Although most cases of lung cancer are associated with tobacco smoking, many lung cancers occur in non-smokers. The causes of lung carcinoma in non-smokers remain mysterious, but cancer-causing viruses are among possible causes. We plan to use a new method to identify disease-causing microbes, computational subtraction, to look for viruses that cause bronchoalveolar carcinoma. This sub-type of lung cancer occurs most frequently in people who have never smoked, compared to other lung cancer types.

We propose the following experiments. 1) To generate cDNA and genomic DNA libraries from cases of bronchoalveolar carcinoma (BAC) from non-smoking patients (preferably women) in high-incidence areas. These libraries will be both conventional libraries as well as using a new concatenated method that we have developed. 2) To sequence these libraries to saturation and then to compare sequences computationally to the human genome. All sequences that match the human genome will be removed. The remaining sequences will be tested by PCR against both bronchoalveolar carcinoma and normal control specimens. 3) Those sequences that are BAC-specific by PCR will be tested for presence in multiple BAC specimens. Any sequences that are found in a high proportion of BAC specimens will be considered as candidate pathogen sequences.