Construction and validation of an aging-related gene signature predicting the prognosis of pancreatic cancer.

Background: Pancreatic cancer is a malignancy with a high mortality rate and worse prognosis. Recently, public databases and bioinformatics tools make it easy to develop the prognostic risk model of pancreatic cancer, but the aging-related risk signature has not been reported. The present study aimed to identify an aging-related risk signature with potential prognostic value for pancreatic cancer patients. Method: Gene expression profiling and human clinical information of pancreatic cancer were derived from The Cancer Genome Atlas database (TCGA). Aging-related gene sets were downloaded from The Molecular Signatures Database and aging-related genes were obtained from the Human Ageing Genomic Resources database. Firstly, Gene set enrichment analysis was carried out to investigate the role of aging process in pancreatic cancer. Secondly, differentially expressed genes and aging-related prognostic genes were screened on the basis of the overall survival information. Then, univariate COX and LASSO analysis were performed to establish an aging-related risk signature of pancreatic cancer patients. To facilitate clinical application, a nomogram was established to predict the survival rates of PCa patients. The correlations of risk score with clinical features and immune status were evaluated. Finally, potential therapeutic drugs were screened based on the connectivity map (Cmap) database and verified by molecular docking. For further validation, the protein levels of aging-related genes in normal and tumor tissues were detected in the Human Protein Atlas (HPA) database. Result: The genes of pancreatic cancer were markedly enriched in several aging-associated signaling pathways. We identified 14 key aging-related genes related to prognosis from 9,020 differentially expressed genes and establish an aging-related risk signature. This risk model indicated a strong prognostic capability both in the training set of TCGA cohort and the validation set of PACA-CA cohort and GSE62452 cohort. A nomogram combining risk score and clinical variables was built, and calibration curve and Decision curve analysis (DCA) have proved that it has a good predictive value. Additionally, the risk score was tightly linked with tumor immune microenvironment, immune checkpoints and proinflammatory factors. Moreover, a candidate drug, BRD-A47144777, was screened and verified by molecular docking, indicating this drug has the potential to treat PCa. The protein expression levels of GSK3B, SERPINE1, TOP2A, FEN1 and HIC1 were consistent with our predicted results. Conclusion: In conclusion, we identified an aging-related signature and nomogram with high prediction performance of survival and immune cell infiltration for pancreatic cancer. This signature might potentially help in providing personalized immunotherapy for patients with pancreatic cancer.

Meta-analysis assessing the effectiveness of SGLT2i+GLP1RA combination therapy versus monotherapy on cardiovascular and cerebrovascular outcomes in diabetic patients.

Relevant meta-analyses have confirmed the cardiovascular and renal benefits of sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1RA) among patients with type 2 diabetes (T2D) and/or cardiorenal disease. However, it is not established whether the combination therapy of SGLT2i and GLP1RA will yield an additive benefit on cardiorenal endpoints. Lopez and colleagues recently did a cohort study (Lopez et al., Am. J. Cardiol., 2022, 181, 87-93) and aimed to address this issue. However, their findings are not consistent with those of previous studies. To confirm Lopez et al.'s findings (Lopez et al., Am. J. Cardiol., 2022, 181, 87-93) and address the aforementioned inconsistencies, we conducted a meta-analysis based on relevant studies. Our meta-analysis identified that SGLT2i + GLP1RA combination therapy was significantly associated with the reduced risks of cardiovascular/cerebrovascular atherosclerotic, heart failure-associated, and death outcomes compared with SGLT2i/GLP1RA monotherapy. These might support this combination therapy used for better reducing cardiovascular and death events in T2D patients, especially in those with high or very high cardiovascular risk. This is a commentary on a previous article (Lopez et al.'s study (Lopez et al., Am. J. Cardiol., 2022, 181, 87-93)) published outside of Frontiers. Therefore, we submitted this manuscript as an Opinion article, as suggested in the Author Guidelines.

Construction of a survival nomogram for gastric cancer based on the cancer genome atlas of m6A-related genes.

Objective: Based on TCGA database, a prediction model for 1-, 3-, and 5-year overall survival rates of gastric cancer (GC) patients was constructed by analyzing the critical risk factors affecting the prognosis of gastric cancer patients. Method: Clinicopathological features as well as gene signature of GC patients were obtained from TCGA database. Patients were randomly divided into a training cohort and an internal validation cohort. Independent predictors of GC prognosis were analyzed by univariate and multivariate Cox analyses to construct nomogram. The accuracy and reliability of the model was further validated by calibration curves, ROC curves, and C-indexes, and the clinical utility of the model was analyzed by decision analysis curves. Result: Age, sex, N stage, M stage, METTL16, RBM15, FMR1, IGFBP1, and FTO were significantly associated with the prognosis of GC patients, and these predictors were further included in the construction of nomogram. The C-indexes for the training cohort and validation set were 0.735 and 0.688, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) exceeded 0.6 in training and validation sets at 1, 3, and 5 years. Conclusion: We have constructed and validated a nomogram that provides individual survival condition prediction for GC patients. The prognostic model integrating gene signatures and clinicopathological characteristics would help clinicians determine the prognosis of patients with GC and develop individualized treatment plans.

A ferroptosis-associated lncRNAs signature predicts the prognosis of hepatocellular carcinoma.

BACKGROUND: Long noncoding RNAs (lncRNAs) have been implicated in the development of hepatocellular carcinoma (HCC). Mounting evidence shows that lncRNAs can be used as prognostic biomarkers of HCC. Here, we developed a multi-lncRNA prognostic signature comprising ferroptosis-related lncRNAs in HCC. METHODS: Gene expression data and clinical information of HCC were obtained from the TCGA dataset. Differentially expressed genes of ferroptosis (DE-Ferrs) were screened. Correlation analysis was carried between lncRNAs and DE-Ferrs to identify ferroptosis-related lncRNAs. lncRNAs associated with prognosis and ferroptosis were identified using Univariate Cox analysis. Data from a TCGA dataset were randomly grouped into training and verification sets. The least absolute shrinkage and selection operator method analysis was carried out to identify lncRNAs with prognostic value. These lncRNAs were used to construct a prognostic signature using the training set. The signature was validated in the verification set. RESULTS: A total of 90 DE-Ferrs-related lncRNAs were identified which were significantly correlated with HCC prognosis. Seven lncRNAs were used to construct a 7-lncRNA signature. The area under the curves for 1-, 3-, and 5-year overall survival (OS) were 0.748, 0.681, and 0.659 in the training set, and 0.791, 0.731, and 0.815 in the validation set, respectively. The results demonstrated that a high-risk score was significantly associated with a high tumor grade, high infiltration of macrophages and fibroblasts in the tumor, and high expression of m6A methylation regulatory factors. A nomogram was constructed using the risk score and clinical features for predicting the prognosis of HCC. The nomogram showed high prediction accuracy. CONCLUSION: In conclusion, the established 7 ferroptosis-related lncRNAs signature can accurately predict HCC prognosis.

Construction and validation of a prognostic risk model of angiogenesis factors in skin cutaneous melanoma.

Melanoma can secrete tumor angiogenesis factors, which is the essential factor for tumor growth and metastasis. However, there are few reports on the relationship between angiogenesis factors and prognosis risk in melanoma. This study aimed to develop a prognostic risk model of angiogenesis for melanoma. Forty-nine differentially expressed angiogenesis were identified from the TCGA database, which were mainly involved in PI3K/Akt pathway, focal adhesion, and MAPK signaling pathway. We then establish an eleven-gene signature. The model indicated a strong prognostic capability in both the discovery cohort and the validation cohort. Patients of smaller height (<170 cm) and lower weight (<80 kg) and those with advanced-stage and ulcerated melanoma had higher risk scores. The risk score was positively correlated with mutation load, homologous recombination defect, neoantigen load and chromosome instability. In addition, the high-risk group had a higher degree of immune cell infiltration, better response to immunotherapy and lower immune score. Therefore, these results indicate that the risk model is an effective method to predict the prognosis of melanoma.

Pegylated Recombinant Human Arginase 1 Induces Autophagy and Apoptosis via the ROS-Activated AKT/mTOR Pathway in Bladder Cancer Cells.

Bladder cancer is one of the most commonly diagnosed cancers worldwide, especially in males. Current therapeutic interventions, including surgery, radiation therapy, chemotherapy, and immunotherapy, have not been able to improve the clinical outcome of bladder cancer patients with satisfaction. Recombinant human arginase (rhArg, BCT-100) is a novel agent with great anticancer effects on arginine-auxotrophic tumors. However, the effects of BCT-100 on bladder cancer remain unclear. In this study, the in vitro anticancer effects of BCT-100 were assessed using four bladder cancer cell lines (J82, SCaBER, T24, and 5637), while the in vivo effects were evaluated by establishing T24 nude mice xenograft models. Intracellular arginine level was observed to be sharply decreased followed by the onset of apoptotic events. Furthermore, BCT-100 was found to induce H2O2 production and mitochondrial membrane depolarization, leading to the release of mitochondrial cytochrome c and Smac to the cytosol. Treatment with BCT was observed to upregulate the expression of LC3B and Becllin-1, but downregulate the expression of p62 in a time-dependent manner. Autophagic flux was also observed upon BCT-100 treatment. Besides, the phosphorylation of the AKT/mTOR pathway was suppressed in a time-dependent fashion in BCT-100-treated T24 cells. While N-acetyl-L-cysteine was shown to alleviate BCT-100-induced apoptosis and autophagy, chloroquine, MK-2206, and rapamycin were found to potentiate BCT-100-triggered apoptosis. Finally, BCT-100 was demonstrated to induce autophagy and apoptosis via the ROS-mediated AKT/mTOR signaling pathway in bladder cancer cells.

Identification of Crucial Genes Associated With Immune Cell Infiltration in Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis.

The dreadful prognosis of hepatocellular carcinoma (HCC) is primarily due to the low early diagnosis rate, rapid progression, and high recurrence rate. Valuable prognostic biomarkers are urgently needed for HCC. In this study, microarray data were downloaded from GSE14520, GSE22058, International Cancer Genome Consortium (ICGC), and The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) were identified among GSE14520, GSE22058, and ICGC databases. Weighted gene co-expression network analysis (WGCNA) was used to establish gene co-expression modules of DEGs, and genes of key modules were examined to identify hub genes using univariate Cox regression in the ICGC cohort. Expression levels and time-dependent receiver operating characteristic (ROC) and area under the curve (AUC) were determined to estimate the prognostic competence of the hub genes. These hub genes were also validated in the Gene Expression Profiling Interactive Analysis (GEPIA) and TCGA databases. TIMER algorithm and GSCALite database were applied to analyze the association of the hub genes with immunocytotic infiltration and their pathway enrichment. Altogether, 276 DEGs were identified and WGCNA described a unique and significantly DEGs-associated co-expression module containing 148 genes, with 10 hub genes selected by univariate Cox regression in the ICGC cohort (BIRC5, FOXM1, CENPA, KIF4A, DTYMK, PRC1, IGF2BP3, KIF2C, TRIP13, and TPX2). Most of the genes were validated in the GEPIA databases, except IGF2BP3. The results of multivariate Cox regression analysis indicated that the abovementioned hub genes are all independent predictors of HCC. The 10 genes were also confirmed to be associated with immune cell infiltration using the TIMER algorithm. Moreover, four-gene signature was developed, including BIRC5, CENPA, FOXM1, DTYMK. These hub genes and the model demonstrated a strong prognostic capability and are likely to be a therapeutic target for HCC. Moreover, the association of these genes with immune cell infiltration improves our understanding of the occurrence and development of HCC.

Identification of hub genes, key pathways, and therapeutic agents in Hutchinson-Gilford Progeria syndrome using bioinformatics analysis.

BACKGROUND: Hutchinson-Gilford Progeria syndrome (HGPS) is a rare lethal premature and accelerated aging disease caused by mutations in the lamin A/C gene. Nevertheless, the mechanisms of cellular damage, senescence, and accelerated aging in HGPS are not fully understood. Therefore, we aimed to screen potential key genes, pathways, and therapeutic agents of HGPS by using bioinformatics methods in this study. METHODS: The gene expression profile of GSE113648 and GSE41751 were retrieved from the gene expression omnibus database and analyzed to identify the differentially expressed genes (DEGs) between HGPS and normal controls. Then, gene ontology and the Kyoto encyclopedia of genes and genomes pathway enrichment analysis were carried out. To construct the protein-protein interaction (PPI) network, we used STRING and Cytoscape to make module analysis of these DEGs. Besides, the connectivity map (cMAP) tool was used as well to predict potential drugs. RESULTS: As a result, 180 upregulated DEGs and 345 downregulated DEGs were identified, which were significantly enriched in pathways in cancer and PI3K-Akt signaling pathway. The top centrality hub genes fibroblast growth factor 2, decorin, matrix metallopeptidase2, and Fos proto-oncogene, AP-1 transcription factor subunit were screened out as the critical genes among the DEGs from the PPI network. Dexibuprofen and parthenolide were predicted to be the possible agents for the treatment of HGPS by cMAP analysis. CONCLUSION: This study identified key genes, signal pathways and therapeutic agents, which might help us improve our understanding of the mechanisms of HGPS and identify some new therapeutic agents for HGPS.

Association of Foxp3 and TGF-ß1 Polymorphisms with Pre-Eclampsia Risk in Chinese Women.

PURPOSE: The aim of this study was to investigate whether single nucleotide polymorphisms (SNPs) in the genes that encode forkhead box p3 (Foxp3) (rs3761549 C>T, rs2280883T>C, rs2232365 A>G and rs3761548 C>A) and transforming growth factor (TGF)-ß1 (rs11466359 C>T, rs11466345 A>G and rs1800469 T>C) are associated with pre-eclampsia (PE) risk in Chinese women. MATERIALS AND METHODS: SNPs were identified by polymerase chain reaction and ligase detection reaction. Allelic variant and genotype frequencies for Foxp3 and TGF-ß1 were compared between PE women (n = 203) and healthy pregnant (HP) controls (n = 243). RESULTS: The TGF-ß1 rs1800469 TT genotype was found more frequently in PE patients than in HP controls [CC vs. CT+TT: odds ratio (OR) = 1.71; 95% confidence interval (CI): 1.04-2.81; p = 0.033], indicating that the T allele of rs1800469 confers a risk for PE [OR = 1.46; 95% CI: 1.12-1.92; p = 0.006]. The Foxp3 rs2232365 A allele was associated with severe PE specifically [OR = 1.70; 95% CI: 1.12-2.58; p = 0.01], compared with mild PE. There were no haplotype associations with PE. CONCLUSIONS: These findings indicate that allelic variants of TGF-ß1 rs1800469 T influence PE risk in Chinese women. Pregnant Han Chinese women carrying the rs1800469 TT genotype were at increased risk of PE.

Contribution of regulatory T cells to immune tolerance and association of microRNA­210 and Foxp3 in preeclampsia.

Increasing evidence suggests that an exaggerated maternal systemic inflammatofrery response may play a central role in the pathogenesis of preeclampsia (PE). Considering the growing evidence on microRNAs (miRNAs) and tissue­specific regulators of gene expression, we investigated the potential association of miR­210 and forkhead box p3 (Foxp3) in preeclamptic patients. Serum levels of the cytokines interleukin (IL)­6, IL­10, IL­17, and transforming grown factor­ß1 were detected with ELISA. Reverse­transcription­quantitative polymerase chain reaction was performed to detect mRNA expression for maternal placenta retinoic acid­related orphan receptor C, Foxp3 and miRNA (miR)­210. Foxp3 protein expression was evaluated by western blot analysis. Serum levels of cytokines IL­10 were significantly lower in preeclamptic patients than in normal pregnant women. mRNA expression of Foxp3 was significantly lower in placenta of PE. mRNA expression of miR­210 was significantly increased in PE. Results of western blot analysis indicated that Foxp3 protein expression was lower in PE than in normal pregnant women. Our data suggest that PE manifests as a decreased number of regulatory T cells (Tregs), which regulate maternal tolerance of the fetus. In placenta from women with PE, compared with normal pregnant women, mRNA expression of Foxp3 was significantly decreased, and expression of miR­210 was significantly increased.

MicroRNA-33 promotes the replicative senescence of mouse embryonic fibroblasts by suppressing CDK6.

MicroRNAs are a large class of tiny noncoding RNAs, which have emerged as critical regulators of gene expression, and thus are involved in multiple cellular processes, including cellular senescence. MicroRNA-33 has previously been established to exert crucial effect on cell proliferation, lipid metabolism and cholesterol metabolism. Nonetheless, the association between microRNA-33 and cellular senescence and its underlying molecular mechanism are far to be elucidated. The present study has attempted to probe into the effect of microRNA-33 on MEFs senescence. Our data unveiled that microRNA-33 was dramatically down-regulated in senescent MEFs compared to the young MEFs, and ectopic expression of microRNA-33 promoted MEFs senescence, while knock-down of microRNA-33 exhibited a protective effect against senescence phenotype. Moreover, we verified CDK6 as a direct target of microRNA-33 in mouse. Silencing of CDK6 induced the premature senescence phenotype of MEFs similarly as microRNA-33, while enforced expression of CDK6 significantly reverse the senescence-induction effect of microRNA-33. Taken together, our results suggested that microRNA-33 enhanced the replicative senescence of MEFs potentially by suppressing CDK6 expression.