Lung cancer remains the most common cancer worldwide, both in terms of incidence and mortality. Lung cancer is classified in two broad histologic classes, which grow and spread differently: small-cell lung carcinomas (SCLC) and non-small cell lung carcinomas (NSCLC). In this project we focused our analysis in the two predominant subtypes of NSCLC which are : lung adenocarcinoma (LUAD) and lung squamous cancer (LUSC). LUAD and LUSC have a high mutational rate, however, around one third of LUAD patients lack druggable genomic mutations and can’t benefit from target therapies. The main hypothesis of this project was that from gene expression data we could identify different subgroups in LUAD and LUSC. Furthermore, we hypothesized that if we were able to understand the molecular and cellular mechanism that differentiated these groups, we would predict specific drugs that may induce an antitumor effect on each group genotype. In this talk we will discuss which bioinformatics analysis we performed, the results we got and finally which were the conclusions.