摘要
目的探讨人胰腺星状细胞(PSCs)的新型分离方法。方法通过gentleMACS“组织处理器.恒温震荡消化制备正常胰腺组织、胰腺癌组织的单细胞悬液。通过密度梯度离心法分离获得静息态和活化态的PSCs。结果通过新型的分离法,1g人正常胰腺组织能够获得约(2.6±0.7)×10^6个静息态PSCs,平均活率约为90.0%,细胞形态符合典型的静息态特征,328Jim激发波长下可观察到短暂蓝绿色自发荧光;1g人胰腺癌组织能够获得约(4.1±1.1)×10^6个活化状态的PSCs,平均活率约为92.0%,活化态的细胞均表达d一平滑肌肌动蛋白(α-SMA)、波形蛋白(vimentin)、成纤维细胞特异性蛋白1(FSP-1)等特征性标记。结论本研究所用新型分离方法,适用于静息态与活化态两种表型的PSCs,不但分离纯度较高,分离时间亦极大缩短,值得推广借鉴。
Objective To explore a new'method for the separation of human pancreatic stellate cells. Methods Single-cell suspension of normal pancreatic tissue and pancreatic cancer tissue was pre- pared by gentle MACSTM tissue processor-constant temperature shaking digestion. Human pancreatic steUate cells of quiescent and activated state were isolated by density gradient centrifugation. Results A new type of isolation method could obtain about (2.6 ± 0.7) × 10^6 quiescent pancreatic stellate cells in 1 g of human normal pancreatic tissue, with a viability of about 90. 0%. The morphology of the cells were conformed to the representative for the quiescent state characteristics and transient blue-green autofluorescence was ob- served at the 328 nm excitation wavelength ; 1 g of human pancreatic cancer was able to obtain approximately (4.1 ± 1.1 ) × 10^6 activated PSCs with a viability of 92.0%, and all of the activated ceils expressed α-SMA vimentin, FSP-1 and other characteristic markers. Conclusions The new separation method of this experi- ment is suitable for both human resting and activated human pancreatic stellate cells. At the same time, the purity is high and the separation time is greatly shortened, which is worth promoting.
作者
孟府陶
黄玫
刘振
黄强
Meng Futao;Huang Mei;Liu Zhen;Huang Qiang(Department of General Surgery,Anhui Provincial Hospital,Hefei 230001,China;Hepatobili- ary and Pancreatic Key Laboratory of Anhui Province,Hefei 230001,China)
出处
《中华肝胆外科杂志》
CAS
CSCD
北大核心
2018年第7期455-458,共4页
Chinese Journal of Hepatobiliary Surgery
基金
国家自然科学基金(81501354)
关键词
胰腺星状细胞
人
分离方法
技术改良
密度梯度离心法
Pancreatic stellate cells,- human
Separation method
Technological improvement
Density gradient centrifugation