To evaluate the clinical utility of combined SHOX2 and RASSF1A methylation analysis in bronchoalveolar lavage fluid (BALF) for lung cancer diagnosis using methylation-specific PCR (MSP). The study aimed to combine BALF methylation results with bronchoscopic cytology, serum tumor markers, and imaging data to assess their diagnostic value. A total of 77 patients were recruited and divided into two groups: 57 patients with lung cancer and 20 control subjects. The methylation levels of SHOX2 and RASSF1A in BALF samples were analyzed using MSP. General data, serum markers, imaging, cytology, and pathology results were collected. The methylation levels were compared between the two groups, and differences in methylation levels across different pathological types and stages were analyzed. Receiver operating characteristic (ROC) curves were constructed to determine the cutoff values. The diagnostic performance of combined SHOX2 and RASSF1A methylation testing was compared with serum markers and cytology. The combined SHOX2 and RASSF1A methylation test showed a sensitivity of 68.42% and a specificity of 95%, significantly improving the detection rate of lung adenocarcinoma. Higher methylation levels were observed in advanced-stage lung cancer compared with early-stage cases. The combined SHOX2 and RASSF1A methylation test exhibited the highest sensitivity, with an area under the curve (AUC) of 0.817, compared with carcinoembryonic antigen (CEA), cytokeratin 19 fragment 21-1 (CY211), and BALF cytology. The combined use of BALF cytology and methylation testing increased the detection rate to 73.68%, higher than BALF cytology alone (40.35%). The odds ratio for positive SHOX2 and RASSF1A methylation in patients with bronchial cutoff signs was 15.167. Combined SHOX2 and RASSF1A methylation testing can serve as an auxiliary diagnostic tool for lung cancer, outperforming serum markers and BALF cytology in diagnostic efficacy. Additionally, it can complement BALF cytology and provide a more accurate diagnosis. The presence of bronchial cutoff signs can be used as a relevant factor to predict positive SHOX2 and RASSF1A methylation.
The pursuit of effective immunotherapy for lung adenocarcinoma (LUAD) is ongoing. Lactylation is a promising target for cancer management; yet role of lactylation-related genes (LRGs) in LUAD is still largely unexplored. This study was designed to identify genes related to lactylation in LUAD to assist in prognostic treatment. The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) database, and related literature were accessed to download gene expression and clinical information. To screen LRGs and create a prognostic model, univariate Cox, multivariate Cox, and Lasso regression analyses were then employed. Based on the median risk score, patients were categorized into high-and low-risk groups, and survival analysis and model validation were done. A nomogram was created, and its capacity for prediction was assessed by plotting ROC and DCA curves. To build PPI networks, enrichment, immune microenvironment, immunotherapy response, and tumor mutation analyses, and medication prediction were completed on differentially expressed genes between high-and low-risk groups. Prognostic model was built using LRGs associated with LUAD prognosis (HNRNPAB, PSMB2, DDX5, SURF6, HOMER3, ENO2, and HSPA1L). Patients' survival in high-risk group was noticeably lower. Risk scores can be included into a nomogram or be utilized as an independent component for prognosis prediction. These genes were mostly concentrated in cAMP signaling pathway, Neuroactive ligand-receptor interaction, and hormone-related pathways. Immunological milieu of high-risk group was compromised, as evidenced by their lower IPS and higher TIDE scores. There was a chance that AP-24534 (low-risk group) and CGP-082996 (high-risk group) might work. To synthesize, the LRGs-LUAD prognostic model came as a viable instrument for forecasting the prognosis of LUAD patients, bolstering clinical practice in prognostic risk appraisal and patient-specific treatment.
Background: N-nitrosodimethylamine (NDMA), a prevalent environmental contaminant found in food, water, and pharmaceuticals, is a recognized carcinogen strongly associated with colorectal cancer (CRC). However, the precise molecular mechanisms underlying NDMA-induced colorectal carcinogenesis remain incompletely understood. This study aimed to systematically investigate the molecular interactions between NDMA and CRC-related proteins to uncover potential mechanisms and therapeutic targets. Methods: We employed an integrated computational approach combining network toxicology and molecular docking. NDMA targets were identified using ChEMBL, STITCH, SwissTargetPrediction, and PharmMapper databases. CRC-associated genes were retrieved from GeneCards, OMIM, and TTD databases. Protein-protein interaction networks were constructed using STRING and analyzed with Cytoscape. Hub genes were identified through centrality analysis, validated using TCGA expression data, and subjected to molecular docking with AutoDock Vina. Results: We identified 370 NDMA targets and 1,575 CRC-related genes, with 91 overlapping genes representing potential mediators of NDMA-induced carcinogenesis. Enrichment analysis revealed significant involvement of xenobiotic response, MAPK signaling, and extracellular matrix remodeling pathways. Network analysis identified TP53, HSP90AB1, and HSP90AA1 as critical hub genes, all showing significant differential expression in CRC tissues (p < 0.05). Molecular docking revealed direct binding of NDMA to TP53 (-4.2 kcal/mol), HSP90AB1 (-4.6 kcal/mol), and HSP90AA1 (-3.8 kcal/mol), suggesting potential functional interference beyond genotoxic effects. Conclusion: This study elucidates multi-faceted mechanisms of NDMA-induced colorectal carcinogenesis, identifying TP53, HSP90AB1, and HSP90AA1 as key molecular targets. The convergence of network analysis, expression validation, and structural predictions provides a comprehensive framework for understanding NDMA toxicity and offers potential targets for preventing CRC in exposed populations.
Although aluminum is the third common metal of the earth, it is physiologically nonessential and its higher levels on regular exposure can be harmful to the human body, affecting several vital organ systems. Environmental aluminum contamination and toxicity are therefore regarded as a "silent killer" as it is associated with the precipitation of several serious health complications chiefly involving the nervous, blood, and musculoskeletal systems. Various natural products obtained from medicinal plants; that is, phytochemicals have been reported to possess aluminum toxicity ameliorative potential. Still now, there is no comprehensive review in this regard. A compilation of research has been published over the past 21 years on the protective properties of plant-derived phytochemicals against the toxicity of aluminum. Reportedly, 45 phytochemicals of diverse chemical classes mitigate the toxicity of experimental aluminum in animals/cells/tissues, leading to marked reduction of aluminum-induced pathophysiological complications, by multiple mechanisms; the prime typical modes, among others, are modulation of oxidative stress-inflammatory pathways and anti-cholinesterase activity. These recent advances may help to develop a potential nutraceutical or phytomedicinal candidate against aluminum toxicity and neurodegenerative diseases for humans.
BACKGROUND:The Mitogen-Activated Protein Kinase (MAPK) signaling pathway is significant in clinical practice for its potential to impede tumor proliferation and migration and to enhance patient prognosis. Yet, the specific contributions of MAPK-related genes to the prognosis of colorectal cancer (CRC) are not clear. METHODS:CRC data was retrieved from TCGA and GEO databases, with the MAPK pathway genes being identified from Kyoto Encyclopedia of Genes and Genomes (KEGG). A risk signature model for CRC associated with the MAPK pathway was formulated using regression analysis. The tumor immune microenvironment of high- and low-risk groups was assessed using single sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithms. We also looked into the potential differential response to immunotherapy by comparing immune checkpoints, immunophenoscore (IPS) scores, and Tumor Immune Dysfunction and Exclusion (TIDE) scores between the two groups. Moreover, the sensitivity to CRC treatment drugs in high- and low-risk groups was probed by forecasting drug IC50 values with the pRRophetic R package. RESULTS:A risk model was established using eight distinct genes (CDC42, CACNA1D, EREG, TRAF2, MAPKAPK3, DDIT3, NGF, TGFB2) identified from the differential expression of MAPK-related genes. The analysis highlighted that patients in the high-risk group had a higher degree of immune cell infiltration but were less sensitive to immunotherapy (indicated by higher TIDE and lower IPS scores). Drug sensitivity predictions suggested that the high-risk group, despite their poor immunotherapy response, had an increased sensitivity to drugs such as Pazopanib, WH-4-023, and WZ-1-84. CONCLUSION:To encapsulate our findings, we have determined eight MAPK pathway-associated CRC prognostic biomarkers and developed a prognostic model accordingly. This model has proven effective in stratifying the risk levels among CRC patients.
