Identification of tissue microRNAs predictive of sutinib activity in patients with metastatic renal cell carcinoma

Purpose: To identify tissue microRNAs predictive of sunitinib activity in patients with metastatic renal-cell carcinoma (MRCC) and to validate them in a cellular model. Selected microRNAs were studied in serum from MRCC patients and healthy individuals. Methods: We screened 673 microRNAs using TaqMan Low-density Arrays (TLDAs) in tumors from MRCC patients with extreme phenotypes of marked efficacy and resistance to sunitinib, selected from an identification cohort (n=41). Differentially expressed microRNAs were selected using bioinformatics-based target prediction analysis and quantified by qRT-PCR in tumors from patients presenting similar phenoytpes selected from an independent cohort (n=117). Results were validated in a cellular model of sunitinib resistance and studied in serum from healthy individuals and MRCC patients. Results: TLDAs identified 64 microRNAs differentially expressed in the identification cohort. Seven candidates were quantified by qRT-PCR in the independent series. MiR-942 was the most accurate predictor of sunitinib efficacy (p=0.0074). High expression of miR-942, miR-133a, miR484, and miR-628-5p was significantly associated with decreased time-to-progression and overall survival. These microRNAs were overexpressed in the sunitinib resistant cell line Caki-2 in comparison with the sensitive parental cell line. Serum levels of miR-942, miR-133a, miR-484, miR-146a-5p, miR-374a and miR-486-5p were significantly reduced in MRCC patients compared to healthy controls. Conclusions: Our strategy identified differentially expressed microRNAs in MRCC patients presenting marked sensitivity and resistance to sunitinib. Mir-942 was the best predictor of efficacy. Results were confirmed in a cellular model of sunitinib resistance. We also identified exosome derived serum microRNAs differentially expressed in MRCC patients and healthy individuals. Taqman Low Density Array for 6 FFPE tissues obtained from extreme phenotype MRCC patients, (n=3 marked resistance to sunitinib treatment patients and n=3 marked sensitivity to sunitinib treatment patients), was performanced to screen 667 microRNAs.

研究目的：本研究旨在鉴定可预测转移性肾细胞癌（metastatic renal-cell carcinoma, MRCC）患者对舒尼替尼（sunitinib）治疗应答的组织源性微小核糖核酸（microRNAs, miRNAs），并在细胞模型中对其进行验证；同时在转移性肾细胞癌患者与健康个体的血清中对筛选得到的微小核糖核酸展开研究。
研究方法：本研究从鉴定队列（n=41）中选取具有舒尼替尼显著疗效与耐药极端表型的转移性肾细胞癌患者肿瘤组织，采用TaqMan低密度芯片（TaqMan Low-density Arrays, TLDAs）对673种微小核糖核酸进行筛选。通过基于生物信息学的靶标预测分析筛选差异表达的微小核糖核酸，并采用实时定量聚合酶链反应（quantitative real-time polymerase chain reaction, qRT-PCR）在独立队列（n=117）中选取的具有相似表型的患者肿瘤组织中对其进行定量检测。研究结果随后在舒尼替尼耐药细胞模型中进行验证，并在健康个体与转移性肾细胞癌患者的血清中展开分析。
研究结果：TaqMan低密度芯片筛选在鉴定队列中鉴定出64种差异表达的微小核糖核酸。在独立队列中通过qRT-PCR对7个候选微小核糖核酸进行了定量检测。其中，miR-942是预测舒尼替尼疗效最准确的生物标志物（p=0.0074）。高表达miR-942、miR-133a、miR-484及miR-628-5p与更短的至疾病进展时间及总生存期显著相关。与舒尼替尼敏感的亲本细胞系相比，这些微小核糖核酸在舒尼替尼耐药细胞系Caki-2中呈高表达状态。与健康对照相比，转移性肾细胞癌患者血清中miR-942、miR-133a、miR-484、miR-146a-5p、miR-374a及miR-486-5p的水平显著降低。
研究结论：本研究策略在具有舒尼替尼显著疗效与耐药极端表型的转移性肾细胞癌患者中鉴定出了差异表达的微小核糖核酸，其中miR-942是疗效预测的最佳生物标志物，且研究结果在舒尼替尼耐药细胞模型中得到了验证。本研究同时鉴定出了在转移性肾细胞癌患者与健康个体血清中差异表达的外泌体（exosome）源性微小核糖核酸。此外，本研究采用TaqMan低密度芯片对6份来自极端表型转移性肾细胞癌患者的福尔马林固定石蜡包埋（formalin-fixed paraffin-embedded, FFPE）组织样本（其中3例为舒尼替尼治疗显著耐药患者，3例为舒尼替尼治疗显著敏感患者）进行检测，以筛选667种微小核糖核酸。