Charkiewicz Radoslaw, Pilz Lothar, Sulewska Anetta, Kozlowski Miroslaw, Niklinska Wieslawa, Moniuszko Marcin, Reszec Joanna, Manegold Christian, Niklinski Jacek
Department of Clinical Molecular Biology, Medical University of Bialystok, Bialystok, Poland.
Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Int J Cancer. 2016 Feb 1;138(3):689-97. doi: 10.1002/ijc.29816. Epub 2015 Sep 10.
Targeted therapy of non-small cell lung cancer (NSCLC) demands a more accurate tumor classification that is crucial for patient selection in personalized treatment. MicroRNAs constitute a promising class of biomarkers and a helpful tool for the distinction between lung adenocarcinoma (AC) and squamous cell lung carcinoma (SCC). The aim of this study was to evaluate the impact of two different normalization strategies, using U6 snRNA and hsa-miR-103 as reference genes, on hsa-miR-205 and hsa-miR-21 expression levels, in terms of the classification of subtypes of NSCLC. By means of a quantitative real-time polymerase chain reaction (qRT-PCR) microRNA expression levels were evaluated in a classification set of 98 surgically resected NSCLC fresh-frozen samples, and validated findings in an independent set of 42 NSCLC samples. The microRNA expression levels were exploited to develop a diagnostic test using two data normalization strategies. The performance of microRNA profiling in different normalization methods was compared. We revealed the microRNA-based qRT-PCR tests to be appropriate measures for distinguishing between AC and SCC (the concordance of histologic diagnoses and molecular methods greater than 88%). Performance evaluation of microRNA tests, based on the two normalization strategies, showed that the procedure using hsa-miR-103 as reference target has a slight advantage (sensitivity 83.33 and 100% in classification and validation set, respectively) compared to U6 snRNA. Molecular tests based on microRNA expression allow a reliable classification of subtypes for NSCLC and can constitute a useful diagnostic strategy in patient selection for targeted therapy.
非小细胞肺癌（NSCLC）的靶向治疗需要更精确的肿瘤分类，这对于个性化治疗中患者的选择至关重要。微小RNA构成了一类有前景的生物标志物，也是区分肺腺癌（AC）和肺鳞状细胞癌（SCC）的有用工具。本研究的目的是评估使用U6小核仁RNA（snRNA）和hsa-miR-103作为参考基因的两种不同归一化策略对hsa-miR-205和hsa-miR-21表达水平的影响，以用于NSCLC亚型的分类。通过定量实时聚合酶链反应（qRT-PCR），在98例手术切除的NSCLC新鲜冷冻样本的分类集中评估微小RNA表达水平，并在42例NSCLC样本的独立集中验证结果。利用微小RNA表达水平，采用两种数据归一化策略开发诊断测试。比较了不同归一化方法中微小RNA谱分析的性能。我们发现基于微小RNA的qRT-PCR测试是区分AC和SCC的合适方法（组织学诊断与分子方法的一致性大于88%）。基于两种归一化策略的微小RNA测试性能评估表明，与U6 snRNA相比，以hsa-miR-103作为参考靶点的方法具有轻微优势（在分类集和验证集中的敏感性分别为83.33%和100%）。基于微小RNA表达的分子测试能够对NSCLC亚型进行可靠分类，并且在靶向治疗的患者选择中可以构成一种有用的诊断策略。
