The overall prognosis for the majority of cancer patients remains poor. Current conventional strategies in clinical cancer research are unable to adequately answer a large number of important unsolved questions. Although some patients achieve substantial benefits from classical cytotoxic chemotherapy, others will not. The mechanisms behind this phenomenon are still not identified in detail. Furthermore, the activity of promising novel molecular targeting anticancer agents like tyrosinkinase inhibitors is currently not predictable within the individual patient. The biological background for this clinical and prognostic heterogeneity in behavior is more or less the large individual variation in the biological nature of tumors within the same classified histological subgroup. The overall usefulness of conventional histopathological classifications to adequately predict patient prognosis or response to chemotherapy is limited. The most promising way to solve this issue is to found clinical research strategies on basic biological evidence. New genomic technologies have been developed within recent years. These techniques are able to analyze thousands of genes and their expression profiles simultaneously. An increasing number of investigations has reported applications of these novel technologies within clinical trials settings. The aim of this approach is to identify new subsets of cancer patients, to improve prediction of their clinical outcome or response to treatment and select new targets for innovative therapeutic drugs based on the findings from gene expression profiles. Results of these gene expression profile studies could potentially lead to more individually tailored systemic cancer therapy. In the recent years, a remarkable number of studies based on these techniques have already been reported. Although the published results are clearly impressive and highly promising, a lot of work remains to be done. Moreover, there is a strong need for an increase in reliability and reproducibility of such gene expression profiling techniques and thus introduction of reproducible quality control in the performance of these assays. Although a large number of issues remain to be clarified prior to a more general application of genomic profiling techniques in clinical cancer research, this strategy will eventually turn out as a promising approach to improve successful management of cancer patients.
Keywords: chemotherapy, tumor biology, breast cancer, predictor, lung cancer, gastrointestinal cancer, retinoblastoma-binding protein.
Rights & PermissionsPrintExport