Abstract 613: Copy number variations distinguish lung adenocarcinomas from squamous cell carcinomas

Abstract

Abstract Purpose To develop a molecular based classification of non-small cell lung carcinomas based on genome wide copy number variations (CNVs). Background For a number of clinical and biologic reasons, the accurate classification of non small cell lung carcinoma (NSCLC) into adenocarcinoma (ADC) and squamous cell carcinoma (SCC) is essential. DNA based tests, which are not currently used, are more robust when applied to formalin fixed paraffin embedded tissues. Materials and Methods TCGA Dataset: The Cancer Genome Atlas project (TCGA) level 3 CNVs data (Affymetrix Genome-Wide Human SNP Array 6.0) of resected ADC (n = 241) and SCC (n = 210) patients were utilized as a Training set along with 1091 non malignant lung samples. SPORE Patient Dataset: The UT Lung SPORE cohort consists of 248 resected lung cancers (168 ADC and 74 SCC samples) run with the Agilent 244K Human Genome CGH Microarray. Molecular signature identification based on the morphologic subclassification of NSCLC: We used statistical algorithms to identify potential CNV biomarkers and combined them with known amplified oncogenes to identify 28 CNV signature genes that were highly correlated with histological classification. Identification of CNV classifier genes. The CNV signature genes were identified through the following four sequential steps: 1) Paired t-test. 2) Elastic Net. 3) Partial lease squares algorithm. 4) Naive Bayes classifier. Results: The 28 gene CNV signature accurately separated squamous cell carcinomas from adenocarcinomas in the Training and Validation sets as well as distinguished tumors from non-malignant tissues (Table 1). Table 1. The classification results between ADC and SCC DataSensitivitySpecificityAccuracyADC vs SCCTraining set (TCGA)0.940.870.91Validation set (SPORE)0.870.840.86Tumor vs Non-malignantADC0.910.960.94SCC0.970.980.98 Conclusions: A 28 gene CNV signature distinguished lung adenocarcinomas from squamous cell carcinomas with great accuracy (86-91%) and the lung tumor samples can be distinguished from the non-malignant lung samples with an accuracy of 94-98%. Citation Format: Kai Song, Guangqiang Zheng, Luc Girard, Ignacio I. Wistuba, Jack A. Roth, Carmen Behrens, Milind B. Suraokar, John D. Minna, Adi F. Gazdar. Copy number variations distinguish lung adenocarcinomas from squamous cell carcinomas. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 613. doi:10.1158/1538-7445.AM2015-613