DNA Methylation-Mediated Lowly Expressed AOX1 Promotes Cell Migration and Invasion of Prostate Cancer

A Highly Sensitive Methylation Assay for Prostate Cancer Diagnosis

PURPOSE

Prostate cancer is a prevalent malignancy among males, necessitating precise diagnosis for effective treatment and prognosis. However, there is a lack of accurate, reliable, and cost-effective methods for precise diagnosis of prostate cancer.

MATERIALS AND METHODS

The bisulfite-treated DNA was amplified by a blocker strand-assisted methylation-specific PCR method, and the signal was amplified by a guiding strand-assisted enzyme/probe detection system. On this basis, an Optimized DNA Methylation Detection Assay was developed. Fifty-five prostate cancer patients and 24 healthy patients were selected for blood/urine sample testing to evaluate the clinical value of the assay.

RESULTS

The experimental results showed that the detection limit of the Tri-Component Liquid Biopsy Assay reached 0.002%. Assays for six prostate cancer methylation variants were constructed and finally three sites, GSTP1, ADCY4, and HOXA7, were selected for the design of prostate cancer diagnostic panel. The differences in methylation were statistically significant. Additionally, evaluating this approach on liquid biopsies from prostate cancer patients, we obtained a sensitivity and specificity of 89% and 76% respectively. Meanwhile, the cost of a single test on this platform is about $7.5, and the testing time is only about 5 hours.

CONCLUSIONS

Here we have successfully developed a highly sensitive methylation assay for prostate cancer diagnosis that features both accuracy, efficiency, and low cost. Combined with the established detection panel, this method can realize accurate and non-invasive early diagnosis of prostate cancer, which substantially augments the pragmatic utility of liquid biopsy.

Interactions between NAD+ metabolism and immune cell infiltration in ulcerative colitis: subtype identification and development of novel diagnostic models

Background

Ulcerative colitis (UC) is a chronic inflammatory disease of the colonic mucosa with increasing incidence worldwide. Growing evidence highlights the pivotal role of nicotinamide adenine dinucleotide (NAD+) metabolism in UC pathogenesis, prompting our investigation into the subtype-specific molecular underpinnings and diagnostic potential of NAD+ metabolism-related genes (NMRGs).

Methods

Transcriptome data from UC patients and healthy controls were downloaded from the GEO database, specifically GSE75214 and GSE87466. We performed unsupervised clustering based on differentially expressed NAD+ metabolism-related genes (DE-NMRGs) to classify UC cases into distinct subtypes. GSEA and GSVA identified potential biological pathways active within these subtypes, while the CIBERSORT algorithm assessed differential immune cell infiltration. Weighted gene co-expression network analysis (WGCNA) combined with differential gene expression analysis was used to pinpoint specific NMRGs in UC. Robust gene features for subtyping and diagnosis were selected using two machine learning algorithms. Nomograms were constructed and their effectiveness was evaluated using receiver operating characteristic (ROC) curves. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was conducted to verify gene expression in cell lines.

Results

In our study, UC patients were classified into two subtypes based on DE-NMRGs expression levels, with Cluster A exhibiting enhanced self-repair capabilities during inflammatory responses and Cluster B showing greater inflammation and tissue damage. Through comprehensive bioinformatics analyses, we identified four key biomarkers (AOX1, NAMPT, NNMT, PTGS2) for UC subtyping, and two (NNMT, PARP9) for its diagnosis. These biomarkers are closely linked to various immune cells within the UC microenvironment, particularly NAMPT and PTGS2, which were strongly associated with neutrophil infiltration. Nomograms developed for subtyping and diagnosis demonstrated high predictive accuracy, achieving area under curve (AUC) values up to 0.989 and 0.997 in the training set and up to 0.998 and 0.988 in validation sets. RT-qPCR validation showed a significant upregulation of NNMT and PARP9 in inflamed versus normal colonic epithelia, underscoring their diagnostic relevance.

Conclusion

Our study reveals two NAD+ subtypes in UC, identifying four biomarkers for subtyping and two for diagnosis. These findings could suggest potential therapeutic targets and contribute to advancing personalized treatment strategies for UC, potentially improving patient outcomes.

Cellular Signaling of Amino Acid Metabolism in Prostate Cancer

Prostate cancer is one of the most common malignancies affecting men worldwide and a leading cause of cancer-related mortality, necessitating a deeper understanding of its underlying biochemical pathways. Similar to other cancer types, prostate cancer is also characterised by aberrantly activated metabolic pathways that support tumour development, such as amino acid metabolism, which is involved in modulating key physiological and pathological cellular processes during the progression of this disease. The metabolism of several amino acids, such as glutamine and methionine, crucial for tumorigenesis, is dysregulated and commonly discussed in prostate cancer. And the roles of some less studied amino acids, such as histidine and glycine, have also been covered in prostate cancer studies. Aberrant regulation of two major signalling pathways, mechanistic target of rapamycin (mTOR) and general amino acid control non-depressible 2 (GCN2), is a key driver of reshaping the amino acid metabolism landscape in prostate cancer. By summarising our current understanding of how amino acid metabolism is modulated in prostate cancer, here, we provide further insights into certain potential therapeutic targets for managing prostate cancer through metabolic interventions.

Comprehensive analysis of abnormal methylation modification differential expression mRNAs between low-grade and high-grade intervertebral disc degeneration and its correlation with immune cells

BACKGROUND

Intervertebral disc degeneration (IDD) is an important cause of low back pain. The aim of this study is to identify the potential molecular mechanism of abnormal methylation-modified DNA in the progression of IDD, hoping to contribute to the diagnosis and management of IDD.

METHODS

Low-grade IDD (grade I-II) and high-grade IDD (grade III-V) data were downloaded from GSE70362 and GSE129789 datasets. The abnormally methylated modified differentially expressed mRNAs (DEmRNAs) were identified by differential expression analysis (screening criteria were p < .05 and |logFC| > 1) and differential methylation analysis (screening criteria were p < .05 and |δβ| > 0.1). The classification models were constructed, and the receiver operating characteristic analysis was also carried out. In addition, functional enrichment analysis and immune correlation analysis were performed and the miRNAs targeted for the abnormally methylated DEmRNAs were predicted. Finally, expression validation was performed using real-time PCR.

RESULTS

Compared with low-grade IDD, seven abnormal methylation-modified DEmRNAs (AOX1, IBSP, QDPR, ABLIM1, CRISPLD2, ACTC1 and EMILIN1) were identified in high-grade IDD, and the classification models of random forests (RF) and support vector machine (SVM) were constructed. Moreover, seven abnormal methylation-modified DEmRNAs and classification models have high diagnostic accuracy (area under the curve [AUC] > 0.8). We also found that AUC values of single abnormal methylation-modified DEmRNA were all lower than those of RF and SVM classification models. Pearson correlation analysis found that macrophages M2 and EMILIN1 had significant negative correlation, while macrophages M2 and IBSP had significant positive correlation. In addition, four targeted relationship pairs (hsa-miR-4728-5p-QDPR, hsa-miR-4533-ABLIM1, hsa-miR-4728-5p-ABLIM1 and hsa-miR-4534-CRISPLD2) and multiple signalling pathways (for example, PI3K-AKT signalling pathway, osteoclast differentiation and calcium signalling pathway) were also identified that may be involved in the progression of IDD.

CONCLUSION

The identification of abnormal methylation-modified DEmRNAs and the construction of classification models in this study were helpful for the diagnosis and management of IDD progression.

Aldehyde oxidase 1 promotes gallbladder carcinogenesis through ROS-mediated activation of the Wnt/β-catenin pathway

BACKGROUND

Aldehyde oxidase 1 (AOX1) is associated with various pathophysiological processes, including cancer. Specifically, AOX1 has been demonstrated to have a close relationship with the progression of certain cancers. However, the expression, function, and mechanisms of action of AOX1 in gallbladder cancer (GBC) remain unclear.

METHODS

Utilizing immunohistochemistry, the study quantified the prevalence of AOX1 within tissues of gallbladder carcinoma and those of the surrounding non-cancerous regions. In vitro assays using gallbladder carcinoma cell lines with modulated AOX1 expression levels were performed to assess the protein's role in cell proliferation, migration, and invasion. Furthermore, flow cytometry techniques were harnessed to determine the influence of AOX1 on the content of reactive oxygen species (ROS) in these cells. Additionally, the expression of epithelial-mesenchymal transition (EMT) markers and the Wnt/β-catenin signaling pathway markersin cells with varied AOX1 expression, detected through Western blot analyses. An in vivo xenograft model involving athymic mice was implemented to explore the influence of AOX1 on gallbladder tumor growth, with Western blot analysis applied to measure EMT marker expression in the resulting tumours.

RESULTS

Elevated AOX1 protein levels have been observed in gallbladder carcinoma tissues, with such upregulation linked to a negative prognostic outlook for patients. In vitro analyses demonstrate that enhanced AOX1 expression facilitates gallbladder carcinoma cell proliferation, migration, and invasion, while AOX1 suppression yields an inhibitory effect on these cellular behaviors. Western blot results reveal an inverse relationship between AOX1 and E-cadherin levels, yet was positively correlation with N-cadherin, Vimentin, and Snail within both gallbladder cancer cells and in vivo xenograft tumours. Further mechanistic investigation indicates that AOX1 elevation augments reactive oxygen species (ROS) production and initiates the Wnt/β-catenin signaling pathway in these cells. The application of N-acetylcysteine (NAC) and/or KY1797K attenuates the proliferative, migratory, and invasive enhancements imparted by AOX1 overexpression and reinforces these effects when AOX1 is silenced-achieved through ROS mitigation and the obstruction of the Wnt/β-catenin pathway. In vivo studies corroborate these findings, showing AOX1 overexpression to amplify xenograft tumor growth and mesenchymal marker expression, whereas AOX1 interference did the opposite.

CONCLUSIONS

The study indicates that AOX1 functions as a carcinogenic factor in gallbladder carcinoma, enhancing cell proliferation, migration, invasion, and the EMT. These effects are driven by the activation of the Wnt/β-catenin pathway mediated by reactive oxygen species (ROS). Therefore,AOX1 presents potential as a valuable prognostic and diagnostic marker as well as a target for therapeutic intervention in the gallbladder cancer.

Identification and validation of immune-related hub genes based on machine learning in prostate cancer and AOX1 is an oxidative stress-related biomarker

To investigate potential diagnostic and prognostic biomarkers associated with prostate cancer (PCa), we obtained gene expression data from six datasets in the Gene Expression Omnibus (GEO) database. The datasets included 127 PCa cases and 52 normal controls. We filtered for differentially expressed genes (DEGs) and identified candidate PCa biomarkers using a least absolute shrinkage and selector operation (LASSO) regression model and support vector machine recursive feature elimination (SVM-RFE) analyses. A difference analysis was conducted on these genes in the test group. The discriminating ability of the train group was determined using the area under the receiver operating characteristic curve (AUC) value, with hub genes defined as those having an AUC greater than 85%. The expression levels and diagnostic utility of the biomarkers in PCa were further confirmed in the GSE69223 and GSE71016 datasets. Finally, the invasion of cells per sample was assessed using the CIBERSORT algorithm and the ESTIMATE technique. The possible prostate cancer (PCa) diagnostic biomarkers AOX1, APOC1, ARMCX1, FLRT3, GSTM2, and HPN were identified and validated using the GSE69223 and GSE71016 datasets. Among these biomarkers, AOX1 was found to be associated with oxidative stress and could potentially serve as a prognostic biomarker. Experimental validations showed that AOX1 expression was low in PCa cell lines. Overexpression of AOX1 significantly reduced the proliferation and migration of PCa cells, suggesting that the anti-tumor effect of AOX1 may be attributed to its impact on oxidative stress. Our study employed a comprehensive approach to identify PCa biomarkers and investigate the role of cell infiltration in PCa.