Shen Cheng, Zheng Bing, Chen Zhan, Zhang Wei, Chen Xinfeng, Xu Siyang, Ji Jianfeng, Fang Xingxing, Shi Chunmei
Department of Urology, Affiliated Hospital 2 of Nantong University, China.
Medical Research Center, Affiliated Hospital 2 of Nantong University, China.
Heliyon. 2024 Mar 13;10(6):e27710. doi: 10.1016/j.heliyon.2024.e27710. eCollection 2024 Mar 30.
One of the most fatal forms of cancer of the urinary system, renal cell carcinoma (RCC), significantly negatively impacts human health. Recent research reveals that abnormal glycosylation contributes to the growth and spread of tumors. However, there is no information on the function of genes related to glycosylation in RCC.
In this study, we created a technique that can be used to guide the choice of immunotherapy and chemotherapy regimens for RCC patients while predicting their survival prognosis. The Cancer Genome Atlas (TCGA) provided us with patient information, while the GeneCards database allowed us to collect genes involved in glycosylation. GSE29609 was used as external validation to assess the accuracy of prognostic models. The "ConsensusClusterPlus" program created molecular subtypes based on genes relevant to glycosylation discovered using differential expression analysis and univariate Cox analysis. We examined immune cell infiltration as measured by estimate, CIBERSORT, TIMER, and ssGSEA algorithms, Tumor Immune Dysfunction and Exclusion (TIDE) and exclusion of tumour stemness indices (TSIs) based on glycosylation-related molecular subtypes and risk profiles. Stratification, somatic mutation, nomogram creation, and chemotherapy response prediction were carried out based on risk factors.
We built and verified 16 gene signatures associated with the prognosis of ccRCC patients, which are independent prognostic variables, and identified glycosylation-related genes by bioinformatics research. Cluster 2 is associated with lower human leukocyte antigen expression, worse overall survival, higher immunological checkpoints, and higher immune escape scores. In addition, cluster 2 had significantly better angiogenic activity, mesenchymal EMT, and stem ability scores. Higher immune checkpoint genes and human leukocyte antigens are associated with lower overall survival and a higher risk score. Higher estimated and immune scores, lesser tumor purity, lower mesenchymal EMT, and higher stem scores were all characteristics of the high-risk group. High amounts of tumor-infiltrating lymphocytes, a high mutation load, and a high copy number alteration frequency were present in the high-risk group.Discussion.According to our research, the 16-gene prognostic signature may be helpful in predicting prognosis and developing individualized treatments for patients with renal clear cell carcinoma, which may result in new personalized management options for these patients.
肾细胞癌（RCC）是泌尿系统最致命的癌症形式之一，对人类健康有显著负面影响。最近的研究表明，异常糖基化有助于肿瘤的生长和扩散。然而，关于RCC中与糖基化相关基因的功能尚无信息。
在本研究中，我们创建了一种技术，可用于指导RCC患者免疫治疗和化疗方案的选择，同时预测其生存预后。癌症基因组图谱（TCGA）为我们提供患者信息，而基因卡片数据库使我们能够收集参与糖基化的基因。GSE29609用作外部验证，以评估预后模型的准确性。“ConsensusClusterPlus”程序基于使用差异表达分析和单变量Cox分析发现的与糖基化相关的基因创建分子亚型。我们通过估计、CIBERSORT、TIMER和ssGSEA算法检测免疫细胞浸润，基于与糖基化相关的分子亚型和风险概况检测肿瘤免疫功能障碍和排除（TIDE）以及肿瘤干性指数（TSI）的排除情况。基于风险因素进行分层、体细胞突变分析、列线图创建和化疗反应预测。
我们构建并验证了与ccRCC患者预后相关的16个基因特征，它们是独立的预后变量，并通过生物信息学研究确定了与糖基化相关的基因。聚类2与较低的人类白细胞抗原表达、较差的总生存期、较高的免疫检查点和较高的免疫逃逸评分相关。此外，聚类2具有显著更好的血管生成活性、间充质上皮转化和干性能力评分。较高的免疫检查点基因和人类白细胞抗原与较低的总生存期和较高的风险评分相关。高估计和免疫评分、较低的肿瘤纯度、较低的间充质上皮转化和较高的干性评分都是高危组的特征。高危组中存在大量肿瘤浸润淋巴细胞、高突变负荷和高拷贝数改变频率。
根据我们的研究，16基因预后特征可能有助于预测肾透明细胞癌患者的预后并制定个体化治疗方案，这可能为这些患者带来新的个性化管理选择。
