Background: Different methods of diagnosis have been found to be inefficient in terms of screening andearly diagnosis of lung cancer. Cancer cells produce proteins whose serum levels may be elevated during theearly stages of cancer development. Therefore, those proteins may be recognized as potential cancer markers.The aim of this study was to differentiate healthy individuals and lung cancer cases by analyzing their serumprotein profiles and evaluate the efficacy of this method in the early diagnosis of lung cancer. Materials and
Methods: 170 patients with lung cancer, 53 under high risk of lung cancer, and 47 healthy people were includedin our study. Proteomic analysis of the samples was performed with the SELDI-TOF-MS approach.
Results:The most discriminatory peak of the high risk group was 8141. When tree classification analysis was performedbetween lung cancer and the healthy control group, 11547 was determined as the most discriminatory peak,with a sensitivity of 85.5%, a specificity of 89.4%, a positive predictive value (PPV) of 96.7% and a negativepredictive value (NPV) of 62.7%.
Conclusions: We determined three different protein peaks 11480, 11547 and11679 were only present in the lung cancer group. The 8141 peak was found in the high-risk group, but not inthe lung cancer and control groups. These peaks may prove to be markers of lung cancer which suggests thatthey may be used in the early diagnosis of lung cancer.