Dataset Information

Analysis of the Prognostic Significance and Immune Infiltration of the Amino Acid Metabolism-Related Genes in Colon Adenocarcinoma.

ABSTRACT: Amino acid metabolization is verified to be a part in the progression of cancer. However, genes related to the amino acid metabolism have not been identified in colon adenocarcinoma (COAD). A systematic prognostic model of COAD becomes a pressing need. Among genes related to the amino acid metabolism, RIMKLB, ASPG, TH, MTAP, AZIN2, PSMB2, HDC, ACMSD, and PSMA8 were identified to construct a risk model. Kaplan-Meier (K-M) analyses demonstrated that the high-risk group achieved a poor prognosis. Area under the respective ROC (AUC) values indicated the robustness of the model. To highlight its clinical value, multivariate Cox was used to obtain the optimal variables to construct a nomogram. A higher tumor mutation burden was observed in the high-risk group. However, the low-risk group had a stronger immune infiltration. Seven molecular subtypes were found by consensus cluster. Twenty-two hub genes were identified related to the ESTIMATE score using WGCNA. In brief, our research constructed a stable prognostic model related to the amino acid metabolism in COAD, revealing its connection to the immune microenvironment. The model guided the outcome of COAD and the direction of immunotherapy.

SUBMITTER: Wang Z

PROVIDER: S-EPMC9399353 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Analysis of the Prognostic Significance and Immune Infiltration of the Amino Acid Metabolism-Related Genes in Colon Adenocarcinoma.

Wang Zhenling Z Huang Changzhi C Wu Jingyu J Zhang Hongqiang H Shao Yu Y Fu Zan Z

Frontiers in genetics 20220810

Amino acid metabolization is verified to be a part in the progression of cancer. However, genes related to the amino acid metabolism have not been identified in colon adenocarcinoma (COAD). A systematic prognostic model of COAD becomes a pressing need. Among genes related to the amino acid metabolism, RIMKLB, ASPG, TH, MTAP, AZIN2, PSMB2, HDC, ACMSD, and PSMA8 were identified to construct a risk model. Kaplan-Meier (K-M) analyses demonstrated that the high-risk group achieved a poor prognosis. A ...[more]

PMID: 36035152

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Project description:Background: Fatty acid metabolism (FAM), as a hallmark of caner, plays important roles in tumor initiation and carcinogenesis. However, the significance of fatty acid metabolism-related genes in colon adenocarcinoma (COAD) are largely unknown. Methods: RNA sequencing data and clinical information were downloaded from the Cancer Genome Atlas (TCGA) cohort. Univariate and multivariate Cox regression analyses were utilized to construct a fatty acid metabolism-related gene signature. Kaplan-Meier survival and receiver operating characteristic (ROC) analyses were used to verify the performance of this signature. GEO datasets were applied to validate the signature. Maftools package was utilized to analyze the mutation profiles of this signature. Correlation between the risk signature and stemness scores was compared by RNA stemness score (RNAss). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set variation analysis (GSVA) were performed to explore the potential functions and signaling pathways. Immune landscape of the signature was explored by analyzing different immune cells infiltration, immune functions and microsatellite instability. A nomogram was constructed by combining the risk signature and multiple clinical factors. Expression levels and prognostic values of the risk genes were revealed in the cancer genome atlas and GEO databases. Moreover, the expression the risk genes were measured in cell lines using real time quantitative PCR (qRT-PCR). Results: Eight fatty acid metabolism-related genes (CD36, ENO3, MORC2, PTGR1, SUCLG2, ELOVL3, ELOVL6 and CPT2) were used to construct a risk signature. This signature demonstrated better prognostic value than other clinicopathological parameters, with AUC value was 0.734 according to the cancer genome atlas database. There was negative correlation between the riskscore and RNA stemness score. The patients in the high-risk group demonstrated higher infiltration of M0 macrophages, and less infiltration of activated CD4 memory T cells and Eosinophils. There were more MSI patients in the high-risk group than those in the low-risk group (38% vs. 30%). The risk scores of patients in the MSI group were slightly higher than those in the microsatellite stability group. Gene ontology, kyoto encyclopedia of genes and genomes and gene set variation analysis enrichment analyses showed that several metabolism-related functions and signaling pathways were enriched. A nomogram showed good predictive capability of the signature. Moreover, qRT-PCR revealed upregulated expression of ENO3, MORC2, SUCLG2 and ELOVL6, and downregulated expression of CPT2 in all examined colon adenocarcinoma cell lines. Conclusion: This study provided novel insights into a fatty acid metabolism-related signature in the prognosis an immune landscape of colon adenocarcinoma patients.

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:BackgroundThe heterogeneity of tumor tissue is one of the reasons for the poor effect of tumor treatment, which is mainly affected by the tumor immune microenvironment and metabolic reprogramming. But more research is needed to find out how the tumor microenvironment (TME) and metabolic features of colon adenocarcinoma (COAD) are related.MethodsWe obtained the transcriptomic and clinical data information of COAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Consensus clustering analysis was used to identify different molecular subtypes, identify differentially expressed genes (DEGs) associated with immune-and metabolism-related genes (IMRGs) prognosis. Univariate and multivariable Cox regression analysis and Lasso regression analysis were applied to construct the prognostic models based on the IMRG risk score. The correlations between risk scores and TME, immune cell infiltration, and immune checkpoint genes were investigated. Lastly, potential appropriate drugs related to the risk score were screened by drug sensitivity analysis.ResultsBy consensus clustering analysis, we identified two distinct molecular subtypes. It was also found that the multilayered IMRG subtypes were associated with the patient's clinicopathological characteristics, prognosis, and TME cell infiltration characteristics. Meanwhile, a prognostic model based on the risk score of IMRGs was constructed and its predictive power was verified internally and externally. Clinicopathological analysis and nomogram give it better clinical guidance. The IMRG risk score plays a key role in immune microenvironment infiltration. Patients in the high-risk groups of microsatellite instability (MSI) and tumor mutational burden (TMB) were found to, although with poor prognosis, actively respond to immunotherapy. Furthermore, IMRG risk scores were significantly associated with immune checkpoint gene expression. The potential drug sensitivity study helps come up with and choose a chemotherapy treatment plan.ConclusionOur comprehensive analysis of IMRG signatures revealed a broad range of regulatory mechanisms affecting the tumor immune microenvironment (TIME), immune landscape, clinicopathological features, and prognosis. And to explore the potential drugs for immunotherapy. It will help to better understand the molecular mechanisms of COAD and provide new directions for disease treatment.

Project description:BackgroundAT-rich interaction domain 1A (ARID1A) is an essential subunit of the switch/sucrose non-fermentable chromatin remodeling complex and is considered to be a tumor suppressor. The Cancer Genome Atlas (TCGA) molecular classification has deepened our understanding of gastric cancer at the molecular level. This study explored the significance of ARID1A expression in TCGA subtypes of gastric adenocarcinoma.MethodsWe collected 1248 postoperative patients with gastric adenocarcinoma, constructed tissue microarrays, performed immunohistochemistry for ARID1A, and obtained correlations between ARID1A and clinicopathological variables. We then carried out the prognostic analysis of ARID1A in TCGA subtypes. Finally, we screened patients by random sampling and propensity score matching method and performed multiplex immunofluorescence to explore the effects of ARID1A on CD4, CD8, and PD-L1 expression in TCGA subtypes.ResultsSeven variables independently associated with ARID1A were screened out: mismatch repair proteins, PD-L1, T stage, differentiation status, p53, E-cadherin, and EBER. The independent prognostic variables in the genomically stable (GS) subtype were N stage, M stage, T stage, chemotherapy, size, and ARID1A. PD-L1 expression was higher in the ARID1A negative group than in the ARID1A positive group in all TCGA subgroups. CD4 showed higher expression in the ARID1A negative group in most subtypes, while CD8 did not show the difference in most subtypes. When ARID1A was negative, PD-L1 expression was positively correlated with CD4/CD8 expression; while when ARID1A was positive, this correlation disappeared.ConclusionsThe negative expression of ARID1A occurred more frequently in the Epstein-Barr virus and microsatellite instability subtypes and was an independent adverse prognostic factor in the GS subtype. In the TCGA subtypes, ARID1A negative expression caused increased CD4 and PD-L1 expression, whereas CD8 expression appeared independent of ARID1A. The expression of CD4/CD8 induced by ARID1A negativity was accompanied by an increase in PD-L1 expression.

Project description:Colon adenocarcinoma (COAD), one of the common clinical cancers, exhibits high morbidity and mortality, and its pathogenesis and treatment are still underdeveloped. Numerous studies have demonstrated the involvement of bile acids in tumour development, while the potential role of their metabolism in the tumor microenvironment (TME) has not been explored. A collection of 481 genes related to bile acid metabolism were obtained, and The Cancer Genome Atlas-based COAD risk model was developed using the least absolute shrinkage selection operator (LASSO) regression analysis. The Gene Expression Omnibus dataset was used to validate the results. The predictive performance of the model was verified using column line plots, principal component analysis and receiver operating characteristic curves. Then, we analysed the differences between the high- and low-risk groups from training set based on clinical characteristics, immune cell infiltration, immune-related functions, chemotherapeutic drug sensitivity and immunotherapy efficacy. Additionally, we constructed a protein-protein interaction network to screen for target genes, which were further investigated in terms of differential immune cell distribution. A total of 234 bile acids-related differentially expressed genes were obtained between normal and tumour colon tissues. Among them, 111 genes were upregulated and 123 genes were down-regulated in the tumour samples. Relying on the LASSO logistic regression algorithm, we constructed a model of bile acid risk score, comprising 12 genes: CPT2, SLCO1A2, CD36, ACOX1, CDKN2A, HADH, GABRD, LEP, TIMP1, MAT1A, SLC6A15 and PPARGC1A. This model was validated in the GEO-COAD set. Age and risk score were observed to be independent prognostic factors in patients with COAD. Genes related to bile acid metabolism in COAD were closely related to bile secretion, intestinal transport, steroid and fatty acid metabolism. Furthermore, the high-risk group was more sensitive to Oxaliplatin than the low-risk group. Finally, the three target genes screened were closely associated with immune cells. We identified a set of 12 genes (CPT2, SLCO1A2, CD36, ACOX1, CDKN2A, HADH, GABRD, LEP, TIMP1, MAT1A, SLC6A15, and PPARGC1A) associated with bile acid metabolism and developed a bile acid risk score model using LASSO regression analysis. The model demonstrated good predictive performance and was validated using an independent dataset. Our findings revealed that the bile acid risk score were independent prognostic factors in COAD patients.

Dataset Information

Analysis of the Prognostic Significance and Immune Infiltration of the Amino Acid Metabolism-Related Genes in Colon Adenocarcinoma.

Publications

Analysis of the Prognostic Significance and Immune Infiltration of the Amino Acid Metabolism-Related Genes in Colon Adenocarcinoma.

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