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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.

SUBMITTER: Li C

PROVIDER: S-EPMC9649750 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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

Li Chunbo C Wu Hao H Guo Luopei L Liu Danyang D Yang Shimin S Li Shengli S Hua Keqin K

Communications biology 20221110 1

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 signat ...[more]

PMID: 36357663

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Project description:Wool is the critical textile raw material which is produced by the hair follicle of sheep. Therefore, it has important implications to investigate the molecular mechanism governing hair follicle development. Due to high cellular heterogeneity as well as the insufficient cellular, molecular, and spatial characterization of hair follicles on sheep, the molecular mechanisms involved in hair follicle development and wool curvature of sheep remains largely unknown. Single-cell RNA sequencing (scRNA-seq) technologies have made it possible to comprehensively dissect the cellular composition of complex skin tissues and unveil the differentiation and spatial signatures of epidermal and hair follicle development. However, such studies are lacking so far in sheep. Here, single-cell suspensions from the curly wool and straight wool lambskins were prepared for unbiased scRNA-seq. Based on UAMP dimension reduction analysis, we identified 19 distinct cell populations from 15,830 single-cell transcriptomes and characterized their cellular identity according to specific gene expression profiles. Furthermore, novel marker gene was applied in identifying dermal papilla cells isolated in vitro. By using pseudotime ordering analysis, we constructed the matrix cell lineage differentiation trajectory and revealed the dynamic gene expression profiles of matrix progenitors' commitment to the hair shaft and inner root sheath (IRS) cells. Meanwhile, intercellular communication between mesenchymal and epithelial cells was inferred based on CellChat and the prior knowledge of ligand-receptor pairs. As a result, strong intercellular communication and associated signaling pathways were revealed. Besides, to clarify the molecular mechanism of wool curvature, differentially expressed genes in specific cells between straight wool and curly wool were identified and analyzed. Our findings here provided an unbiased and systematic view of the molecular anatomy of sheep hair follicle comprising 19 clusters; revealed the differentiation, spatial signatures, and intercellular communication underlying sheep hair follicle development; and at the same time revealed the potential molecular mechanism of wool curvature, which will give important new insights into the biology of the sheep hair follicle and has implications for sheep breeding.

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

Publications

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

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