Nicotinamide N-Methyltransferase and Its Precursor Substrate Methionine Directly and Indirectly Control Malignant Metabolism During Progression of Renal Cell Carcinoma

Nicotinamide N-Methyltransferase (NNMT) is Involved in Gastric Adenocarcinoma Immune Infiltration by Driving Amino Acid Metabolism

Objectives: This study investigates the role of Nicotinamide N-methyltransferase (NNMT) in immune infiltration modulation through amino acid metabolism in gastric adenocarcinoma (STAD). Methods: Utilizing data from The Cancer Genome Atlas (TCGA) and validated with clinical samples, we analyzed NNMT expression and its prognostic implications in STAD. Differential amino acid profiles between cancerous and adjacent normal tissues were assessed, along with their associations with NNMT. Results: NNMT exhibits heightened expression in STAD cancer tissues, positively correlating with tumor immune infiltration. Additionally, twenty-eight amino acids display differential expression in gastric tissue, with their metabolic enzymes showing connections to NNMT. Conclusions: Elevated NNMT expression in STAD tissues potentially influences amino acid metabolism, thereby affecting immune infiltration dynamics and tumorigenesis in gastric adenocarcinoma.

Identification and validation of m6A-associated ferroptosis genes in renal clear cell carcinoma

Urinary cancer is synonymous with clear cell renal cell carcinoma (ccRCC). Unfortunately, existing treatments for this illness are ineffective and unpromising. Finding novel ccRCC biomarkers is crucial to creating successful treatments. The Cancer Genome Atlas provided clear cell renal cell carcinoma transcriptome data. Functional enrichment analysis was performed on ccRCC and control samples' differentially expressed N6-methyladenosine RNA methylation and ferroptosis-related genes (DEMFRGs). Machine learning was used to find and model ccRCC patients' predicted genes. A nomogram was created for clear cell renal cell carcinoma patients. Prognostic genes were enriched. We examined patients' immune profiles by risk score. Our prognostic genes predicted ccRCC treatment drugs. We found 37 DEMFRGs by comparing 1913 differentially expressed ccRCC genes to 202 m6A RNA methylation FRGs. Functional enrichment analysis showed that hypoxia-induced cell death and metabolism pathways were the most differentially expressed methylation functional regulating genes. Five prognostic genes were found by machine learning: TRIB3, CHAC1, NNMT, EGFR, and SLC1A4. An advanced renal cell carcinoma nomogram with age and risk score accurately predicted the outcome. These five prognostic genes were linked to various cancers. Immunological cell number and checkpoint expression differed between high- and low-risk groups. The risk model successfully predicted immunotherapy outcome, showing high-risk individuals had poor results. NIACIN, TAE-684, ROCILETINIB, and others treat ccRCC. We found ccRCC prognostic genes that work. This discovery may lead to new ccRCC treatments.

Elevated Plasma Concentration of 4-Pyridone-3-carboxamide-1-β-D-ribonucleoside (4PYR) Highlights Malignancy of Renal Cell Carcinoma

Nicotinamide (NA) derivatives play crucial roles in various biological processes, such as inflammation, regulation of the cell cycle, and DNA repair. Recently, we proposed that 4-pyridone-3-carboxamide-1-β-D-ribonucleoside (4PYR), an unusual derivative of NA, could be classified as an oncometabolite in bladder, breast, and lung cancer. In this study, we investigated the relations between NA metabolism and the progression, recurrence, metastasis, and survival of patients diagnosed with different histological subtypes of renal cell carcinoma (RCC). We identified alterations in plasma NA metabolism, particularly in the clear cell RCC (ccRCC) subtype, compared to papillary RCC, chromophobe RCC, and oncocytoma. Patients with ccRCC also exhibited larger tumor sizes and elevated levels of diagnostic serum biomarkers, such as hsCRP concentration and ALP activity, which were positively correlated with the plasma 4PYR. Notably, 4PYR levels were elevated in advanced stages of ccRCC cancer and were associated with a highly aggressive phenotype of ccRCC. Additionally, elevated concentrations of 4PYR were related to a higher likelihood of mortality, recurrence, and particularly metastasis in ccRCC. These findings are consistent with other studies, suggesting that NA metabolism is accelerated in RCC, leading to abnormal concentrations of 4PYR. This supports the concept of 4PYR as an oncometabolite and a potential prognostic factor in the ccRCC subtype.

Novel amino acid metabolism‐related gene signature to predict prognosis in clear cell renal cell carcinoma

Background: Amino acid metabolism (AAM) deregulation, an emerging metabolic hallmark of malignancy, plays an essential role in tumour proliferation, invasion, and metastasis. However, the expression of AAM-related genes and their correlation with prognosis in clear cell renal cell carcinoma (ccRCC) remain elusive. This study aims to develop a novel consensus signature based on the AAM-related genes.

Methods: The RNA-seq expression data and clinical information for ccRCC were downloaded from the TCGA (KIRC as training dataset) and ArrayExpress (E-MTAB-1980 as validation dataset) databases. The AAM‐related differentially expressed genes were screened via the “limma” package in TCGA cohorts for further analysis. The machine learning algorithms (Lasso and stepwise Cox (direction = both)) were then utilised to establish a novel consensus signature in TCGA cohorts, which was validated by the E-MTAB-1980 cohorts. The optimal cutoff value determined by the “survminer” package was used to categorise patients into two risk categories. The Kaplan-Meier curve, the receiver operating characteristic (ROC) curve, and multivariate Cox regression were utilised to evaluate the prognostic value. The nomogram based on the gene signature was constructed, and its performance was analysed using ROC and calibration curves. Gene Set Enrichment Analysis (GSEA) and immune cell infiltration analysis were conducted on its potential mechanisms. The relationship between the gene signature and key immune checkpoint, N6-methyladenosine (m⁶A)-related genes, and sensitivity to chemotherapy was assessed.

Results: A novel consensus AMM‐related gene signature consisting of IYD, NNMT, ACADSB, GLDC, and PSAT1 is developed to predict prognosis in TCGA cohorts. Kaplan-Meier survival shows that overall survival in the high-risk group was more dismal than in the low-risk group in the TCGA cohort, validated by the E-MTAB-1980 cohort. Multivariate regression analysis also demonstrates that the gene signature is an independent predictor of ccRCC. Immune infiltration analysis highlighted that the high-risk group indicates an immunosuppressive microenvironment. It is also closely related to the level of key immune checkpoints, m⁶A modification, and sensitivity to chemotherapy drugs.

Conclusion: In this study, a novel consensus AAM-related gene signature is developed and validated as an independent predictor to robustly predict the overall survival from ccRCC, which would further improve the clinical outcomes.

Nicotinamide N-Methyltransferase: A Promising Biomarker and Target for Human Cancer Therapy

Cancer cells typically exhibit a tightly regulated program of metabolic plasticity and epigenetic remodeling to meet the demand of uncontrolled cell proliferation. The metabolic-epigenetic axis has recently become an increasingly hot topic in carcinogenesis and offers new avenues for innovative and personalized cancer treatment strategies. Nicotinamide N-methyltransferase (NNMT) is a metabolic enzyme involved in controlling methylation potential, impacting DNA and histone epigenetic modification. NNMT overexpression has been described in various solid cancer tissues and even body fluids, including serum, urine, and saliva. Furthermore, accumulating evidence has shown that NNMT knockdown significantly decreases tumorigenesis and chemoresistance capacity. Most importantly, the natural NNMT inhibitor yuanhuadine can reverse epidermal growth factor receptor tyrosine kinase inhibitor resistance in lung cancer cells. In this review, we evaluate the possibility of NNMT as a diagnostic biomarker and molecular target for effective anticancer treatment. We also reveal the exact mechanisms of how NNMT affects epigenetics and the development of more potent and selective inhibitors.

Methylosystem for Cancer Sieging Strategy

As cancer is a genetic disease, methylation defines a biologically malignant phenotype of cancer in the association of one-carbon metabolism-dependent S-adenosylmethionine (SAM) as a methyl donor in each cell. Methylated substances are involved in intracellular metabolism, but via intercellular communication, some of these can also be secreted to affect other substances. Although metabolic analysis at the single-cell level remains challenging, studying the "methylosystem" (i.e., the intercellular and intracellular communications of upstream regulatory factors and/or downstream effectors that affect the epigenetic mechanism involving the transfer of a methyl group from SAM onto the specific positions of nucleotides or other metabolites in the tumor microenvironment) and tracking these metabolic products are important research tasks for understanding spatial heterogeneity. Here, we discuss and highlight the involvement of RNA and nicotinamide, recently emerged targets, in SAM-producing one-carbon metabolism in cancer cells, cancer-associated fibroblasts, and immune cells. Their significance and implications will contribute to the discovery of efficient methods for the diagnosis of and therapeutic approaches to human cancer.

Macrocyclic peptides as allosteric inhibitors of nicotinamide N-methyltransferase (NNMT)

Nicotinamide N-methyltransferase (NNMT) methylates nicotinamide to form 1-methylnicotinamide (MNA) using S-adenosyl-l-methionine (SAM) as the methyl donor. The complexity of the role of NNMT in healthy and disease states is slowly being elucidated and provides an indication that NNMT may be an interesting therapeutic target for a variety of diseases including cancer, diabetes, and obesity. Most inhibitors of NNMT described to date are structurally related to one or both of its substrates. In the search for structurally diverse NNMT inhibitors, an mRNA display screening technique was used to identify macrocyclic peptides which bind to NNMT. Several of the cyclic peptides identified in this manner show potent inhibition of NNMT with IC₅₀ values as low as 229 nM. The peptides were also found to downregulate MNA production in cellular assays. Interestingly, substrate competition experiments reveal that these cyclic peptide inhibitors are noncompetitive with either SAM or NA indicating they may be the first allosteric inhibitors reported for NNMT.

Nicotinamide N-Methyltransferase Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Gastric Cancer

Gastric cancer (GC) is the third most common cause of cancer-related death in the word. Immunotherapy is a promising treatment of cancer. However, it is unclear which GC subpopulation would benefit most from immunotherapy and it is necessary to develop effective biomarkers for predicting immunotherapy response. Nicotinamide N-methyltransferase (NNMT) is a metabolic regulator of cancer-associated fibroblast (CAF) differentiation and cancer progression. In this study, we explored the correlations of NNMT to tumor-infiltrating immune cells (TIICs) and immune marker sets in The Cancer Genome Atlas Stomach Adenocarcinoma STAD (TCGA-STAD). Subsequently, we screened the NNMT correlated genes and performed the enrichment analysis of these genes. We eventually predicted the 19 most potential small-molecule drugs using the connectivity map (CMap) and Comparative Toxicogenomics Database (CTD). Also, nadolol, tranexamic acid, felbinac and dapsone were considered the four most promising drugs for GC. In summary, NNMT can be used as a prognostic biomarker that reflect immune infiltration level and a novel therapeutic target in GC.