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Development and validation of ferroptosis-related lncRNA signature and immune-related gene signature for predicting the prognosis of cutaneous melanoma patients

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Abstract

Ferroptosis, a form of cell death caused by iron-dependent peroxidation of lipids, plays an important role in cancer. Recent studies have shown that long noncoding RNAs (lncRNAs) are involved in the regulation of ferroptosis in tumor cells and are also closely related to tumor immunity. Immune cell infiltration in the tumor microenvironment affects the prognosis and clinical outcome of immunotherapy in melanoma patients, and immune cell classification may be able to accurately predict the prognosis of melanoma patients. However, the prognostic value of ferroptosis-related lncRNAs (FRLs) in melanoma has not been thoroughly explored, and it is difficult to define the immune characteristics of melanoma. We used The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) database, and the FerrDb database to identify FRLs. FRLs with prognostic value were evaluated in an experimental cohort utilizing univariate, LASSO (least absolute shrinkage and selection operator) and multivariate Cox regression, followed by in vitro assays evaluating the expression levels and the biological functions of three candidate FRLs. Kaplan–Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to assess the validity of the risk model, and the drug sensitivity of FRLs was examined by drug sensitivity analysis. The differentially expressed genes between the high- and low-risk groups in the risk model were enriched in the immune pathway, and we further found immune gene signatures (IRGs) that could predict the prognosis of melanoma patients through a series of methods including single-sample Gene Set Enrichment Analysis (ssGSEA). Finally, two GEO cohorts were used to validate the predictive accuracy and reliability of these two signature models. Our findings suggest that FRLs and IRGs have the potential to predict the prognosis of patients with cutaneous melanoma.

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Data availability

The data that support the findings of this study are available from the corresponding author upon request.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (82073019 and 82073018), Hunan Provincial Natural Science Foundation of China (under grant 2022JJ30189), Teaching Reform Research Project of Universities in HunanProvince (under grant HNJG-2021-1120), and Shenzhen Science and Technology Innovation Commission, China (Natural Science Foundation of Shenzhen, JCYJ20210324113001005 and JCYJ20210324114212035).

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Authors and Affiliations

  1. Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China

    Kaifen Xiong

  2. School of Computer Science, Hunan First Normal University, Changsha, 410205, China

    Zheng Wang & Li Peng

  3. School of Mathematics and Statistics, Central South University, Changsha, 410083, China

    Alphonse Houssou Hounye

  4. Department of Dermatology, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University, The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518020, Guangdong, China

    Jianglin Zhang

  5. Candidate Branch of National Clinical Research Center for Skin Diseases, Shenzhen, 518020, Guangdong, China

    Jianglin Zhang

  6. Department of Geriatrics, Shenzhen People’s Hospital(The Second Clinical Medical College, Jinan UniversityThe First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518020, Guangdong, China

    Jianglin Zhang

  7. Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, 410008, China

    Min Qi

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Conception and design: Kaifen Xiong; Financial support: Min Qi, Zheng Wang and Jianglin Zhang; Administrative support: Li Peng, Min Qi, and Jianglin Zhang; Collection and assembly of data: Kaifen Xiong Alphonse Houssou Hounye, and Li Peng; Data analysis and interpretation: Kaifen Xiong, Zheng Wang, and Alphonse Houssou Hounye; Manuscript writing: All authors; Final approval of manuscript: All authors; accountable for all aspects of the work: All authors.

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Xiong, K., Wang, Z., Hounye, A.H. et al. Development and validation of ferroptosis-related lncRNA signature and immune-related gene signature for predicting the prognosis of cutaneous melanoma patients. Apoptosis 28, 840–859 (2023). https://doi.org/10.1007/s10495-023-01831-7

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