Subtyping of Human Papillomavirus-Positive Cervical Cancers Based on the Expression Profiles of 50 Genes

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.

Sequencing-based transcriptome analysis reveals diversification of immune response- and angiogenesis-related expression patterns of early-stage cervical carcinoma as compared with high-grade CIN

“…Relatedness of the DDR-associated processes and “heating-up” the immune TME has also been underscored by some researchers ( 42 , 46 – 48 ). As regards cell-type enrichment of the immune and stromal TME, our observations on early invasive CeCa are in agreement with the existence of immune-active and immune-suppressed phenotypes ( 49 – 51 ). However, intriguingly, cancer samples with an immune-active profile expressed relatively less well explored checkpoint markers, such as PDL2, BTN3A, TIGIT, and CD73; their dual stimulatory/inhibitory role in the immune response regulation attracts growing interest in view of their diagnostic/therapeutic potential.…”

Single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer

“…They revealed highly heterogenous molecular profiles across samples and identified three subtypes, i.e., the keratin-low squamous, keratin-high squamous and adenocarcinoma-rich subtype. Zhu et al identified two subtypes of HPV + CC based on the most varied 50 genes across CC samples 8 . Furthermore, an increasing number of studies have identified molecular units (including DNA, RNA, and proteins) as biomarkers for the diagnosis and treatment of CC [9][10][11] .…”

Gene and Genetic Studies of Tumor Microenvironment

“…Maud Kamal et al discovered the different integration signatures of HPV genome in cervical cancer that may imply prognostic significance (Kamal et al, 2021). With the 50 genes having the largest expression variation, Xiaojun Zhu et al demonstrated two molecular subgroups in cervical cancer and explored the heterogeneity, which provided novel targets for diagnosis and treatment (Zhu et al, 2022). Here we provided a novel classification approach to dissect the heterogeneity of cervical cancer from the immunological and metabolic perspectives.…”