Project description
This project establishes a unified quality control standard for biological sample collection of gastric cancer based on the characteristics and disease types of gastric cancer in China. It is based on the big data of multi recombination science (including primary and post metastasis transcriptome, genomics, proteomics, intestinal microbiome, and clinical real world big data), combined with bioinformatics analysis and artificial intelligence analysis based on deep learning, Establish a new method for high-precision identification of genes and epigenetic information related to the pathogenesis and metastasis of gastric cancer, provide personalized treatment plans for gastric cancer through precise molecular typing, and establish a comprehensive gastric cancer risk assessment, precise treatment, and standardized clinical application analysis report system through big data sharing cloud platform, benefiting gastric cancer patients. Based on the large sample of life omics big data of gastric cancer in China, we will develop new technologies and methods for high-precision identification of genes and epigenetic information related to the pathogenesis and metastasis of gastric cancer. We will draw genetic and epigenetic characteristic maps specific to various subtypes of gastric cancer, and verify the molecular and clinical characteristics and mechanisms of recurrence and metastasis of each subtype in the molecular typing of gastric cancer genes, Screening specific molecular markers and drug targets that can be used for precise clinical diagnosis and treatment, constructing a full chain technology system for precise diagnosis and treatment of gastric cancer, and developing a standardized clinical application analysis system. The research focuses on (1) establishing unified quality control standards and inclusion standards for the collection of gastric cancer biological samples, improving and integrating a highly unified biological resource large sample library, (2) building a network cloud platform for big data storage, transmission, analysis, sharing, and personalized diagnosis and treatment decision-making and evaluation, (3) determining high-precision and sensitive molecular typing standards for gastric cancer, Draw genetic and epigenetic characteristic maps specific to various subtypes of gastric cancer (4) Construct a full chain technology system for precise diagnosis and treatment of gastric cancer, and develop a standardized clinical application analysis system. According to the large sample of systematic and accurate molecular typing of gastric cancer patients, gastric cancer seriously endangers the people's health in China. According to the "2017 Latest Report on the Current Situation and Trend of Cancer in China", academician He Jie, director of the National Cancer Center, its incidence rate ranks second in male cancer and fourth in female cancer, while its mortality rate is second in male and female cancer, with a trend of youth, mostly occurring in the 35-55 age group. The 5-year relative survival rate of gastric cancer patients in China is only 27%, which is closely related to the high metastasis, high mutation, drug resistance caused by the diversity of gastric cancer causes, the heterogeneity of genome and phenotype, the reversibility of epigenetic modification, and the oneness of treatment methods. There is no systematic and precise molecular typing study on large samples of gastric cancer patients. How to efficiently apply multi recombination big data for integration and mining is the key to accurate diagnosis and treatment of gastric cancer, which has practical urgency.