EXPERIMENTAL STRATEGY FOR IDENTIFYING MEMBRANE PROTEINS SPECIFICALLY EXPRESSED IN PROSTATE TUMORS FOR CLINICAL APLLICATIONS

INTRODUCTION AND OBJECTIVE: The National Cancer Institute (INCA) estimated 68,220 new cases for prostate tumors and 14,484 cases mortality for 2019 (INCA, 2018). These data reflect several clinical limitations, regarding difficulties about early diagnosis and systemic toxicity, resistance, and debilitating side effects in cancer treatment. An effective solution to circumvent this scenario is the characterization of membrane proteins to address second generation nanoparticles. The aim of this project is to describe a strategy for optimized selection of membrane target proteins in prostate tumors. MATERIAL AND METHODS: The Cancer Genome Atlas (TCGA) transcriptome data was used to identify positively regulated membrane protein genes in prostate tumor by comparison with the paired non-tumor tissue (training set = 51 patients; validation set = 499 patients). The expression profile of overexpressed proteins in prostate tumors in different healthy tissues was evaluated: colon (n = 41), bladder (n = 19), lung (n = 59), pancreas (n = 4), esophagus (n = 11), kidney (n = 19), stomach (n = 32), liver (n = 50), rectum (n = 6) and thyroid (n = 52). Geo Data Set transcriptome data (GSE89223) was used to validate the expression profile of selected membrane proteins for prostate tumors in a cohort of benign prostate hyperplasia (BPH). RESULTS AND CONCLUSION: The membrane proteins identified in this work should be kept confidential for intellectual property reasons. A list of 7 (seven) target proteins was proposed based in this methodology for prostate tumor patients, which includes the different staging and gleason score. Based in a study of the combination 2 (two) and 3 (three) target proteins, it is possible to diagnosis larger number of patients, and this data is explained by the heterogeneity of the tumors. In the context of the literature, we identified proteins with a function characterized in the prostate cancer progression, but we identified proteins not yet described in the progression of this disease. Molecular network-based inference of target proteins to identify individual specificities within a group of compatible patients for a given treatment is at the heart of the concept of personalized medicine. In the case of cancer, the aim is to direct drugs to tumors, thus avoiding the systemic side effects of traditional therapies and to outline a specific strategy for prostate cancer differentiating it from other dysplasia. One of the advantages of taking drugs directly to specific tissues is that it allows relatively more toxic and efficient drugs to be used with less risk of collateral damage to other body tissues.