Cancer Bioinformatics Research: Database Construction Of Copy Number Variation In Prostate Cancer And Biomarkers For Ovarian Cancer Diagnosis

More and more attention has been paid on cancer due to its second mortality rate around the world. It is also a leading cause of death in china. Early diagnosis for the cancer treatment is really important. P4 medical theory which focuses on Predictive, Preventive, Personalized and Participatory has been well recognized as the modern medical concept and technology develop.We have conducted an in-depth research on Personalized and Predictive of P4. Firstly, we have constructed CNVPC-the database of Copy Number Variation in Prostate Cancer-which is designed an online database of copy number variation in prostate cancer based on LAMP technique and B/S framework. All the data are acquired from Pub Med and updated regularly. Our database not only integrates data automatically, but also can be searched by the users, meanwhile they can download the data to save the information. We showed the concept of personalized on every piece of variation data with detailed information which includes sample, patient and experiment platform. Secondly, we have recognized micro RNA as biomarker of ovarian cancer based on micro RNA-m RNA regulatory network. Micro RNA is a kind of non-coding RNA with the function of regulating gene expression. We find out micro RNA by comparing and analyzing the micro RNA data of ovarian cancer patients and normal people. We focus on the independent regulated genes by micro RNA and the genes that regulate the important biological functions(transcription factor). We define two new indicators-NOD&TFP-to quantify the two kinds of the ability above. In the previous research, we find that micro RNA has a strong capacity to regulate gene independently and could regulate more transcription factor gene, so it is more applicable to be the biomarker. We filter out three Micro RNAs, mi R-30 e, mi R-595, mi R-184, as the biomarkers of ovarian cancer. The conclusion has suggested certain reliability through the verification of literature review, ROC curve, clustering analysis and enrichment.These studies have important realistic roles not only for providing the help of personalized cancer treatment but also for expanding the existing theories.