4.6 Article

Identification and Validation of a Ferroptosis-Related Long Non-coding RNA Signature for Predicting the Outcome of Lung Adenocarcinoma

Journal

FRONTIERS IN GENETICS
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2021.690509

Keywords

ferroptosis; lung adenocarcinoma; long non-coding RNA signature; prognosis; The Cancer Genome Atlas

Funding

  1. National Natural Science Foundation of China [82072355]

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By studying ferroptosis-related long non-coding RNAs, we established a novel signature that can accurately predict the outcome of LUAD and is associated with the immune response.
Background: Ferroptosis is a recently recognized type of programmed cell death that is involved in the biological processes of various cancers. However, the mechanism of ferroptosis in lung adenocarcinoma (LUAD) remains unclear. This study aimed to determine the role of ferroptosis-associated long non-coding RNAs (lncRNAs) in LUAD and to establish a prognostic model. Methods: We downloaded ferroptosis-related genes from the FerrDb database and RNA sequencing data and clinicopathological characteristics from The Cancer Genome Atlas. We randomly divided the data into training and validation sets. Ferroptosis-associated lncRNA signatures with the lowest Akaike information criteria were determined using COX regression analysis and the least absolute shrinkage and selection operator. The risk scores of ferroptosis-related lncRNAs were calculated, and patients with LUAD were assigned to high- and low-risk groups based on the median risk score. The prognostic value of the risk scores was evaluated using Kaplan-Meier curves, Cox regression analyses, and nomograms. We then explored relationships between ferroptosis-related lncRNAs and the immune response using gene set enrichment analysis (GSEA). Results: Ten ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan-Meier and Cox regression analyses confirmed that the risk scores were independent predictors of LUAD outcome in the training and validation sets (all P < 0.05). The area under the curve confirmed that the signatures could determine the prognosis of LUAD. The predictive accuracy of the established nomogram model was verified using the concordance index and calibration curve. The GSEA showed that the 10 ferroptosis-related lncRNAs might be associated with tumor immune response. Conclusion: We established a novel signature involving 10 ferroptosis-related lncRNAs (LINC01843, MIR193BHG, AC091185.1, ACO27031.2, AL021707.2, AL031667.3, AL606834.1, ACO26355.1, AC124045.1, and ACO25048.4) that can accurately predict the outcome of LUAD and are associated with the immune response. This will provide new insights into the development of new therapies for LUAD.

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