Identificação e avaliação da expressão de marcadores moleculares envolvidos na tumorigênese de pulmão

Abstract

Introduction: Lung cancer is the most common malignancy in human. The average 5 years survival rate is one of the lowest among aggressive cancers, showing no significant improvement in recent years. When detected early, lung cancer has a good prognosis, but most patients present metastatic disease at the time of diagnostic, which significantly reduces survival rates. Despite all the recent advances in cancer treatment, prognostic of these patients have improved minimally. Objectives: The present study aimed to investigate the molecular profile of non-small cell lung cancer as well as new tumor makers relevant to diagnosis and prognosis of this disease. Methods: Total RNA from frozen surgical tissues was extracted using TRIZOL reagent and RNeasy FFPE kit was used for RNA extraction from formalin fixed, paraffin embedded tissue. Aiming to identify differentially expressed genes involved in lung cancer, we analyzed combined data from normal and tumor SAGE (Serial Analysis of Gene Expression) libraries available in the public domain. Proteome profiling was also analyzed in adenocarcinoma, squamous cell carcinoma and normal surgical margin samples using two-dimensional electrophoresis and mass spectrometry. Results: The statistical analysis of SAGE data indentified a subset of differentially expressed tags between normal surgical margins and adenocarcinoma libraries. Three genes displaying differential regulation in SAGE or proteomic analysis, two up- (COL3A1, CTSB) and one down-regulated (ITGB1) in neoplastic cells, were selected for real-time polymerase chain reaction (PCR) experiments using the same set of samples. Similar to the statistical results, quantitative PCR confirmed the upregulation of COL3A1 and CTSB in carcinomas when compared to tumor free tissues. Conclusion: RNA from frozen and arquived samples is appropriate for amplification experiments by real time PCR, although with lower efficiency among the last ones. Therefore, improved methods of RNA extraction in arquived tissues are suitable for Real Time quantitative RT-PCR, and may be used for gene expression profiling of paraffin embedded tissues from cancer patients. To the best of our knowledge, this is the first study reporting SAGE data analysis in lung cancer. The statistical approach as well as the proteomic evaluation were effective in identifying differentially expressed genes and proteins reportedly involved in cancer development and may be useful to disclose new tumor makers relevant to lung tumorigenesis.