Single-cell transcriptomics reveals tumor microenvironment remodeling in hepatocellular carcinoma with varying tumor subclonal complexity.

cell-cell communications immune activation intra-tumoral heterogeneity subclonal structure tumor microenvironment

Journal

Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621

Informations de publication

Date de publication:
2024
Historique:
received: 20 07 2024
accepted: 19 08 2024
medline: 13 9 2024
pubmed: 13 9 2024
entrez: 13 9 2024
Statut: epublish

Résumé

The complexity of tumor cell subclonal structure has been extensively investigated in hepatocellular carcinoma. However, the role of subclonal complexity in reshaping the tumor microenvironment (TME) remains poorly understood. We integrated single-cell transcriptome sequencing data from four independent HCC cohorts, involving 30 samples, to decode the associations between tumor subclonal complexity and the TME. We proposed a robust metric to accurately quantify the degree of subclonal complexity for each sample based on discrete copy number variations (CNVs) profiles. We found that tumor cells in the high-complexity group originated from the cell lineage with FGB overexpression and exhibited high levels of transcription factors associated with poor survival. In contrast, tumor cells in low-complexity patients showed activation of more hallmark signaling pathways, more active cell-cell communications within the TME and a higher immune activation status. Additionally, cytokines signaling activity analysis suggested a link between Our study sheds light on the intricate relationship between the complexity of subclonal structure and the TME, offering novel insights into potential therapeutic targets for HCC.

Identifiants

pubmed: 39268081
doi: 10.3389/fgene.2024.1467682
pii: 1467682
pmc: PMC11390501
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1467682

Informations de copyright

Copyright © 2024 Shi, Zhang, Xu and Wang.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Jian Shi (J)

Department of Oncology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Institute of Precision Medicine, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.

Yanru Zhang (Y)

Institute of Precision Medicine, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.

Lixia Xu (L)

Department of Oncology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.

Fang Wang (F)

Institute of Precision Medicine, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.

Classifications MeSH