Gill Rajbir K, Vazquez Madeline F, Kramer Arin, Hames Megan, Zhang Lijuan, Heselmeyer-Haddad Kerstin, Ried Thomas, Shilo Konstantin, Henschke Claudia, Yankelevitz David, Jen Jin
Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
Clin Cancer Res. 2008 Nov 15;14(22):7481-7. doi: 10.1158/1078-0432.CCR-07-5242.
We seek to establish a genetic test to identify lung cancer using cells obtained through computed tomography-guided fine needle aspiration (FNA).
We selected regions of frequent copy number gains in chromosomes 1q32, 3q26, 5p15, and 8q24 in non-small cell lung cancer and tested their ability to determine the neoplastic state of cells obtained by FNA using fluorescent in situ hybridization. Two sets of samples were included. The pilot set included six paraffin-embedded, noncancerous lung tissues and 33 formalin-fixed FNA specimens. These 39 samples were used to establish the optimal fixation and single scoring criteria for the samples. The test set included 40 FNA samples. The results of the genetic test were compared with the cytology, pathology, and clinical follow-up for each case to assess the sensitivity and specificity of the genetic test.
Nontumor lung tissues had < or= 4 signals per nucleus for all tested markers, whereas tumor samples had > or = 5 signals per nucleus in five or more cells for at least one marker. Among the 40 testing cases, 36 of 40 (90%) FNA samples were analyzable. Genetic analysis identified 15 cases as tumor and 21 cases as nontumor. Clinical and pathologic diagnoses confirmed the genetic test in 15 of 16 lung cancer cases regardless of tumor subtype, stage, or size and in 20 of 20 cases diagnosed as benign lung diseases.
A set of only four genetic markers can distinguish the neoplastic state of lung lesion using small samples obtained through computed tomography-guided FNA.
我们试图建立一种基因检测方法，利用计算机断层扫描引导下细针穿刺抽吸（FNA）获得的细胞来识别肺癌。
我们选择了非小细胞肺癌中1q32、3q26、5p15和8q24染色体上常见拷贝数增加的区域，并使用荧光原位杂交技术测试它们确定FNA获得的细胞肿瘤状态的能力。纳入了两组样本。试点组包括6个石蜡包埋的非癌性肺组织和33个福尔马林固定的FNA标本。这39个样本用于确定样本的最佳固定和单一评分标准。测试组包括40个FNA样本。将基因检测结果与每个病例的细胞学、病理学和临床随访结果进行比较，以评估基因检测的敏感性和特异性。
对于所有测试标记，非肿瘤肺组织每个细胞核的信号数≤4个，而肿瘤样本中至少有一个标记在五个或更多细胞中每个细胞核的信号数≥5个。在40个测试病例中，40个FNA样本中有36个（90%）可进行分析。基因分析确定15例为肿瘤，21例为非肿瘤。临床和病理诊断在16例肺癌病例中的15例中证实了基因检测结果，无论肿瘤亚型、分期或大小如何，在20例诊断为良性肺病的病例中也证实了基因检测结果。
仅一组四个基因标记就可以利用计算机断层扫描引导下FNA获得的小样本区分肺病变的肿瘤状态。
