398 been examined together with colon tumors, and patients have not been stratified by stage, gender, or age. Thus, many have been statistically underpowered to provide meaningful results. Using large cohorts of patients, such as those in the PETACC-3 and CALGB 89803 trials, may address many of these issues and provide an accu- rate assessment of the prognostic and predictive (of re- sponse to irinotecan-based treatment) capabilities of the promising biomarkers described. 2. In many studies, a lack of standardization of methodol- ogies for marker measurement has resulted in data that are not comparable. It is hoped in the approaches used in the PETACC-3 [116] and CALGB 89803 studies to cen- tralize and standardize sample handling and methodolo- gies that these important issues will be addressed. 3. Often, the methodology chosen in studies does not rep- resent a comprehensive analysis of multiple components of a specific biological pathway, each of which may in- cur defects in multihit tumorigenesis. Significant asso- ciations between molecular lesions in a pathway and clinical parameters may therefore be missed. A prime example of this is the analysis of chromosome 18q in co- lon cancer patients undergoing adjuvant treatment. It is recommended that future studies employ methods that can discriminate among different molecular patholo- gies, such as combinations of a-CGH, single nucleotide polymorphism (SNP) arrays, and other methods that de- tect DNA ploidy. The concurrent consideration of gene or protein expression data for candidate genes on 18q might also be necessary to demonstrate meaningful associations. 4. Often, not all mutations within a given gene are screened. An example is the KRAS gene, for which the frequently occurring mutations at codons 12 or 13 are measured but other, less common, mutations at codons 61 and 146 are not assessed. This can also be a source of potential bias in an investigation. Furthermore, other candidate genes in related signaling pathways will need to be examined to provide a pathway-centric approach to make sense of some of the observations made with single candidate genes. For example, KRAS mutation status should be judged in conjunction with the PI3K–AKT axis because there is extensive crosstalk between these path- ways [117]. Studies to date have demonstrated the urgent need for biomarker development and have highlighted the method- ological challenges of this research. Attempts have been made to provide guidelines for the validation and optimiza- tion of biomarkers for use in the clinical setting, prime ex- amples being: the tumor marker utility grading system Biomarkers in Colon Cancer Adjuvant Treatment (TMUGS) [118]; reporting recommendations for tumor marker prognostic studies (REMARK) [119]; guidelines for gene expression localization experiments; and the min- imum information specification for in situ hybridization and immunohistochemistry experiments (MISFISHIE) [120]. FUTURE CONSIDERATIONS FOR BIOMARKER INVESTIGATIONS IN THE ADJUVANT SETTING IN THE POSTGENOMIC ERA In this postgenomic era, technological developments have occurred in which the whole genome can be rapidly and cost-effectively investigated with high-throughput ap- proaches. We now review how a combination of functional genomics and molecular profiling in conjunction with care- fully designed clinical trials can be applied to identifying biomarkers and provide a vision for the future for adjuvant colon cancer. Postgenomic Technologies A number of technology platforms have been developed to detect genomewide alterations in tumors. These tools also have the potential to provide predictive profiles for patient prognosis and response to chemotherapy and are being ap- plied to CRC in general. Gene expression microarrays al- low the analysis of global gene-expression patterns in mRNA extracted from tissue samples. Changes in tumor DNA copy number have been traditionally characterized using a-CGH, based on bacterial artificial chromosome construct probes [58, 121]. Although copy number– depen- dent AI and copy number–neutral AI have been assessed by SNP microarrays [57], often the two technologies are com- bined to allow a more precise definition of the molecular basis of AI events occurring in tumors [57]. It has also been reported that SNP-bead arrays can discriminate between both copy number– dependent and copy number–neutral AI events [122, 123]. Furthermore, with the development of high-throughput gene sequencing and mutation detection capabilities, a detailed picture of the mutation spectrum of many genes in individual tumors can be realistically achieved [124]. Recently, many of these technology plat- forms and methods were adapted for use with DNA or RNA extracted from FFPE tissues [123, 125–127]. Following the identification of candidate genes of interest through expres- sion profiling, the feasibility of developing quantitative re- verse transcription PCR assays for use on FFPE material from colon cancer patients in a clinical setting was demon- strated [128]. These developments are important for bi- omarker validation in large retrospective analyses, in which FFPE material is often the only tissue available for study.