Abstract 3165: Profiling of circulating tumor-associated autoantibodies for lung adenocarcinoma detection (2011)

Abstract Purpose: To identify a panel of tumor associated autoantibodies which potentially can be used as biomarkers for detection of early lung cancer. Background: Lung cancer is the leading cause of cancer-related death worldwide, and early detection of lung cancer is essential for improved patient outcome. However, currently there is not a single validated molecular biomarker for early lung cancer diagnosis. Methods: With a lung adenocarcinoma phage display library derived from 20 tumor tissues (stage I-IV), we used biopan enrichment techniques and immunochemical detection to identify the presumptive phage expressed tumor-associated proteins with the patients’ autologous and normal healthy donors’ sera. After sequence analysis, the open reading frames of phage expressed proteins were correlated with their respective gene expression microarray profiles in Non-small Cell Lung Cancer (NSCLC) cell lines to confirm their expression levels. We then measured corresponding autoantibodies in serum samples from 40 lung adenocarcinoma patients and 36 healthy matched controls. The up-regulated gene encoded proteins were selected to develop phage protein enzyme-linked immunoadsorbent assays (ELISAs). Logistic regression models and leave-one-out validation tests were used to evaluate prediction ability of a single marker versus combined markers, and the latter statistic method was also employed to analyze the data in association with the disease stage. Results: Of 64 presumptive tumor-associated phage clones isolated, 25 contained phage proteins were in frame and unique. Based on expression profiling, four were selected for further study. The mRNA transcripts of these four proteins (SMOX, NOLC1, MALAT1 and HMMR) were significantly up-regulated in NSCLC cell lines as compared with normal human bronchial epithelial cells (Ratio&amp;gt;1.5, p&amp;lt;0.05). Analysis of these four antibodies by a logistic regression model achieved 50.0% sensitivity and 94.4% specificity in predicting sample status, while leave-one-out validation achieved 66.7% sensitivity and 60.0% specificity. Both receiver operating characteristic curve analysis and the leave-one-out method revealed that combined measurements of the four antibodies produced a better predicting value than any single marker alone. The leave-one-out validation also showed sensitivity of 63.6%, 62.5% and 82.4% for detecting stage I, stage II and stage III lung adenocarcinoma patients, respectively. Conclusion: The panel of autoantibody profiles we identified has potential to be used in developing screening tests for detecting early-stage lung adenocarcinoma. (Supported by the grants from National Eleventh-Five-Year Key Task Project of China No.2006BAI02A01 and China-Sweden International Cooperative Project No.09ZCZDSF04100) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3165. doi:10.1158/1538-7445.AM2011-3165