Lung cancer has been the most common death causing cancer in the world for several decades. This study is focused on the metabolite profiling of plasma from lung cancer (LC) patients with three control groups including healthy non-smoker (NS), smokers (S) and chronic obstructive pulmonary disease patients (COPD) samples using gas chromatography-mass spectrometry (GC-MS) in order to identify the comparative and distinguishing metabolite pattern for lung cancer. Metabolites obtained were identified through National Institute of Standards and Technology (NIST) mass spectral (Wiley registry) and Fiehn Retention Time Lock (RTL) libraries. Mass Profiler Professional (MPP) Software was used for the alignment and for all the statistical analysis. 32 out of 1,877 aligned metabolites were significantly distinguished among three controls and lung cancer using p-value ≤ 0.001. Partial Least Square Discriminant Analysis (PLSDA) model was generated using statistically significant metabolites which on external validation provide high sensitivity (100%) and specificity (78.6%). Elevated level of fatty acids, glucose and acids were observed in lung cancer in comparison with control groups apparently due to enhanced glycolysis, gluconeogenesis, lipogenesis and acidosis, indicating the metabolic signature for lung cancer.