Site‐specific gene expression analysis from archived human intestine samples combining laser‐capture microdissection and multiplexed color‐coded probes

Background Alterations of site‐specific gene expression profiles in disease‐relevant networks within the different layers of the intestinal wall may contribute to the onset and clinical course of gastrointestinal disorders. To date, no systematic analysis has assessed and compared sub‐regional gene expression patterns in all distinct layers of the gut using fresh frozen human samples. Our aim was to establish an optimized protocol for site‐specific RNA isolation in order to achieve maximum RNA quality and amount for subsequent gene expression analysis combining laser‐capture microdissection (LCM) with a probe‐based technology, the NanoString nCounter Analysis system. Methods Four full‐thickness colon samples from patients who underwent surgery due to pathological conditions were processed and separated into epithelium, lamina propria, myenteric plexus, submucosa, and tunica muscularis by LCM. Site‐specific marker expression by nCounter technology was performed on total RNA from each sub‐region, respectively. Key Results Collecting ~10 mm² (~100 000‐250 000 cells) of tissue from the epithelial layer, lamina propria, and myenteric plexus provided sufficient amounts of RNA of appropriate quality for subsequent analyses. In contrast, ~40 mm² (~250 000‐650 000 cells) of tissue were dissected from the less cell‐rich submucosal and tunica muscularis layer. nCounter analysis revealed a site‐specific expression pattern of marker genes in the different layers of the colonic wall which were highly correlating (r > .9). Conclusions and Inferences LCM in combination with nCounter expression analysis enables site‐specific, sensitive, reliable detection, and quantification of mRNA from histologically heterogeneous tissues. The enrichment of specific cell populations from archived patient specimens is key to nail down their specific role in disease pathogenesis. However, the majority of studies to date have identified diseases‐associated gene expression changes in full‐thickness tissue samples, which may mask the specific contribution of particular cell populations. In this study, we have optimized a laser‐capture microdissection (LCM) procedure to separate full‐thickness tissue samples into epithelium, lamina propria, myenteric plexus, submucosa, and tunica muscularis. Combining LCM with the nCounter technology enabled site‐specific gene expression analysis with minimal cross‐contamination across the different tissue layers.