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Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types.

Authors :
Kang, Junho
Lee, Jun Hyeong
Cha, Hongui
An, Jinhyeon
Kwon, Joonha
Lee, Seongwoo
Kim, Seongryong
Baykan, Mert Yakup
Kim, So Yeon
An, Dohyeon
Kwon, Ah-Young
An, Hee Jung
Lee, Se-Hoon
Choi, Jung Kyoon
Park, Jong-Eun
Source :
Nature Communications; 5/14/2024, Vol. 15 Issue 1, p1-17, 17p
Publication Year :
2024

Abstract

The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8887 TCGA, and 1261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n = 1261) including our lung cancer cohort (n = 497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity. Single-cell sequencing has enabled detailed analyses of the tumour microenvironment (TME). Here, the authors perform an integrative analysis of the TME using single-cell and spatial transcriptomics data from over a thousand tumours across thirty cancer types, identifying interferon-enriched community states predictive of immunotherapeutic responses. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20411723
Volume :
15
Issue :
1
Database :
Complementary Index
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
177250827
Full Text :
https://doi.org/10.1038/s41467-024-48310-4