Identification of cervical cancer stem cells using single-cell transcriptomes of normal cervix, cervical premalignant lesions, and cervical cancer
Background: Cervical cancer is the fourth leading cause of mortality among gynecological malignancies. However, the identification of cervical cancer stem cells remains unclear. Methods: We performed single-cell mRNA sequencing on ∼122,400 cells from 20 cervical biopsies, including 5 healthy controls, 4 high-grade intraepithelial neoplasias, 5 microinvasive carcinomas of the cervix, and 6 invasive cervical squamous carcinomas. Bioinformatic results were validated by multiplex immunohistochemistry (mIHC) in cervical cancer tissue microarrays (TMA) (n = 85). Findings: We identified cervical cancer stem cells and highlighted the functional changes in cervical stem cells during malignant transformation. The original non-malignant stem cell properties (characterized by high proliferation) gradually diminished, whereas the tumor stem cell properties (characterized by epithelial-mesenchymal transformation and invasion) were enhanced. The mIHC results of our TMA cohort confirmed the existence of stem-like cells and indicated that cluster correlated with neoplastic recurrence. Subsequently, we investigated malignant and immune cell heterogeneity in the cervical multicellular ecosystem across different disease stages. We observed global upregulation of interferon responses in the cervical microenvironment during lesion progression. Interpretation: Our results provide more insights into cervical premalignant and malignant lesion microenvironments. Funding: This research was supported by the Guangdong Provincial Natural Science Foundation of China (2023A1515010382), Grant 2021YFC2700603 from the National Key Research & Development Program of China and the Hubei Provincial Natural Science Foundation of China (2022CFB174 and 2022CFB893). Keywords: Cancer stem cell; Cervical cancer; HSIL; Microinvasive carcinoma of the cervix; Single-cell RNA sequencing; Tumor microenvironment.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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