Dataset Information

The Evaluation of Prognostic Value and Immune Characteristics of Ferroptosis-Related Genes in Lung Squamous Cell Carcinoma.

ABSTRACT: Background The purpose of our study was to construct a prognostic model based on ferroptosis-related gene signature to improve the prognosis prediction of lung squamous carcinoma (LUSC). Methods The mRNA expression profiles and clinical data of LUSC patients were downloaded. LUSC-related essential differentially expressed genes were integrated for further analysis. Prognostic gene signatures were identified through random forest regression and univariate Cox regression analyses for constructing a prognostic model. Finally, in a preliminary experiment, we used the reverse transcription-quantitative polymerase chain reaction assay to verify the relationship between the expression of three prognostic gene features and ferroptosis. Results Fifty-six ferroptosis-related essential genes were identified by using integrated analysis. Among these, three prognostic gene signatures (HELLS, POLR2H, and POLE2) were identified, which were positively affected by LUSC prognosis but negatively affected by immune cell infiltration. Significant overexpression of immune checkpoint genes occurred in the high-risk group. In preliminary experiments, we confirmed that the occurrence of ferroptosis can reduce three prognostic gene signature expression. Conclusions The three ferroptosis-related genes could predict the LUSC prognostic risk of antitumor immunity.

SUBMITTER: Su J

PROVIDER: S-EPMC10615648 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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The Evaluation of Prognostic Value and Immune Characteristics of Ferroptosis-Related Genes in Lung Squamous Cell Carcinoma.

Su Jialin J Tan Shuhua S Gong Houwu H Luo Yongzhong Y Cheng Tianli T Yang Hua H Wen Xiaoping X Jiang Zhou Z Li Yuning Y Zhang Lemeng L

Global medical genetics 20231030 4

<b>Background</b> The purpose of our study was to construct a prognostic model based on ferroptosis-related gene signature to improve the prognosis prediction of lung squamous carcinoma (LUSC). <b>Methods</b> The mRNA expression profiles and clinical data of LUSC patients were downloaded. LUSC-related essential differentially expressed genes were integrated for further analysis. Prognostic gene signatures were identified through random forest regression and univariate Cox regression analyses f ...[more]

PMID: 37915460

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Project description:BackgroundIn recent years, the clinical application of targeted therapies and immunotherapy has significantly improved survival outcomes for patients with lung adenocarcinomas(LUAD). However, due to fewer mutations, lung squamous cell carcinomas(LUSC) shows limited efficacy with targeted and immunotherapy, resulting in a notably lower 5-year survival rate compared to lung adenocarcinoma. The m7G modification plays an important role in tumorigenesis, progression, immune evasion, and therapeutic response. This study aims to develop a novel scoring system based on m7G modification and immune status to clinically predict the prognosis of patients with LUSC and to provide new therapeutic targets.MethodsIn this study, we utilized RNA-seq data from the TCGA-LUSC database as the training set and GSE50081 from the GEO database as the validation set. Immunotherapy data were obtained from the IMMPORT database, and m7G data from previous research. Using bioinformatics, we developed a prognostic model for LUSC based on m7G pathway-related immune gene characteristics. We analyzed the correlation between the prognostic model and clinical pathological features of LUSC, as well as the model's independent prognostic capability. Subsequently, patients were divided into high-risk and low-risk groups, and we examined the differences in enriched pathways, immune cell infiltration correlations, and drug sensitivity between the two groups.ResultsThe m7G immune-related genes FGA, CSF3R, and ORM1 increase the survival risk in patients with lung squamous cell carcinoma, whereas NTS exerts a protective effect. The prognostic risk model for lung squamous cell carcinoma (LUSC) based on m7G immune-related gene expression demonstrates that the overall survival of the high-risk group is significantly poorer than that of the low-risk group.ConclusionThe risk model developed based on m7G immune-related genes can help predict the clinical prognosis of LUSC patients and guide treatment decisions.

Project description:BackgroundTo investigate the prognostic value of ferroptosis-related long noncoding RNAs (lncRNAs) in oral squamous cell carcinoma (OSCC) and to construct a prognostic risk and immune activity model.MethodsWe obtained clinical and RNA-seq information on OSCC patient data in The Cancer Genome Atlas (TCGA) Genome Data Sharing (GDC) portal. Through a combination of a differential analysis, Pearson correlation analysis and Cox regression analysis, ferroptosis-related lncRNAs were identified, and a prognostic model was established based on these ferroptosis-related lncRNAs. The accuracy of the model was evaluated via analyses based on survival curves, receiver operating characteristic (ROC) curves, and clinical decision curve analysis (DCA). Univariate Cox and multivariate Cox regression analyses were performed to evaluate independent prognostic factors. Then, the infiltration and functional enrichment of immune cells in high- and low-risk groups were compared. Finally, certain small-molecule drugs that potentially target OSCC were predicted via use of the L1000FWD database.ResultsThe prognostic model included 8 ferroptosis-related lncRNAs (FIRRE, LINC01305, AC099850.3, AL512274.1, AC090246.1, MIAT, AC079921.2 and LINC00524). The area under the ROC curve (AUC) was 0.726. The DCA revealed that the risk score based on the prognostic model was a better prognostic indicator than other clinical indicators. The multivariate Cox regression analysis showed that the risk score was an independent prognostic factor for OSCC. There were differences in immune cell infiltration, immune functions, m6A-related gene expression levels, and signal pathway enrichment between the high- and low-risk groups. Subsequently, several small-molecule drugs were predicted for use against differentially expressed ferroptosis-related genes in OSCC.ConclusionsWe constructed a new prognostic model of OSCC based on ferroptosis-related lncRNAs. The model is valuable for prognostic prediction and immune evaluation, laying a foundation for the study of ferroptosis-related lncRNAs in OSCC.

Project description:BackgroundLung squamous cell carcinoma (LUSC), one of the main pathological types of lung cancer, has led to consequential socioeconomic burden. Ferroptosis is an iron-dependent form of cell death process with potentials for therapeutic target in various kinds of tumors. However, whether ferroptosis-related genes (FRGs) are associated with the prognosis of LUSC patients is still unclear. The aim of this study was to establish a FRGs-based signature which could stratify patients with LUSC.MethodsThe RNA sequencing profiles and corresponding clinical data of LUSC patients were retrieved from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) dataset. A FRG-based signature was developed using the TCGA-LUSC cohort and validated in the GEO cohort. Gene set enrichment analysis (GSEA) and analysis of immune cell characteristics were conducted to assess the relationship between FRGs and biological function or immune status. A nomogram based on selected clinical factors and the risk scores which were generated from the FRG-based signature was developed using the TCGA cohort and validated in the GEO cohort.ResultsA set of 16 FRGs, significantly associated with overall survival (OS) in the TCGA cohort, was identified and could classify LUSC patients into two risk groups. Kaplan-Meier analysis illustrated that the survival rate of the high-risk group was significantly lower than the low-risk group. Assessment and external validation of the signature showed that the survival predictive performance of this signature was adequate. Additionally, multiple pathways and functions were enriched through GSEA and the analysis of immune cell characteristics showed significantly different abundances of immune cells among the two risk groups. Finally, a nomogram integrating the FRG-based signature and selected clinical factors was also developed and assessed in both the TCGA and GEO cohort.ConclusionThis study indicated the association between the FRGs and prognosis of patients with LUSC. Targeting ferroptosis may serve as a novel potential therapeutic alternative for LUSC.

Dataset Information

The Evaluation of Prognostic Value and Immune Characteristics of Ferroptosis-Related Genes in Lung Squamous Cell Carcinoma.

Publications

The Evaluation of Prognostic Value and Immune Characteristics of Ferroptosis-Related Genes in Lung Squamous Cell Carcinoma.

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