An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours

Abstract

Generation of large amounts of genomic data is now feasible and cost-effective with improvements in next generation sequencing (NGS) technology. Ribonucleic acid sequencing (RNA-Seq) is becoming the preferred method for comprehensively characterising global transcriptome activity. Unique to cytoreductive surgery (CRS), multiple spatially discrete tumour specimens could be systematically harvested for genomic analysis. To facilitate such downstream analyses, laser capture microdissection (LCM) could be utilized to obtain pure cell populations. The aim of this protocol study was to develop a methodology to obtain high-quality expression data from matched primary tumours and metastases by utilizing LCM to isolate pure cellular populations. We demonstrate an optimized LCM protocol which reproducibly delivered intact RNA used for RNA sequencing and quantitative polymerase chain reaction (qPCR). After pathologic annotation of normal epithelial, tumour and stromal components, LCM coupled with cDNA library generation provided for successful RNA sequencing. To illustrate our framework's potential to identify targets that would otherwise be missed with conventional bulk tumour sequencing, we performed qPCR and immunohistochemical technical validation to show that the genes identified were truly expressed only in certain sub-components. This study suggests that the combination of matched tissue specimens with tissue microdissection and NGS provides a viable platform to unmask hidden biomarkers and provides insight into tumour biology at a higher resolution. High-throughput next-generation sequencing (NGS) is a powerful strategy to study cancer progression at the molecular level, where ribonucleic acid sequencing (RNA-Seq) is becoming the preferred method for comprehensively characterising global transcriptome activity 1. By comparing the transcriptomes, differential expression of genes in discrete cell populations can be easily identified. This approach has emerged as a useful tool for characterising the transcriptomes and molecular signatures of tissues-of-interest via RNA or protein profiling, which may reflect their functionality 2. In recent years, large genomic consortiums such as The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) have been established 1. With these publically available large-scale integrated data, much effort have been placed into identifying putative prognostic biomarkers using NGS, however, few have made it to clinical practice 3. A plausible reason for this could be due to the

Laser Capture Microdissection of Single Neurons with Morphological Visualization Using Fluorescent Proteins Fused to Transmembrane Proteins

“…RNA integrity numbers for two samples reached 7.5 and 7.2 ( Schroeder et al, 2006 ). These values indicate a good quality of RNA, which is typically obtained by laser capture methods and is sufficient for downstream qPCR and transcriptomic applications ( Butler et al, 2016 ; Ong et al, 2020 ). Thus, we validated that our hydration, laser capture, and RNA isolation method produce good-quality RNA.…”

Opioid Receptor Expression in Colorectal Cancer: A Nested Matched Case-Control Study

“…Altogether, this highlights the importance of tissue composition in data generation and the need to correctly define the extraction source to compare different experiments. The method of laser-capture microdissection (LCM) is an option to procure subpopulations of tissue cells under direct microscopic visualization to use in the following procedures ( 34 , 35 ). These methodological issues are well documented in the literature, but there is no established standard yet ( 36 ).…”

Single‐cell RNA‐sequencing of retrieved human oocytes and eggs in clinical practice and for human ovarian cell atlasing

“…Typically, LCM has been used to isolate whole tumors and their associated cells compared to control regions of a fixed histology slide for transcriptomic characterization (Gómez-Cuadrado et al, 2022;Ong et al, 2020). This technique has been co-opted for use in the ovary to collect single oocytes for RNA sequencing (Ernst et al, 2017).…”