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      Technology insight: Identification of biomarkers with tissue microarray technology.

      Nature clinical practice. Oncology
      Gene Expression Profiling, Humans, Neoplasms, metabolism, pathology, Tissue Array Analysis, Tumor Markers, Biological

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          Abstract

          High-throughput technologies have been developed in the hope of increasing the pace of biomedical research, and accelerating the rate of translation from bench to bedside. Using such technology in target discovery has resulted in the need for systematic validation of the targets in an equally rapid manner. For example, gene expression microarrays have highlighted many potential targets in cancer, and tissue microarrays have emerged as a powerful tool to validate these targets by measuring tumor-specific protein expression and linking it to clinical outcome. Automated quantitative analysis of the tissue microarray 'spots' is beginning to take the technology a step further, removing observer bias, and providing standards for quality control and the potential for high-throughput analysis. The validation required for translation of tissue biomarkers from the research lab to the clinical lab will probably rely heavily on the combination of tissue microarray technology with automated quantitative analysis.

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          Most cited references22

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          Tissue microarrays for high-throughput molecular profiling of tumor specimens.

          Many genes and signalling pathways controlling cell proliferation, death and differentiation, as well as genomic integrity, are involved in cancer development. New techniques, such as serial analysis of gene expression and cDNA microarrays, have enabled measurement of the expression of thousands of genes in a single experiment, revealing many new, potentially important cancer genes. These genome screening tools can comprehensively survey one tumor at a time; however, analysis of hundreds of specimens from patients in different stages of disease is needed to establish the diagnostic, prognostic and therapeutic importance of each of the emerging cancer gene candidates. Here we have developed an array-based high-throughput technique that facilitates gene expression and copy number surveys of very large numbers of tumors. As many as 1000 cylindrical tissue biopsies from individual tumors can be distributed in a single tumor tissue microarray. Sections of the microarray provide targets for parallel in situ detection of DNA, RNA and protein targets in each specimen on the array, and consecutive sections allow the rapid analysis of hundreds of molecular markers in the same set of specimens. Our detection of six gene amplifications as well as p53 and estrogen receptor expression in breast cancer demonstrates the power of this technique for defining new subgroups of tumors.
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            Delineation of prognostic biomarkers in prostate cancer.

            Prostate cancer is the most frequently diagnosed cancer in American men. Screening for prostate-specific antigen (PSA) has led to earlier detection of prostate cancer, but elevated serum PSA levels may be present in non-malignant conditions such as benign prostatic hyperlasia (BPH). Characterization of gene-expression profiles that molecularly distinguish prostatic neoplasms may identify genes involved in prostate carcinogenesis, elucidate clinical biomarkers, and lead to an improved classification of prostate cancer. Using microarrays of complementary DNA, we examined gene-expression profiles of more than 50 normal and neoplastic prostate specimens and three common prostate-cancer cell lines. Signature expression profiles of normal adjacent prostate (NAP), BPH, localized prostate cancer, and metastatic, hormone-refractory prostate cancer were determined. Here we establish many associations between genes and prostate cancer. We assessed two of these genes-hepsin, a transmembrane serine protease, and pim-1, a serine/threonine kinase-at the protein level using tissue microarrays consisting of over 700 clinically stratified prostate-cancer specimens. Expression of hepsin and pim-1 proteins was significantly correlated with measures of clinical outcome. Thus, the integration of cDNA microarray, high-density tissue microarray, and linked clinical and pathology data is a powerful approach to molecular profiling of human cancer.
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              Medicine. The NIH Roadmap.

              E Zerhouni (2003)
              The NIH Roadmap is a set of bold initiatives aimed at accelerating medical research. These initiatives will address challenges that no single NIH institute could tackle alone, but the agency as a whole must undertake. The Roadmap identifies the most compelling opportunities in three arenas: new pathways to discovery, research teams of the future, and reengineering the clinical research enterprise.
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                Author and article information

                Journal
                16264828
                10.1038/ncponc0046

                Chemistry
                Gene Expression Profiling,Humans,Neoplasms,metabolism,pathology,Tissue Array Analysis,Tumor Markers, Biological

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