Biomedical subjects

Eytan Domany

Publications and source records attributed to Eytan Domany.

30 records · Page 2Linked to original sources

PubMed2004

Outcome signature genes in breast cancer: is there a unique set?

MOTIVATION: Predicting the metastatic potential of primary malignant tissues has direct bearing on the choice of therapy. Several microarray studies yielded gene sets whose expression profiles successfully predicted survival. Nevertheless, the overlap between these gene sets is almost zero. Such small overlaps were observed also in other complex diseases, and the variables that could account for the differences had evoked a wide interest. One of the main open questions in this context is whether the disparity can be attributed only to trivial reasons such as different technologies, different patients and different types of analyses. RESULTS: To answer this question, we concentrated on a single breast cancer dataset, and analyzed it by a single method, the one which was used by van't Veer et al. to produce a set of outcome-predictive genes. We showed that, in fact, the resulting set of genes is not unique; it is strongly influenced by the subset of patients used for gene selection. Many equally predictive lists could have been produced from the same analysis. Three main properties of the data explain this sensitivity: (1) many genes are correlated with survival; (2) the differences between these correlations are small; (3) the correlations fluctuate strongly when measured over different subsets of patients. A possible biological explanation for these properties is discussed. CONTACT: eytan.domany@weizmann.ac.il SUPPLEMENTARY INFORMATION: http://www.weizmann.ac.il/physics/complex/compphys/downloads/liate/

Biomarkers, Tumor↗

PubMed2004

Lack of ultrametricity in the low-temperature phase of three-dimensional Ising spin glasses.

We study the low-temperature spin-glass phases of the Sherrington-Kirkpatrick (SK) model and of the 3-dimensional short-range Ising spin-glass (3DISG). By using clustering to focus on the relevant parts of phase space and reduce finite size effects, we found that for the SK model ultrametricity becomes clearer as the system size increases, while for the short-range case our results indicate the opposite, i.e., lack of ultrametricity. Another method, which does not rely on clustering, indicates that the mean-field solution works for the SK model but does not apply in detail to the 3DISG, for which stochastic stability is also violated.

Journal Article↗

PubMed2004

F2CS: FSSP to CATH and SCOP prediction server.

UNLABELLED: The F2CS server provides access to the software, F2CS2.00, which implements an automated prediction method of SCOP and CATH classifications of proteins, based on their FSSP Z-scores. AVAILABILITY: Free at http://www.weizmann.ac.il/physics/complex/compphys/f2cs/ SUPPLEMENTARY INFORMATION: The site contains links to additional figures and tables.

Algorithms↗

PubMed2003

Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes.

The development of targeted treatment strategies adapted to individual patients requires identification of the different tumor classes according to their biology and prognosis. We focus here on the molecular aspects underlying these differences, in terms of sets of genes that control pathogenesis of the different subtypes of astrocytic glioma. By performing cDNA-array analysis of 53 patient biopsies, comprising low-grade astrocytoma, secondary glioblastoma (respective recurrent high-grade tumors), and newly diagnosed primary glioblastoma, we demonstrate that human gliomas can be differentiated according to their gene expression. We found that low-grade astrocytoma have the most specific and similar expression profiles, whereas primary glioblastoma exhibit much larger variation between tumors. Secondary glioblastoma display features of both other groups. We identified several sets of genes with relatively highly correlated expression within groups that: (a). can be associated with specific biological functions; and (b). effectively differentiate tumor class. One prominent gene cluster discriminating primary versus nonprimary glioblastoma comprises mostly genes involved in angiogenesis, including VEGF fms-related tyrosine kinase 1 but also IGFBP2, that has not yet been directly linked to angiogenesis. In situ hybridization demonstrating coexpression of IGFBP2 and VEGF in pseudopalisading cells surrounding tumor necrosis provided further evidence for a possible involvement of IGFBP2 in angiogenesis. The separating groups of genes were found by the unsupervised coupled two-way clustering method, and their classification power was validated by a supervised construction of a nearly perfect glioma classifier.

Adolescent↗

PubMed2003

Coupled two-way clustering analysis of breast cancer and colon cancer gene expression data.

UNLABELLED: We present and review coupled two-way clustering, a method designed to mine gene expression data. The method identifies submatrices of the total expression matrix, whose clustering analysis reveals partitions of samples (and genes) into biologically relevant classes. We demonstrate, on data from colon and breast cancer, that we are able to identify partitions that elude standard clustering analysis. AVAILABILITY: Free, at http://ctwc.weizmann.ac.il.. SUPPLEMENTARY INFORMATION: http://www.weizmann.ac.il/physics/complex/compphys/bioinfo2/

Algorithms↗

PubMed2003

Coupled two-way clustering server.

UNLABELLED: The CTWC server provides access to the software, CTWC1.00, that implements Coupled Two Way Clustering (Getz et al., 2000), a method designed to mine gene expression data AVAILABILITY: Free, at http://ctwc.weizmann.ac.il. SUPPLEMENTARY INFORMATION: The site has a link to an example which provides figures and detailed explanations

Algorithms↗

PubMed2003

Genome-wide comparison of human keratinocyte and squamous cell carcinoma responses to UVB irradiation: implications for skin and epithelial cancer.

To gain insight into the transformation of epidermal cells into squamous carcinoma cells (SCC), we compared the response to ultraviolet B radiation (UVB) of normal human epidermal keratinocytes (NHEK) versus their transformed counterpart, SCC, using biological and molecular profiling. DNA microarray analyses (Affymetrix), approximately 12000 genes) indicated that the major group of upregulated genes in keratinocytes fall into three categories: (i). antiapoptotic and cell survival factors, including chemokines of the CXC/CC subfamilies (e.g. IL-8, GRO-1, -2, -3, SCYA20), growth factors (e.g. HB-EGF, CTGF, INSL-4), and proinflammatory mediators (e.g. COX-2, S100A9), (ii). DNA repair-related genes (e.g. GADD45, ERCC, BTG-1, Histones), and (iii). ECM proteases (MMP-1, -10). The major downregulated genes are DeltaNp63 and PUMILIO, two potential markers for the maintenance of keratinocyte stem cells. NHEK were found to be more resistant than SCC to UVB-induced apoptosis and this resistance was mainly because of the protection from cell death by secreted survival factors, since it can be transferred from NHEK to SCC cultures by the conditioned medium. Whereas the response of keratinocytes to UVB involved regulation of key checkpoint genes (p53, MDM2, p21(Cip1), DeltaNp63), as well as antiapoptotic and DNA repair-related genes - no or little regulation of these genes was observed in SCC. The effect of UVB on NHEK and SCC resulted in upregulation of 251 and 127 genes, respectively, and downregulation of 322 genes in NHEK and 117 genes in SCC. To further analyse these changes, we used a novel unsupervised coupled two-way clustering method that allowed the identification of groups of genes that clearly partitioned keratinocytes from SCC, including a group of genes whose constitutive expression levels were similar before UVB. This allowed the identification of discriminating genes not otherwise revealed by simple static comparison in the absence of UVB irradiation. The implication of the changes in gene profile in keratinocytes for epithelial cancer is discussed.

Apoptosis↗

PubMed2003

Inhibition of p53-induced apoptosis without affecting expression of p53-regulated genes.

Using DNA microarray and clustering of expressed genes we have analyzed the mechanism of inhibition of wild-type p53-induced apoptosis by the cytokine interleukin 6 (IL-6) and the calcium mobilizer thapsigargin (TG). Clustering analysis of 1,786 genes, the expression level of which changed after activation of wild-type p53 in the absence or presence of IL-6 or TG, showed that these compounds did not cause a general inhibition of the ability of p53 to up-regulate or down-regulate gene expression. Expression of various p53 targets implicated as mediators of p53-induced apoptosis was also not affected by IL-6 or TG. These compounds thus can bypass the effect of wild-type p53 on gene expression and inhibit apoptosis. IL-6 and TG activated different p53-independent pathways of gene expression that include up-regulation of antiapoptotic genes. IL-6 and TG also activated different differentiation-associated genes. The ability of compounds such as cytokines and calcium mobilizers to inhibit p53-mediated apoptosis without generally inhibiting gene expression regulated by p53 can facilitate tumor development and tumor resistance to radiation and chemotherapy in cells that retain wild-type p53.

Apoptosis↗

PubMed2003

Potts ferromagnets on coexpressed gene networks: identifying maximally stable partitions.

Clustering gene expression data by exploiting phase transitions in granular ferromagnets requires transforming the data to a granular substrate. We present a method using the recently introduced homogeneity order parameter Lambda [H. Agrawal, Phys. Rev. Lett. 89, 268702 (2002)]] for optimizing the parameter controlling the "granularity" and thus the stability of partitions. The model substrates obtained for gene expression data have a highly granular structure. We explore properties of phase transition in high q ferromagnetic Potts models on these substrates and show that the maximum of the width of superparamagnetic domain, corresponding to maximally stable partitions, coincides with the minimum of Lambda.

Colonic Neoplasms↗

PubMed2003

Cluster analysis of human autoantibody reactivities in health and in type 1 diabetes mellitus: a bio-informatic approach to immune complexity.

Informatic methodologies are being applied successfully to analyze the complexity of the genome. But beyond the genome, the immune system reflects the state of the body in health and disease. Traditionally, immunologists have reduced the immune system, where possible, to one-to-one relationships between particular antigens and particular antibodies or T-cell clones. Autoimmune diseases, caused by an immune attack against a body component, are usually investigated by following the response to single self-antigens. In this study, we apply informatics to analyze patterns of autoantibodies rather than single species of autoantibodies. This study was designed not to replace traditional approaches to immune diagnosis, but to test whether meaningful patterns of autoantibodies might exist. Using an unbiased solid-phase ELISA antibody test, we detected serum IgG and IgM antibodies in the sera of 20 healthy persons and 20 persons with type 1 diabetes mellitus binding to an array of 87 different antigens, mostly self-antigens. The healthy subjects manifested autoantibodies to a variety of self-antigens, many known to be associated with autoimmune diseases. We investigated the patterns of these autoantibodies using a coupled two-way clustering algorithm developed for analyzing data from gene arrays. We now report that the reactivity patterns of autoantibodies to particular subsets of self-antigens exhibited non-trivial structure, which significantly discriminated between healthy persons and persons with type 1 diabetes. The results show that despite the wide prevalence of autoantibodies, the patterns of reactivity to defined subsets of self-antigens can provide information about the state of the body.

Autoantibodies↗

PubMed2002

Automated assignment of SCOP and CATH protein structure classifications from FSSP scores.

We present an automated procedure to assign CATH and SCOP classifications to proteins whose FSSP score is available. CATH classification is assigned down to the topology level, and SCOP classification is assigned to the fold level. Because the FSSP database is updated weekly, this method makes it possible to update also CATH and SCOP with the same frequency. Our predictions have a nearly perfect success rate when ambiguous cases are discarded. These ambiguous cases are intrinsic in any protein structure classification that relies on structural information alone. Hence, we introduce the "twilight zone for structure classification." We further suggest that to resolve these ambiguous cases, other criteria of classification, based also on information about sequence and function, must be used.

Algorithms↗

PubMedDate not supplied

GeneNote: whole genome expression profiles in normal human tissues.

A novel data set, GeneNote (Gene Normal Tissue Expression), was produced to portray complete gene expression profiles in healthy human tissues using the Affymetrix GeneChip HG-U95 set, which includes 62 839 probe-sets. The hybridization intensities of two replicates were processed and analyzed to yield the complete transcriptome for twelve human tissues. Abundant novel information on tissue specificity provides a baseline for past and future expression studies related to diseases. The data is posted in GeneNote (http://genecards.weizmann.ac.il/genenote/), a widely used compendium of human genes (http://bioinfo.weizmann.ac.il/genecards).

Gene Expression↗