Prognostic recurrence detection marker tool for patient suffering from papillary renal cell carcinoma and construction of risk assessment model of prognostic recurrence detection marker tool
A risk assessment model, technology of renal cell carcinoma, applied in the determination/testing of microorganisms, DNA/RNA fragments, recombinant DNA technology, etc., can solve the problems affecting the process of angiogenesis, impact, etc.
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Embodiment 1
[0028] The establishment of a prognostic recurrence risk assessment model for patients with papillary renal cell carcinoma includes the following steps:
[0029] (1) Selection of test data: Collect all miRNA expression profiles and their related pRCC clinical information from the TCGA database, where the clinical information includes OS and RFS, and randomly divide these patients into two parts, namely training and validation groups, of which 202 Patients were assigned to the training cohort, while the remaining 86 patients were assigned to the internal validation cohort;
[0030] (2) Identification of differentially expressed miRNAs: LIMMA analysis was used to evaluate and compare the differences in miRNA expression between pRCC tissues and normal tissues. First, univariate Kaplan-Meier (K-M) survival analysis was performed to detect whether each miRNA was significantly associated with OS or RFS in pRCC patients. correlation, and then extract the relevant miRNAs as candidate ...
Embodiment 2
[0036] Identification of pRCC and normal tissue DEmiRs based on Example 1 above:
[0037] First, principal component analysis (PCA) revealed that tumor tissues differed from normal tissues in their transcriptomes ( figure 1 A). Subsequently, differential genetic analysis (DEG) was obtained from the training set column of the TCGA database by LIMMA analysis. A total of 92 up-regulated miRNAs were screened out (fold change>2, Pfigure 1 B), in which the highest expressed miRNA was miR-599, which was up-regulated by 4.41 times in tumor tissue compared with the normal group; similarly, another 101 down-regulated miRNAs were screened out (fold change figure 1 B), miR-184 was down-regulated about 5.35-fold in tumor tissues compared with normal tissues.
[0038] Example 2:
[0039] Establishment of miRNA markers associated with OS and RFS prediction in papillary renal cell carcinoma:
[0040] Based on the above Example 1, OS and RFS-related miRNAs were screened out in the pRCC pati...
Embodiment 3
[0051] OS and RFS Analysis:
[0052] Based on Example 1 above, K-M curves were used to assess whether miRNA predictive markers could distinguish differences in OS or RFS between low-risk and high-risk groups; as image 3 According to the miRNA formula related to OS prediction, pRCC patients in the training set and validation set were divided into low-risk group or high-risk group, and the overall survival of patients in the low-risk group and higher-risk group in the training set was significantly prolonged (P image 3 A), also showed similar results in the validation set (P=0.002) ( image 3 B). According to the miRNA formula related to RFS prediction, the recurrence-free survival rate of patients in the high-risk group and the low-risk group in the training set was shortened, (P=0.00091)( image 3 C), also showed similar results in the validation set (P=0.0063) ( image 3 D).
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