Single-cell transcriptomics in ovarian cancer identify a metastasis-associated cell cluster overexpressed RAB13

Abstract

Background Metastasis, the leading cause of cancer-related death in patients diagnosed with ovarian cancer (OC), is a complex process that involves multiple biological effects. With the continuous development of sequencing technology, single-cell sequence has emerged as a promising strategy to understand the pathogenesis of ovarian cancer. Methods Through integrating 10 × single-cell data from 12 samples, we developed a single-cell map of primary and metastatic OC. By copy-number variations analysis, pseudotime analysis, enrichment analysis, and cell–cell communication analysis, we explored the heterogeneity among OC cells. We performed differential expression analysis and high dimensional weighted gene co-expression network analysis to identify the hub genes of C4. The effects of RAB13 on OC cell lines were validated in vitro. Results We discovered a cell subcluster, referred to as C4, that is closely associated with metastasis and poor prognosis in OC. This subcluster correlated with an epithelial–mesenchymal transition (EMT) and angiogenesis signature and RAB13 was identified as the key marker of it. Downregulation of RAB13 resulted in a reduction of OC cells migration and invasion. Additionally, we predicted several potential drugs that might inhibit RAB13. Conclusions Our study has identified a cell subcluster that is closely linked to metastasis in OC, and we have also identified RAB13 as its hub gene that has great potential to become a new therapeutic target for OC.

Single-cell and spatial transcriptome sequencing uncover a platinum-resistant cluster overexpressed TACSTD2 in high-grade serous ovarian cancer

“…To better investigate the roles of E0 in epithelial cells, inferCNV showed that E0 displayed the highest gene CNV among all epithelial subgroups, further supported by pseudotime trajectory analysis, positioning E0 at the late stage of tumour cell differentiation with E4 as the starting point (Figure 2 F, G). Along trajectory, late stage of epithelial subclusters indicate tumour cells' metastatic, treatment resistant characteristics 17 .…”

Investigating cellular similarities and differences between upper tract urothelial carcinoma and bladder urothelial carcinoma using single-cell sequencing

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Unlocking ovarian cancer heterogeneity: advancing immunotherapy through single-cell transcriptomics

“…Although many studies have explored the mechanisms and treatment of ovarian cancer at single cell level, the primary focus was given to the commonalities among multiple patients limited by the sample size and the high inter-tumor heterogeneity of ovarian cancer. Nevertheless, a study by Guo et al successfully constructed a cell atlas containing normal epithelium, primary carcinoma, and metastatic carcinoma by integrating single-cell sequence data from 12 patients (81). In this study, the developmental trajectory of cancer cells during metastasis was characterized using pseudo-time trajectory analysis at various phases, and a cell subcluster with commonality in patients and close association with metastasis was found.…”

“…Nevertheless, a study by Guo et al. successfully constructed a cell atlas containing normal epithelium, primary carcinoma, and metastatic carcinoma by integrating single-cell sequence data from 12 patients ( 81 ). In this study, the developmental trajectory of cancer cells during metastasis was characterized using pseudo-time trajectory analysis at various phases, and a cell subcluster with commonality in patients and close association with metastasis was found.…”