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基于基因表达的特征可预测肾癌对索拉非尼的反应。

Gene Expression-Based Signature Can Predict Sorafenib Response in Kidney Cancer.

作者信息

Gudkov Alexander, Shirokorad Valery, Kashintsev Kirill, Sokov Dmitriy, Nikitin Daniil, Anisenko Andrey, Borisov Nicolas, Sekacheva Marina, Gaifullin Nurshat, Garazha Andrew, Suntsova Maria, Koroleva Elena, Buzdin Anton, Sorokin Maksim

机构信息

I. M. Sechenov First Moscow State Medical University, Moscow, Russia.

Moscow City Oncological Hospital №. 62, Moscow, Russia.

出版信息

Front Mol Biosci. 2022 Mar 14;9:753318. doi: 10.3389/fmolb.2022.753318. eCollection 2022.

DOI:10.3389/fmolb.2022.753318
PMID:35359606
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8963850/
Abstract

Sorafenib is a tyrosine kinase inhibitory drug with multiple molecular specificities that is approved for clinical use in second-line treatments of metastatic and advanced renal cell carcinomas (RCCs). However, only 10-40% of RCC patients respond on sorafenib-containing therapies, and personalization of its prescription may help in finding an adequate balance of clinical efficiency, cost-effectiveness, and side effects. We investigated whether expression levels of known molecular targets of sorafenib in RCC can serve as prognostic biomarker of treatment response. We used Illumina microarrays to profile RNA expression in pre-treatment formalin-fixed paraffin-embedded (FFPE) samples of 22 metastatic or advanced RCC cases with known responses on next-line sorafenib monotherapy. Among them, nine patients showed partial response (PR), three patients-stable disease (SD), and 10 patients-progressive disease (PD) according to Response Evaluation Criteria In Solid Tumors (RECIST) criteria. We then classified PR + SD patients as "responders" and PD patients as "poor responders". We found that gene signature including eight sorafenib target genes was congruent with the drug response characteristics and enabled high-quality separation of the responders and poor responders [area under a receiver operating characteristic curve (AUC) 0.89]. We validated these findings on another set of 13 experimental annotated FFPE RCC samples (for 2 PR, 1 SD, and 10 PD patients) that were profiled by RNA sequencing and observed AUC 0.97 for 8-gene signature as the response classifier. We further validated these results in a series of qRT-PCR experiments on the third experimental set of 12 annotated RCC biosamples (for 4 PR, 3 SD, and 5 PD patients), where 8-gene signature showed AUC 0.83.

摘要

索拉非尼是一种具有多种分子特异性的酪氨酸激酶抑制药物,已被批准用于转移性和晚期肾细胞癌(RCC)的二线治疗。然而,只有10%-40%的RCC患者对含索拉非尼的治疗有反应,其处方的个性化可能有助于在临床疗效、成本效益和副作用之间找到适当的平衡。我们研究了RCC中索拉非尼已知分子靶点的表达水平是否可作为治疗反应的预后生物标志物。我们使用Illumina微阵列对22例转移性或晚期RCC病例的治疗前福尔马林固定石蜡包埋(FFPE)样本中的RNA表达进行分析,这些病例对后续索拉非尼单药治疗的反应已知。其中,根据实体瘤疗效评价标准(RECIST),9例患者显示部分缓解(PR),3例患者病情稳定(SD),10例患者病情进展(PD)。然后,我们将PR+SD患者分类为“反应者”,将PD患者分类为“低反应者”。我们发现,包括8个索拉非尼靶基因的基因特征与药物反应特征一致,能够高质量地区分反应者和低反应者[受试者操作特征曲线(AUC)下面积为0.89]。我们在另一组13个经实验注释的FFPE RCC样本(2例PR、1例SD和10例PD患者)上验证了这些发现,这些样本通过RNA测序进行分析,观察到8基因特征作为反应分类器的AUC为0.97。我们在第三组12个经注释的RCC生物样本(4例PR、3例SD和5例PD患者)的一系列qRT-PCR实验中进一步验证了这些结果,其中8基因特征的AUC为0.83。

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