Background Glycolysis metabolism is an attractive target for cancer therapy. Reprogramming metabolic pathways could improve the ability of metabolic inhibitors to suppress cancers with limited treatment options. The ubiquitin–proteasome system facilitates the turnover of most intracellular proteins with E3 ligase conferring the target selection and specificity. Ubiquitin protein ligase E3 component N-recognin 7 (UBR7), among the least studied E3 ligases, recognizes its substrate through a plant homeodomain (PHD) finger. Here, we bring into focus on its suppressive role in glycolysis and HCC tumorigenesis, dependent on its E3 ubiquitin ligase activity toward monoubiquitination of histone H2B at lysine 120 (H2BK120ub). Methods In this study, we carried out high-throughput RNAi screening to identify epigenetic candidates in regulating lactic acid and investigated its possible roles in HCC progression. Results UBR7 loss promotes HCC tumorigenesis both in vitro and in vivo. UBR7 inhibits glycolysis by indirectly suppressing HK2 expression, a downstream target of Nrf2/Bach1 axis. Mechanically, UBR7 regulates H2BK120ub to bind to Keap1 promoter through H2BK120ub monoubiquitination, thereby modulating Keap1 expression and downstream Nrf2/Bach1/HK2 signaling. Pharmaceutical and genetic inhibition of glycolytic enzymes attenuate the promoting effect of UBR7 deficiency on tumor growth. In addition, methyltransferase ALKBH5, downregulated in HCC, regulated UBR7 expression in an m6A-dependent manner. Conclusions These results collectively establish UBR7 as a critical negative regulator of aerobic glycolysis and HCC tumorigenesis through regulation of the Keap1/Nrf2/Bach1/HK2 axis, providing a potential clinical and therapeutic target for the HCC treatment.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent malignancy worldwide, with high incidence and poor survival rates. Increased expression of microRNA-205-5p (miR-205-5p) may influence the outcomes of HNSCC, but the identities of miR-205-5p target genes and the potential signaling pathways related to HNSCC remain unclear. RT-qPCR was used to detect the expression levels of miR-205-5p in the plasma of patients with HNSCC. We also performed a meta-analysis using data from relevant literature, and the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases to evaluate the expression level of miR-205-5p in HNSCC. Next, we predicted the potential miR-205-5p target genes in HNSCC. We also used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for enrichment analyses adapted to investigate the dynamics and possible mechanisms of miR-205-5p in HNSCC. Lastly, we predicted the potential miR-205-5p target genes by evaluating their expression level and using Spearman analysis. Expression of miR-205-5p was higher in HNSCC tissues compared to normal unafflicted tissue samples (P < 0.05), and the corresponding summary receiver operating characteristic (sROC) was 0.82.The pooled sensitivity, specificity, PLR, NLR, and DOR values were 0.78 (95% CI: 0.75-0.81), 0.67 (95% CI: 0.60-0.73), 2.34 (95% CI: 1.45-3.76), 0.34 (95% CI: 0.19-0.60), and 8.16 (95% CI: 4.01-16.64), respectively. Based on GO and KEGG analyses, we found that miR-205-5p was correlated with the progression of HNSCC through association with signaling pathways, including the drug metabolism-cytochrome P450 pathway. Analysis of the target genes revealed that flavin-containing monooxygenase isoform 2 (FMO2) and alcohol dehydrogenase 1B (ADH1B) may be important targets of miR-205-5p. In summary, miR-205-5p may have a significant role in the prognosis of HNSCC and may serve as a potential biomarker in HNSCC.

Background. Gastric cancer (GC) is one of the gastrointestinal tumors with the highest mortality rate. The number of GC patients is still high. As a way of iron-dependent programmed cell death, ferroptosis activates lipid peroxidation and accumulates large reactive oxygen species. The role of ferroptosis in GC prognosis was underrepresented. The objective was to investigate the role of ferroptosis-related genes (FRGs) in the prognosis and development of GC. Methods. Datasets of GC patients were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database that include clinical information and RNA seq data. Through nonnegative matrix factorization (NMF) clustering, we identified and unsupervised cluster analysis of the expression matrix of FRGs. And we constructed the co-expression network between genes and clinical characteristics by consensus weighted gene co-expression network analysis (WGCNA). The prognostic model was constructed by univariate and multivariate regression analysis. The potential mechanisms of development and prognosis in GC were explored by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene ontology (GO), tumor immune microenvironment (TIME), and tumor mutation burden (TMB). Results. Two molecular subclusters with different expression patterns of FRGs were identified, which have significantly different survival states. Ferroptosis subcluster-related modular genes were identified by WGCNA. Based on 8 ferroptosis subcluster-related modular genes (collagen triple helix repeat containing 1 (CTHRC1), podoplanin (PDPN), procollagen-lysine,2-oxoglutarate 5-dioxygenase 2 (PLOD2), glutamine-fructose-6-phosphate transaminase 2 (GFPT2), ATP-binding cassette subfamily A member 1 (ABCA1), G protein-coupled receptor 176 (GPR176), serpin family E member 1 (SERPINE1), dual specificity phosphatase 1 (DUSP1)) and clinicopathological features, a nomogram was constructed and validated for their predictive efficiency on GC prognosis. Through receiver operating characteristic (ROC) analysis, the results showed that the area under the curve (AUC) of 1-, 3-, and 5-year survival were 0.721, 0.747, and 0.803, respectively, indicating that the risk-scoring model we constructed had good prognosis efficacy in GC. The degree of immune infiltration in high-risk group was largely higher than low-risk group. It indicated that the immune cells have a good response in high-risk group of GC. The TMB of high-risk group was higher, which could generate more mutations and was more conducive to the body’s resistance to the development of cancer. Conclusion. The risk-scoring model based on 8 ferroptosis subcluster-related modular genes has shown outstanding advantages in predicting patient prognosis. The interaction of ferroptosis in GC development may provide new insights into exploring molecular mechanisms and targeted therapies for GC patients.