scholarly journals DNA Primase Subunit 1 Expression in Hepatocellular Carcinoma and Its Clinical Implication

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yipeng Zhang ◽  
Lijun Li ◽  
Renzhi Liu ◽  
Changchun Zeng
Keyword(s):  
Clinical Implication ◽  
Enrichment Analysis ◽  
Normal Liver ◽  
Prognostic Indicator ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Diagnostic Significance ◽  
Aberrant Expression ◽  
Dna Primase ◽  
Kaplan Meier

DNA Primase Subunit 1 (PRIM1) is crucial for cancer development and progression. However, there remains a lack of comprehension concerning the clinical implication of PRIM1 in HCC. Here, aberrant expression of PRIM1 was identified in HCC according to available databases. The prognostic value of PRIM1 in patients presenting with HCC was further assessed based on TCGA data. Gene set enrichment analysis (GSEA) was subsequently conducted to investigate the potential function of PRIM1. Additionally, the correlations between tumor-infiltrating immune cells (TIICs) and PRIM1 expression were evaluated. The data from TCGA, GEO, ONCOMINE, and HCCDB databases illustrated that PRIM1 was overexpressed in HCC tissues, compared to normal liver tissues (all p<0.05). Kaplan-Meier analysis revealed that high PRIM1 expression in HCC was closely correlated with worse overall survival (p<0.05). The univariate and multivariate analyses illustrated that PRIM1 expression was an independent novel prognostic indicator in HCC. Additionally, the area under the receiver operating characteristic (AUROC) curve for PRIM1 reached 0.8651, indicating the diagnostic significance of PRIM1 in patients with HCC. GSEA showed that PRIM1 overexpression was significantly enriched in several tumor-related signaling pathways. Besides, TIIC analysis clarified the association between PRIM1 expression and TIICs in HCC. The findings disclose that PRIM1 profoundly implicated in promoting tumorigenesis might work as a desirable biomarker for HCC.

HSF2 is a Promising Prognostic Biomarker and is Correlated With Immune Infiltration in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Bihui Han ◽  
Yanxiu Meng ◽  
Yumei Fan ◽  
Bing Liu ◽  
Jiajie Hou ◽  
...  
Keyword(s):  
Immune Cells ◽  
Critical Role ◽  
Enrichment Analysis ◽  
Normal Liver ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
The Relationship ◽  
Kaplan Meier Plotter

Abstract BackgroundHepatocellular carcinoma (HCC) is one of the most common malignancies and ranks as the second leading cause of cancer-related mortality worldwide. Heat shock factor 2 (HSF2) is a transcription factor that plays a critical role in development, particularly corticogenesis and spermatogenesis. However, studies on the expression and prognostic value of HSF2 and its association with tumor-infiltrating immune cells in HCC are still rare. MethodsThe TCGA, Oncomine, UALCAN, HCCDB and HPA databases were used to investigate HSF2 expression in HCC. Kaplan-Meier plotter, GEPIA and HCCDB databases were used to evaluate the association of HSF2 with the prognosis of HCC patients. Genetic alteration of HSF2 was examined by the cBioPortal database. The mechanism was investigated with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GESA), and the relationship between HSF2 expression and immune infiltration was explored through the TIMER database and CIBERSORT algorithm.Results In the present study, we found that HSF2 expression was significantly upregulated in HCC compared with normal liver tissues. High HSF2 expression was associated with poor survival in HCC patients. GO, KEGG and GESA analyses demonstrated that HSF2 was associated with various signaling pathways, including the immune response. Notably, HSF2 expression was significantly correlated with the infiltration levels of different immune cells. HSF2 expression also displayed a significant correlation with multiple immune marker sets in HCC. ConclusionsIn summary, we explored the clinical significance of HSF2 and provided a therapeutic basis for the early diagnosis, prognostic judgment, and immunotherapy of HCC.

scholarly journals DPYSL2 as potential diagnostic and prognostic biomarker linked to immune infiltration in lung adenocarcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yang-Jie Wu ◽  
Ai-Tao Nai ◽  
Gui-Cheng He ◽  
Fei Xiao ◽  
Zhi-Min Li ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Roc Curve ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
List Type ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Kaplan Meier Plotter

Abstract Background Dihydropyrimidinase like 2 (DPYSL2) has been linked to tumor metastasis. However, the function of DPSY2L in lung adenocarcinoma (LUAD) is yet to be explored. Methods Herein, we assessed DPYSL2 expression in various tumor types via online databases such as Oncomine and Tumor Immune Estimation Resource (TIMER). Further, we verified the low protein and mRNA expressions of DPYSL2 in LUAD via the ULCAN, The TCGA and GEPIA databases. We applied the ROC curve to examine the role of DPYSL2 in diagnosis. The prognostic significance of DPYSL2 was established through the Kaplan–Meier plotter and the Cox analyses (univariate and multivariate). TIMER was used to explore DPYSL2 expression and its connection to immune infiltrated cells. Through Gene Set Enrichment Analysis, the possible mechanism of DPYSL2 in LUAD was investigated. Results In this study, database analysis revealed lower DPYSL2 expression in LUAD than in normal tissues. The ROC curve suggested that expression of DPYSL2 had high diagnostic efficiency in LUAD. The DPYSL2 expression had an association with the survival time of LUAD patients in the Kaplan–Meier plotter and the Cox analyses. The results from TIMER depicted a markedly positive correlation of DPYSL2 expression with immune cells infiltrated in LUAD, such as macrophages, dendritic cells, CD4+ T cells, and neutrophils. Additionally, many gene markers for the immune system had similar positive correlations in the TIMER analysis. In Gene Set Enrichment Analysis, six immune-related signaling pathways were associated with DPYSL2. Conclusions In summary, DPYSL2 is a novel biomarker with diagnostic and prognostic potential for LUAD as well as an immunotherapy target. Highlights Expression of DPYSL2 was considerably lower in LUAD than in normal tissues. Investigation of multiple databases showed a high diagnostic value of DPYSL2 in LUAD. DPYSL2 can independently predict the LUAD outcomes. Immune-related mechanisms may be potential ways for DPYSL2 to play a role in LUAD.

scholarly journals Identification of Epithelial–Mesenchymal Transition-Related Prognostic lncRNAs Biomarkers Associated With Melanoma Microenvironment

2021 ◽  
Vol 9 ◽  
Author(s):  
Bo Xiao ◽  
Liyan Liu ◽  
Zhuoyuan Chen ◽  
Aoyu Li ◽  
Pingxiao Wang ◽  
...  
Keyword(s):  
Cox Regression ◽  
Epithelial Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Roc Curves ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Mesenchymal Transition ◽  
Cox Regression Analysis ◽  
Kaplan Meier

Melanoma is the most common cancer of the skin, associated with a worse prognosis and distant metastasis. Epithelial–mesenchymal transition (EMT) is a reversible cellular biological process that plays significant roles in diverse tumor functions, and it is modulated by specific genes and transcription factors. The relevance of EMT-related lncRNAs in melanoma has not been determined. Therefore, RNA expression data and clinical features were collected from the TCGA database (N = 447). Melanoma samples were randomly assigned into the training (315) and testing sets (132). An EMT-related lncRNA signature was constructed via comprehensive analyses of lncRNA expression level and corresponding clinical data. The Kaplan-Meier analysis showed significant differences in overall survival in patients with melanoma in the low and high-risk groups in two sets. Receiver operating characteristic (ROC) curves were used to measure the performance of the model. Cox regression analysis indicated that the risk score was an independent prognostic factor in two sets. Besides, a nomogram was constructed based on the independent variables. Gene Set Enrichment Analysis (GSEA) was applied to evaluate the potential biological functions in the two risk groups. Furthermore, the melanoma microenvironment was evaluated using ESTIMATE and CIBERSORT algorithms in the risk groups. This study indicates that EMT-related lncRNAs can function as potential independent prognostic biomarkers for melanoma survival.

scholarly journals Increased Expression of LYNX1 in Ovarian Serous Cystadenocarcinoma Predicts Poor Prognosis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Hui Liu ◽  
Ao Wang ◽  
Yushan Ma
Keyword(s):  
Ovarian Cancer ◽  
Univariate Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Serous Cystadenocarcinoma ◽  
Kaplan Meier ◽  
Pathologic Features ◽  
The Relationship

Few studies have reported the function of LYNX1 in ovarian cancer. We retrieved LYNX1 gene expression data and clinical information of 376 patients with ovarian cancer from The Cancer Genome Atlas (TCGA) project website. Wilcoxon signed-rank test and logistic regression were used to analyze the relationship between clinical pathologic features and LYNX1 expression. The Kaplan–Meier method was used to draw survival curves of patients, and Cox regression was used to calculate the relationship between LYNX1 expression and survival rate or the clinicopathological characteristics of the patients. Gene set enrichment analysis (GSEA) was performed, and the correlation between LYNX1 expression and cancer immune infiltrates was investigated via single sample gene set enrichment analysis (ssGSEA). High LYNX1 expression in ovarian serous cystadenocarcinoma (OVs) was associated with tumor residual disease (RD). In Kaplan–Meier survival analysis, patients with OVs who also displayed high LYNX1 expression had decreased overall survival (OS) and disease-specific survival (DSS) than those with low LYNX1 expression. Univariate analysis also supported that patients with high LYNX1 expression had lower OS than those with low LYNX1 expression. LYNX1 expression has the potential to be a prognostic molecular marker of poor survival in OVs.

scholarly journals Decreased DHRS1 expression is a novel predictor of poor survival in patients with hepatocellular carcinoma

2021 ◽  
Vol 15 (15) ◽  
pp. 1319-1331
Author(s):  
Li Li ◽  
Hui-Jing Situ ◽  
Wen-Cheng Ma ◽  
Xuan Liu ◽  
Lu-Lu Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Aberrant Expression ◽  
Normal Tissues ◽  
Multiple Data ◽  
Kaplan Meier ◽  
Survival Gene ◽  
Mrna And Protein Expression

Aim: To investigate the effect of aberrant expression of DHRS1 on hepatocellular carcinoma (HCC). Materials & methods: Kaplan–Meier and Cox regression analyses were performed to evaluate the correlation between DHRS1 and overall survival. Gene set enrichment analysis was performed to explore the potential function of DHRS1 in HCC. Results: Multiple data analysis revealed that DHRS1 mRNA and protein expression level were remarkably lower in HCC than that in normal tissues. In survival analysis, patients with low DHRS1 expression presented a poorer prognosis, and was an independent risk factor for HCC. Conclusion: Decreased DHRS1 expression may be a potential predictor of poor prognosis in HCC.

scholarly journals Identification of Seven Novel Ferroptosis-Related Long Non - Coding RNA Signatures as a Diagnostic Biomarker for Acute Myeloid Leukemia

2021 ◽  
Author(s):  
Zhiyuan Zheng ◽  
Wei Wu ◽  
Zehang Lin ◽  
Shuhan Liu ◽  
Qiaoqian Chen ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Risk Score ◽  
Myeloid Leukemia ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Kaplan Meier ◽  
Acute Myeloid

Abstract Background: Ferroptosis is a newly discovered type of programmed cell death that participates in the biological processes of various cancers. However, the mechanism by which ferroptosis modulates acute myeloid leukemia (AML) remains unclear. This study aimed to investigate the role of ferroptosis-related long non-coding RNAs (lncRNAs) in AML and establish a corresponding prognostic model.Methods: RNA-sequencing data and clinicopathological characteristics were obtained from The Cancer Genome Atlas database, and ferroptosis-related genes were obtained from the FerrDb database. The “limma” R package, Cox regression, and the least absolute shrinkage and selection operator were used to determine the ferroptosis-related lncRNA signature with the lowest Akaike information criteria (AIC). The risk score of ferroptosis-related lncRNAs was calculated and patients with AML were divided into high- and low-risk groups based on the median risk score. The Kaplan-Meier curve and Cox regression were used to evaluate the prognostic value of the risk score. Finally, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the biological functions of the ferroptosis-related lncRNAs.Results: Seven ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan-Meier and Cox regression analyses confirmed that risk scores were independent prognostic predictors of AML in both the training and validation groups (All P < 0.05). In addition, the area under the curve (AUC) analysis confirmed that the signatures had a good predictive ability for the prognosis of AML. GSEA and ssGSEA showed that the seven ferroptosis-related lncRNAs were related to glutathione metabolism and tumor immunity.Conclusions: In this study, seven novel ferroptosis-related lncRNA signatures (AP001266.2, AC133961.1, AF064858.3, AC007383.2, AC008906.1, AC026771.1, and KIF26B-AS1) were established. These signatures were shown to accurately predict the prognosis of AML, which would provide new insights into strategies for the development of new AML therapies.

scholarly journals Identification of Potential Prognostic Biomarker for Predicting Survival in Multiple Myeloma Using Bioinformatics Analysis and Experiments

2021 ◽  
Vol 12 ◽  
Author(s):  
Jian Zhou ◽  
Menghui Zhang ◽  
Yan Zhang ◽  
Xi Shi ◽  
Linlin Liu ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Plasma Cells ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Protein Protein Interaction ◽  
Kaplan Meier ◽  
New Biomarkers ◽  
Protein Protein Interaction Network

Multiple myeloma (MM) is a malignant disease of plasma cells, which remains incurable because of its unclear mechanism and drug resistance. Herein, we aimed to explore new biomarkers and therapeutic targets in MM. After screening differentially expressed genes (DEGs) in GSE6477 and GSE13591 dataset, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of DEGs using DAVID online database. The results indicated that the downregulated DEGs were mainly enriched in the immune-associated biological process. The protein–protein interaction network was constructed by STRING database, on which we performed module analysis and identified key genes. Gene set enrichment analysis (GSEA) and Kaplan–Meier analysis showed that RRM2 could be a novel biomarker in MM diagnosis. We further confirmed that novel RRM2 inhibitor osalmid inhibited MM cell proliferation and triggered cell cycle S phase arrest. Targeting RRM2 was expected to develop new therapeutic strategies for malignant MM.

scholarly journals Overexpression of CENPF correlates with poor prognosis and tumor bone metastasis in breast cancer

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Jingbo Sun ◽  
Jingzhan Huang ◽  
Jin Lan ◽  
Kun Zhou ◽  
Yuan Gao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Bone Metastasis ◽  
Western Blot ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Free Survival ◽  
Gene Set ◽  
Oncomine Database ◽  
Kaplan Meier

Abstract Background Centromere Protein F (CENPF) associates with the centromere–kinetochore complex and influences cell proliferation and metastasis in several cancers. The role of CENPF in breast cancer (BC) bone metastasis remains unclear. Methods Using the ONCOMINE database, we compared the expression of CENPF in breast cancer and normal tissues. Findings were confirmed in 60 BC patients through immunohistochemical (IHC) staining. Microarray data from GEO and Kaplan–Meier plots were used analyze the overall survival (OS) and relapse free survival (RFS). Using the GEO databases, we compared the expression of CENPF in primary lesions, lung metastasis lesions and bone metastasis lesions, and validated our findings in BALB/C mouse 4T1 BC models. Based on gene set enrichment analysis (GSEA) and western blot, we predicted the mechanisms by which CENPF regulates BC bone metastasis. Results The ONCOMINE database and immunohistochemical (IHC) showed higher CENPF expression in BC tissue compared to normal tissue. Kaplan–Meier plots also revealed that high CENPF mRNA expression correlated to poor survival and shorter progression-free survival (RFS). From BALB/C mice 4T1 BC models and the GEO database, CENPF was overexpressed in primary lesions, other target organs, and in bone metastasis. Based on gene set enrichment analysis (GSEA) and western blot, we predicted that CENPF regulates the secretion of parathyroid hormone-related peptide (PTHrP) through its ability to activate PI3K–AKT–mTORC1. Conclusion CENPF promotes BC bone metastasis by activating PI3K–AKT–mTORC1 signaling and represents a novel therapeutic target for BC treatment.

scholarly journals Increased Expression of FN1 in Head and Neck Squamous Cell Carcinoma Predicts Poor Prognosis

2021 ◽  
Author(s):  
Hung-Sheng Shih ◽  
Li-Yu Hung ◽  
Ming-Yu Hsieh
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Neck Squamous Cell Carcinoma ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Kaplan Meier

Abstract Background: A few recent studies have addressed the function of FN1 (Fibronectin 1) in head and neck cancer. The clinical information from 500 HNSCC (Head and neck squamous cell carcinoma) patients with FN1 gene expression data set was published by The Cancer Genome Atlas (TCGA). The correlation between clinicopathologic characteristics and FN1 expression was analyzed by Logistic regression and Wilcoxon signed rank test. Survival function was performed employing Kaplan-Meier estimator, and the relationship between clinicopathological characteristics, prognostic outcome, and FN1 expression were examined by using Cox regression analysis. As Gene set enrichment analysis (GSEA) was performed, we investigated the correlation between FN1 expression and immune cell infiltrates with single-sample gene set enrichment analysis (ssGSEA). Results: Patients with high FN1 expression revealed a significantly decreased overall survival (OS), and disease-specific survival (DSS) than those with low FN1 expression in Kaplan-Meier survival analyses. According to the above results, univariate and multivariate analysis revealed that patients with high FN1 expression had lower OS than those with low FN1 expression.Conclusions: The findings of this research provide insights for FN1 may be potential prognostic biomarkers for diagnosis as well as therapeutic targets in HNSCC patients.

scholarly journals Molecular Features of Glioma Determined and Validated Using Combined TCGA and GTEx Data Analyses

2021 ◽  
Vol 11 ◽  
Author(s):  
Zijiang Yang ◽  
Weiyi Gong ◽  
Ting Zhang ◽  
Heng Gao
Keyword(s):  
Expression Analysis ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Normal Brain ◽  
Gene Set Enrichment ◽  
The Core ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Gliomas are among the most common intracranial tumors which originated from neuroepithelial cells. Increasing evidence has revealed that long noncoding RNA (lncRNA)-microRNA (miRNA)-mRNA module regulation and tumor-infiltrating immune cells play important regulatory roles in the occurrence and progression of gliomas. However, the precise underlying molecular mechanisms remain largely unknown. Data on gliomas in The Cancer Genome Atlas lack normal control samples; to overcome this limitation, we combined 665 The Cancer Genome Atlas glioma RNA sequence datasets with 188 Genotype-Tissue Expression normal brain RNA sequences to construct an expression matrix profile after normalization. We systematically analyzed the expression of mRNAs, lncRNAs, and miRNAs between gliomas and normal brain tissues. Kaplan–Meier survival analyses were conducted to screen differentially expressed mRNAs, lncRNAs, and miRNAs. A prognostic miRNA-related competitive endogenous RNA network was constructed, and the core subnetworks were filtered using 6 miRNAs, 3 lncRNAs, and 11 mRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to investigate the biological functions of significantly dysregulated mRNAs. Co-expression network analysis was performed to analyze and screen the core genes. Furthermore, single-sample Gene Set Enrichment Analysis and immune checkpoint gene expression analysis were performed, as co-expression analysis indicated immune gene dysregulation in glioma. Finally, the expression of representative dysregulated genes was validated in U87 cells at the transcriptional level, establishing a foundation for further research. We identified 7017 mRNAs, 437 lncRNAs, and 9 miRNAs that were differentially expressed in gliomas. Kaplan–Meier survival analysis revealed 5684 mRNAs, 61 lncRNAs, and 7 miRNAs with potential as prognostic signatures in patients with glioma. The hub subnetwork of the competing endogenous RNA network between PART1-hsa-mir-25-SLC12A5/TACC2/BSN/TLN2/ZDHHC8 was screened out. Gene co-expression network, single-sample Gene Set Enrichment Analysis, and immune checkpoint expression analysis demonstrated that tumor-infiltrating immune cells are closely related to gliomas. We identified novel potential biomarkers to predict survival and therapeutic targets for patients with gliomas based on a large-scale sample. Importantly, we filtered pivotal genes that provide valuable information for further exploration of the molecular mechanisms underlying glioma tumorigenesis and progression.

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