Ed with BRCA, BRCA and sporadic breast tumors. That is a discovering that wants further quantification and confirmation. Conclusions ArrayCGH is usually effectively applied on archival formalinfixed tumor samples. ArrayCGH profiles prove valuable inside the classification of hereditary (BRCA) breast tumors. Additional information alysis really should reveal irrespective of whether BRCAx can be classified is this manner. We propose the usage of arrayCGH profiles in clinical genetic counseling and are at present functioning towards thioal. Acknowledgement EvB and SJ are funded by the Dutch Cancer Society, NKB. References. Wessels LF, et al.: Molecular classification of breast carcinomas by comparative genomic hybridization: a distinct somatic genetic profile for BRCA tumors. Cancer Res, :. van Beers EH, et al.: CGH profiles in human BRCA and BRCA breast tumors highlight differential sets of genomic aberrations. Cancer Res, :. Jong K, et al.: Breakpoint identification and smoothing of array comparative genomic hybridization information. Bioinformatics, :. Chung YJ, et al.: A wholegenome mouse BAC microarray with Mb resolution for alysis of D copy quantity changes by array comparative genomic hybridization. Genome Res, :.P. Outcome sigture genes in breast cancer: is there a exceptional setI Kela, L EinDor, G Getz, D Givol, E Domany Department of Physics of Complex Systems and Division of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel Breast Cancer Analysis, (Suppl ):P. (DOI.bcr) Predicting the metastatic potential of key malignt tissues has direct bearing around the decision of therapy. A number of microarray 
research yielded gene sets whose expression profiles effectively predicted survival. Nonetheless, the overlap amongst these gene sets is almost zero. One of the key open questions in this [D-Ala2]leucine-enkephalin context is whether the disparity might be attributed only to trivial motives such as distinctive technologies, unique sufferers and different types of alysis. To answer this question we concentrated on one single breast cancer dataset, and alyzed it by 1 single approach, that employed by van `t Veer and colleagues, to generate an outcome predictive sigture set of genes. We show that in actual fact the resulting set of genes will not be special; it really is strongly influenced by the subset of individuals used for gene get 4EGI-1 choice. Numerous equally predictive lists could happen to be produced from the very same alysis. 3 major properties from the data explain this sensitivity: many genes are correlated with survival; the differences involving these correlations are smaller; plus the correlations fluctuate strongly when measured over distinctive subsets of sufferers. A possible correlation of this finding and the complexity of gene expression in cancer is discussed. Reference. van `t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, et al.: Gene expression profiling predicts clinical outcome of breast cancer. ture, :.P. Chromosomal imbalances mapped by arraybased comparative genomic hybridization in an integrated strategy to combat breast cancer in DenmarkJ Li, X Zhang, TD Jensen, K Wang, S K vraa, L Bolund Institute of Human Genetics, University of Aarhus, Denmark Breast Cancer Study, (Suppl ):P. (DOI.bcr) Since its invention by Kallioniemi and colleagues in, comparative genomic 
hybridization (CGH) has revolutionized the detection and mapping of chromosomal imbalances in neoplasias. Even so, conventiol CGH is handicapped by its low resolution. Arraybased CGH brings the PubMed ID:http://jpet.aspetjournals.org/content/107/2/165 resolution tow.Ed with BRCA, BRCA and sporadic breast tumors. That is a discovering that desires additional quantification and confirmation. Conclusions ArrayCGH is usually successfully applied on archival formalinfixed tumor samples. ArrayCGH profiles prove valuable within the classification of hereditary (BRCA) breast tumors. Additional data alysis need to reveal irrespective of whether BRCAx is usually classified is this manner. We propose the usage of arrayCGH profiles in clinical genetic counseling and are presently operating towards thioal. Acknowledgement EvB and SJ are funded by the Dutch Cancer Society, NKB. References. Wessels LF, et al.: Molecular classification of breast carcinomas by comparative genomic hybridization: a certain somatic genetic profile for BRCA tumors. Cancer Res, :. van Beers EH, et al.: CGH profiles in human BRCA and BRCA breast tumors highlight differential sets of genomic aberrations. Cancer Res, :. Jong K, et al.: Breakpoint identification and smoothing of array comparative genomic hybridization data. Bioinformatics, :. Chung YJ, et al.: A wholegenome mouse BAC microarray with Mb resolution for alysis of D copy number changes by array comparative genomic hybridization. Genome Res, :.P. Outcome sigture genes in breast cancer: is there a unique setI Kela, L EinDor, G Getz, D Givol, E Domany Department of Physics of Complicated Systems and Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel Breast Cancer Research, (Suppl ):P. (DOI.bcr) Predicting the metastatic possible of major malignt tissues has direct bearing on the option of therapy. Various microarray studies yielded gene sets whose expression profiles effectively predicted survival. Nonetheless, the overlap in between these gene sets is nearly zero. Among the primary open concerns within this context is no matter if the disparity may be attributed only to trivial factors like distinctive technologies, diverse sufferers and distinctive varieties of alysis. To answer this question we concentrated on 1 single breast cancer dataset, and alyzed it by one single technique, that applied by van `t Veer and colleagues, to produce an outcome predictive sigture set of genes. We show that in reality the resulting set of genes isn’t exceptional; it truly is strongly influenced by the subset of patients employed for gene choice. Quite a few equally predictive lists could have already been developed from the identical alysis. 3 key properties of your data explain this sensitivity: lots of genes are correlated with survival; the variations among these correlations are compact; and the correlations fluctuate strongly when measured over distinctive subsets of individuals. A doable correlation of this acquiring along with the complexity of gene expression in cancer is discussed. Reference. van `t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, et al.: Gene expression profiling predicts clinical outcome of breast cancer. ture, :.P. Chromosomal imbalances mapped by arraybased comparative genomic hybridization in an integrated strategy to combat breast cancer in DenmarkJ Li, X Zhang, TD Jensen, K Wang, S K vraa, L Bolund Institute of Human Genetics, University of Aarhus, Denmark Breast Cancer Study, (Suppl ):P. (DOI.bcr) Given that its invention by Kallioniemi and colleagues in, comparative genomic hybridization (CGH) has revolutionized the detection and mapping of chromosomal imbalances in neoplasias. Even so, conventiol CGH is handicapped by its low resolution. Arraybased CGH brings the PubMed ID:http://jpet.aspetjournals.org/content/107/2/165 resolution tow.