Lung cancer is the leading cause of all cancer related deaths with a worldwide mortality of 1.2 million each year. The 5-year survival rate ranges from 80% in early stages to a dismal 5% in advanced disease. Prognosis is currently mostly determined based on the extension of disease at diagnosis. Thereby it has become evident that predicted and real outcomes can vary significantly, even for patients with the same stage of disease. Novel biomarkers with a reliable predictive significance are therefore clearly needed. In this study we implemented an activity-based, solely mass spectrometry dependent biomarker discovery platform. We investigated the role of serine hydrolase activities as potential biomarkers for human lung adenocarcinoma, the most common lung cancer subtype. Forty pairs of fresh frozen malignant and matching non-neoplastic lung tissues were analyzed and enzymatic activities linked to clinical follow-up data. We found that the activities of Abhydrolase domain-containing protein 11 and Esterase D predict the development of distant metastases and the presence of aggressive lung adenocarcinomas, respectively, in a statistically significant model. We conclude that serine hydrolase activities bear a predictive potential for human lung adenocarcinoma and that activity-based proteomics represents a powerful methodology in the search for novel disease biomarkers.