Background. Colorectal cancer (CRC) arises from series of multiple acquired genetic and epigenetic changes and is recognizable as the adenoma-carcinoma sequence. Its complexity at the gene level is reduced to a limited number of alterations within signaling pathways. Aim. To evaluate potential and challenges of the translation of microarray-based gene expression profiling into the functional aspects of CRC carcinogenesis. Methods. Studies were performed on samples of normal mucosa, adenomas and CRCs obtained during surgery or colonoscopy. The study protocol was approved by the local Bioethical Committee. The collections of cryostat sections prepared from tissue samples were evaluated by the pathologist to control the relative cell type content, and RNA was isolated from 105 macroand 48 microdissected specimens. The measurements were done using the Affymetrix GeneChip HG-U133 Plus 2.0 Array, and the data were evaluated using pair-wise comparisons, clustering analyses and data decomposition into SVD modes and ICA independent components. To derive the functional meaning from the selected gene lists, we performed over-representation analysis grouping genes according to the pre-defined KEGG signaling pathway annotations by the use of the hipergeometric and Kolmogorov-Smirnov tests. Results. 31962 and 25410 probe sets of macrodissected samples and 29242 and 24002 probe sets of microdissected samples passed the filtering procedure according to MAS5 and GCRMA+ LVS algorithms, respectively. Gene expression fully discriminated both macroand microdissected specimens according to the histological classification of the tissue sample; the two main clusters represented normal and neoplastic tissues. Tumor samples were further divided into the two subgroups representing adenomas and CRCs. Although data processing significantly influences the functional analyses, differentially expressed genes between normal mucosa and adenomas have been attributed to the p53 signaling pathway, purine metabolism, aminoacyl-tRNA biosynthesis, cell cycle and DNA replication, while functional groups of genes with alternated expression between adenomas and CRCs have represented ECM-receptor interaction, focal adhesion, PPAR signaling pathway, cytokine-cytokine receptor interaction, fatty acid and amino acid metabolism. Conclusions. Microarray data analyses allow pointing essential signaling alterations. However, lack of methods which would independently verify gene expression-based functional annotations makes difficult to establish detailed oncogenic signaling. Supported by PBZ-MNiI-2/1/2005 grant.