PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Genomic Profiles Associated with Early Micrometastatis in Lung Cancer: Relevance of 4q Deletion
Michaela Wrage, Salla Ruosaari, Paul P. Eijk, Jussuf T. Kaifi, Jaakko Hollmen, Emre F. Yekebas, Jacob R. Izbicki, Ruud H. Brakenhoff, Thomas Streichert, Sabine Riethdorf, Bauke Ylstra, Klaus Pantel and Harriet Wikman
Clinical Cancer Research 2008.


PURPOSE: Bone marrow (BM) 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 BM from lung cancer patients by an immunocytochemical cytokeratin assay. Genomic aberrations and expression profiles of the respective primary tumors were assessed by microarrays and FISH 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 CGH) with gene expression profiles identified five chromosomal regions differentiating BM-negative from BM-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). FISH analyses on further primary lung tumor samples confirmed the association between loss of 4q and the BM-positive status. In BM-positive patients, 4q was frequently lost (37% vs. 7%), whereas gains could be commonly found among BM-negative patients (7% vs. 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 hematogeneous dissemination of tumor cells might be driven by a specific pattern of genomic changes.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
ID Code:4209
Deposited By:Jaakko Hollmen
Deposited On:21 November 2008