Dataset Information

Single-cell tumor heterogeneity landscape of hepatocellular carcinoma: unraveling the pro-metastatic subtype and its interaction loop with fibroblasts.

ABSTRACT:

Background

Tumor heterogeneity presents a formidable challenge in understanding the mechanisms driving tumor progression and metastasis. The heterogeneity of hepatocellular carcinoma (HCC) in cellular level is not clear.

Methods

Integration analysis of single-cell RNA sequencing data and spatial transcriptomics data was performed. Multiple methods were applied to investigate the subtype of HCC tumor cells. The functional characteristics, translation factors, clinical implications and microenvironment associations of different subtypes of tumor cells were analyzed. The interaction of subtype and fibroblasts were analyzed.

Results

We established a heterogeneity landscape of HCC malignant cells by integrated 52 single-cell RNA sequencing data and 5 spatial transcriptomics data. We identified three subtypes in tumor cells, including ARG1⁺ metabolism subtype (Metab-subtype), TOP2A⁺ proliferation phenotype (Prol-phenotype), and S100A6⁺ pro-metastatic subtype (EMT-subtype). Enrichment analysis found that the three subtypes harbored different features, that is metabolism, proliferating, and epithelial-mesenchymal transition. Trajectory analysis revealed that both Metab-subtype and EMT-subtype originated from the Prol-phenotype. Translation factor analysis found that EMT-subtype showed exclusive activation of SMAD3 and TGF-β signaling pathway. HCC dominated by EMT-subtype cells harbored an unfavorable prognosis and a deserted microenvironment. We uncovered a positive loop between tumor cells and fibroblasts mediated by SPP1-CD44 and CCN2/TGF-β-TGFBR1 interaction pairs. Inhibiting CCN2 disrupted the loop, mitigated the transformation to EMT-subtype, and suppressed metastasis.

Conclusion

By establishing a heterogeneity landscape of malignant cells, we identified a three-subtype classification in HCC. Among them, S100A6⁺ tumor cells play a crucial role in metastasis. Targeting the feedback loop between tumor cells and fibroblasts is a promising anti-metastatic strategy.

SUBMITTER: Guo DZ

PROVIDER: S-EPMC11295380 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Single-cell tumor heterogeneity landscape of hepatocellular carcinoma: unraveling the pro-metastatic subtype and its interaction loop with fibroblasts.

Guo De-Zhen DZ Zhang Xin X Zhang Sen-Quan SQ Zhang Shi-Yu SY Zhang Xiang-Yu XY Yan Jia-Yan JY Dong San-Yuan SY Zhu Kai K Yang Xin-Rong XR Fan Jia J Zhou Jian J Huang Ao A

Molecular cancer 20240802 1

<h4>Background</h4>Tumor heterogeneity presents a formidable challenge in understanding the mechanisms driving tumor progression and metastasis. The heterogeneity of hepatocellular carcinoma (HCC) in cellular level is not clear.<h4>Methods</h4>Integration analysis of single-cell RNA sequencing data and spatial transcriptomics data was performed. Multiple methods were applied to investigate the subtype of HCC tumor cells. The functional characteristics, translation factors, clinical implications ...[more]

PMID: 39095854

Similar Datasets

Project description:BackgroundThe tumour microenvironment consists of a complex and dynamic milieu of cancer cells, including tumour-associated stromal cells (leukocytes, fibroblasts, vascular cells, etc.) and their extracellular products. During invasion and metastasis, cancer cells actively remodel the tumour microenvironment and alterations of microenvironment, particularly cancer-associated fibroblasts (CAFs), can promote tumour progression. However, the underlying mechanisms of the CAF formation and their metastasis-promoting functions remain unclear.MethodsPrimary liver fibroblasts and CAFs were isolated and characterized. CAFs in clinical samples were identified by immunohistochemical staining and the clinical significance of CAFs was also analysed in two independent cohorts. A transwell coculture system was used to confirm the role of HCC cells in CAF recruitment and activation. qRT-PCR, western blotting and ELISA were used to screen paracrine cytokines. The role and mechanism of Egfl7 in CAFs were explored via an in vitro coculture system and an in vivo mouse orthotopic transplantation model.ResultsWe showed that CAFs in hepatocellular carcinoma (HCC) are characterized by the expression of α-SMA and that HCC cells can recruit liver fibroblasts (LFs) and activate them to promote their transformation into CAFs. High α-SMA expression, indicating high CAF infiltration, was correlated with malignant characteristics. It was also an independent risk factor for HCC survival and could predict a poor prognosis in HCC patients. Then, we demonstrated that EGF-like domain multiple 7 (Egfl7) was preferentially secreted by HCC cells, and exhibited high potential to recruit and activate LFs into the CAF phenotype. The ability of Egfl7 to modulate LFs relies upon increased phosphorylation of FAK and AKT via the receptor ανβ3 integrin. Strikingly, CAFs activated by paracrine Egfl7 could further remodel the tumour microenvironment by depositing fibrils and collagen and in turn facilitate HCC cell proliferation, invasion and metastasis.ConclusionOur data highlighted a novel role of Egfl7 in remodelling the tumour microenvironment: it recruits LFs and activates them to promote their transformation into CAFs via the ανβ3 integrin signaling pathway, which further promotes HCC progression and contributes to poor clinical outcomes in HCC patients. Video Abstract.

Project description:The recent surge of next generation sequencing of breast cancer genomes has enabled development of comprehensive catalogues of somatic mutations and expanded the molecular classification of subtypes of breast cancer. However, somatic mutations and gene expression data have not been leveraged and integrated with epigenomic data to unravel the genomic-epigenomic interaction landscape of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC). We performed integrative data analysis combining somatic mutation, epigenomic and gene expression data from The Cancer Genome Atlas (TCGA) to unravel the possible oncogenic interactions between genomic and epigenomic variation in TNBC and non-TNBC. We hypothesized that within breast cancers, there are differences in somatic mutation, DNA methylation and gene expression signatures between TNBC and non-TNBC. We further hypothesized that genomic and epigenomic alterations affect gene regulatory networks and signaling pathways driving the two types of breast cancer. The investigation revealed somatic mutated, epigenomic and gene expression signatures unique to TNBC and non-TNBC and signatures distinguishing the two types of breast cancer. In addition, the investigation revealed molecular networks and signaling pathways enriched for somatic mutations and epigenomic changes unique to each type of breast cancer. The most significant pathways for TNBC were: retinal biosynthesis, BAG2, LXR/RXR, EIF2 and P2Y purigenic receptor signaling pathways. The most significant pathways for non-TNBC were: UVB-induced MAPK, PCP, Apelin endothelial, Endoplasmatic reticulum stress and mechanisms of viral exit from host signaling Pathways. The investigation revealed integrated genomic, epigenomic and gene expression signatures and signing pathways unique to TNBC and non-TNBC, and a gene signature distinguishing the two types of breast cancer. The study demonstrates that integrative analysis of multi-omics data is a powerful approach for unravelling the genomic-epigenomic interaction landscape in TNBC and non-TNBC.

Dataset Information

Single-cell tumor heterogeneity landscape of hepatocellular carcinoma: unraveling the pro-metastatic subtype and its interaction loop with fibroblasts.

Background

Methods

Results

Conclusion

Publications

Single-cell tumor heterogeneity landscape of hepatocellular carcinoma: unraveling the pro-metastatic subtype and its interaction loop with fibroblasts.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets