Research Center for Biomedical Information Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen 518055, China.
Int J Mol Sci. 2018 Nov 15;19(11):3607. doi: 10.3390/ijms19113607.
Cervical cancer is traditionally classified into two major histological subtypes, cervical squamous cell carcinoma (CSCC) and cervical adenocarcinoma (CA). However, heterogeneity exists among patients, comprising possible subpopulations with distinct molecular profiles. We applied consensus clustering to 307 methylation samples with cervical cancer from The Cancer Genome Atlas (TCGA). Fisher's exact test was used to perform transcription factors (TFs) and genomic region enrichment. Gene expression profiles were downloaded from TCGA to assess expression differences. Immune cell fraction was calculated to quantify the immune cells infiltration. Putative neo-epitopes were predicted from somatic mutations. Three subclasses were identified: Class 1 correlating with the CA subtype and Classes 2 and 3 dividing the CSCC subtype into two subclasses. We found the hypomethylated probes in Class 3 exhibited strong enrichment in promoter region as compared with Class 2. Five TFs significantly enriched in the hypomethylated promoters and their highly expressed target genes in Class 3 functionally involved in the immune pathway. Gene function analysis revealed that immune-related genes were significantly increased in Class 3, and a higher level of immune cell infiltration was estimated. High expression of 24 immune genes exhibited a better overall survival and correlated with neo-epitope burden. Additionally, we found only two immune-related driver genes, and , to be significantly increased in Class 3. Our analyses provide a classification of the largest CSCC subtype into two new subclasses, revealing they harbored differences in immune-related gene expression.
宫颈癌传统上分为两种主要的组织学亚型，宫颈鳞状细胞癌（CSCC）和宫颈腺癌（CA）。然而，患者之间存在异质性，可能包含具有不同分子特征的亚群。我们应用共识聚类分析了来自癌症基因组图谱（TCGA）的 307 个宫颈癌甲基化样本。Fisher 精确检验用于进行转录因子（TF）和基因组区域富集分析。从 TCGA 下载基因表达谱以评估表达差异。计算免疫细胞分数以量化免疫细胞浸润。从体细胞突变预测潜在的新表位。鉴定出三个亚类：与 CA 亚型相关的类 1 和将 CSCC 亚型分为两个亚类的类 2 和 3。我们发现与类 2 相比，类 3 中的低甲基化探针在启动子区域表现出强烈的富集。在低甲基化启动子中显著富集的五个 TF 及其在类 3 中高表达的靶基因，在功能上参与免疫途径。基因功能分析显示，类 3 中免疫相关基因显著增加，估计免疫细胞浸润水平更高。24 个免疫基因的高表达显示出更好的总生存率，并与新表位负担相关。此外，我们发现只有两个免疫相关的驱动基因，和 ，在类 3 中显著增加。我们的分析为最大的 CSCC 亚型提供了一种新的分类方法，揭示了它们在免疫相关基因表达方面存在差异。
