Early Lung Cancer Detection via Global Protein Modification Profiles
Abstract
In recent years, the five-year survival rate of patients diagnosed with localized lung cancer (had not spread) is almost 50%. Although prognostic tests have been developed to evaluate the metastatic recurrence risk in lung cancer, they have shown limited success in reducing patient mortality. Clearly, there is an urgent need for tests that identify lung cancer patients at high risk of recurrence. Biomarker screens performed at the protein level hold promise in the development of such tests. In particular, it is well established that many of the differences in tumor behavior are related to protein post-translational modifications (PTMs). In this investigation, we seek to identify a small set of PTM- related, highly predictive protein biomarkers and develop test for predicting lung cancer metastatic recurrence with an emphasis on identifying high-risk patients with higher accuracy than current prognostic tests. Our technology is based on rapid separation of whole proteins from tumor biopsy samples using automated two-dimensional ultra-high pressure liquid chromatography and microfractionation to generate large protein arrays. The arrays are used as a platform to quantify the levels of specific PTMs. In this study we generated PTMprotein arrays from biopsy samples of a clinically annotated lung tumor cohort consisting of 20 patients each (recurrence < 3 years and no recurrence at 5 years of follow-up) and measured ubiquitylation levels in each array fraction (spot). Nineteen potential markers of which 10 showed increased ubiquitination in tumors and 2 had reduced protein modification. Mass spectrometry techniques identified one of the markers with increased ubiquitination as DNA methyltransferase 1 (DNMT1). These preliminary results suggest that DNMT1 may play a role in lung cancer progression and could serve as a potential biomarker for lung cancer recurrence. Further analysis of the protein arrays will likely yield additional markers.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2013
- Accession Number
- ADA600735
Entities
People
- Augusto Lois