Abstract
Background
Cancer-associated fibroblasts (CAFs) are an essential component of the tumor immune microenvironment that are involved in extracellular matrix (ECM) remodeling. We aim to investigate the characteristics of CAFs in prostate cancer and develop a biochemical recurrence (BCR)-related CAF signature for predicting the prognosis of PCa patients.
Methods
The bulk RNA-seq and relevant clinical information were obtained from the TCGA and GEO databases, respectively. The infiltration scores of CAFs in prostate cancer patients were calculated using the MCP counter and EPIC algorithms. The single-cell RNA sequencing (scRNA-seq) was downloaded from the GEO database. Subsequently, univariate Cox regression analysis was employed to identify prognostic genes associated with CAFs. We identified two subtypes (C1 and C2) of prostate cancer that were associated with CAFs via non-negative matrix factorization (NMF) clustering. In addition, the BCR-related CAF signatures were constructed using Lasso regression analysis. Finally, a nomogram model was established based on the risk score and clinical characteristics of the patients.
Results
Initially, we found that patients with high CAF infiltration scores had shorter biochemical recurrence-free survival (BCRFS) times. Subsequently, CAFs in four pairs of tumors and paracancerous tissues were identified. We discovered 253 significantly differentially expressed genes, of which 13 had prognostic significance. Using NMF clustering, we divided PCa patients into C1 and C2 subgroups, with the C1 subgroup having a worse prognosis and substantially enriched cell cycle, homologous recombination, and mismatch repair pathways. Furthermore, a BCR-related CAFs signature was established. Multivariate COX regression analysis confirmed that the BCR-related CAFs signature was an independent prognostic factor for BCR in PCa. In addition, the nomogram was based on the clinical characteristics and risk scores of the patient and demonstrated high accuracy and reliability for predicting BCR. Lastly, our findings indicate that the risk score may be a useful tool for predicting PCa patients’ sensitivity to immunotherapy and drug treatment.
Conclusion
NMF clustering based on CAF-related genes revealed distinct TME immune characteristics between groups. The BCR-related CAF signature accurately predicted prognosis and immunotherapy response in prostate cancer patients, offering a promising new approach to cancer treatment.
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All the data used to support the conclusions of this study are included in the article. Please contact the corresponding author for data requests.
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This work was supported by the National Natural Science Foundation of China (Grant number: 81870516).
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TL, ZZ, and ZX designed and completed original manuscript writing; XF and YZ implemented data analysis and literature collection; YZ and XS reviewed the manuscript; YR supervised and funded this work. All authors read and approved the final manuscript.
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Figure S1
: Prognosis and expression distribution of 10 BCR-related CAF signature genes. (A) K-M curves for evaluating ASPN, MT1X, ALDH1A1, HOPX, ANGPT1, FXYD6, CCL2, BCAM, GADD45B, and COL1A2 in the TCGA-PRAD cohort. (B) UMAP displayed the distribution of 10 genes in scRNA-seq from prostate cancer patients. (PNG 812 kb)
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Li, T., Zhou, Z., Xie, Z. et al. Identification and validation of cancer-associated fibroblast-related subtypes and the prognosis model of biochemical recurrence in prostate cancer based on single-cell and bulk RNA sequencing. J Cancer Res Clin Oncol 149, 11379–11395 (2023). https://doi.org/10.1007/s00432-023-05011-7
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DOI: https://doi.org/10.1007/s00432-023-05011-7