Marker molecule related to endometrial cancer and application thereof in diagnosis of endometrial cancer
A technology of endometrial cancer and diagnosis system, applied in the application field of diagnosis of endometrial cancer, can solve the problems of unpredictable recurrence, low sensitivity, and difficult screening of patients
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Embodiment 1
[0072] Example 1 Screening of biomarkers associated with endometrial cancer
[0073] 1. Screening method
[0074] (1) Screening data and preprocessing methods
[0075]In this example, the data for screening biomarkers related to endometrial cancer were downloaded from the GEO database and the TCGA database, respectively, and the public gene expression data and complete clinical data of endometrial cancer were searched with the keyword "endometrial cancer". Note, in which, the microarray data and clinical information of the GSE17025 dataset were downloaded from the GEO database as a training set, and the sample size was endometrial cancer group: control group=91:12; endometrial cancer RNA- The seq data and clinical information were used as the validation set, and the sample size was endometrial cancer group: control group=543:35;
[0076] Use fastp software double-end sequence automatic detection mode to process the raw data; the minimum N base number threshold is 5, the mini...
Embodiment 2
[0083] Example 2 Verifying and analyzing the diagnostic efficacy of the screened biomarkers
[0084] 1. Validation analysis method
[0085] The receiver operating curve (ROC) was drawn by the R package "pROC", and the biomarkers CDH1, RPS4X, CDH1 that were screened in Example 1 and showed significant differential expression between the control group and the endometrial cancer group were analyzed The AUC value, sensitivity and specificity of +RPS4X were used to judge its diagnostic performance for endometrial cancer. Among them, the gene expression (Log 2 expression) for evaluation and analysis, and the point corresponding to the largest Youden index was selected as its cutoff value, that is, the optimal division threshold was determined by the point with the largest Youden index; In terms of the diagnostic efficiency of cancer, first perform logistic regression analysis on the gene CDH1+RPS4X. In the logistic regression analysis, the independent variable is CDH1+RPS4X, and t...
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