Chrome Extension
WeChat Mini Program
Use on ChatGLM

Clinic-Pathological Characteristics And Prognostic Value Of Pd-L1 And Her2 In Gastric Cancer

DNA AND CELL BIOLOGY(2021)

Cited 6|Views11
No score
Abstract
The aim of this study is to study the relationship between programmed cell death-1 ligand (PD-L1) and human epidermal growth receptor 2 (HER2) and the clinical-pathological features of gastric cancer (GC) and its predictive effect on the prognosis of gastric cancer (GC) patients. A retrospective analysis was performed on 113 patients undergoing GC surgery. The expression of PD-L1 and HER2 in GC and paired adjacent nontumor tissues was detected by immunohistochemistry or fluorescence in situ hybridization, and the relationships between PD-L1 and HER2 expression and clinical-pathological features and survival were analyzed by chi-square analysis, Pearson analysis, logistic regression analysis, Kaplan-Meier analysis, and Cox regression model. PD-L1 and HER2 were expressed in tumor tissues, but not in adjacent nontumor tissues. There was no correlation between the expression of PD-L1 and HER2. The expression of PD-L1 in GC was closely related to gender (p = 0.019), regional lymph node (p = 0.006), metastasis (p = 0.033), and survival status (p = 0.033), while HER2 was closely related to tumor differentiation (p = 0.033), regional lymph node (p = 0.016), and tumor-node-metastasis (TNM) stage (p = 0.036). The survival time of PD-L1-positive patients was longer than that of PD-L1-negative patients (p = 0.020). The expression of HER2 showed no difference in overall survival (p = 0.125). Multivariate analysis suggested that the TNM stage (p = 0.001) and PD-L1 expression (p = 0.047) were independent prognostic factors for survival time of GC. The expression of PD-L1 has biological significance in GC, which is closely related to the clinical-pathological characteristics and prognosis of GC patients.
More
Translated text
Key words
GC, PD-L1, HER2, prognosis, predictive biomarker
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined