ArticleJournal of translational medicine2024
Integrating single-cell and bulk RNA sequencing data unveils antigen presentation and process-related CAFS and establishes a predictive signature in prostate cancer.
Article in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.
- Integration of single-cell and bulk RNA-sequencing data reveals the prognostic potential of epithelial gene markers for prostate cancer.Molecular oncology · 2025Pooled it
- Single-cell and spatial RNA sequencing in prostate cancer.Nature reviews. Urology · 2026Review
- Single-cell and spatial transcriptomic profiling identifies a fibroblast-like endothelial state and the MDK-NCL signaling axis in prostate cancer microenvironment remodeling.Translational oncology · 2026Article
- Heterogeneity of cancer-associated fibroblast subtypes in the prostate cancer microenvironment and their clinical implications: prognostic model construction and therapeutic target exploration based on bioinformatics analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Decoding chromatin regulator-LAIR1Clinical and experimental medicine · 2026Article
- Unfolding Immune Dysregulation in COPD: Identification of a Three-Gene Signature and Functional Validation ofInternational journal of molecular sciences · 2026Article
- Probing uric acid-related prognostic genes and their molecular mechanisms in prostate cancer based on transcriptomic data.Discover oncology · 2026Article
- NGF-mediated tumor-stroma crosstalk promotes prostate cancer aggressiveness.Journal of translational medicine · 2026Article
- Single-cell mapping of cholesterol metabolism reveals FDPS as a therapeutic vulnerability in hepatocellular carcinoma.Cellular oncology (Dordrecht, Netherlands) · 2026Article
- Prostate Cancer-Associated Fibroblasts: A Review on CAF Functions, Heterogeneity, Resistance Mechanisms, and Future in a Chip.International journal of molecular sciences · 2026Review
- Antibody screening for tumor and immune hotspot targets: The frontier of new methods and technologies.Journal of pharmaceutical analysis · 2026Review
- The molecular underpinnings of the immune landscape in prostate cancer: decoding a "cold" tumor.Frontiers in oncology · 2026Review
- Machine learning-based identification of hub genes and prognostic biomarkers in prostate cancer.Frontiers in genetics · 2026Article
- Decoding vascular calcification-neutrophil signature in pathogenesis of chronic IgA nephropathy: evidence from artificial intelligence-driven multi-omics andFrontiers in physiology · 2026Article
- The Role of Distinct Cancer-Associated Fibroblast Subtypes in Prostate Cancer Immunotherapy.International journal of biological sciences · 2026Review
- JGR-NMF: joint graph-regularized non-negative matrix factorization for spatial domain identification.PeerJ · 2026Article
- Targeting Cancer-Associated Fibroblasts in Prostate Cancer: Recent Advances and Therapeutic Opportunities.Cancers · 2025Review
- Identification of hub genes contributing to acute eczema using transcriptome sequencing and machine-learning approaches.BMC medical genomics · 2025Article
- A novel six-biomarker panel identified from male breast cancer-associated fibroblasts demonstrates prognostic power for prostate tumors.Journal of translational medicine · 2025Article
- Research Advances in Cancer-Associated Fibroblasts in Prostate Cancer Progression.Biomolecules · 2025Review
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7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundCancer-associated fibroblasts (CAFs) are heterogeneous and can influence the progression of prostate cancer in multiple ways; however, their capacity to present and process antigens in PRAD has not been investigated. In this study, antigen presentation and process-related CAFs (APPCAFs) were identified using bioinformatics, and the clinical implications of APPCAF-related signatures in PRAD were investigated.
methodsSMART technology was used to sequence the transcriptome of primary CAFs isolated from patients undergoing different treatments. Differential expression gene (DEG) screening was conducted. A CD4 + T-cell early activation assay was used to assess the activation degree of CD4 + T cells. The datasets of PRAD were obtained from The Cancer Genome Atlas (TCGA) database and NCBI Gene Expression Omnibus (GEO), and the list of 431 antigen presentation and process-related genes was obtained from the InnateDB database. Subsequently, APP-related CAFs were identified by nonnegative matrix factorization (NMF) based on a single-cell seq (scRNA) matrix. GSVA functional enrichment analyses were performed to depict the biological functions. A risk signature based on APPCAF-related genes (APPCAFRS) was developed by least absolute shrinkage and selection operator (LASSO) regression analysis, and the independence of the risk score as a prognostic factor was evaluated by univariate and multivariate Cox regression analyses. Furthermore, a biochemical recurrence-free survival (BCRFS)-related nomogram was established, and immune-related characteristics were assessed using the ssGSEA function. The immune treatment response in PRAD was further analyzed by the Tumor Immune Dysfunction and Exclusion (TIDE) tool. The expression levels of hub genes in APPCAFRS were verified in cell models.
resultsThere were 134 upregulated and 147 downregulated genes, totaling 281 differentially expressed genes among the primary CAFs. The functions and pathways of 147 downregulated DEGs were significantly enriched in antigen processing and presentation processes, MHC class II protein complex and transport vesicle, MHC class II protein complex binding, and intestinal immune network for IgA production. Androgen withdrawal diminished the activation effect of CAFs on T cells. NMF clustering of CAFs was performed by APPRGs, and pseudotime analysis yielded the antigen presentation and process-related CAF subtype CTSK + MRC2 + CAF-C1. CTSK + MRC2 + CAF-C1 cells exhibited ligand‒receptor connections with epithelial cells and T cells. Additionally, we found a strong association between CTSK + MRC2 + CAF-C1 cells and inflammatory CAFs. Through differential gene expression analysis of the CTSK + MRC2 + CAF-C1 and NoneAPP-CAF-C2 subgroups, 55 significant DEGs were identified, namely, APPCAFRGs. Based on the expression profiles of APPCAFRGs, we divided the TCGA-PRAD cohort into two clusters using NMF consistent cluster analysis, with the genetic coefficient serving as the evaluation index. Four APPCAFRGs, THBS2, DPT, COL5A1, and MARCKS, were used to develop a prognostic signature capable of predicting BCR occurrence in PRAD patients. Subsequently, a nomogram with stability and accuracy in predicting BCR was constructed based on Gleason grade (p = n.s.), PSA (p < 0.001), T stage (p < 0.05), and risk score (p < 0.01). The analysis of immune infiltration showed a positive correlation between the abundance of resting memory CD4 + T cells, M1 macrophages, resting dendritic cells, and the risk score. In addition, the mRNA expression levels of THBS2, DPT, COL5A1, and MARCKS in the cell models were consistent with the results of the bioinformatics analysis.
conclusionsAPPCAFRS based on four potential APPCAFRGs was developed, and their interaction with the immune microenvironment may play a crucial role in the progression to castration resistance of PRAD. This novel approach provides valuable insights into the pathogenesis of PRAD and offers unexplored targets for future research.
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