Non-small cell lung adenocarcinoma is the most frequently diagnosed lung cancer type and remains the leading cause of cancer mortality for men and women in the United States. Management of lung cancer is hindered by high false-positive rates due to the inability to resolve benign versus malignant tumors. Therefore, better molecular analysis comparing malignant and non-malignant tissues will provide additional evidence of the underlying biology contributing to tumorigenesis. In the current study, we utilized a proteomics approach to analyze 38 malignant and non-malignant paired tissue samples obtained from current or former smokers with early stage (Stage IA/IB) lung adenocarcinoma. Statistical mixed effects modeling and orthogonal partial least squares discriminant analysis were used to identify key cancer-associated perturbations in the malignant tissue proteome. Identified proteins were subsequently assessed against clinicopathological variables.