Background: Lung cancer (LC) is the dominant cause of death by cancer in the world, being responsible for more than a million deaths annually. It is a highly lethal common tumor that is frequently diagnosed in advanced stages for which effective alternative therapeutics do not exist. In view of this, there is an urgent need to improve the diagnostic, prognostic, and therapeutic classification systems, currently based on clinicopathological criteria that do not adequately translate the enormous biologic complexity of this disease. Methods: The advent of the human genome sequencing project and the concurrent development of many genomic-based technologies have allowed scientists to explore the possibility of using expression profiles to identify homogenous tumor subtypes, new prognostic factors of human cancer, response to a particular treatment, etc. and thereby select the best possible therapies while decreasing the risk of toxicities for the patients. Therefore, it is becoming increasingly important to identify the complete catalog of genes that are altered in cancer and to discriminate tumors accurately on the basis of their genetic background. Results and Discussion: In this article, we present some of the works that has applied high-throughput technologies to LC research. In addition, we will give an overview of recent results in the field of LC genomics, with their effect on patient care, and discuss challenges and the potential future developments of this area.
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