Abstract
BackgroundHuman papillomavirus-positive (HPV+) cervical cancers are highly heterogeneous in molecular and clinical features. However, the molecular classification of HPV+ cervical cancers remains insufficiently unexplored.MethodsBased on the expression profiles of 50 genes having the largest expression variations across the HPV+ cervical cancers in the TCGA-CESC dataset, we hierarchically clustered HPV+ cervical cancers to identify new subtypes. We further characterized molecular, phenotypic, and clinical features of these subtypes.ResultsWe identified two subtypes of HPV+ cervical cancers, namely HPV+G1 and HPV+G2. We demonstrated that this classification method was reproducible in two validation sets. Compared to HPV+G2, HPV+G1 displayed significantly higher immune infiltration level and stromal content, lower tumor purity, lower stemness scores and intratumor heterogeneity (ITH) scores, higher level of genomic instability, lower DNA methylation level, as well as better disease-free survival prognosis. The multivariate survival analysis suggests that the disease-free survival difference between both subtypes is independent of confounding variables, such as immune signature, stemness, and ITH. Pathway and gene ontology analysis confirmed the more active tumor immune microenvironment in HPV+G1 versus HPV+G2.ConclusionsHPV+ cervical cancers can be classified into two subtypes based on the expression profiles of the 50 genes with the largest expression variations across the HPV+ cervical cancers. Both subtypes have significantly different molecular, phenotypic, and clinical features. This new subtyping method captures the comprehensive heterogeneity in molecular and clinical characteristics of HPV+ cervical cancers and provides potential clinical implications for the diagnosis and treatment of this disease.
Highlights
Cervical cancer is the most common gynecological malignancy [1], of which around 90% are squamous cell carcinomas and 10% are adenocarcinomas
Previous studies have revealed that human papillomavirus (HPV)-18 infection is an adverse prognostic parameter and that HPV-16 infection has no significant association with survival prognosis in cervical cancer [3]
We hierarchically clustered HPV+ cervical cancers based on the expression profiles of 50 genes which had the largest expression variations across the HPV+ cervical cancers
Summary
Cervical cancer is the most common gynecological malignancy [1], of which around 90% are squamous cell carcinomas and 10% are adenocarcinomas. Previous studies have revealed that HPV-18 infection is an adverse prognostic parameter and that HPV-16 infection has no significant association with survival prognosis in cervical cancer [3]. Most of cervical squamous cell carcinoma (CESC) patients are HPV-positive, while about 25% of cervical adenocarcinoma patients are HPV-negative [4]. Previous studies have revealed that cervical cancer is highly heterogeneous in clinical and molecular profiles [5]. TCGA identified three subtypes of cervical cancer, namely keratin-low squamous, keratin-high squamous, and adenocarcinoma-rich by an integrative analysis of copy number, methylation, mRNA and microRNA profiles [5]. Human papillomavirus-positive (HPV+) cervical cancers are highly heterogeneous in molecular and clinical features. The molecular classification of HPV+ cervical cancers remains insufficiently unexplored
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