Abstract
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, CARD11 and JAK3, 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.
Highlights
Cervical cancer is the second most prevalent cancer in females worldwide and can be traditionally classified into two common histological subtypes: cervical squamous cell carcinoma (CSCC) and cervical adenocarcinoma (CA)
CSCC accounts for approximately 80% of all cervical cancer cases [1], with most of the remaining cases being CA
By combining the clustering results with the clinical information, we found that the largest cervical cancer subtype CSCC could be divided into two new subclasses, while the CA subtype stayed a single separate subclass
Summary
Cervical cancer is the second most prevalent cancer in females worldwide and can be traditionally classified into two common histological subtypes: cervical squamous cell carcinoma (CSCC) and cervical adenocarcinoma (CA). CSCC accounts for approximately 80% of all cervical cancer cases [1], with most of the remaining cases being CA. Evidences have shown that differences exist between these two subtypes, including risk factors [2], incidence rates [3], clinical features [4], and mutations [5]. In addition to the histological difference, cervical cancer shows heterogeneity related to microenvironments such as hypoxia, variation in response to treatment, risk of metastasis, and gene expression [7,8,9,10]. Intratumoral metabolic and gene mutation heterogeneities are observed in cervical cancer [11,12]. It is possible that the subpopulations present will have distinct molecular profiles with different levels of intrinsic response to therapy. Accurate subclass identification and characterization of the underlying mechanism are pivotal for our understanding of the disease and for the guiding of personalized therapies
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