Versican Secreted by Cancer-Associated Fibroblasts is a Poor Prognostic Factor in Hepatocellular Carcinoma

Prediction of CAF-related genes in immunotherapy and drug sensitivity in hepatocellular carcinoma: a multi-database analysis

This study aims to identify the cancer-associated fibroblasts (CAF)-related genes that can affect immunotherapy and drug sensitivity in hepatocellular carcinoma (HCC). Expression data and survival data associated with HCC were obtained in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Weighted correlation network analysis (WGCNA) analysis was performed to obtain CAF-related genes. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for regression analysis and risk models. Subsequently, Gene Set Enrichment Analysis (GSEA) analysis, Gene Set Enrichment Analysis (ssGSEA) analysis, Tumor Immune Dysfunction and Exclusion (TIDE) analysis and drug sensitivity analysis were performed on the risk models. Survival analysis of CAF scores showed that the survival rate was lower in samples with high CAF scores than those with low scores. However, this difference was not significant, suggesting CAF may not directly influence the prognosis of HCC patients. Further screening of CAF-related genes yielded 33 CAF-related genes. Seven risk models constructed based on CDR2L, SPRED1, PFKP, ENG, KLF2, FSCN1 and VCAN, showed significant differences in immunotherapy and partial drug sensitivity in HCC. Seven CAF-related genes may have important roles in immunotherapy, drug sensitivity and prognostic survival in HCC patients.

Cancer-associated fibroblasts in neoadjuvant setting for solid cancers

Therapeutic approaches for cancer have become increasingly diverse in recent times. A comprehensive understanding of the tumor microenvironment (TME) holds great potential for enhancing the precision of tumor therapies. Neoadjuvant therapy offers the possibility of alleviating patient symptoms and improving overall quality of life. Additionally, it may facilitate the reduction of inoperable tumors and prevent potential preoperative micrometastases. Within the TME, cancer-associated fibroblasts (CAFs) play a prominent role as they generate various elements that contribute to tumor progression. Particularly, extracellular matrix (ECM) produced by CAFs prevents immune cell infiltration into the TME, hampers drug penetration, and diminishes therapeutic efficacy. Therefore, this review provides a summary of the heterogeneity and interactions of CAFs within the TME, with a specific focus on the influence of neoadjuvant therapy on the microenvironment, particularly CAFs. Finally, we propose several potential and promising therapeutic strategies targeting CAFs, which may efficiently eliminate CAFs to decrease stroma density and impair their functions.

The role of noncoding RNAs in the tumor microenvironment of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the leading fatal malignancy worldwide. The tumor microenvironment (TME) can affect the survival, proliferation, migration, and even dormancy of cancer cells. Hypoxia is an important component of the TME, and hypoxia-inducible factor-1α (HIF-1α) is the most important transcriptional regulator. Noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), comprise a large part of the human transcriptome and play an important role in regulating the tumorigenesis of HCC. This review discusses the role of ncRNAs in hepatocarcinogenesis, epithelial-mesenchymal transition (EMT), and angiogenesis in a hypoxic microenvironment, as well as the interactions between ncRNAs and key components of the TME. It further discusses their use as biomarkers and the potential clinical value of drugs, as well as the challenges faced in the future.

Cancer-Associated Fibroblasts in Gastrointestinal Cancers: Unveiling Their Dynamic Roles in the Tumor Microenvironment

Gastrointestinal cancers are highly aggressive malignancies with significant mortality rates. Recent research emphasizes the critical role of the tumor microenvironment (TME) in these cancers, which includes cancer-associated fibroblasts (CAFs), a key component of the TME that have diverse origins, including fibroblasts, mesenchymal stem cells, and endothelial cells. Several markers, such as α-SMA and FAP, have been identified to label CAFs, and some specific markers may serve as potential therapeutic targets. In this review article, we summarize the literature on the multifaceted role of CAFs in tumor progression, including their effects on angiogenesis, immune suppression, invasion, and metastasis. In addition, we highlight the use of single-cell transcriptomics to understand CAF heterogeneity and their interactions within the TME. Moreover, we discuss the dynamic interplay between CAFs and the immune system, which contributes to immunosuppression in the TME, and the potential for CAF-targeted therapies and combination approaches with immunotherapy to improve cancer treatment outcomes.

Predicting Survival Signature of Bladder Cancer Related to Cancer-Associated Fibroblast (CAF) Constructed by Intersecting Genes in TCGA and GEO

Bladder cancer was one of the most common carcinomas around the world. However, the mechanism of the disease still remained to be investigated. We expected to establish a prognostic survival model with 9 prognostic genes to predict overall survival (OS) in patients of bladder cancer. The gene expression data of bladder cancer were obtained from TCGA and GEO datasets. TCGA and GEO datasets were used for screening prognostic genes along with developing and validating a 9-gene prognostic survival model by method of weighted gene co-expression network analysis (WGCNA) and LASSO with Cox regression. The relative analysis of evaluate tumor burden mutation (TBM), GO, KEGG, chemotherapy drug and functional pathway were also performed based on CAF-related mRNAs. 151 Overlapping CAF-related genes were distinguished after intersecting differentially expressed genes from 945 genes in TCGA and 491 genes in GEO dataset. 9 Prognostic genes (MSRB2, AGMAT, KLF6, DDAH2, GADD45B, SERPINE2, STMN3, TEAD2, and COMP) were used for construction of prognostic model after LASSO with Cox regression. Receiver operating characteristic (ROC) curves showed a good survival prediction by this model. Functional analysis indicated chemokine, cytokine, ECM interaction, oxidative stress and apoptosis were highly appeared. Potential drugs targeted different CAF-related genes like vemurafenib, irofulven, ghiotepa, and idarubicin were found as well. We constructed a novel 9 CAF-related mRNAs prognostic model and explored the gene expression and potential functional information of related genes, which might be worthy of clinical application. In addition, potential chemotherapy drugs could provide useful insights into the potential clinical treatment of bladder cancer.

TGF-β1 dominates stromal fibroblast-mediated EMT via the FAP/VCAN axis in bladder cancer cells

BACKGROUND

Bladder cancer is one of the most common malignant tumors of the urinary system and is associated with a poor prognosis once invasion and distant metastases occur. Epithelial-mesenchymal transition (EMT) drives metastasis and invasion in bladder cancer. Transforming growth factor β1 (TGF-β1) and stromal fibroblasts, especially cancer-associated fibroblasts (CAFs), are positive regulators of EMT in bladder cancer. However, it remains unclear how TGF-β1 mediates crosstalk between bladder cancer cells and CAFs and how it induces stromal fibroblast-mediated EMT in bladder cancer. We aimed to investigate the mechanism of TGF-β1 regulation of stromal fibroblast-mediated EMT in bladder cancer cells.

METHODS

Primary CAFs with high expression of fibroblast activation protein (FAP) were isolated from bladder cancer tissue samples. Subsequently, different conditioned media were used to stimulate the bladder cancer cell line T24 in a co-culture system. Gene set enrichment analysis, a human cytokine antibody array, and cytological assays were performed to investigate the mechanism of TGF-β1 regulation of stromal fibroblast-mediated EMT in bladder cancer cells.

RESULTS

Among the TGF-β family, TGF-β1 was the most highly expressed factor in bladder cancer tissue and primary stromal fibroblast supernatant. In the tumor microenvironment, TGF-β1 was mainly derived from stromal fibroblasts, especially CAFs. In stimulated bladder cells, stromal fibroblast-derived TGF-β1 promoted bladder cancer cell migration, invasion, and EMT. Furthermore, TGF-β1 promoted the activation of stromal fibroblasts, inducing CAF-like features, by upregulating FAP in primary normal fibroblasts and a normal fibroblast cell line. Stromal fibroblast-mediated EMT was induced in bladder cancer cells by TGF-β1/FAP. Versican (VCAN), a downstream molecule of FAP, plays an essential role in TGF-β1/FAP axis-induced EMT in bladder cancer cells. VCAN may also function through the PI3K/AKT1 signaling pathway.

CONCLUSIONS

TGF-β1 is a critical mediator of crosstalk between stromal fibroblasts and bladder cancer cells. We revealed a new mechanism whereby TGF-β1 dominated stromal fibroblast-mediated EMT of bladder cancer cells via the FAP/VCAN axis and identified potential biomarkers (FAP, VCAN, N-cadherin, and Vimentin) of bladder cancer. These results enhance our understanding of bladder cancer invasion and metastasis and provide potential strategies for diagnosis, treatment, and prognosis.

Cancer-associated fibroblasts and its derived exosomes: a new perspective for reshaping the tumor microenvironment

Cancer-associated fibroblasts (CAFs) are the most abundant stromal cells within the tumor microenvironment (TME). They extensively communicate with the other cells. Exosome-packed bioactive molecules derived from CAFs can reshape the TME by interacting with other cells and the extracellular matrix, which adds a new perspective for their clinical application in tumor targeted therapy. An in-depth understanding of the biological characteristics of CAF-derived exosomes (CDEs) is critical for depicting the detailed landscape of the TME and developing tailored therapeutic strategies for cancer treatment. In this review, we have summarized the functional roles of CAFs in the TME, particularly focusing on the extensive communication mediated by CDEs that contain biological molecules such as miRNAs, proteins, metabolites, and other components. In addition, we have also highlighted the prospects for diagnostic and therapeutic applications based on CDEs, which could guide the future development of exosome-targeted anti-tumor drugs.

Cancer-Associated Fibroblasts in Hepatocellular Carcinoma and Cholangiocarcinoma

Primary liver cancer (PLC) includes hepatocellular carcinoma and intrahepatic cholangiocarcinoma and is the sixth most common cancer worldwide with poor prognosis. PLC is characterized by an abundant stromal reaction in which cancer-associated fibroblasts (CAFs) are one of the major stromal components. Solid evidence has demonstrated the crucial role of CAFs in tumor progression, and CAF abundance is often correlated with poor clinical outcomes. Although CAFs are regarded as an attractive and promising target for PLC treatment, a poor understanding of CAF origins and heterogeneity and a lack of specific CAF markers are the major hurdles to efficient CAF-specific therapy. In this review, we examine recent advances in the understanding of CAF diversity in the context of biomarkers, subtypes, and functions in PLC. The regulatory roles of CAFs in extracellular matrix remodeling, metastasis, cancer stemness, and therapeutic resistance are summarized. With an increasing link between CAF abundance and reduced antitumor immune responses, we provide updated knowledge on the crosstalk between CAFs and immune cells within the tumor microenvironment, which leads to immune resistance. In addition, we present current CAF-targeted therapies and describe some future perspectives. A better understanding of CAF biology will shed light on a novel therapeutic strategy against PLC.

Characterization of cancer-related fibroblasts (CAF) in hepatocellular carcinoma and construction of CAF-based risk signature based on single-cell RNA-seq and bulk RNA-seq data

Background

Cancer-associated fibroblasts (CAFs) are involved in tumor growth, angiogenesis, metastasis, and resistance to therapy. We sought to explore the CAFs characteristics in hepatocellular carcinoma (HCC) and establish a CAF-based risk signature for predicting the prognosis of HCC patients.

Methods

The signal-cell RNA sequencing (scRNA-seq) data was obtained from the GEO database. Bulk RNA-seq data and microarray data of HCC were obtained from the TCGA and GEO databases respectively. Seurat R package was applied to process scRNA-seq data and identify CAF clusters according to the CAF markers. Differential expression analysis was performed to screen differentially expressed genes (DEGs) between normal and tumor samples in TCGA dataset. Then Pearson correlation analysis was used to determine the DEGs associated with CAF clusters, followed by the univariate Cox regression analysis to identify CAF-related prognostic genes. Lasso regression was implemented to construct a risk signature based on CAF-related prognostic genes. Finally, a nomogram model based on the risk signature and clinicopathological characteristics was developed.

Results

Based on scRNA-seq data, we identified 4 CAF clusters in HCC, 3 of which were associated with prognosis in HCC. A total of 423 genes were identified from 2811 DEGs to be significantly correlated with CAF clusters, and were narrowed down to generate a risk signature with 6 genes. These six genes were primarily connected with 39 pathways, such as angiogenesis, apoptosis, and hypoxia. Meanwhile, the risk signature was significantly associated with stromal and immune scores, as well as some immune cells. Multivariate analysis revealed that risk signature was an independent prognostic factor for HCC, and its value in predicting immunotherapeutic outcomes was confirmed. A novel nomogram integrating the stage and CAF-based risk signature was constructed, which exhibited favorable predictability and reliability in the prognosis prediction of HCC.

Conclusion

CAF-based risk signatures can effectively predict the prognosis of HCC, and comprehensive characterization of the CAF signature of HCC may help to interpret the response of HCC to immunotherapy and provide new strategies for cancer treatment.