Abstract

To retrospectively identify quantitative computed tomographic (CT) features that correlate with the three major driver gene mutations in surgically resected lung adenocarcinomas with dominant ground-glass opacity (GGO) stratified by the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS) classification in a Chinese cohort of patients. Surgically resected lung adenocarcinomas from Shanghai Pulmonary Hospital were enrolled. EGFR, KRAS and EML4-ALK mutations were detected by qPCR. Clinical and pathological characteristics including gender, age, TNM stage, smoking status and CT pattern were analyzed. Histologic subtype was classified according to IASLC/ATS/ERS classification. At preoperative chest CT, the percentage of GGO volume, diameter, solid volume and total tumor volume of each tumor were measured by using a semiautomated algorithm. Distribution of driver gene mutations was evaluated by using the Fisher exact test, the Student's t test, and Pearson correlation analysis. 788 in total and 158 GGO tumors were taken in this cohort. GGO pattern occurred at a significantly higher frequency in younger, female and non-smoking patients. EGFR/KRAS mutations and EML4-ALK fusions were similar between GGO and solid adenocarcinomas. GGO volume and diameter showed correlation with EGFR mutation. With regard to association between lung adenocarcinoma histological subtypes and GGO features, GGO proportion was significantly higher in lepidic predominant adenocarcinomas, including adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic predominant invasive adenocarcinoma. No significant differences of driver gene mutations were found between subtypes of lung adenocarcinoma. It is important that we understand GGO lesions of lung adenocarcinoma to identify molecular biomarkers including EGFR, KRAS and EML4-ALK. These markers would offer useful information for determining the appropriate strategy to treat lung adenocarcinoma with GGO lesions detected by helical CT.

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