Abstract PR08: Pro-surfactant protein B as a biomarker for lung cancer prediction.
Authors: Sin Don D. , Tammemagi C Martin , Lam Stephen , Barnett Matt J. , Duan Xiaobo , Tam Anthony , Auman Heidi , Feng Ziding , Goodman Gary E. , Hanash Samir M. , Taguchi Ayumu 
Published: August 2014

Background: The National Lung Screening Trial reported that low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20% in adults at high risk for lung cancer. Despite these significant results, there are major concerns regarding lung cancer screening with LDCT. They include high false positivity, cost, and radiation exposure. Blood-based markers are a promising and attractive approach to complement LDCT because of the potential to identify those subjects that may be at increased risk of developing lung cancer, or that may be harboring early and potentially curable lung cancer, or that need to undergo further work-up for their indeterminate nodules. Our prior proteomic study suggested pro-surfactant protein B (SFTPB) as a promising circulating biomarker for non-small cell lung cancer (NSCLC). In this study we aimed to determine if plasma levels of pro-SFTPB are associated with lung cancer independently of known clinical risk factors, and improve lung cancer prediction beyond currently existing prediction models in individuals at high-risk for lung cancer at the screening setting.

Methods: Pro-SFTPB levels were measured in 2,485 individuals, including 113 subjects later diagnosed as lung cancer, who enrolled in the Pan-Canadian Early Detection of Lung Cancer Study using plasma sample collected at the baseline visit. Multivariable logistic regression models were used to evaluate the predictive ability of pro-SFTPB in addition to known lung cancer risk factors. Calibration and discrimination were evaluated; the latter by an area under the receiver operator characteristics curve (AUC). Independent validation using a case-control study design was performed with serum samples collected in the Carotene and Retinol Efficacy Trial (CARET) participants consisting of 61 NSCLC subjects and matched 121 control subjects.

Results: In the logistic model fully adjusted for lung cancer risk factors (age, sex, body mass index (BMI), personal history of cancer, family history of lung cancer, forced expiratory volume in 1 second percent predicted, average number of cigarettes smoked per day, and smoking duration), log-transformed pro-SFTPB (log-proSFTPB) was a significant independent predictor of lung cancer (odds ratio (OR) = 2.220, 95% confidence interval (CI) = 1.727-2.853, p &lt; 0.001). The AUCs of the full model with and without pro-SFTPB were 0.741 (95% CI = 0.696-0.783) and 0.669 (95% CI = 0.620-0.717) (P value for difference in AUC = 0.0007). When the full model was estimated in 96 individuals with stage I or II lung cancer, log-proSFTPB remained a statistically significant predictor (OR = 2.195, 95%CI = 1.679-2.870; p &lt; 0.001). In the CARET study, pro-SFTPB levels were significantly higher among NSCLC cases compared with controls (P &lt; 0.0001) and ROC analysis yielded AUC of 0.683 (95% CI, 0.604-0.761). In multivariate logistic regression analysis, the risk of NSCLC increased along with the pro-SFTPB concentration gradient in the CARET set (Ptrend = 0.001, adjusted for matching variables, pack-years, years since quitting smoking, asbestos exposure, and BMI).

Conclusions: Our study demonstrates that plasma pro-SFTPB is significantly and independently associated with lung cancer and adds to lung cancer prediction beyond those contributed by established risk factors in two independent cohorts. Furthermore, pro-SFTPB was associated with early stage lung cancer, suggesting its potential utility in predicting early staged NSCLC tumors, which may be amenable to surgical resection.

This abstract is also presented as Poster A33.

Citation Format: Don D. Sin, C Martin Tammemagi, Stephen Lam, Matt J. Barnett, Xiaobo Duan, Anthony Tam, Heidi Auman, Ziding Feng, Gary E. Goodman, Samir M. Hanash, Ayumu Taguchi. Pro-surfactant protein B as a biomarker for lung cancer prediction. [abstract]. In: Proceedings of the AACR-IASLC Joint Conference on Molecular Origins of Lung Cancer; 2014 Jan 6-9; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2014;20(2Suppl):Abstract nr PR08.