Abstract：
BACKGROUND: 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).
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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.
摘要：
背景：癌症相关成纤维细胞（CAFs）是前列腺基质细胞的主要组成部分之一，在肿瘤的发展和治疗抵抗中起着至关重要的作用。本研究旨在建立CAFs相关microRNAs(miRNAs)模型,以评估预后差异,肿瘤微环境，通过整合单细胞RNA测序（scRNA-seq）和批量RNA测序（buRNA-seq）的数据来筛选抗癌药物。
方法：原发性前列腺癌（PCa）的scRNA-seq和buRNA-seq数据从基因表达Omnibus和癌症基因组图谱数据库下载。统计方法包括最小绝对收缩和选择算子(Lasso)，Lasso被罚了,随机森林,随机森林组合，进行和支持向量机(SVM)以选择中枢miRNA。使用基因集富集分析和CIBERSORT算法进行浸润性免疫细胞的途径分析和评估。通过实时定量PCR验证CAFs相关miRNAs在成纤维细胞中的表达。细胞计数套件8(CCK8),伤口愈合,克隆形成,和细胞迁移试验用于探索细胞增殖，增长,和体外迁移。建立小鼠异种移植模型以研究体内CAF对肿瘤生长的影响。
结果：通过34例PCa患者的单细胞转录组学分析，鉴定了89个CAF相关的mRNA。基于9个CAFs相关miRNA（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）用于预测生化复发（BCR）。我们通过两种预测方法确定NVP-TAE684可能是治疗CAF的最佳靶向治疗药物。在CAFs中下调hsa-miR-106b-5p显著抑制细胞增殖，迁移,和体外集落形成。使用异种移植模型的体内研究进一步证实hsa-miR-106b-5p下调显著降低肿瘤生长。
结论：我们的发现进行了综合生物信息学分析，以开发CAFs相关的miRNA模型，该模型为前列腺腺癌患者的个体化和精确治疗提供了预后见解。miR-106b-5p在CAFs中的下调显著抑制肿瘤生长，提示癌症治疗的潜在治疗靶点。
方法：原发性前列腺癌（PCa）的scRNA-seq和buRNA-seq数据从基因表达Omnibus和癌症基因组图谱数据库下载。统计方法包括最小绝对收缩和选择算子(Lasso)，Lasso被罚了,随机森林,随机森林组合，进行和支持向量机(SVM)以选择中枢miRNA。使用基因集富集分析和CIBERSORT算法进行浸润性免疫细胞的途径分析和评估。通过实时定量PCR验证CAFs相关miRNAs在成纤维细胞中的表达。细胞计数套件8(CCK8),伤口愈合,克隆形成,和细胞迁移试验用于探索细胞增殖，增长,和体外迁移。建立小鼠异种移植模型以研究体内CAF对肿瘤生长的影响。
结果：通过34例PCa患者的单细胞转录组学分析，鉴定了89个CAF相关的mRNA。基于9个CAFs相关miRNA（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）用于预测生化复发（BCR）。我们通过两种预测方法确定NVP-TAE684可能是治疗CAF的最佳靶向治疗药物。在CAFs中下调hsa-miR-106b-5p显著抑制细胞增殖，迁移,和体外集落形成。使用异种移植模型的体内研究进一步证实hsa-miR-106b-5p下调显著降低肿瘤生长。
结论：我们的发现进行了综合生物信息学分析，以开发CAFs相关的miRNA模型，该模型为前列腺腺癌患者的个体化和精确治疗提供了预后见解。miR-106b-5p在CAFs中的下调显著抑制肿瘤生长，提示癌症治疗的潜在治疗靶点。
