研究动态
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CCL5 促进肾癌循环肿瘤细胞的上皮-间质转化。

CCL5 promotes the epithelial-mesenchymal transition of circulating tumor cells in renal cancer.

发表日期:2024 Sep 03
作者: Yibing Guan, Xueyi Liu, Juanhua Tian, Guang Yang, Fangshi Xu, Ni Guo, Lingyu Guo, Ziyan Wan, Zhixin Huang, Mei Gao, Tie Chong
来源: Genes & Diseases

摘要:

循环肿瘤细胞 (CTC) 在多种癌症的肿瘤转移中至关重要,但它们在肾癌中的具体作用仍不清楚。本研究利用生物信息学在体内研究了 C-C 基序趋化因子配体 5 (CCL5) 对肾癌细胞和 CTC 的致瘤影响,以及体外实验。它还通过Lasso回归和Kaplan-Meier生存曲线评估了肾癌患者CTC的预后价值。生物信息学分析揭示了CTC和肿瘤细胞之间的细胞粘附和迁移的差异基因。 CCL5 在各种 CTC 中表现出高表达,与肾癌的不良预后相关。在 786-O-CTC 中,CCL5 增强了恶性程度,而在肾细胞癌细胞系 CAKI-2 和 786-O 中,它通过 smad2/3 促进上皮间质转化 (EMT),影响细胞特征。裸鼠模型表明CCL5增加了CTC并增强了EMT,增强了肺转移。临床结果显示,不同EMT类型的CTC的预后价值不同,其中间质CTC的价值最高。综上所述,CCL5通过smad2/3促进肾癌细胞和CTC的EMT,增强恶性表型并促进肺转移。间质型 CTC 相关因素可以构建肾癌患者的风险模型,从而允许基于转移风险预测的个性化治疗。© 2024。作者。
Circulating tumor cells (CTCs) are pivotal in tumor metastasis across cancers, yet their specific role in renal cancer remains unclear.This study investigated C-C motif chemokine ligand 5 (CCL5)'s tumorigenic impact on renal cancer cells and CTCs using bioinformatics, in vivo, and in vitro experiments. It also assessed renal cancer patients' CTCs prognostic value through Lasso regression and Kaplan-Meier survival curves.Bioinformatics analysis revealed differential genes focusing on cellular adhesion and migration between CTCs and tumor cells. CCL5 exhibited high expression in various CTCs, correlating with poor prognosis in renal cancer. In 786-O-CTCs, CCL5 enhanced malignancy, while in renal cell carcinoma cell line CAKI-2 and 786-O, it promoted epithelial-mesenchymal transition (EMT) via smad2/3, influencing cellular characteristics. The nude mouse model suggested CCL5 increased CTCs and intensified EMT, enhancing lung metastasis. Clinical results shown varying prognostic values for different EMT-typed CTCs, with mesenchymal CTCs having the highest value.In summary, CCL5 promoted EMT in renal cancer cells and CTCs through smad2/3, enhancing the malignant phenotype and facilitating lung metastasis. Mesenchymal-type CTC-related factors can construct a risk model for renal cancer patients, allowing personalized treatment based on metastatic risk prediction.© 2024. The Author(s).