Identification of Protein Phosphatase 1 Regulatory Subunit 3 as a Prognostic Biomarker in Patients with Gastric Cancer

Abstract Background: The study aimed to determine: (1) The potential application of the protein phosphatase 1 regulatory subunit 3 (PPP1R3B) gene as a prognostic marker in gastric cancer (GC) and (2) The possible role of PPP1R3B in biological processes and pathways.Methods: The complete RNA-sequencing (RNA-seq) data and other relevant clinical and survival information was acquired from The Cancer Genome Atlas (TCGA). The univariate survival analysis with Cox regression model and Kaplan‐Meier analysis was used to investigate the association between clinical pathologic features and PPP1R3B gene expression. A genome-wide gene set enrichment analysis (GSEA) was also conducted to define the underlying molecular mechanism of the PPP1R3B gene in GC development.Results: The Log rank test and Cox regression identified the prognostic application of PPP1R3B expression in GC patients. Comprehensive survival analysis suggested that PPP1R3B might be an independent predictive factor for the survival time in patients with GC. The prognostic relationship between PPP1R3B and GC was also verified by the Kaplan–Meier plotter (KM plotter). Patients with a high expression of PPP1R3B were associated with a shorter clinical survival time. Additionally, GSEA demonstrated that PPP1R3B might be involved in multiple biological processes and pathways.Conclusions: Our findings demonstrated that the PPP1R3B gene could be used as a potential molecular marker for GC prognosis.

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

Frontiers in Oncology ◽

10.3389/fonc.2021.740120 ◽

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.

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Role of CXCR4 as a Prognostic Biomarker Associated With the Tumor Immune Microenvironment in Gastric Cancer

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.654504 ◽

2021 ◽

Vol 9 ◽

Author(s):

Yuyang Gu ◽

Wenyue Gu ◽

Rongrong Xie ◽

Zhi Chen ◽

Tongpeng Xu ◽

...

Keyword(s):

Gastric Cancer ◽

Immune Cells ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

Biological Processes ◽

Regression Analyses ◽

Related Gene ◽

Ppi Network ◽

Tumor Tissues

Background: Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide, accounting for high rates of morbidity and mortality in the population. The tumor microenvironment (TME), which plays a crucial role in GC progression, may serve as an optimal prognostic predictor of GC. In this study, we identified CXC motif chemokine receptor 4 (CXCR4) as a TME-related gene among thousands of differentially expressed genes (DEGs). We showed that CXCR4 can be used to predict the effect of immunotherapy in patients with GC.Methods: GC samples obtained from The Cancer Genome Atlas (TCGA) were analyzed for the presence of stroma (stromal score), the infiltration of immune cells (immune score) in tumor tissues, and the tumor purity (estimate score) using the ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) algorithm. DEGs were sorted based on differences in the values of the three scores. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to determine the biological processes and pathways enriched in these DEGs. The correlations of scores with clinicopathological features and overall survival (OS) of patients with GC were assessed by the Kaplan–Meier survival and Cox regression analyses. Through subsequent protein–protein interaction (PPI) network and univariate Cox regression analyses, CXCR4 was identified as a TME-related gene. Gene Set Enrichment Analysis (GSEA) was performed to assess the role of CXCR4 in the TME of GC. The CIBERSORT algorithm was used to further explore the correlation between tumor-infiltrating immune cells (TIICs) and CXCR4. Finally, the TISIDB database was used to predict the efficacy of immunotherapy in patients with GC.Results: We extracted 1231 TME-related DEGs and by an overlapping screening of PPI network and univariate Cox regression, CXCR4 was identified as a biomarker of TME, which deeply engaged in immune-related biological processes of gastric cancer and have close association with several immunocompetent cells.Conclusion: CXCR4 may be a useful biomarker of prognosis and an indicator of the TME in GC.

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Identification of crucial genes of pyrimidine metabolism as biomarkers for gastric cancer prognosis

Cancer Cell International ◽

10.1186/s12935-021-02385-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Zhengxin Wu ◽

Jinshui Tan ◽

Yifan Zhuang ◽

Mengya Zhong ◽

Yubo Xiong ◽

...

Keyword(s):

Gastric Cancer ◽

Regression Analysis ◽

Survival Analysis ◽

Risk Model ◽

Cox Regression ◽

Clinical Samples ◽

Pyrimidine Metabolism ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Cox Analysis

Abstract Background Metabolic reprogramming has been reported in various kinds of cancers and is related to clinical prognosis, but the prognostic role of pyrimidine metabolism in gastric cancer (GC) remains unclear. Methods Here, we employed DEG analysis to detect the differentially expressed genes (DEGs) in pyrimidine metabolic signaling pathway and used univariate Cox analysis, Lasso-penalizes Cox regression analysis, Kaplan–Meier survival analysis, univariate and multivariate Cox regression analysis to explore their prognostic roles in GC. The DEGs were experimentally validated in GC cells and clinical samples by quantitative real-time PCR. Results Through DEG analysis, we found NT5E, DPYS and UPP1 these three genes are highly expressed in GC. This conclusion has also been verified in GC cells and clinical samples. A prognostic risk model was established according to these three DEGs by Univariate Cox analysis and Lasso-penalizes Cox regression analysis. Kaplan–Meier survival analysis suggested that patient cohorts with high risk score undertook a lower overall survival rate than those with low risk score. Stratified survival analysis, Univariate and multivariate Cox regression analysis of this model confirmed that it is a reliable and independent clinical factor. Therefore, we made nomograms to visually depict the survival rate of GC patients according to some important clinical factors including our risk model. Conclusion In a word, our research found that pyrimidine metabolism is dysregulated in GC and established a prognostic model of GC based on genes differentially expressed in pyrimidine metabolism.

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Identified a Disintegrin and Metalloproteinase with Thrombospondin Motifs 6 Serve as a Novel Gastric Cancer Prognostic Biomarker by Bioinformatics Analysis

Bioscience Reports ◽

10.1042/bsr20204359 ◽

2021 ◽

Author(s):

Ya-zhen Zhu ◽

Yi Liu ◽

Xi-wen Liao ◽

Shan-shan Luo

Keyword(s):

Gastric Cancer ◽

Survival Analysis ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Rank Test ◽

Poor Overall Survival ◽

Qrt Pcr ◽

A Genome ◽

A Disintegrin And Metalloproteinase

Objective: We aimed to explore the prognostic value of a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS) genes in gastric cancer (GC). Methods: The RNA-sequencing (RNA-seq) expression data for 351 GC patients and other relevant clinical data was acquired from The Cancer Genome Atlas (TCGA). Survival analysis and a genome-wide gene set enrichment analysis (GSEA) were performed to define the underlying molecular value of the ADAMTS genes in GC development. Besides, qRT-PCR and immunohistochemistry were all employed to validate the relationship between the expression of these genes and GC patient prognosis. Results: The Log rank test with both Cox regression and Kaplan–Meier survival analysis showed that ADAMTS6 expression profile correlated with the GC patients clinical outcome. Patients with a high expression of ADAMTS6 were associated with poor overall survival (OS). Comprehensive survival analysis of the ADAMTS genes suggests that ADAMTS6 might be an independent predictive factor for the OS in patients with GC. Besides, GSEA demonstrated that ADAMTS6 might be involved in multiple biological processes and pathways, such as the vascular endothelial growth factor A (VEGFA), kirsten rat sarcoma viral oncogene (KRAS), tumor protein P53, c-Jun N-terminal kinase (JNK), cadherin (CDH1) or tumor necrosis factor (TNF) pathways. It was also confirmed by immunohistochemistry and qRT-PCR that ADAMTS6 is highly expressed in GC, which may be related to the prognosis of GC patients. Conclusions: In summary, our study demonstrated that ADAMTS6 gene could be used as a potential molecular marker for GC prognosis.

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Identified a Disintegrin and Metalloproteinase with Thrombospondin Motifs 6 Serve as a Novel Gastric Cancer Prognostic Biomarker by Integrating Analysis of Gene Expression Profile

10.21203/rs.3.rs-41038/v1 ◽

2020 ◽

Author(s):

Ya-zhen Zhu ◽

Yi Liu ◽

Xi-wen Liao ◽

Xian-wei Mo ◽

Yuan Lin ◽

...

Keyword(s):

Gastric Cancer ◽

Survival Analysis ◽

Expression Profile ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Rank Test ◽

Poor Overall Survival ◽

A Genome ◽

A Disintegrin And Metalloproteinase

Abstract Objective: We aimed to explore the prognostic value of a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS) genes in gastric cancer (GC).Methods: The RNA-sequencing (RNA-seq) expression data for 351 GC patients and other relevant clinical data was acquired from The Cancer Genome Atlas (TCGA). Survival analysis and a genome-wide gene set enrichment analysis (GSEA) were performed to define the underlying molecular value of the ADAMTS genes in GC development.Results: The Log rank test with both Cox regression and Kaplan–Meier survival analysis showed that ADAMTS6 expression profile correlated with the GC patients’ clinical outcome. Patients with a high expression of ADAMTS6 were associated with poor overall survival (OS). Comprehensive survival analysis of the ADAMTS genes suggests that ADAMTS6 might be an independent predictive factor for the OS in patients with GC. Besides, GSEA demonstrated that ADAMTS6 might be involved in multiple biological processes and pathways, such as the vascular endothelial growth factor A (VEGFA), kirsten rat sarcoma viral oncogene (KRAS), tumor protein P53, c-Jun N-terminal kinase (JNK), cadherin (CDH1) or tumor necrosis factor (TNF) pathways.Conclusions: In summary, our study demonstrated that ADAMTS6 gene could be used as a potential molecular marker for GC prognosis.

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LncRNA MSC-AS1 Is a Diagnostic Biomarker and Predicts Poor Prognosis in Patients With Gastric Cancer by Integrated Bioinformatics Analysis

Frontiers in Medicine ◽

10.3389/fmed.2021.795427 ◽

2021 ◽

Vol 8 ◽

Author(s):

Wei Yang ◽

Fusheng Ge ◽

Shuaibing Lu ◽

Zhiming Shan ◽

Liangqun Peng ◽

...

Keyword(s):

Gastric Cancer ◽

Overall Survival ◽

Logistic Regression ◽

Survival Analysis ◽

Mapk Pathway ◽

Gene Set Enrichment Analysis ◽

Wild Type ◽

Kaplan Meier ◽

Potential Biomarker ◽

The Impact

Numerous studies have shown that long uncoded RNA (lncRNA) MSC-AS1 may play an important role in the occurrence and development of some types of cancer. However, its role in gastric cancer has rarely been discussed. This study aimed to clarify the association between lncRNA MSC-AS1 and gastric cancer using The Cancer Genome Atlas (TCGA) database. We determined the expression of MSC-AS1 using the Wilcoxon rank sum test; in addition, logistic regression was applied to evaluate the association between MSC-AS1 and clinicopathological characteristics. Also, Kaplan-Meier and Cox regression were used to evaluate the relationship between MSC-AS1 and survival. A nomogram was conducted to predict the impact of MSC-AS1 on prognosis. Moreover, Gene Set enrichment analysis (GSEA) was performed to annotate the biological function of MSC-AS1. Quantitative analysis of immune infiltration was carried out by single-set GSEA (ssGSEA). The MSC-AS1 level was elevated in gastric cancer tissues. An increased MSC-AS1 level was significantly correlated with T stage (odds ratio [OR] = 2.55 for T3 and T4 vs. T1 and T2), histological type (OR = 5.28 for diffuse type vs. tubular type), histological grade (OR = 3.09 for grade 3 vs. grades 1 and 2), TP53 status (OR = 0.55 for mutated vs. wild type), and PIK3CA status (OR = 0.55 for mutated vs. wild type) (all p < 0.05) by univariate logistic regression. Kaplan-Meier survival analysis showed high MSC-AS1 expression had a poor overall survival [hazard ratio (HR) = 1.75; 95% confidence interval (CI): 1.25–2.45; p = 0.001] and progression-free interval (HR = 1.47; 95% CI: 1.03–2.10; p = 0.034). Multivariate survival analysis revealed that MSC-AS1 expression (HR = 1.681; 95% CI: 1.057–2.673; p = 0.028) was independently correlated with overall survival. GSEA demonstrated that the P38/MAPK pathway, the VEGF pathway, the cell adhesion molecules cams, the NOD-like receptor signaling pathway were differentially enriched in the high MSC-AS1 expression phenotype. SsGSEA and Spearman correlation revealed the relationships between MSC-AS1 and macrophages, NK cells, and Tems were the strongest. Coregulatory proteins were included in the PPI network. Upregulated lncRNA MSC-AS1 might be a potential biomarker for the diagnosis and prognosis of gastric cancer.

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Identification of Crucial Genes of Pyrimidine Metabolism as Biomarkers for Gastric Cancer Prognosis

10.21203/rs.3.rs-951416/v1 ◽

2021 ◽

Author(s):

Zhengxin Wu ◽

Jinshui Tan ◽

Yifan Zhuang ◽

Mengya Zhong ◽

Yubo Xiong ◽

...

Keyword(s):

Gastric Cancer ◽

Regression Analysis ◽

Survival Analysis ◽

Risk Model ◽

Cox Regression ◽

Clinical Samples ◽

Pyrimidine Metabolism ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Cox Analysis

Abstract Background Metabolic reprogramming has been reported in various kinds of cancers and is related to clinical prognosis, but the prognostic role of pyrimidine metabolism in gastric cancer (GC) remains unclear. Methods Here, we employed DEG analysis to detect the differentially expressed genes (DEGs) in pyrimidine metabolic signaling pathway and used univariate Cox analysis, Lasso-penalizes Cox regression analysis, Kaplan-Meier survival analysis, univariate and multivariate Cox regression analysis to explore their prognostic roles in GC. The DEGs were experimentally validated in GC cells and clinical samples by quantitative real-time PCR. Results Through DEG analysis, we found NT5E, DPYS and UPP1 these three genes are highly expressed in GC. This conclusion has also been verified in GC cells and clinical samples. A prognostic risk model was established according to these three DEGs by Univariate Cox analysis and Lasso-penalizes Cox regression analysis. Kaplan-Meier survival analysis suggested that patient cohorts with high risk score undertook a lower overall survival rate than those with low risk score. Stratified survival analysis, Univariate and multivariate Cox regression analysis of this model confirmed that it is a reliable and independent clinical factor. Therefore, we made nomograms to visually depict the survival rate of GC patients according to some important clinical factors including our risk model. Conclusion In a word, our research found that pyrimidine metabolism is dysregulated in GC and established a prognostic model of GC based on genes differentially expressed in pyrimidine metabolism.

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Faculty Opinions recommendation of Selective inhibition of a regulatory subunit of protein phosphatase 1 restores proteostasis.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.9847956.12716056 ◽

2011 ◽

Author(s):

Wolfgang Peti

Keyword(s):

Protein Phosphatase ◽

Selective Inhibition ◽

Protein Phosphatase 1 ◽

Regulatory Subunit

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Comprehensive analysis of genomic mutation signature and tumor mutation burden for prognosis of intrahepatic cholangiocarcinoma

BMC Cancer ◽

10.1186/s12885-021-07788-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Rui Zhang ◽

Qi Li ◽

Jialu Fu ◽

Zhechuan Jin ◽

Jingbo Su ◽

...

Keyword(s):

Intrahepatic Cholangiocarcinoma ◽

Cox Regression ◽

Tnm Stage ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Tumor Mutation Burden ◽

Kaplan Meier ◽

Mutation Burden ◽

Significant Difference ◽

Genomic Mutation

Abstract Background Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy of the biliary tract. Analysis of somatic mutational profiling can reveal new prognostic markers and actionable treatment targets. In this study, we explored the utility of genomic mutation signature and tumor mutation burden (TMB) in predicting prognosis in iCCA patients. Methods Whole-exome sequencing and corresponding clinical data were collected from the ICGC portal and cBioPortal database to detect the prognostic mutated genes and determine TMB values. To identify the hub prognostic mutant signature, we used Cox regression and Lasso feature selection. Mutation-related signature (MRS) was constructed using multivariate Cox regression. The predictive performances of MRS and TMB were assessed using Kaplan–Meier (KM) analysis and receiver operating characteristic (ROC). We performed a functional enrichment pathway analysis using gene set enrichment analysis (GSEA) for mutated genes. Based on the MRS, TMB, and the TNM stage, a nomogram was constructed to visualize prognosis in iCCA patients. Results The mutation landscape illustrated distributions of mutation frequencies and types in iCCA, and generated a list of most frequently mutated genes (such as Tp53, KRAS, ARID1A, and IDH1). Thirty-two mutated genes associated with overall survival (OS) were identified in iCCA patients. We obtained a six-gene signature using the Lasso and Cox method. AUCs for the MRS in the prediction of 1-, 3-, and 5-year OS were 0.759, 0.732, and 0.728, respectively. Kaplan–Meier analysis showed a significant difference in prognosis for patients with iCCA having a high and low MRS score (P < 0.001). GSEA was used to show that several signaling pathways, including MAPK, PI3K-AKT, and proteoglycan, were involved in cancer. Conversely, survival analysis indicated that TMB was significantly associated with prognosis. GSEA indicated that samples with high MRS or TMB also showed an upregulated expression of pathways involved in tumor signaling and the immune response. Finally, the predictive nomogram (that included MRS, TMB, and the TNM stage) demonstrated satisfactory performance in predicting survival in patients with iCCA. Conclusions Mutation-related signature and TMB were associated with prognosis in patients with iCCA. Our study provides a valuable prognostic predictor for determining outcomes in patients with iCCA.

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