Background The prognostic and clinicopathological significance of POU Class 5 Homeobox 1 (POU5F1) among various cancers are disputable heretofore. The diagnostic value and functional mechanism of POU5F1 in liver hepatocellular carcinoma (LIHC) have not been studied thoroughly. Methods An integrative strategy of meta‐analysis, bioinformatics, and wet‐lab approach was used to explore the diagnostic and prognostic significance of POU5F1 in various types of tumors, especially in LIHC. Meta‐analysis was utilized to investigate the impact of POU5F1 on prognosis and clinicopathological parameters in various cancers. The expression level and diagnostic value of POU5F1 were assessed by qPCR in plasma collected from LIHC patients and controls. The correlation between POU5F1 and tumor infiltrating immune cells (TIICs) in LIHC was evaluated by CIBERSORT. Gene set enrichment analysis (GSEA) was performed based on TCGA. Hub genes and related pathways were identified on the basis of co‐expression genes of POU5F1. Results Elevated POU5F1 was associated with poor OS, DFS, RFS, and DSS in various cancers. POU5F1 was confirmed as an independent risk factor for LIHC and correlated with tumor occurrence, stage, and invasion depth. The combination of POU5F1 and AFP in plasma was with high diagnostic validity (AUC = 0.902, p < .001). Specifically, the level of POU5F1 was correlated with infiltrating levels of B cells, T cells, dendritic cells, and monocytes in LIHC. GSEA indicated that POU5F1 participated in multiple cancer‐related pathways and cell proliferation pathways. Moreover, CBX3, CCHCR1, and NFYC were filtered as the central hub genes of POU5F1. Conclusion Our study identified POU5F1 as a pan‐cancer gene that could not only be a prognostic and diagnostic biomarker in various cancers, especially in LIHC, but functionally carcinogenic in LIHC.
Aim: This study aimed to excavate the roles of BCYRN1 in hepatocellular carcinoma (HCC). Methods: A comprehensive strategy of microarray data mining, computational biology and experimental verification were adopted to assess the clinical significance of BCYRN1 and identify related pathways. Results: BCYRN1 was upregulated in HCC and its expression was positively associated with both tumor, node, metastasis and worse survival rate in patients with HCC. Through combing plasma BCYRN1 with alpha fetoprotein, the diagnosis of HCC was remarkably improved. BCYRN1 may regulate some cancer-related pathways to promote HCC initiation via an lncRNA–miRNA–mRNA network. Conclusion: Our results propose BCYRN1 as a potential diagnostic and prognostic biomarker and offer a novel perspective to explore the etiopathogenesis of HCC.
Background Coronavirus disease 2019 (COVID-19) is an emerging infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Up to 20%–30% of patients hospitalized with COVID-19 have evidence of cardiac dysfunction. Xuebijing injection is a compound injection containing five traditional Chinese medicine ingredients, which can protect cells from SARS-CoV-2-induced cell death and improve cardiac function. However, the specific protective mechanism of Xuebijing injection on COVID-19-induced cardiac dysfunction remains unclear. Methods The therapeutic effect of Xuebijing injection on COVID-19 was validated by the TCM Anti COVID-19 (TCMATCOV) platform. RNA-sequencing (RNA-seq) data from GSE150392 was used to find differentially expressed genes (DEGs) from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) infected with SARS-CoV-2. Data from GSE151879 was used to verify the expression of Angiotensin I Converting Enzyme 2 (ACE2) and central hub genes in both human embryonic-stem-cell-derived cardiomyocytes (hESC-CMs) and adult human CMs with SARS-CoV-2 infection. Results A total of 97 proteins were identified as the therapeutic targets of Xuebijing injection for COVID-19. There were 22 DEGs in SARS-CoV-2 infected hiPSC-CMs overlapped with the 97 therapeutic targets, which might be the therapeutic targets of Xuebijing injection on COVID-19-induced cardiac dysfunction. Based on the bioinformatics analysis, 7 genes (CCL2, CXCL8, FOS, IFNB1, IL-1A, IL-1B, SERPINE1) were identified as central hub genes and enriched in pathways including cytokines, inflammation, cell senescence and oxidative stress. ACE2, the receptor of SARS-CoV-2, and the 7 central hub genes were differentially expressed in at least two kinds of SARS-CoV-2 infected CMs. Besides, FOS and quercetin exhibited the tightest binding by molecular docking analysis. Conclusion Our study indicated the underlying protective effect of Xuebijing injection on COVID-19, especially on COVID19-induced cardiac dysfunction, which provided the theoretical basis for exploring the potential protective mechanism of Xuebijing injection on COVID19-induced cardiac dysfunction.
DNA methylation plays an essential role in the pathogenesis of coronary artery disease (CAD) through regulating mRNA expressions. This study aimed to identify hub genes regulated by DNA methylation as biomarkers of CAD. Gene expression and methylation datasets of peripheral blood leukocytes (PBLs) of CAD were downloaded from the Gene Expression Omnibus (GEO) database. Subsequently, multiple computational approaches were performed to analyze the regulatory networks and to recognize hub genes. Finally, top hub genes were verified in a case-control study, based on their differential expressions and methylation levels between CAD cases and controls. In total, 535 differentially expressed-methylated genes (DEMGs) were identified and partitioned into 4 subgroups. TSS200 and 5 UTR were confirmed as high enrichment areas of differentially methylated CpGs sites (DMCs). The function of DEMGs is enriched in processes of histone H3-K27 methylation, regulation of post-transcription and DNAdirected RNA polymerase activity. Pathway enrichment showed DEMGs participated in the VEGF signaling pathway, adipocytokine signaling pathway, and PI3K-Akt signaling pathway. Besides, expressions of hub genes fibronectin 1 (FN1), phosphatase (PTEN), and tensin homolog and RNA polymerase III subunit A (POLR3A) were discordantly expressed between CAD patients and controls and related with DNA methylation levels. In conclusion, our study identified the potential biomarkers of PBLs for CAD, in which FN1, PTEN, and POLR3A were confirmed.
Background: Hepatocellular carcinoma (HCC) is one of the most common neoplastic diseases worldwide. Available biomarkers are not sensitive enough for the diagnosis of HCC, seeking new biomarkers of HCC is urgent and challenging. The purpose of this study was to investigate the role of F-box and leucine-rich repeat protein 19-antisense RNA 1 (FBXL19-AS1) through competing endogenous RNA (ceRNA) network and its diagnostic and prognostic value in HCC.Methods: A comprehensive strategy of genomic data mining, bioinformatics and experimental validation was used to evaluate the clinical value of FBXL19-AS1 in the diagnosis and prognosis of HCC and to identify the pathways that FBXL19-AS1 may be involved in.Results: FBXL19-AS1 was up-regulated in HCC, and its high expression was associated with TNM stage and poor prognosis of HCC patients. The combined use of plasma FBXL19-AS1 and alpha-fetoprotein (AFP) could prominently improve the diagnostic validity for HCC. FBXL19-AS1 might participate in regulating HCC related pathways, including hepatitis C, hepatitis B, microRNAs in cancer, cell cycle, viral carcinogenesis, and proteoglycans in cancer through ceRNA network.Conclusions: Our findings indicated that FBXL19-AS1 not only serves as a potential biomarker for HCC diagnosis and prognosis, but it may be functionally carcinogenic.
Background DNA methylation-regulated genes have been demonstrated as the crucial participants in the occurrence of coronary heart disease (CHD). The machine learning based on DNA methylation-regulated genes has tremendous potential for mining non-invasive predictive biomarkers and exploring underlying new mechanisms of CHD. Results First, the 2085 age-gender-matched individuals in Framingham Heart Study (FHS) were randomly divided into training set and validation set. We then integrated methylome and transcriptome data of peripheral blood leukocytes (PBLs) from the training set to probe into the methylation and expression patterns of CHD-related genes. A total of five hub DNA methylation-regulated genes were identified in CHD through dimensionality reduction, including ATG7, BACH2, CDKN1B, DHCR24 and MPO. Subsequently, methylation and expression features of the hub DNA methylation-regulated genes were used to construct machine learning models for CHD prediction by LightGBM, XGBoost and Random Forest. The optimal model established by LightGBM exhibited favorable predictive capacity, whose AUC, sensitivity, and specificity were 0.834, 0.672, 0.864 in the validation set, respectively. Furthermore, the methylation and expression statuses of the hub genes were verified in monocytes using methylation microarray and transcriptome sequencing. The methylation statuses of ATG7, DHCR24 and MPO and the expression statuses of ATG7, BACH2 and DHCR24 in monocytes of our study population were consistent with those in PBLs from FHS. Conclusions We identified five DNA methylation-regulated genes based on a predictive model for CHD using machine learning, which may clue the new epigenetic mechanism for CHD.
Hepatocellular carcinoma (HCC) is one of the most common neoplastic diseases worldwide. Available biomarkers are not sensitive enough for the diagnosis of HCC, hence seeking new biomarkers of HCC is urgent and challenging. The purpose of this study was to investigate the role of F-box and leucine-rich repeat protein 19-antisense RNA 1 (FBXL19-AS1) through a functional network and inquire into its diagnostic and prognostic value in HCC. A comprehensive strategy of genomic data mining, bioinformatics and experimental validation was used to evaluate the clinical value of FBXL19-AS1 in the diagnosis and prognosis of HCC and to identify the pathways in which FBXL19-AS1 might be involved. FBXL19-AS1 was up-regulated in HCC tissues, and its high expression was associated with TNM stage and poor prognosis of HCC patients. The combination of FBXL19-AS1 and alpha-fetoprotein (AFP) in plasma could prominently improve the diagnostic validity for HCC. FBXL19-AS1 might stabilize FBXL19 to reduce the amount of macrophage M1, and then promote the occurrence and development of HCC. Meanwhile, FBXL19-AS1 might participate in regulating HCC related pathways through FBXL19-AS1-miRNA-mRNA network. Our findings indicated that FBXL19-AS1 not only serves as a potential biomarker for HCC diagnosis and prognosis, but also might be functionally carcinogenic.
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