Dataset Information

Constructing and Validating a Pyroptosis-Related Genes Prognostic Signature for Stomach Adenocarcinoma and Immune Infiltration: Potential Biomarkers for Predicting the Overall Survival.

ABSTRACT:

Background

Stomach adenocarcinoma (STAD) is a kind of cancer that begins in the stomach cells and has a poor overall survival rate. Following resection surgery, chemotherapy has been suggested as a curative method for stomach cancer. However, it is ineffective. Pyroptosis, a kind of inflammatory programmed cell death, has been shown to play a significant role in the development and progression of STAD. However, whether pyroptosis-related genes (PRGs) can be utilized to predict the diagnosis and prognosis of gastric cancer remains unknown.

Method

The research measured at predictive PRGs in STAD samples from TCGA and GEO. Lasso regression was used to build the prediction model. Coexpression analysis revealed that gene expression was linked to pyroptosis. PRGs were found to be overexpressed in high-risk individuals, implying that they could be used in a model to predict STAD prognosis.

Result

Immunological and tumor-related pathways were discovered using GSEA. In STAD patients, the genes GPX3, PDGFRL, RGS2, and SERPINE1 may be connected to the cancer process. The levels of expression also differed between the two risk groups.

Conclusion

The purpose of this study is to identify and verify STAD-associated PRGs that can effectively guide prognosis and the immunological milieu in STAD patients as well as offer evidence for the development of pyroptosis-related molecularly targeted therapeutics. Therefore, PRGs and the link between immunological and PRGs in STAD may be therapeutic targets.

SUBMITTER: Xu J

PROVIDER: S-EPMC9529402 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Constructing and Validating a Pyroptosis-Related Genes Prognostic Signature for Stomach Adenocarcinoma and Immune Infiltration: Potential Biomarkers for Predicting the Overall Survival.

Xu Jingmin J Chen Ke K Wei Zhou Z Wu Zixuan Z Huang Xuyan X Cai Minjie M Yuan Kai K Huang Peidong P Zhang Jing J Wang Shuai S

Journal of oncology 20220926

<h4>Background</h4>Stomach adenocarcinoma (STAD) is a kind of cancer that begins in the stomach cells and has a poor overall survival rate. Following resection surgery, chemotherapy has been suggested as a curative method for stomach cancer. However, it is ineffective. Pyroptosis, a kind of inflammatory programmed cell death, has been shown to play a significant role in the development and progression of STAD. However, whether pyroptosis-related genes (PRGs) can be utilized to predict the diagno ...[more]

PMID: 36199800

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Project description:BackgroundStomach adenocarcinoma (STAD), caused by mutations in stomach cells, is characterized by poor overall survival. Chemotherapy is commonly administered for stomach cancer patients following surgical resection. An imbalance in tumor metabolic pathways is connected to tumor genesis and growth. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. Metabolic reprogramming is associated with clinical prognosis in various cancers. However, the role of glutamine metabolism genes (GlnMgs) in the fight against STAD remains poorly understood.MethodsGlnMgs were determined in STAD samples from the TCGA and GEO datasets. The TCGA and GEO databases provide information on stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and clinical characteristics. Lasso regression was performed to build the prediction model. The relationship between gene expression and Gln metabolism was investigated using co-expression analysis.ResultsGlnMgs, found to be overexpressed in the high-risk group even in the absence of any symptomatology, demonstrated strong predictive potential for STAD outcomes. GSEA highlighted immunological and tumor-related pathways in the high-risk group. Immune function and m6a gene expression differed significantly between the low- and high-risk groups. AFP, CST6, CGB5, and ELANE may be linked to the oncology process in STAD patients. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and medication sensitivity all revealed a strong link to the gene.ConclusionGlnMgs are connected to the genesis and development of STAD. These corresponding prognostic models aid in predicting the prognosis of STAD GlnMgs and immune cell infiltration in the tumor microenvironment (TME) may be possible therapeutic targets in STAD. Furthermore, the glutamine metabolism gene signature presents a credible alternative for predicting STAD outcomes, suggesting that these GlnMgs could open a new field of study for STAD-focused therapy Additional trials are needed to validate the results of the current study.

Project description:Oxidative stress (OS) response is crucial in oncogenesis and progression of tumor. But the potential prognostic importance of OS-related genes (OSRGs) in stomach adenocarcinoma (STAD) lacked comprehensive study. STAD clinical information and transcriptome data were retrieved from the Gene Expression Omnibus and The Cancer Genome Atlas databases. The prognostic OSRGs were filtered via the univariate Cox analysis and OSRG-based molecular subtypes of STAD were developed using consensus clustering. Weighted gene co-expression network analysis (WGCNA) was subsequently conducted to filter molecular subtype-associated gene modules. The prognosis-related genes were screened via univariate and least absolute shrinkage and selection operator Cox regression analysis were used to construct a prognostic risk signature. Finally, a decision tree model and nomogram were developed by integrating risk signature and clinicopathological characteristics to analyze individual STAD patient's survival. Four OSRG-based molecular subtypes with significant diversity were developed based on 36 prognostic OSRGs for STAD, and an OSRGs-based subtype-specific risk signature with eight genes for prognostic prediction of STAD was built. Survival analysis revealed a strong prognostic performance of the risk signature exhibited in predicting STAD survival. There were significant differences in mutation patterns, chemotherapy sensitivity, clinicopathological characteristics, response to immunotherapy, biological functions, immune microenvironment, immune cell infiltration among different molecular subtypes and risk groups. The risk score and age were verified as independent risk factors for STAD, and a nomogram integrating risk score and age was established, which showed superior predictive performance for STAD prognosis. We developed an OSRG-based molecular subtype and identified a novel risk signature for prognosis prediction, providing a useful tool to facilitate individual treatment for patients with STAD.

Project description:BackgroundPyroptosis has been demonstrated to be an inflammatory form of programmed cell death recently. However, the expression of pyroptosis-related genes (PRGs) in colon adenocarcinoma (COAD) and their correlations with prognosis remain unclear.MethodsData of COAD patients were obtained from The Cancer Genome Atlas (TCGA) database to screen differentially expressed genes (DEGs). Univariate Cox regression analysis and the LASSO Cox regression analysis were applied to construct a gene signature. All COAD patients in TCGA cohort were separated into low-risk subgroup or high-risk subgroup via the risk score. Kaplan-Meier survival analysis and receiver operator characteristic (ROC) curves were adopted to assess its prognostic efficiency. COAD data from the GSE17537 datasets was used for validation. A prognostic nomogram was established to predict individual survival. The correlation between PRGs and immune cell infiltration in COAD was verified based on TIMER database. CIBERSORT analysis was utilized on risk subgroup as defined by model. The protein and mRNA expression level of PRGs were verified by HPA database and qPCR.ResultsA total of 51 differentially expressed PRGs were identified in TCGA cohort. Through univariate Cox regression analysis and LASSO Cox regression analysis, a prognostic model containing 7 PRGs was constructed. Kaplan-Meier survival analysis indicated that patients in the low-risk subgroup exhibited better prognosis compared to those in the high-risk subgroup. Additionally, the area under the curve (AUC) of ROC is 0.60, 0.63, and 0.73 for 1-, 3-, and 5-year survival in TCGA cohort and 0.63, 0.65, and 0.64 in validation set. TIMER database showed a strong correlation between 7 PRGs and tumor microenvironment in COAD. Moreover, CIBERSORT showed significant differences in the infiltration of plasma cells, M0 macrophages, resting dendritic cells, and eosinophils between low-risk subgroup and high-risk subgroup. HPA database showed that protein expression level of SDHB, GZMA, BTK, EEF2K, and NR1H2 was higher in normal tissues. And the transcriptional level of CASP5, BTK, SDHB, GZMA, and RIPK3 was high in normal tissues.ConclusionsOur study identified a novel PRGs signature that could be used to predict the prognosis of COAD patients, which might provide a new therapeutic target for the treatment of COAD patients.

Project description:Stomach adenocarcinoma (STAD) is a common gastric histological cancer type with a high mortality rate. Immunogenic cell death (ICD) plays a key factor during carcinogenesis progress, whereas the prognostic value and role of ICD-related genes (ICDRGs) in STAD remain unclear. The MSigDB database collecting ICDRGs were selected by univariate Cox regression analysis and LASSO algorithm to establish a novel risk model. The Kaplan-Meier survival analysis indicated a significant difference of OS rate of patients by risk score stratification. ESTIMATE, CIBERSORT, and single sample gene set enrichment analysis (ssGSEA) algorithms were conducted to estimate the immune infiltration landscape by risk stratification. Subgroup analysis and tumor mutation burden analysis were also analyzed to identify characteristics between groups. Differences in therapeutic responsiveness to chemotherapeutic drugs and targeted drugs were also analyzed between high-risk group and low-risk group. The impact of one ICDRG, GPX1, on the proliferation, migration and invasiveness of was confirmed by in vitro experiments in GC cells to test the reliability of bioinformatics results. This study gives evidence of the involvement of ICD process in STAD and provides a new perspective for further accurate assessment of prognosis and therapeutic efficacy in STAD patients. Stomach adenocarcinoma (STAD) is a common gastric histological cancer type with a high mortality rate. Immunogenic cell death (ICD) plays a key factor during carcinogenesis progress, whereas the prognostic value and role of ICD-related genes (ICDRGs) in STAD remains unclear. The MSigDB database collected ICDRGs were selected by univariate Cox regression analysis and LASSO algorithm to establish a novel risk model. The Kaplan-Meier survival analysis indicated a significant difference of OS rate of patients by risk score stratification. ESTIMATE, CIBERSORT, and single sample gene set enrichment analysis (ssGSEA) algorithms were conducted to estimate the immune infiltration landscape by risk stratification. Subgroup analysis and tumor mutation burden analysis were also analyzed to identify characteristics between groups. Differences in therapeutic responsiveness to chemotherapeutic drugs and targeted drugs were also analyzed between high-risk group and low-risk group. The impact of one ICDRG, GPX1, on the proliferation, migration and invasiveness of was confirmed by in vitro experiments in GC cells to test the reliability of bioinformatics results. This study gives evidence of the involvement of ICD process in STAD and provides a new perspective for further accurate assessment of prognosis and therapeutic efficacy in STAD patients.

Dataset Information

Constructing and Validating a Pyroptosis-Related Genes Prognostic Signature for Stomach Adenocarcinoma and Immune Infiltration: Potential Biomarkers for Predicting the Overall Survival.

Background

Method

Result

Conclusion

Publications

Constructing and Validating a Pyroptosis-Related Genes Prognostic Signature for Stomach Adenocarcinoma and Immune Infiltration: Potential Biomarkers for Predicting the Overall Survival.

Similar Datasets

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