The Expression and Clinical Significance of Aldo-Keto Reductase 1 Member B1 in Gastric Carcinoma

NRF2 inhibits RSL3 induced ferroptosis in gastric cancer through regulation of AKR1B1

Gastric cancer is a malignant tumor associated with a high mortality rate. Recently, emerging evidence has shown that ferroptosis, a regulated form of cell death induced by iron (Fe)-dependent lipid peroxidation. Nuclear factor E2 related factor 2 (NRF2) is a key regulator of intracellular oxidation homeostasis that plays a pivotal role in controlling lipid peroxidation, which is closely related to the process of ferroptosis. However, the molecular mechanism of NRF2 on ferroptosis remains to be investigated in gastric cancer. In our study, NRF 2 was found to transcriptionally activate Aldo-keto reductase 1 member B1 (AKR1B1) expression in gastric cancer. AKR1B1 is involved in the regulation of lipid metabolism by removing the aldehyde group of glutathione. We found that AKR1B1 is highly expressed in gastric cancer and is associated with a poor prognosis of the patients. In vitro experiments found that AKR1B1 has the ability to promote the proliferation and invasion of gastric cancer cells. AKR1B1 inhibited RSL3-induced ferroptosis in gastric cancer by reducing reactive oxygen species accumulation and lipid peroxidation, as well as decreasing intracellular ferrous ion and malondialdehyde expression and increasing glutathione expression. Our study demonstrated that AKR1B1 resisted RSL3-induced ferroptosis by regulating GPX4, PTGS2 and ACSL4, which was further demonstrated in a xenograft nude mouse model. Our work reveals a critical role for the AKR1B1 in the resistance to RSL3-induced ferroptosis in gastric cancer.

The polyol pathway and nuclear ketohexokinase A signaling drive hyperglycemia-induced metastasis of gastric cancer

Diabetes might be associated with increased cancer risk, with several studies reporting hyperglycemia as a primary oncogenic stimulant. Since glucose metabolism is linked to numerous metabolic pathways, it is difficult to specify the mechanisms underlying hyperglycemia-induced cancer progression. Here, we focused on the polyol pathway, which is dramatically activated under hyperglycemia and causes diabetic complications. We investigated whether polyol pathway-derived fructose facilitates hyperglycemia-induced gastric cancer metastasis. We performed bioinformatics analysis of gastric cancer datasets and immunohistochemical analyses of gastric cancer specimens, followed by transcriptomic and proteomic analyses to evaluate phenotypic changes in gastric cancer cells. Consequently, we found a clinical association between the polyol pathway and gastric cancer progression. In gastric cancer cell lines, hyperglycemia enhanced cell migration and invasion, cytoskeletal rearrangement, and epithelial-mesenchymal transition (EMT). The hyperglycemia-induced acquisition of metastatic potential was mediated by increased fructose derived from the polyol pathway, which stimulated the nuclear ketohexokinase-A (KHK-A) signaling pathway, thereby inducing EMT by repressing the CDH1 gene. In two different xenograft models of cancer metastasis, gastric cancers overexpressing AKR1B1 were found to be highly metastatic in diabetic mice, but these effects of AKR1B1 were attenuated by KHK-A knockdown. In conclusion, hyperglycemia induces fructose formation through the polyol pathway, which in turn stimulates the KHK-A signaling pathway, driving gastric cancer metastasis by inducing EMT. Thus, the polyol and KHK-A signaling pathways could be potential therapeutic targets to decrease the metastatic risk in gastric cancer patients with diabetes.

Construction and validation of a prognosis signature based on the immune microenvironment in gastric cancer

Background

Gastric cancer (GC) is an aggressive malignant tumor with a high degree of heterogeneity, and its immune microenvironment is closely associated with tumor growth, development and drug resistance. Therefore, a classification system of gastric cancer based explicitly on the immune microenvironment context might enrich the strategy for gastric cancer prognosis and therapy.

Methods

A total of 668 GC patients were collected from TCGA-STAD (n = 350), GSE15459 (n = 192), GSE57303 (n = 70) and GSE34942 (n = 56) datasets. Three immune-related subtypes (immunity-H, -M, and -L) were identified by hierarchical cluster analysis based on the ssGSEA score of 29 immune microenvironment-related gene sets. The immune microenvironment-related prognosis signature (IMPS) was constructed via univariate Cox regression, Lasso-Cox regression and multivariate Cox regression, and nomogram model combining IMPS and clinical variables was further constructed by the “rms” package. RT-PCR was applied to validate the expression of 7 IMPS genes between two human GC cell lines (AGS and MKN45) and one normal gastric epithelial cell line (GES-1).

Results

The patients classified as immunity-H subtype exhibited highly expressed immune checkpoint and HLA-related genes, with enriched naïve B cells, M1 macrophages and CD8 T cells. We further constructed and validated a 7-gene (CTLA4, CLDN6, EMB, GPR15, ENTPD2, VWF and AKR1B1) prognosis signature, termed as IMPS. The patients with higher IMPS expression were more likely to be associated with higher pathology grade, more advanced TNM stages, higher T and N stage, and higher ratio of death. In addition, the prediction values of the combined nomogram in predicting 1-year (AUC = 0.750), 3-year (AUC = 0.764) and 5-year (AUC = 0.802) OS was higher than IMPS and individual clinical characteristics.

Conclusions

The IMPS is a novel prognosis signature associated with the immune microenvironment and clinical characteristics. The IMPS and the combined nomogram model provide a relatively reliable predictive index for predicting the survival outcomes of gastric cancer.

ZNF521/EBF1 axis regulates AKR1B1 to promote the proliferation, migration, and invasion of gastric cancer cells

Although the incidence and death rates of gastric cancer (GC) are decreasing, approximately one million new cases and 800,000 GC-related deaths were reported worldwide in 2018. Currently, the oncogenesis of GC remains unclear, and the demand for novel treatment options are unmet. Here, we explored the role of aldo-keto reductase family 1 member B (AKR1B1) in the progression of GC. The proliferation, migration, and invasion of GC cells were evaluated by CCK-8 assay, wound healing assay, and transwell assay, respectively. The interaction between EBF transcription factor 1 (EBF1) and the promoter region of AKR1B1 was determined by luciferase reporter assay and chromatin immunoprecipitation (ChIP). Gene expression levels were measured by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting assay. The expression of AKR1B1 was elevated in GC cells, resulting in increased cell proliferation, migration, and invasion. Meanwhile, EBF1 was a negative regulator of AKR1B1; its overexpression suppressed AKR1B1 expression and GC progression. Furthermore, knockdown of ZNF521 induced EBF1 expression, thus suppressing AKR1B1 expression and resulting in attenuated GC growth and invasiveness. Notably, knockdown of ZNF521 attenuated GC progression and was rescued by overexpression of AKR1B1. Our current study revealed a novel ZNF521/EBF1/AKR1B1 axis in GC and elaborated its important role in promoting GC progression, providing potential therapeutic targets for anti-GC treatments.

Integrative Analysis Identifies a TNFα-Derived Gene Signature for Predicting Prognosis, Tumor Immunity, and Treatment Sensitivity in Gastric Cancer

Objective: TNF-α is an essential pro-inflammatory cytokine in the tumor microenvironment of gastric cancer (GC), possessing a key biological and clinical impact. Here, we conducted an integrative analysis of the role of TNFα-derived genes in GC prognosis and precision medicine.

Methods: We pooled transcriptome and clinical features of GC patients from TCGA and GSE15459 projects. TNFα signaling was quantified through the ssGSEA algorithm, and TNFα-derived genes were screened with WGCNA. Thereafter, a LASSO model was established. The somatic mutation was analyzed across GC specimens. Immune cell infiltrations were inferred through ESTIMATE and ssGSEA algorithms, followed by measuring the immune checkpoint expression. AKR1B1, CPVL, and CTSL expressions were measured in gastric mucosal cells GES-1 and GC cells (HGC-27, MKN-28, and AGS) through RT-qPCR and Western blotting.

Results: A TNFα-derived gene signature (containing AKR1B1, CPVL, and CTSL) was developed for GC. A high-risk score indicated more undesirable OS, DFS, DSS, and PFS outcomes. Time-independent ROC curves and multivariate cox regression models confirmed that the signature reliably and independently predicted GC prognosis. Additionally, risk scores displayed significant correlations to more severe histological grades and pathological stages. A low-risk score was characterized by increased somatic mutation, while a high-risk score was characterized by immune and stromal activation, enhanced immune cell infiltrations, and increased expression of immune checkpoint molecules. Experimental results confirmed the significant upregulation of AKR1B1, CPVL, and CTSL in GC cells.

Conclusion: Collectively, stratification based on the TNFα-derived gene signature might enable GC patients to predict prognosis, benefit from immunotherapy, and assist in formulating novel therapeutic regimens.

Recognition of DNA Methylation Molecular Features for Diagnosis and Prognosis in Gastric Cancer

Background: The management of gastric cancer (GC) still lacks tumor markers with high specificity and sensitivity. The goal of current research is to find effective diagnostic and prognostic markers and to clarify their related mechanisms.

Methods: In this study, we integrated GC DNA methylation data from publicly available datasets obtained from TCGA and GEO databases, and applied random forest and LASSO analysis methods to screen reliable differential methylation sites (DMSs) for GC diagnosis. We constructed a diagnostic model of GC by logistic analysis and conducted verification and clinical correlation analysis. We screened credible prognostic DMSs through univariate Cox and LASSO analyses and verified a prognostic model of GC by multivariate Cox analysis. Independent prognostic and biological function analyses were performed for the prognostic risk score. We performed TP53 correlation analysis, mutation and prognosis analysis on eleven-DNA methylation driver gene (DMG), and constructed a multifactor regulatory network of key genes.

Results: The five-DMS diagnostic model distinguished GC from normal samples, and diagnostic risk value was significantly correlated with grade and tumor location. The prediction accuracy of the eleven-DMS prognostic model was verified in both the training and validation datasets, indicating its certain potential for GC survival prediction. The survival rate of the high-risk group was significantly lower than that of the low-risk group. The prognostic risk score was an independent risk factor for the prognosis of GC, which was significantly correlated with N stage and tumor location, positively correlated with the VIM gene, and negatively correlated with the CDH1 gene. The expression of CHRNB2 decreased significantly in the TP53 mutation group of gastric cancer patients, and there were significant differences in CCDC69, RASSF2, CHRNB2, ARMC9, and RPN1 between the TP53 mutation group and the TP53 non-mutation group of gastric cancer patients. In addition, CEP290, UBXN8, KDM4A, RPN1 had high frequency mutations and the function of eleven-DMG mutation related genes in GC patients is widely enriched in multiple pathways.

Conclusion: Combined, the five-DMS diagnostic and eleven-DMS prognostic GC models are important tools for accurate and individualized treatment. The study provides direction for exploring potential markers of GC.

Development of Aldose Reductase Inhibitors for the Treatment of Inflammatory Disorders and Cancer: Current Drug Design Strategies and Future Directions

Aldose Reductase (AR) is an enzyme that converts glucose to sorbitol during the polyol pathway of glucose metabolism. AR has been shown to be involved in the development of secondary diabetic complications due to its involvement in causing osmotic as well as oxidative stress. Various AR inhibitors have been tested for their use to treat secondary diabetic complications, such as retinopathy, neuropathy, and nephropathy in clinical studies. Recent studies also suggest the potential role of AR in mediating various inflammatory complications. Therefore, the studies on the development and potential use of AR inhibitors to treat inflammatory complications and cancer besides diabetes are currently on the rise. Further, genetic mutagenesis studies, computer modeling, and molecular dynamics studies have helped design novel and potent AR inhibitors. This review discussed the potential new therapeutic use of AR inhibitors in targeting inflammatory disorders and cancer besides diabetic complications. Further, we summarized studies on how AR inhibitors have been designed and developed for therapeutic purposes in the last few decades.