Department of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730000, Gansu, China; Gansu Province Clinical Research Center for Urinary System Disease, Lanzhou, 730030, Gansu, China.
Comput Biol Med. 2024 Sep;180:108989. doi: 10.1016/j.compbiomed.2024.108989. Epub 2024 Aug 13.
Cancer-associated fibroblasts (CAFs) are one of the major components of prostate stromal cells, which play a crucial part in tumor development and treatment resistance. This study aimed to establish a model of CAFs-related microRNAs (miRNAs) to assess prognostic differences, tumor microenvironments, and screening of anticancer drugs by integrating data from single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (buRNA-seq).
scRNA-seq and buRNA-seq data of primary prostate cancer (PCa) were downloaded from Gene Expression Omnibus and The Cancer Genome Atlas databases. Statistical methods including Least absolute shrinkage and selection operator (Lasso), Lasso penalized, Random Forest, Random Forest Combination, and Support Vector Machine (SVM) were performed to select hub miRNAs. Pathway analyses and assessment of infiltrating immune cells were conducted using Gene Set Enrichment Analysis and the CIBERSORT algorithm. The expression of CAFs-related miRNAs in fibroblast cell lines were validated through quantitative real-time PCR. Cell Counting Kit 8 (CCK8), wound-healing, clone formation, and cell migration assays were used to explore cell proliferation, growth, and migration in vitro. A mouse xenograft model was established to investigate the effect of CAFs on tumor growth in vivo.
Through single-cell transcriptomics analysis in 34 PCa patients, 89 CAFs-related mRNAs were identified. A prognostic model based on 9 CAFs-related miRNAs (hsa-miR-1258, hsa-miR-133b, hsa-miR-222-3p, hsa-miR-145-3p, hsa-miR-493-5p, hsa-miR-96-5p, hsa-miR-15b-5p, hsa-miR-106b-5p, and hsa-miR-191-5p) was established to predict biochemical recurrence (BCR). We have determined through two prediction methods that NVP-TAE684 may be the optimal targeted therapy drug for treating CAFs. Downregulation of hsa-miR-106b-5p in CAFs significantly suppressed cell proliferation, migration, and colony formation in vitro. In vivo studies using a xenograft model further confirmed that hsa-miR-106b-5p downregulation significantly reduced tumor growth.
Our findings conducted an integrated bioinformatic analysis to develop a CAFs-related miRNAs model that provides prognostic insights into individualized and precise treatment for prostate adenocarcinoma patients. Downregulation of miR-106b-5p in CAFs significantly suppressed tumor growth, suggesting a potential therapeutic target for cancer treatment.
癌症相关成纤维细胞(CAFs)是前列腺基质细胞的主要成分之一,在肿瘤发展和治疗耐药性中起着至关重要的作用。本研究旨在通过整合单细胞 RNA 测序(scRNA-seq)和批量 RNA 测序(buRNA-seq)数据,建立 CAFs 相关 microRNAs(miRNAs)模型,以评估预后差异、肿瘤微环境和筛选抗癌药物。
从基因表达综合数据库和癌症基因组图谱数据库中下载原发性前列腺癌(PCa)的 scRNA-seq 和 buRNA-seq 数据。使用最小绝对收缩和选择算子(Lasso)、Lasso 惩罚、随机森林、随机森林组合和支持向量机(SVM)等统计方法筛选关键 miRNAs。通过基因集富集分析和 CIBERSORT 算法进行通路分析和浸润免疫细胞评估。通过定量实时 PCR 验证 CAFs 相关 miRNA 在成纤维细胞系中的表达。通过细胞计数试剂盒 8(CCK8)、划痕愈合、克隆形成和细胞迁移实验研究体外细胞增殖、生长和迁移。建立小鼠异种移植模型以研究 CAFs 对体内肿瘤生长的影响。
通过对 34 名 PCa 患者的单细胞转录组分析,鉴定出 89 个 CAFs 相关 mRNAs。基于 9 个 CAFs 相关 miRNAs(hsa-miR-1258、hsa-miR-133b、hsa-miR-222-3p、hsa-miR-145-3p、hsa-miR-493-5p、hsa-miR-96-5p、hsa-miR-15b-5p、hsa-miR-106b-5p 和 hsa-miR-191-5p)建立了预测生化复发(BCR)的预后模型。通过两种预测方法确定,NVP-TAE684 可能是治疗 CAFs 的最佳靶向治疗药物。CAFs 中 hsa-miR-106b-5p 的下调显著抑制了体外细胞增殖、迁移和集落形成。异种移植模型的体内研究进一步证实,hsa-miR-106b-5p 的下调显著降低了肿瘤生长。
本研究通过整合生物信息学分析,建立了 CAFs 相关 miRNAs 模型,为前列腺腺癌患者的个体化和精准治疗提供了预后见解。CAFs 中 miR-106b-5p 的下调显著抑制肿瘤生长,提示其可能成为癌症治疗的潜在治疗靶点。