Two MicroRNA Panels to Discriminate Three Subtypes of Lung Carcinoma in Bronchial Brushing Specimens
Two MicroRNA Panels to Discriminate Three Subtypes of Lung Carcinoma in Bronchial Brushing Specimens
复制标题
两个 microRNA 组可区分支气管刷检标本中肺癌的三种亚型。
DOI：
10.1164/rccm.201203-0534oc
复制
发表时间：
2012-12-01
影响因子：
24.7
通讯作者：
Lu, Shao-hua
中科院分区：
文献类型：
--
作者：
Huang, Wei;Hu, Jie;Lu, Shao-hua
理由：肺癌的有效治疗需要对癌症亚型进行准确的细分。目标：鉴定支气管刷检样本中的 microRNA，以区分小细胞肺癌 (SCLC) 与非小细胞肺癌 (NSCLC)，并进一步区分鳞状细胞癌 (SQ) 与腺癌 (AC)。方法：使用微阵列从激光捕获的显微解剖癌细胞中筛选 723 个 microRNA 82 个速冻外科肺标本。对 153 个福尔马林固定、石蜡包埋 (FFPE) 的手术肺标本进行了定量逆转录聚合酶链反应，以评估从微阵列中发现的 7 个候选 microRNA。两个 microRNA 组是在训练队列 (n = 85) 的基础上构建的，并使用独立队列 (n = 68) 进行验证。在 207 个支气管刷检标本中，将 microRNA 组用作 SCLC 与 NSCLC 以及 SQ 与 AC 的区分器。测量和主要结果：两个 microRNA 组在区分 SCLC 与 NSCLC 方面（miR-29a 和 miR-375；训练和验证数据集的曲线下面积 [AUC] 分别为 0.991 和 0.982）以及区分 SQ 与 AC 具有较高的诊断准确性（miR-205 和 miR-34a；训练和验证数据集的 AUC 分别为 0.977 和 0.982）在 FFPE 手术肺标本中。此外，在支气管刷检标本中，microRNA panel 可准确地区分 SCLC 与 NSCLC（AUC，0.947）以及 SQ 与 AC（AUC，0.962）。结论：我们发现两个 microRNA panel 可准确区分支气管刷检标本中肺癌的三种亚型。鉴定出的 microRNA 组合可能在肺癌亚型的鉴别诊断和优化治疗策略方面具有相当大的临床价值。
Rationale: Effective treatment for lung cancer requires accuracy in subclassification of carcinoma subtypes.Objectives: To identify microRNAs in bronchial brushing specimens for discriminating small cell lung cancer (SCLC) from non-small cell lung cancer, (NSCLC) and for further differentiating squamous cell carcinoma (SQ) from adenocarcinoma (AC).Methods: Microarrays were used to screen 723 microRNAs in laser-captured, microdissected cancer cells from 82 snap-frozen surgical lung specimens. Quantitative reverse-transcriptase polymerase chain reaction was performed on 153 macrodissected formalin-fixed, paraffin-embedded (FFPE) surgical lung specimens to evaluate seven microRNA candidates discovered from microarrays. Two microRNA panels were constructed on the basis of a training cohort (n = 85) and validated using an independent cohort (n = 68). The microRNA panels were applied as differentiators of SCLC from NSCLC and of SQ from AC in 207 bronchial brushing specimens.Measurements and Main Results: Two microRNA panels yielded high diagnostic accuracy in discriminating SCLC from NSCLC (miR-29a and miR-375; area under the curve [AUC], 0.991 and 0.982 for training and validation data set, respectively) and in differentiating SQ from AC (miR-205 and miR-34a; AUC, 0.977 and 0.982 for training and validation data set, respectively) in FFPE surgical lung specimens. Moreover, the microRNA panels accurately differentiated SCLC from NSCLC (AUC, 0.947) and SQ from AC (AUC, 0.962) in bronchial brushing specimens.Conclusions: We found two microRNA panels that accurately discriminated between the three subtypes of lung carcinoma in bronchial brushing specimens. The identified microRNA panels may have considerable clinical value in differential diagnosis and optimizing treatment strategies based on lung cancer subtypes.