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Background <p>Cancer-associated fibroblasts (CAFs) are critical components of the tumor microenvironment (TME) and have important roles in carcinogenesis and metastasis by facilitating cancer cell proliferation, angiogenesis, extracellular matrix (ECM) remodeling, and drug resistance. The purpose of this study is to extensively describe CAFs in esophageal cancer (ESCA) and develop a CAF-based prognostic risk score to predict clinical outcomes in patients with ESCA.</p> Methods <p>Data for single-cell RNA sequencing (scRNA-seq) were collected from the GEO database. The GEO and TCGA databases provided the bulk RNA-seq data and microarray data for esophageal squamous cell carcinoma (ESCC), respectively. The Seurat R program was used to identify CAF clusters from scRNA-seq data. Univariate Cox regression analysis was then used to identify prognosis-related genes linked to CAFs. Using 65 machine learning algorithms, a risk signature was created using CAF-related prognosis genes. We investigated the relationships between the CAF-related gene risk score and clinical features, mutation landscape, immunotherapy response, and medication sensitivity.</p> Results <p>Using scRNA-seq analysis in ESCC, 4856 genes associated with CAF clusters were identified, 14 of which were selected to construct a prognostic risk signature. Functional validation revealed that overexpression of the regulator of G-protein signaling 16-nuclear factor (RGS16) in CAFs co-cultured with the ESCC cell line KYSE520 significantly increased cancer cell proliferation, invasion, and migration. The secreted midkine (MDK) coupled to its receptor syndecan1 (SDC1) on ESCC cells, further helping their malignant tendencies.</p> Conclusions <p>Comprehensive assessment of CAF heterogeneity in ESCC sheds light into the mechanisms of immunotherapy resistance and suggests prospective options for creating novel treatment therapies. Furthermore, we demonstrate that RGS16+ CAFs promote ESCC progression through the nuclear factor kappa B(NF-κB)-MDK-SDC1 axis, highlighting their crucial involvement in tumor-stromal interaction. These findings emphasize the therapeutic potential of targeting RGS16+ CAFs, which presents a promising method for disrupting the tumor-promoting microenvironment and improving clinical outcomes in ESCC patients.</p> Clinical trial number <p>Not applicable.</p>

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RGS16-driven cancer-associated fibroblasts promote esophageal squamous cell carcinoma progression via the MDK-SDC1 axis-mediated intercellular crosstalk

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月15日

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  • Di Wu,
  • Mingzhi Cao,
  • Changgang Yang,
  • Wanshun Li,
  • Deyu Zhang,
  • Shihua Yao,
  • Hong Yu,
  • Gengxi Jiang

摘要

Background

Cancer-associated fibroblasts (CAFs) are critical components of the tumor microenvironment (TME) and have important roles in carcinogenesis and metastasis by facilitating cancer cell proliferation, angiogenesis, extracellular matrix (ECM) remodeling, and drug resistance. The purpose of this study is to extensively describe CAFs in esophageal cancer (ESCA) and develop a CAF-based prognostic risk score to predict clinical outcomes in patients with ESCA.

Methods

Data for single-cell RNA sequencing (scRNA-seq) were collected from the GEO database. The GEO and TCGA databases provided the bulk RNA-seq data and microarray data for esophageal squamous cell carcinoma (ESCC), respectively. The Seurat R program was used to identify CAF clusters from scRNA-seq data. Univariate Cox regression analysis was then used to identify prognosis-related genes linked to CAFs. Using 65 machine learning algorithms, a risk signature was created using CAF-related prognosis genes. We investigated the relationships between the CAF-related gene risk score and clinical features, mutation landscape, immunotherapy response, and medication sensitivity.

Results

Using scRNA-seq analysis in ESCC, 4856 genes associated with CAF clusters were identified, 14 of which were selected to construct a prognostic risk signature. Functional validation revealed that overexpression of the regulator of G-protein signaling 16-nuclear factor (RGS16) in CAFs co-cultured with the ESCC cell line KYSE520 significantly increased cancer cell proliferation, invasion, and migration. The secreted midkine (MDK) coupled to its receptor syndecan1 (SDC1) on ESCC cells, further helping their malignant tendencies.

Conclusions

Comprehensive assessment of CAF heterogeneity in ESCC sheds light into the mechanisms of immunotherapy resistance and suggests prospective options for creating novel treatment therapies. Furthermore, we demonstrate that RGS16+ CAFs promote ESCC progression through the nuclear factor kappa B(NF-κB)-MDK-SDC1 axis, highlighting their crucial involvement in tumor-stromal interaction. These findings emphasize the therapeutic potential of targeting RGS16+ CAFs, which presents a promising method for disrupting the tumor-promoting microenvironment and improving clinical outcomes in ESCC patients.

Clinical trial number

Not applicable.