This paper proposes a preliminary investigation on the volatile production patterns generated from three sets of in-vitro cancerous cell samples of headspace that contains volatile organic compounds using the electronic nose system.  A commercialized electronic nose consisting of 32 conducting polymer sensors (Cyranose 320) is used to analyze the three classes of signals which are lung cancer cells grown in media, breast cancer cells grown in media and the blank media (without cells). Neural Network (PNN) based classification technique is applied to investigate the performance of an electronic nose (E-nose) system for cancerous lung cell classification.