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논문 기본 정보

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학술저널
저자정보
표경호 (연세대학교) 황준연 (연세대학교) 김영택 (연세대학교) 나광민 (연세대학교) 김동권 (연세대학교) 이슬 (연세대학교) 강성산 (제욱 부설 암연구소) 백수정 (연세대학교) 양승민 (연세대학교) 김미현 (연세대학교) 한희경 (연세대학교) 정성수 (연세대학교) 이채영 (연세대학교) 한유진 (연세대학교) 손지온 (서울대학교) 예상규 (서울대학교)
저널정보
연세대학교 의과대학 Yonsei Medical Journal Yonsei Medical Journal Vol.65 No.9
발행연도
2024.9
수록면
544 - 555 (12page)
DOI
10.3349/ymj.2023.0639

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Purpose: By utilizing both protein and mRNA expression patterns, we can identify more detailed and diverse immune cells, providing insights into understanding the complex immune landscape in cancer ecosystems. Materials and Methods: This study was performed by obtaining publicly available Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) data of peripheral blood mononuclear cells (PBMCs) from the Gene Expression Omnibus database. A total of 94674 total cells were analyzed, of which 32412 were T cells. There were 228 protein features and 16262 mRNA features in the data. The Seurat package was used for quality control and preprocessing, principal component analysis was performed, and Uniform Manifold Approximation and Projection was used to visualize the clusters. Protein and mRNA levels in the CITE-seq were analyzed. Results: We observed that a subset of T cells in the clusters generated at the protein level divided better. By identifying mRNA markers that were highly correlated with the CD4 and CD8 proteins and cross-validating CD26 and CD99 markers using flow cytometry, we found that CD4+ and CD8+ T cells were better discriminated in PBMCs. Weighted Nearest Neighbor clustering results identified a previously unobserved T cell subset. Conclusion: In this study, we used CITE-seq data to confirm that protein expression patterns could be used to identify cells more precisely. These findings will improve our understanding of the heterogeneity of immune cells in the future and provide valuable insights into the complexity of the immune response in health and disease.

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