A comparative analysis of signaling pathways in lung cancer using optimization methods

Lung cancer is the leading cancer compared among other tumors in both men and women throughout the world. The protein expression and genes behavior are the keys can be used to investigate the response of cancer cell and their ability to proliferate. Epidermal growth factor receptor (EGFR) and insulin-like growth factor-1 receptor (IGF1R) are often over-expressed in cancer that will cause conformational changes on the parts of the cell and as a result will lead to lung cancer. Several studies have been done, yet, the positive response is rarely achieved due to some resistance towards chemotherapeutics and other molecularly targeted drugs. This suggests that the clinical response of tumors is limited. It is important to achieve a better understanding on the molecular mechanism involved in cancer to give a contribution to the development of more effective treatments. The goal of this research is to propose a Firefly Algorithm (FA) and Simplex Algorithm (SA) optimization methods for analyzing the EGFR and IGF1R pathways in lung cancer.