Abstract 1677: Immuno-target selection of infiltrating immune cells and laser capture microdissection mediated transcriptional profiling

Author(s):  
Ross Haggart ◽  
Chaxiraxi Arzola-Donate ◽  
Elliott Harrison ◽  
Benjamin J. Reed ◽  
Saba Alzabin ◽  
...  
2012 ◽  
Vol 520 (16) ◽  
pp. 3617-3632 ◽  
Author(s):  
Syann Lee ◽  
Angie L. Bookout ◽  
Charlotte E. Lee ◽  
Laurent Gautron ◽  
Matthew J. Harper ◽  
...  

Medicina ◽  
2019 ◽  
Vol 55 (9) ◽  
pp. 520
Author(s):  
Katiane de Almeida da Costa ◽  
Helena Malvezzi ◽  
Bruno Gallani Viana ◽  
Renée Zon Filippi ◽  
Rosa Maria Neme ◽  
...  

Background and Objectives: The presence of endometrial-like tissue outside the uterine cavity is a key feature of endometriosis. Although endometriotic lesions appear to be histologically quite similar to the eutopic endometrium, detailed studies comparing both tissues are required because their inner and surrounding cellular arrangement is distinct. Thus, comparison between tissues might require methods, such as laser capture microdissection (LCM), that allow for precise selection of an area and its specific cell populations. However, it is known that the efficient use of LCM depends on the type of studied tissue and on the choice of an adequate protocol. Recent studies have reported the use of LCM in endometriosis studies. The main objective of the present study is to establish a standardized protocol to obtain good-quality microdissected material from eutopic or ectopic endometrium. Materials and Methods: The main methodological steps involved in the processing of the lesion samples for LCM were standardized to yield material of good quality to be further used in molecular techniques. Results: We obtained satisfactory results regarding the yields and integrity of RNA and protein obtained from LCM-processed endometriosis tissues. Conclusion: LCM can provide more precise analysis of endometriosis biopsies, provided that key steps of the methodology are followed.


2014 ◽  
Vol 9 (8) ◽  
pp. e29427 ◽  
Author(s):  
Yuko Ogo ◽  
Yusuke Kakei ◽  
Reiko Nakanishi Itai ◽  
Takanori Kobayashi ◽  
Hiromi Nakanishi ◽  
...  

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