Colon cancer diagnostic marker and application thereof
A diagnostic marker, colon cancer technology, applied in the direction of measuring devices, instruments, scientific instruments, etc., can solve the problems of high difficulty in sample acquisition, unsuitable for early screening of diseases, etc., achieve good clinical application value, improve detection convenience, The effect of promoting standardization
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Embodiment 1
[0024] Screening of urine differential metabolites between colon cancer patients and healthy individuals
[0025] 1. Collection and grouping of urine samples:
[0026] According to the pre-experimental design, the biomedical engineering laboratory of China Pharmaceutical University collected urine samples from 32 cases of colon cancer patients and 58 cases of healthy people, according to standardized and reasonable operation procedures, strictly followed the relevant scientific research ethics requirements and Volunteers gave informed consent and informed. 10 mL of mid-morning urine from volunteers was collected and immediately divided into packages (0.5 mL per tube) and stored in a -80°C refrigerator.
[0027] 2. Main reagents and instruments
[0028] Chromatographically pure reagents acetonitrile, formic acid, and methanol were purchased from Merck, Germany, and pseudouridine, N 2 ,N 2 -Dimethylguanosine, Kynurenine, Valine, N-Acetyl-L-Valine, N-Acetyl-L-Glutamic Acid, 5...
Embodiment 2
[0052] Construct a ROC curve to compare the ability of 16 markers to distinguish colon cancer patients from healthy people
[0053] Binary logistic regression was performed using SPSS software, the level of each metabolic marker was set as a covariate, the group was set as a dependent variable, and the regression method was direct entry. After all the variables were introduced into the regression model, the regression equation of the optimal Logistic prediction model of disease occurrence was obtained according to the regression coefficient (B). After obtaining the tumor occurrence probability P value of each sample by the Logistic regression formula, the receiver operating characteristic analysis was continued on the probability P value. Select different values in the range of 0-1 as the critical P value, compare the P value calculated by the above test sample with the critical P value, and calculate the predictive sensitivity and specificity for tumor occurrence under the ...
Embodiment 3
[0062] Application of 16 Markers in Colon Cancer Screening
[0063] In addition, 20 cases of urine samples from patients diagnosed with colon cancer and 20 cases of normal people were selected, and the samples were prepared according to the method described in Example 1, and the metabolites of the urine samples were qualitatively analyzed by LC-MC. Quantitative determination. In this implementation case, 16 marker combinations with the best diagnostic performance were selected. The quantitative data of 16 kinds of markers are brought into the regression equation of the Logistic prediction optimal model obtained by Example 2, and the negative and positive samples are judged according to the calculated Logit (P) value and the size of the cutoff value, if Logit (P ) value is higher than the cut-off value, it is judged as positive (colon cancer), otherwise, it is judged as negative (normal person). The diagnostic results of a total of 40 samples are shown in Table 3.
[0064] T...
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