Abstract

BackgroundThe methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. The benefit gained from the higher tissue specificity realized through LCM sampling is evaluated in this study through a comparison of microarray expression profiles obtained from same-samples using bulk and LCM processing.MethodsExpression data from ten lung adenocarcinoma samples and six adjacent normal samples were acquired using LCM and bulk sampling methods. Expression values were evaluated for correlation between sample processing methods, as well as for bias introduced by the additional linear amplification required for LCM sample profiling.ResultsThe direct comparison of expression values obtained from the bulk and LCM sampled datasets reveals a large number of probesets with significantly varied expression. Many of these variations were shown to be related to bias arising from the process of linear amplification, which is required for LCM sample preparation. A comparison of differentially expressed genes (cancer vs. normal) selected in the bulk and LCM datasets also showed substantial differences. There were more than twice as many down-regulated probesets identified in the LCM data than identified in the bulk data. Controlling for the previously identified amplification bias did not have a substantial impact on the differences identified in the differentially expressed probesets found in the bulk and LCM samples.ConclusionLCM-coupled microarray expression profiling was shown to uniquely identify a large number of differentially expressed probesets not otherwise found using bulk tissue sampling. The information gain realized from the LCM sampling was limited to differential analysis, as the absolute expression values obtained for some probesets using this study's protocol were biased during the second round of amplification. Consequently, LCM may enable investigators to obtain additional information in microarray studies not easily found using bulk tissue samples, but it is of critical importance that potential amplification biases are controlled for.

Highlights

  • The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling

  • The results presented in this study should provide investigators with the information necessary to critically assess the value of Laser capture microdissection (LCM)-coupled microarray expression profiling of lung adenocarcinoma, and determine if this approach would benefit their research goals

  • The average probeset expression value across all six bulk normal samples was compared to the average probeset expression value across all six LCM normal samples, and likewise for the cancer samples, identifying 387 probesets in normal tissue and 500 probesets in cancer tissue with significantly varied expression levels

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Summary

Introduction

The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. Microarray gene expression profiling is extensively used to study the etiology of disease and identify differential expression between two states This high-throughput technology simultaneously measures expression levels in thousands of transcripts, providing a snapshot of the molecular makeup of a sample. LCM is a precise extraction method that targets and extracts single cells from a sample [1,2,3,4,5,6,7] Using this technology, a homogeneous collection of thousands of cells can be acquired and used to generate an accurate gene expression profile for a target tissue

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