Metabonomics Study On Colorectal Cancer Using Combined Chromatography-mass Spectrometry Strategy

Colon cancer, also known as colorectal cancer (CRC), is one of the most common malignant tumors in the digestive tract. CRC represents the third leading deaths among the cancers worldwide, and the second in the Western developed countries. In China, the number of new cases and deaths of CRC are rapidly increasing along with the elevation of living standards and the increased consumption of high protein diet. As a multi-factorial and polygenic condition, CRC has complex molecular mechanisms which are not well understood by biomedical scientists and pathologists, and therefore, necessitate systematic investigations. Meanwhile, the clinical efficacy on CRC treatment is highly correlated with the pathological stages of the disease. For example, the five-year survival rate of stage I patient is about 93%, and this number sharply decreases to only about 8% for the stage IV patients. Despite of the apparent benefit on early treatment, there are few proper measures to detect CRC at early stage. The current"golden diagnostic tool", colonoscopy, is not suitable for most of the population due to the cost and inconvenience in clinic use. It is therefore of vital importance to develop alternative or complementary measures for early diagnosis of CRC.Metabonomics/ metabolomics is a newly developed approach, as an integral part of the systems biology encompassing a number of omics sciences such as genomics, transcriptomics and proteomics, and has become one of the hottest subjects worldwide. Metabonomics uses multivariate statistical technique to analyze highly complex data sets generated by high-throughput spectroscopy such as nuclear magnetic resonance (NMR) and mass spectrometry (MS) of biological samples to capture metabolic variations in response to genetic modifications and environmental stimuli. As metabolites in serum and urine contain the general functional information generated by the biochemical regulatory systems in the whole body, metabonomics reveals a systems and dynamic outcome of the development of a pathological state. Therefore, the high-flux metabolic information originated from variations of global metabonome reveals important clues to disease onset and development, and thus, can be used for diagnostic applications such as CRC detection. Meanwhile, the noninvasive or less invasive bio-fluid sample (urine and serum) collection makes such a methodology easy to be adopted in clinical diagnosis or in routine physical examination. In this study, we try to establish chromatography in hyphenation with mass spectrometry metabonomic technology to investigate metabolic variations in precancerous colon rats and CRC patients and to investigate the applicability of such metabonomics method in CRC diagnosis.Main methods and results:1. We used ethyl chloroformate derivatization and gas chromatography-mass spectrometry (GC/MS) based metabonomic analysis of urines from 1,2-dimethylhydrazine (DMH)-induced precancerous colon rats, herbal medicine treated rats and healthy controls. The time-dependent variations of metabolite profile showed a progressive deviation of the metabolism in the model group from the initial pattern over time and a systemic recovery of the metabolism in the treatment group, which is consistent with the histological results. Additionally, the in-depth study of these metabolite alterations also allowed the simultaneous identification of key sites and pathways, such as gut microflora, COX 2 and cytochrome P450, which were closely associated with the herbal medicine treatment.2. We used a GC/MS-based metabonomic approach to investigate the CRC-related pathophysiological variations of the urinary metabolite profiles from 51 CRC patients in comparison to those from 39 age-matched volunteers. A group of metabolites significantly differed in CRC patients from the healthy controls were identified including the decreased levels of succinate, butyrate, citrate, histidine and 2-hydroxyhippurate, and the increased levels of histamine, hippurate, 5-hydroxyindoleacetate and glycine. In addition, such a GC/MS-based metabonomic approach was able to clearly recognize five patients (stage I) from the healthy controls and appeared to reveal a different metabolic pattern of patients at different pathological features (stage II and stage III).3. UPLC/QTOFMS based urinary metabolic profiling method was basically established. By comparing different solvent and dilution fold, we selected 2 fold diluting with pure water of urine as the final pretreatment method. Through this method, the similar separation between urines from CRC patients and healthy controls with GC/MS analysis and a slight better separation between stage II and stage III patients was obtained.4. The GC/TOFMS based serum metabonomic analysis method was optimized. The method validations revealed a wide linearity range, good repeatability and acceptable recovery rate for the proposed method. Based on the established method in this study, sera from CRC patients and healthy controls were analyzed to detect metabolite variations associated with CRC morbidity. The similar separation results were obtained with urine metabolic profiles. After identification of metabolites significantly varied in the CRC patients, oleamide metabolism, anaerobic and aerobic energy metabolism, ornithine metabolism and some other amino acids metabolism were associated with CRC morbidity.Conclusions:1. Using ethyl chloroformate derivatization and GC/MS analysis based urinary metabonomic study, we can visualize time-dependent variations in the DMH-induced precancerous colon rat and the reversal effect of herbal medicine, which reveals great potential of metabonomics used in detection of insight pathological variations and in tracking of the effect of drug intervention.2. Based on GC/MS and UPLC/QTOFMS urine metabonomic analysis, we can precisely distinguish CRC patients from healthy controls including 5 patients of early stage (stage I) and can generally differentiate patients of different pathological stage (stage II and stage III), which reveals great potential of urine metabolic profile in CRC diagnosis.3. The established GC/TOFMS based serum metabonomic analysis method in this research was reliable and stable. Using this method, we can clearly visualize the metabonomic differences in the OPLS-DA model between CRC patients and healthy controls and can even tell apart from patients of different pathological stages (stage II and stage III). 4. From the results of urine metabolic profile of DMH induced precancerous colon rats and biofluids (urine and serum) from CRC patients, we found that oleamide metabolism, energy supply metabolism, tryptophan metabolism, polyamine metabolism, and the altered gut flora structure are closely related to CRC morbidity.