Research on the molecular biology of colorectal cancer has increased our expectation that a better understanding of molecular changes in colorectal tumours may improve our knowledge of aetiology and treatment. Recently, investigators have recognised that molecular characteristics of colorectal cancers are associated with prognosis and therapeutic response. Studies suggest that some of the major genetic players in colorectal neoplasia, such as p53 mutations, are associated with poorer prognosis (Hardingham et al, 1998
). Other studies report correlations between K-ras mutations, tumour stage, and survival (Andreyev et al, 1998
; Samowitz et al, 2000
). In a population-based study of 607 colorectal cancer patients, Gryfe et al (2000)
observed that high-frequency microsatellite instability (MSI) conferred significant survival advantage independent of other prognostic factors including tumour stage.
Molecular studies in colorectal cancer may help us better understand how genetic alterations could alter prognosis or impact response to cytotoxic agents. However, there are limitations in the analysis of molecular markers in studies of colorectal cancer prognosis. Oftentimes, studies have a limited amount of tissue samples or have samples from a small number of subjects. Furthermore, variation in the expression of markers in tumour samples might be too small to detect differences in prognosis, thus limiting the utility of some markers. Therefore, there is a need to devise strategies to utilise resources efficiently in studies of molecular markers of prognosis.
In the conduct of a population-based study to determine prognostic and predictive molecular factors for colorectal cancer, we used data from more than 100 patients to develop a strategy to determine whether specific molecular markers possess sufficient variability to yield meaningful results in a study of sample size 1000. Using this method, molecular markers that were unlikely to be informative were abandoned in an early stage of the study in favour of mutations or protein markers showing more promise. This method allowed us to conserve time and resources, and may be applicable to other molecular studies.