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. 2020 Dec 4;11:607009. doi: 10.3389/fgene.2020.607009

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Copyright © 2020 Dai, Xu, Ye and Ding.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Schematic of this study. Survival and relevant clinical information, along with IRG expression data, were acquired from an online database. The TCGA database (n = 487) was used as the training group. An IRG prediction panel was developed via the aforementioned procedures and was tested for its function via GO and KEGG analyses. The model’s discrimination was assessed and validated in GSE39582 (n = 578) and GSE17538 (n = 224). TCGA, The Cancer Genome Atlas; IRG, Immune-related gene; RSFA, random survival forest algorithm.