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

Commun Biol. 2022 Nov 10;5(1):1208. doi: 10.1038/s42003-022-04142-w.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cancer-Associated Fibroblasts* / pathology
  • Female
  • Humans
  • Prognosis
  • Single-Cell Analysis / methods
  • Transcriptome
  • Uterine Cervical Neoplasms* / genetics
  • Uterine Cervical Neoplasms* / pathology