The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Dissecting transcriptional heterogeneity in primary gastric adenocarcinoma by single cell RNA sequencing
Open accessAbstract
Objective: Tumour heterogeneity represents a major obstacle to accurate diagnosis and treatment in gastric adenocarcinoma (GA). Here, we report a systematic transcriptional atlas to delineate molecular and cellular heterogeneity in GA using single-cell RNA sequencing (scRNA-seq). Design: We performed unbiased transcriptome-wide scRNA-seq analysis on 27 677 cells from 9 tumour and 3 non-tumour samples. Analysis results were validated using large-scale histological assays and bulk transcriptomic datasets. Results: Our integrative analysis of tumour cells identified five cell subgroups with distinct expression profiles. A panel of differentiation-related genes reveals a high diversity of differentiation degrees within and between tumours. Low differentiation degrees can predict poor prognosis in GA. Among them, three subgroups exhibited different differentiation grade which corresponded well to histopathological features of Lauren’s subtypes. Interestingly, the other two subgroups displayed unique transcriptome features. One subgroup expressing chief-cell markers (eg, LIPF and PGC ) and RNF43 with Wnt/β-catenin signalling pathway activated is consistent with the previously described entity fundic gland-type GA (chief cell-predominant, GA-FG-CCP). We further confirmed the presence of GA-FG-CCP in two public bulk datasets using transcriptomic profiles and histological images. The other subgroup specifically expressed immune-related signature genes (eg, LY6K and major histocompatibility complex class II) with the infection of Epstein-Barr virus. In addition, we also analysed non-malignant epithelium and provided molecular evidences for potential transition from gastric chief cells into MUC6 + TFF2 + spasmolytic polypeptide expressing metaplasia. Conclusion: Altogether, our study offers valuable resource for deciphering gastric tumour heterogeneity, which will provide assistance for precision diagnosis and prognosis.
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Comprehensive molecular characterization of gastric adenocarcinoma
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Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma
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Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes
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Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing
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Cited by
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Lei, Y., Tang, R., Xu, J., Wang, W., Zhang, B., Liu, J., Yu, X., & Shi, S. (2021) · Journal of Hematology & Oncology · doi:10.1186/s13045-021-01105-2 · Cited by 592
Kumar, V., Ramnarayanan, K., Sundar, R., Padmanabhan, N., Srivastava, S., Koiwa, M., Yasuda, T., Koh, V., Huang, K. K., Tay, S. T., et al. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0683 · Cited by 573
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Deterministic evolution and stringent selection during preneoplasia
Karlsson, K., Przybilla, M. J., Kotler, E., Khan, A., Xu, H., Karagyozova, K., Sockell, A., Wong, W. H., Liu, K., Mah, A., et al. (2023) · Nature · doi:10.1038/s41586-023-06102-8 · Cited by 83
Benchmarking algorithms for pathway activity transformation of single-cell RNA-seq data
Zhang, Y., Ma, Y., Huang, Y., Zhang, Y., Jiang, Q., Zhou, M., & Su, J. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2020.10.007 · Cited by 79
Metadata
- Authors
- Zhang, M., Hu, S., Min, M., Ni, Y., Lu, Z., Sun, X., Wu, J., Liu, B., Ying, X., & Liu, Y.
- Venue
- Gut
- Publisher
- BMJ
- Published
- 2020-06-12
- Volume
- 70
- Issue
- 3
- Pages
- 464-475
- ISSN
- 0017-5749 (ISSN-L)
- 1468-3288
- OpenAlex
- W3034402905
- Cited by
- 339
- References
- 40
- FWCI
- 10.99
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Zhang, M., Hu, S., Min, M., Ni, Y., Lu, Z., Sun, X., Wu, J., Liu, B., Ying, X., & Liu, Y. (2021). Dissecting transcriptional heterogeneity in primary gastric adenocarcinoma by single cell RNA sequencing. Gut. https://doi.org/10.1136/gutjnl-2019-320368
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