Identification of Ferroptosis-Related Biomarkers for Prognosis and Immunotherapy in Patients With Glioma

Shi, Junfeng; Lai, Donglin; Zuo, Xiaojia; Chen, Bing; Zheng, Yanjun; Lu, Changlian; Gu, Xuefeng

doi:10.3389/fcell.2022.817643

Cited by 11 publications

(12 citation statements)

References 77 publications

(84 reference statements)

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“…The high risk scores were positively related to immune, stromal, and ESTIMAT scores, with Spearman correlation coefficients of 0.739, 0.717, and 0.749, respectively (Figure 5C). In addition, 14 immune checkpoint genes (PD1, PDL1, CTLA4, LAG3, TIM3, CD48, CCL2, CD276, CD4, IL1A, IL6, LAP3, PDCD1LG2, and TGFB1) had significantly higher expression in the high-risk group than in the low-risk group (Figure 5D), which is consistent with other findings (21,22). Our results revealed differences in the immune microenvironment between low-and high-risk patients.…”

Section: Immune Infiltration and Immune Checkpoint Genessupporting

confidence: 91%

A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma

Yuan

Jin²,

Chen³

et al. 2022

Front. Immunol.

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BackgroundGlioma is a highly aggressive brain cancer with a poor prognosis. Necroptosis is a form of programmed cell death occurring during tumor development and in immune microenvironments. The prognostic value of necroptosis in glioma is unclear. This study aimed to develop a prognostic glioma model based on necroptosis.MethodsA necroptosis-related risk model was constructed by Cox regression analysis based on The Cancer Genome Atlas (TCGA) training set, validated in two Chinese Glioma Genome Atlas (CGGA) validation sets. We explored the differences in immune infiltration and immune checkpoint genes between low and high risk groups and constructed a nomogram. Moreover, we compiled a third validation cohort including 43 glioma patients. The expression of necroptosis-related genes was verified in matched tissues using immunochemical staining in the third cohort, and we analyzed their relationship to clinicopathological features.ResultsThree necroptosis-related differentially expressed genes (EZH2, LEF1, and CASP1) were selected to construct the prognostic model. Glioma patients with a high risk score in the TCGA and CGGA cohorts had significantly shorter overall survival. The necroptosis-related risk model and nomogram exhibited good predictive performance in the TCGA training set and the CGGA validation sets. Furthermore, patients in the high risk group had higher immune infiltration status and higher expression of immune checkpoint genes, which was positively correlated with poorer outcomes. In the third validation cohort, the expression levels of the three proteins encoded by EZH2, LEF1, and CASP1 in glioma tissues were significantly higher than those from paracancerous tissues. They were also closely associated with disease severity and prognosis.ConclusionsOur necroptosis-related risk model can be used to predict the prognosis of glioma patients and improve prognostic accuracy, which may provide potential therapeutic targets and a theoretical basis for treatment.

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Section: Immune Infiltration and Immune Checkpoint Genessupporting

confidence: 91%

A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma

Yuan

Jin²,

Chen³

et al. 2022

Front. Immunol.

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“…Finally, we established a risk assessment model based on 3 FRLs. Compared to ROC curves of published literature ( He et al2021 ; Shi et al 2022 ), our signature has more predictive ability of prognosis and contains fewer lncRNAs. The lncRNA prognosis assessment kits that have been commercialized at present are composed of only 3-5 lncRNAs (Patent No.…”

Section: Discussionmentioning

confidence: 86%

“…LINC00336 as a competing endogenous RNA inhibits ferroptosis in lung cancer ( Wang et al, 2019 ; Mao et al, 2019), and the lncRNA GABPB1-AS1 regulates erastin-induced ferroptosis through GABPB1 in HepG2 hepatocellular carcinoma ( Qi et al, 2019 ). Furthermore, there are 3 different ferroptosis-related lncRNAs(FRL) signatures were observed to be associated with glioma prognosis, containing 15 ferroptosis-related lncRNAs, 14 ferroptosis-related lncRNAs and 9 ferroptosis-related lncRNAs, respectively ( He et al, 2021 ; Zheng et al, 2021 ; Shi et al, 2022 ). In machine learning models, a consistent cutoff value for different datasets enhances generalizability, and thereby increasing applicability in real world.…”

Section: Introductionmentioning

confidence: 99%

Identification and validation of ferroptosis-related lncRNA signatures as a novel prognostic model for glioma

Huang

Zhang²,

Gong³

et al. 2022

Front. Genet.

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Background: Ferroptosis is a newly discovered form of regulated cell death with distinct properties and recognizing functions involved in physical conditions or various diseases, including cancers. However, the relationship between gliomas and ferroptosis-related lncRNAs (FRLs) remains unclear.Methods: We collected a total of 1850 samples from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEX) databases, including 698 tumor and 1,152 normal samples. A list of ferroptosis-related genes was downloaded from the Ferrdb website. Differentially expressed FRLs (DEFRLS) were analyzed using the “limma” package in R software. Subsequently, prognosis-related FRLs were obtained by univariate Cox analysis. Finally, a prognostic model based on the 3 FRLs was constructed using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm. The prognostic power of the model was assessed using receiver operating characteristic (ROC) curve analysis and Kaplan-Meier (K-M) survival curve analysis. In addition, we further explored the relationship of the immune landscape and somatic mutations to prognostic model characteristics. Finally, we validated the function of LINC01426 in vitro.Results: We successfully constructed a 3-FRLs signature and classified glioma patients into high-risk and low-risk groups based on the risk score calculated from this signature. Compared with traditional clinicopathological features [age, sex, grade, isocitrate dehydrogenase (IDH) status], the prognostic accuracy of this model is more stable and stronger. Additionally, the model had stable predictive power for overall survival over a 5-year period. In addition, we found significant differences between the two groups in cellular immunity, the numbers of many immune cells, including NK cells, CD4+, CD8+ T-cells, and macrophages, and the expression of many immune-related genes. Finally, the two groups were also significantly different at the level of somatic mutations, especially in glioma prognosis-related genes such as IDH1 and ATRX, with lower mutation rates in the high-risk group leading to poorer prognosis. Finally, we found that the ferroptosis process of glioma cells was inhibited after knocking down the expression of LINC01426.Conclusion: The proposed 3-FRL signature is a promising biomarker for predicting prognostic features in glioma patients.

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“…Although bioinformatic analyses have identified a significant negative correlation between tumor ferroptosis and M2 infiltration [39,[47][48][49][50][51][52], there are few studies exploring the direct effects of M2 macrophages on tumor ferroptosis. Instead, M2 macrophages are more likely to play an indirect role in regulating ferroptosis by disrupting the ferroptosis-promoting function of CTLs [53].…”

Section: Dual Effects Of Macrophage On Ferroptosismentioning

confidence: 99%

Targeting the Macrophage-Ferroptosis Crosstalk: A Novel Insight into Tumor Immunotherapy

Shi¹,

Xu²,

Hu³

et al. 2022

Front. Biosci. (Landmark Ed)

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Ferroptosis is an emerging form of non-apoptotic, regulated cell death that is mechanistically dependent on aberrant iron accumulation and excessive lipid peroxidation. Further evidence indicates that ferroptosis plays a crucial role in the efficacy of tumor immunotherapy. Ferroptosis is often constrained by tumor-associated macrophages (TAMs), and this poses a challenge to clinicians aiming to exploit the potency of immunotherapy to treat various forms of cancer. Current advances revealed a dual character to TAMs in regulating tumor ferroptosis. Specifically, some signaling molecules released from cells undergoing ferroptosis can exert effects on TAM polarization. In this review, we summarize the currently characterized mechanisms of macrophage-ferroptosis crosstalk, discuss how macrophageferroptosis crosstalk affects the outcome of tumor immunotherapy, and provide an overview of current advances that seek to leverage this crosstalk to improve cancer immunotherapy efficacy. Despite the fact that further efforts are still required to achieve a more comprehensive understanding of the mechanisms that control this signaling, targeting macrophage-ferroptosis crosstalk has clear potential for reversing immunotherapeutic resistance and may shed light on new therapeutic strategies to overcome some advanced and metastatic malignancies.

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Identification of Ferroptosis-Related Biomarkers for Prognosis and Immunotherapy in Patients With Glioma

Cited by 11 publications

References 77 publications

A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma

A novel model based on necroptosis-related genes for predicting immune status and prognosis in glioma

Identification and validation of ferroptosis-related lncRNA signatures as a novel prognostic model for glioma

Targeting the Macrophage-Ferroptosis Crosstalk: A Novel Insight into Tumor Immunotherapy

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