Microarray technology normalization

III. APPLICATIONS OF THE MICROARRAY TECHNOLOGY FOR ASSESSMENT OF GENOME ACTIVITY IN NORMAL AND PATHOLOGIC CELLS AND TISSUES... 

Protein microarray technology provides a platform for the in vitro study of protein function at a genome-wide level (Talapatra et al. 2002). Immobilized proteins can be assayed in parallel under many different conditions and with many different samples. However, whole-proteome microarrays are difficult to achieve for higher organisms. Until recently, they have been limited to studies of the yeast proteome because production of a large number of pure recombinant proteins in parallel is a tedious and expensive process. cDNAs must be cloned into expression vectors, and the translated proteins must be purified in large amounts. Furthermore, in the case of genome-wide approaches, the cDNA library must be normalized. 

Normalization of cDNA microarray data is a very important step in the process of data analysis. With current technology, systematic hias is unavoidable and must he dealt with in a sensible manner. Furthermore, normalization methods need to be consistently apphed to all raw data. Using different normalization methods on different datasets may introduce bias and thereby decrease the validity of the data. Normahzed data should be free of systematic bias and should thereby provide a truer representation of the biological variance. Furthermore, normahzed data increases the validity of shde to shde comparisons. 

Using SELDI technology, a-defensin isoforms were found to be elevated in serum from colon cancer patients and in protein extracts from CRC [59]. This result was confirmed by expression analysis of microarray data obtained from 283 tumors and normal tissues followed by serum analysis of colon cancer patients and controls by ELISA. This study yielded a diagnostic sensitivity of 70%i and specificity of 83% for a-defensin in colon cancer [60]. Although these figures appear too low for developing a screening test, this... 

Some early studies demonstrated the potential of the new technology [39-41] to examine the differences between normal and malignant colonic tissue [39] and identifying potential subclassifications of breast cancer [41]. An interesting aside to these studies was the different analytical methods used by the authors to analyze and interpret the data. This variability of approach remains a feature of microarray studies and can hinder the comparison of data from different studies. However, there are now processes in place which attempt to standardize at least some of the analyses [42],... 

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