| 孔 明,陈 雯,刘坤坤,王 哲,陈 玮.PD-1、PD-L1的表达与肺癌临床病理特征及预后的相关性分析[J].现代生物医学进展英文版,2020,(15):2904-2909. |
| PD-1、PD-L1的表达与肺癌临床病理特征及预后的相关性分析 |
| Correlation of PD-1, PD-L1 Expression with the Clinicopathological Characteristics and Prognosis of Lung Cancer |
| Received:March 06, 2020 Revised:March 31, 2020 |
| DOI：10.13241/j.cnki.pmb.2020.15.021 |
| 中文关键词: 肺癌 程序性死亡因子-1 程序性死亡1-配体 临床病理特征 预后 |
| 英文关键词: Lung Cancer Programmed death factor-1 Programmed death 1-ligand Clinicopathological features Prognosis |
| 基金项目:山东省自然科学基金项目(ZR2015HL130) |
| Author Name | Affiliation | E-mail | | KONG Ming | Thoracic surgery, Shandong otolaryngology Hospital Affiliated to Shandong University (West Hospital of Shandong Provincial Hospital), Ji'nan, Shandong, 250022, China | rtfg25fkk@163.com | | CHEN Wen | Thoracic surgery, Shandong otolaryngology Hospital Affiliated to Shandong University (West Hospital of Shandong Provincial Hospital), Ji'nan, Shandong, 250022, China | | | LIU Kun-kun | Thoracic surgery, Shandong otolaryngology Hospital Affiliated to Shandong University (West Hospital of Shandong Provincial Hospital), Ji'nan, Shandong, 250022, China | | | WANG Zhe | Thoracic surgery, Shandong otolaryngology Hospital Affiliated to Shandong University (West Hospital of Shandong Provincial Hospital), Ji'nan, Shandong, 250022, China | | | CHEN Wei | Department of Anesthesiology, Shandong otolaryngology Hospital Affiliated to Shandong University (West Hospital of Shandong Provincial Hospital), Ji'nan, Shandong, 250022, China | |
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| 中文摘要: |
| 摘要 目的：分析程序性死亡因子-1(PD-1)、程序性死亡1-配体(PD-L1)的表达与肺癌临床病理特征及预后的相关性。方法：回顾性分析我院2015年3月~2016年6月收治的73例肺癌患者的临床资料，取距离切除肿瘤边缘3cm内的非癌组织作为癌旁组织。比较两组PD-1、PD-L1的表达，分析其和肺癌患者临床病理特征和预后的关系，采用COX比例回归分析肺癌患者预后的影响因素。结果：肺癌组织PD-1、PD-L1阳性表达率均显著高于癌旁组织(P<0.05)。不同性别、年龄、病理类型、吸烟情况、EGFR表达、肿瘤大小肺癌患者PD-1、PD-L1的阳性表达率比较差异无统计学意义(P>0.05)；低分化程度、临床分期III及IV期、有淋巴结转移肺癌患者PD-1、PD-L1阳性表达率分别高于中分化程度、临床分期III期、无淋巴结转移患者，差异有统计学意义(P<0.05)。PD-1、PD-L1阳性表达及阴性表达组无疾病进展生存期比较均有统计学差异(P<0.05)。COX比例风险回归模型显示分化程度、临床分期、淋巴结转移、PD-1、PD-L1的表达是影响肺癌患者预后的危险因素(P<0.05)。结论：肺癌组织PD-1、PD-L1呈高表达，可能参与肺癌的发生发展，有助于病情严重程度的评价和预后预测。 |
| 英文摘要: |
| ABSTRACT Objective: To analyze the correlation of the expression of programmed death factor -1(PD-1) and programmed death 1- ligand (PD-L1) with the clinicopathological features and prognosis of lung cancer. Methods: The clinical data of 73 patients with lung cancer admitted to our hospital from March 2015 to June 2016 were retrospectively analyzed. Non-cancerous tissues within 3cm from the edge of the resected tumor were taken as paracancerous tissues. The expressions of PD-1 and PD-L1 in the two groups were compared, and the relationship between PD-1 and PD-L1 expression and the clinicopathological features and prognosis of lung cancer patients were analyzed. COX proportional regression was used to analyze the influencing factors of prognosis of lung cancer patients. Results: The positive expression rates of PD-1 and PD-L1 in lung cancer tissues were significantly higher than those in the adjacent tissues (P<0.05). There was no significant difference in the positive expression rates of PD-1 and PD-L1 between patients with lung cancer of different sex, age, pathological type, smoking status, EGFR expression and tumor size (P>0.05). The positive expression rates of PD-1 and PD-L1 in patients with low differentiation degree, clinical stage III and IV, and lung cancer with lymph node metastasis were higher than those in patients with medium differentiation degree, clinical stage I and II, and without lymph node metastasis(P<0.05). There were significant differences in the disease-free progression survival time between PD-1 and PD-L1 positive and negative expression groups (P<0.05). COX proportional hazards regression model showed that differentiation degree, clinical stage, lymph node metastasis, PD-1, PD-L1 expression were risk factors affecting the prognosis of lung cancer patients (P<0.05). Conclusion: PD-1 and PD-L1 are highly expressed in lung cancer tissues, which may participate in the occurrence and development of lung cancer and contribute to the evaluation of disease severity and prognosis prediction. |
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