Clinical Information Mining And Tissue Microarray Researches For High-risk Population Of Colorectal Carcinoma

Background and Objective High-risk population of colorectal carcinoma (CRC) is the population that includes high-risk individuals with the occurrence of CRC pre-cancerous alterations and high probability of CRC exposed or exposing on the various risk factors. As its individual is in the pre-cancerous stage, the high-risk population of CRC is considered the important early preventive objects of CRC. However, due to the particularities of human objects and limits of current research techniques and methods, the CRC high-risk population is not studied well. On the one hand, the research data sources of CRC high-risk population is not easy to take, the large sample studies are very few and the clinical and pathological characters are realized little, and it is also still the main difficult how to screen the CRC high-risk individuals effectively and exactly from nature population.On the other hand, the conventional molecular pathology and molecular biology methods do not meet the needs of macrobiological researches of CRC high-risk population, and many tumor related genes and biomarkers are not profiling on the CRC high-risk population and the reasonable screen and diagnostic biomarkers are still not found, and it is very difficult to scientifically evaluate or predict the real CRC risk of individuals.The aims of this research are as follow: (1) to establish a new method to collect and analyze large quantity and high quality case data of CRChigh-risk population by the modem information technology; (2) with the new method, to analyze the clinical and pathological features and evaluate the early clinical diagnostic value of the existent CRC high-risk individual screen strategies; (3) to create a novel method of tissue microarray to resolve the technique problems and meet the high-through put need with high-risk population study and tissue sample exam; (4) to research the profiling expression pattern of some colorectal tumor related genes and proteins in high-risk population of CRC by with the novel TMA technology for providing the basic ideas and methods of molecular screen and risk prediction of CRC high-risk population.Method (1) Clinical information characteristics of CRC high-risk cases were studied with the computer database technology and modern medical information coding and data mining methods. A quicker, more scientific and accurate case information collecting and mining method for CRC high-risk individual was established and a related computer management system was researched and evaluated by software engineering method and application test. (2) The clinical and pathological case information of CRC high-risk individuals were gathered and a population based case-control study was performed between and within three colonoscopic examinate groups of field screening, health examination and surveillance, and clinical symptomatic consultation. The distributions of age, gender and detective conditions of pre-cancerious alterations and CRC, as well as the relationship of pathological conditions and ages were analyzed between and within the three groups to evaluate the existent strategies of colonoscopy for CRC high-risk population. (3) To make up the inadequacy of existent method of TMA, a mew methodology of TMA, which is convenient, high-tech and well applicable, was designed to profile the colorectal tumor related molecules in CRC high-risk population and CRC patients.Results (1) A new concept of "case record element" was proposed and the clinical case information of CRC and its high-risk population was elementized and standardized by the new idea. ( 2 ) A record element-database linkage (REDL) computer case information management system (REDL system) was also designed and programmed. (3) With the REDL system, the clinical, endoscopic and pathological data of 2627 colorectal neoplasm cases in Nanfang Hospital were collected and transformed to analyze automatically through computer trials. (4 ) Compared with the Word file case records, the system is significantly quicker on average case information i...