Villaamil V Medina, Gallego G Aparicio, Caínzos I Santamarina, Ruvira L Valbuena, Valladares-Ayerbes M, Aparicio L M Antón
INIBIC, CHU A Coruña. A Coruña, Spain;
Int J Biomed Sci. 2011 Dec;7(4):273-82.
Renal cell carcinoma is the most common type of kidney cancer. A better understanding of the critical pathways and interactions associated with alterations in renal function and renal tumour properties is required. Our final goal is to combine the knowledge provided by a regulatory network with experimental observations provided by the dataset.
In this study, a systems biology approach was used, integrating immunohistochemistry protein expression profiles and protein interaction information with the STRING and MeV bioinformatics tools. A group consisting of 80 patients with renal cell carcinoma was studied. The expression of selected markers was assessed using tissue microarray technology on immunohistochemically stained slides. The immunohistochemical data of the molecular factors studied were analysed using a parametric statistical test, Pearson's correlation coefficient test.
Bioinformatics analysis of tumour samples resulted in 2 protein networks. The first network consists of proteins involved in the angiogenesis pathway and the apoptosis suppressor, BCL2, and includes both positive and negative correlations. The second network shows a negative interaction between the p53 tumour suppressor protein and the glucose transporter type 4.
The comprehensive pathway network will help us to realise the cooperative behaviours among pathways. Regulation of metabolic pathways is an important role of p53. The pathway involving the tumour suppressor gene p53 could regulate tumour angiogenesis. Further investigation of the proteins that interact with this pathway in this type of tumour may provide new strategies for cancer therapies to specifically inhibit the molecules that play crucial roles in tumour progression.
肾细胞癌是最常见的肾癌类型。需要更好地理解与肾功能改变和肾肿瘤特性相关的关键途径及相互作用。我们的最终目标是将调控网络提供的知识与数据集提供的实验观察结果相结合。
在本研究中，采用了系统生物学方法，将免疫组织化学蛋白质表达谱和蛋白质相互作用信息与STRING和MeV生物信息学工具相结合。对一组由80例肾细胞癌患者组成的样本进行了研究。使用组织微阵列技术在免疫组织化学染色的玻片上评估所选标志物的表达。使用参数统计检验（Pearson相关系数检验）分析所研究分子因子的免疫组织化学数据。
对肿瘤样本的生物信息学分析产生了2个蛋白质网络。第一个网络由参与血管生成途径的蛋白质和凋亡抑制因子BCL2组成，包括正相关和负相关。第二个网络显示p53肿瘤抑制蛋白与4型葡萄糖转运蛋白之间存在负相互作用。
全面的途径网络将有助于我们认识途径之间的协同行为。代谢途径的调控是p53的重要作用。涉及肿瘤抑制基因p53的途径可调节肿瘤血管生成。进一步研究在这类肿瘤中与该途径相互作用蛋白质可能为癌症治疗提供新策略，以特异性抑制在肿瘤进展中起关键作用的分子。
