Computational Modeling and Analysis of Non-Small Cell Lung Cancer (NSCLC) Pathway using Static Analysis Approach to Identify Potential Biomarkers and Drug Targets

Abstract

Latterly, a vital prototype shift has been manifested in the management of non-small cell lung Cancer (NSCLC). Owing to the fact that NSCLC could be sub-categorized on the basis of its physiological morphology along with concerned genetic alterations. Lung cancer regimen has been revolutionized with advancement of drugs that are to some extent effectual in targeting the prime driver mutations and immune control points. While, targeted therapy is anticipated to ameliorate patients results along with the standard of life. Computational simulation techniques have greatly contributed in the progression of molecular biology targeted based therapies by allowing the biological abstractions meticulous and demonstrable along with implementing reference map that confines together the discrete biological insights. The current research exercises one of the remarkable computational technique of software Pint under the parasol of Process Hitting. It enlightened us about an extensive catalogue of significant Biomarkers inclusive of presence of prolonged cell survival along with uninterrupted G1/S cell cycle progression and enhanced proliferation of the tumor cells marks down the footprints for an early and effective diagnosis of NSCLC. Application of cut set on AKT allowed us to regain homeostatic apoptotic process. It also contributed towards therapeutic strategies for NSCLC treatment by providing the important drug targets such as ALK, mTORC1, STK4, CCND1 and besides others. The current study tends to fulfil the scientific gap between wet lab studies and cost effective along with time saving computational strategies for an effectual treatment for deadly diseases like non-small cell lung cancer.