Research On Colorectal Cancer Using Metabonomics And Glycomics Technology

Colorectal cancer(CRC) is one of the most common malignant tumors in the digestive tract, which seriously threatens human health. In China, the morbidity and mortality of CRC are increasing year by year, and showing younger trend. The development of CRC is a multi-factor, multi-step process, and the pathogenesis is not yet fully understood. Currently, the overall 5-year survival rate of CRC patient is still less than 60%, and the clinical evaluation and prognostic monitoring of CRC remains to be further improved. Therefore, development of simple and feasible method for CRC diagnosis and prognosis, has become the key issue to improve the survival rate of CRC patient.With the implementation and completion of “Human Genome Project”, it has entered into the era of systems biology for life science. Metabonomics is a rising branch of the systems biology methodology. It mainly study on the metabolic variations of biological systems in different physiological and pathological states, in order to discover the essence of abnormal metabolism. Metabonomics has tremendous development potential in the field of cancer research. As important biological information molecules, the importance of glycan in the life process becomes more and more attractive. Glycomics has provided new idea and vision for the comprehensive understanding of the pathogenesis of cancer.Considering the advantage of “omics technology” for comprehensive research, in this study, a systematical and in-depth research on CRC has been performed based on metabonomics and glycomics platform, respectively. In part one, we performed a detail study on CRC serum metabolic profile on the basis of metabonomcis platform, and investigated the potential metabolic biomarker candidates related to CRC. In part two, we performed a in-depth research on CRC tissue glycome profile by means of lectin microarray-based glycomics technology, and improved a simple platform for glyco-biomarker discovery. We try to do some exploratory research on the connection between metabonomics and glycomics of colorectal cancer. However, the link between this two fields has not yet to be found due to the limitation.The main methods and results are as follows:1. We used the gas chromatography time-of-?ight mass spectrometry(GC-TOFMS) and ultra performance liquid chromatography and quadruple/time-of-flight mass spectrometry(UPLC-QTOFMS) platforms to analysis the serum metabolic profile variations between CRC patients(n=101) and healthy controls(n=102). With the comparative analysis of the two platforms, it was found that mostly metabolites identified by the respective platforms were different. Totally, 249 serum metabolites have been identified based on the combination of GC-TOFMS and UPLC-QTOFMS platforms.2. A robust OPLS-DA model has been established by means of orthogonal partial least square-discriminate analysis(OPLS-DA) based on 249 serum metabolites, which could discriminate all CRC patients(including early stage patients) from healthy controls. And it was confirmed that the OPLS-DA model had a good predictive ability. 72 significant differential metabolites between CRC patients and healthy controls have been selected according to the result of statistical analysis. This study not only confirmed the result of CRC serum metabonomics in our previous study, but also greatly expanded the differential serum metabolites library of CRC. In this study, we systematically observed the metabolite disorder of CRC patient, including glycolysis, amino acid metabolism, tricarboxylic acid cycle(TCA cycle), urea cycle, lipid metabolism, and gut flora metabolism. Notably, it was comprehensively observed the distinct abnormal lipid metabolism in CRC patient.3. Furthermore, 7 typical differential metabolites have been selected as potential CRC diagnostic biomarkers, which related to lipid metabolism, TCA cycle, urea cycle, amino acid metabolism, and gut flora metabolism. In addition, another 4 differnential metabolites have been selected as potential CRC prognostic biomarkers, which also related to TCA cycle, urea cycle, fatty acid metabolism, and amino acid metabolism. It was found that these typical differential metabolites has potential clinical utility.4. We used lectin microarray-based glycomics platform to investigate the tissue glycome profile variations in CRC patients. It was found that the glycome profiling of tumor tissue were significantly different from normal tissue adjacent to cancer. Some differential lectins have been selected to indicate the changes of glycan signal. Furthermore, we found several differential lectins candidates used for distinguishing CRC patient with lymph node metastasis and without lymph node metastasis.5. We improved a simple and effective platform for glyco-biomarker discovery by the combination of tissue array, lectin microarray, and lectin affinitiy capturing. As a proof of our concept, we performed a in-depth and detailed comparative analysis of tissue glycome between CRC patients with good prognoses and poor prognoses. We found some glyco-biomarker candidates for CRC prognosis, and proposed an optimized scheme for target glycoprotein enrichment.In this study, it was designed to investigate the variation characteristics of terminal signal(including metabolites and glycans) caused by CRC based on differential observation window, which aimed to provide some reference for study on the pathogenesis of CRC. And tried to seek some CRC-related biomarker candidate, which might contribute to supply some useful information for early diagnosis, prognosis monitoring, and new medicament research of CRC. In addition, this study provided a new thinking for the application of glycomics in the field of glyco-biomarker discovery.