Multiomic integrative analysis is an effective strategy to facilitate the investigation of molecular mechanism, cause, and early intervention of specific diseases. Gastric cancer is specifically chosen for our research target to decrease its incidence and improve survival. To increase precision diagnosis, prognosis and precision therapy, patients from Taiwan are selected as cohort subjects. The aim of this study is to establish multiomic big data under strictly collected clinical samples from tumors, adjacent normal tissue, blood, and clinical data then analyze by using integrated proteomics and genetics platform. Genome, transcriptome, genomic methylation, proteomics, and post-translational modification will be used to construct a map for determine the in-depth carcinogenesis of gastric cancer and strategies for cancer early diagnosis, prevention, and targeted treatments.
The aim of this study is to establish multiomic big data under strictly collected clinical samples from tumors, adjacent normal tissue, blood, and clinical data then analyze by using integrated proteomics and genetics platform.