C H A P T E R

11Nuclear Receptor Co-regulators

David M. Lonard, Bert W. O’MalleyDepartment of Molecular and Cellular Biology, Baylor College of Medicine, One Baylor Plaza, Houston,

TX 77030, USA

INTRODUCTION

Since the discovery of the first co-activator 15 years ago [1], co-regulator biology has developed as an inte-gral part of our understanding of nuclear receptor (NR)-mediated biology. NRs are members of a superfamily of ligand-regulated (and orphan) transcription factors that transduce steroid, retinoid, thyroid, and lipophilic endo-crine hormones into specific physiological responses. NRs were identified as receptors for their cognate ligands and they primarily function as ligand-activated DNA-binding transcription factors [2]. Ultimately, 48 NRs have been identified in humans, including many ‘orphan’ NRs for which a cognate ligand has yet to be identified [3]. As examples, the progesterone (PR), androgen (AR), and estrogen (ERα and ERβ) recep-tors function in reproduction and target tissue growth; the thyroid hormone receptors (TR) control oxidative metabolism; the glucocorticoid receptor (GR) regulates glucose metabolism, inflammation, and stress; and per-oxisome proliferator-activated receptors (PPARs) have central roles in regulating energy and lipid metabolism. NRs have been popular drug targets and a variety of synthetic ligands are used clinically.

As transcription factors, NRs directly regulate the expression of hormone response genes. This regulatory capacity of NRs occurs because of their ability to recog-nize specific sequences in the promoters of their target genes, and their interaction with the RNA polymerase II holocomplex and the chromatin environment that sur-rounds the genes they regulate [3]. Central to our discus-sion here, co-regulators have broad genome-wide effects on mRNA expression through their ability to interact with numerous NRs and other non-NR transcription factors. Co-activators that enhance NR-mediated tran-scription have counterparts known as co-repressors that act in an opposite manner to repress gene expression,

Genetic Steroid Disorders. http://dx.doi.org/10.1016/B978-0-12-416006-4.00024-7 30

primarily through their interaction with unliganded NRs [4]. Here, we will focus mostly on co-activators as they have been more broadly studied. Presently, more than 400 co-regulators have been reported in the literature, frequently in connection with numerous physiological functions and pathological states [5].

MOLECULAR FEATURES OF CO-ACTIVATORS

As more co-regulators were identified, it was realized early on that they vary considerably in their amino acid compositions. It was found that they possess a diverse array of enzymatic and functional capabilities that control transcription, emphasizing the complex regulatory events involved in regulating RNA polymerase II-mediated transcription [2]. They are not merely “bridging” agents between NRs and RNA polymerase II as first thought, but possess numerous enzymatic capabilities that regulate all of the multiple substeps of transcription [6]. Initially, after the identification of ERAP160, a protein that specifi-cally interacts with agonist-bound receptors [7], and the cloning of the first NR co-activator SRC-1 [1], we thought that only a handful of co-activators would be identified; instead, given that we now know how complex transcrip-tion really is, the much larger number of co-regulators that have been identified is not too surprising [5].

CO-ACTIVATORS EXIST IN MULTIPROTEIN COMPLEXES

Recent advancements in high-throughput proteomic technologies are allowing us a means to understand how multiple proteins work together at a functional level [8]. Following their discovery, molecular biological

Copyright © 2014 Elsevier Inc. All rights reserved.1

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analyses revealed that co-activators and co-repressors, like most other regulatory proteins, exist in large steady-state multiprotein complexes in mammalian cells [9,10]. We now believe that gene transcription occurs as a consequence of the sequential recruitment by DNA-binding transcription factors (TFs) of a series of different co-activator complexes that are required for accurate and efficient gene expression [11]. These multi-subunit complexes contain a collection of the diverse enzymes needed to direct distinct subreactions of tran-scription, such as histone acetylation, methylation, ubiquitination, nucleosome rearrangement, transcrip-tional initiation and elongation, RNA splicing, and, finally, degradation of the ‘activated’ co-regulators and TFs themselves [2]. In short, our current understanding of transcription is quite different from earlier theories that considered the role of only a single functional pro-tein in this process. Many examples of the compositions of these multiprotein complexes are available, and the cooperative actions of different co-activators in the transcription of specific genes have been demonstrated in multiple contexts [12–14].

CO-ACTIVATORS ARE MASTER REGULATORS OF GENE EXPRESSION

PROGRAMS

The complexity of these co-activator complex enzy-matic machines contributes to a great deal of regulatory flexibility in the control of NR-mediated transcription [2]. In addition to functioning as histone code writing proteins that place post-translational marks (PTMs) on

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histones, co-activators and co-co-activators serve as recipients of PTMs themselves (Fig. 11.1). Co-regulator activity is determined by its phosphorylation, acetyla-tion, and methylation status that forms a co-activator PTM code. This code then goes on to establish the co-activator complex’s transcriptional activity and prefer-ences for different transcription factors and target genes [15]. In this way, the co-activator PTM code is able to regulate the co-activator’s function as a “master gene” that can control broad transcriptional programs respon-sible for cell growth, differentiation, and metabolic func-tions [16]. Our laboratory has discovered that SRC-3 is phosphorylated at specific serine/threonine residues by growth factors’ signaling cascades that generate a dis-tinct phosphorylation code on the co-activator (Fig. 11.2). This upstream signaling is then channeled through the PTM-encoded co-activator to the selective co-activation of NR and other transcription factors [17]. This finding is likely to explain why overexpression of both SRC-3 and the human epidermal growth factor receptor (her-2/neu) kinase is associated with decreased breast cancer survival and tamoxifen resistance [18,19]. Growth factor signaling systems and co-activators thus work in coordi-nation to control gene expression programs responsible for cell growth.

Because of the central role that PTM coding has in co-activator biology, high-throughput proteomic tech-nologies are expected to contribute to a greater under-standing of co-activator biology. We and others have shown that co-activator proteins are degraded by ubiq-uitin-dependent (Fig. 11.3A) and -independent protea-some pathways (Fig. 11.3B) [20,21]. In normal tissues, most co-activators are expressed at a steady level and are

FIGURE 11.1 SRC-3 regulates gene expression at multiple levels. Kinase targeting of SRC-3 can alter its biological activity to differentially influence its classical function as a coactivator (1). SRC-3 can also influence transcript splicing decisions in conjunction with the co-co-activator Caper α (2). In (3), SRC-3 acts as a translational repressor for cytokines, and in (4) it functions at the cell membrane to regulate cell motility. P, Phosphorylation. See color plate at the back of the book.

THE RElATioNsHiP BETwEEN Co-REgulAT

not subject to dynamic regulation in response to exter-nal stimuli (PGC-1 is an exception) [22], although can-cer cells may also alter co-activator expression through upregulation at the mRNA level or through gene ampli-fication. At the protein level, cellular co-activator con-centration is extensively regulated by PTMs in response to NR ligands and other stimuli that activate growth fac-

tor signaling pathways [20,23].

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THE RELATIONSHIP BETWEEN CO-REGULATORS AND HUMAN

GENETIC DISORDERS

More than 100 mouse genetic models exist that link individual co-regulators to distinct physiological func-tions and pathological states, as described in a previ-

ous review [5]. Here, we will discuss some of the more

TNF

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FIGURE 11.2 Upstream kinase signaling systems influence SRC-3 transcription factor preferences. Upstream signaling systems induced by estrogens (E), tumor necrosis factor-α (TNFα) and by the Her-2 and epidermal growth factor receptor (EGFR) signaling systems impinge on SRC-3, resulting in distinct post-translational modification patterns that direct the co-activator’s preference for the estrogen receptor (ER), NF-κB, or other transcription factors (TF), leading to distinct patterns of overall gene expression and altered cellular functions. IKK, IκB kinase; PK, protein kinase; MAPK, MAP kinase; CARM1, co-activator-associated arginine methyltransferase 1; CoA-X, co-activator X; CoA-Y; co-activator Y. See color plate at the back of the book.

(A) (B)

FIGURE 11.3 Two distinct proteasome-mediated pathways are responsible for cellular SRC-3 protein degradation. In (A) transcriptionally engaged SRC-3 is targeted by ubiquitin ligases, leading to ubiquitination and degradation of the co-activator. In (B), cellular SRC-3 that is not en-gaged in transcription is targeted by the REGγ proteasome for degradation in an ubiquitin-independent manner to regulate the steady state levels of the inactive form of SRC-3. See color plate at the back of the book.

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recent findings that connect co-regulators to human dis-ease and physiology, focusing on findings that allow us to emphasize how co-regulators can be illustrated to be prominent molecular components of human disease.

First, we will discuss the steroid receptor co-activator (SRC) family, composed of SRC-1, SRC-2 (TIF2/GRIP1/NCOA2), and SRC-3 (AIB1/ACTR/NCOA3). Each member of the SRC family enhances the transcriptional activities of NRs and other transcription factors [2], and mouse genetic studies have demonstrated distinct roles for each SRC in reproduction, energy metabolism, and cancer [2,24]. Importantly, these mouse genetic stud-ies have revealed interesting links between SRCs and distinct human genetic disorders. For instance, a strik-ing similarity in the phenotype between SRC-2-/- mice and humans suffering from Von Gierke’s disease has been reported [25]. Mutations in glucose-6-phosphatase (G6Pase), a rate-limiting enzyme that serves as a gate-keeper for hepatic glucose release into the plasma, is responsible for this genetic syndrome. SRC-2 functions as a key regulator of G6Pase expression, and deletion of the SRC-2 gene in mice results in reduced G6Pase expression, mimicking human Von Gierke’s syndrome. In addition to this, further characterization of SRC-2 in mice has uncovered roles for it in regulating fat absorp-tion and whole body energy accretion [26].

Other mouse knockout studies have found that SRC-1 and SRC-2 possess additional and distinct roles in energy metabolism. SRC-1-/- mice become obese owing to decreased energy expenditure. On the other hand, and outside of its impact on liver glycogen regu-lation, SRC-2-/- mice are leaner because of the reduced transcriptional co-activation of PPARγ2, an NR that drives adipocyte differentiation [27]. In SRC-2 knock-out mice, an increase in PGC-1α interaction with SRC-1 is observed, promoting thermogenesis in brown fat. In contrast, SRC-3 promotes white adipose cell differentia-tion and knockout of SRC-3 in mice results in decreased adipose tissue mass [28].

In another study, SRC-3 was found to have a central role in regulating long-chain fatty acid metabolism by reg-ulating expression of the carnitine/acylcarnitine translo-case (CACT) gene [29]. Oxidation of lipids is essential for survival in fasting and other catabolic conditions, spar-ing glucose for use by glucose-dependent tissues such as the brain. Genetic defects in CACT expression in humans results in a constellation of metabolic problems, includ-ing the build-up of toxic metabolites leading to hypo-ketotic hypoglycemia, hyperammonemia, and impaired neurologic, cardiac, and skeletal muscle performance, each of which is apparent in SRC-3-/- mice. As is the case in human cases of CACT deficiency, dietary rescue with short-chain fatty acids ameliorates the metabolic consequences of the disease in mice devoid of SRC-3. These findings position SRC-3 as a key regulator of

β-oxidation in muscle. Moreover, these data demonstrate yet another potential link between a solely monogenic syndrome caused by the loss of a metabolic enzyme and a co-activator. Taken as a whole, it is clear that all three SRC family co-activators have broad and distinct regu-latory roles needed for healthy, normal energy metabo-lism. This may seem surprising given the emphasis that SRC family co-activators receive for their roles in cancer biology. However, given the fact that energy metabolism is grossly reconfigured in cancer cells, it makes sense that the roles that SRC co-activators have in regulat-ing energy metabolism are utilized by cancer cells to enhance cancer cell growth.

Examples exist for other co-activators that are involved in genetic disease states. Peroxisome prolif-erator-activated receptor γ (PPARγ) co-activator-1 α (PGC-1α) is another co-activator responsible for the regulation of energy metabolism [30,31]. It has been demonstrated that PGC-1α is expressed in muscle and brown adipose tissue in mice and its expression is highly inducible in response to fasting and cold exposure. In humans, a polymorphism in the PGC-1α gene and in the gene’s promoter have been reported to be associ-ated with an increased risk for type 2 diabetes [32,33]. A related co-activator, PGC-1β has been knocked out in mice, revealing that it too regulates energy metabo-lism. PGC-1β-/- mice experience reduced mitochondrial function and defects in fatty acid metabolism [34-36]. PGC-1β overexpression promotes the formation of oxidative type IIx slow twitch muscle fiber which is responsible for long duration physical exercise [37]. Disruption of PGC-1α function has been implicated in impaired mitochondrial biogenesis and energy metabo-lism, bringing it to attention as a possible drug target. For instance, a drug that could stimulate PGC-1α could be used to treat mitochondrial defects associated with Huntington’s disease [38] or in the regulation of bile acid homeostasis [39].

Co-activators have also been implicated in genetic diseases that affect the nervous system, immune response, and other biological systems. Rubinstein–Taybi syndrome results from mutations in the cyclic AMP response element binding protein (CBP) or p300 genes, and leads to mental retardation and morphologi-cal facial defects [40,41]. Because CBP and p300 are both strong histone acetyltransferases and Rubinstein–Taybi syndrome cells from patients have chromatin with hypoacetylated histones, HDAC inhibitors have been investigated as drugs to treat this syndrome [42]. The phenotype of this syndrome possesses pleiotropic char-acteristics that are also seen in other co-activator-related genetic diseases. While the neurological problems asso-ciated with Rubinstein–Taybi syndrome receive the most attention, these patients suffer from a variety of other medical issues [43].

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Co-REPREssoRs ANd

SRC-1 also plays a role in brain development. In the cerebellum, Purkinje cells express SRC-1 and a time course analysis of Purkinje cell development during embryogenesis revealed a delay in the development of these cells in SRC-1-/- mice. Loss of SRC-1 led to mod-erate motor dysfunction in adult mice [44]. SRC-1 and SRC-3 have been implicated in other aspects of brain function related to their role in modulating the actions of sex steroids in distinct regions of the brain [45].

In thyroid development, TAZ/WWTR1 has been shown to be a co-activator for Pax8 and other genes nec-essary for thyroid differentiation, and its misregulation has been linked to thyroid dysgenesis [46]. Also, TAZ/WWTR1 overexpression has been linked to thyroid carcinomas [47]. In a separate study, thyroid receptor-mediated gene expression was found to depend on the CARM1 and SNF5 co-activators which work together to drive transcription of genes required for thyroid gland differentiation [48].

Another potential link between a co-activator and neurological function was identified for metastasis- associated protein 1 (MTA1), a co-activator that is over-expressed in breast and other cancers, revealing a role for it in the regulation of dopamine production in the brain [49]. MTA1 was found to promote expression of tyrosine hydroxylase (TH) in neuronal cells and MTA1-/- mice had lower TH expression in the striatum and sub-stantia nigra. MTA1 drives TH expression in conjunction with DJ1 (Parkinson disease 1) and Pitx3 at the bicoid binding element (BBE) on the TH promoter. Because defects in Pitx3 and DJ1 expression have already been linked to Parkinson disease, MTA1 likely contributes to the control of TH expression.

Majeed syndrome has been linked to a missense mutation (S734L) in the Lipin-2 co-activator, manifesting as inflammation, osteomyelitis, fever, and anemia [50]. Lipin-1 has been reported to function as a co-activator for PPARγ [51], and investigation of an S734L mutation in the related Lipin-2 protein in patients with Majeed syndrome is linked to enzymatic function as a phospha-tidate phosphatase [52] that is required for its function as a co-activator.

Co-activators have also been linked to cardiac disease. Myocardin-related transcription factor-A (MRTF-A) is a potent co-activator that promotes serum response factor-driven gene expression [53]. Stretching of cardiomyo-cytes induces nuclear accumulation of MRTF-A, leading to enhanced SRF-mediated gene expression. In MRTF-A-/- mice, expression of brain natriuretic peptide (BNP) and other SRF-dependent fetal cardiac genes in response to acute mechanical stress was blunted [54]. In relation to cardiac disease, mutation of an SRF-binding site within the BNP promoter, or knockdown of MRTF-A, reduced the responsiveness of the BNP promoter to mechanical stretching. Overall, these findings illustrate a unique

mechanism where mechanical stress-regulated nuclear import of a co-activator controls cardiac myocyte gene expression.

CO-REPRESSORS AND GENETIC DISEASE

Silencing mediator (co-repressor) for retinoid and thyroid hormone receptors (SMRT) [55] and nuclear receptor co-repressor (NCoR) [56] were the first co-repressors identified, and they have been extensively studied in cell culture and animal model systems [57]. They too have been associated with certain genetic dis-orders and could have value as drug targets [58]. Their link to human disease explains the molecular features of genetic resistance to thyroid hormones. Humans with resistance to thyroid hormone (RTH) often possess point mutations in their thyroid hormone receptors, result-ing in a failure of the mutant receptor to release NCoR or SMRT in the presence of thyroid hormone, resulting in a spectrum of medical problems [59]. In addition to their role in RTH, NCoR and SMRT have been linked to acute promyelocytic leukemia and acute myeloid leu-kemia. Genetic translocations that result in the expres-sion of co-repressor proteins fused to other proteins that are not normally regulated by NCoR or SMRT lead to inappropriate repression of genes required to arrest cell growth. In many of these leukemias, treatment with HDAC inhibitors that inhibit NCoR- and SMRT- associated HDACs can be particularly effective [60]. Another related example is the BCL-6-interacting co-repressor (BCoR) that has been linked to oculofaciocar-diodental and Lenz microphthalmia syndromes [61]. BCoR is a co-repressor of retinoid acid signaling, and fusions between it and the retinoic acid receptor-α occur in some acute promyelocytic leukemias [62].

Brachydactyly mental retardation syndrome (BDMR) occurs due to deletions at the chromosome 2q37 locus, resulting in disabilities, developmental delays, behav-ioral abnormalities, sleep disturbance, craniofacial and skeletal abnormalities, and autism. Mapping analysis of this deletion region revealed that the histone deacetylase 4 (HDAC4) is responsible for the BDMR phenotype [63]. Consistent with the human phenotype, Hdac4-/- mice suffer from bone malformations owing to premature ossification of developing bones [64].

Following observations that histone deacetylases (HDACs) are involved in the repression of proinflamma-tory cytokines in alveolar macrophages, a link was found between HDACs and chronic obstructive pulmonary disease (COPD) [65]. Total HDAC activity in alveolar macrophages from COPD patients is inversely corre-lated with disease severity. In healthy macrophages, acti-vated glucocorticoid receptors are able to direct HDACs to the promoters of proinflammatory cytokines to reduce

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airway swelling, but in COPD the loss of HDAC activ-ity blunts the anti-inflammatory actions of glucocorti-coids. By combining glucocorticoids with the HDAC activator theophylline, it was possible to restore the anti-inflammatory effects of glucocorticoids in patients with COPD [66]. A related mechanism has been reported to be responsible for glucocorticoid resistance in patients with asthma and in other inflammatory diseases in the lung [67,68].

CO-REGULATORS AND CANCER

By modulating gene expression regulated by hor-mones, growth factors, and cytokines, co-regulators can promote pathological processes associated with cancer, including cell proliferation, differentiation, carcinogen-esis, and metastasis [2]. The SRC family of co-activators has been prominently implicated in a wide number of cancer types and, because of this, they deserve strong consideration as key targets for future anti-cancer drugs. This is attested to by the findings that SRC-3 expres-sion is upregulated significantly in breast cancers and correlates with HER2-positive status, disease recur-rence in HER2-positive breast cancers and resistance to tamoxifen [69,70]. Recent work has shown that SRC-1 is required for breast cancer metastasis in a mouse model system [71]. SRC-3 has been implicated in a wide range of cancers and, more recently, it has been shown to be highly associated with rapid progression of lung can-cers [72,73]. Recurrent oncogenic themes in lung cancers have identified several potential therapeutic targets, including epidermal growth factor receptor (EGFR), K-ras, PIK3CA, BRAF, and p53 [74–78]. Although new drugs based on these proteins have been developed (e.g. the EGFR inhibitors gefitinib and erlotinib) [79,80], their monotherapeutic clinical efficacy has been limited. Indeed, a common theme of the most recent clinical stud-ies has been the inability of any one therapeutic strategy by itself to block cancer cell growth [39]. With that in mind, it is possible that approaches that combine exist-ing targeted therapy with co-activator-targeting drugs might be used to treat cancers more effectively.

CO-ACTIVATORS AND RESISTANCE TO CHEMOTHERAPY

Cancers are highly adaptable and frequently evade the growth-inhibiting action of individual anti-cancer agents. For instance, growth factor signaling cascades such as the HER-2/neu, PI3/AKT, NF-κB pathways are frequently activated in breast cancers in response to treatment with anti-estrogens. With a diversity of growth-promoting mechanisms available to it, the

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cancer cell can evade targeted chemotherapeutic agents designed to inactivate specific growth factor pathways. However, because SRC-3 lies at the nexus between ste-roid hormone and growth factor signaling as an integra-tor [16], the response of cancer cells to small molecule inhibitors (SMIs) that perturb its co-activator function is predicted to be different. SRC-3 receives growth sig-naling information by kinases in the PKCι, PKCζ [81], PI3/AKT [82], NF-κB [83], and other growth factor sig-naling pathways. Phosphorylation of SRC-3 by these kinases licenses SRC-3 to function as a co-activator for many transcription factors such as ERα, NF-κB, and E2F1 [84]. Because of SRC-3’s central position at the hub of multiple growth factor signaling pathways, SMIs that interfere with the co-activator’s function should simulta-neously interfere with the activity of alternative growth signaling pathways that lead to cancer chemotherapy resistance (Fig. 11.4).

CO-ACTIVATORS AS DRUG TARGETS

While many proteins, including NRs, are considered ‘druggable’ targets owing to the presence of a high-affinity, high-specificity ligand binding site for small lipophilic ligands, co-activators are thought of as harder molecules to target (Fig. 11.5) [85]. Most other targeted cancer therapeutic SMIs are typically designed to target the enzyme substrate binding site of kinases [86]. NR antagonists such as tamoxifen and the EGFR tyrosine kinase inhibitor gefitinib are examples of these types of SMIs, respectively. In contrast, many critical proteins involved in cancer cell growth have traditionally been thought to be beyond the reach of SMIs. However, the successful development of SMIs that are capable of tar-geting non-receptor/non-enzyme proteins are challeng-ing this pessimistic view. Examples of SMIs for such hard targets include drugs that can target Bcl-2, p53, TNFα, β-catenin, Rac, and HIV gp120 [87–91]. So, even though SRC-3 lacks a high-affinity ligand binding pocket or a defined enzyme catalytic surface, given its significance as a key oncogene, there is a strong impetus to develop SRC-3 SMIs. Indeed, high-throughput screens in aca-demic labs have already identified SMIs that are able to interfere with the binding of NRs to co-activators such as SRC-family members to ERα, ERβ, and PPARγ [92–94]. Importantly, we recently demonstrated that a SMI can directly target SRC-3/SRC-1 independently of its association with NRs, leading to co-activator protein degradation [95]; we characterized gossypol as a SRC-3/SRC-1 SMI that binds to the co-activator receptor inter-acting domain (RID). In breast, prostate, lung, and other cancer cell lines, gossypol is able to selectively reduce the cellular protein concentrations of SRC-1 and SRC-3 without grossly altering overall protein expression

Co-REgulAToR ‘omiCs’: usiNg HigH-THRougHPuT dATA To

patterns, SRC-2, or other co-activators such as p300 and CARM1. We think that SMIs directed against other co-activators will also have clinical value. As an example, SMIs designed to modulate the activities of metabolic co-activators such as PGC-1α and RIP140 could be used to treat metabolic syndrome and diabetes. Considering that mouse knockouts of PGC-1α, RIP140, SRC-1, and SRC-3 [31,96–98] are viable, it is predicted that SMIs against these co-activators would be well tolerated by normal cells.

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CoNNECT Co-REgulAToR Biology To HumAN disEAsE 307

CO-REGULATOR ‘OMICS’: USING HIGH-THROUGHPUT DATA TO CONNECT

CO-REGULATOR BIOLOGY TO HUMAN DISEASE

Technological advances in high-throughput mass pectrometric analyses of co-activator complexes has ed to the finding that co-activators exist and func-ion in protein complexes, broadly falling under the ategory of tight binding co-regulator proteins and a

FIGURE 11.4 Co-activator-based drugs should block cancer cell resistance to chemotherapy. In (A), chemotherapeutic agents designed to target ERα (such as selective estrogen receptor modulators [SERMS] and HER-2 such as Herceptin) cannot block co-activator stimulation of other growth-promoting pathways driven through E2F1, NF-κB, or PI3K/AKT in SRC-3-overexpressing cancer cells. (B) In contrast, a SRC-3 targeting drug is predicted to simultaneously inhibit different growth pathways that are activated in SRC-3 overexpressing cancer cells, blocking their ability to access alternative growth pathways that become activity in chemotherapy-resistant cancer cells. See color plate at the back of the book.

-degradingcompounds Co-activator

Co-activator

binding

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FIGURE 11.5 Co-activator-targeting small molecule inhibitors as novel anti-cancer agents. Using ERαsignaling as an example, SMIs that target the receptor such as tamoxifen and estrogen synthesis (aromatase inhibitors) have enjoyed widespread clinical use. Compounds that target receptor–co-activator interaction or that directly target co-activators should be distinct and better matched to co-activator-overexpressing cancers. AF1, Activation function 1; AF2, activation function 2; DBD, DNA binding domain. See color plate at the back of the book.

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larger number of loosely interacting co-co-activator partners [99]. If we count these co-co-activator part-ners, about half of the proteins encoded by the genome can be counted as transcriptional co-regulators. This study also revealed that cancer gene products group together in select protein complexes, supporting the idea that the perturbation of a protein complex as a whole can underlie distinct disease states and that co-regulator complexes should be considered as a whole when evaluating the likely response to a given targeted therapeutic agent. This model might also apply to the etiology of polygenic metabolic or central nervous sys-tem diseases, where mutations in multiple genes may be responsible. We speculate that, if mutations accumu-late within two or more proteins that exist in a single co-regulator complex, this accumulation of mutations would lead to a defect in the function of the co-regulator complex, resulting in a polygenic disease.

Ongoing technological advances in mass spectro-metry, DNA sequencing, and mRNA expression analysis are expected to lead to proteomic, genomic, and tran-scriptomic assessments of co-regulators that promise to revolutionize how we understand their biology. For instance, we know that SRC co-activators possess an extensive PTM code that forms an essential part of how SRCs can function as ‘master genes’ to control broad transcriptional programs responsible for cell growth, differentiation, and metabolic functions [16,100]. Pro-teomic technologies are expected to open up our ability to understand SRC co-activator functions at this level, something that cannot be interrogated through high-throughput sequencing or transcriptomics.

Nevertheless, genome-wide association studies have identified a variety of co-regulator single nucleotide polymorphisms (SNPs) associated with certain disease risks or human traits [101]. SNP risk alleles have linked SRC-1 to type 1 diabetes [102]. A SRC-3 SNP has been identified that predicts response to chemotherapy for lymphoblastic lymphomas and another SRC-3 SNP has been linked to breast cancer risk [103,104]. We specu-late that co-regulator dysfunction will not be restricted solely to rare genetic conditions such as that seen in highly penetrant monogenic inherited diseases. In con-trast, many co-regulators, including all three SRC fam-ily members, are not essential for viability and even their complete knockout is not lethal. We argue that this is likely related to the roles that co-activators like SRC-3 have as integrators of diverse signals from the environ-ment [16]. We propose that, because co-activators must be genetically flexible enough to function as integrators of diverse metabolic and environmental stimuli, they cannot be genes whose function is essential for viability. This co-activator genetic variation and their increased freedom to evolve is possibly linked to the vastly diverse environments that different human popula-tion groups are able to inhabit. Indeed, computational

searches for genes undergoing strong selective pressure have identified SRC-1 as such a gene in an African pop-ulation [105]. Co-activators are thus free to function at the vanguard of adaptive genetic changes necessary for humans to exist in diverse and rapidly changing geo-graphic conditions.

CO-ACTIVATORS, OUR ENVIRONMENT AND HUMAN EVOLUTIONARY HISTORY

Prior to the advent of agriculture, humans were pri-marily hunter–gatherers and ate a wide range of foods [106]. About 10 000 years ago, a dramatic shift in diet and seasonal variations in food supply occurred, including periods of food abundance and scarcity. Now, though, we are experiencing a third major shift in our diet and lifestyle that is distinct from previous epochs of human existence. These changes have altered a number of key nutritional and environmental parameters that existed throughout the majority of our existence as a species. These changes have affected glycemic load, fatty acid composition, macronutrient composition, and other fac-tors. Chronic disease states such as obesity, diabetes, and coronary disease are products of this new dietary regime that were rare only a century ago. In spite of this abrupt change, individual humans still exhibit a wide range of responses to the western diet owing to differences in our genetic makeup. Experimental paradigms that integrate genome-wide polymorphism data and diet along with information about co-activator biology have the poten-tial to reveal personalized information that can guide the design of individualized diet and medical care to respond to these disease states.

Recent evidence for positive selection of specific alleles for a variety of traits for skin color, immune response, and for specific nutritional factors such as amylase expres-sion and lactose tolerance in adults has been identified [107]. Evidence points to co-activator alleles being part of this process as well. Computational studies to identify alleles subject to strong selective pressure sweeps have identified a number of co-activators as agents of posi-tive selection in different human populations [5,105]. Considerable effort is being directed towards under-standing how SNPs or copy number variations influence human disease susceptibility [108]. Of particular inter-est to co-activator biology, in a bioinformatic approach used to analyze positive selection pressures in HapMap project data, SRC-1 (NCOA1) was predicted to be under very strong selective pressure in an African ethnic group [105]. Signals for strong selective pressures have been found for other co-activator genes, including GAC63 and CAPER [5]. Thus many co-activators are predicted to be important genes for human evolutionary adapta-tion and may have arisen from ethnic differences in diet or other environmental factors. However, in the context

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of our modern lifestyle and diet, it is easy to speculate that these formerly good alleles are now maladaptive, particularly those alleles that confer for more efficient use of energy now that food is so readily available.

CO-ACTIVATORS AS WEAKLY PENETRANT DISEASE RISK ALLELES

Because negative selection eliminates deleterious alleles from populations, genetic diseases with mono-genic etiologies are generally rare. Inherited monogenic diseases are relatively easy to trace through family pedigrees because they follow clear Mendelian rules. In contrast, the genetic basis of common disorders such as obesity [109,110], diabetes [111], dyslipidemia [112], allergies [113,114], polycystic ovarian syndrome, hyper-tension [115], and central nervous system disorders [116] are primarily polygenic. Genome-wide association stud-ies have had limited success in identifying the weakly penetrant alleles that underlie these conditions [101]. Already, though, an SNP adjacent to SRC-1 has been identified as a significant and highly ranking risk factor for type 1 diabetes [102]. In another study, a polymor-phism in SRC-3 was found to contribute to the success of chemotherapy in the treatment of acute lymphoblas-tic lymphoma [103]. These common disease-associated alleles have very low phenotypic penetrance, are not sub-ject to strong negative selective pressure, and are found at much higher frequencies in human populations. For a number of reasons (discussed above) and as a result of evidence from mouse knockout studies, SRC family co-activator polymorphic alleles have low phenotypic pen-etrance, like other common but weakly penetrant alleles that contribute to polygenic disease states.

Another important and somewhat counterintui-tive characteristic of SRC family co-activators that also applies to other master regulators such as p53 [117] and PGC-1α [118] is the fact that even complete loss of these genes is not lethal. We postulate that this is an impor-tant element that allows these proteins the flexibility to accommodate diverse signals from the environment. In contrast, genes that underlie core biological processes such as RNA polymerases or histones, for example, are likely to be intolerant of any change, unable to exist as weakly penetrant alleles in human populations, and ultimately be unable to contribute to polygenic disease states [16].

CONCLUSIONS

Co-regulators represent a large and growing class of proteins. While more than 400 co-regulators have been identified, a full appreciation of the size of this body of proteins and their pervasive involvement in

normal and disease physiology is only beginning to be appreciated. As discussed above, co-regulators are key regulators of reproduction, energy metabolism, and cancer, and it comes as little surprise that we see that they also have roles in human genetic diseases. We speculate that the genetic basis of co-regulator biology will expand further once we consider the impact that environmental stress has on human physiology. Along these lines, co-regulator mouse genetic model systems often only show phenotypes when animals are sub-ject to stresses such as a high fat diet, endocrine or immune challenge, or exposure to mutagens or other toxins.

Future work promises an understanding of how human polymorphisms in co-activator genes relate to variations in human physiology related to energy metab-olism, endocrine function, neurological conditions, or susceptibility to cancer. Developing genomic and pro-teomic technologies will add greatly to our understand-ing of the basic roles that these master regulators play at multiple levels, from the control of gene expression up to that of organism-wide regulation of energy metabolism and endocrine signaling systems.

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