Progress in cancer research requires the discovery of novel biochemical and molecular targets for targeted treatments, novel biomarkers for early cancer detection and diagnosis, and improved classification and subtyping of cancers for prognostication and treatment selection.
To facilitate these goals, efforts have focused on understanding the molecular basis and cellular biology of human cancer.
The examination of multiple expressed genes and/or proteins provides useful information for both classification and prognostication of individual tumors. The development of microarray methodology, which permits the expression of thousands of genes to be assayed simultaneously, represents a powerful technique to read the "molecular signature" of an individual patient's tumor. This process is termed gene expression profiling (GEP). Analyzing gene expression patterns across individual patients with the "same" disease may reveal molecular differences. Such classification may allow better treatment selection and prognostication.
A description of the methods used for GEP will be presented here. More detailed discussion of the applications of these techniques to specific tumor types is discussed in the appropriate tumor topics.
GEP AND DNA MICROARRAY ANALYSIS - The traditional method of measuring the level of expression of a single gene is by assaying RNA by Northern blot analysis. DNA microarray analysis uses the same principles to simultaneously measure the expression level of thousands of genes on a platform called a microarray.
There are several stages to performing a microarray analysis:
Preparation of the microarrayGeneration of fluorescent targets from the RNA of the samplesHybridization to the probesData acquisition: scanning of the signal intensity emanating from the hybridized labeled probesData analysis: the extraction of biologically useful information from the vast quantity of data that is generated from microarray analysis. This aspect is often the most challenging component of GEP.Preparation of the microarray - The DNA array consists of an orderly arrangement of DNA spots on a glass slide or chip. In its simplest form, a few dozen complementary DNAs (cDNAs) or oligonucleotides corresponding to particular genes are immobilized onto the substrate in a known order within the grid.
In highly-sophisticated microarray "chips", up to hundreds of thousands of unique oligonucleotide probes, representing thousands of known genes or expressed sequence tags (ESTs), are synthesized in a microgrid on a glass substrate about the size of a thumbnail. ESTs are segments of expressed genes that have been sequenced, but do not correspond to known genes.
Each oligonucleotide probe, which is specific for a particular gene, is located on a precise place within the microgrid; this is the probe cell. Each probe cell is very small, about 24 microns by 24 microns, and contains millions of copies of each specific oligonucleotide. A particular gene (eg, the gene encoding thymidylate synthetase) may be represented on the microgrid by 20 or more probe cells, called a probe set. The oligonucleotide probes (usually 15 to 25 nucleotides in length) in each probe cell of the probe set may differ from each other, some corresponding to the 5' end of the mRNA sequence, some the middle, and some the 3' end. This gives the sample RNA a broad range of sequences with which to hybridize.
In summary, the rapidly evolving field of DNA microarray analysis and gene expression profiling has wide-ranging implications for the molecular classification of tumors, refinement of prognostic estimates, and prediction of response to therapy. Despite its exciting potential and significant recent advances, this field remains relatively new, and it is premature to conclude that microarray data can be used as a sole means of classifying cancers or predicting outcomes of treatment.
Among the specific challenges that must be met are the need for larger studies with appropriate validation, standardization of methods and establishment of guidelines for the conduct and reporting of studies, and the formation of repositories and registries where research institutions may deposit data for comparison with independent works involving the same malignant disorder. Finally, DNA microarray-based tests must demonstrate utility in prospectively designed clinical trials before this technology is considered a routine part of clinical evaluation.
These studies may eventually establish a new treatment paradigm in personalized cancer therapy in the future.
Dr. Richard Graydon, http://www.medauthor.com/, trained as an Oncologist, holding both M.D. and PhD degrees, and specializes in molecular genetics and cancer research. His education and experience have provided him analytical and clinical skills for keen insight into diagnosis, treatment, and care of cancer patients. See http://www.medauthor.com/ for further information
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