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Updated: Jun 23, 2026

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment
Published on: June 3, 2022
Gene expression analysis of immunostained endothelial cells isolated from formaldehyde-fixated paraffin embedded
Tomoatsu Kaneko1, Takashi Okiji, Reika Kaneko
1Pulp Biology and Endodontics, Department of Restorative Sciences, Graduate School, Tokyo Medical and Dental University, Yushima 1-5-45, Bunkyo-Ku, 113-8549, Tokyo, Japan. tomoendo@tmd.ac.jp
Abstract:
Laser capture microdissection (LCM) allows microscopic procurement of specific cell types from tissue sections that can then be used for gene expression analysis. In conventional LCM, frozen tissues stained with hematoxylin are normally used to the molecular analysis. Recent studies suggested that it is possible to carry out gene expression analysis of formaldehyde-fixated paraffin embedded (FFPE) tissues that were stained with hematoxylin. However, it is still unclear if quantitative gene expression analyses can be performed from LCM cells from FFPE tissues that were subjected to immunostaining to enhance identification of target cells. In this proof-of-principle study, we analyzed by reverse transcription-PCR (RT-PCR) and real time PCR the expression of genes in factor VIII immunostained human endothelial cells that were dissected from FFPE tissues by LCM. We observed that immunostaining should be performed at 4 degrees C to preserve the mRNA from the cells. The expression of Bcl-2 in the endothelial cells was evaluated by RT-PCR and by real time PCR. Glyceraldehyde-3-phosphate dehydrogenase and 18S were used as house keeping genes for RT-PCR and real time PCR, respectively. This report unveils a method for quantitative gene expression analysis in cells that were identified by immunostaining and retrieved by LCM from FFPE tissues. This method is ideally suited for the analysis of relatively rare cell types within a tissue, and should improve on our ability to perform differential diagnosis of pathologies as compared to conventional LCM.
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