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Biomedical subjects

G Getz

Publications and source records attributed to G Getz.

7 recordsLinked to original sources
PubMed2003

Expression profiles of acute lymphoblastic and myeloblastic leukemias with ALL-1 rearrangements.

The ALL-1 gene is directly involved in 5-10% of acute lymphoblastic leukemias (ALLs) and acute myeloid leukemias (AMLs) by fusion to other genes or through internal rearrangements. DNA microarrays were used to determine expression profiles of ALLs and AMLs with ALL-1 rearrangements. These profiles distinguish those tumors from other ALLs and AMLs. The expression patterns of ALL-1-associated tumors, in particular ALLs, involve oncogenes, tumor suppressors, antiapoptotic genes, drug-resistance genes, etc., and correlate with the aggressive nature of the tumors. The genes whose expression differentiates between ALLs with and without ALL-1 rearrangement were further divided into several groups, enabling separation of ALL-1-associated ALLs into two subclasses. One of the groups included 43 genes that exhibited expression profiles closely linked to ALLs with ALL-1 rearrangements. Further, there were evident differences between the expression profiles of AMLs in which ALL-1 had undergone fusion to other genes and AMLs with partial duplication of ALL-1. The extensive analysis described here pinpointed genes that might have a direct role in pathogenesis.

Chromosome Aberrations↗
PubMed2001

DNA microarrays identification of primary and secondary target genes regulated by p53.

The transcriptional program regulated by the tumor suppressor p53 was analysed using oligonucleotide microarrays. A human lung cancer cell line that expresses the temperature sensitive murine p53 was utilized to quantitate mRNA levels of various genes at different time points after shifting the temperature to 32 degrees C. Inhibition of protein synthesis by cycloheximide (CHX) was used to distinguish between primary and secondary target genes regulated by p53. In the absence of CHX, 259 and 125 genes were up or down-regulated respectively; only 38 and 24 of these genes were up and down-regulated by p53 also in the presence of CHX and are considered primary targets in this cell line. Cluster analysis of these data using the super paramagnetic clustering (SPC) algorithm demonstrate that the primary genes can be distinguished as a single cluster among a large pool of p53 regulated genes. This procedure identified additional genes that co-cluster with the primary targets and can also be classified as such genes. In addition to cell cycle (e.g. p21, TGF-beta, Cyclin E) and apoptosis (e.g. Fas, Bak, IAP) related genes, the primary targets of p53 include genes involved in many aspects of cell function, including cell adhesion (e.g. Thymosin, Smoothelin), signaling (e.g. H-Ras, Diacylglycerol kinase), transcription (e.g. ATF3, LISCH7), neuronal growth (e.g. Ninjurin, NSCL2) and DNA repair (e.g. BTG2, DDB2). The results suggest that p53 activates concerted opposing signals and exerts its effect through a diverse network of transcriptional changes that collectively alter the cell phenotype in response to stress.

Animals↗
PubMed2000

Coupled two-way clustering analysis of gene microarray data.

We present a coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task. We present an algorithm, based on iterative clustering, that performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

Cluster Analysis↗
PubMed1982

Alteration of protein synthesis and induction of specific protein phosphorylation by hyperthermia.

Confluent cultures of the mouse cell line clone 1D were subjected to 1-hr hyperthermic treatments. Temperatures were increased from the control level of 37 degrees to values ranging from 38 to 45 degrees. Protein synthesis patterns were determined in fluorograms of sodium dodecyl sulfate-polyacrylamide gels labeled with [3H]leucine. Although incorporation into most proteins was either repressed or decreased by the treatment, several proteins showed an increased label of were apparently induced de novo. Among the induced proteins was a prominent band, probably a doublet, with an estimated molecular weight of 70,000 to 69,000. Crude cell lysates made from 37 degrees, 41 degrees, and 45 degrees-treated cells were tested for kinase activity at 30 degrees by a 10-min incubation with adenosine [gamma-32P]triphosphate. Several specific proteins exhibited increased phosphorylation, while phosphorylation of other proteins decreased. The most significant increase in phosphorylation was shown by a protein with molecular weight of about 37,000. We suggest that heat treatment induces or activates one or more specific phosphokinase(s) with the ability to phosphorylate proteins with approximate molecular weights of 37,000, 36,000, 23,000, and 16,000.

Animals↗