Cao Jian, Liu Zhizhong, Yuan Junbin, Luo Yanwei, Wang Jinrong, Liu Jianye, Bo Hao, Guo Jie
Hunan Cancer Hospital, Department of Urology, The Affiliated Cancer Hospital of Xiangya School of Medicine of Central South University, Changsha, 410013, Hunan, China.
Department of Urology, Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
Heliyon. 2024 Jan 8;10(2):e24320. doi: 10.1016/j.heliyon.2024.e24320. eCollection 2024 Jan 30.
Testicular germ cell tumors (TGCT) are the most common reproductive system malignancies in men aged 15-44 years, accounting for 95 % of all testicular tumors. Our previous studies have been shown that long non-coding RNAs (lncRNAs), such as LINC00313, TTTY14 and RFPL3S, were associated with development of TGCT. Subgrouping TGCT according to differential expressed lncRNAs and immunological characteristics is helpful to comprehensively describe the characteristics of TGCT and implement precise treatment. In this study, the TGCT transcriptome data in The Cancer Genome Atlas Program (TCGA) database was used to perform consensus clustering analysis to construct a prognostic model for TGCT. TGCT was divided into 3 subtypes C1, C2, and C3 based on the differentially expressed lncRNAs. C1 subtype was sensitive to chemotherapy drugs, while the C2 subtype was not sensitive to chemotherapy drugs, and C3 subtype may benefit from immunotherapy. We defined the C1 subtype as epidermal progression subtype, the C2 subtype as mesenchymal progression subtype, and the C3 subtype as T cell activation subtype. Subgrouping based on differentially expressed genes (DEGs) and immunological characteristics is helpful for the precise treatment of TGCT.
睾丸生殖细胞肿瘤（TGCT）是15至44岁男性中最常见的生殖系统恶性肿瘤，占所有睾丸肿瘤的95%。我们之前的研究表明，长链非编码RNA（lncRNA），如LINC00313、TTTY14和RFPL3S，与TGCT的发生发展有关。根据差异表达的lncRNA和免疫特征对TGCT进行亚组分类，有助于全面描述TGCT的特征并实施精准治疗。在本研究中，利用癌症基因组图谱计划（TCGA）数据库中的TGCT转录组数据进行一致性聚类分析，构建TGCT的预后模型。基于差异表达的lncRNA，TGCT被分为C1、C2和C3三种亚型。C1亚型对化疗药物敏感，而C2亚型对化疗药物不敏感，C3亚型可能从免疫治疗中获益。我们将C1亚型定义为表皮进展亚型，C2亚型定义为间充质进展亚型，C3亚型定义为T细胞激活亚型。基于差异表达基因（DEG）和免疫特征进行亚组分类有助于TGCT的精准治疗。
