Hereditas最新文献

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.

Background: In terms of global incidence and mortality, breast cancer continues to surpass all other cancers affecting women.

Methods: To explore the role of miR-596, qRT-PCR was applied to measure its expression in tissue and cell samples from 137 enrolled subjects. The regulatory interaction between miR-596 and EIF5AL1 was verified by dual-luciferase reporter assays. CCK-8 and Transwell assays were utilized to respectively measure the proliferation, migration, and invasion capabilities of the two breast cancer cell lines, MCF-7 and MDA-MB-231.

Results: A significant downregulation of miR-596 was observed in breast cancer tissues and cell lines (all P < 0.001). Clinically, reduced miR-596 expression was associated with advanced TNM stage, lymph node metastasis, and inferior overall survival (P < 0.05). EIF5AL1 was validated as a direct target gene of miR-596, and their expression levels were inversely correlated in clinical samples (r = -0.801, P < 0.001). Reintroduction of miR-596 markedly suppressed the proliferation, migration, and invasion of cancer cells, effects that were largely reversed by overexpressing EIF5AL1 (all P < 0.001).

Conclusion: In breast cancer, miR-596 suppresses malignancy and predicts prognosis by targeting EIF5AL1. Thus, therapeutic modulation of this axis offers novel avenues for treatment and risk assessment.

Background: Dysregulated expression of long non-coding RNA (lncRNA) TUG1 participates in the etiopathogenesis of polycystic ovary syndrome (PCOS). This study analyzed the genetic association of the TUG1 rs5749201 polymorphism in PCOS patients.

Methods: Genotype and allele distributions of rs5749201 were analyzed in 210 PCOS patients and 230 healthy volunteers. Serum TUG1 levels were detected via qRT-PCR. The relationship between gene polymorphism and PCOS risk was analyzed via multivariate logistic regression.

Results: Compared with the control group, the PCOS group had a significantly higher proportion of carriers with TUG1 rs5749201 AA genotype and a lower proportion of TT genotype carriers. Rs5749201 TT genotype carriers had notably reduced PCOS risk. This genetic association was also found in dominant and recessive models, with the locus independently linked to PCOS (OR = 0.427, 95%CI: 0.242-0.753; P = 0.003). AA genotype carriers had higher LDL, TG and FBS than AT/TT genotype carriers. PCOS patients had elevated TUG1 levels, with AA genotype carriers showing the highest.

Conclusion: TUG1 rs5749201 was linked to PCOS susceptibility, which is correlated with its regulatory role in TUG1 expression.