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Immunogenic cell death related risk model to delineate ferroptosis pathway and predict immunotherapy response of patients with GBM.

ABSTRACT: Immunogenic cell death (ICD) is a type of cell death that leads to the regulation and activation of the immune response, which is marked by the exposure and delivery of damage-associated molecular patterns (DAMPs) in the tumor microenvironment. Accumulating evidence has revealed the significance of ICD-related genes in tumor progression and therapeutic response. In this study, we obtained two ICD-related clusters for glioblastoma (GBM) by applying consensus clustering, and further constructed a risk signature on account of the prognostic ICD genes. Based on the risk signature, we found that higher risk scores were associated with worse patient prognosis. Besides, the results illustrated that ferroptosis regulators/markers were highly enriched the high-risk group, and ferroptosis were correlated with cytokine signaling pathway and other immune-related pathways. We also discovered that high-risk scores were correlated to specific immune infiltration patterns and good response to immune checkpoint blockade (ICB) treatment. In conclusion, our study highlights the significance of ICD-related genes as prognostic biomarkers and immune response indicators in GBM. And the risk signature integrating prognostic genes possessed significant potential value to predict the prognosis of patients and the efficacy of ICB treatment.

SUBMITTER: Feng S

PROVIDER: S-EPMC9554879 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Immunogenic cell death related risk model to delineate ferroptosis pathway and predict immunotherapy response of patients with GBM.

Feng Songshan S Liang Xisong X Li Jing J Wang Zeyu Z Zhang Hao H Dai Ziyu Z Luo Peng P Liu Zaoqu Z Zhang Jian J Xiao Xiaoxiong X Cheng Quan Q

Frontiers in immunology 20220926

Immunogenic cell death (ICD) is a type of cell death that leads to the regulation and activation of the immune response, which is marked by the exposure and delivery of damage-associated molecular patterns (DAMPs) in the tumor microenvironment. Accumulating evidence has revealed the significance of ICD-related genes in tumor progression and therapeutic response. In this study, we obtained two ICD-related clusters for glioblastoma (GBM) by applying consensus clustering, and further constructed a ...[more]

PMID: 36248827

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Project description:BackgroundImmunogenic cell death (ICD) is related to cancer prognosis, which has a synergic effect in combination with chemotherapy or immunotherapy. Yet, the relationship between ICD and osteosarcoma remained unclear.Materials and methodsThree osteosarcoma datasets including therapeutically applicable research to generate effective treatments (TARGET), GSE126209 and GSE21257 datasets were included. A protein-protein interaction network was constructed based on ICD-related genes. We performed unsupervised consensus clustering to classify molecular subtypes (clusters). Survival analysis, Estimation of stromal and immune cells in malignant tumour tissues using expression data (ESTIMATE), Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), and differential analysis were employed to characterize the molecular differences between different clusters. Univariate Cox regression analysis was conducted to confirm prognostic genes. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to demonstrate the aberrant expression of ICD-correlated signature genes in osteosarcoma. A series of cellular experiments, including cell counting kit-8 (CCK-8), transwell, and flow cytometry, were used to demonstrate the regulatory role of key genes in the ICD model on the malignant phenotype of osteosarcoma.ResultsThree clusters (cluster1, 2, 3) were constructed and they showed distinct overall survival and immune infiltration. ICD-related genes were highly expressed in cluster1. Moreover, Cluster1 had the best prognosis, high immune score and high expression of human leukocyte antigen (HLA)-related genes. TLR4, LY96, IFNGR1, CD4, and CASP1 were identified as prognostic genes for establishing an ICD-related risk signature. According to the risk signature, two risk groups (high and low risks) showing differential prognosis and response to immunotherapy. The low risks group had a better prognosis but was not sensitive to immunotherapy. Molecular assays verified that prognostic genes were abnormally under-expressed in osteosarcoma. Cellular assays demonstrated that LY96, the most significantly down-regulated gene in osteosarcoma, inhibited the migration, invasion, and proliferation phenotypes of osteosarcoma cells and prolonged the cell cycle. Analysis of oxidative stress related pathway enrichment in tumor microenvironment was conducted by single-sample gene set enrichment analysis (ssGSEA).ConclusionsThis study demonstrated the prognostic significance of ICD-correlated genes in osteosarcoma patients. The five-gene risk signature facilitate prognostic evaluation and prediction of osteosarcoma patients' response to immunotherapy. The risk signature also offered a possibility for the exploit of novel ICD-related treatment.

Project description:IntroductionNumerous studies have demonstrated acute myeloid leukemia (AML) is one of the malignancies with high mortality worldwide. Immunogenic cell death (ICD) is a form of cell death that is specialised in that it triggers the body's immune response, particularly the adaptive immune response. Recent evidence has confirmed that pseudogenes are implicated in multiple human tumorigenesis and progression although lacking the function of coding protein. However, the roles of ICD-associated genes in AML remain largely unascertained.MethodsTCGA-AML and GSE71014 cohorts were picked out and we combined them into a merged dataset by removing the batch effect using the sva package in the R project. A consensus clustering analysis of the ICD genes in AML was performed to define subgroups. Based on the expression of 15 prognostic-related pseudogenes, we developed a prognostic model and categorized AML samples into low and high-risk groups.ResultsAML was differentiated into two subgroups (C1 and C2 clusters). Most ICD-related genes were significantly up-regulated in the C2 cluster. The single sample gene set enrichment analysis (ssGSEA) revealed that the immune cell infiltration and immune checkpoint gene expression of the C2 cluster was strongly high, suggesting that the C2 population responded well to immune checkpoint blockade (ICB) therapy and had better survival. The C1 group was sensitive to chemotherapy, including Cytarabine, Midostaurin, and Doxorubicin. On the other hand, 15 ICD-related pseudogenes were identified to be associated with AML prognosis. The receiver operator curve (ROC) analysis and nomogram manifested that our prognostic model had high accuracy in predicting survival. However, the high-risk group was sensitive to ICB therapy and chemotherapy such as Methotrexate, Cytarabine, and Axitinib while the low-risk group benefited from 5-Fluorouracil, Talazoparib, and Navitoclax therapy.DiscussionIn summary, we defined two subgroups relying on 33 ICD-related genes and this classification exerted a decisive role in assessing immunotherapy and chemotherapy benefit. Significantly, a prognostic signature identified by critical ICD-related pseudogene was created. The pseudogene prognostic signature had a powerful performance in predicting prognosis and therapeutic efficacy, including immunotherapy and chemotherapy to AML. Our research points out novel implications of ICD in cancer prognosis and treatment approach choice.

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Immunogenic cell death related risk model to delineate ferroptosis pathway and predict immunotherapy response of patients with GBM.

Publications

Immunogenic cell death related risk model to delineate ferroptosis pathway and predict immunotherapy response of patients with GBM.

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