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No clear patterns in molecular changes underlying the malignant processes in lung cancer of different histological types have been found so far. To identify critical genes in lung cancer progression we compared the expression profile of cancer related genes in 14 pulmonary adenocarcinoma patients with normal lung tissue by using the cDNA array technique. Principal component analyses (PCA) and permutation test were used to detect the differentially expressed genes. The expression profiles of 10 genes were confirmed by semiquantitative real-time RT -PCR. In tumour samples, as compared to normal lung tissue, the up-regulated genes included such known tumour markers as CCNB1, PLK, tenascin, KRT8, KRT19 and TOP2A. The downregulated genes included caveolin 1 and 2, and TIMP3. We also describe, for the first time, down-regulation of the interesting SOCS2 and 3, DOC2 and gravin. We show that silencing of SOCS2 is not caused by methylation of exon 1 of the gene. In conclusion, by using the cDNA array technique we were able to reveal marked differences in the gene expression level between normal lung and tumour tissue and find possible new tumour markers for pulmonary adenocarcinoma.

DNA copy number amplifications activate oncogenes and are hallmarks of nearly all advanced tumors. Amplified genes represent attractive targets for therapy, diagnostics and prognostics. To investigate DNA amplifications in different neoplasms, we performed a bibliomics survey using 838 published chromosomal comparative genomic hybridization studies and collected amplification data at chromosome band resolution from more than 4500 cases. Amplification profiles were determined for 73 distinct neoplasms. Neoplasms were clustered according to the amplification profiles, and frequently amplified chromosomal loci (amplification hot spots) were identified using computational modeling. To investigate the site specificity and mechanisms of gene amplifications, colocalization of amplification hot spots, cancer genes, fragile sites, virus integration sites and gene size cohorts were tested in a statistical framework. Amplification-based clustering demonstrated that cancers with similar etiology, cell-oforigin or topographical location have a tendency to obtain convergent amplification profiles. The identified amplification hot spots were colocalized with the known fragile sites, cancer genes and virus integration sites, but global statistical significance could not be ascertained. Large genes were significantly overrepresented on the fragile sites and the reported amplification hot spots. These findings indicate that amplifications are selected in the cancer tissue environment according to the qualitative traits and localization of cancer genes.

The Self-Organizing Map (SOM) is a powerful neural network method for analysis and visualization of high-dimensional data. It maps nonlinear statistical dependencies between high-dimensional measurement data into simple geometric relationships on a usually twodimensional grid. The mapping roughly preserves the most important topological and metric relationships of the original data elements and, thus, inherently clusters the data. The need for visualization and clustering occur, for instance, in the analysis of various engineering problems. In this paper, the SOM has been applied in monitoring and modeling of complex industrial processes. Case studies, including pulp process, steel production, and paper industry are described.

Purpose: Bone marrow is a common homing organ for early disseminated tumor cells (DTC) and their presence can predict the subsequent occurrence of overt metastasis and survival in lung cancer. It is still unclear whether the shedding of DTC from the primary tumor is a random process or a selective release driven by a specific genomic pattern. Experimental Design: DTCs were identified in bone marrow from lung cancer patients by an immunocytochemical cytokeratin assay. Genomic aberrations and expression profiles of the respective primary tumors were assessed by microarrays and fluorescence in situ hybridization analyses. The most significant results were validated on an independent set of primary lung tumors and brain metastases. Results: Combination of DNA copy number profiles (array comparative genomic hybridization) with gene expression profiles identified five chromosomal regions differentiating bone marrownegative from bone marrow-positive patients (4q12-q32, 10p12-p11, 10q21-q22, 17q21, and 20q11-q13). Copy number changes of 4q12-q32 were the most prominent finding, containing the highest number of differentially expressed genes irrespective of chromosomal size (P = 0.018). Fluorescence in situ hybridization analyses on further primary lung tumor samples confirmed the association between loss of 4q and bone marrow-positive status. In bone marrowpositive patients, 4q was frequently lost (37% versus 7%), whereas gains could be commonly found among bone marrow-negative patients (7% versus 17%). The same loss was also found to be common in brain metastases from both small and non-small cell lung cancer patients (39%). Conclusions:Thus, our data indicate, for the first time, that early hematogenous dissemination of tumor cells might be driven by a specific pattern of genomic changes.Lung cancer is one of the most frequently diagnosed cancers in developed countries and the main cause of cancer-related deaths, with an overall relative 5-year survival rate of 15% (1). Approximately 40% of patients with completely resected nonsmall cell lung cancer (NSCLC) without lymph node metastasis (N 0 ) or clinical signs of overt distant metastases (M 0 ) at time of the primary surgery relapse within 24 months.