Abstract 272: Nanoscale high-throughput quantitative RT-PCR for the characterization of targeted-therapy related molecular biomarkers from recurrent and non-recurrent NSCLC tissues
Authors: Heidi S. Erickson, Katherine Hale, Lixia Diao, Angela Silvestro, Christina McDowell, M. Gabriela Raso, M. Carmen Behrens, Elen Ortenberg, Doug Roberts, Joe Heath, Brian T. Hennessy, Gordon Mills, Jing Wang, Ignacio Wistuba
Journal: Cancer Research (2012)

Abstract Currently, there are no good biomarkers to predict targeted therapy outcomes for patients whose cancers recur vs. those that do not. Technology limitations have prevented extensive qRT-PCR biomarker analysis on small tumor tissue samples obtained in our unique lung cancer MD Anderson BATTLE clinical trials. Clinical sample size limitations are inherent due to the extremely small core needle biopsies (CNB) and fine needle aspirates (FNA). Identifying technology that can reliably analyze, in a quantitative manner, molecular biomarker signatures of 200-300 genes from CNB and FNA, will allow for comparative analysis of patients’ untreated tumor with treated follow-up tissue samples. We hypothesize RNA amplification coupled with nanoscale high-throughput (HT) qRT-PCR, will allow analysis of 320 gene expression patterns from 10ng RNA from frozen NSCLC tissues. We believe primary NSCLC tumors that recur have a different pattern of molecular abnormalities than NSCLCs from non-recurrent tumors (&amp;lt; 5 years), possibly accounting for lack of response to targeted therapy in some patients. RNA from 40 frozen adenocarcinoma (ADC) NSCLC tumor and matched normal cases with annotated clinicopathologic data was extracted/isolated and quantity/quality measured. 10ng from each sample was pre-amplified by WT-Ovation Pico protocol (NuGEN). Nanoscale high-throughput OpenArray quantitative RT-PCR (Life Technologies) with SYBR chemistry and DLD platform TaqMan chemistry was used to analyze 206 and 94 genes of interest, respectively, and 18 endogenous controls (EC). EC geometric mean was used for data normalization. Two-sample t-test was applied as test statistic for identifying differentially expressed genes in respect to recurrence, clinical stage, race and gender. Statistical significant level was set as p≤0.05. Statistical analysis was conducted using R packages. WT-Ovation Pico protocol successfully amplified all 10ng samples (mean = 235.2ng/ul, 1.94 260/280). OpenArray qRT-PCR successfully produced quantitative gene expression measurements as assessed by technical replicates (SD, median = 0.14; range = 0.00 to 12.70; R=0.931) and sample to sample correlation from chip to chip for each gene (Spearman Rho median = 0.3; range = −0.44 to 0.82). 14 genes included in the SYBR subset (KDRα, SLCO4A1α, ESR1α, TIE1α, EZH2α, VEGFAα, ADMα, CYP1A1α, NEO1α, CXCL5α, FGFR2α, HMBSα, ID1α, NRP2β) and 3 genes included in the TaqMan subset (DDX20α, CIDECα, PERPβ) were significantly dysregulated in recurrent vs. non-recurrent ADC NSCLCs. Amplification coupled with nanoscale HT qRT-PCR allowed for 320 quantitative gene expression measurements from 10ng RNA from NSCLC tissue. Data identified 17 genes with significantly dysregulated expression in recurrent vs. non-recurrent ADC NSCLCs. Supported in part by DoD PROSPECT grant W81XWH-07-1-0306. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 272. doi:1538-7445.AM2012-272