
doi: 10.1159/000083764
pmid: 15703470
Until recently, diagnostic and prognostic assessment of diseased tissues in a Pathology laboratory relied on histological and immunohistological studies. DNA microarray technology now allows the simultaneous analysis of up to thousands of different genes in histological or cytological specimens. Thus, the microarray techniques offer opportunities for the pathologist to obtain ‘molecular signatures’ of the state of activity of diseased cells in patient tissue samples, providing new information, such as the biological staging of tumors, a risk assessment of pre-malignant lesions, resistance to, and side effects of, treatment, molecular mechanisms in neurodegeneration and inflammation, and detection of micro-organisms. However, despite the great promise of this revolutionary technology, there are several issues that may undermine the power of the DNA microarray approach. After a short summary of the different forms of microarray and the contribution of this technology to understanding human disease, this short review focuses on the potential pitfalls and the important issues that must be considered when using a DNA microarray. Although this new approach shows great potential, the successful application of gene arrays to diagnostic and prognostic problems requires thoughtful interpretation and a strong correlation with other data, such as clinical, histopathological and immunohistochemical findings.
Gene Expression Profiling, Neoplasms, Biomarkers, Tumor, Animals, Humans, Diagnosis, Computer-Assisted, Biomarkers, Neoplasm Proteins, Oligonucleotide Array Sequence Analysis
Gene Expression Profiling, Neoplasms, Biomarkers, Tumor, Animals, Humans, Diagnosis, Computer-Assisted, Biomarkers, Neoplasm Proteins, Oligonucleotide Array Sequence Analysis
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 20 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
