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Expression of Ferroptosis-Related Genes Shapes Tumor Microenvironment and Pharmacological Profile in Gastric Cancer

ABSTRACT: Background: Ferroptosis is a form of regulated cell death that occurs as a consequence of lethal lipid peroxidation. A wealth of studies has demonstrated that ferroptosis profoundly modulated numerous biological behaviors of tumor. However, its natural functions in gastric cancer (GC) remain to be explored. Methods: Firstly, a total of over 1,000 GC patients from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database were included in our study. Secondly, 32 ferroptosis-related genes were extracted from the ferrDb website. Then, unsupervised clustering was performed to classify patients into three distinct ferroptosis-related clusters. Subsequently, we systematically and comprehensively explored the biological characteristics of each cluster. Finally, we constructed a scoring system, named ferroptosis score, to quantify each cluster and also investigated the predictive therapeutic value of the ferroptosis score for chemotherapy and immunotherapy. Results: Based on the expressions of 32 ferroptosis-related genes, three distinct ferroptosis-related subtypes with various biological characteristics were determined. Integrated analysis showed that cluster 1 is a microsatellite instability (MSI)-like subtype, cluster 2 is an epithelial–mesenchymal transition (EMT)-like subtype, while cluster 3 tends to be a metabolic-like subtype. Prognostic analysis revealed that patients in cluster 2 had a worse overall survival and relapse-free survival. The distribution of the ferroptosis score was significantly different in clusters and gene clusters. The ferroptosis score could predict the biological characteristics of each cluster, the stromal activity, and progression of tumor. The low ferroptosis score group was characterized by the activation of antigen processing and presentation, DNA damage repair pathways, and metabolic pathways, while the high ferroptosis score group was characterized by stromal activation. In response to anticancer drugs, the ferroptosis score was highly negatively associated with drugs targeting MAPK signaling and PI3K/mTOR signaling, while it was positively correlated with drugs targeting the cell cycle, mitosis, and metabolism. Finally, we also proved that the ferroptosis score could serve as a reliable biomarker to predict response to immunotherapy. Conclusion: This work revealed that tumor cells and their surrounding microenvironment could be shaped by varying the activation degrees of ferroptosis. Establishing ferroptosis-related subtypes would guide in predicting the biological features of individual tumors and selecting appropriate treatment protocols for patients.

SUBMITTER: Xiao S

PROVIDER: S-EPMC8517126 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundGastric cancer (GC) is an important disease and the fifth most common malignancy worldwide. Autophagy is an important process for the turnover of intracellular substances. Autophagy-related genes (ARGs) are crucial in cancer. Accumulating evidence indicates the clinicopathological significance of the tumor microenvironment (TME) in predicting prognosis and treatment efficacy.MethodsClinical and gene expression data of GC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. A total of 22 genes with differences in expression and prognosis were screened from 232 ARGs. Three autophagy patterns were identified using an unsupervised clustering algorithm and scored using principal component analysis to predict the value of autophagy in the prognosis of GC patients. Finally, the relationship between autophagy and ferroptosis was validated in gastric cancer cells.ResultsThe expression of ARGs showed obvious heterogeneity in GC patients. Three autophagy patterns were identified and used to predict the overall survival of GC patients. These three patterns were well-matched with the immunophenotype. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses showed that the biological functions of the three autophagy patterns were different. A scoring system was then set up to quantify the autophagy model and further evaluate the response of the patients to the immunotherapy. Patients with high autophagy scores had a more severe tumor mutation burden and better prognosis. High autophagy scores were accompanied by high microsatellite instability. Patients with high autophagy scores had significantly higher PD-L1 expression and increased survival. The experimental results confirmed that the expression of ferroptosis genes was positively correlated with the expression of autophagy genes in different autophagy clusters, and inhibition of autophagy dramatically reversed the decrease in ferroptotic cell death and lipid accumulation.ConclusionsAutophagy patterns are involved in TME diversity and complexity. Autophagy score can be used as an independent prognostic biomarker in GC patients and to predict the effect of immunotherapy and ferroptosis-based therapy. This might benefit individualized treatment for GC.

Project description:BackgroundCervical cancer (CC) is a disease that affects female health; therefore, timely prevention and diagnosis of CC are crucial to decrease its mortality. Ferroptosis, an iron-dependent form of non-apoptotic cell death, is involved in tumor progression. However, the role of ferroptosis-related genes (FRGs) in the immune microenvironment of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) remains unclear.MethodsThe data sets of CESC patients, including RNA sequencing (RNA-seq) data and clinical information, were obtained from The Cancer Genome Atlas (TCGA). The ESTIMATE algorithm was used to determine the stromal score, immune score, estimate score, and tumor purity in the CESC patients' data. Additionally, FRGs were identified and used to construct a signature marker for the diagnosis and prognosis of CESC. Patients were assigned to a high- or low-risk group based on their median risk score. The tumor microenvironment (TME), immune infiltration, and functional enrichment were compared between the low- and high-risk groups. Functional analyses, including Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and single-sample Gene Set Enrichment Analysis (ssGSEA), were conducted to explore the underlying mechanisms in the development and prognosis of CESC.ResultsThe results showed that the estimate score was suitable for predicting the prognosis of CESC patients. Additionally, a prediction model involving four FRGs [phosphatidylethanolamine-binding protein 1 (PEBP1), dual oxidase 1 (DUOX1), iron-sulfur cluster assembly enzyme (ISCU), and cytochrome b (-245) beta subunit (CYBB)] was constructed. The performance of the prognostic model and significant clinical characteristics in predicting CESC prognosis was subsequently validated. Our results showed that the expression of CYBB affected immune cells. Gene functional enrichment analyses showed that these differentially expressed FRGs were mainly enriched in the immunity-related signaling pathways, which indicated that FRGs might affect the development and prognosis of CC by regulating the immune microenvironment.ConclusionsThe expression profiles of FRGs are closely related to the TME and the prognostic survival of CESC patients. The interaction between ferroptosis and immunity in the development of CC provides new insight into the molecular mechanisms of CC.

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Expression of Ferroptosis-Related Genes Shapes Tumor Microenvironment and Pharmacological Profile in Gastric Cancer

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