Dataset Information

Single-cell RNA-sequencing reveals the landscape of cervical cancer heterogeneity

ABSTRACT: Cervical cancer (CC) is the forth leading cause of deaths in gynecological tumor. Although the etiology of CC has been extensively investigated, the exact pathogenesis of CC remains incomplete. Therefore, we applied single-cell RNA sequencing on cancer tissue and normal adjacent tissue from a patient with CC. Together, we identified four tumor cell subpopulations in tumor cells, which had specific signature genes with different biological functions and presented different prognosis. Among them, we identified a subset of cancer stem cell (CSCs), which was related to the developmental hierarchy of tumor progression. These data facilitate the understanding of the CC landscape and provides deeper insights into the development of prognostic biomarkers and therapeutic targets in the CC.

ORGANISM(S): Homo sapiens

PROVIDER: GSE168652 | GEO | 2021/05/12

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Cervical cancer (CC) is one of the most common malignancy in women worldwide. It is characterized by a natural continuous phenomenon, that is, it is in the initial stage of HPV infection, progresses to intraepithelial neoplasia, and then develops into invasion and metastasis. Determining the complexity of tumor microenvironment (TME) can deepen our understanding of lesion progression and provide novel therapeutic strategies for CC. We performed the single-cell RNA sequencing on the normal cervix, intraepithelial neoplasia, primary tumor and metastatic lymph node tissues to describe the composition, lineage, and functional status of immune cells and mesenchymal cells at different stages of CC progression. A total of 59913 single cells were obtained and divided into 9 cellular clusters, including immune cells (T/NK cells, macrophages, B cells, plasma cells, mast cells and neutrophils) and mesenchymal cells (endothelial cells, smooth muscle cells and fibroblasts). Our results showed that there were distinct cell subpopulations in different stages of CC. High-stage intraepithelial neoplasia (HSIL) tissue exhibited a low, recently activated TME, and it was characterized by high infiltration of tissue-resident CD8 T cell, effector NK cells, Treg, DC1, pDC, and M1-like macrophages. Tumor tissue displayed high enrichment of exhausted CD8 T cells, resident NK cells and M2-like macrophages, suggesting immunosuppressive TME. Metastatic lymph node consisted of naive T cell, central memory T cell, circling NK cells, cytotoxic CD8+ T cells and effector memory CD8 T cells, suggesting an early activated phase of immune response. This study is the first to delineate the transcriptome profile of immune cells during CC progression using single-cell RNA sequencing. Our results indicated that HSIL exhibited a low, recently activated TME, tumor displayed immunosuppressive statue, and metastatic lymph node showed early activated phase of immune response. Our study enhanced the understanding of dynamic change of TME during CC progression and has implications for the development of novel treatments to inhibit the initiation and progression of CC.

Dataset Information

Single-cell RNA-sequencing reveals the landscape of cervical cancer heterogeneity

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets