TP53, P16及K-ras在胆囊高级别上皮内瘤变及早期癌中的表达及随机森林预测模型的建立

Qi Li, Yuhan Wu, Rui Zhang, Chen Chen, Zhiqiang Cai, Shubin Si, Zhimin Geng, Dong Zhang

科研成果: 期刊稿件文章同行评审

2 引用 (Scopus)

摘要

Objective: To explore the different expressions of TP53, P16 and K-ras in gallbladder high-grade intraepithelial neoplasia and early carcinoma, and establish their mutation random forest prediction model. Methods: We retrospectively analyzed the clinicopathological data of 71 patients who underwent cholecystectomy at The First Affiliated Hospital of Xi'an Jiaotong University from January 2013 to December 2018, including 20 cases of chronic cholecystitis, 28 cases of gallbladder high-grade intraepithelial neoplasia, and 23 cases of early gallbladder carcinoma. The immunohistochemical SP method was conducted to detect the expressions of TP53, P16 and K-ras in the gallbladder pathological tissues; the correlation between the above genes and clinicopathological data was analyzed. A random forest prediction model of each gene mutation was established based on the clinicopathological data and gene expression. Results: The positive expressions of TP53, P16 and K-ras were related to the gallbladder with cholecystolithiasis or polyps and gallbladder pathological tissue type. The positive rates of the three genes in the gallbladder polyps were significantly higher than those in the cholecystolithiasis group (P< 0.05). The positive rates of the three genes in the latter two groups of gallbladder high-grade intraepithelial neoplasia and early gallbladder carcinoma were significantly higher than those in the chronic cholecystitis (P< 0.05), while there was no statistical difference between the latter two groups (P> 0.05). The mutations of TP53, P16 and K-ras had a certain correlation (χ2=6.285, 19.595, 4.070, r=0.298, 0.525, 0.239, P< 0.05). TP53, P16 and K-ras mutation prediction models based on random forest had good accuracy (AUC=77.42%, 80.06%, 71.75%, accuracy=76.06%, 76.06%, 67.61%). Conclusion: TP53, P16 and K-ras gene mutations promote the transformation of chronic cholecystitis to gallbladder carcinoma. The mutation prediction model based on random forest has a good accuracy, which can provide an important reference for carcinogenesis and early diagnosis of gallbladder carcinoma.

投稿的翻译标题Expressions of TP53, P16 and K-ras in gallbladder high-grade intraepithelial neoplasia and early carcinoma and establishment of a random forest prediction model
源语言繁体中文
页(从-至)18-24
页数7
期刊Journal of Xi'an Jiaotong University (Medical Sciences)
42
1
DOI
出版状态已出版 - 5 1月 2021

关键词

  • Gallbladder carcinoma
  • Gallbladder high-grade intraepithelial neoplasia
  • K-ras
  • P16
  • Prediction model
  • Random forest
  • TP53

指纹

探究 'TP53, P16及K-ras在胆囊高级别上皮内瘤变及早期癌中的表达及随机森林预测模型的建立' 的科研主题。它们共同构成独一无二的指纹。

引用此