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深度免疫表型分析揭示了大规模结直肠癌中具有临床显著差异的细胞状态和生态系统。

Deep immunophenotyping reveals clinically distinct cellular states and ecosystems in large-scale colorectal cancer.

机构信息

Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, 571199, China.

School of Interdisciplinary Medicine and Engineering, Harbin Medical University, Harbin, 150081, China.

出版信息

Commun Biol. 2023 Jul 27;6(1):785. doi: 10.1038/s42003-023-05117-1.

Abstract

Determining the diverse cell types in the tumor microenvironment (TME) and their organization into cellular communities, is critical for understanding the biological heterogeneity and therapy of cancer. Here, we deeply immunophenotype the colorectal cancer (CRC) by integrative analysis of large-scale bulk and single cell transcriptome of 2350 patients and 53,137 cells. A rich landscape of 42 cellular states and 7 ecosystems in TMEs is uncovered and extend the previous immune classifications of CRC. Functional pathways and potential transcriptional regulators analysis of cellular states and ecosystems reveal cancer hallmark-related pathways and several critical transcription factors in CRC. High-resolution characterization of the TMEs, we discover the potential utility of cellular states (i.e., Monocytes/Macrophages and CD8 T cell) and ecosystems for prognosis and clinical therapy selection of CRC. Together, our results expand our understanding of cellular organization in TMEs of CRC, with potential implications for the development of biomarkers and precision therapies.

摘要

确定肿瘤微环境(TME)中的多种细胞类型及其组织成细胞群落,对于理解癌症的生物学异质性和治疗至关重要。在这里,我们通过对 2350 名患者和 53137 个细胞的大规模批量和单细胞转录组的综合分析,深入免疫表型分析了结直肠癌(CRC)。揭示了 TME 中 42 种细胞状态和 7 个生态系统的丰富景观,并扩展了之前 CRC 的免疫分类。对细胞状态和生态系统的功能途径和潜在转录因子分析揭示了与癌症特征相关的途径和 CRC 中的几个关键转录因子。通过对 TME 的高分辨率特征分析,我们发现细胞状态(即单核细胞/巨噬细胞和 CD8 T 细胞)和生态系统在 CRC 的预后和临床治疗选择方面具有潜在的应用价值。总之,我们的研究结果扩展了我们对 CRC 中 TME 中细胞组织的理解,这可能对生物标志物和精准治疗的发展具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b57/10374645/ba3b3397ee6a/42003_2023_5117_Fig1_HTML.jpg

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