Improvements in cancer classification using micro-arrays "have been central to advances in cancer treatment". This technology can distinguish disease subtypes that differ in their response to a particular therapy. This will help doctors choose the most appropriate treatment for individual patients.
Drug development strategies are changing. Researchers are designing drugs that target the molecular characteristics of cancer rather than focusing on conventional, and often less specific, cytotoxic agents. Imatinib mesylate (Gleevec, Glivec), a c-ABL kinase inhibitor, is the leading example of the success of this approach. Patients with chronic myelogenous leukaemia show high response rates to imatinib, without experiencing the debilitating side-effects often associated with traditional treatments. But after this first flush of success, scientists have hit a hurdle - drug resistance. This is a common clinical occurrence following treatment with imatinib and other targeted agents. In the November issue of the EJC**, Dr. Clarke explains how micro-arrays can be used to help understand and predict this resistance. As the number of these targeted agents increases, this knowledge will be of paramount importance.
Micro-arrays measure the gene expression profiles of the cell*. These profiles provide clues to the cell's genetic makeup and response to the environment. They are unique 'signatures' that can identify common regulatory mechanisms, biochemical pathways and broader cellular functions. For example, studying the signatures of tumours and normal cells may pinpoint differences that can be exploited in drug development. Genes associated with failure to treatment or poor outcome can be identified. 'Metagenes', a combination of individual genes that describes a particular pathway or gene activity, can also be generated providing additional therapeutic targets.
The technology is used as a complement to other genetic methods. "The development of safe and effective drugs remains challenging", he says. "These new technologies will improve the rate at which novel molecular therapeutics are developed and evaluated". They have "provided a wealth of information", according to researchers at the National Cancer Institute [2]. "We are just at the beginning of refining how this information is to be used".
Conventional chemotherapy remains a powerful tool, albeit with a low specificity, for the treatment of cancer, say Drs. Damia and Broggini (Laboratory of Molecular Pharmacology, Department of Oncology, Mario Negri Institute, Milan, Italy) [3]. To overcome this, more work is needed to find and test molecules that increase the selectivity of available agents.
Professor Maurizio D'Incalci (Department of Oncology, Mario Negri Institute, Milan, Italy), who edited the volume with Nobel Prize winner Professor Renato Dulbecco (The Salk Institute, La Jolla, CA, U.S.A.), says "Scientists and clinicians will have to work in close collaboration to make tangible improvements in the diagnosis and therapy of tumours [4]. Our reason for preparing this issue was to illustrate important changes in current diagnostic and therapeutic approaches. But, many scientifically attractive ideas and approaches still lack rigorous validation and we need further clinical investigation. The exploitation of the novel approaches discussed in this volume, once validated, will have an important impact on the survival and quality of life of cancer patients in the next decade. We want to prompt further research and stimulate the ideas of scientists and clinicians in the hope of alleviating the suffering of cancer patients. Viva la rivoluzione".
*Additional Information about Micro-arrays
The technology generally consists of four phases: (a) fabrication of the array; (b) RNA isolation and labelling; (c) application of the labelled sample to the array and measurement of hybridisation; and (d) data analysis and interpretation. Data can be normalised to make it comparable by using 'house-keeping' genes that are likely to be constitutively expressed.
Several strategies are used to analyse the data. One common method is 'hierarchical clustering' that exploits the concept that genes with similar expression profiles are likely to be functionally related. Data can be clustered from a given set of conditions or cell types, whereby a 'guilt by association' strategy identifies functional clusters.
** 'Gene transcription and cancer, from the genome project to practical achievements in diagnosis and therapy' (EJC November issue 2004) 40:17.
[1] Paul A. Clarke, Robert te Poele and Paul Workman. Gene expression microarray technologies in the development of new therapeutic agents. EJC(2004) 40:17.[2] Sausville E. A. Holbeck S. L. Transcription profiling of gene expression in drug discovery and development : the NCI experience. EJC (2004) 40:17. [3] Giovanna Damia and Massimo Broggini. Improving the selectivity of cancer treatments by interfering with cell response pathways. EJC (2004) 40:17. [4] Maurizio D'Incalci and Renato Dulbecco. Introduction. EJC (2004) 40:17.
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