Hereditas最新文献

Background: Glioblastoma (GBM) is a highly aggressive brain tumor characterized by poor prognosis and limited therapeutic options. Understanding the molecular mechanisms driving GBM progression is essential for developing more effective diagnostic and therapeutic approaches. Specifically, investigating Cell Division Cycle-Associated (CDCA) genes offers new perspectives on cell cycle regulation and the proliferation of GBM cells, which are key factors in tumor growth and resistance to treatment. These genes have not been extensively studied in GBM, making them a promising area for targeted research and potential therapeutic interventions. This project was launched to elucidate the pathogenic, diagnostic, and therapeutic roles of CDCA genes in GBM.

Methodology: Total RNA was extracted from GBM cell lines followed by RT-qPCR to analyze the expression of CDCA genes. The expression validation, prognostic significance, and mutational analysis of CDCA genes were performed using various databases. Functional assays, including gene knockdown, colony formation, proliferation, and wound healing, were conducted in U87MG cells to assess the role of CDCA7 and CDCA8 in GBM.

Results: The expression analysis of CDCA genes in 12 GBM cell lines and 6 normal brain cell lines revealed significant overexpression of these genes in GBM. ROC curve analysis demonstrated excellent diagnostic potential, with AUC values of 1 for most genes. This indicates that CDCA gene expression effectively distinguishes GBM cells from normal brain cells. Validation using additional TCGA data confirmed the upregulation of these genes in GBM tumors, with significant association to key cancer-related pathways. Survival analysis showed that higher expression of CDCA genes correlated with poor prognosis in GBM patients. Mutation, CNV, and methylation analyses revealed alterations in these genes, further supporting their role in GBM. Additionally, CDCA gene expression was linked to immune modulation and cell cycle-related functions, suggesting their involvement in immune evasion and tumor proliferation. Knockdown experiments of CDCA7 and CDCA8 in U87MG cells demonstrated a reduction in cell proliferation, colony formation, and migration, highlighting their potential as therapeutic targets.

Conclusion: Overall, our findings suggest that CDCA genes could serve as both diagnostic biomarkers and therapeutic targets for GBM.

Background: Neuroblastoma (NB) is a prevalent extracranial solid tumor in pediatric patients. Of these, the MYCN-amplified type has a poor treatment response and prognosis. To enhance therapeutic efficacy and prognostic outcomes, numerous research teams have undertaken extensive investigations through various pathways and directions. Among these, ferroptosis has recently emerged as a significant area of research focus.Ferroptosis, a type of iron-dependent cell death, is primarily caused by lipid peroxides. This study intends to develop a prognosis model based on MYCN-amplified NB and ferroptosis-related genes (FGs).

Methods: Data for this study were sourced from the TARGET and FerrDb databases. Lasso regression algorithms and univariate COX analysis were leveraged to determine feature genes; multivariate COX analysis was employed to develop a prediction model and risk scores; and receiver operating characteristic (ROC) curves and Kaplan-Meier analysis were utilized to assess the predictive ability of the model. Furthermore, discrepancies in immune cell infiltration (ICI) between the high-risk (HR) and low-risk (LR) populations were assessed via CIBERSORT analysis. Finally, experiments were conducted on MYCN-amplified and MYCN non-amplified cells so as to validate the differential expression of the gene.

Results: A prediction model was constructed and risk scores were calculated based on 4 genes (LIFR, TP53, NRAS, and OSBPL9). The HR group, which was stratified by the median score, had a lower overall survival rate than the LR group.The differences in expression of each gene between MYCN-amplified and MYCN non-amplified cells were further confirmed through cell experiments and qPCR.

Conclusion: The prediction model in this study can be employed to forecast the prognosis of MYCN-amplified NB. These genes may represent promising new ferroptosis-related intervention targets (FITs) in treating MYCN-amplified NB, with the potential to improve patient outcomes.

Background: Genes that participate in the absorption, distribution, metabolism, excretion (ADME) processes occupy a central role in pharmacokinetics. Meanwhile, variability in clinical outcomes and responses to treatment is notable in bladder cancer (BLCA).

Methods: Our study utilized expansive datasets from TCGA and the GEO to explore prognostic factors in bladder cancer. Utilizing both univariate Cox regression and the lasso regression techniques, we identified ADME genes critical for patient outcomes. Utilizing genes identified in our study, a model for assessing risk was constructed. The evaluation of this model's predictive precision was conducted using Kaplan-Meier survival curves and assessments based on ROC curves. Furthermore, we devised a predictive nomogram, offering a straightforward visualization of crucial prognostic indicators. To explore the potential factors mediating the differences in outcomes between high and low risk groups, we performed comprehensive analyses including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)-based enrichment analyses, immune infiltration variations, somatic mutation landscapes, and pharmacological sensitivity response assessment etc. Immediately following this, we selected core genes based on the PPI network and explored the prognostic potential of the core genes as well as immune modulation, and pathway activation. And the differential expression was verified by immunohistochemistry and qRT-PCR. Finally we explored the potential of the core genes as pan-cancer biomarkers.

Results: Our efforts culminated in the establishment of a validated 17-gene ADME-centered risk prediction model, displaying remarkable predictive accuracy for BLCA prognosis. Through separate cox regression analyses, the importance of the model's risk score in forecasting BLCA outcomes was substantiated. Furthermore, a novel nomogram incorporating clinical variables alongside the risk score was introduced. Comprehensive studies established a strong correlation between the risk score and several key indicators: patterns of immune cell infiltration, reactions to immunotherapy, landscape of somatic mutation and profiles of drug sensitivity. We screened the core prognostic gene CYP2C8, explored its role in tumor bioregulation and validated its upregulated expression in bladder cancer. Furthermore, we found that it can serve as a reliable biomarker for pan-cancer.

Conclusion: The risk assessment model formulated in our research stands as a formidable instrument for forecasting BLCA prognosis, while also providing insights into the disease's progression mechanisms and guiding clinical decision-making strategies.

Objective: This study employed bioinformatics techniques to identify diagnostic genes associated with programmed cell death (PCD) and to explore potential therapeutic agents for the treatment of sepsis.

Methods: Gene expression profiles from sepsis patients were analyzed to identify differentially expressed genes (DEGs) and hub genes through Weighted Gene Co-expression Network Analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to elucidate the functions of the DEGs. PCD-related genes were cross-referenced with the identified DEGs. Diagnostic genes were selected using Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF) methodologies. Single-cell RNA sequencing was utilized to assess gene expression in blood cells, while CIBERSORT was employed to evaluate immune cell infiltration. A transcription factor (TF)-microRNA (miRNA)-hub gene network was constructed, and potential therapeutic compounds were predicted using the Drug Gene Interaction Database (DGIdb). Mendelian Randomization (MR) methods were applied to analyze genome-wide association study (GWAS) data for S100A9, TXN, and GSTO1.

Results: The analysis revealed 2156 PCD-related genes, 714 DEGs, and 1198 hub genes, with 88 genes enriched in immune and cell death pathways. Five pivotal PCD-related genes (IRAK3, S100A9, TXN, NFATC2, and GSTO1) were identified, leading to the construction of a network comprising six transcription factors and 171 microRNAs. Additionally, seven drugs targeting S100A9, TXN, and NFATC2 were identified. MR analysis suggested that a decrease in GSTO1 levels is associated with an increased risk of sepsis, and that sepsis influences the levels of S100A9, TXN, and GSTO1.

Conclusions: Through bioinformatics approaches, this study successfully identified five genes (IRAK3, S100A9, TXN, NFATC2, and GSTO1) associated with programmed cell death in the context of sepsis. This research identified seven candidate drugs for sepsis treatment and established a methodological framework for predicting biomarkers and drug targets that could be applicable to other diseases.

Background: Nasopharyngeal carcinoma (NPC) is a malignant head and neck cancer with high mortality and dismal prognosis. Emerging research have disclosed that circRNAs are crucial gene expression regulators engaged in tumor advancement. This work aspired to identify novel oncogenic circRNA driving NPC progression.

Methods: Bioinformatics analysis was performed to explore and predict underlying circRNA and downstream targets. Luciferase reporter assay was executed to check the binding relationship between these genes. Cell function tests were conducted using CCK-8, would healing, and flow cytometry. The stemness markers CD133, Nanog and Oct4 was detected via western blot.

Results: CircCENPM was notably enhanced in NPC. Silencing of circCENPM suppressed NPC cell growth, migration, and stemness in vitro, simultaneously impeded tumorigenesis of NPC in vivo. Moreover, circCENPM could interact with miR-362-3p, whereas miR-362-3p inhibitor apparently reversed the mitigated growth and stemness induced by circCENPM knockdown in NPC cells. Furthermore, BMI1 was identified to be the downstream target of miR-362-3p, and BMI1 introduction partially offset the anti-tumor function of miR-362-3p in NPC cells.

Conclusion: CircCENPM functioned as a carcinogenic driver and facilitated NPC growth and stemness via miR-362-3p/BMI1 regulatory network, which provided a potential biomarker and attractive target for NPC intervention and treatment.

Background: Blood metabolites play an important role in predicting or influencing the occurrence and development of cancers. We aimed to evaluate the relationship between blood metabolites and the occurrence of head and neck cancer (HNC).

Methods: We employed a Mendelian randomization (MR) approach to investigate the role of blood metabolites in HNC predisposition. The HNC cell line HN30 was treated with butyrylcarnitine, the metabolite identified through MR analysis, and subjected to a series of cellular assays to assess its potential carcinogenic effects.

Results: Among the 258 blood metabolites analyzed, butyrylcarnitine emerged as the only metabolite demonstrating a potential causal association with HNC risk following Bonferroni correction (inverse-variance-weighted MR method: β = 0.904, P < 0.001). Genetically predicted higher levels of butyrylcarnitine (log-transformed) were causally linked to an increased risk of HNC (OR: 2.470, 95% CI: 1.530-3.987). Sensitivity analyses, including MR-Egger regression, leave-one-out analysis, and funnel plots, confirmed the robustness of the findings, with no evidence of directional pleiotropy. In vitro experiments further demonstrated that butyrylcarnitine promoted the proliferation, migration and invasion of HN30 cells.

Conclusions: By employing a genetic epidemiological framework, our research assessed the impact of metabolite butyrylcarnitine on HNC susceptibility. These findings offer valuable insights into potential therapeutic targets and highlight the promise of targeted metabolic strategies for reducing HNC risk. Nevertheless, further research is required to elucidate the precise biological mechanisms underlying these findings.

Cholecystectomy is often excessively utilized in the management of gallbladder polyps. It is crucial to effectively differentiate between adenomatous and cholesterol polyps to reduce unnecessary cholecystectomies. This study aimed to investigate the potential of miR-33 as a novel diagnostic biomarker for distinguishing cholesterol from adenomatous polyps. Gallbladder specimens were retrospectively collected from gallbladder polyp patients who underwent laparoscopic cholecystectomy at the Second Department of General Surgery, Dongzhimen Hospital, Beijing University of Traditional Chinese Medicine, between June 2021 and December 2021. Pathological analysis categorized the specimens into two groups: the cholesterol polyp group (n = 13) and the adenomatous polyp group (n = 12). The expression levels of miR-33a and miR-33b in both groups were assessed using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). MiR-33a level and the miR-33a/miR-33b ratio were significantly lower in cholesterol polyps than in adenomatous polyps (p < 0.05). Spearman correlation analysis showed a strong positive correlation between miR-33a and miR-33b (r = 0.956, p < 0.001). Stepwise logistic regression analysis revealed that decreased miR-33b and elevated miR-33a/miR-33b ratio are independent risk factors for cholesterol polyps (p < 0.05). A predictive model was constructed, with the model's AUC for diagnosing adenomatous polyps being 0.885 (95% CI: 0.753-1.000, p = 0.001), exhibiting a notable specificity of 84.62% and a sensitivity of 83.33% at a cut-off of 0.424. MiR-33 could serve as a novel diagnostic biomarker for distinguishing cholesterol from adenomatous polyps to facilitate the diagnosis and treatment of clinicians.

Background: The screening and monitoring of gastric cancer is still a clinical challenge. Both N⁶-methyladenosine (m⁶A) and lncRNAs have been evidenced as critical regulators of gastric cancer, but their interaction and potential in modulating tumor progression remain unclear. This study aimed to evaluate the function of lncRNA LINC00968 in gastric cancer biological processes, and we discovered the role of KIAA1429, a typical m⁶A eraser, in mediating LINC00968 function.

Materials and methods: The expression of LINC00968 was assessed using PCR and regulated by cell transfection. Cellular processes were evaluated by CCK8 and Transwell assays. The m⁶A modification and the interaction of LINC00968 with KIAA1429 were identified with Methylated RNA immunoprecipitation-qPCR. The regulatory effect of LINC00968 on miR-3202 and VIRMA was estimated by luciferase reporter assay.

Results: Significantly increased LINC00968 was observed in gastric cancer cells. Silencing LINC00968 suppressed gastric cancer cell growth and motility. m⁶A-modified sites were predicted in LINC00968 and overexpressing KIAA1429 enhanced the enrichment and stability of LINC00968 in gastric cancer and reversed the knockdown of LINC00968. The overexpression of KIAA1429 could attenuate the inhibitory effect of LINC00968 knockdown on gastric cancer cellular processes. LINC00968 could negatively regulate the expression of miR-3202, which further regulate VIRMA, the coding gene of KIAA1429, in gastric cancer cells.

Conclusions: LINC00968 contributes to the enhanced cell growth and metastasis of gastric cancer, which was mediated by KIAA1429-mediating m⁶A modification and the miR-3202/VIRMA axis.

Background: Acute myocardial infarction (AMI) is the primary cause of cardiac mortality worldwide. However, myocardial ischemia-reperfusion injury (MIRI) following reperfusion therapy is common in AMI, causing myocardial damage and affecting the patient's prognosis. Presently, there are no effective treatments available for MIRI.

Methods: We performed a comprehensive bioinformatics analysis using three GEO datasets on differentially expressed genes, including gene ontology (GO), pathway enrichment analyses, and protein-protein interaction (PPI) network analysis. Cytoscape and LASSO methods were employed to identify novel regulator genes for ischemia-reperfusion (I/R). Notably, gene S100A9 was identified as a potential regulator of I/R. Additionally, clinical sample datasets were analyzed to prove the expression and mechanism of S100A9 and its down genes in I/R. The correlation of S100A9 with cardiac events was also examined to enhance the reliability of our results.

Results: We identified 135 differential genes between the peripheral blood of 47 controls and 92 I/R patients. S100A9 was distinguished as a novel regulator gene of I/R with diagnostic potential. RT-qPCR test demonstrated significant upregulation of S100A9 in I/R. We also verified that S100A9 expression strongly correlates with left ventricular ejection fraction (LVEF) and MIRI.

Conclusion: This study confirms that S100A9 is a key regulator of I/R progression and may participate in ischemia-reperfusion injury by upregulating RAGE /NFKB-NLRP3 activation. Elevated S100A9 levels may serve as a marker for identifying high-risk MIRI patients, especially those with coronary artery no-reflow (CNR), who might benefit from targeted therapeutic interventions. Furthermore, Peripheral blood S100A9 in AMI represents a new therapeutic target for preventing MIRI.