Tumor Microdissection

Microdissection of a tumor was initially carried out using a standard syringe (5). The tumor was viewed under a microscope so that it could be separated from the surrounding normal tissues. For this method to be effective, tumors needed to be easily defined under the microscope, which limited the number of samples that were compatible. Microdissection techniques have further evolved to include techniques such as laser microbeam microdissection (LMM) and laser capture microdissection (LCM). These techniques afford laser precision and the possibility to isolate single cells (14). As a result, these methods have gained importance as tools to obtain purified cell populations from tissue (15).

LCM has been used as a tool for the purification and stratification of tumor samples that are to be used in subsequent microarray analyses (16,17,18,19,20,21). Separation of the tumor from the surrounding tissue provides cleaner populations of cells that can be used for the subsequent analysis of gene expression profiles or chromosomal aberrations. Furthermore, by purifying individual cell types, distinct signatures for each cell type can also be obtained using microarray profiling (22, 23). Such analyses demonstrate that the cancers are not homogenous at the molecular level. Yang et al. (23) demonstrated that the signature obtained from bulk tumors can include many common genes found in more pure populations of epithelial cells, but that both the purified epithelia and the bulk tumor have characteristic sets of genes that are unique as well. In analysing the results of a gene expression profiling on purified epithelia from ER-a positive and ER-a negative cells, a total of 146 ER-related genes were identified. When the authors then compared the expression profiles to those of the bulk tumors from which the purified cell populations were obtained, 61 of these genes were identified as being in-common. Thus, 85 of the genes identified (58%) could only be identified by using the pure cell population (23).

As LCM becomes more commonly used upstream of microarray analysis, the quality of data as well as the usefulness of the signatures obtained will likely increase. With a greater understanding of the molecular heterogeneity at the transcriptome level for example, it will be possible to develop combinatorial therapies that use multiple different drugs to target the several different cell types involved in the disease. Very few other technologies hold the promise of microarrays when it comes to understanding cancers at this level of detail, and thus it is likely that these new and more focused approaches will lead to new therapeutic strategies.

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