scholarly journals Expression and prognosis of CDC45 in cervical cancer based on the GEO database

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12114 ◽  
Author(s):  
Zikang He ◽  
Xiaojin Wang ◽  
Zhiming Yang ◽  
Ying Jiang ◽  
Luhui Li ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Cervical Cancer ◽  
Cox Regression ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cox Regression Analysis ◽  
Potential Biomarker ◽  
Geo Database ◽  
Differential Genes

Cervical cancer is one of the most common malignant tumors in women, and its morbidity and mortality are increasing year by year worldwide. Therefore, an urgent and challenging task is to identify potential biomarkers for cervical cancer. This study aims to identify the hub genes based on the GEO database and then validate their prognostic values in cervical cancer by multiple databases. By analysis, we obtained 83 co-expressed differential genes from the GEO database (GSE63514, GSE67522 and GSE39001). GO and KEGG enrichment analysis showed that these 83 co-expressed it mainly involved differential genes in DNA replication, cell division, cell cycle, etc.. The PPI network was constructed and top 10 genes with protein-protein interaction were selected. Then, we validated ten genes using some databases such as TCGA, GTEx and oncomine. Survival analysis demonstrated significant differences in CDC45, RFC4, TOP2A. Differential expression analysis showed that these genes were highly expressed in cervical cancer tissues. Furthermore, univariate and multivariate cox regression analysis indicated that CDC45 and clinical stage IV were independent prognostic factors for cervical cancer. In addition, the HPA database validated the protein expression level of CDC45 in cervical cancer. Further studies investigated the relationship between CDC45 and tumor-infiltrating immune cells via CIBERSORT. Finally, gene set enrichment analysis (GSEA) showed CDC45 related genes were mainly enriched in cell cycle, chromosome, catalytic activity acting on DNA, etc. These results suggested CDC45 may be a potential biomarker associated with the prognosis of cervical cancer.

scholarly journals Identification of a five-gene signature in association with overall survival for hepatocellular carcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11273
Author(s):  
Lei Yang ◽  
Weilong Yin ◽  
Xuechen Liu ◽  
Fangcun Li ◽  
Li Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Overall Survival ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Enrichment Score ◽  
Hub Genes ◽  
Cox Regression Analysis

Background Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. Methods The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. Results We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.

scholarly journals Identification and Validation of Immune-Related LncRNA Prognostic Signature for Lung Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Guomin Wu ◽  
Qihao Wang ◽  
Ting Zhu ◽  
Linhai Fu ◽  
Zhupeng Li ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Lung Adenocarcinoma ◽  
Clinical Features ◽  
Cox Regression ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Immune Infiltration

This study aimed to establish a prognostic risk model for lung adenocarcinoma (LUAD). We firstly divided 535 LUAD samples in TCGA-LUAD into high-, medium-, and low-immune infiltration groups by consensus clustering analysis according to immunological competence assessment by single-sample gene set enrichment analysis (ssGSEA). Profile of long non-coding RNAs (lncRNAs) in normal samples and LUAD samples in TCGA was used for a differential expression analysis in the high- and low-immune infiltration groups. A total of 1,570 immune-related differential lncRNAs in LUAD were obtained by intersecting the above results. Afterward, univariate COX regression analysis and multivariate stepwise COX regression analysis were conducted to screen prognosis-related lncRNAs, and an eight-immune-related-lncRNA prognostic signature was finally acquired (AL365181.2, AC012213.4, DRAIC, MRGPRG-AS1, AP002478.1, AC092168.2, FAM30A, and LINC02412). Kaplan–Meier analysis and ROC analysis indicated that the eight-lncRNA-based model was accurate to predict the prognosis of LUAD patients. Simultaneously, univariate COX regression analysis and multivariate COX regression analysis were undertaken on clinical features and risk scores. It was illustrated that the risk score was a prognostic factor independent from clinical features. Moreover, immune data of LUAD in the TIMER database were analyzed. The eight-immune-related-lncRNA prognostic signature was related to the infiltration of B cells, CD4+ T cells, and dendritic cells. GSEA enrichment analysis revealed significant differences in high- and low-risk groups in pathways like pentose phosphate pathway, ubiquitin mediated proteolysis, and P53 signaling pathway. This study helps to treat LUAD patients and explore molecules related to LUAD immune infiltration to deeply understand the specific mechanism.

scholarly journals The increasing expression of GPX7 related to the malignant clinical features leading to poor prognosis of glioma patients

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Jiawei Yao ◽  
Xin Chen ◽  
Zhendong Liu ◽  
Ruotian Zhang ◽  
Cheng Zhang ◽  
...  
Keyword(s):  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Multidimensional Data ◽  
Normal Brain ◽  
Cox Regression Analysis ◽  
Diagnosis And Prognosis ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
Therapy Target

Abstract Background Glioma is the most common malignant brain tumor in adults. The standard treatment scheme of glioma is surgical resection combined alternative radio- and chemotherapy. However, the outcome of glioma patients was unsatisfied. Here, we aimed to explore the molecular and biological function characteristics of GPX7 in glioma. Methods The multidimensional data of glioma samples were downloaded from Chinese Glioma Genome Atlas (CGGA). RT-qPCR method was used to identify the expression status of GPX7. Kaplan–Meier curves and Cox regression analysis were used to explore the prognostic value of GPX7. Gene Set Enrichment Analysis (GSEA) was applied to investigate the GPX7-related functions in glioma. Results The results indicated that the expression of GPX7 in glioma was higher compared to that in normal brain tissue. Univariate and multivariate Cox regression analyses confirmed that the expression value of GPX7 was an independent prognostic factor in glioma. The GSEA analysis showed that GPX7 was significantly enriched in the cell cycle pathway, ECM pathway, focal adhesion pathway, and toll-like receptor pathway. Conclusions The GPX7 was recommended as an independent risk factor for patients diagnosed with glioma for the first time and GPX7 could be potentially used as the therapy target in future. Furthermore, we attempted to explore a potential biomarker for improving the diagnosis and prognosis of patients with glioma.

scholarly journals Molecular Classification Based on Prognostic and Cell Cycle-Associated Genes in Patients With Colon Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhiyuan Zhang ◽  
Meiling Ji ◽  
Jie Li ◽  
Qi Wu ◽  
Yuanjian Huang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Colon Cancer ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Molecular Classification ◽  
Original Data ◽  
Gene Set Enrichment Analysis ◽  
Data Sets ◽  
Data Set ◽  
Cox Regression Analysis

The molecular classification of patients with colon cancer is inconclusive. The gene set enrichment analysis (GSEA) of dysregulated genes among normal and tumor tissues indicated that the cell cycle played a crucial role in colon cancer. We performed univariate Cox regression analysis to find out the prognostic-related genes, and these genes were then intersected with cell cycle-associated genes and were further recognized as prognostic and cell cycle-associated genes. Unsupervised non-negative matrix factorization (NMF) clustering was performed based on cell cycle-associated genes. Two subgroups were identified with different overall survival, clinical features, cell cycle enrichment profile, and mutation profile. Through nearest template prediction (NTP), the molecular classification could be effectively repeated in the original data set and validated in several independent data sets indicating that the classification is highly repeatable. Furthermore, we constructed two prognostic signatures in two subgroups, respectively. Our molecular classification based on cell cycle may provide novel insight into the treatment and the prognosis of colon cancer.

scholarly journals A Novel Ferroptosis-Related lncRNA Signature and an Immune Perspective of Cervical Cancer

2021 ◽  
Author(s):  
Pengxiang Li ◽  
Dongchun Qin ◽  
Xuefeng Lv ◽  
Lu Liu ◽  
Mengle Peng
Keyword(s):  
Cervical Cancer ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
Immune Checkpoints ◽  
Roc Curve Analysis ◽  
Cox Regression Analysis ◽  
Immune Related Genes

Abstract Background: Cervical cancer (CC) is the most common reproductive neoplasm in women, especially in developing countries. Ferroptosis, a novel type of cell death, and lncRNAs play critical roles in the prognosis of CC patients and antitumor immunity. Methods: A ferroptosis-related lncRNA signature (FRLS) was constructed by LASSO Cox regression analysis. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, multivariate analysis, and nomogram were used to evaluate and predict the FRLS. Based on the FRLS, immune-related genes, the tumor microenvironment (TME), immune checkpoints, and immunotherapy were investigated. Results: The FRLS was composed of ten lncRNAs and was markedly associated with the overall survival (OS) of CC patients. Gene set enrichment analysis (GSEA) demonstrated that the FRLS was largely associated with immune-related pathways. Weighted gene co-expression network analysis (WGCNA) was performed to analyze immune-related genes and to identify the optimal modules and genes. TLR4 was eventually identified, and its expression was verified in the Gene Expression Omnibus (GEO) database. Then, quantitative real-time PCR (qRT-PCR) was used to validate the results in CC and paracancerous tissues. Besides, our results showed that CD8+ T cells were significantly correlated between the low- and high-risk groups, and it could modulate ferroptosis during tumor immunotherapy. The expression of immune checkpoints was substantially different between the two groups. Additionally, tumor immune dysfunction and exclusion (TIDE) was applied to predict the sensitivity of immune checkpoint inhibitor (ICI) treatment. Conclusion: The FRLS established was significantly associated with prognosis; moreover, the FRLS is a prospective therapeutic target, and combined with immunotherapy, can be used in the treatment of CC patients.

scholarly journals MYD88 Is a Potential Prognostic Gene and Immune Signature of Tumor Microenvironment for Gliomas

2021 ◽  
Vol 11 ◽  
Author(s):  
Qinglong Guo ◽  
Xing Xiao ◽  
Jinsen Zhang
Keyword(s):  
Tumor Microenvironment ◽  
Cox Regression ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Who Grade ◽  
Cox Regression Analysis ◽  
Clinical Cases

PurposeTo explore the profiles of immune and stromal components of the tumor microenvironment (TME) and their related key genes in gliomas.MethodsWe applied bioinformatic techniques to identify the core gene that participated in the regulation of the TME of the gliomas. And immunohistochemistry staining was used to calculate the gene expressions in clinical cases.ResultsThe CIBERSORT and ESTIMATE were used to figure out the composition of TME in 698 glioma cases from The Cancer Genome Atlas (TCGA) database. Differential expression analysis identified 2103 genes between the high and the low-score group. Then the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, univariate Cox regression analysis, and protein–protein interaction (PPI) network construction were conducted based on these genes. MYD88 was identified as the key gene by the combination univariate Cox and PPI analysis. Furthermore, MYD88 expression was significantly associated with the overall survival and WHO grade of glioma patients. The genes in the high-expression MYD88 group were mainly in immune-related pathways in the Gene Set Enrichment Analysis (GSEA). We found that macrophage M2 accounted for the largest portion with an average of 27.6% in the glioma TIICs and was associated with high expression of MYD88. The results were verified in CGGA database and clinical cases in our hospital. Furthermore, we also found the MYD88 expression was higher in IDH1 wild types. The methylation rate was lower in high grade gliomas.ConclusionMYD88 had predictive prognostic value in glioma patients by influencing TIICs dysregulation especially the M2-type macrophages.

scholarly journals High CTHRC1 expression may be closely associated with angiogenesis and indicates poor prognosis in lung adenocarcinoma patients

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yangshan Chen ◽  
Yu Sun ◽  
Yongmei Cui ◽  
Yiyan Lei ◽  
Neng Jiang ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Predictive Model ◽  
Tumor Angiogenesis ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Progression Free Survival ◽  
Gene Set Enrichment Analysis ◽  
Cox Regression Analysis ◽  
Potential Biomarker

Abstract Background This study aimed to investigate the prognostic value of the potential biomarker collagen triple helix repeat containing 1 (CTHRC1) in lung adenocarcinoma (LUAD) patients. Methods A total of 210 LUAD patients diagnosed between 2003 and 2016 in the Department of Pathology of the First Affiliated Hospital of Sun Yat-sen University were included in this study. The expression of CTHRC1 and vascular endothelial growth factor (VEGF), and microvessel density (MVD, determined by CD34 immunostaining) were evaluated by immunohistochemistry in LUAD tissues. The association between the expression of these proteins and clinicopathological features or clinical outcomes was analyzed. Results Here, we confirmed that CTHRC1 expression was associated with prognosis and can serve as a significant predictor for overall survival (OS) and progression-free survival (PFS) in LUAD. Additionally, we observed that CTHRC1 expression was positively associated with tumor angiogenesis markers, such as VEGF expression (P < 0.001) and MVD (P < 0.01). Then, we performed gene set enrichment analysis (GESA) and cell experiments to confirm that enhanced CTHRC1 expression can promote VEGF levels. Based on and cox regression analysis, a predictive model that included CTHRC1, VEGF and MVD was constructed and confirmed as a more accurate independent predictor for OS (P = 0.001) and PFS (P < 0.001) in LUAD than other parameters. Conclusions These results demonstrated that high CTHRC1 expression may be closely related to tumor angiogenesis and poor prognosis in LUAD. The predictive model based on the CTHRC1 level and tumor angiogenesis markers can be used to predict LUAD patient prognosis more accurately.

scholarly journals CKAP2L, as an Independent Risk Factor, Closely Related to the Prognosis of Glioma

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Li Zhu ◽  
Yanlei Zheng ◽  
Ronghua Hu ◽  
Chenchen Hu
Keyword(s):  
Cell Cycle ◽  
Risk Factor ◽  
Independent Risk Factor ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Biological Behavior ◽  
Therapeutic Effects ◽  
Cox Regression Analysis

Recent studies have found that cytoskeleton-associated protein 2 like (CKAP2L), an important oncogene, is involved in the biological behavior of many malignant tumors, but its function in the malignant course of glioma has not been confirmed. The main purpose of this study was to clarify the relationship between prognostic clinical characteristics of glioma patients and CKAP2L expression using data collected from the GEPIA, HPA, CGGA, TCGA, and GEO databases. CKAP2L expression was significantly increased in glioma. Further, Kaplan-Meier plots revealed that increased expression of CKAP2L was associated with shorter survival time of glioma patients in datasets retrieved from multiple databases. Cox regression analysis indicated that CKAP2L can serve as an independent risk factor but also has relatively reliable diagnostic value for the prognosis of glioma patients. The results of gene set enrichment analysis suggested that CKAP2L may play a regulatory role through the cell cycle, homologous recombination, and N-glycan biosynthesis cell signaling pathways. Several drugs with potential inhibitory effects on CKAP2L were identified in the CMap database that may have therapeutic effects on glioma. Finally, knockdown of CKAP2L inhibited the proliferation and invasion of cells by reducing the expression level of cell cycle-related proteins. This is the first study to demonstrate that high CKAP2L expression leads to poor prognosis in glioma patients, providing a novel target for diagnosis and treatment of glioma.

scholarly journals Prognostic Signature for Lung Adenocarcinoma Patients Based on Cell-Cycle-Related Genes

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Jiang ◽  
Jiameng Xu ◽  
Zirui Liao ◽  
Guangbin Li ◽  
Chengpeng Zhang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Training Group ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
External Test

ObjectiveTo screen lung adenocarcinoma (LUAC)-specific cell-cycle-related genes (CCRGs) and develop a prognostic signature for patients with LUAC.MethodsThe GSE68465, GSE42127, and GSE30219 data sets were downloaded from the GEO database. Single-sample gene set enrichment analysis was used to calculate the cell cycle enrichment of each sample in GSE68465 to identify CCRGs in LUAC. The differential CCRGs compared with LUAC data from The Cancer Genome Atlas were determined. The genetic data from GSE68465 were divided into an internal training group and a test group at a ratio of 1:1, and GSE42127 and GSE30219 were defined as external test groups. In addition, we combined LASSO (least absolute shrinkage and selection operator) and Cox regression analysis with the clinical information of the internal training group to construct a CCRG risk scoring model. Samples were divided into high- and low-risk groups according to the resulting risk values, and internal and external test sets were used to prove the validity of the signature. A nomogram evaluation model was used to predict prognosis. The CPTAC and HPA databases were chosen to verify the protein expression of CCRGs.ResultsWe identified 10 LUAC-specific CCRGs (PKMYT1, ETF1, ECT2, BUB1B, RECQL4, TFRC, COCH, TUBB2B, PITX1, and CDC6) and constructed a model using the internal training group. Based on this model, LUAC patients were divided into high- and low-risk groups for further validation. Time-dependent receiver operating characteristic and Cox regression analyses suggested that the signature could precisely predict the prognosis of LUAC patients. Results obtained with CPTAC, HPA, and IHC supported significant dysregulation of these CCRGs in LUAC tissues.ConclusionThis prognostic prediction signature based on CCRGs could help to evaluate the prognosis of LUAC patients. The 10 LUAC-specific CCRGs could be used as prognostic markers of LUAC.

scholarly journals Mining novel cell glycolysis related gene markers that can predict the survival of colon adenocarcinoma patients

2020 ◽  
Vol 40 (8) ◽  
Author(s):  
Sihan Chen ◽  
Guodong Cao ◽  
Wei Wu ◽  
Yida Lu ◽  
Xiaobo He ◽  
...  
Keyword(s):  
Cox Regression ◽  
Mechanistic Model ◽  
Single Gene ◽  
Colon Adenocarcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Gene Markers ◽  
Cox Regression Analysis

Abstract Colon adenocarcinoma (COAD) is a malignant gastrointestinal tumor, often occurring in the left colon, which is regulated by glycolysis-related processes. In past studies, multiple genes that influence the prognosis for survival have been discovered through bioinformatics analysis. However, the prediction of disease prognosis using a single gene is not an accurate method. In the present study, a mechanistic model was established to achieve better prediction for the prognosis of COAD. COAD-related data downloaded from The Cancer Genome Atlas (TCGA) were correlated with the glycolysis process using gene set enrichment analysis (GSEA) to determine the glycolysis-related genes that regulate COAD. Using COX regression analysis, glycolysis-related genes associated with the prognosis of COAD were identified, and the genes screened to establish a predictive model. The risk scores of this model were correlated with relevant clinical data to obtain a connection diagram between the model and survival rate, tumor characteristic data, etc. Finally, genes in the model were correlated with cells in the tumor microenvironment, finding that they affected specific immune cells in the model. Seven genes related to glycolysis were identified (PPARGC1A, DLAT, 6PC2, P4HA1, STC2, ANKZF1, and GPC1), which affect the prognosis of patients with COAD and constitute the model for prediction of survival of COAD patients.

Sign in / Sign up

Export Citation Format

Share Document