There have been several notable achievements; however, cancer is an economically and socially burdensome cause of death. The exact mechanisms of tumor initiation and development remain unclear. As the amount of data provided by cost-effective high-throughput technologies increases, multi-omics data integration strategies including genomes, epigenomes, transcriptomes, proteomes, and metabolomes accelerate predictive, preventive, and personalized medicine ultimately enabling precision medicine of cancer.

There are several important points in the collection of tissue samples used in these studies. The ischemia time also plays a major role in the collection of tissue samples, and in the case of large-scale research, tissue samples are stored for a long time and analyzed, which is one of the factors that can have a major impact on the tissue sample quality.

In this presentation, we present a new analytical framework for proteogenomics and evaluate the eligibility of tissues through 18-paired NAT and tumor tissues collected from 2009 to 2017 to discover whether tissues maintain molecular properties at each omics level or between omics over time. Through this, we discuss the sample selection criteria for tissue research and show sufficient tumor characteristics to carry out multi-omics data integration strategies over time.