SMARCA4缺失性尿路上皮癌临床病理学分析
SMARCA4-deficient urothelial carcinoma of the urinary tract:a clinicopathological analysis
贾梅 1谢建兰 1张彦宁 1郑媛媛 1郑晓丹 1王琳 1张坤 1陈光勇1
作者信息
- 1. 首都医科大学附属北京友谊医院病理科,北京 100050
- 折叠
摘要
目的 探讨SMARCA4缺失性尿路上皮癌(UC)临床病理特点及其预后.方法 对5例SMARCA4缺失的UC临床病理特点进行分析,包括文献报道的1例,并对其治疗、预后进行讨论.结果 患者平均年龄67岁,以男性为主,均有血尿症状.大体表现为单发、灰白色肿物,局灶出血,界欠清.H&E示瘤细胞低分化;部分表达GATA3、p63及CK7,SMARCA4缺失,Ki-67平均45％.根治性手术治疗后病理显示均为肌层浸润性UC,1例淋巴结转移、2例脉管侵犯.术后生存时间5天～5月,1例存活至今且未见转移(已随访6月),1例失访.此类肿瘤手术治疗效果有限,尚无系统性化疗方案,部分患者免疫检查点抑制剂治疗有效.结论 SMARCA4缺失的UC预后差,需及时诊断,可尝试免疫检查点抑制剂治疗.
Abstract
Objective To study the clinical pathological features and prognosis of SMARCA4-deficient urothelial carcinoma(UC).Methods Five cases of SMARCA4-deficient UC were reviewed,including 1 case reported in literature.We analyzed the clinical pathological features,and discussed the treatment and prognosis of these patients.Results The mean age was 67-year-old,with the predominance of male.All patients had hematuria.The gross examination confirmed a solitary gray white tumor,with focal hemorrhage,and the boundary was not clear.H&E slides demonstrated that tumor cells were poorly differentiated.Tumor cells were focal positive for GATA3,p63 and CK7,with SMARCA4 deficient.The mean Ki-67 index was 45％.All patients applied radical surgery,and pathological reports showed 5 cases were muscle invasion UC.One case showed lymph node metastasis,and two cases showed lymphovascular metastasis.The survival time of patients after surgery varied for 5 days to 5 months,and one patient alive for 6 months with no metastasis detected,and one was lost to follow-up.Literatures showed limited surgical treatment efficacy,and no potent systemic chemotherapy were reported,but these diseases may show unexpected good responses for immune checkpoint inhibition.Conclusion It is important to diagnose SMARCA4-deficient UC in time.The prognosis is poor,but ICI probably effective.
关键词
SMARCA4/SWI/SNF/尿路上皮癌/临床病理特点/治疗Key words
SMARCA4/SWI/SNF/Urothelial carcinoma/Clinical pathological features/Treatment引用本文复制引用
出版年
2024
NETL
NSTL
万方数据