Gene Expression Ratio Test Distinguishes Normal Lung from Lung Tumors in Solid Tissue and FNA Biopsies
作者：Assunta De Rienzo, Beow Y. Yeap, Edmund S. Cibas, William G. Richards, Lingsheng Dong, Ritu R. Gill, David J. Sugarbaker, Raphael Bueno

Lung cancer is the leading cause of cancer-related deaths worldwide. Prognosis and survival are dependent on cell type, early detection, and surgical treatment. Hence, optimal screening strategies and new therapies are urgently required. Although surveillance with low-dose computed tomography can reduce lung cancer mortality by 20%, the number of false-positive detections is significant. Tissue diagnosis aids in the identification of benign nodules, reducing the number of false positive detections. To determine whether molecular testing of fine-needle aspirations (FNAs) can reduce false-positive detections, we developed a gene expression–based test that distinguishes normal from cancerous lung tissues. The test first was applied to published microarray data, showing overall sensitivity and specificity values of 95% (95% CI, 90%–98%) and 100% (95% CI, 40%–100%), respectively. Subsequently, it was validated on 30 solid and ex vivo FNA lung cancer tumor samples and matched normal lung specimens using real-time PCR. The validation test was 93% (95% CI, 78%–99%) sensitive and 100% (95% CI, 88%–100%) specific for the detection of tumor versus normal lung on solid samples, whereas FNA specimens yielded a sensitivity of 91% (95% CI, 72%–99%) and a specificity of 94% (95% CI, 70%–100%). This study supports the hypothesis that the gene-ratio approach reliably distinguishes normal lung from cancerous tissues in FNA samples and can be optimized to diagnose benign nodules.
信源地址：http://www.sciencedirect.com/science/journal/15251578/16/2