Identification of a ferroptosis-related gene signature (FRGS) for predicting clinical outcome in lung adenocarcinoma

Wang, Sheng; Wu, Chunlei; Mao, Dehua; Hu, Quanteng

doi:10.7717/peerj.11233

Cited by 15 publications

(13 citation statements)

References 35 publications

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“…A previous study showed that repression of aldehyde dehydrogenase 2 family (ALDH2) promotes lung tumor progression through accumulated acetaldehyde and DNA damage (Li et al, 2019). CYBB, a gene related to ETC and ferroptosis, associated signature could predict the 1-, 3-, and 5-year survival rates of LUAD patients (Wang et al, 2021). Also, mutation of the CYBB gene selectively affects macrophages and is associated with immune changes (Bustamante et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

FDX1 can Impact the Prognosis and Mediate the Metabolism of Lung Adenocarcinoma

et al. 2021

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Background: Lung cancer has emerged as one of the most common cancers in recent years. The mitochondrial electron transport chain (ETC) is closely connected with metabolic pathways and inflammatory response. However, the influence of ETC-associated genes on the tumor immune response and the pathogenesis of lung cancer is not clear and needs further exploration.Methods: The RNA-sequencing transcriptome and clinical characteristic data of LUAD were downloaded from the Cancer Genome Atlas (TCGA) database. The LASSO algorithm was used to build the risk signature, and the prediction model was evaluated by the survival analysis and receiver operating characteristic curve. We explored the function of FDX1 through flow cytometry, molecular biological methods, and liquid chromatography–tandem mass spectrometry/mass spectrometry (LC–MS/MS).Results: 12 genes (FDX1, FDX2, LOXL2, ASPH, GLRX2, ALDH2, CYCS, AKR1A1, MAOB, RDH16, CYBB, and CYB5A) were selected to build the risk signature, and the risk score was calculated with the coefficients from the LASSO algorithm. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves of the dataset were 0.7, 0.674, and 0.692, respectively. Univariate Cox analysis and multivariate Cox regression analysis indicated that the risk signature is an independent risk factor for LUAD patients. Among these genes, we focused on the FDX1 gene, and we found that knockdown of FDX1 neither inhibited tumor cell growth nor did it induce apoptosis or abnormal cell cycle distribution. But FDX1 could promote the ATP production. Furthermore, our study showed that FDX1 was closely related to the glucose metabolism, fatty acid oxidation, and amino acid metabolism.Conclusion: Collectively, this study provides new clues about carcinogenesis induced by ETC-associated genes in LUAD and paves the way for finding potential targets of LUAD.

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Section: Discussionmentioning

confidence: 99%

FDX1 can Impact the Prognosis and Mediate the Metabolism of Lung Adenocarcinoma

et al. 2021

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“…FANCD2, a nuclear protein that responds to DNA damage repair, negatively regulated ferroptosis of bone marrow injury in cancer treatment and could be a potential target of anticancer therapies ( Song et al, 2016 ). In addition, a 10 ferroptosis-related genes signature and a ferroptosis-related gene signature with five genes were constructed to predict the prognosis of patients with LUAD ( Wang S. et al, 2021 ; Zhu et al, 2021 ). In general, ferroptosis-related genes play important roles in the progression of LUAD.…”

Section: Discussionmentioning

confidence: 99%

Construction of a Ferroptosis-Related Long Non-coding RNA Prognostic Signature and Competing Endogenous RNA Network in Lung Adenocarcinoma

Fei

Wang

et al. 2021

Front. Cell Dev. Biol.

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Ferroptosis-related genes play an important role in the progression of lung adenocarcinoma (LUAD). However, the potential function of ferroptosis-related lncRNAs in LUAD has not been fully elucidated. Thus, to explore the potential role of ferroptosis-related lncRNAs in LUAD, the transcriptome RNA-seq data and corresponding clinical data of LUAD were downloaded from the TCGA dataset. Pearson correlation was used to mine ferroptosis-related lncRNAs. Differential expression and univariate Cox analysis were performed to screen prognosis related lncRNAs. A ferroptosis-related lncRNA prognostic signature (FLPS), which included six ferroptosis-related lncRNAs, was constructed by the least absolute shrinkage and selection operator (LASSO) Cox regression. Patients were divided into a high risk-score group and low risk-score group by the median risk score. Receiver operating characteristic (ROC) curves, principal component analysis (PCA), and univariate and multivariate Cox regression were performed to confirm the validity of FLPS. Enrichment analysis showed that the biological processes, pathways and markers associated with malignant tumors were more common in high-risk subgroups. There were significant differences in immune microenvironment and immune cells between high- and low-risk groups. Then, a nomogram was constructed. We further investigated the relationship between six ferroptosis-related lncRNAs and tumor microenvironment and tumor stemness. A competing endogenous RNA (ceRNA) network was established based on the six ferroptosis-related lncRNAs. Finally, we detected the expression levels of ferroptosis-related lncRNAs in clinical samples through quantitative real-time polymerase chain reaction assay (qRT-PCR). In conclusion, we identified the prognostic ferroptosis-related lncRNAs in LUAD and constructed a prognostic signature which provided a new strategy for the evaluation and prediction of prognosis in LUAD.

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“…It is essential for regulating iron and ROS homeostasis in cells and plays a key role in promoting cancer cell proliferation and supporting tumor growth and metastasis [38]. Additionally, CISD1 is overexpressed in both lung adenocarcinoma and breast cancer [39,40].…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Novel 3-Gene Prognostic Model for Pancreatic Adenocarcinoma Based on Ferroptosis-Related Genes

Yang

Wei

et al. 2021

Preprint

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Background: Molecular markers play an important role in predicting clinical outcomes in pancreatic adenocarcinoma (PAAD) patients. Analysis of the ferroptosis-related genes may provide novel potential targets for the prognosis and treatment of PAAD. Methods: RNA-sequence data of PAAD was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) public databases. The PAAD samples were clustered by a non-negative matrix factorization (NMF) algorithm. The R software package clusterProfiler was used for functional enrichment analysis. By LASSO regression, we established a multi-gene prognostic model, and the model was validated by qPCR and immunohistochemistry and T3M4 cell line. Results: Three molecular subtypes were identified, and a 3-gene signature model (ALOX5, ALOX12, and CISD1) was constructed. The prognostic model showed good independent prognostic ability in PAAD. In the GSE62452 external validation set, the molecular model also showed good risk prediction. The predictive efficiency of the 3-gene signature-based nomogram was significantly better than that of traditional clinical features. Finally, qPCR and immunohistochemical staining and cell function results suggested that ALOX5 may be an oncogene and ALOX12 and CISD1 may be tumor suppressor genes. Conclusions: We present a novel prognostic molecular model for PAAD based on ferroptosis-related genes, which serves as a potentially effective tool for prognostic differentiation in pancreatic cancer patients.

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Identification of a ferroptosis-related gene signature (FRGS) for predicting clinical outcome in lung adenocarcinoma

Cited by 15 publications

References 35 publications

FDX1 can Impact the Prognosis and Mediate the Metabolism of Lung Adenocarcinoma

FDX1 can Impact the Prognosis and Mediate the Metabolism of Lung Adenocarcinoma

Construction of a Ferroptosis-Related Long Non-coding RNA Prognostic Signature and Competing Endogenous RNA Network in Lung Adenocarcinoma

Development and Validation of a Novel 3-Gene Prognostic Model for Pancreatic Adenocarcinoma Based on Ferroptosis-Related Genes

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