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Single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9649750/ https://www.ncbi.nlm.nih.gov/pubmed/36357663 http://dx.doi.org/10.1038/s42003-022-04142-w |
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author | Li, Chunbo Wu, Hao Guo, Luopei Liu, Danyang Yang, Shimin Li, Shengli Hua, Keqin |
author_facet | Li, Chunbo Wu, Hao Guo, Luopei Liu, Danyang Yang, Shimin Li, Shengli Hua, Keqin |
author_sort | Li, Chunbo |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9649750 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96497502022-11-15 Single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer Li, Chunbo Wu, Hao Guo, Luopei Liu, Danyang Yang, Shimin Li, Shengli Hua, Keqin Commun Biol Article 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. Nature Publishing Group UK 2022-11-10 /pmc/articles/PMC9649750/ /pubmed/36357663 http://dx.doi.org/10.1038/s42003-022-04142-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Li, Chunbo Wu, Hao Guo, Luopei Liu, Danyang Yang, Shimin Li, Shengli Hua, Keqin Single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer |
title | Single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer |
title_full | Single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer |
title_fullStr | Single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer |
title_full_unstemmed | Single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer |
title_short | Single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer |
title_sort | single-cell transcriptomics reveals cellular heterogeneity and molecular stratification of cervical cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9649750/ https://www.ncbi.nlm.nih.gov/pubmed/36357663 http://dx.doi.org/10.1038/s42003-022-04142-w |
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