Development of a Cancer-associated Fibroblast Signature for Evaluating Immunotherapy Response and Prognosis of Hepatocellular Carcinoma
- 1Department of Hepatobiliary Surgery, Wuhan No.1 Hospital, Wuhan, 430022, China.
- 2Department of Rehabilitation Medicine, Wuhan No.1 Hospital, Wuhan, 430022, China.
- 3Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
- 4Department of Hepatobiliary Surgery, Hainan Hospital of Chinese PLA General Hospital, Sanya, 572013, China.
- 0Department of Hepatobiliary Surgery, Wuhan No.1 Hospital, Wuhan, 430022, China.
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View abstract on PubMed
Summary
This summary is machine-generated.Cancer-associated fibroblasts (CAFs) are crucial in hepatocellular carcinoma (HCC) development and treatment response. Targeting the CAF tumor microenvironment may improve personalized HCC treatment strategies.
Area Of Science
- Oncology
- Cancer Biology
- Immunology
Background
- Hepatocellular carcinoma (HCC) is often diagnosed at advanced stages, challenging effective treatment.
- Key risk factors include alcohol abuse, non-alcoholic fatty liver disease (NAFLD), and viral hepatitis (B and C).
- Understanding the tumor microenvironment's role is critical for improving HCC patient outcomes.
Purpose Of The Study
- To investigate the role of cancer-associated fibroblasts (CAFs) in hepatocellular carcinoma (HCC) pathogenesis.
- To develop a prognostic model based on CAF-related genes for HCC patients.
- To explore the relationship between the CAF prognostic score (CAFPS) and drug sensitivity.
Main Methods
- Analysis of HCC datasets from TCGA and GEO databases.
- Quantification of tumor microenvironment (TME) components using the ESTIMATE algorithm.
- Weighted gene co-expression network analysis (WGCNA) to identify CAF-associated gene modules.
- Development of a CAF prognostic score (CAFPS) model using Cox regression.
- Gene Ontology (GO) and KEGG pathway analyses.
- Correlation analysis between CAFPS and drug sensitivity using GDSC.
Main Results
- Significant differences in immune, stromal, CAF, and T-cell scores were observed across different HCC TNM stages.
- WGCNA identified lightyellow and greenyellow modules strongly correlated with CAF scores.
- Twelve prognostic CAF-related genes were identified, with high expression linked to lower survival.
- The developed CAFPS model indicated that lower scores correlate with better patient survival.
Conclusions
- Cancer-associated fibroblasts (CAFs) significantly influence HCC pathogenesis and treatment response.
- Targeting the CAF-rich tumor microenvironment presents a potential therapeutic strategy for HCC.
- The CAFPS model may aid in developing personalized treatment approaches for HCC patients.
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