Formalin-fixed, paraffin-embedded (FFPE) tissue archives are the largest and longest time-spanning collections of patient material in pathology archives. Methods to disclose information with molecular techniques, such as array comparative genomic hybridisation (aCGH) have rapidly developed but are still not optimal. Array comparative genomic hybridisation is one efficient method for finding tumour suppressors and oncogenes in solid tumours, and also for classification of tumours. The fastest way of analysing large numbers of tumours is through the use of archival tissue samples with first, the huge advantage of larger median follow-up time of patients studied and second, the advantage of being able to locate and analyse multiple tumours, even across generations, from related individuals (families). Unfortunately, DNA from archival tissues is not always suitable for molecular analysis due to insufficient quality. Until now, this quality remained undefined. We report the optimisation of a genomic-DNA isolation procedure from FFPE pathology archives in combination with a subsequent multiplex PCR-based quality-control that simply identified all samples refractory to further DNA-based analyses. British Journal of Cancer (2006) Cancer cytogenetics has benefited greatly from the introduction of comparative genomic hybridisation (CGH) for mapping chromosomal gains and losses at a genome-wide scale (Kallioniemi et al, 1993;Gray et al, 1994). Subsequent development of the technique into array-CGH (also named matrix-CGH) has allowed increased automation, improved reproducibility and precision due to more accurate mapping of aberrations. This technology has been applied successfully to characterise congenital abnormalities at unprecedented precision (Veltman et al, 2002) and to characterise and classify tumours (Wessels et al, 2002;Nessling et al, 2005).In most pathology laboratories, large archives of formalin-fixed, paraffin embedded (FFPE) material are often the only source of material for cancer research. It is our experience (Wessels et al, 2002;Van Beers et al, 2005) that a proportion of archival specimens appears unsuited for aCGH analysis, which is troublesome because array comparative genomic hybridisation (aCGH) experiments are tedious and expensive. In the past, we have noticed that this was not solved by repeating aCGH experiments, even when DNA was isolated from new sections from the same tissue blocks (Van Beers et al, 2005). Nevertheless, it is possible to obtain high-quality data using archival DNA samples in array CGH experiments (Figure 1) (Gray et al, 1994;Ried et al, 1995;Albertson and Pinkel, 2003;Heidenblad et al, 2004;Loo et al, 2004;Devries et al, 2005), even from 20-year-old tissue blocks, provided that robust procedures, high-quality reagents and 'good' sample DNA quality are being used. A 'good sample quality' definition and an assay to determine this FFPE DNA sample quality would therefore be of great value.Molecular biological assays, including aCGH on FFPE archival specimens, would be more eff...

BackgroundAccurate staging of colorectal cancer (CRC) with clinicopathological parameters is important for predicting prognosis and guiding treatment but provides no information about organ site of metastases. Patterns of genomic aberrations in primary colorectal tumors may reveal a chromosomal signature for organ specific metastases.MethodsArray Comparative Genomic Hybridization (aCGH) was employed to asses DNA copy number changes in primary colorectal tumors of three distinctive patient groups. This included formalin-fixed, paraffin-embedded tissue of patients who developed liver metastases (LM; n = 36), metastases (PM; n = 37) and a group that remained metastases-free (M0; n = 25).A novel statistical method for identifying recurrent copy number changes, KC-SMART, was used to find specific locations of genomic aberrations specific for various groups. We created a classifier for organ specific metastases based on the aCGH data using Prediction Analysis for Microarrays (PAM).ResultsSpecifically in the tumors of primary CRC patients who subsequently developed liver metastasis, KC-SMART analysis identified genomic aberrations on chromosome 20q. LM-PAM, a shrunken centroids classifier for liver metastases occurrence, was able to distinguish the LM group from the other groups (M0&PM) with 80% accuracy (78% sensitivity and 86% specificity). The classification is predominantly based on chromosome 20q aberrations.ConclusionLiver specific CRC metastases may be predicted with a high accuracy based on specific genomic aberrations in the primary CRC tumor. The ability to predict the site of metastases is important for improvement of personalized patient management.

Background: Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, leading to cancer. Therefore, the identification of DNA amplifications or deletions across tumors may reveal key genes involved in cancer and improve our understanding of the underlying biological processes associated with the disease.