title: Laser-capture Microdissection of Human Prostatic Epithelium for RNA Analysis.
abstract: The prostate gland contains a heterogeneous milieu of stromal, epithelial, neuroendocrine and immune cell types. Healthy prostate is comprised of fibromuscular stroma surrounding discrete epithelial-lined secretory lumens and a very small population of immune and neuroendocrine cells. In contrast, areas of prostate cancer have increased dysplastic luminal epithelium with greatly reduced or absent stromal population. Given the profound difference between stromal and epithelial cell types, it is imperative to separate the cell types for any type of downstream molecular analysis. Despite this knowledge, the bulk of gene expression studies compare benign prostate to cancer without micro-dissection, leading to stromal bias in the benign samples. Laser-capture micro-dissection (LCM) is an effective method to physically separate different cell types from a specimen section. The goal of this protocol is to show that RNA can be successfully isolated from LCM-collected human prostatic epithelium and used for downstream gene expression studies such as RT-qPCR and RNAseq.
authors.affiliation: Department of Pathology, University of Illinois at Chicago.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Lugli
authors.affiliation: Department of Pathology, University of Illinois at Chicago.
authors.forename: Yachana
authors.initials: Y
authors.lastname: Kataria
authors.affiliation: Department of Pathology, University of Illinois at Chicago.
authors.forename: Zachary
authors.initials: Z
authors.lastname: Richards
authors.affiliation: Department of Pathology, University of Illinois at Chicago.
authors.forename: Peter
authors.initials: P
authors.lastname: Gann
authors.affiliation: Department of Periodontics, University of Illinois at Chicago.
authors.forename: Xiaofeng
authors.initials: X
authors.lastname: Zhou
authors.affiliation: Department of Pathology, University of Illinois at Chicago; lnonn@uic.edu.
authors.forename: Larisa
authors.initials: L
authors.lastname: Nonn