Nucleic acid quantification and disease outcome prediction in colorectal cancer

Abstract

Histopathological stage at diagnosis remains the most important prognostic determinant for colorectal cancer. However, conventional staging is unable to predict disease outcome accurately for each individual patient. This results in considerable prognostic heterogeneity within a given tumor stage and is of particular relevance for a subgroup of patients with stage II disease that would benefit from adjuvant therapy. The recent advances in functional genomics are beginning to have a significant impact on clinical oncology, and there is widespread interest in using molecular techniques for clinical applications. These have focused on two approaches: the use of polymerase chain reaction (PCR)-based methods for the detection of occult disease in lymph nodes, bone marrow and blood and the use of microarrays for the expression profiling of primary tumors. The aim is to develop molecular classifiers that will allow the prediction of disease outcome, thus matching patients with individualized treatment. Despite the obvious attractions of these approaches, there have been significant technical, biological and analytical problems in their translation into clinically relevant practice. This is particularly true for colorectal cancer, the second most common cancer in the western world. Nevertheless, progress is being made and the improved awareness and appreciation of those difficulties is beginning to generate results that should prove useful for clinical oncology.