MOLECULAR DIAGNOSTICS
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One promising platform is the DNA microarray, which facilitates the multiplex analysis of multiple genetic factors simultaneously. Since many diseases and potential treatment outcomes are determined by the function of multiple genes, DNA microarrays will be an important molecular diagnostic technology. However, there are some major concerns with DNA microarrays for diagnostic applications. Such issues include cost, complexity, reproducible performance, and regulatory concerns. This article will discuss the use of DNA microarrays in diagnostic applications, specifically highlighting one platform that addresses many of the concerns and provides a rapid approach to developing and delivering microarray-based diagnostics.
Microarrays in Disease Management
Since the completion of the Human Genome Project, there has been a movement toward taking a molecular approach to the diagnosis and management of disease. However, clinical reference laboratories are grounded in a singleanalyte paradigm: the sequential analysis of single genes or markers, and slide-based morphological analysis. While clinically relevant, such approaches ignore the fact that most diseases are multivariate, and are the sum result of complex genetic, social, and environmental factors.
DNA microarrays have recently been used to obtain global perspectives of human disease and to identify genetic markers that are important for diagnosis and therapy.1–7 Such applications for microarrays have focused on analyzing genetic alterations and gene expression patterns underlying the biological properties and clinical behavior of pathogenic diseases. This genomewide approach is required to understand the fundamental complexities of disease. For example, cancer displays amazing heterogeneity, including gene amplifications, deletions, and genetic instability, even among tumors considered to be within the same class. Microarray technologies have already contributed to the discovery of new biomarkers for diseases and have spurred the rapid growth of a multianalyte paradigm for disease diagnosis and treatment. The resulting gene signatures, which are groups of gene expression patterns associated with a disease or trait, offer the promise of improved disease staging, risk stratification, and treatment decisions.
By focusing on genetic determinants of drug responses at the human genome level, pharmacogenomics plays an important role in prescribing safer and more-effective individually tailored drugs. DNA microarrays have shown great promise in clinical medicine by paving the way toward such effective individualized drug regimens. Microarray technologies and proteomics are instrumental in predicting drug sensitivity and potential side effects by studying the cellular pathways through gene expression profiles. Such information is changing the understanding of how genetics influences disease development and drug response, and contributing to the discovery of new treatments. Prospective genotyping of patients for various genes to determine drug targets, drug metabolism, and disease pathways is the first step toward individualized therapy, by matching the patient’s unique genetic makeup with an optimally effective drug.8
This article will review some of the key emerging microarray technologies, discuss the impact of these technologies on the IVD industry, and explore some key challenges, opportunities, and applications.
Microarrays: An Overview
DNA microarrays are a combination of technologies that are grouped by their ability to measure global changes in gene expression. The human genome consists of thousands of genes, each with a unique nucleotide pattern of G, A, T, and C molecules. Within any group of cells, a pattern of expression for these genes is observed, generating an mRNA copy with a nucleotide pattern that is specific to each gene. Microarrays are a hybridization-based platform that is composed of thousands of probes; such probes are positioned at defined locations, and are capable of binding to a specific gene-associated mRNA. Cellular gene expression is assessed by labeling an RNA sample, applying the labeled RNA to a DNA microarray, enabling hybridization between the probes and mRNA, and measuring the signal intensity at the probe positions. By measuring the amount of label present on the probes, a microarray can analyze the expression levels of thousands of genes in a single assay reaction.
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Figure 1. The CustomArray 12K (a) and CustomArray Synthesizer (b) by CombiMatrix (Mukilteo, WA). The CustomArray 12K is an active semiconductor-based array on which up to 12,500 DNA probes can be synthesized in situ utilizing an electrochemical approach. The synthesis is performed on the CustomArray Synthesizer, a benchtop instrument that has a capacity of up to 8 customized microarrays per run.
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A number of companies have been producing DNA microarray-based technologies, including Affymetrix (Santa Clara, CA), Agilent Technologies Inc. (Santa Clara, CA), Applied Biosystems (Foster City, CA), CombiMatrix (Mukilteo, WA), and GE Healthcare (Chalfont St. Giles, UK). These companies have microarray platforms that offer solutions to the problem of multianalyte analysis. For example, the CodeLink Bioarray by GE Healthcare is a slide-based array in which each synthesized oligonucleotide probe is embedded in a proprietary three-dimensional polyacrylamide aqueous-gel matrix. In contrast, the Affymetrix platform is an in situ synthesized approach that utilizes light-activated deprotection chemistry for in situ synthesis onto a silica-based surface. Similarly, Agilent’s arrays are constructed in situ with synthesis directed by ink-jet printing, thereby precisely building oligonucleotides from a silicon surface. CombiMatrix’s core technology is based on a modified electronic silicon chip. Using an electrochemical reaction, oligonucleotide probes are synthesized off the surface of a live active semiconductor. The flexibility of this platform enables rapid customization of probe design and synthesis of the DNA microarray (see Figure 1a).
During the past decade, DNA microarrays have been used in every facet of biological research, from basic science to the study of clinically relevant diseases. Microarrays have also been utilized in various other manners, including gene expression profiling, singlenucleotide polymorphism (SNP) analysis, and comparative genomic hybridization (CGH) analysis.
Microarray Applications
Gene Expression Profiling. A vast majority of the published clinical studies involving DNA microarray technologies have focused on identifying gene expression profiles of pathogenic and genetic diseases. Such studies have demonstrated the ability to identify gene expression patterns or classifiers that can distinguish between multiple common malignancies.1–7 Microarrays offer the ability to diagnose tumors based on molecular rather than morphologic characteristics, which allows tumor classification based on pathways rather than on appearance. Microarray-based gene expression analysis of breast cancer and leukemia have revealed that similar tumor types have distinctly different molecular characteristics.2–4 For example, leukemia includes more than 20 morphologic, genetic, and molecular subclasses. This characterization has led to the development of cancer databases, and the movement from a subjective phenotypic classification to a uniform molecular-based diagnosis of cancer.
SNP Analysis. SNPs are DNA sequence variations that occur when a single nucleotide (A, T, C, or G) in the genome sequence is altered. They are useful polymorphic markers that are often associated with susceptibility to diseases or are related to drug responsiveness. A small subset of SNPs may directly influence the quality or quantity of the gene product, resulting in an increased risk of certain diseases or severe drug side effects.9
CGH Analysis. Gross genetic aberrations are responsible for many diseases (e.g., Down, Prader-Willi, Angelman, and Cri du Chat syndromes), and for the development of neoplastic potential in a number of malignancies. CGH was developed for genomewide analysis of DNA sequence copy number in a single experiment. CGH analysis has been applied to study the chromosomal changes that occur in cancer cells, including the loss or duplication of regions of chromosomal DNA. Microarray-based CGH analysis has enabled researchers to explore rapidly such chromosomal changes on the same platform used to study gene expression changes. Combining such powerful tools on a single platform has greatly affected the discovery of oncogenes, tumor suppressor genes, drug targets, and biomarkers.10
Bringing Microarrays into the Lab
In clinical diagnostics, microarrays have been historically viewed as powerful research tools to identify markers for traditional IVD applications. Once markers were identified from a survey of tens of thousands of initial candidates, more-affordable, sensitive, and rapid assays have been created by using other platforms, such as quantitative polymerase chain reaction (PCR). However, with the recent advent of commercially available, low-cost, reproducible, technically simple arrays, and easy-to-use analytical software, the direct use of microarrays as diagnostic platforms in reference laboratories is beginning to be explored.
While the opportunities to improve patient care are clear, the path to clinical implementation of DNA microarrays is less defined. However, with increased awareness of the diagnostic potential of DNA microarrays, reference laboratories are being challenged to implement assays based on this technology. Implementing any new technology in a clinical setting creates a series of challenges, including staff licensure, technical training, and equipment purchases.
Staff licensing requirements for microarray applications are similar to most other molecular technologies that must comply with either national credentialing agency or state certification in the general or molecular categories. The technical component of a microarray assay is similar to quantitative PCR or hybrid capture assays, which are conducted daily in thousands of laboratories. In contrast, the professional interpretative aspects of microarray analysis, including quality control, data normalization, and results analysis, are unique to microarray technologies.
One area of concern that the licensing bodies currently overlook is the field of bioinformatics and microarray data analysis. While most diagnostic applications provide automated computer analysis algorithms, bioinformatics will clearly become an integral component of esoteric microarray assay analysis.11
The essential equipment used for DNA microarray applications is not significantly more expensive than that for other molecular-based diagnostic assays. Besides adding a specialized imaging system, many microarray-based assays can be performed with the same basic equipment found in a molecular diagnostics lab.
Developing Clinical Microarrays
There are two routes to developing and commercializing a clinical diagnostic assay: submitting a test for FDA approval, or conducting an internal validation to create a laboratory-developed test which is commonly known as a home-brew test.
Through the first route, there are two options: either the premarket approval (PMA) process, or 510(k) premarket notification that is based on a comparison to a predicate device. While these options allow a test to be sold to licensed reference laboratories in the United States, the process can be slow, expensive, and time-consuming. This route is required for high-volume products which are intended for manufacture and sale to third-party laboratories.
The second route is routinely undertaken by clinical laboratories and involves in-house internal assay validation. IVD tests developed and validated internally are indeed considered medical devices, and are created utilizing general-purpose reagents and analyte specific reagents (ASRs). In 1996, FDA introduced regulations that outline how ASRs and general-purpose reagents should be used to develop home-brew assays.12
In this regulation, FDA defined ASRs as “antibodies, both polyclonal and monoclonal, specific receptor proteins, ligands, nucleic acid sequences, and similar reagents which, through specific binding or chemical reaction with substances in a specimen, are intended for use in a diagnostic application for identification and quantification of an individual chemical substance or ligand in biological specimens.” According to this regulation, all ASRs purchased from third-party vendors must be registered with FDA, be labeled as an ASR, and comply with certain quality control guidelines.
In essence, FDA recognizes a legitimate home-brew test as an assay comprised of ASRs and general-purpose reagents (e.g., buffers or reactive materials without specific intended uses). In addition, all laboratories conducting in-house testing are required to meet CLIA high-complexity certification requirements, establish the performance of the home-brew tests per CLIA regulations, and label such tests that are developed using ASRs with the following statement: “This test was developed and its performance characteristics determined by (laboratory name). It has not been cleared or approved by FDA.”13
As of January 2006, FDA has not authorized any microarrays to be sold as ASRs. Consequently, the only available route for clinical implementation of non-FDA-approved microarrays is through the second route, by producing the entire microarray in-house from general-purpose reagents. The CustomArray and Microarray Synthesizer by CombiMatrix is the only commercially available platform that offers in-house synthesis capability (see Figure 1b). The benchtop Microarray Synthesizer allows clinical research groups to rapidly develop clinical diagnostic assays in-house. By using either the 12k (with up to 12,500 DNA probes) or the 95k (with up to 95,000 DNA probes) microarrays, molecular gene signatures can be rapidly created and validated.
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Figure 2. Tumor classification and drug response database. A bioinformatic database comprised of gene expression signatures of tumor biopsy samples is built. The expression signature of each biopsy sample is correlated with clinical history that includes information on the response of the patient to therapy. This database is comprised of signatures from multiple cancers and patients treated with multiple drugs. When a new patient is diagnosed with cancer, the corresponding biopsy or tumor is analyzed, and comparison of that expression signature with those in the database provides information to the physician that aids in the management of the patient.
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Another feature of the CombiMatrix platform is the ability to segment arrays. Through segmentation, a 12k array can be subdivided into four separate arrays of 2000 features. While many research applications require genomewide analyses, many clinical diagnostics will only necessitate the measurement of a smaller gene cohort. This platform can measure the preferred 250–500 genes with replicates and controls.
Key Application
One application that is currently being developed with the CombiMatrix system is a tumor classification and drug response prognostic (see Figure 2). The central focus of this product is the development of a prognostic database. Multiple tumor samples are analyzed with the CombiMatrix CustomArray to generate gene expression signatures. For each of the gene expression signatures, a corresponding detailed clinical history exists, which includes all relevant information including type and grade of tumor, response of the patient and tumor to drug therapies, and outcome. Once the database has been built and validated with blinded samples, it can serve as a powerful diagnostic tool to aid physicians in managing cancer patients.
For example, a biopsy or tumor sample from a diagnosed patient is analyzed with the CombiMatrix CustomArray; a gene expression signature is provided and then compared with expression signatures in the database. Though each expression signature is expected to be unique, certain patterns and trends will be similar to the signatures in the database. An analysis of the common patterns will provide information to physicians indicating that the patient exhibits an expression signature that is characteristic of a particular tumor type and grade, and a response probability to various drug treatment options. This product and other similar products will change the way patients are managed in a clinical setting.
Conclusion
The introduction of microarray-based applications in clinical laboratories has been a slow process, due to myriad problems involving technical, regulatory, and financial reasons. Nonetheless, it has become apparent that microarray platforms may revolutionize clinical diagnostics as they enable laboratory professionals to move away from single-analyte analysis and focus on complex multianalyte applications. The clear winner in this process will be the patients, as the healthcare industry learns to manage the complex processes of human diseases with 21st-century tools.
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| (Left to right) Amit Kumar, PhD, is president and chief executive officer at CombiMatrix Corp. (Mukilteo, WA) and chairman at CombiMatrix Molecular Diagnostics. Michael Opel, PhD, is a senior scientist at CombiMatrix Molecular Diagnostics. They can be reached at akumar@combimatrix.com and mopel@cmdiagnostics.com, respectively. Matthew Moore, PhD, and David Baunoch, PhD, (not pictured) were formerly at CombiMatrix Molecular Diagnostics. | ||
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12. Code of Federal Regulations, 21 CFR 864.4020.
13. “Guidance for Industry: Analyte Specific Reagents; Small Entity Compliance Guidance; Guidance for Industry,” Center for Devices and Radiological Health Web site (Rockville, MD: 2003 [cited 5 October 2006]); available from Internet: www. fda.gov/cdrh/oivd/guidance/1205.html.
