scholarly journals Screening of independent prognostic long non-coding RNA for gastric cancer in TCGA

2020 ◽  
Author(s):  
Qiang Zhang ◽  
Qiongyun Chen ◽  
Yinyin Lv ◽  
Xuan Dong ◽  
Xiaoqing Huang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Prognostic Factor ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
Unfavorable Prognostic Factor ◽  
Non Coding Rna ◽  
Cox Analysis

Abstract Background The global incidence of gastric cancer (GC) ranks the fourth among cancers and its 5-year survival is less than 25%. LncRNAs are vital regulators involved in pathological processes of cancer. It is urgent to screen the prognostic lncRNA in GC. Method Expression file and clinical data of GC were downloaded from TCGA. Differentially expressed lncRNAs were calculated by edger R package, followed by the prognosis analysis. COX analysis was conducted to compute the independent factor of GC. Potential signaling pathways that the screened lncRNAs enriched in were evaluated by gene set enrichment analysis (GSEA). At last, Pearson analysis was conducted to predict the possible mechanism of lncRNA in GC process. Result ENSG00000224363 was an unfavorable prognostic factor to OS (overall survival) and DFS (disease-free survival) of GC as COX regression analyzed. GSEA analysis indicated that ENSG00000224363 may regulate cell cycle, apoptosis and autophagy of GC cells. Conclusion LncRNA ENSG00000224363 is overexpressed in GC, serving as an independent unfavorable prognostic factor.

scholarly journals A Prognostic Autophagy-Related Long Non-coding RNA (ARlncRNA) Signature in Acute Myeloid Leukemia (AML)

2021 ◽  
Vol 12 ◽  
Author(s):  
Chunxia Zhao ◽  
Yulu Wang ◽  
Famei Tu ◽  
Shuai Zhao ◽  
Xiaoying Ye ◽  
...  
Keyword(s):  
Cox Regression ◽  
Survival Curve ◽  
Pearson Correlation ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Kaplan Meier ◽  
Non Coding Rna ◽  
Novel Biomarkers ◽  
Meier Survival Curve

BackgroundSome studies have proven that autophagy and lncRNA play important roles in AML. Several autophagy related lncRNA signatures have been shown to affect the survival of patients in some other cancers. However, the role of autophagy related lncRNA in AML has not been explored yet. Hence, this study aims to find an autophagy related lncRNA signature that can affect survival for AML patients.MethodA Pearson correlation analysis, a Kaplan–Meier survival curve, a univariate cox regression, and a multivariate cox regression were performed to establish an autophagy related lncRNA signature. A univariate cox regression, a multivariate cox regression, a Kaplan–Meier survival curve, and a ROC curve were applied to confirm if the signature is an independent prognosis for AML patients. The relationship between the signature and the clinical features was explored by using a T test. Gene Set Enrichment Analysis (GSEA) was used to investigate the potential tumor related pathways.ResultsA four-autophagy related lncRNA (MIR133A1HG, AL359715.1, MIRLET7BHG, and AL356752.1) signature was established. The high risk score based on signature was related to the short survival time of AML patients. The signature was an independent factor for the prognosis for AML patients (HR = 1.684, 95% CI = 1.324–2.142, P < 0.001). The signature was correlated with age, leukocyte numbers, and FAB (M3 or non-M3). The P53, IL6/JAK/STAT3, TNF-α, INF-γ, and IL2/STAT5 pathways might contribute to the differences between the risk groups based on signature in AML.ConclusionThe four autophagy related lncRNAs and their signature might be novel biomarkers for predicting the survival of AML patients. Some biological pathways might be the potential mechanisms of the signature for the survival of AML patients.

scholarly journals Development and Validation of an Apoptosis-Related Genes Signature in Patients with Gastric Cancer

2021 ◽  
Author(s):  
Jianqiao Yang ◽  
Liang Shang ◽  
Leping Li ◽  
Zixiao Wang ◽  
Kangdi Dong ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cox Regression ◽  
External Validation ◽  
Treatment Strategies ◽  
Enrichment Analysis ◽  
Malignant Tumour ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores

Abstract Background: Gastric cancer (GC) is a common malignant tumour of the digestive tract. the prognosis of GC patients is still not optimistic. Apoptosis-related genes (ARGs) plays an important role in the development, invasion, metastasis and drug resistance of GC. Therefore, assessing the interaction between ARGs and the prognosis of GC patients may help identify specific biomarkers.Methods: Differentially expressed genes (DEGs) were identified by integrating gene expression profiling analyses from The Cancer Genome Atlas (TCGA) GC cohort and Gene Set Enrichment Analysis (GSEA) Database. Then, a risk score model was built based on Kaplan-Meier (K-M), least absolute shrinkage and selector operation (LASSO), and multivariate Cox regression analyses. Another cohort (GSE84426) was used for external validation. By combining risk scores with clinical variables, a nomogram was constructed to predict the prognosis of GC patients. Results: We screened 39 DEGS and established a three-gene signature(CAV1、F2、LUM) based on 161 ARGs. In addition, three-gene signature was identified as an independent factor in predicting the prognosis of GC patients and validated in an external independent cohort. Finally, we developed a nomogram that can be applied to clinical practice.Conclusions: Our study established a three-gene signature of GC based on ARGs that has reference significance for in-depth research on the apoptosis mechanism of GC and the exploration of new clinical treatment strategies.

scholarly journals Identification of the m6A RNA Methylation Regulators WTAP as a Novel Prognostic Biomarker and Genomic Alterations in Cutaneous Melanoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Zi-Yi Feng ◽  
Ting Wang ◽  
Xin Su ◽  
Shu Guo
Keyword(s):  
Prognostic Factor ◽  
Cutaneous Melanoma ◽  
Prognostic Value ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Gene Set Enrichment Analysis ◽  
Consensus Clustering ◽  
Genomic Alterations ◽  
Rna Methylation

Background: The purpose of our research was to establish a gene signature and determine the prognostic value of m6A methylation regulators in cutaneous melanoma and WTAP as a protective gene in cutaneous melanoma prognosis, we also evaluated gene mutations in cutaneous melanoma.Methods: We downloaded the RNA-seq transcriptome data and the clinical information for cutaneous melanoma patients from the GTEx and TCGA databases. Consensus clustering analysis was applied to divide the samples into two groups. Then the least absolute shrinkage and selection operator (LASSO) analyses were conducted to construct a risk signature, and we use external and internal datasets to verify its predictive value. We further searched the cBioPortal tools to detect genomic alterations and WTAP mutations. Finally, WTAP was further identified as a prognostic factor, and the related mechanisms mediated by WTAP were predicted by gene set enrichment analysis (GSEA). Experimental validations and have been further carried out.Results: Notably, m6A RNA methylation regulators play significant roles in tumorigenesis and development. In total, we selected three subtypes of cutaneous melanoma according to consensus clustering of the m6A RNA methylation regulators, and the stage of cutaneous melanoma was proven to be related to the subtypes. The Cox regression and LASSO analyses built a risk signature including ELF3, ZC3H13 and WTAP. The prognostic value of the risk signature in internal and external datasets have been proven then. The whole-genome and selected gene WTAP mutations were further explored. WTAP as a single prognostic factor was also explored and found to serve as an independent protective prognostic factor.Conclusions: Our study constructed a stable risk signature composed of m6A RNA methylation regulators in cutaneous melanoma. Moreover, WTAP was identified as a valuable prognostic factor and potential molecular target for cutaneous melanoma treatment.

scholarly journals High ATF4 Expression Is Associated With Poor Prognosis, Amino Acid Metabolism, and Autophagy in Gastric Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Mingliang Wang ◽  
Yida Lu ◽  
Huizhen Wang ◽  
Youliang Wu ◽  
Xin Xu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cell Cycle ◽  
Survival Analysis ◽  
Cell Cycle Progression ◽  
Cox Regression ◽  
Cell Clone ◽  
Intracellular Localization ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis

BackgroundThe role of activating transcription factor 4 (ATF4) underlying gastric cancer (GC) remains unclear. The purpose of this study was to investigate the expression levels and biological functions of ATF4 in GC.MethodsExpression of ATF4 was detected by quantitative PCR (qPCR), Western blotting, and immunohistochemistry. Cox regression was used for survival analysis and the construction of the nomogram. Immunofluorescence was used to identify the intracellular localization of ATF4. Knockdown and overexpression of ATF4 in GC cells followed by wound healing and Transwell assays, EdU and Calcein-AM/propidium iodide (PI) staining, and cell cycle detection were performed to examine its function in vitro. Transmission electron microscopy was performed to assess the autophagy levels upon ATF4 silencing. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and gene set enrichment analysis (GSEA) were used to determine gene enrichment. SPSS 22.0 software, GraphPad Prism 7.0, and R version 3.6.1 were used for statistical analysis.ResultsATF4 expression was upregulated in GC cells and tissues compared with corresponding normal tissues. Survival analysis suggested that a high ATF4 expression was strongly associated with worse overall survival (OS) of GC patients (p < 0.001). The nomogram and the receiver operating characteristic (ROC) curves demonstrated that ATF4 was a highly sensitive and specific prognostic marker of GC [C-index = 0.797, area under the ROC curve (AUC) of 3-year OS = 0.855, and AUC of 5-year OS = 0.863]. In addition, ATF4 knockdown inhibited the cell proliferation, migration, invasion, and cell cycle progression of GC cells in vitro, while overexpression of ATF4 exerted the opposite effects. Bioinformatics analysis showed that ATF4 could promote GC progression possibly by regulating asparagine (Asn) metabolism and autophagy pathways. Further experiments indicated that ATF4 expression was significantly positively correlated with ASNS expression. The inhibition of cell clone formation in Asn-deprived conditions was more significant in the shATF4 group. Finally, we found that ATF4 promoted autophagy through regulating the mTORC1 pathway in GC cells.ConclusionThese findings suggested that ATF4 can significantly promote GC development and serve as an independent prognostic factor for GC.

scholarly journals Identification the ferroptosis-related gene signature in Gastric cancer based on weighted gene co-expression network analysis (WGCNA)

2021 ◽  
Author(s):  
Feng Wang ◽  
Cheng Chen ◽  
Wei-Peng Chen ◽  
Zu-Ling Li ◽  
Hui Cheng
Keyword(s):  
Gastric Cancer ◽  
Prognostic Model ◽  
Biological Function ◽  
Cox Regression ◽  
Prognostic Index ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Analysis Survival ◽  
Blue Module

Abstract Background Ferroptosis is a mode of regulated cell death that depends on iron, plays pivotal roles in regulating various biological process in human cancers. However, the role of ferroptosis in Gastric cancer (GC) remains unclear. Methods A total of 2721 differentially expressed genes (DEGs) were filtered base on The Cancer Genome Atlas (TCGA) (n = 375) dataset. Gene modules were identified based on co-expression network analysis (WGCNA). Functional analysis was performed to explore the biological function. Lasso-penalized and univariate Cox regression (UCR) analysis, survival genes were screened out to construct a prognostic model, which validated by the GSE43292 dataset. Gene set enrichment analysis (GSEA) for prognostic index was performed. Finally, the correlations of ferroptosis and immune cells were assessed through the TIMER database. Results Compared to normal specimens, 1063 highly upregulated and 1658 downregulated genes respectively and their normal counterparts in GC specimens were screened. WGCNA analysis was used and identified 7 modules, of which, blue module with the most significant enrichment result was selected. By taking intersections of blue module and differentially expressed ferroptosis-related genes (DEFRGs), we got 23 common genes. Functional analysis was performed to explore the biological function of the interested genes, and with the consequences Lasso-penalized and univariate Cox regression (UCR) analysis, survival genes were screened out to construct a prognostic model based on 3 genes (SLC1A5, ANGPTL4, and CGAS), which could play a role in predicting the survival of GC patients. UCR and multivariate Cox regression (MCR) analysis revealed that the prognostic index could be used as independent prognostic indicators and validated using another GSE84437 dataset. Notably, patients in high-risk groups had higher levels of higher mutation frequencies such as TTN and TP53.Mechanistically. Gene set enrichment analysis (GSEA) unveiled several significant and pathways involved in GC. TIMER analysis demonstrated that risk score strongly correlated with Macrophage and CD4 + T cells infiltration. In addition, high- and low-risk group illustrated different distributions in different immune status. Conclusions In this study, a novel FRGs signature was built. It could accurately predict GC prognosis and pave the new way for diagnosis and therapy strategy. May reflect the status of tumor immune microenvironment.

scholarly journals Long non-coding RNA ERICH3-AS1 is an unfavorable prognostic factor for gastric cancer

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8050
Author(s):  
Qiongyun Chen ◽  
Xiaoqing Huang ◽  
Xuan Dong ◽  
Jingtong Wu ◽  
Fei Teng ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cell Cycle ◽  
Prognostic Factor ◽  
Disease Free Survival ◽  
The Cancer Genome Atlas ◽  
Apoptosis Pathway ◽  
Non Coding Rna ◽  
Potential Biomarker ◽  
Associated Proteins ◽  
Wnt Pathways

Long non-coding RNAs (lncRNAs) play important roles in gastric cancer (GC), but the mechanism is not fully clear. ERICH3-AS1 (ERICH3 antisense RNA1) is affiliated with the non-coding RNA class which has proven to be involved in the prognostic of GC, but the function of ERICH3-AS1 is still unclear. In this study, we aim to explore the potential function of ERICH3-AS1 in the development of GC and analyze the prognostic role of ERICH3-AS1 in GC. We found that the lncRNA ERICH3-AS1 was significantly up-regulated in GC tissues in the analysis of The Cancer Genome Atlas (TCGA) data; the Kaplan-Meier analysis showed that the higher the expression of ERICH3-AS1 was, the earlier the recurrence and the poorer the prognosis would be in patients. Cox univariate and multivariate analyses revealed that ERICH3-AS1 was a risk factor of disease-free survival (DFS) (p < 0.05) and overall survival (OS) (p < 0.05) of patients. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, it demonstrated that the ERBB pathways, the mitogen-activated protein kinase (MAPK) pathways, the MTOR pathways, p53 pathways and Wnt pathways were differentially enriched in ERICH3-AS1 high expression phenotype. Furthermore, the correlation analysis showed that ERICH3-AS1 had significant correlations with apoptosis-related proteins such as BCL2L10 and CASP14; cell cycle-associated proteins CDK14 and invasion and migration-associated proteins such as MMP20, MMP26 and MMP27. In summary, we identified that increased ERICH3-AS1 might be a potential biomarker for diagnosis and independent prognostic factor of GC. Moreover, ERICH3-AS1 might participate in the oncogenesis and development of tumors via cell cycle and apoptosis pathway mediated by ERBB, MAPK, MTOR, p53 and Wnt pathways.

scholarly journals A novel identified pyroptosis-related prognostic signature of colorectal cancer

2021 ◽  
Vol 18 (6) ◽  
pp. 8783-8796
Author(s):  
Chen Zheng ◽  
◽  
Zhaobang Tan ◽  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Cox Regression ◽  
Critical Role ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Prognostic Signature ◽  
Cox Regression Analysis

<abstract> <p>Colorectal cancer (CRC), one of the most common malignancies worldwide, leads to abundant cancer-related mortalities annually. Pyroptosis, a new kind of programmed cell death, plays a critical role in immune response and tumor progression. Our study aimed to identify a prognostic signature for CRC based on pyroptosis-related genes (PRGs). The difference in PRGs between CRC tissues and normal tissues deposited in the TCGA database was calculated by "limma" R package. The tumor microenvironment (TME) of CRC cases was accessed by the ESTIMATE algorithm. The prognostic PRGs were identified using Cox regression analysis. A least absolute shrinkage and selector operation (LASSO) algorithm was used to calculate the risk scores and construct a clinical predictive model of CRC. Gene Set Enrichment Analysis (GSEA) was performed for understanding the function annotation of the signature in the tumor microenvironment. We found that most PRGs were significantly dysregulated in CRC. Through the LASSO method, three key PRGs were selected to calculate the risk scores and construct the prognostic model for CRC. The risk score was an independent indicator of patient's prognosis. In addition, we classified the CRC patients into two clusters based on risk scores and discovered that CRC patients in cluster 2 underwent worse overall survival and owned higher expression levels of immune checkpoint genes in tumor tissues. In conclusion, our study identified a PRG-related prognostic signature for CRC, according to which we classified the CRC patients into two clusters with distinct prognosis and immunotherapy potential.</p> </abstract>

scholarly journals A model of twenty-three metabolic-related genes predicting overall survival for lung adenocarcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10008
Author(s):  
Zhenyu Zhao ◽  
Boxue He ◽  
Qidong Cai ◽  
Pengfei Zhang ◽  
Xiong Peng ◽  
...  
Keyword(s):  
Prognostic Factor ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Independent Prognostic Factor ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Mechanism Analysis ◽  
Cox Regression Analysis

Background The highest rate of cancer-related deaths worldwide is from lung adenocarcinoma (LUAD) annually. Metabolism was associated with tumorigenesis and cancer development. Metabolic-related genes may be important biomarkers and metabolic therapeutic targets for LUAD. Materials and Methods In this study, the gleaned cohort included LUAD RNA-SEQ data from the Cancer Genome Atlas (TCGA) and corresponding clinical data (n = 445). The training cohort was utilized to model construction, and data from the Gene Expression Omnibus (GEO, GSE30219 cohort, n = 83; GEO, GSE72094, n = 393) were regarded as a testing cohort and utilized for validation. First, we used a lasso-penalized Cox regression analysis to build a new metabolic-related signature for predicting the prognosis of LUAD patients. Next, we verified the metabolic gene model by survival analysis, C-index, receiver operating characteristic (ROC) analysis. Univariate and multivariate Cox regression analyses were utilized to verify the gene signature as an independent prognostic factor. Finally, we constructed a nomogram and performed gene set enrichment analysis to facilitate subsequent clinical applications and molecular mechanism analysis. Result Patients with higher risk scores showed significantly associated with poorer survival. We also verified the signature can work as an independent prognostic factor for LUAD survival. The nomogram showed better clinical application performance for LUAD patient prognostic prediction. Finally, KEGG and GO pathways enrichment analyses suggested several especially enriched pathways, which may be helpful for us investigative the underlying mechanisms.

scholarly journals Upregulation of FGD6 Predicts Poor Prognosis in Gastric Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Jianmin Zeng ◽  
Man Li ◽  
Huasheng Shi ◽  
Jianhui Guo
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Prognostic Factor ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Independent Prognostic Factor ◽  
Gene Set Enrichment Analysis ◽  
High Expression ◽  
Cox Regression Analysis ◽  
The Relationship

Background: The aim of this study was to investigate the prognostic significance of faciogenital dysplasia 6 (FGD6) in gastric cancer (GC).Methods: The data of GC patients from The Cancer Genome Atlas (TCGA) database were used for the primary study. Then, our data were validated by the GEO database and RuiJin cohort. The relationship between the FGD6 level and various clinicopathological features was analyzed by logistic regression and univariate Cox regression. Multivariate Cox regression analysis was used to evaluate whether FGD6 was an independent prognostic factor for survival of patients with GC. The relationship between FGD6 and overall survival time was explored by the Kaplan–Meier method. In addition, gene set enrichment analysis (GSEA) was performed to investigate the possible biological processes of FGD6.Results: The FGD6 level was significantly overexpressed in GC tissues, compared with adjacent normal tissues. The high expression of FGD6 was related to a high histological grade, stage, and T classification and poor prognosis of GC. Multivariate Cox regression analysis showed that FGD6 was an independent prognostic factor for survival of patients with GC. GSEA identified that the high expression of FGD6 was mainly enriched in regulation of actin cytoskeleton.Conclusion: FGD6 may be a prognostic biomarker for predicting the outcome of patients with GC.

scholarly journals ADAMTS12 acts as a tumor microenvironment related cancer promoter in gastric cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yangming Hou ◽  
Yingjuan Xu ◽  
Dequan Wu
Keyword(s):  
Gastric Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Tumor Promoter ◽  
Protein Protein Interaction ◽  
Oxidative Phosphorylation Pathway ◽  
Cox Proportional Hazard Regression

AbstractThe infiltration degree of immune and stromal cells has been shown clinically significant in tumor microenvironment (TME). However, the utility of stromal and immune components in Gastric cancer (GC) has not been investigated in detail. In the present study, ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cell (TIC) in GC cohort, including 415 cases from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were screened by Cox proportional hazard regression analysis and protein–protein interaction (PPI) network construction. Then ADAMTS12 was regarded as one of the most predictive factors. Further analysis showed that ADAMTS12 expression was significantly higher in tumor samples and correlated with poor prognosis. Gene Set Enrichment Analysis (GSEA) indicated that in high ADAMTS12 expression group gene sets were mainly enriched in cancer and immune-related activities. In the low ADAMTS12 expression group, the genes were enriched in the oxidative phosphorylation pathway. CIBERSORT analysis for the proportion of TICs revealed that ADAMTS12 expression was positively correlated with Macrophages M0/M1/M2 and negatively correlated with T cells follicular helper. Therefore, ADAMTS12 might be a tumor promoter and responsible for TME status and tumor energy metabolic conversion.

Sign in / Sign up

Export Citation Format

Share Document