A Ferroptosis-Related Gene Signature for Predicting Survival and Immunotherapy Effect in Renal Cancer

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Abstract

Background. Most recently, no efficient prognostic indictor is present for kidney cancer. Thus, we aimed to build and validate a new prognostic gene signature for renal cancer patients using the Cancer Genomic Atlas (TCGA). Methods. A "time-dependent receiver operating characteristic (tROC)"curve was generated, and a log-rank test was performed to assess the performance of the biomarker in training and validation. A "ferroptosis-related gene signature"was developed. In different training and validations sets, tROC and log-rank test were used to validate the biomarker's performance. Results. In the training set with a P value less than 0.01 and the validation set, the "gene signature"was significantly correlated with survival. Eventually, it was found that the ferroptosis-related gene signature was directly correlated with immune score and the score of tumor mutation, suggesting its role in predicting response to immunotherapy. Conclusion. We developed and validated a "ferroptosis-related gene signature"that can be sued for patients with kidney cancer. It can also assist in facilitating the plan for treatment and risk stratification.

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Tong, L., Yin, Z. F., Peng, L., Li, Y. T., Liu, R., Cai, J. R., & Kang, L. (2022). A Ferroptosis-Related Gene Signature for Predicting Survival and Immunotherapy Effect in Renal Cancer. Computational and Mathematical Methods in Medicine, 2022. https://doi.org/10.1155/2022/3317624

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