AUTHOR=Zhou Jian-Guo , Yang Jie , Jin Su-Han , Xiao Siyu , Shi Lei , Zhang Ting-You , Ma Hu , Gaipl Udo S. 

TITLE=Development and Validation of a Gene Signature for Prediction of Relapse in Stage I Testicular Germ Cell Tumors

JOURNAL=Frontiers in Oncology

VOLUME=10

YEAR=2020

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2020.01147

DOI=10.3389/fonc.2020.01147

ISSN=2234-943X

ABSTRACT=<p><bold>Background:</bold> Testicular germ cell tumors (TGCTs) are commonly diagnosed tumors in young men. However, a satisfactory approach to predict relapse of stage I TGCTs is still lacking. Therefore, this study aimed to develop a robust risk score model for stage I TGCTs.</p><p><bold>Method:</bold> RNA-sequence data of stage I TGCTs and normal testis samples were downloaded and analyzed to identify different expression genes. Gene-based prognostic model was constructed in The Cancer Genome Atlas (TCGA) using least absolute shrinkage and selection operator (LASSO) regression analysis and validated in GSE99420 dataset. Potential biological functions of the genes in prognostic model were determined via Gene Set Enrichment Analysis (GSEA) between high-risk and low-risk patients.</p><p><bold>Results:</bold> A total of 9,391 differentially expressed genes and 84 prognosis-related genes were identified. An eight-gene-based risk score model was constructed to divide patients into high or low risk of relapse. The low-risk patients had a significantly better relapse-free survival (RFS) than high-risk patients in both training and validation cohorts (HR = 0.129, 95% CI = 0.059–0.284, <italic>P</italic> &lt; 0.001; HR = 0.277, 95% CI = 0.116–0.661, <italic>P</italic> = 0.004, respectively). The area under the receiver operating characteristic curve (AUC) values at 5 years was 0.805 and 0.724 in the training and validation cohorts, respectively. Functional enrichment analyses showed that DNA replication, ribosome, cell cycle, and TGF-beta signaling pathway may contribute to the relapse process.</p><p><bold>Conclusion:</bold> In summary, our analysis provided a novel eight-gene signature that could predict RFS in stage I TGCT patients.</p>