A group of piRNA biomarkers for early diagnosis of breast cancer and its application
A biomarker and breast cancer technology, applied in the fields of molecular biology and oncology, can solve the problems of unclear diagnostic value of expression level and achieve the effect of making up for poor specificity
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Embodiment 1
[0018] Example 1 qRT-PCR detection of piR651, piR17458 and piR20485 levels in serum of breast cancer patients
[0019] Sera from breast cancer patients and healthy individuals were obtained from the Third Affiliated Hospital of Guangzhou Medical University. Serum was placed in a high-speed refrigerated centrifuge at 10,000 rpm for 10 minutes to remove cell debris. RNA was extracted using miRNeasy Serum / Plasma Kit from QIAGEN Company, miScript II RT Kit was used for reverse transcription, and real-time fluorescent PCR experiments were performed with miScript SYBR Green PCR Kit.
[0020] PCR reaction system: 10 μl of 2X SYBR Green PCR mixture, 2 μl of universal primers, 4 μl of RNase free water, 2 μl of cDNA template and 2 μl of corresponding specific piRNA primers. The specific primer sequences are shown in Table 1.
[0021] PCR reaction program: 95°C for 15min; 94°C for 15s, 55°C for 30s, 70°C for 30s, a total of 40 amplification cycles.
[0022] Table 1 qRT-PCR primers
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Embodiment 2
[0025] Example 2 ROC curve analysis of the application value of the combination of piR651, piR17458 and piR20485 in serum in the diagnosis of breast cancer
[0026] SPSS17.0 software was used to analyze the application value of the combination of piR651, piR17458 and piR20485 in the diagnosis of breast cancer. The result is as figure 2 As shown, the ROC curve analysis results show that the combination of piR651, piR17458 and piR20485 in the diagnosis of breast cancer has an AUC area of 0.8113, indicating that the combination of serum piR651, piR17458 and piR20485 has a good clinical value for the diagnosis of breast cancer; at the same time, the ROC curve analysis It shows that the sensitivity and specificity of the combination of piR651, piR17458 and piR20485 in the diagnosis of breast cancer are 67.7% and 84.8%, respectively; the 95% confidence interval is 0.3-0.7, which has the characteristics of good specificity and high sensitivity.
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