Gene composition, kit and method used for detecting pulmonary adenocarcinoma KRAS mutation
A technique for lung adenocarcinoma and composition is applied in the field of gene composition for detecting KRAS mutation of lung adenocarcinoma, which can solve the problems of high cost, low accuracy, cumbersome process and the like, and achieves high accuracy, good sensitivity and specificity, Easy-to-use effects
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Embodiment 1
[0028] Example 1: Sensitivity and specificity of gene composition for detecting KRAS mutation in lung adenocarcinoma
[0029] To construct a scoring model for detecting KRAS mutations in lung adenocarcinoma, the steps are as follows:
[0030] 1. The gene expression data of 510 cases of lung adenocarcinoma samples were obtained from the TCGA database, which were divided into KRAS mutation, EGFR mutation and wild group, and the differential genes of the three groups were screened out through the R language limma package.
[0031] 2. Select the 56 genes with the strongest correlation with KRAS mutation among the modules most related to KRAS gene mutation through WGCNA.
[0032] 3. Screen 25 genes by Lasso regression: ELN, PODN, LAMC3, COL5A3, CRYAB, SOX18, AKT3, FAM101B, TIE1, SH3PXD2A, EXOC3L2, NOTCH1, NDST1, MMRN2, SH3RF3, ZMIZ1, RNF122, FLT4, F10, TLN1 , SOX17, PIP5K1C, TMEM255B, WSCD1, PCDHB3.
[0033] 4. Determine the threshold value of each gene through the ROC curve, as ...
Embodiment 2
[0041] Embodiment 2 clinical trials
[0042] 47 samples of lung adenocarcinoma were collected from the Thoracic Surgery Department of Zhongshan Hospital affiliated to Fudan University for gene sequencing, and the gene expression data were divided into two groups according to the Score scoring model. The cut-off value of cancer is non-KRAS mutation group, and its sensitivity and specificity are shown in Table 3.
[0043] table 3
[0044] Clinical detection of KRAS mutation+ Clinical detection of KRAS mutations - Predicted KRAS mutation+ 9 4 Predicted KRAS mutation- 1 33
[0045] It can be seen from Table 3 that the sensitivity is 0.90 and the specificity is 0.89. Clinical trials have verified that the lung adenocarcinoma KRAS mutation scoring model constructed by the genetic composition of the present invention has high accuracy, good sensitivity and specificity for detecting lung adenocarcinoma KRAS mutations .
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