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Background  Small cell lung cancer (SCLC) is highly aggressive and is associated with a dismal prognosis. However, there are no clinically recognized biomarkers for early diagnosis. In this study, we used quantitative proteomics to build differential mitochondrial protein profiles that may be used for early diagnosis and investigated the pathogenesis of lung cancer.    Methods  We cultured SCLC cells (NCI‐H446) and normal human bronchial epithelial cells (16‐HBE); mitochondria were extracted and purified using differential and Percoll density gradient centrifugation. Subsequently, we used Western blot analysis to validate mitochondrial purity and labeled proteins/peptides from NCI‐H446 and 16‐HBE cells using relative and absolute quantification of ectopic tags. We then analyzed mixed samples and identified proteins using two‐dimensional liquid chromatography‐tandem mass spectrometry. Additionally, we performed subsequent bioinformatic proteome analyses using the programs ExPASy, GOA, and STRING. Finally, the relationship between ornithine aminotransferase expression and clinicopathological features in lung cancer patients was evaluated using immunohistochemistry.    Results  One hundred and fifty‐three mitochondrial proteins were differentially expressed between 16‐HBE and NCI‐H446 cells. The expression of 30 proteins between 16‐HBE and NCI‐H446 cells increased more than 1.3‐fold. The upregulation of ornithine aminotransferase was associated with pathological grade and clinical tumor node metastasis stage.    Conclusion  Our experiment represented a promising method for building differential mitochondrial protein profiles between NCI‐H446 and 16‐HBE cells. Such analysis may also help to identify novel biomarkers of lung cancer.

thoracic cancer

Quantitative proteomic analysis of mitochondrial proteins differentially expressed between small cell lung cancer cells and normal human bronchial epithelial cells