Identification of cancer associated proteins is the crucial problem in cancer research. Recently various techniques have been developed to discover novel cancer genes/proteins. Topological network of protein-protein interaction with their gene ontology annotation are good predictors of cancer proteins. Protein-protein interaction information has provided a basis for studying the cancer cellular network. In this study, we implemented clique percolation clustering approach on lung cancer protein-protein interaction information to identify cancer associated proteins, the enriched protein biological function in molecular networks of the clique motif and also the enriched KEGG pathways were observed.