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Background: Gastric cancer (GC) is one of the most common malignant tumors with poor prognosis. So far, other than the HER2, GC lacks effective therapeutic targets. Transferrin receptor 1 (TFR1) expressions are abnormally upregulated in various cancers for the satisfaction of iron demand increased. This study aimed to explore the expression and clinical value of TFR1 in GC. Methods: A tissue microarray including GC tissues and matched noncancerous tissues from 155 GC patients were collected. Moreover, the level of TFR1 expression was detected by immunohistochemistry, and we also evaluated the relationship between TFR1 expression and the clinicopathologic characteristics. What is more, univariate analysis and multivariate analysis were used to evaluate the risk factors and independent risk factors affecting the prognosis of GC. Results: We found that TFR1 was overexpressed in GC tissues compared with noncancerous tissues, and a significant relationship was found between TFR1 expression and age (P=0.001), Lauren type (P=0.008), T stage (P=0.003), HER2 (P=0.003), PD-L1 (P < 0.001), and the level of CA72-4 (P=0.028). Survival analysis confirmed that GC patients with positive TFR1 expression had a poorer OS than that with negative TFR1 expression, and TFR1 expression was an independent risk factor in GC. Furthermore, we also found that there was a significant difference between the TFR1-PD-L1- group and the TFR1+PD-L1+ group (P=0.023), while there was no significant difference between the TFR1-PD-L1- group and the TFR1+PD-L1- group (P=0.119), or between the TFR1-PD-L1- group and the TFR1-PD-L1+ group (P=0.396). Conclusions: TFR1 was overexpressed in GC and its aberrant expression identifies a novel potential prognostic marker and therapeutic target. In addition, TFR1 expression may be associated with the immune microenvironment and suppress the immune response via regulating the PD-L1 expression.
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With the continuous improvement of living standards but the lack of exercise, aging-associated metabolic diseases such as obesity, type 2 diabetes mellitus (T2DM), and non-alcoholic fatty liver disease (NAFLD) are becoming a lingering dark cloud over society. Studies have found that metabolic disorders are near related to glucose, lipid metabolism, and cellular aging. Fibroblast growth factor 21 (FGF21), a member of the FGFs family, efficiently regulates the homeostasis of metabolism and cellular aging. By activating autophagy genes and improving inflammation, FGF21 indirectly delays cellular aging and directly exerts anti-aging effects by regulating aging genes. FGF21 can also regulate glucose and lipid metabolism by controlling metabolism-related genes, such as adipose triglyceride lipase (ATGL) and acetyl-CoA carboxylase (ACC1). Because FGF21 can regulate metabolism and cellular aging simultaneously, FGF21 analogs and FGF21 receptor agonists are gradually being valued and could become a treatment approach for aging-associated metabolic diseases. However, the mechanism by which FGF21 achieves curative effects is still not known. This review aims to interpret the interactive influence between FGF21, aging, and metabolic diseases and delineate the pharmacology of FGF21, providing theoretical support for further research on FGF21.
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BACKGROUND: Apoptosis-related genes(Args)play an essential role in the occurrence and progression of hepatocellular carcinoma(HCC). However, few studies have focused on the prognostic significance of Args in HCC. In the study, we aim to explore an efficient prognostic model of Asian HCC patients based on the Args. METHODS: We downloaded mRNA expression profiles and corresponding clinical data of Asian HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The Args were collected from Deathbase, a database related to cell death, combined with the research results of GeneCardsãNational Center for Biotechnology Information (NCBI) databases and a lot of literature. We used Wilcoxon-test and univariate Cox analysis to screen the differential expressed genes (DEGs) and the prognostic related genes (PRGs) of HCC. The intersection genes of DEGs and PGGs were seen as crucial Args of HCC. The prognostic model of Asian HCC patients was constructed by least absolute shrinkage and selection operator (lasso)- proportional hazards model (Cox) regression analysis. Kaplan-Meier curve, Principal Component Analysis (PCA) analysis, t-distributed Stochastic Neighbor Embedding (t-SNE) analysis, risk score curve, receiver operating characteristic (ROC) curve, and the HCC data of ICGC database and the data of Asian HCC patients of Kaplan-Meier plotter database were used to verify the model. RESULTS: A total of 20 of 56 Args were differentially expressed between HCC and adjacent normal tissues (p < 0.05). Univariate Cox regression analysis showed that 10 of 56 Args were associated with survival time and survival status of HCC patients (p < 0.05). There are seven overlapping genes of these 20 and 10 genes, including BAK1, BAX, BNIP3, CRADD, CSE1L, FAS, and SH3GLB1. Through Lasso-Cox analysis, an HCC prognostic model composed of BAK1, BNIP3, CSE1L, and FAS was constructed. Kaplan-Meier curve, PCA, t-SNE analysis, risk score curve, ROC curve, and secondary verification of ICGC database and Kaplan-Meier plotter database all support the reliability of the model. CONCLUSIONS: Lasso-Cox regression analysis identified a 4-gene prognostic model, which integrates clinical and gene expression and has a good effect. The expression of Args is related to the prognosis of HCC patients, but the specific mechanism remains to be further verified.
