ArticleScientific reports2024
RNA-seq and bulk RNA-seq data analysis of cancer-related fibroblasts (CAF) in LUAD to construct a CAF-based risk signature.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- ABCC2 as a novel therapeutic target in lung adenocarcinoma: a machine learning-driven discovery linking ammonia metabolism to prognosis and drug resistance.Journal of translational medicine · 2026Article
- Radiation-Induced Alterations in Cancer-Associated Fibroblasts: Drivers of Tumor Radioresistance and Therapeutic Targets.Biomolecules · 2026Review
- Integrated single-cell and bulk RNA sequencing reveals novel biomarkers of invasive adenocarcinoma subtypes in lung adenocarcinoma.Translational cancer research · 2026Article
- The evolving role of OMICS in gastrointestinal tumor biology and clinical practice.Molecular cancer · 2026Review
- Identification of succinylation-related genes in bladder cancer: integration of single-cell and transcriptomic data.Frontiers in immunology · 2026Article
- Fibrinogen beta chain as a prognostic biomarker and therapeutic target in tobacco-associated lung adenocarcinoma.Discover oncology · 2025Article
- Comprehensive analysis of a machine learning prognostic model for the interaction between mitochondrial function and lactylation in lung adenocarcinoma.Discover oncology · 2025Article
- Single-cell RNA sequencing technology was employed to construct a risk prediction model for genes associated with pyroptosis and ferroptosis in lung adenocarcinoma.Respiratory research · 2025Article
- Identification of a fibroblast-derived gene signature reveals prognostic and therapeutic insights in pancreatic cancer.Clinical and experimental medicine · 2025Article
- Cancer-Associated Fibroblasts as the "Architect" of the Lung Cancer Immune Microenvironment: Multidimensional Roles and Synergistic Regulation with Radiotherapy.International journal of molecular sciences · 2025Review
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4 authors.
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Abstract
Angiogenesis, metastasis, and resistance to therapy are all facilitated by cancer-associated fibroblasts (CAFs). A CAF-based risk signature can be used to predict patients' prognoses for Lung adenocarcinoma (LUAD) based on CAF characteristics. The Gene Expression Omnibus (GEO) database was used to gather signal-cell RNA sequencing (scRNA-seq) data for this investigation. The GEO and TCGA databases were used to gather bulk RNA-seq and microarray data for LUAD. The scRNA-seq data were analyzed using the Seurat R program based on the CAF markers. Our goal was to use differential expression analysis to discover differentially expressed genes (DEGs) across normal and tumor samples in the TCGA dataset. Pearson correlation analysis was utilized to discover prognostic genes related with CAF, followed by univariate Cox regression analysis. Using Lasso regression, a risk signature based on CAF-related prognostic genes was created. A nomogram model was created based on the clinical and pathological aspects. 5 CAF clusters were identified in LUAD, 4 of which were associated with prognosis. From 2811 DEGs, 1002 genes were found to be significantly correlated with CAF clusters, which led to the creation of a risk signature with 8 genes. These 8 genes were primarily connected with 41 pathways, such as antigen paocessing and presentation, apoptosis, and cell cycle. 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 LUAD, 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 LUAD. CAF-based risk signatures can be effective in predicting the prognosis of LUAD, and they may provide new strategies for cancer treatments by interpreting the response of LUAD to immunotherapy.
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