Introductory sentence indicating the purposes of the study:

Lung cancer will remain the number one cancer killer worldwide for the foreseeable future (Globocan 2012). Although low-dose CT screening has been shown to reduce mortality, there is an urgent need to improve risk prediction models to identify those subjects at high risk and most likely to benefit from screening in order its improve the screening efficacy (PMID: 23697514, 25372087).

Brief description of pertinent experimental procedures:

We have assembled a compendium of promising blood-based risk biomarkers for lung cancer that are currently being validated in order to identify a panel of validated risk markers for use in lung cancer risk assessment. Using pre-diagnostic serum samples from CARET cohort participants (current or former heavy smokers) we have recently validated pro-surfactant protein B (Pro-SFTPB) and Diacetyl spermine (DAS) as risk markers for non-small cell lung cancer (PMID: 26282655). Validation of additional markers from the compendium using Pro-SFTPB and DAS as anchor markers with further refinement of the risk prediction models is currently being performed in two large independent cohort studies (EPIC and NSHDS). Biospecimens from these cohorts include pre-diagnostic plasma from 550 former and current smoking lung cancer cases that were diagnosed within 5 years of blood draw, along with 1,100 matched controls.

Summary of the new, unpublished data and conclusion:

Preliminary data indicate that blood-based biomarkers of lung cancer risk have a strong potential to improve on questionnaire-based risk prediction models for lung cancer (PMID: 26282655). During the meeting we will present detailed results of the individual risk biomarkers and their associations with lung cancer risk up to 2 years prior to diagnosis, as well as an assessment of the extent to which they can improve traditional risk prediction models.

Citation Format: Mattias A. Johansson, Ayumu Taguchi, David Muller, Samir Hanash, Paul Brennan. Comprehensive evaluation of promising biomarkers for lung cancer risk prediction. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2259.