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Single-cell transcriptomic analysis of endometriosis.

ABSTRACT: Endometriosis is a common condition in women that causes chronic pain and infertility and is associated with an elevated risk of ovarian cancer. We profiled transcriptomes of >370,000 individual cells from endometriomas (n = 8), endometriosis (n = 28), eutopic endometrium (n = 10), unaffected ovary (n = 4) and endometriosis-free peritoneum (n = 4), generating a cellular atlas of endometrial-type epithelial cells, stromal cells and microenvironmental cell populations across tissue sites. Cellular and molecular signatures of endometrial-type epithelium and stroma differed across tissue types, suggesting a role for cellular restructuring and transcriptional reprogramming in the disease. Epithelium, stroma and proximal mesothelial cells of endometriomas showed dysregulation of pro-inflammatory pathways and upregulation of complement proteins. Somatic ARID1A mutation in epithelial cells was associated with upregulation of pro-angiogenic and pro-lymphangiogenic factors and remodeling of the endothelial cell compartment, with enrichment of lymphatic endothelial cells. Finally, signatures of ciliated epithelial cells were enriched in ovarian cancers, reinforcing epidemiologic associations between these two diseases.

SUBMITTER: Fonseca MAS

PROVIDER: S-EPMC10950360 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Single-cell transcriptomic analysis of endometriosis.

Fonseca Marcos A S MAS Haro Marcela M Wright Kelly N KN Lin Xianzhi X Abbasi Forough F Sun Jennifer J Hernandez Lourdes L Orr Natasha L NL Hong Jooyoon J Choi-Kuaea Yunhee Y Maluf Horacio M HM Balzer Bonnie L BL Fishburn Aaron A Hickey Ryan R Cass Ilana I Goodridge Helen S HS Truong Mireille M Wang Yemin Y Pisarska Margareta D MD Dinh Huy Q HQ El-Naggar Amal A Huntsman David G DG Anglesio Michael S MS Goodman Marc T MT Medeiros Fabiola F Siedhoff Matthew M Lawrenson Kate K

Nature genetics 20230109 2

Endometriosis is a common condition in women that causes chronic pain and infertility and is associated with an elevated risk of ovarian cancer. We profiled transcriptomes of >370,000 individual cells from endometriomas (n = 8), endometriosis (n = 28), eutopic endometrium (n = 10), unaffected ovary (n = 4) and endometriosis-free peritoneum (n = 4), generating a cellular atlas of endometrial-type epithelial cells, stromal cells and microenvironmental cell populations across tissue sites. Cellular ...[more]

PMID: 36624343

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Project description:BackgroundThe ability to interrogate circulating tumor cells (CTC) and disseminated tumor cells (DTC) is restricted by the small number detected and isolated (typically <10). To determine if a commercially available technology could provide a transcriptomic profile of a single prostate cancer (PCa) cell, we clonally selected and cultured a single passage of cell cycle synchronized C4-2B PCa cells. Ten sets of single, 5-, or 10-cells were isolated using a micromanipulator under direct visualization with an inverted microscope. Additionally, two groups of 10 individual DTC, each isolated from bone marrow of 2 patients with metastatic PCa were obtained. RNA was amplified using the WT-Ovation™ One-Direct Amplification System. The amplified material was hybridized on a 44K Whole Human Gene Expression Microarray. A high stringency threshold, a mean Alexa Fluor® 3 signal intensity above 300, was used for gene detection. Relative expression levels were validated for select genes using real-time PCR (RT-qPCR).ResultsUsing this approach, 22,410, 20,423, and 17,009 probes were positive on the arrays from 10-cell pools, 5-cell pools, and single-cells, respectively. The sensitivity and specificity of gene detection on the single-cell analyses were 0.739 and 0.972 respectively when compared to 10-cell pools, and 0.814 and 0.979 respectively when compared to 5-cell pools, demonstrating a low false positive rate. Among 10,000 randomly selected pairs of genes, the Pearson correlation coefficient was 0.875 between the single-cell and 5-cell pools and 0.783 between the single-cell and 10-cell pools. As expected, abundant transcripts in the 5- and 10-cell samples were detected by RT-qPCR in the single-cell isolates, while lower abundance messages were not. Using the same stringency, 16,039 probes were positive on the patient single-cell arrays. Cluster analysis showed that all 10 DTC grouped together within each patient.ConclusionsA transcriptomic profile can be reliably obtained from a single cell using commercially available technology. As expected, fewer amplified genes are detected from a single-cell sample than from pooled-cell samples, however this method can be used to reliably obtain a transcriptomic profile from DTC isolated from the bone marrow of patients with PCa.

Project description:BackgroundEndometriosis is a hormone-dependent disease, which can usually be divided into peritoneal endometriosis (PEM), deep-infiltrating endometriosis (DIE) and ovarian endometriosis (OEM). Although the three pathologic types are essentially the same disease, they differ in pathological manifestations, molecular features, pain symptoms and hormonal responsiveness. However, there is limited literature focusing on the differences among these types. In this study, we employed single-cell RNA sequencing (scRNA-seq) to profile the transcriptome of each type using surgical biopsy samples obtained from six patients. We aimed to explore and elucidate the variations among these different types of endometriosis.ResultsWe identified five major cell types and 44 subpopulations, including the presence of mesothelial cells in all pathological types, including OEM. Furthermore, we characterised the variations in cell types across different pathological types by employing enrichment analysis to assess functions and pathways. Notably, our findings reveal distinct levels of epithelial-mesenchymal transition (EMT) processes experienced by mesothelial cells within the microenvironment of endometriotic lesions. Through ligand-receptor analysis and referencing relevant literature, we propose that mesothelial cells exert an influence on progesterone resistance in stromal cells through intercellular communication mediated by the FN1-AKT pathway.ConclusionsOur study comprehensively characterises the heterogeneity of the different pathologic types of endometriosis and offers valuable insights into the underlying mechanisms contributing to variations in progesterone resistance across the three subtypes.Key pointsSingle-cell RNA (ScRNA) atlas across types of endometriosis is established. Mesothelial cells are founded in ovarian endometriosis. Endometriosis-associated mesothelial cells (EAMCs) experience various level of epithelial-mesenchymal transition (EMT) process in different subtypes. EAMCs may exert an influence on progesterone resistance in stromal cells through intercellular communication mediated by the FN1-AKT pathway.

Dataset Information

Single-cell transcriptomic analysis of endometriosis.

Publications

Single-cell transcriptomic analysis of endometriosis.

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