Cancer-testis (CT) genes are a group of genes restrictedly expressed in testis and multiple cancers and can serve as candidate driver genes participating in the development of cancers. Our previous study identified a number of CT genes in nongerm cell tumors, but their expression pattern in testicular germ cell tumor (TGCT), a cancer type characterized by less genomic alterations, remained largely unknown. In this study, we systematically investigated the expression pattern of CT genes in TGCT samples and evaluated the transcriptome difference between TGCT and normal testis tissues, using datasets from the UCSC Xena platform, The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project. Pathway enrichment analysis and survival analysis were conducted to evaluate the biological function and prognostic effect of expressed CT genes. We identified that 1036 testis-specific expressed protein-coding genes and 863 testis-specific expressed long noncoding RNAs (lncRNAs) were expressed in TGCT samples, including 883 CT protein-coding genes and 710 CT lncRNAs defined previously. The number of expressed CT genes was significantly higher in seminomas (P = 3.48 × 10-13 ) which were characterized by frequent mutations in driver genes (KIT, KRAS and NRAS). In contrast, the number of expressed CT genes showed a moderate negative correlation with the fraction of copy number altered genomes (cor = -0.28, P = 1.20 × 10-3 ). Unlike other cancers, our analysis revealed that 96.16% of the CT genes were down-regulated in TGCT samples, while CT genes in stem cell maintenance related pathways were up-regulated. Further survival analysis provided evidence that CT genes could also predict the prognosis of TGCT patients with both disease-free interval and progression-free interval as clinical endpoints. Taken together, our study provided a global view of CT genes in TGCT and provided evidence that CT genes played important roles in the progression and maintenance of TGCT.
Cancer medicine. 2019 May 09 [Epub ahead of print]
Yuting Chang, Xuewei Wang, Yide Xu, Liu Yang, Qufei Qian, Sihan Ju, Yao Chen, Shuaizhou Chen, Na Qin, Zijian Ma, Juncheng Dai, Hongxia Ma, Guangfu Jin, Erbao Zhang, Cheng Wang, Zhibin Hu
Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China., Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China.