Immunofluorescence-based screening identifies germ cell associated microRNA 302 as an antagonist to p63 expression

The tumor suppressor homologue p63 is required for proper skin and limb development, but specific isoforms of it also act as a “guardian of the germline." To gain insight into the regulation of p63 expression, we performed immunofluorescence-based screening assays. Using a large collection of microRNA expression plasmids, we identified microRNAs of the 302 cluster as potent suppressors of p63 accumulation in various cell species. MiR-302 reduces p63 protein and mRNA levels through two target sites within the p63 3’ untranslated region. In testicular cancer cells, endogenous miR-302 contributes to the suppression of p63. MiR-302 might also contribute to the elimination of p63 in mature oocytes. Thus, miR-302 appears as part of a stringent regulatory mechanism for p63 in germ cells, reminiscent of the tight control for p53 levels in somatic cells.     

p53, p63 and p73--solos, alliances and feuds among family members

p53 controls crucial stress responses that play a major role in preventing malignant transformation. Hence, inactivation of p53 is the single most common genetic defect in human cancer. With the recent discovery of two close structural homologs, p63 en p73, we are getting a broader view of a fascinating gene family that links developmental biology with tumor biology. While unique roles are apparent for each of these genes, intimate biochemical cross-talk among family members suggests a functional network that might influence many different aspects of individual gene action. The most interesting part of this family network derives from the fact that the p63 and p73 genes are based on the "two-genes-in-one" idea, encoding both agonist and antagonist in the same open reading frame. In this review, we attempt to present an overview of the current status of this fast moving field.     

Structural diversity of p63 and p73 isoforms

AbstractThe p53 protein family is the most studied protein family of all. Sequence analysis and structure determination have revealed a high similarity of crucial domains between p53, p63 and p73. Functional studies, however, have shown a wide variety of different tasks in tumor suppression, quality control and development. Here we review the structure and organization of the individual domains of p63 and p73, the interaction of these domains in the context of full-length proteins and discuss the evolutionary origin of this protein family. Facts

• Distinct physiological roles/functions are performed by specific isoforms.
• The non-divided transactivation domain of p63 has a constitutively high activity while the transactivation domains of p53/p73 are divided into two subdomains that are regulated by phosphorylation.
• Mdm2 binds to all three family members but ubiquitinates only p53.
• TAp63α forms an autoinhibited dimeric state while all other vertebrate p53 family isoforms are constitutively tetrameric.
• The oligomerization domain of p63 and p73 contain an additional helix that is necessary for stabilizing the tetrameric states. During evolution this helix got lost independently in different phylogenetic branches, while the DNA binding domain became destabilized and the transactivation domain split into two subdomains.

Open questions

• Is the autoinhibitory mechanism of mammalian TAp63α conserved in p53 proteins of invertebrates that have the same function of genomic quality control in germ cells?
• What is the physiological function of the p63/p73 SAM domains?
• Do the short isoforms of p63 and p73 have physiological functions?
• What are the roles of the N-terminal elongated TAp63 isoforms, TA* and GTA?

Subject terms: X-ray crystallography, Solution-state NMR     

Evaluation of p63 and p73 antibodies for cross-reactivity

The tumor suppressor p53 is commonly mutated in human cancers. However, two homologs of p53, p63 and p73, are frequently over-expressed in tumors and are associated with tumor subtypes, clinical outcomes, and responses to therapy. There are many isoforms of p53, p63, and p73 (the p53 family). Proper detection of and discrimination between the members of this tumor suppressor family in human tissues is of critical importance to cancer research and clinical care. In this study, we assessed the specificity of several commercially available and newly generated p73 antibodies, focusing on antibodies that distinguish between the TAp73 and ?Np73 isoforms by Western analysis, immunohistochemistry, and immunofluorescence. In addition, we found that the pan-p63 and pan-p73 antibodies tested cross-react with p73 and p63 respectively. The results of this study have important implications for analysis of p63 and p73 expression and co-expression in human tumors, and for potential use of these reagents in molecular diagnostics and therapeutic decision-making.     

Interaction of regulators Mdm2 and Mdmx with transcription factors p53, p63 and p73

The negative regulation of p53, a major human tumor suppressor, by Mdm2 and Mdmx is crucial for the survival of a cell, whereas its aberrant function is a common feature of cancer. Both Mdm proteins act through the spatial occlusion of the p53 transactivation (TA) domain and by the ubiquitination of p53, resulting in its degradation. Two p53 homologues, p63 and p73, have been described in humans. Unlike p53, these proteins regulate developmental processes rather than genome stability. Both p63 and p73 contain TA domains homologous to that of p53, but relatively little is known about their regulation by Mdm2 or Mdmx. Here, we present a detailed characterization of the interaction of Mdm2 and Mdmx with the TA domains of p63 and p73. Earlier reports of Mdm2 and Mdmx interactions with p73 are substantiated by the detailed quantitative characterization reported in this study. Most importantly, earlier contradictions concerning the presumed interaction of the Mdm proteins with p63 are convincingly resolved and for the first time, the affinities of these interactions are determined. Finally, the contribution of these findings to our understanding of the physiological role of these interactions is discussed.     

Novel therapeutic interventions for p53-altered tumors through manipulation of its family members,p63 and p73

TP53 is highly mutated in human cancers, thus targeting this tumor suppressor pathway is highly desirable and will impact many cancer patients.^1,2 Iwakuma T, Lozano G, Flores ER. Li-Fraumeni syndrome: a p53 family affair. Cell Cycle 2005; 4:865-7; PMID:15917654; http://dx.doi.org/10.4161/cc.4.7.1800 Muller PA, Vousden KH. p53 mutations in cancer. Nat Cell Biol 2013; 15:2-8; PMID:23263379; http://dx.doi.org/10.1038/ncb2641  Therapeutic strategies to reactivate the p53-pathway have been challenging,^3,4 Martins CP, Brown-Swigart L, Evan GI. Modeling the therapeutic efficacy of p53 restoration in tumors. Cell 2006; 127:1323-34; PMID:17182091; http://dx.doi.org/10.1016/j.cell.2006.12.007 Ventura A. Restoration of p53 function leads to tumour regression in vivo. Nature 2007; 445:661-5; PMID:17251932; http://dx.doi.org/10.1038/nature05541  and no effective treatment exists.⁵ Khoo KH, Verma CS, Lane DP. Drugging the p53 pathway: understanding the route to clinical efficacy. Nat Rev Drug Discov 2014; 13:217-36; PMID:24577402; http://dx.doi.org/10.1038/nrd4288[Crossref], [PubMed], [Web of Science ®] , [Google Scholar] We utilized the p53-family members, p63 and p73, which are not frequently mutated in cancer, to treat p53-defective cancers. The N-terminal splice variants of p63 and p73 are denoted as the TA and ΔN isoforms. We recently demonstrated that deletion of either ΔNp63 or ΔNp73 in p53-deficient mouse tumors results in tumor regression mediated by metabolic programming. Using this strategy, we identified pramlintide, a synthetic analog of amylin, as an effective treatment for p53 deficient and mutant tumors. Here, we show the utility of using pramlintide, as a potential cancer preventive option for p53-deficient tumors in mouse models. Additionally, we found that in vivo inhibition of both ΔNp63 and ΔNp73 in combination accelerates tumor regression and increases survival of p53-deficient mice. We report that inhibition of both ΔNp63 and ΔNp73 in combination results in upregulation of 3 key metabolic regulators, IAPP, GLS2, and TIGAR resulting in an increase in apoptosis and tumor regression in ΔNp63/ΔNp73/p53 deficient thymic lymphomas. These data highlight the value of generating inhibitors that will simultaneously target ΔNp63 and ΔNp73 to treat cancer patients with alterations in p53.     

Targeting Notch signalling by the conserved miR-8/200 microRNA family in development and cancer cells

Notch signalling is crucial for the correct development and growth of numerous organs and tissues, and when subverted it can cause cancer. Loss of miR-8/200 microRNAs (miRNAs) is commonly observed in advanced tumours and correlates with their invasion and acquisition of stem-like properties. Here, we show that this miRNA family controls Notch signalling activation in Drosophila and human cells. In an overexpression screen, we identified the Drosophila miR-8 as a potent inhibitor of Notch-induced overgrowth and tumour metastasis. Gain and loss of mir-8 provoked developmental defects reminiscent of impaired Notch signalling and we demonstrated that miR-8 directly inhibits Notch ligand Serrate. Likewise, miR-200c and miR-141 directly inhibited JAGGED1, impeding proliferation of human metastatic prostate cancer cells. It has been suggested that JAGGED1 may also be important for metastases. Although in metastatic cancer cells, JAGGED1 modestly regulated ZEB1, the miR-200c's target in invasion, studies in Drosophila revealed that only concurrent overexpression of Notch and Zfh1/ZEB1 induced tumour metastases. Together, these data define a new way to attenuate or boost Notch signalling that may have clinical interest.     

An integrative genomic approach to uncover molecular mechanisms of prokaryotic traits

With mounting availability of genomic and phenotypic databases, data integration and mining become increasingly challenging. While efforts have been put forward to analyze prokaryotic phenotypes, current computational technologies either lack high throughput capacity for genomic scale analysis, or are limited in their capability to integrate and mine data across different scales of biology. Consequently, simultaneous analysis of associations among genomes, phenotypes, and gene functions is prohibited. Here, we developed a high throughput computational approach, and demonstrated for the first time the feasibility of integrating large quantities of prokaryotic phenotypes along with genomic datasets for mining across multiple scales of biology (protein domains, pathways, molecular functions, and cellular processes). Applying this method over 59 fully sequenced prokaryotic species, we identified genetic basis and molecular mechanisms underlying the phenotypes in bacteria. We identified 3,711 significant correlations between 1,499 distinct Pfam and 63 phenotypes, with 2,650 correlations and 1,061 anti-correlations. Manual evaluation of a random sample of these significant correlations showed a minimal precision of 30% (95% confidence interval: 20%-42%; n = 50). We stratified the most significant 478 predictions and subjected 100 to manual evaluation, of which 60 were corroborated in the literature. We furthermore unveiled 10 significant correlations between phenotypes and KEGG pathways, eight of which were corroborated in the evaluation, and 309 significant correlations between phenotypes and 166 GO concepts evaluated using a random sample (minimal precision = 72%; 95% confidence interval: 60%-80%; n = 50). Additionally, we conducted a novel large-scale phenomic visualization analysis to provide insight into the modular nature of common molecular mechanisms spanning multiple biological scales and reused by related phenotypes (metaphenotypes). We propose that this method elucidates which classes of molecular mechanisms are associated with phenotypes or metaphenotypes and holds promise in facilitating a computable systems biology approach to genomic and biomedical research.