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The classification of lung cancer (LC) according to the degree of anatomical extension (TNM) allows the estimation of the prognosis of the patient, although its accuracy is limited. In fact, one third of surgically-treated patients with initial disease have recurrences during follow-up, despite the negativity of node dissection at surgery. The incorporation of genetic, epigenetic and proteomic information to TNM staging will characterize more accurately the lung cancer, and thereby improve the prognostic and the prediction of the therapeutic response in these patients.In this project a prospective cohort of 320 patients with lung cancer staged I-IIp will be studied, combining the clinical and pathologic information available with genetic, epigenetic and proteomic markers in tumour samples, pulmonary tissue, regional nodes and peripheral blood, preserved in suitable systems for the application of complex analytical methodologies. Thus, a knowledge database will be created with the aim of improving the prognostic and prediction capabilities of TNM staging.This project is coordinated with related sub-projects that cover the required laboratory tests on biological samples and with Spanish collaborative group in lung cancer.
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200 participants in 1 patient group
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