Van Eyk, Dunn - Proteomic and Genomic Analysis of Cardiovascular Disease - 2003 (522919), страница 15
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A potent tumor-suppressor function has been confirmed by performing an in vivo loss-of-function via gene ablation studies in mice. Mice with only37382 Cardiac Disease and The Transcriptomeone functional copy of the gene are more likely to develop tumors of multiple origins, while loss of both alleles leads to embryonic lethality [60–62].PTEN is a dual-specificity phosphatase with homology to the focal adhesion-associated protein tensin [63]. In vitro, PTEN can dephosphorylate acidic polypeptides, focal adhesion kinase (FAK), and the adaptor protein, Shc. However, themajor in vivo substrate for PTEN appears to be phosphatidylinositol 3, 4, 5-triphosphate (PIP3), as embryonic fibroblasts taken from PTEN null mouse strains haveabnormally high levels of PIP3 and are resistant to apoptosis [61].
The PTEN-/- fibroblasts have very high levels of activated Akt, a serine/threonine kinase that isregulated by PIP3 and phosphatidylinositol 3, 4-biphosphate (PIP2). Intriguingly,Akt is an important regulator of both cell survival and growth [64], and PTEN hasbeen defined genetically and biochemically to act as a negative regulator of Akt inopposition to the evolutionarily conserved IGF-1/PI3K/Akt signaling pathway [65–67].
Thus, the biological annotation for this candidate is extraordinarily rich,although the data are from systems other than the heart. Nevertheless, the overallfunctional annotation of PTEN was of sufficient value as to warrant further exploration.High throughput functional screens are critical for assigning biological value tocandidates identified by genome or proteome wide screens. A general limitationof the cardiovascular field is the paucity of accurate screens for determining a candidate protein’s functional role, unless one assumes in vitro binding assays withputative partners (such as defined transcriptional factor activation domains, etc.)are truly accurate representations of a candidate’s biological role.
Therefore, to determine the (potential) role PTEN might play during cardiac hypertrophy, we restricted our approach to either cell culture or transgenic animals using complementary gain- and loss-of-function approaches whenever possible.To explore the possibility of a biological function for PTEN in the hypertrophicresponse, adenovirus was used to overexpress the protein in primary cultures ofneonatal rat cardiomyocytes. Overexpression resulted in fewer viable cells as a result of apoptotic pathway activation. More interestingly, expression of a catalytically inactive form of PTEN [63] we termed H123YPTEN, led to cardiomyocyte hypertrophy with a well-ordered sarcomeric structure being conserved in the cardiomyocytes as shown by a-actinin staining [50]. Molecular markers, cell volume andshape, as well as protein synthetic rates were all consistent with the inactive formmediating a robust hypertrophy in the cultured cardiomyocytes [50].There are several possible mechanisms by which H123YPTEN might act as adominant suppressor of endogenous PTEN, including the sequestration of PTENbinding partners needed for full activity.
For example, PTEN can bind to focal adhesion kinase directly, leading to its dephosphorylation and inactivation. Consistent with the ability of H123YPTEN to sequester FAK from endogenous PTEN,FAK tyrosine phosphorylation in AdH123Y infected cells was increased. We arecurrently analyzing whether the H123Y mutation stabilizes the interaction withFAK in cardiomyocytes.Although these data are intriguing they do not provide enough informationabout the way PTEN acts within the cellular networks to make any firm conclu-2.6 Concluding Remarkssions about its role in a physiologically relevant hypertrophy. Rather, the data illustrate that cell culture experiments represent yet another biological filter againstwhich to test putative candidates isolated from the screens.
The data do, however,justify a more extensive exploration of PTEN’s activity within the whole organ andwhole animal contexts using drug-inducible, cardiac-specific transgenesis.2.6Concluding RemarksWhen used correctly, large-scale transcriptome analyses can and will provide critical insights into the biology that underlies cardiovascular function, but only whencoupled with richly annotated databases. This has already been realized in othermammalian-based systems such as in the profiling of different tumors [68, 69], aswell as in simpler systems such as yeast [70]. With the human, mouse and rat sequence information that is now available, the list of sparsely annotated, or completely unknown genes continues to grow: perhaps the best use of the array technology in the short term for cardiovascular discovery will be to identify new candidates from this list and generate the new hypotheses that will determine the experiments necessary to define the biology of the genes and their products.The recent advances in transgenic and gene targeting approaches have significantly increased our insights into the causes and development of a number of cardiovascular diseases.
Although these animal models have their limitations, thefurther development of inducible and conditional systems will allow us to evenmore precisely control single genes. However, the pathogenesis of many humandisorders depends on the interaction of either a single or several genes with environmental factors and can be influenced by modifiers or interacting genes, thereby contributing to the heterogeneity of human disease.
Interestingly, variable penetrance consistent with the human phenotype has also been observed in somemouse models [35, 71]. Despite the differences between mice and man, studyingthe interplay of multiple factors in genetically altered mice will give us a basis forunraveling modulating mechanisms in humans, and much of the informationneeded for validation of the mouse models will come from comparing the totalhuman and murine transcriptomes during development of the various cardiovascular pathologies.Transcriptional profiling, as represented in the current literature when appliedto cardiovascular disease, suffers from a certain narrowness of view. Most studieshave focused on the response of the heart to a single surgical or pharmacologicaltreatment or genetic mutation.
The power of applying massive, parallel analysesto the problem of transcript profiling is currently best illustrated in yeast, whereHughes and colleagues first constructed a reference database or “compendium” ofexpression profiles, corresponding to 300 mutations/chemical treatments of S. cerevisiae. This massive database showed that a compendium could serve as an important reference tool, against which any yeast profile could be compared, and thesimilarities and differences then used to determine which pathways were actually39402 Cardiac Disease and The Transcriptomeperturbed in the new, unknown transcriptome by simply comparing the data tothe compendium. Thus, after the initial annotation was complete, data from theunknown could be quickly analyzed, similarities between single genes, subgroupsand groups of genes identified and a “fingerprint” of the new transcriptional profile identified.Such a task, while daunting for the heart, is obtainable; indeed elements of thisare some of the goals of a current funding initiative by the National Institutes ofHealth (http://www.nhlbi.nih.gov/resources/pga/resource.htm) and research consortia (http://www.cellularsignaling.org/).
However, the yeast data, when compared to that emanating from the cardiovascular research community, underscores the immense scope of a truly comprehensive and global analysis. A largeconsortium of experimentalists and bioinformatics experts were needed to planthe experiments, carry them out, filter the data and choose the appropriatemining algorithms for the data’s true value to emerge. Wrapping the profilingdata within the biological phenomenology, the so-called “phenome” in which themodel under study is completely characterized in terms of the changes at the cellular, biochemical, organ and system levels needs to be done by the cardiovascularcommunity in order to enhance the data’s value.
As we begin to develop more efficient ways of understanding and perturbing entire networks and the resultantfunctional consequences, the reductionist approaches that have served us so wellin the last half of the twentieth century will assume less importance. Nothing ofthis scope has been attempted in mammalian species, but it is these approachesthat will provide data mines of immense value for the formulation of novel andtestable hypotheses that will lead to unexpected and important insights into thebiogenesis of cardiovascular disease.2.7References1234Hoffman, E. P., Brown, R.
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