An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis\xa0on Matched Primary and Metastatic Colorectal Tumours

Choon Kiat Ong,Chin-Ann Johnny Ong ,Hui Jun Lim,Tony Kiat Hon Lim,Weng Khong Lim,Wai Har Ng,Josephine Hendrikson,Grace Hwei Ching Tan ,Kelvin K.n Koh ,Oi Lian Kon,Khee Chee Soo,Joey Wee-Shan Tan ,Seettha D Wasudevan,Cedric Chuan‐Young Ng ,Vikneswari Rajasegaran,Qiu Xuan Tan,Nicholas B Shannon,Bin Tean Teh,Claramae Shulyn Chia,Marissa Teo

doi:10.1038/s41598-019-55146-2

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.

Highlights

Laser capture microdissection (LCM) is a unique method which allows the segregation of pure cell populations from defined anatomical locations instead of whole tumour biopsies[9]
Given limited tissue quantity of early neoplastic lesions, maximising genetic and molecular information obtained from these tissue specimens represents a vital technical challenge. These findings suggest that in the era of next generation sequencing (NGS) and large consortiums, a fraction of samples should be subjected to LCM before transcriptomics analysis to enable the identification of robust targets
In principle, a method that reliably produces high quality RNA from fresh-frozen colorectal and Krukenberg microdissected matched specimens that are amenable to transcriptome profiling that has not been demonstrated before

Summary

Introduction

Laser capture microdissection (LCM) is a unique method which allows the segregation of pure cell populations from defined anatomical locations instead of whole tumour biopsies[9]. A feasible approach using targeted LCM that precisely captures areas of interest to achieve accurate RNA sequencing with minimal starting material is pertinent in light of the challenges of procuring adequate amounts of tissue samples. In this protocol paper, we aim to demonstrate a validated workflow incorporating LCM for robust transcriptomics analysis in the era of NGS compared to the conventional bulk tumour sequencing. The optimized workflow for RNA isolation and sequencing from LCM samples of matched normal mucosal, colorectal and Krukenberg tumours was determined. To determine if LCM samples performed better compared to whole tumour samples, qPCR analyses on both microdissected and non-microdissected matched trios of normal-primary-metastatic samples were conducted

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Conclusion