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多区域单细胞剖析肿瘤和免疫细胞揭示肝癌中稳定的锁钥特征。

Multiregional single-cell dissection of tumor and immune cells reveals stable lock-and-key features in liver cancer.

机构信息

Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, 20892, USA.

Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, Bethesda, MD, 20892, USA.

出版信息

Nat Commun. 2022 Dec 7;13(1):7533. doi: 10.1038/s41467-022-35291-5.


DOI:10.1038/s41467-022-35291-5
PMID:36476645
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9729309/
Abstract

Intratumor heterogeneity may result from the evolution of tumor cells and their continuous interactions with the tumor microenvironment which collectively drives tumorigenesis. However, an appearance of cellular and molecular heterogeneity creates a challenge to define molecular features linked to tumor malignancy. Here we perform multiregional single-cell RNA sequencing (scRNA-seq) analysis of seven liver cancer patients (four hepatocellular carcinoma, HCC and three intrahepatic cholangiocarcinoma, iCCA). We identify cellular dynamics of malignant cells and their communication networks with tumor-associated immune cells, which are validated using additional scRNA-seq data of 25 HCC and 12 iCCA patients as a stable fingerprint embedded in a malignant ecosystem representing features of tumor aggressiveness. We further validate the top ligand-receptor interaction pairs (i.e., LGALS9-SLC1A5 and SPP1-PTGER4 between tumor cells and macrophages) associated with unique transcriptome in additional 542 HCC patients. Our study unveils stable molecular networks of malignant ecosystems, which may open a path for therapeutic exploration.

摘要

肿瘤内异质性可能源于肿瘤细胞的进化及其与肿瘤微环境的持续相互作用,这些共同推动了肿瘤的发生。然而,细胞和分子异质性的出现给定义与肿瘤恶性程度相关的分子特征带来了挑战。在这里,我们对 7 名肝癌患者(4 名肝细胞癌,HCC 和 3 名肝内胆管癌,iCCA)进行了多区域单细胞 RNA 测序(scRNA-seq)分析。我们确定了恶性细胞的细胞动态及其与肿瘤相关免疫细胞的通讯网络,并用另外 25 名 HCC 和 12 名 iCCA 患者的额外 scRNA-seq 数据进行了验证,这些数据作为嵌入恶性生态系统中的稳定指纹,代表了肿瘤侵袭性的特征。我们还在另外 542 名 HCC 患者中验证了与肿瘤细胞和巨噬细胞之间独特转录组相关的顶级配体-受体相互作用对(即 LGALS9-SLC1A5 和 SPP1-PTGER4)。我们的研究揭示了恶性生态系统的稳定分子网络,这可能为治疗探索开辟了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/aa5b7fc4d783/41467_2022_35291_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/67a99a907edd/41467_2022_35291_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/9c9fb25f0262/41467_2022_35291_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/22cbbd7cebfc/41467_2022_35291_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/16488fd0302d/41467_2022_35291_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/1ed96b982ab0/41467_2022_35291_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/8a8010cac38e/41467_2022_35291_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/aa5b7fc4d783/41467_2022_35291_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/67a99a907edd/41467_2022_35291_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/9c9fb25f0262/41467_2022_35291_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/22cbbd7cebfc/41467_2022_35291_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/16488fd0302d/41467_2022_35291_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/1ed96b982ab0/41467_2022_35291_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/8a8010cac38e/41467_2022_35291_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6e1/9729309/aa5b7fc4d783/41467_2022_35291_Fig7_HTML.jpg

相似文献

[1]
Multiregional single-cell dissection of tumor and immune cells reveals stable lock-and-key features in liver cancer.

Nat Commun. 2022-12-7

[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma.

Front Bioinform. 2025-8-18

[2]
Dissecting the heterogeneity and tumor-associated dynamics of human liver group I ILC via scRNA sequencing data.

Immunol Res. 2025-8-23

[3]
Elucidating the dynamic tumor microenvironment through deep transcriptomic analysis and therapeutic implication of MRE11 expression patterns in hepatocellular carcinoma.

Cancer Cell Int. 2025-8-21

[4]
Genomic and the tumor microenvironment heterogeneity in multifocal hepatocellular carcinoma.

Hepatology. 2025-9-1

[5]
Harnessing multi-omics and artificial intelligence: revolutionizing prognosis and treatment in hepatocellular carcinoma.

Front Immunol. 2025-7-23

[6]
Comparative transcriptomic and genomic analysis of tumor cells in the marginal and center regions of tumor nests in human hepatocellular carcinoma.

Front Cell Dev Biol. 2025-7-16

[7]
Integrated Multi-Omics Profiling Identifies PDZ-Binding Kinase (PBK) as a Novel Prognostic Biomarker in Hepatocellular Carcinoma.

J Hepatocell Carcinoma. 2025-7-17

[8]
Characterization of T cell proliferation-associated hepatocellular carcinoma subtypes, predictive signatures, and candidate targets.

J Gastrointest Oncol. 2025-6-30

[9]
Viral-Track integrated single-cell RNA-sequencing reveals HBV lymphotropism and immunosuppressive microenvironment in HBV-associated hepatocellular carcinoma.

Commun Biol. 2025-7-9

[10]
VETC predicting model based on CE-CT can predict prognosis and assisting treatment plan for solitary HCC: better together with radiomics.

BMC Cancer. 2025-7-1

本文引用的文献

[1]
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