The biobank of the National Medical Research Centre for Oncology as a resource for research in the field of personalized medicine: A review

Abstract

Biobanks are the platform for innovative biomedical research in the field of translational and personalized medicine. The important aspect for conducting large-scale research in the field of genomics, transcriptomics, proteomics is the availability of a sample information of the documented high-resolution samples. The biobanks solve the problem of forming groups of patients with different nosology within the population of interest and provide clinical and laboratory information on each sample. The aim of this article is to describe the Biobank processes of the National Medical Research Centre for Oncology within the framework of existing projects and build up collections. The review discusses the main stages of the systematized biobank process, describes the methods of sample preparation of different types of biological material, and also provides statistics of the build up collections. To this date, the predominant part of the depository consists of tissue samples of patients diagnosed with colorectal cancer 24% and stomach cancer 23% of the total number of tissue samples, while the number of tissue samples of pancreatic cancer is 10%, and esophageal cancer and breast cancer 22%. In addition to tissue samples, the biobank of the National Medical Research Centre for Oncology stores 24 cell lines of a human origin and the collection of 200 microbiota samples: 100 are from patients diagnosed with lung cancer and 100 from conditional healthy donors. Currently, the studies have been performed on biomaterial from the biobank build up collections to search for prognostic biomarkers and potential targets for targeted therapy by using high-throughput sequencing in patients diagnosed with pancreatic cancer and brain cancer. Thus, the collections play an important role for research in the field of personalized medicine, providing early diagnosis and effective treatment for each patient.