Fekete János Tibor, Welker Ágnes, Győrffy Balázs
Department of Bioinformatics and 2nd Department of Pediatrics, Semmelweis University, H-1094 Budapest, Hungary.
Research Center for Natural Sciences, Momentum Cancer Biomarker Research Group, Institute of Enzymology, Magyar tudósok körútja 2., H-1117 Budapest, Hungary.
Cancers (Basel). 2020 Dec 28;13(1):63. doi: 10.3390/cancers13010063.
Squamous cell carcinomas (SCC) are a major subgroup of malignant tumors with a platinum-based first-line systematic chemotherapy. miRNAs play a role in various diseases and modulate therapy response as well. The aim of this study was to identify predictive miRNAs in platinum-treated SCCs.
miRNA expression data of platinum-treated head and neck (HNSC), cervical (CESC) and lung (LUSC) cancer were collected from the TCGA repositories. Treatment response was defined based on presence or absence of disease progression at 18 months. Responder and nonresponder cohorts were compared using Mann-Whitney and Receiver Operating Characteristic tests. Logistic regression was developed to establish a predictive miRNA signature. Significance was set at FDR < 5%.
The integrated database includes 266 SCC patient samples with platinum-based therapy and available follow-up. We uncovered 16, 103, and 9 miRNAs correlated to chemotherapy response in the CESC, HNSC, and LUSC cohorts, respectively. Eight miRNAs overlapped between the CESC and HNSC subgroups, and three miRNAs overlapped between the LUSC and HNSC subgroups. We established a logistic regression model in HNSC and CESC which included six miRNAs: hsa-miR-5586 (Exp (B): 2.94, = 0.001), hsa-miR-632 (Exp (B): 10.75, = 0.002), hsa-miR-2355 (Exp (B): 0.48, = 0.004), hsa-miR-642a (Exp (B): 2.22, = 0.01), hsa-miR-101-2 (Exp (B): 0.39, = 0.013) and hsa-miR-6728 (Exp (B): 0.21, = 0.016). The model using these miRNAs was able to predict chemotherapy resistance with an AUC of 0.897.
We performed an analysis of RNA-seq data of squamous cell carcinomas samples and identified significant miRNAs correlated to the response against platinum-based therapy in cervical, head and neck, and lung tumors.
鳞状细胞癌(SCC)是恶性肿瘤的一个主要亚组,采用铂类一线全身化疗。微小RNA(miRNA)在多种疾病中发挥作用,并调节治疗反应。本研究的目的是在接受铂类治疗的SCC中鉴定预测性miRNA。
从癌症基因组图谱(TCGA)数据库中收集接受铂类治疗的头颈部癌(HNSC)、宫颈癌(CESC)和肺癌(LUSC)的miRNA表达数据。根据18个月时疾病进展的有无来定义治疗反应。使用曼-惠特尼检验和受试者工作特征检验比较反应者和无反应者队列。建立逻辑回归模型以建立预测性miRNA特征。显著性设定为错误发现率(FDR)<5%。
整合数据库包括266例接受铂类治疗且有可用随访资料的SCC患者样本。我们分别在CESC、HNSC和LUSC队列中发现了16、103和9个与化疗反应相关的miRNA。CESC和HNSC亚组之间有8个miRNA重叠,LUSC和HNSC亚组之间有3个miRNA重叠。我们在HNSC和CESC中建立了一个逻辑回归模型,其中包括6个miRNA:hsa-miR-5586(指数(B):2.94,P = 0.001)、hsa-miR-632(指数(B):10.75,P = 0.002)、hsa-miR-2355(指数(B):0.48,P = 0.004)、hsa-miR-642a(指数(B):2.22,P = 0.01)、hsa-miR-101-2(指数(B):0.39,P = 0.013)和hsa-miR-6728(指数(B):0.21,P = 0.016)。使用这些miRNA的模型能够以0.897的曲线下面积(AUC)预测化疗耐药性。
我们对鳞状细胞癌样本的RNA测序数据进行了分析,并鉴定出与宫颈癌、头颈部癌和肺癌中铂类治疗反应相关的显著miRNA。