Coelho Karoline Brito Caetano Andrade, Wosniaki Denise Kusma, Pereira Jonatas Luiz, Luz Murilo, Albrecht Letusa, Nardin Jeanine Marie, Aoki Mateus Nobrega, Reis Leonardo O, Dos Reis Rodolfo Borges, Zanette Dalila Lucíola
Uro-Oncology Laboratory, Surgery and Anatomy Department, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirão Preto 14090-000, SP, Brazil.
Laboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba 81350-010, PR, Brazil.
Biology (Basel). 2025 May 6;14(5):505. doi: 10.3390/biology14050505.
This study aimed to identify the cytokine expression profile in prostate cancer (PCa) patients compared to healthy individuals. Plasma samples from 75 PCa patients and 14 healthy controls were analyzed using Multiplex ELISA (Luminex) to measure the expression levels of 12 cytokines: IL-4, IL-5, IL-6, IL-10, IL-1β, IL-17A, IL-12p70, MCP-1/CCL2, MIP-1α/CCL3, MIP-1β/CCL4, TNF-α, and IFN-γ. Differences in cytokine expression levels were analyzed using the Mann-Whitney test, Wilcoxon's rank-sum test, Spearman's rank correlation, and K-means Clustering unsupervised machine learning to validate cytokine expression patterns. In PCa patients, MIP-1α/CCL3, MIP-1β/CCL4, IFN-γ, and interleukins exhibited significantly higher expression levels; conversely, TNF-α and MCP-1/CCL2 both had decreased expression compared to healthy individuals. The clustering analysis confirmed that PCa patients exclusively exhibit the highest associations with MIP-1α/CCL3, IFN- γ, IL-12p70, IL-4, and IL-5. Furthermore, specific correlations between IL-4 and MIP-1 beta, IL-4 and IFN-gamma, IL-5 and IL-12p70, and IL-5 and IFN-gamma in PCa patients did not occur in healthy individuals. Such results will guide forthcoming in vitro and in vivo human prostate cancer-drug treatment models, paving the way for exploration of future drug targets and candidates with potential to predict FDA-approved prostate cancer treatment responses by targeting cytokine levels and the oncogenesis pathways.
本研究旨在确定前列腺癌（PCa）患者与健康个体相比的细胞因子表达谱。使用多重酶联免疫吸附测定法（Luminex）分析了75例PCa患者和14例健康对照者的血浆样本，以测量12种细胞因子的表达水平：白细胞介素-4（IL-4）、白细胞介素-5（IL-5）、白细胞介素-6（IL-6）、白细胞介素-10（IL-10）、白细胞介素-1β（IL-1β）、白细胞介素-17A（IL-17A）、白细胞介素-12p70（IL-12p70）、单核细胞趋化蛋白-1/CCL2（MCP-1/CCL2）、巨噬细胞炎性蛋白-1α/CCL3（MIP-1α/CCL3）、巨噬细胞炎性蛋白-1β/CCL4（MIP-1β/CCL4）、肿瘤坏死因子-α（TNF-α）和干扰素-γ（IFN-γ）。使用曼-惠特尼检验、威尔科克森秩和检验、斯皮尔曼秩相关分析以及K均值聚类无监督机器学习来分析细胞因子表达水平的差异，以验证细胞因子表达模式。在PCa患者中，MIP-1α/CCL3、MIP-1β/CCL4、IFN-γ和白细胞介素的表达水平显著更高；相反，与健康个体相比，TNF-α和MCP-1/CCL2的表达均降低。聚类分析证实，PCa患者与MIP-1α/CCL3、IFN-γ、IL-12p70、IL-4和IL-5的关联度最高。此外，PCa患者中IL-4与MIP-1β、IL-4与IFN-γ、IL-5与IL-12p70以及IL-5与IFN-γ之间的特定相关性在健康个体中并未出现。这些结果将为即将开展的体外和体内人类前列腺癌药物治疗模型提供指导，为探索未来的药物靶点和候选药物铺平道路，这些药物有可能通过靶向细胞因子水平和肿瘤发生途径来预测FDA批准的前列腺癌治疗反应。
