Dataset Information

Delineation of fatty acid metabolism in gastric cancer: Therapeutic implications.

ABSTRACT:

Background

The prognosis of gastric cancer is extremely poor. Metabolic reprogramming involving lipids has been associated with cancer occurrence and progression.

Aim

To illustrate fatty acid metabolic mechanisms in gastric cancer, detect core genes, develop a prognostic model, and provide treatment options.

Methods

Raw data from The Cancer Genome Atlas and Gene Expression Omnibus databases were collected and analyzed. Differentially expressed fatty acid metabolism genes were identified and incorporated into a risk model based on least absolute shrinkage and selection operator regression analysis. Then, patients from The Cancer Genome Atlas were assigned to high- and low-risk cohorts according to the mean value of the risk score as the threshold, which was verified in the Gene Expression Omnibus database. Relationships between chemotherapeutic sensitivity and tumor microenvironment features were assessed.

Results

An integrated evaluation was performed in this study. Fatty acid metabolism-related genes were used to construct the risk model. Patients classified into the high-risk cohort were considered to be resistant to chemotherapy based on results of the "pRRophetic" R package. Patients in the high-risk cohort were associated with type I/II interferon activation, increased inflammation level, immune cell infiltration, and tumor immune dysfunction based on the exclusion algorithm, indicating the potential benefit of immunotherapy in these patients.

Conclusion

We constructed a fatty acid-related risk score model to assess the comprehensive fatty acid features in gastric cancer and validated its vital role in prognosis, chemotherapy sensitivity, and immunotherapy.

SUBMITTER: Fu Y

PROVIDER: S-EPMC10424035 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Publications

Delineation of fatty acid metabolism in gastric cancer: Therapeutic implications.

Fu Yu Y Wang Bin B Fu Peng P Zhang Lei L Bao Yi Y Gao Zhen-Zhen ZZ

World journal of clinical cases 20230701 20

<h4>Background</h4>The prognosis of gastric cancer is extremely poor. Metabolic reprogramming involving lipids has been associated with cancer occurrence and progression.<h4>Aim</h4>To illustrate fatty acid metabolic mechanisms in gastric cancer, detect core genes, develop a prognostic model, and provide treatment options.<h4>Methods</h4>Raw data from The Cancer Genome Atlas and Gene Expression Omnibus databases were collected and analyzed. Differentially expressed fatty acid metabolism genes we ...[more]

PMID: 37583992

Similar Datasets

Project description:BackgroundWith the deepening research on fatty acid metabolism, people have achieved a preliminary understanding of it in the development and prognosis of tumors. However, few studies are still on the expression pattern and prognostic value of fatty acid metabolism-related genes in gastric cancer (GC).MethodsWe chose 93 genes relevant to fatty acid metabolism from the Gene Set Enrichment Analysis (GSEA) database. We analyzed differentially expressed genes (DEGs) in The Cancer Genome Atlas (TCGA) patients. Univariate Cox analysis and LASSO regression were used to select the genes most related to prognosis and therefore developed a prognosis model. In addition, a dataset of 76 samples from Gene Expression Omnibus (GEO) selected as a test set to aid in the development of a prognostic model. The prognostic relevance of this model was confirmed using Kaplan-Meier survival analysis, univariate/multivariate Cox analysis, and receiver operating characteristic (ROC) curve. Finally, enrichment analysis and protein-protein interaction (PPI) were used to analyze the functional differences of patients with different risk. Immune infiltration analysis based on CIBERSORT could check the infiltration degree and immune function changes of immune cell subtypes in patients with different risk groups.ResultsOverexpression of ELOVL4, ADH4, CPT1C, and ADH1B was linked to poor overall survival (OS) in GC patients, according to our findings. Furthermore, according to prognostic factors, patients with lower risk score tend to have better prognosis than patients with higher risk score. In addition, we also found that the infiltration levels of B cells, dendritic cells, auxiliary T cells, mast cells, neutrophils and tumor-infiltrating lymphocytes in patients with high-risk group were significantly increased, and the type II IFN response of immune cells, CCR and MHC class I receptor functions were significantly enhanced, suggesting that the tumor microenvironment immune activity in patients with high-risk group was active.ConclusionsFour fatty acid metabolism-related genes were discovered to be closely connected to the prognosis of individuals with GC. Through analysis and verification, we believed that this prognostic model was reliable and instructive in the prediction of the prognosis of GC.

Dataset Information

Delineation of fatty acid metabolism in gastric cancer: Therapeutic implications.

Background

Aim

Methods

Results

Conclusion

Publications

Delineation of fatty acid metabolism in gastric cancer: Therapeutic implications.

Similar Datasets

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