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Background and Purpose malignancies no doubt harm to human health. In China, with the aggravation of population aging trend, the overall incidence of cancer is rising, which listed several former were: gastric cancer, esophageal cancer, liver cancer, lung cancer, uterine cancer, colorectal cancer and breast cancer . Due to the improvement of living standards of the people, the lifestyle changes, psychological changes brought about by social pressure, colorectal cancer incidence increased year by year; China is a high incidence of esophageal cancer mortality of malignant forefront. Meanwhile, China's population, the level of economic development is uneven the uneven health education, secondary prevention of malignant tumors, immediate early discovery, early diagnosis, early treatment is still the direction of malignancy. The esophagus and colorectal cancer diagnosis: 1, imaging tests, such as gastrointestinal barium X-ray angiography, CT, MRI, EUS (esophageal endoscopic ultrasound), TRUS (transrectal ultrasound) etc.; 2, endoscopy, gastroscopy, fiber colonoscopy; 3, serological tests, the detection of a variety of tumor markers; 4, other tests, such as genomics check. Above, a variety of methods exist to varying degrees of poor patient compliance, not higher detection sensitivity and specificity. In this study, surface-enhanced laser desorption / ionization time-of-flight mass spectrometer (surface-enhanced laser desorption / ionization-time of flight-mass spectrometry, SELDI-TOF-MS) and isotope labeling relative and absolute quantitation (isobaric tags for relative and absolute quantification, iTRAQ) proteomics technology to establish the diagnosis of colorectal cancer and screening, the diagnosis of esophageal cancer classification tree model, find a more reliable, more direct tumor marker proteins, to explore a more convenient and effective colorectal cancer and esophageal cancer screening, diagnostic methods. Method 1, 1.1 serum samples of the research object modeling group: 35 cases of colorectal cancer, colorectal adeno 14 cases, the knot the proctitis disease 12 cases, 26 cases of esophageal cancer and normal subjects 44 cases. The test group: 30 cases of colorectal cancer, 10 cases of colorectal adenomas, nodal rectitis disease and 10 cases, 10 cases of esophageal cancer and normal subjects 30 cases. 1.2 tissue samples of colorectal cancer tissue and corresponding normal colorectal mucosa tissue in 4 cases, esophageal cancer tissues and corresponding normal esophageal epithelial tissue in 4 cases. 2, the establishment of the classification tree model application of SELDI-TOF-MS technology combined with the copper ion protein chip 35 patients with colorectal cancer, 14 cases of colorectal adenomas, 12 cases of colitis disease, 26 patients with esophageal cancer and 44 cases of normal serum protein spectrum. Analysis of 35 patients with colorectal cancer and 44 patients with normal serum sample application Biomarker Wizard and Biomarker Pattern Software, get a diagnosis of colorectal cancer classification tree model; analysis of 14 cases of colorectal adenomas, 12 cases of colitis disease (colitis STDs) and 44 normal serum samples of colorectal cancer screening classification tree model; diagnosis of esophageal cancer classification tree model analysis of 26 patients with esophageal cancer, 44 cases of normal human serum samples. 3, double-blind verify the classification tree model randomly selected healthy subjects and in patients with colorectal cancer, 30 cases blinded verify the diagnosis of colorectal cancer classification tree model; normal subjects 30 cases, 10 cases of colorectal adenoma and colorectal the proctitis disease 10 cases The blinded validation colorectal cancer screening classification tree model; validate the diagnosis of esophageal cancer classification tree model normal people of the 30 cases, 10 cases of esophageal blinded. Differences in the organization of protein mining applications iTRAQ combination with other proteomics technology to compare tumor and normal tissue of colorectal cancer, esophageal tumors and normal tissue differences in the organization of protein. 5, the comparison compare differences in the organization of the differences in the organization of differences in protein and serum protein protein and serum differential proteins mining association may exist. Results 1 to establish and blinded to verify the diagnosis of colorectal cancer, the screening classification tree model, comparing tumor tissue differences in protein and analysis of its differences with the corresponding serum protein by 35 cases of colorectal cancer, 44 cases of normal human serum samples detection analysis, to establish settled cancer diagnostic model. The model in the test mode, the diagnostic accuracy rate of 87.34%, the sensitivity, specificity, and positive predictive value was 90.91%, 82.86% and 87.88%, respectively, double-blind verify the diagnosis overall accuracy rate of 80%, a sensitivity of 83.33%, The specificity of 76.67%, a positive predictive value of 78.13%, Kappa value of 0.5775. Detection of colorectal adenoma and 14 cases, 44 serum samples knot the proctitis disease 12 cases and normal controls, the establishment of the settlement of of rectal adenomas screening classification tree model. In test mode, the model diagnostic accuracy rate of 91.43%, sensitivity 71.43%, specificity 96.43%, positive predictive value of 92.86%, double-blind verify the accuracy rate of 84.62%, a sensitivity of 60% and a specificity of 100 %. Kappa value of 0.7059. Compare four cases of colorectal cancer tissues with corresponding normal colorectal mucosal tissues, a total of 802 differentially expressed proteins, including 87 protein expression difference was statistically significant (P lt; 0.05). The 87 differentially expressed proteins found in the serum of colorectal cancer and normal differences in protein no significant correlation. 2, to establish the diagnosis of esophageal cancer classification tree model to compare tumor tissue and normal tissue differences in protein and analyzed its difference with the corresponding serum protein by analysis of 26 patients with esophageal cancer and 44 patients with normal serum samples tested to establish the diagnosis of esophageal cancer model. Of these populations are grouped in test mode, the accuracy rate of 75.71%, the sensitivity and specificity were 92.31%, 65.91%, a positive predictive value of 61.53%, double-blind verify the overall accuracy of 72.5%, a sensitivity of 70%, The specificity of 73.33%, a positive predictive value of 46.67%. Kappa value of 0.3476. Compare four cases of esophageal cancer tissues with corresponding normal esophageal epithelium, a total of 802 proteins, including 49 protein expression difference was statistically significant (P lt; 0.05). 49 differentially expressed proteins with esophageal cancer and normal differences found in the serum protein was no significant correlation. Conclusion of colorectal cancer and esophageal cancer during the development of a variety of specific proteins, application of proteomics technology can detect these specific protein, they have the potential to become a new, more effective tumor marker. Same time, these specific proteins reveal colorectal and esophageal carcinogenesis mechanism will play an important role. Broad and bright prospects for the application of proteomics technologies in the mining potential tumor markers, an important value for the screening and diagnosis of malignant tumors, have a positive effect on the secondary prevention of malignant tumors.
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