National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for Use of Tumor Markers in Clinical Practice: Quality requirements




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НазваниеNational Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for Use of Tumor Markers in Clinical Practice: Quality requirements
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MICROARRAYS IN CANCER DIAGNOSTICS3 4

Background


Genomic microarrays were first introduced in 1996 by Affymetrix (65). Gene chip protein microarray technology successfully exploits the principles of the ambient analyte ligand analysis first described by Ekins and co-workers in the early 1980s (66, 67). Briefly, Ekins’ Ambient Analyte Theory concept recognizes that a minute amount of binding material (e.g. antibody or other receptor) does not significantly change the sample concentration and can give much higher sensitivity than assay formats using 100 or 1000 times the amount of binding material (66, 68). In particular, the use of microscopic spots of “binding agent” located at high surface density on a solid support (coupled with the use of very high specific activity labels, such as fluorescent labels) can yield higher sensitivity and shorter incubation times than conventional ligand assay methods, especially so-called non-competitive assay methods. A comprehensive review of the principles of this technology has recently been published (69).

Although still generally restricted to research use, the versatility of microarrays - depending on the biomolecule immobilized on the surface, these devices are commonly known as biochips, DNA-chips, protein-chips or cell-chips – is such that the major potential clinical applications of the technology in the field of oncology were immediately recognized. Disease classification, prognosis, monitoring and prediction of therapeutic response are some of the areas where microarrays have the potential to become routine diagnostic tools. This technology enables substitution of linear studies of individual events to parallel and simultaneous analysis of complex systems and pathways. Regardless of the application, the resulting information comprises thousands of individual measurements and provides an intricate and complex snapshot of biological properties of the cell, tissue, organ or fluid. Microarrays relevant to cancer diagnostics have now been commercially introduced and/or are being developed by Affymetrix (GenechipR technology) (65), Randox (EvidenceR technology) (70) and other major manufacturers.


PRINCIPLES OF MICROARRAYS

A microarray is a compact device that contains a large number of well-defined immobilized capture molecules (e.g. synthetic oligos, PCR products, proteins, antibodies) assembled in an addressable format. The best-known microarrays, DNA-biochips, are miniature arrays of oligonucleotides attached to a glass or plastic surface. These chips are used to examine gene activity (expression profiling) and identify gene mutations or single nucleotide polymorphisms (SNPs), by hybridization between the sequences on the microarray and a labelled probe (the sample of interest). There are two major methods for microarray fabrication: a) photolithography, as is used in the Affymetrix system (400,000 spots in a 1.25 x 1.25 cm area), and b) mechanical deposition or printing on glass slides, membranes etc. as originally developed by Boehringer-Mannheim and now adopted by Roche Diagnostics (71) [In this context it is important to note that at least 1000-fold greater sensitivities are required in the case of protein as compared with gene microarrays.]

Major potential advantages of microarray-based assays include high sensitivity, small amounts of binding reagents required, their independence of sample volume, decreased incubation times, minimal wasted reagents, simultaneous access to many genes or proteins, massive parallel information, automation and potentially quantification. More detailed information on the subject is readily available in specialized books and reviews (69, 72, 73) and an entire issue of Nature Genetics (74).

TISSUE MICROARRAYS


High-throughput analysis of tissues is facilitated by new technologies such as multi-tissue northern blots, protein arrays or real-time PCR (75-78). However, the problem with these methods is that tissues are disintegrated before analysis, preventing identification of the cell types expressing the gene of interest (79). These and other shortcomings can be overcome by tissue microarray (TMA) techniques (80). TMAs consist of up to a 1000 tiny cylindrical tissue samples (0.6 mm in diameter) assembled on a regular-sized routine histology paraffin block. Sections are cut from TMA blocks using standard microtomes. TMA sections allow simultaneous analysis of up to a 1000 tissue samples in a single experiment. The technique is therefore cost-effective. Despite the small size of arrayed samples, TMA studies generally provide reasonably representative information. TMAs are applied over a broad range of cancer research: prevalence TMAs (81-83), progression TMAs (80, 84-86), prognostic TMAs and TMAs composed of experimental tissues such as cell lines (87, 88) or xenografts (85).

APPLICATIONS OF MICROARRAYS

Microarrays have been successfully applied in a variety of settings including

  • Gene expression profiling (the most popular application)

  • Detection of Single Nucleotide Polymorphisms (SNPs) (Pharmacogenetics)

  • Sequencing by hybridization (genotyping/mutation detection)

  • Protein expression profiling

  • Protein-protein interaction studies

  • Whole genome biology experiments

Cancer is a heterogeneous disease in many respects, including its cellularity, different genetic alterations and diverse clinical behavior. Many analytical methods have been used to study human tumors and to classify patients into groups with similar clinical behavior. Most methods require specialized pathologist interpretation; yet none of the classifications are homogeneous enough. It has been hypothesized that the genetic heterogeneity and clinical behavior of cancer could be better assessed by studying genome-wide gene expression profiles by microarrays (89). Although the potential of microarrays is yet to be fully realized, these tools have shown great promise in deciphering complex diseases, including cancer (89). A partial list of applications of microarrays in cancer is presented in Table 6. As is the case with many new technologies, microarrays have many shortcomings, briefly discussed in the following section.

LIMITATIONS OF MICROARRAYS

Microarray technologies are still evolving and this presents difficulties for standardization and consensus development. There are no ‘gold standards’ such as reference reagents or bioinformatics algorithms. These standards are essential for comparison of data between laboratories and on different platforms (90). Recent reports suggest that microarray data are noisy and not reproducible (91, 92). Furthermore, bias poses a significant threat to the validity of data generated by such technologies (93).
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