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

Abstract

Cervical cancer (CC) is the most common gynecological malignancy, whose cellular heterogeneity has not been fully understood. Here, we performed single-cell RNA sequencing (scRNA-seq) to survey the transcriptomes of 57,669 cells derived from three CC tumors with paired normal adjacent non-tumor (NAT) samples. Single-cell transcriptomics analysis revealed extensive heterogeneity in malignant cells of human CCs, wherein epithelial subpopulation exhibited different genomic and transcriptomic signatures. We also identified cancer-associated fibroblasts (CAFs) that may promote tumor progression of CC, and further distinguished inflammatory CAF (iCAF) and myofibroblastic CAF (myCAF). CD8⁺ T cell diversity revealed both proliferative (MKI67⁺) and non-cycling exhausted (PDCD1⁺) subpopulations at the end of the trajectory path. We used the epithelial signature genes derived from scRNA-seq to deconvolute bulk RNA-seq data of CC, identifying four different CC subtypes, namely hypoxia (S-H subtype), proliferation (S-P subtype), differentiation (S-D subtype), and immunoactive (S-I subtype) subtype. The S-H subtype showed the worst prognosis, while CC patients of the S-I subtype had the longest overall survival time. Our results lay the foundation for precision prognostic and therapeutic stratification of CC.

Single-cell RNA sequencing of cervical cancer reveals four different cancer subtypes and provides information on populations of cancer-associated fibroblasts as well as CD8+ T cell diversity.