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首页> 外文会议>National SBIR/STTR conference;Annual nanotech conference and expo;Annual TechConnect world innovation conference expo >From Nanogenomics and Structural-Functional Proteomics to Personalized Medicine for Oral Lichen Planus (OLP) as a Translational Model of Oral Cancer Useful to Introduce an Industrial Technical Innovation
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From Nanogenomics and Structural-Functional Proteomics to Personalized Medicine for Oral Lichen Planus (OLP) as a Translational Model of Oral Cancer Useful to Introduce an Industrial Technical Innovation

机译：从纳米基因组学和结构功能蛋白质组学到口腔扁平苔藓（OLP）的个性化医学，作为口腔癌的转化模型，可用于引入工业技术创新

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Oral Lichen Planus (OLP) is a common chronic inflammatory disease, which involves the mucous membranes of the oral cavity, with an overall age-standardized prevalence of 1.27% (0.96% in men and 1.57% in women) as reported in the literature by McCartan and Healy. In our previous work, we exploited a bioinformatics approach, namely the Leader Gene Algorithm (LGA), enabling to underpin the main hub genes (termed as Leader Genes) involved in biological processes. In the case of OLP, we found a complex network made up of 132 genes and, in particular, we found five Leader Genes (namely, JUN, EGFR, FOS, IL2, and ITGB4). Using a subsequent bioinformatics algorithm, we managed to find the 48.39% of the already established OLP-related microRNAs (miRNAs), suggesting that at least half of the OLP-related microRNAome (miRNAome) finely tunes few, highly interconnected hub genes. Now, we would use real clinical samples in order to validate our predicted biomarkers. using molecular biology techniques, mass-spectrometry (MS) and ad hoc in-house developed instruments, such as nanoconductimetry via Quartz Crystal Microbalance with Dissipation factor monitoring (QCM_D). A unique combination of genomics and proteomics approaches can indeed represent a promising innovation for a personalized treatment of OLP and oral cancer.
机译：口腔扁平苔藓（OLP）是一种常见的慢性炎性疾病，涉及口腔粘膜，按年龄分类的总体患病率为1.27％（男性为0.96％，女性为1.57％），据文献报道麦卡丹（McCartan）和希利（Healy）。在我们之前的工作中，我们利用了一种生物信息学方法，即前导基因算法（LGA），可以支持生物过程中涉及的主要枢纽基因（称为前导基因）。对于OLP，我们发现了一个由132个基因组成的复杂网络，尤其是发现了五个Leader基因（即，JUN，EGFR，FOS，IL2和ITGB4）。使用后续的生物信息学算法，我们设法找到了48.39％的已建立的与OLP相关的microRNA（miRNA），这表明至少有一半与OLP相关的microRNAome（miRNAome）能够微调很少的，高度相互连接的集线器基因。现在，我们将使用真实的临床样本来验证我们预测的生物标志物。使用分子生物学技术，质谱（MS）和内部专门开发的仪器，例如通过石英晶体微天平和耗散因子监测（QCM_D）进行的纳米电导。基因组学和蛋白质组学方法的独特结合确实可以代表个性化OLP和口腔癌治疗的有前途的创新。

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