Fibronectin 1 derived from tumor-associated macrophages and fibroblasts promotes metastasis through the JUN pathway in hepatocellular carcinoma

Zhang, Liwei; Zhang, Cong; Xing, Zhengwei; Lou, Chunyang; Fang, Jianbang; Wang, Zhiwei; Li, Mingxing; He, Hongping; Bai, Hualong

doi:10.1016/j.intimp.2022.109420

Cited by 16 publications

(6 citation statements)

References 25 publications

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“…Among the upregulated genes in CS1 (Additional file 6 : Table S1), SFRP2 and SFRP4 are Wnt-regulator and can modulate the differentiation of cancer-associated fibroblasts (CAFs), which contribute to the progression and metastasis of the tumor [ 41 – 43 ]. And CAFs can drive FN1, COMP to regulate tumor metastasis and stemness in hepatocellular carcinoma [ 44 , 45 ]. For CS2 upregulated gene, ZG16 exhibited a sequential decrease from normal to adenoma, and finally to carcinoma in CRC [ 46 ].…”

Section: Discussionmentioning

confidence: 99%

Multi-omics cluster defines the subtypes of CRC with distinct prognosis and tumor microenvironment

Ma,

Li,

Zhao

et al. 2024

Eur J Med Res

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Background Colorectal cancer (CRC) is a complex malignancy characterized by diverse molecular profiles, clinical outcomes, and limited precision in prognostic markers. Addressing these challenges, this study utilized multi-omics data to define consensus molecular subtypes in CRC and elucidate their association with clinical outcomes and underlying biological processes. Methods Consensus molecular subtypes were obtained by applying ten integrated multi-omics clustering algorithms to analyze TCGA-CRC multi-omics data, including mRNA, lncRNA, miRNA, DNA methylation CpG sites, and somatic mutation data. The association of subtypes with prognoses, enrichment functions, immune status, and genomic alterations were further analyzed. Next, we conducted univariate Cox and Lasso regression analyses to investigate the potential prognostic application of biomarkers associated with multi-omics subtypes derived from weighted gene co-expression network analysis (WGCNA). The function of one of the biomarkers MID2 was validated in CRC cell lines. Results Two CRC subtypes linked to distinct clinical outcomes were identified in TCGA-CRC cohort and validated with three external datasets. The CS1 subtype exhibited a poor prognosis and was characterized by higher tumor-related Hallmark pathway activity and lower metabolism pathway activity. In addition, the CS1 was predicted to have less immunotherapy responder and exhibited more genomic alteration compared to CS2. Then a prognostic model comprising five genes was established, with patients in the high-risk group showing substantial concordance with the CS1 subtype, and those in the low-risk group with the CS2 subtype. The gene MID2, included in the prognostic model, was found to be correlated with epithelial–mesenchymal transition (EMT) pathway and distinct DNA methylation patterns. Knockdown of MID2 in CRC cells resulted in reduced colony formation, migration, and invasion capacities. Conclusion The integrative multi-omics subtypes proposed potential biomarkers for CRC and provided valuable knowledge for precision oncology.

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Section: Discussionmentioning

confidence: 99%

Multi-omics cluster defines the subtypes of CRC with distinct prognosis and tumor microenvironment

Ma,

Li,

Zhao

et al. 2024

Eur J Med Res

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“…EGFR is a member of the ErbB receptor family, known to be involved in CAFs-mediated promotion of tumor invasion and metastasis [ 42 ]. FN1 , encoding fibronectin 1 derived from CAFs, can also promote invasion and metastasis [ 43 ]. COL1A1 , encoding collagen type I alpha 1, has been shown to play a critical role in tumor progression [ 44 ].…”

Section: Resultsmentioning

confidence: 99%

An atlas of cell-type-specific interactome networks across 44 human tumor types

Li,

Liu,

Yang

et al. 2024

Genome Med

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Background Biological processes are controlled by groups of genes acting in concert. Investigating gene–gene interactions within different cell types can help researchers understand the regulatory mechanisms behind human complex diseases, such as tumors. Methods We collected extensive single-cell RNA-seq data from tumors, involving 563 patients with 44 different tumor types. Through our analysis, we identified various cell types in tumors and created an atlas of different immune cell subsets across different tumor types. Using the SCINET method, we reconstructed interactome networks specific to different cell types. Diverse functional data was then integrated to gain biological insights into the networks, including somatic mutation patterns and gene functional annotation. Additionally, genes with prognostic relevance within the networks were also identified. We also examined cell–cell communications to investigate how gene interactions modulate cell–cell interactions. Results We developed a data portal called CellNetdb for researchers to study cell-type-specific interactome networks. Our findings indicate that these networks can be used to identify genes with topological specificity in different cell types. We also found that prognostic genes can deconvolved into cell types through analyzing network connectivity. Additionally, we identified commonalities and differences in cell-type-specific networks across different tumor types. Our results suggest that these networks can be used to prioritize risk genes. Conclusions This study presented CellNetdb, a comprehensive repository featuring an atlas of cell-type-specific interactome networks across 44 human tumor types. The findings underscore the utility of these networks in delineating the intricacies of tumor microenvironments and advancing the understanding of molecular mechanisms underpinning human tumors.

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“…As Peng Z et al reported, fibronectin from fibroblasts promotes tumor growth and angiogenesis through interactions with liver cancer cells [27]. Additionally, a multiomics analysis indicated that FN1 derived from tumor-associated macrophages and fibroblasts facilitates metastasis in hepatocellular carci-Am J Cancer Res 2024;14(2):526-544 noma [28]. MK, a growth factor overexpressed in several human carcinomas [29], plays a crucial role in cell growth, metastasis, migration, and angiogenesis [30].…”

Section: Discussionmentioning

confidence: 99%

Single-cell analysis reveals one cancer-associated fibroblasts subtype linked to metastasis in breast cancer: MXRA5 as a potential novel marker for prognosis

Deng

2024

Am J Cancer Res

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Cancer-associated fibroblasts (CAFs) are prevalent in the tumor microenvironment of breast cancer, comprising a group of cell subpopulations with spatial, phenotypic, and functional heterogeneity. Due to the lack of specific markers for CAF subpopulations, their specific mechanisms in breast cancer remain unclear. We identified eight distinct CAF phenotypes in breast cancer using multiple single-cell RNA sequencing datasets and determined distinct transcription factors (TFs) of CAFs through SCENIC analysis. Our study highlights one CAF subtype in breast cancer, FN1+CAF2, associated with metastasis and macrophage polarization. We observed elevated FN1 expression in the stromal tissue of breast cancer patients. Furthermore, FN1 knockdown in CAFs reduced the migration ability of breast cancer cells. We identified a regulatory gene, MXRA5, in CAF2, which may play crucial roles in breast cancer. Our results indicated upregulated MXRA5 expression in breast cancer tissues and CAFs from patients with lymph node metastasis in the following experiment. Overall, our study reveals that the FN1+CAF2 subtype is associated with metastasis and suggests that MXRA5 may be a novel marker mediating the effects of CAF2 on breast cancer metastasis. This study enriches our understanding of CAF heterogeneity and offers new insights for treating breast cancer metastasis.

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Fibronectin 1 derived from tumor-associated macrophages and fibroblasts promotes metastasis through the JUN pathway in hepatocellular carcinoma

Cited by 16 publications

References 25 publications

Multi-omics cluster defines the subtypes of CRC with distinct prognosis and tumor microenvironment

Multi-omics cluster defines the subtypes of CRC with distinct prognosis and tumor microenvironment

An atlas of cell-type-specific interactome networks across 44 human tumor types

Single-cell analysis reveals one cancer-associated fibroblasts subtype linked to metastasis in breast cancer: MXRA5 as a potential novel marker for prognosis

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