Gene expression measurement technologies: innovations and ethical considerations

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Abstract

Knowledge of the overall gene expression profile within a cell can provide key insights into cellular physiology. Therefore, it is not surprising that a great deal of effort has been devoted to measuring the expression level of all of the genes in a cell. With the advent of DNA microarray technology, researchers now have the ability to collect expression data on every gene in a cell simultaneously. The vast datasets created with this technology are providing valuable information that can be used to accurately diagnose, prevent, or cure a wide range of genetic and infectious diseases. In this article, we describe the key technologies for measuring gene expression and discuss how these approaches can be used to identify the correlation between the observed expression patterns and disease. Additionally, we will highlight the key ethical considerations and discuss how these tremendously powerful technologies may impact society.

Introduction

Knowledge of the overall gene expression profile within a cell can provide key insights into cellular physiology. Therefore, it is not surprising that a great deal of effort has been devoted to measuring the expression level of all of the genes in a cell. With the advent of DNA microarray technology, researchers now have the ability to collect expression data on every gene in a cell simultaneously. The vast datasets created with this technology are providing valuable information that can be used to accurately diagnose, prevent, or cure a wide range of genetic and infectious diseases. Thus, an area of active research is the development of tools to accurately collect, analyze, and interpret massive quantities of data on gene expression levels in the cell. There are several examples in the literature where computational tools have been applied to analyze gene expression data (Marcotte, Pellegrini, Thompson, Yeates, & Eisenberg, 1999; Marcotte, Pellegrini, Yeates, & Eisenberg, 1999; Marcotte et al., 1999; Pellegrini, Marcotte, Thompson, Eisenberg, & Yeates, 1999; McGuire, Hughes, & Church, 2000; Roth, Hughes, Estep, & Church, 1998; Alizadeh, Eisen, Botstein, Brown, & Staudt, 1998; Alter, Brown, & Botstein, 2000; DeRisi et al., 2000; Eisen, Spellman, Brown, & Botstein, 1998; Spellman et al., 1998, Wilson et al., 1999; Sudarsanam, Iyer, Brown, & Winston, 2000; D’Haeseleer, Wen, Fuhrman, & Somogyi, 1999; Bassett, Eisen, & Boguski, 1999; Liang, Fuhrman, & Somogyi, 1998; Chen, He, & Church, 1999; Getz, Levine, & Domany, 2000; Tavazoie, Hughes, Campbell, Cho, & Church, 1999; Michaels et al., 1998, Tamayo et al., 1999), with the most common method being cluster analysis (Eisen et al., 1998).

The technological developments in gene expression measurement are promising, but at the same time it is incumbent upon us to raise numerous ethical concerns. Scientists and engineers who are involved in developing and utilizing gene expression technology have a responsibility to consider ethical issues and are in a key position to take an active role in policy development and other efforts to ensure that gene expression measurement technologies are used ethically. Four important considerations will be discussed in this manuscript: (1) insurance and employment discrimination and issues of individual privacy; (2) fair access to tests and treatments; (3) technological limitations such as accuracy of diagnosis, ability to relate genetic information to a disease, and diagnosis of “untreatable” conditions; and (4) genetic counseling and issues about release of information to patients.

In this article, we will describe the key technologies for measuring gene expression and discuss how these approaches can be used to identify the correlation between the observed expression patterns and disease. Additionally, we will highlight the key ethical considerations and discuss how these tremendously powerful technologies may impact society.

Section snippets

Genome-scale gene expression monitoring technology

A number of technologies have been developed to acquire gene expression information on a “whole transcriptome” level, where the transcriptome is defined as the complete set of all expressed genes (transcripts) in a given cell. The techniques currently in vogue are based on either direct sequence analysis (Weinstock, Kirkness, Lee, Earle-Hughes, & Venter, 1994; Adams, 1996) or specific hybridization of complex cDNA or mRNA probes to microarrays of oligonucleotides or cDNAs (Ramsay, 1998,

Polymerase colony approach

A new technique that minimizes the limitations and maximizes the detection power of other sequencing approaches is polymerase colony (polony) technology. The Church laboratory at Harvard Medical School has demonstrated that in situ polymerase chain reaction can be used to generate clones of single nucleic acid molecules (Merritt et al., 2003; Mitra & Church, 1999; Mikkilineni et al., 2004, Mitra et al., 2003; Zhu, Shendure, Mitra, & Church, 2003; Butz, Wickstrom, & Edwards, 2003; Butz, Yan,

Gene expression analysis and cancer

One potential application of the gene expression technologies discussed above is in detection and classification of cancer. There are hundreds of different types of cancer, and it has been estimated that at least five genes are mutated in a tumor (Hilgers & Kern, 1999). Based on these data, it was subsequently estimated that there are ∼200 different genes that are mutated in different cancers (Wooster, 2000). Furthermore, each gene can be mutated at different locations; therefore, every tumor

Ethical considerations

The innovative technologies that are rapidly emerging in the field of high-throughput gene expression analysis are exciting and promising. These technologies provide hope for earlier and more accurate diagnosis of diseases and for personal genetic profiling that can determine and predict differences in individuals’ responses to different treatments. However, our enthusiasm should be tempered by careful attention to numerous ethical considerations. Typically, the predominant emphasis of

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