Evidence of a Role for Antizyme and Antizyme Inhibitor as Regulators of Human Cancer

Vascular Biology Program, Department of Surgery, Children's Hospital Boston, MA, USA.
Molecular Cancer Research (Impact Factor: 4.38). 08/2011; 9(10):1285-93. DOI: 10.1158/1541-7786.MCR-11-0178
Source: PubMed


Antizyme and its endogenous antizyme inhibitor have recently emerged as prominent regulators of cell growth, transformation, centrosome duplication, and tumorigenesis. Antizyme was originally isolated as a negative modulator of the enzyme ornithine decarboxylase (ODC), an essential component of the polyamine biosynthetic pathway. Antizyme binds ODC and facilitates proteasomal ODC degradation. Antizyme also facilitates degradation of a set of cell cycle regulatory proteins, including cyclin D1, Smad1, and Aurora A kinase, as well as Mps1, a protein that regulates centrosome duplication. Antizyme has been reported to function as a tumor suppressor and to negatively regulate tumor cell proliferation and transformation. Antizyme inhibitor binds to antizyme and suppresses its known functions, leading to increased polyamine synthesis, increased cell proliferation, and increased transformation and tumorigenesis. Gene array studies show antizyme inhibitor to be amplified in cancers of the ovary, breast, and prostate. In this review, we summarize the current literature on the role of antizyme and antizyme inhibitor in cancer, discuss how the ratio of antizyme to antizyme inhibitor can influence tumor growth, and suggest strategies to target this axis for tumor prevention and treatment.

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    • "Exceptional translation (4): a single translational frameshift is highly conserved D. melanogaster has a single example of translational frameshifting, involving the gene Oda (Ornithine decarboxylase antizyme) (Ivanov et al. 1998). This event is part of a mechanism of polyamine autoregulation that is conserved from yeast through mammals (Ivanov et al. 2000; Olsen and Zetter 2011). The ornithine decarboxylase antizyme regulates the activity of the enzyme ornithine decarboxylase (ODC), a key enzyme in the synthesis of polyamines. "
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    ABSTRACT: In the context of the FlyBase annotated gene models in Drosophila melanogaster, we describe the many exceptional cases we have curated from the literature or identified in the course of FlyBase analysis. These range from atypical but common examples such as dicistronic and polycistronic transcripts, non-canonical splices, trans-spliced transcripts, non-canonical translation starts, and stop-codon readthroughs, to single exceptional cases such as ribosomal frameshifting and HAC1-type intron processing. In FlyBase, exceptional genes and transcripts are flagged with Sequence Ontology terms and/or standardized comments. Because some of the rule-benders create problems for handlers of high-throughput data we discuss plans for flagging these cases in bulk data downloads. Copyright © 2015 Author et al.
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    • "Keren-Paz et al. (2006) also demonstrated that AzI-overexpressing cells grew in the presence of low concentrations of serum, formed colonies in soft agar and gave rise to tumours when injected into nude mice, which all are attributes of transformed cells. In addition, AzI has been found to be up-regulated in a large number of cancers and thus may be regarded as a putative oncogene (Jung et al. 2000; Schaner et al. 2003; van Duin et al. 2005; Chin et al. 2007; Olsen and Zetter 2011). Conversely, silencing of AzI expression has been shown to reduce cell proliferation in vitro (Choi et al. 2005; Keren-Paz et al. 2006; Kim et al. 2006; Olsen et al. 2012), as well as repress tumour growth in vivo (Olsen et al. 2012). "
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    ABSTRACT: The polyamines are important for a variety of cellular functions, including cell growth. Their intracellular concentrations are controlled by a complex network of regulatory mechanisms, in which antizyme (Az) has a key role. Az reduces the cellular polyamine content by down-regulating both the enzyme catalysing polyamine biosynthesis, ornithine decarboxylase (ODC), and the uptake of polyamines. The activity of Az is repressed by the binding of a protein, named Az inhibitor (AzI), which is an enzymatically inactive homologue of ODC. Two forms of AzI have been described: AzI1, which is ubiquitous, and AzI2 which is expressed in brain and testis. In the present study, we have investigated the role of AzI1 in polyamine homeostasis and cell proliferation in breast cancer cells. The results obtained showed that the cellular content of AzI increased transiently after induction of cell proliferation by diluting cells in fresh medium. Inhibition of polyamine biosynthesis induced an even larger increase in the cellular AzI content, which remained significantly elevated during the 7-day experimental period. However, this increase was not a consequence of changes in cell cycle progression, as demonstrated by flow cytometry. Instead, the increase appeared to correlate with the cellular depletion of polyamines. Moreover, induced overexpression of AzI resulted in an increased cell proliferation with a concomitant increase in ODC activity and putrescine content. During mitosis, AzI1 was localised in a pattern that resembled that of the two centrosomes, confirming earlier observations. Taken together, the results indicate that AzI fulfils an essential regulatory function in polyamine homeostasis and cell proliferation.
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    • "The following literature analysis suggests their possible regulations either with HIF or hypoxia. The AZIN1 was an inhibitor for the antizyme and both were highly regulated in human cancers and antizyme induced HIF, during increased cellular redox potential [51-53]. The TICAM2 physically bridged toll like receptor-4 (TLR4) with TICAM1 and the TLR4 partially regulated by the HIF during adenocarcinoma [54,55]. "
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    ABSTRACT: Background The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used ‘Gene Ontology semantic similarity score’ to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal) and disease (cancer) sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Results Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95) identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1–4). Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1), chemotherapy/drug resistance biomarkers (panel 2), hypoxia regulated biomarkers (panel 3) and lung extra cellular matrix biomarkers (panel 4). Conclusions Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3), HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1/SAG, AIB1 and AZIN1) are significantly down regulated. All down regulated genes in this panel were highly up regulated in most other types of cancers. These panels of proteins may represent signature biomarkers for lung cancer and will aid in lung cancer diagnosis and disease monitoring as well as in the prediction of responses to therapeutics.
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