CRC, correlates with TNM stage, nodal metastasis, elevated CA19-9 levels, and poor survival, and suppresses CRC cell proliferation, migration, and invasion by directly targeting SCAMP4, thereby qualifying as a potential prognostic biomarker for CRC.