Abnormal p16 expression and prognostic significance in esophageal squamous cell carcinoma

HISTOLOGY AND HISTOPATHOLOGY(2024)

引用 0|浏览1
暂无评分
摘要
Background. The purpose of this study was to analyze p16 expression status and evaluate whether abnormal p16 expression was associated with prognosis in a large-scale esophageal squamous cell carcinoma (ESCC) cohort of patients.
Methods. We retrospectively evaluated p16 expression status of 525 ESCC samples using immunohistochemistry. Associations between abnormal p16 expression and survival were analyzed.
Results. P16 negative, focal expression and overexpression were found in 87.6%, 6.9% and 5.5% of ESCC patients. No significant association was observed between abnormal p16 expression and age, sex, tumor site and location, differentiation, vessel and nerve invasion, T stage and lymph node metastasis. In all patients, the survival of p16 focal expression group tended to be better compared with negative group (disease free survival/DFS P=0.040 and overall survival/OS P=0.052) and overexpression group (DFS P=0.201 and OS P=0.258), and there was no survival difference between negative group and overexpression group. The multivariate analysis for OS and DFS found that only clinical stage was a significantly independent prognostic factor (P<0.001). When patients were divided into I-II stage (n=290) and III-IVa stage (n=235), the survival of focal expression group was better compared with negative group (DFS P=0.015 and OS P=0.019), and tended to be better compared with overexpression group (DFS P=0.405 and OS P=0.432) in I-II stage ESCC, which was not found in III-IVa stage ESCC.
Conclusion. P16 overexpression or negative expression tend to be associated with unfavorable outcomes, especially in I-II stage ESCC. Our study will help to identify a subgroup of ESCC patients with excellent prognosis after surgical therapy.
更多
查看译文
关键词
P16 focal expression,P16 overexpression,P16 negative,Prognosis,Esophageal squamous cell carcinoma (ESCC)
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要