Single-Nucleus RNA Sequencing and Spatial Transcriptomics Reveal the Immunological Microenvironment of Cervical Squamous Cell Carcinoma.
|
IF: 17.521
|
Cited by: 16
|
Datasets
|

Abstract

The effective treatment of advanced cervical cancer remains challenging. Herein, single-nucleus RNA sequencing (snRNA-seq) and SpaTial enhanced resolution omics-sequencing (Stereo-seq) are used to investigate the immunological microenvironment of cervical squamous cell carcinoma (CSCC). The expression levels of most immune suppressive genes in the tumor and inflammation areas of CSCC are not significantly higher than those in the non-cancer samples, except for LGALS9 and IDO1. Stronger signals of CD56+ NK cells and immature dendritic cells are found in the hypermetabolic tumor areas, whereas more eosinophils, immature B cells, and Treg cells are found in the hypometabolic tumor areas. Moreover, a cluster of pro-tumorigenic cancer-associated myofibroblasts (myCAFs) are identified. The myCAFs may support the growth and metastasis of tumors by inhibiting lymphocyte infiltration and remodeling of the tumor extracellular matrix. Furthermore, these myCAFs are associated with poorer survival probability in patients with CSCC, predict resistance to immunotherapy, and might be present in a small fraction (< 30%) of patients with advanced cancer. Immunohistochemistry and multiplex immunofluorescence staining are conducted to validate the spatial distribution and potential function of myCAFs. Collectively, these findings enhance the understanding of the immunological microenvironment of CSCC and shed light on the treatment of advanced CSCC.

Keywords

Spatial Transcriptomics
mIF
Stereo-seq
cancer-associated fibroblasts
cervical cancer
single-nucleus RNA sequencing
spatial transcriptomics
tumor microenvironment

MeSH terms

Female
Humans
Carcinoma, Squamous Cell
Neoplasms, Connective Tissue
RNA, Small Nuclear
Sequence Analysis, RNA
Transcriptome
Tumor Microenvironment
Uterine Cervical Neoplasms

Authors

Ou, Zhihua
Lin, Shitong
Qiu, Jiaying
Ding, Wencheng
Ren, Peidi
Chen, Dongsheng
Wang, Jiaxuan
Tong, Yihan
Wu, Di
Chen, Ao
Deng, Yuan
Cheng, Mengnan
Peng, Ting
Lu, Haorong
Yang, Huanming
Wang, Jian
Jin, Xin
Ma, Ding
Xu, Xun
Wang, Yanzhou
Li, Junhua
Wu, Peng