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Artificial intelligence predicts the immunogenic landscape of SARS-CoV-2
Reporter: Irina Robu, PhD
Artificial intelligence makes it imaginable for machines to learn from experience, adjust to new inputs and perform human-like tasks. Using the technologies, computer can be trained to achieve specific tasks by processing large amount of data and recognizing patterns. Scientists from NEC OncoImmunity use artificial intelligence to forecast designs for designing universal vaccines for COVID 19, that contain a broad spectrum of T-cell epitopes capable of providing coverage and protection across the global population. To help test their hypothesis, they profiled the entire SARS COV2 proteome across the most frequent 100 HLA-A, HLA-B and HLA-DR alleles in the human population using host infected cell surface antigen and immunogenicity predictors from NEC Immune Profiler suite of tools, and generated comprehensive epitope maps. They use the epitope maps as a starting point for Monte Carlo simulation intended to identify the most significant epitope hotspot in the virus. Then they analyzed the antigen arrangement and immunogenic landscape to recognize a trend where SARS-COV-2 mutations are expected to have minimized potential to be accessible by host-infected cells, and subsequently noticed by the host immune system. A sequence conservation analysis then removed epitope hotspots that occurred in less-conserved regions of the viral proteome.
By merging the antigen arrangement to the infected-host cell surface and immunogenicity estimates of the NEC Immune Profiler with a Monte Carlo and digital twin simulation, the researchers have outlined the entire SARS-CoV-2 proteome and recognized a subset of epitope hotspots that could be used in a vaccine formulation to provide a wide-ranging coverage across the global population.
By using the database of HLA haplotypes of approximately 22,000 individuals to design a “digital twin” type simulation to model how efficient various combinations of hotspots would work in a varied human population.
Connecting the Immune Response to Amyloid-β Aggregation in Alzheimer’s Disease via IFITM3
Reporter : Irina Robu, PhD
Alzheimer’s disease is a complex condition and it begins with slow aggregation of amyloid-β deposits over the course of years. This produces a mild cognitive impairment and a state of chronic inflammation enough to trigger harmful aggregation of the altered tau protein. Clearing amyloid-β from the brain hasn’t produced telling benefits to patients suggesting that it is not the key process in the development of the condition.
Recent research indicates that beta-amyloid has antiviral and antimicrobial properties, indicating a possible link between the immune response against infections and development of Alzheimer’s disease. Scientists have discovered evidence that protein interferon-induced transmembrane protein 3 (IFITM3) is involved in immune response to pathogens and play a key role in the accumulation of beta amyloid in plaques. IFITM3 is able to alter the activity of gamma-secretase enzyme, which breaks down the precursor proteins into fragments of beta-amyloid that make up plaques.
Yet it was determined that the production of IFITM3 starts in reply to activation of the immune system by invading viruses and bacteria. Indeed, researchers found that the level of IFITM3 in human brain samples correlated with levels of certain viral infections as well as with gamma-secretase activity and beta-amyloid production. Age is the number one risk factor for Alzheimer’s and the levels of both inflammatory markers and IFITM3 increased with advancing age in mice.
Innate immunity is also correlated with Alzheimer’s disease1, but the influence of immune activation on the production of amyloid beta is unknown. They were able to identify IFITM3 as γ-secretase modulatory protein, and establish a mechanism by which inflammation affects the generation of amyloid-β.
According to the current research, inflammatory cytokines induce the expression of IFITM3 in neurons and astrocytes, which binds to γ-secretase and upregulates its activity, thereby increasing the production of amyloid-β. The expression of IFITM3 is increased with ageing and in mouse models that express Alzheimer’s disease genes. IFITM3 protein is upregulated in tissue samples from a subset of patients with late-onset Alzheimer’s disease that exhibit higher γ-secretase activity. The amount of IFITM3 in the γ-secretase complex has a strong and positive correlation with γ-secretase activity in samples from patients with late-onset Alzheimer’s disease. These conclusions disclose a mechanism in which γ-secretase is controlled by neuroinflammation via IFITM3 and the risk of Alzheimer’s disease is thus amplified
Researchers at the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) have discovered that innate lymphoid cells, early responders of the immune system, are primed at the DNA level for rapid action. [National Institutes of Health]
Scientists at the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) have found that the development of innate lymphoid cells (ILCs) gradually prepares these cells for rapid response to infection. This work (“Developmental Acquisition of Regulomes Underlies Innate Lymphoid Cell Functionality”), which appears in Cell, sheds light on the development and function of a cell type that is increasingly recognized as having an important role in the body’s immune defense.
“Up until now, researchers have focused on T cells, another type of immune cell,” said John J. O’Shea, M.D., scientific director of NIAMS and senior author of the paper. “ILCs are coming into the spotlight because they appear to have a critical role in defending the body’s barrier regions, such as the skin, lungs, and gut, where microbes must first pass to make their way into the body.”
The importance of T cells became apparent during the 1980s with the emergence of the human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS). HIV attacks a certain class of T cells, destroying a person’s immune defenses and leaving him or her susceptible to infection and cancer. Since that time, investigators around the world have identified the distinct functions of T cell subclasses, providing new insights into their roles in host defense and opportunities for novel therapeutic strategies.
ILCs have received less attention, despite their critical role in mounting the innate immune response. Recent work has revealed that ILCs and T cells mirror each other in their subclasses, which are defined by the kinds of cytokines they produce. However, the relationships between the two types of cells have been unclear.
To determine what sets ILCs apart from T cells, Dr. O’Shea’s team looked to the foundation of a cell’s identity—its genetic information, which provides detailed instructions for how a cell functions. Part of what makes each cell type unique is its distinctive pattern of DNA structure and regulatory factors. The combination of a stretch of DNA and a set of regulatory factors can be thought of as a switch; it helps determine whether a gene is turned off or on.
Inactive regions of the DNA molecule are twisted into tight coils, whereas active regions are open and accessible to the cellular machinery that reads the genetic information. The open portions of the genome include genes themselves, as well as many regions that contribute to the regulation of their activities (the switches). The areas of the genome and the factors that control whether or not the information is read, in total, are referred to as the cell’s regulome.
Working in mice, the NIAMS researchers analyzed regions of the genome that control the cytokine genes produced by both ILCs and T cells. They found that each subclass of ILCs is associated with a distinct pattern of accessible regions. These patterns can be viewed as a type of barcode for each subclass. Further experiments showed that ILCs acquire their barcodes in a stepwise manner over the course of cellular development.
Importantly, the analysis showed that the barcodes are in place in ILCs before they encounter infection. This open, accessible configuration surrounding the switches that control cytokine genes may be instrumental in enabling ILCs to launch an assault rapidly upon infection.
In contrast, the researchers found that many of the DNA regions controlling cytokine genes in the mice’s T cells are inaccessible and silenced prior to exposure to a pathogen. But upon infection, T cells adopted barcodes similar to those of their ILC counterparts. This result reflected earlier findings that ILC and T cell subclasses produce similar sets of cytokines, but also revealed differences in how the two cell types control the activities of these key immune response genes.
While the regulatory landscapes of ILCs are primed for a quick defense upon infection, those of T cells are minimally prepared when the pathogen invades. Only following infection are modifications in the landscape made that enable T cells to launch their attack.
“ILCs and T cells appear very different, but in the end, the way they control key responses is amazingly similar,” said Han-Yu Shih, Ph.D., a postdoctoral fellow at NIAMS and first author of the paper. “ILCs were discovered less than a decade ago, but the parallels between them and T cells will enable us to more quickly understand how they work and to develop ways to enhance or inhibit their function in treating a variety of immune and inflammatory diseases.”
Oncolytic viruses are novel anticancer agents, currently under investigation in Phase I–III clinical trials. Until recently, most studies have focused on the direct antitumor properties of these viruses, although there is now an increasing body of evidence that the host immune response may be critical to the efficacy of oncolytic virotherapy. This may be mediated via innate immune effectors, adaptive antiviral immune responses eliminating infected cells or adaptive antitumor immune responses. This report summarizes preclinical and clinical evidence for the importance of immune interactions, which may be finely balanced between viral and tumor elimination. On this basis, oncolytic viruses represent a promising novel immunotherapy strategy, which may be optimally combined with existing therapeutic modalities.
The anticancer activity of viruses has been reported throughout the 20th century. Developments in virology, genetic manipulation and molecular biology have led to a surge of research investigating viruses with oncolytic or antitumor properties over the last 15 years. Several oncolytic viruses are currently in Phase I–III clinical trials [1]. Until recently, despite the multitude of studies investigating direct viral effects upon cancer cells, relatively little attention had been paid to the interaction between oncolytic viruses and the immune system. We discuss the evidence supporting the view that the host immune response is critical to the efficacy of oncolytic virotherapy. The potential of oncolytic viruses to break immunological tumor tolerance, generating antitumor immunity, represents a novel avenue of immunotherapy.
Oncolytic viruses are self-replicating, tumor selective and directly lyze cancer cells [2]. They may be tumor selective in wild-type or attenuated forms or may be engineered to provide tumor selectivity. Naturally occurring oncolytic viruses include the double-stranded RNA reovirus and single-stranded RNA Newcastle disease virus (NDV) and vesicular stomatitis virus (VSV). By contrast, human DNA viruses, including adenoviruses, vaccinia and herpes simplex viruses (HSV) have been genetically modified in a variety of ways to provide tumor selectivity. A diverse range of mechanisms provide tumor specificity, including inactivation of antiviral defences, such as type I IFN responses in many cancer cells, viral deletions permitting replication only in tumor cells that can substitute for viral defects, tumor-selective uptake via upregulated or mutated receptors, and targeting to tumor promoters.
In the majority of clinical trials performed so far, oncolytic viruses have been administered via intratumoral injection. A smaller number of studies have examined regional or intravenous delivery. Clinical experience has demonstrated a favorable toxicity and safety profile and a number of tumor responses, although overall antitumor efficacy has been limited [1]. For example, ONYX-015, a modified adenovirus, has been used in clinical trials with response rates of 0–14% following intratumoral administration [3]. In view of the short history of oncolytic virotherapy, along with recent scientific advances in methods of viral delivery and enhancing antitumor potency, these low levels of single-agent clinical responses provide encouragement for the future.
An increasingly powerful body of evidence supports the ability of the immune system to modify the immunogenicity and behavior of tumors [4]. A host of tumor-associated antigens (TAA) have been characterized [5] and in a single tumor, tumor-infiltrating lymphocytes directed towards multiple TAAs can be identified [6]. Despite these antigenic differences, the antitumor immune response is commonly ineffectual. Tumors can subvert antitumor immunity, generating an immunosuppressive tumor microenvironment by a multitude of mechanisms. These include the induction of Treg cells, secretion of soluble immunosuppressive mediators including nitric oxide, IL-10 and TGF-β and recruitment of myeloid suppressor cells [4]. Matzinger’s ‘danger’ hypothesis proposes that the prime role of the immune system is to respond to cellular or tissue distress as opposed to nonself per se [7]. Several danger signals have been identified, including RNA, DNA, IFN-α, heat-shock proteins, uric acid and hyaluron, providing a mechanistic basis for this hypothesis [8]. On this basis, tumor-associated danger signals are critical to the generation of effective antitumor immunity. In addition to their ability to disrupt immune responses, tumors commonly lack such signals and successful tumor immunotherapy will probably to depend upon their provision. Oncolytic virotherapy represents a potent approach to cancer immunotherapy, combining the enhanced release of TAA via tumor cell death, in the context of danger signals (FIGURE 1).
Figure 1Concept of how oncolytic viral infection of tumor cells may lead to the generation of antitumor immune responses
The role of the innate immune response to cancer is double-edged. Chronic inflammatory changes can promote tumor progression via proliferative and proangiogenic signals [9], while by contrast, the infiltration of activated innate inflammatory cells can mediate tumor regression in vivo [10]. Manipulation of the immune environment within a tumor is a potentially critical strategy towards successful tumor immunotherapy [11].
Oncolytic viruses represent prime candidates to enhance the immunogenicity of the tumor microenvironment. As detailed below, oncolytic virotherapy may be immunomodulatory via tumor cell death, production of endogenous danger signals, the release of tumor-derived cytokines and direct effects upon cells of the innate immune system. Evidence from preclinical models suggests that an early influx of immune cells, including macrophages and natural killer (NK) cells, occurs in response to tumor viral therapy [12–14]. These changes within the tumor hold the potential to alter the pre-existing immunosuppressive microenvironment, in favor of the generation of therapeutic immune responses. Dendritic cells (DC), the prime antigen-presenting cells and a component of the innate immune response are critical for the subsequent generation of antigen-specific or adaptive immune responses. However, as discussed later, the outcome of the innate response is finely balanced between promotion of tumor clearance and viral clearance limiting efficacy.
Virally induced cell death would be expected to enhance the availability of TAA for uptake by DC. Indeed, viral infection of tumors has been reported to enhance the phagocytosis of tumor-derived material [15,16]. The relationship between the mode of cell death and tumor immunogenicity has, however, been controversial; the immunogenicity of tumors has been reported not to be affected by whether tumor cells are alive, apoptotic or necrotic [17]. Even if the mode of cell death is not an immunogenic determinant, the release of intrinsic cell factors, including heat-shock protein [18], uric acid [19] and bradykinin [20], can be identified as danger signals by DC. Oncolytic viral infection may mediate production of these factors. For example, tumor cell infection by a modified oncolytic adenovirus increases intracellular uric acid levels, activating DC [19].
An array of cytokines provides costimulation for T-cell responses, while by contrast, tumor-derived cytokines, including TGF-β and IL-10, have immunosuppressive properties. In addition, the tumor-derived proinflammatory cytokines VEGF, TNF-α and several chemokines have been linked to promotion of tumor growth [21]. Oncolytic viral infection is likely to alter the balance of cytokines produced and the nature of the subsequent immune response. We have investigated the release of cytokines following infection of melanoma cells with reovirus, a naturally occurring double-stranded RNA virus currently in clinical trials [22]. Reovirus was found to induce secretion of IL-8, RANTES and MIP-1α/β, which play a role in the recruitment of DC, neutrophils and monocytes [23], and of IL-6, which can inhibit the immunosuppressive function of Treg cells [24]. Reovirus additionally reduced tumor secretion of the immunosuppressive cytokine IL-10. The immunogenic property of tumor-conditioned media from reovirus-infected tumor cells (filtered to remove viral particles) was confirmed by their ability to activate DC.
DC & the response to viral infection
The immune system is adept at pathogen recognition and a host of receptors specific for pathogen-associated molecular patterns, including the toll-like receptors (TLR), have been identified [25]. Innate viral recognition can center around viral nucleic acids or viral proteins [25]. DC play a critical role in the early innate immune responses, reciprocally interacting with other innate immune cells, including NK cells [26]. In this context, oncolytic viruses can influence the nature of the innate tumor response. Reovirus-infected DC, for example, enhance NK cytotoxicity towards tumor cells [27].
The effect of viruses upon DC is virus specific: measles and a vaccinia virus strain impair DC phenotype and function [28,29], an oncolytic adenovirus has a neutral effect [30], while reovirus is directly stimulatory to DC [27]. Although the immunomodulatory effects of oncolytic viruses have been investigated to a limited degree, it follows that the immune consequences of therapy with different viruses will vary widely. In addition, the genetic modification of viruses to confer oncolytic specificity may involve interference with virulence genes whose function is to modify the antiviral immune response, including type I interferon response genes [2,31]; alteration of such immunomodulatory genes will alter the consequences of the immune interactions of these modified viruses.
Oncolytic viruses & adaptive antitumor immunity
The innate immune response is thought to provide an important link to the generation of adaptive immune responses. DC are key to this link, taking up TAA, integrating danger signals and presenting antigen in an appropriate costimulatory context to the adaptive arm of the immune system. An adaptive antitumor immune response requires activation of cytotoxic CD8 T cells by DC presenting tumor antigen on MHC class I molecules. The presentation of exogenous antigen in a MHC class I context is termed ‘cross-presentation’. Critically, virally infected cells have been shown to be superior at delivering nonviral antigen for cross-presentation and cross-priming adaptive immune responses in vivo [32]. Intriguingly, recent work has defined a role for TLR-4 receptor ligands (bacterially derived lipopolysaccharide) in enhancing cross-presentation [33]; a similar effect of viral as opposed to bacterial TLR ligands has yet to be explored. Inflammatory stimuli have additionally been shown to enhance antigen processing and the generation of MHC class II complexes, required for CD4+ T-cell help in adaptive immune responses [34,35]; such inflammatory stimuli could be provided by viral tumor infection. Oncolytic virotherapy may therefore enhance immune priming via multiple effects upon DC. There is an emerging body of data from murine and human preclinical research supporting the concept that the efficacy of oncolytic virotherapy is at least partially immune mediated and that antitumor immunity can be generated.
Overall, the antiviral humoral and cellular immune responses may have contrasting consequences. Methods of enhancing viral delivery to tumors or immunomodulation provide an opportunity to alter this balance in favor of therapeutic benefit.
Clinical trials & the immune response
Although preclinical studies have provided support for the concept that the efficacy of oncolytic virotherapy may be dependent upon the host immune response, there are limited data on the immune response following virotherapy from early clinical trials.
Studies of intratumoral administration have provided direct evidence of a cellular immunological response. In a Phase I trial of a second-generation oncolytic HSV expressing GM–CSF injected into subcutaneous metastases from a variety of tumor types, post-treatment biopsies revealed an extensive immune cell infiltrate [54]. Additionally, suggestive of an immune-mediated antitumor effect, was the observation of inflammation in uninjected tumor deposits in four of 30 treated patients. Similarly, in a study of intratumoral administration of a recombinant vaccinia–GM–CSF virus in patients with melanoma deposits, treated lesions were shown to have a dense immune cell infiltrate. The generation of antitumor immunity was implied by the regression of noninjected regional dermal metastases in association with an immune infiltrate in four of seven treated patients [55]. A Phase I study of injection of JX-594, a targeted poxvirus armed with GM–CSF, into primary and metastatic liver tumors has recently been reported with encouraging evidence of activity, with a partial response in three and stable disease in six of ten evaluable patients by Response Evaluation Criteria in Solid Tumors (RECIST) [56]. Consistent with a possible antitumor immune response was the durability of tumor responses. Notably, there was evidence of functional response in noninjected tumors in three of seven evaluable patients by Choi criteria for reduction in Hounsfield units (n = 2) and by reduced 18F-fluorodeoxyglucose (18FDG)-PET signal (n = 1). There was evidence of viral dissemination to noninjected tumor tissue. The responses in injected and noninjected tumor tissue could therefore have been mediated by direct viral oncolysis, antiviral immune responses towards virally infected cells or antitumor immune responses established in the injected lesions.
Oncolytic viruses have been combined with tumor vaccines in an attempt to exploit viral danger signals. Vaccinia virus–melanoma cell lysate vaccines were used in an adjuvant Phase III study of 700 patients following melanoma resection, with no improvement in recurrence or overall survival [57]. A series of clinical studies has been performed by Schirrmacher et al. using a live autologous tumor vaccine infected by NDV irradiated to render tumor cells nonviable [58]. A significant proportion of patients developed antitumor immune responses as assessed by a delayed-type hypersensitivity response to skin prick tests. Phase II studies have been performed in glioblastoma multiforme, melanoma, breast and colorectal cancer with improvements in overall survival by 20–36% at 2–5-year follow-up compared with historical controls. These studies suggest that oncolytic viruses can break immunological tumor tolerance, although Phase III studies are needed to confirm these findings.
Combination therapy may be the optimal context in which to exploit the immunotherapeutic potential of oncolytic viruses. A rationale exists for combination with existing immunotherapy strategies, along with conventional therapy.
Adoptive cellular therapy & viral delivery
The use of cell carriers to chaperone viral particles to the tumor is a promising innovation [51]. Cells of the immune system have proven particularly adept, including cytokine-activated killer cells [52] and T lymphocytes [36]. Adoptive cellular therapy has met with some clinical success, but has been limited by the trafficking to and survival of T cells in the tumor microenvironment [62]. In a mouse model, the combination of oncolytic virus delivery with antigen-specific adoptive T-cell therapy has been shown to improve upon either treatment modality alone [63]. Although yet to be tested in clinical trials, these findings are of significant translational potential.
Immunotherapy combinations
Immunotherapy approaches may be logically combined with virotherapy to enhance antitumor responses.
The host immune response will probably be critical to the efficacy of oncolytic virotherapy, although it is a fine balance between rapid viral elimination and innate and adaptive responses, which may mediate tumor regression. The rational design of combination therapy, modulating the immunological outcome, may hold the key to fulfilling the potential of these novel agents. Clinical trials should be designed to include specific assessment of immune responses to both tumor and viral antigens, and recognize the immunotherapeutic potential of virotherapy in terms of clinical end points and patient selection.
Oncolytic Viruses and Their Application to Cancer Immunotherapy
Oncolytic virus (OV) therapy is based on selective replication of viruses in cancer cells and their subsequent spread within a tumor without causing damage to normal tissue (1, 2). It represents a unique class of cancer therapeutics with distinct mechanisms of action. The activity of OVs is very much a reflection of the underlying biology of the viruses from which they are derived and the host–virus interactions that have evolved in the battle between pathogenesis and immunity. This provides a diverse set of activities that can be harnessed and manipulated. Typically, OVs fall into two classes: (i) viruses that naturally replicate preferentially in cancer cells and are nonpathogenic in humans often due to elevated sensitivity to innate antiviral signaling or dependence on oncogenic signaling pathways. These include autonomous parvoviruses, myxoma virus (MYXV; poxvirus), Newcastle disease virus (NDV; paramyxovirus), reovirus, and Seneca valley virus (SVV; picornavirus); and (ii) viruses that are genetically manipulated for use as vaccine vectors, including measles virus (MV; paramyxovirus), poliovirus (PV; picornavirus), and vaccinia virus (VV; poxvirus), and/or those genetically engineered with mutations/deletions in genes required for replication in normal but not in cancer cells including adenovirus (Ad), herpes simplex virus (HSV), VV, and vesicular stomatitis virus (VSV; rhabdovirus; refs. 1,3). Genetic engineering has facilitated the rapid expansion of OVs in the past two decades, enabling a broad range of potentially pathogenic viruses to be manipulated for safety and targeting (3). Many of the hallmarks of cancer described by Hanahan and Weinberg (4) provide a permissive environment for OVs; they include sustained proliferation, resisting cell death, evading growth suppressors, genome instability, DNA damage stress, and avoiding immune destruction. In addition, insertion of foreign sequences can endow further selectivity for cancer cells and safety, as well as altering virus tropism through targeting of translation with internal ribosome entry sites (IRES) or microRNAs (PV and VSV), transcription with cell-specific promoter/enhancers (Ad, HSV), or transduction with altered virus receptors (HSV, Ad, MV, and VSV; refs.1, 3). These strategies are also being used to target replication-deficient viral vectors for gene therapy applications in cancer immunotherapy.
OVs have many features that make them advantageous and distinct from current therapeutic modalities: (i) there is a low probability for the generation of resistance (not seen so far), as OVs often target multiple oncogenic pathways and use multiple means for cytotoxicity; (ii) they replicate in a tumor-selective fashion and are relatively nonpathogenic and, in fact, only minimal systemic toxicity has been detected; (iii) virus dose in the tumor increases with time due to in situ virus amplification, as opposed to classical drug pharmacokinetics that decrease with time; and (iv) safety features can be built in, such as drug and immune sensitivity. These features should result in a very high therapeutic index. An important issue for OV therapy is delivery. Although systemic intravenous administration is simpler than intratumoral injection and can target multiple tumors, it has drawbacks, including nonimmune human serum, anti-OV antibodies that preexist for human viruses or can be induced by multiple administrations, lack of extravasation into tumors, and sequestration in the liver (1). Cell carriers [i.e., mesenchymal stromal cells, myeloid-derived suppressor cells (MDSC), neural stem cells, T cells, cytokine-induced killer cells, or irradiated tumor cells] can shield virus from neutralization and facilitate virus delivery to the tumor (5). The effectiveness will vary depending upon the cell phenotype, permissiveness to virus infection, tumor-homing ability, and transfer of infectious virus to tumor cells. To block virus neutralization and extend vascular circulation, viruses can also be coated in nanoparticles (i.e., PEGylation; ref. 1).
OV Immunotherapy
Virus infection and pathogenicity have been major drivers in the evolution of the human immune system, and vaccination against viruses is the quintessential exploitation of adaptive immunity. A major goal of OV-mediated immunotherapy is to activate and redirect functional innate and adaptive immune responses toward the tumor. Interactions between innate and adaptive immune cells and signaling factors (i.e., cytokines and chemokines), often involved in virus infections, play a large role in antitumor immunity or lack thereof, as well as successful immunotherapies (Fig. 1). Virus infection induces an inflammatory response leading to adaptive antivirus immunity. Thus, the immune system was seen initially as a negative factor in OV therapy for limiting virus infection/delivery because of preexisting or therapy-induced immunity, virus replication because of innate antiviral responses, and virus spread because of the infiltration of innate immune cells (6). In addition, most early studies were performed in human xenograft tumor models in immunodeficient mice lacking adaptive immune responses because some viruses were species selective or replicated better in human cells, and because there was availability of a broad diversity of human cancer cell lines. With the use of syngeneic tumor models in immunocompetent mice, it became clear that the consequences of the immune system were complex, but that the induction of antitumor immunity was feasible and efficacious (6). In particular, many OVs act asin situ vaccines, inducing robust, long lasting, and specific adaptive antitumor responses, often CD8+ T cell–mediated (7, 8). Interestingly, adaptive antiviral immunity can enhance antitumor immunity for HSV, but not for VSV (8, 9).
Figure 1.
Cartoon of OV-mediated effects in tumor. First phase, OV delivered intratumorally or systemically, infects tumor cells (can be blocked by humoral defense systems; antibodies). After infection, OV replicates (can be blocked by innate responses; i.e., IFN-α/β), kills cells often by ICD, and spreads throughout the tumor (can be blocked by innate immune cells, i.e., NK cells and macrophages), eliciting an inflammatory response. When an armed OV is used, the immunomodulatory transgene is expressed (transgene product). Second phase, ICD and inflammation recruit DCs to the tumor, where they take up TAAs and induce an adaptive immune response (T and B cells), which targets the tumor (can be blocked by Tregs and MDSCs). Innate cells such as NK cells also have antitumor activities. Antitumor immune responses can be further enhanced by transgene products. CPA, cyclophosphamide.
The inflammatory cascade and immunogenic cell death (ICD) induced by OV infection of tumors makes OVs particularly powerful inducers of antitumor immunity (8, 10). Among the many different types of cell death, some are immunogenic and characterized by the release of danger-associated molecular patterns (DAMP), such as calreticulin, high-mobility group protein B1 (HMGB1), and ATP, along with tumor-associated antigens (TAA; ref. 10). Multiple forms of ICD have been observed after OV (Ad, VV, HSV, MV, and coxsackievirus) infection of cancer cells, and there is a suggestion that ICD occurs in patients after treatment with oncolytic Ad and temozolomide (11). However, much remains to be learned about the mechanisms of OV-mediated cell death and how it can be exploited to enhance immunogenicity. Inflammation, typically chronic, can also promote tumorigenesis and inhibit T-cell antitumor activity (12). Restraining antiviral immune responses and minimizing pathology, while promoting antitumor immune responses, is a complex and poorly understood balancing act that will dictate OV therapy outcomes. In some cases, where minimal OV replication occurs in mouse tumors (i.e., HSV) or no replication is required (i.e., reovirus; ref. 13), antitumor efficacy is principally due to OV-induced immune responses. Understanding, harnessing, modulating, and/or enhancing OV-mediated immune responses for effective antitumor immunity are major areas in current research that intersect with other immunotherapeutic strategies.
Many viruses express immune evasion genes that enable them to establish infections and spread within their host (14). Mutations in these genes (i.e., HSV Us11, VV E3L, MYXV M156R, Ad VAI, and reovirus σ2/σ3, inhibitors of PKR; HSV ICP0, VV N2, NDV V, and MV V, inhibitors of IRF3; HSV ICP0, MYXV M13L, MV V, PV 3C, and VSV M, inhibitors of NF-κB; VV B8R and MYXV MT-7, inhibitors of IFN-γ; HSV ICP47 and AdE3-19K, inhibitors of MHC class I presentation; MV gp, inhibitor of T cells; and MYXV M128L and MV H, inhibitors of CD46) are likely to enhance the induction of immunity and possibly cross-presentation of TAAs. Such mutations should improve the safety of OVs by making them more visible to the immune system, as well as increasing antitumor immune responses. Conversely, they may diminish virus replication and spread. An additional problem not as easily addressed is OV infection of immune cells, especially dendritic cells (DC), that interferes with their function (15, 16).
Innate Immunity
Although adaptive immunity seems to provide and, in fact, represent even the major mode of anticancer action for OVs, it is also evident that an initial host response against an administered OV could destroy it along with the infected cells before the OV has a chance to replicate and induce cytotoxicity of a magnitude that is sufficient to set up an effective vaccination response (17). Location and site of OV administration is an important determinant of the characteristics of these initial host responses against the OV. For instance, intravenous or intra-arterial administration of OVs, such as recombinant HSV1, leads to its rapid recognition and elimination by the circulating complement and antibodies of the humoral defense system (18, 19). This has also been shown for VV (20), NDV (21), MV (22), and Ad (23, 24). Intratumoral administration can also lead to complement- and antibody-mediated destruction of the OV. In addition, intracellular and microenvironmental antiviral defense responses in infected tumor cells can also greatly limit the magnitude of OV replication (25–31). Finally, innate immune cells can rapidly respond to an administered OV, further limiting its survival and that of OV-infected tumor cells (32–35). In all these models, circumvention of such responses using pharmacologic agents, such as histone deacetylase (HDAC) inhibitors or immunomodulating drugs, or genes that block antiviral defense mechanisms, has led to improved OV replication and tumor cytotoxicity (reviewed in ref. 36). When pharmacologic agents are used, the interference of antiviral responses can be applied in a transient fashion usually right before or at the time of OV administration. This should lead to an initial burst of OV replication leading to tumor cell lysis. As the pharmacologic effects against host innate immunity wane, a large debris field of OVs and tumor antigens could be more promptly recognized by the antiviral host response, leading to a secondary long-term vaccination effect responsible for effective tumor immunity (Fig. 1). However, quantification of responses to OV therapy is a sorely needed area of investigation. For instance, the number of OV-replicative rounds, the tumor cell-OV burst size, the number of OV-replicative tumor foci, and the temporal kinetics of innate response suppression that are needed for an efficient lytic and vaccination effect are still undetermined. In fact, current applications of innate immunity modulation with OV administration remain to be determined in an empirical manner.
Enhancing OV Immunotherapy
Many OVs can accommodate gene insertions and thus can be “armed” with therapeutic transgenes, combining local gene delivery with oncolytic activity (42). Local expression in the tumor obviates toxicity arising from systemic administration of potent immune modulators. GM-CSF, based on its effects in cytokine-transduced cancer cell vaccines (i.e., clinically approved Sipuleucel-T), has been incorporated into a number of OVs [HSV T-Vec, VV JX-594, Ad Ad5/3-D24-GMCSF (43), and CG0070 (44)] that have entered clinical trials (8). GM-CSF–expressing OVs demonstrated only moderate activity in preclinical studies (45, 46), while JX-594 was not compared with a VV lacking GM-CSF (47). Other therapeutic transgenes include interleukin (IL)-2 (NDV, HSV, and parvovirus), IL-12 (Ad and HSV), IL-15 (VSV), IL-18 (HSV), IFN-α/β (Ad, VSV, and VV), soluble CD80 (Ad and HSV), 4-1BB (VV), CD40L (Ad, and no effect with VSV), Flt3L (Ad and HSV), CCL3 (Ad), CCL5 (Ad and VV), and combinations thereof (2). In addition to transgenes that enhance adaptive immune responses, cytokines/chemokines directed at the tumor microenvironment can alter the immune cell balance toward productive therapeutic immunity (Fig. 1). IL-12, a potent antitumor cytokine with antiangiogenic activities, when expressed from oncolytic HSV, reduced neovasculature and tumor regulatory T cells (Treg) and induced T cell–mediated immunity in an immunocompetent cancer stem cell model (48). Expression of a CXCR4 antagonist from oncolytic VV reduced tumor vasculature and accumulation of bone marrow–derived epithelial and myeloid cells and induced antitumor humoral responses (49).
Like many cancer vaccine strategies, OVs expressing TAAs can be used to induce tumor-selective adaptive immune responses. The combination of TAA expression in the tumor and OV-mediated cell killing induces enhanced T-cell migration and activation compared with OV-infected tumor cells expressing the TAA (50). This can be coupled to a prime (replication-deficient Ad or oncolytic Semliki Forest virus expressing a TAA)–boost (oncolytic VSV or VV expressing the same TAA) vaccine strategy, in which the boosted secondary response to the tumor dominates the primary anti-OV response (6, 8). To expand the antigenic repertoire, cDNA libraries from normal tissue (e.g., prostate for prostate tumors) or recurrent tumors have been inserted into VSV, and induced therapeutic immunity (51). Further enhancement was obtained by expressing xenogeneic TAAs (51, 52). The ability of oncolytic VSV expressing TAAs to induce IL-17 in the context of tumor immunity has been exploited to screen tumor cDNA libraries for individual TAAs and optimal TAA combinations, limiting potentially inappropriate responses of whole-cell or cDNA vaccines (53). Developing a similar strategy in a human setting would be a major advance.
A number of immunomodulatory agents have been examined to restrain antiviral immune responses and promote OV replication and spread. Cyclophosphamide can increase OV replication and inhibit tumor growth by suppressing innate immune cell (34) and antibody responses (54), depleting Tregs, and enhancing the antitumor activity of CTLs (Fig. 1; ref.8). A challenge is to identify immunosuppressive strategies that can blunt acute innate cells from blocking virus replication and spread, while permitting sufficient inflammation and cross-priming for robust antitumor immunity. Conversely, it will be of interest to combine OV with chemotherapies that induce ICD (e.g., cyclophosphamide, oxaloplatin, or anthracyclines such as doxorubicin and mitoxantrone), increase tumor cell antigenicity (e.g., gemcitabine, cisplatin, or etoposide) or susceptibility to immune cells (e.g., HDAC inhibitors, paclitaxel, or doxorubicin), or suppress MDSCs (e.g., gemcitabine and paclitaxel) and Tregs (e.g., cyclophosphamide or sunitinib; ref. 55) in immunocompetent preclinical models.
In conclusion, the field of virotherapy is becoming mature in its knowledge of effective anticancer mechanisms in animal tumor models with OVs that are also safe in human clinical trials. It seems that there may soon be a first-in-humans OV approved for use in the United States, which will further stimulate laboratory and clinical endeavors with this therapeutic strategy.
Oncolytic viruses: a new class of immunotherapy drugs.
Oncolytic viruses represent a new class of therapeutic agents that promote anti-tumour responses through a dual mechanism of action that is dependent on selective tumour cell killing and the induction of systemic anti-tumour immunity. The molecular and cellular mechanisms of action are not fully elucidated but are likely to depend on viral replication within transformed cells, induction of primary cell death, interaction with tumour cell antiviral elements and initiation of innate and adaptive anti-tumour immunity. A variety of native and genetically modified viruses have been developed as oncolytic agents, and the approval of the first oncolytic virus by the US Food and Drug Administration (FDA) is anticipated in the near future. This Review provides a comprehensive overview of the basic biology supporting oncolytic viruses as cancer therapeutic agents, describes oncolytic viruses in advanced clinical trials and discusses the unique challenges in the development of oncolytic viruses as a new class of drugs for the treatment of cancer.
MC Speranza, K Kasai, SE Lawler – ILAR Journal, 2016 – ilarjournal.oxfordjournals.org
Abstract After more than two decades of research and development, oncolytic herpes
viruses (oHSVs) are moving into the spotlight due to recent encouraging clinical trial data.
oHSV and other oncolytic viruses function through direct oncolytic cancer cell–killing …
THOUSAND OAKS, Calif., Oct. 27, 2015/PRNewswire/–Amgen (AMGN) today announced
that the US Food and Drug Administration (FDA) has approved the Biologics License
Application for IMLYGIC™(talimogene laherparepvec), a genetically modified oncolytic …
The serpin family comprises a structurally similar, yet functionally diverse, set of proteins. Named originally for their function as serine proteinase inhibitors, many of its members are not inhibitors but rather chaperones, involved in storage, transport, and other roles. Serpins are found in genomes of all kingdoms, with 36 human protein-coding genes and five pseudogenes. The mouse has 60 Serpin functional genes, many of which are orthologous to human SERPIN genes and some of which have expanded into multiple paralogous genes. Serpins are found in tissues throughout the body; whereas most are extracellular, there is a class of intracellular serpins. Serpins appear to have roles in inflammation, immune function, tumorigenesis, blood clotting, dementia, and cancer metastasis. Further characterization of these proteins will likely reveal potential biomarkers and therapeutic targets for disease.
Serpins represent the largest and most functionally diverse family of protease inhibitors. The name serpin originates from the first described function of this family, viz., serine proteinase inhibitors. In their native state, serpins exist as monomeric proteins. Most serpin family members inhibit serine proteinases of the chymotrypsin family [1], thereby inhibiting proteolytic cascades. However, some serpins exhibit functions unrelated to inhibition of catalytic activity, such as hormone transport and other mechanisms.
Approximately 1,500 serpin sequences have been identified; they are found in the genomes of all five kingdoms [2]. There are 36 identified human putatively functional protein-coding genes [3]. The serpin superfamily is divided into groups called clades according to their sequence similarity. Clades are classified as A–P, with clades A–I representing human serpins [4].
Serpins have well-conserved secondary structures with an exposed reactive center loop (RCL) (Figure 1), which interacts with the protease active site to inhibit protease activity [5]. The ability for serpins to undergo conformational change is crucial for their function, in which serpins act via a suicide substrate inhibitory mechanism [2,4]. Although most serpins selectively inhibit serine proteases, some inhibit cysteine proteases, such as caspases and cathespins; others perform hormone transport and blood pressure regulation [4]. Serpins play important physiological roles in hormone transport, corticosteroid binding, coagulation, and blood pressure regulation.
Native SERPINA1. Native SERPINA1 with labeled structural elements: β sheet a and reactive center loop (RCL); α helices in red, β sheets in turquoise, turns in green. (Adapted from PDB 1HP7).
Serpin nomenclature
Initially named for tissue location or function (Table 1), a nomenclature committee convened in 1999 with the goal of standardizing serpin gene nomenclature [4]. ‘SERPIN’ was designated as the gene symbol for humans and other species because it is well known and used in the literature and as a keyword [4]. Serpins were not named for activity or function due to the diversity of member structure and tissue distribution. In 2005, proteinase in human gene names was replaced with the term peptidase; however, ‘serpin’ remains the stem because the name was designated prior to this change. The current classification of serpins involves division into clades that are based on phylogenetic relationships (Figure 2). There are 16 clades labeled A–P. Human serpins are represented in the first nine clades (i.e., A–I), with a variety of members being in each clade. Clades are phylogenetically unique and it is important to recognize that no relationships between the clade letters are implied by their order [4]. Some serpins are classified as orphans because they do not group with any other clade. It is likely that they will form clades as new serpins are identified. An example to help illustrate the nomenclature would be α-1-antitrypsin. This was assigned to the first clade, giving it the symbol SERPINA1 with the ‘A’ referencing the clade and the ‘1’ referencing the gene number within the clade [4].
SERPIN phylogenetic tree. Phylogenetic tree of human and mouse serpin proteins. Protein sequences were aligned using TCOFFEE and analysed using neighbour-joining methods with 10,000 bootstrap replicates in the Phylip package.
Structure function
Serpins have a metastable structure that is required for their function. It consists of a highly conserved secondary structure with three β-sheets (A, B, and C), nine α-helices and a RCL (Figure 1), which serve as bait for target proteases [4,6]. Well-conserved throughout the serpin family, the tertiary structure of scaffold allows for a conformational change critical to protease inhibitor activity [4]. In their native state, serpins exist as monomeric proteins. A serpin molecule consists of a single 330- to 500-amino acid polypeptide chain that has conserved secondary helices and sheets. To inhibit proteolytic activity, the serpin acts as a suicide substrate for the protease [4]. This is accomplished by the RCL of the serpin interacting with the protease’s active site [6].
Serpins can exist in several forms, viz., active, latent, cleaved, delta, and polymeric. Each form is defined by the RCL, which is the moiety required for inhibitory activity. The active form (or the native state) has an exposed RCL that allows it to interact with the protease. The RCL forms an exposed extension located above the molecule. Following proteolysis, the amino acid terminus of the RCL inserts into the A β sheet forming a fourth strand. This process is called the ‘stressed (S) to relaxed (R) transition’ [3] used to inhibit proteases, resulting in the cleaved form. The cleaved form is necessary for inhibition of proteases resulting in an irreversible covalent complex with the target protease thus inactivating both the serpin and the target. Some serpins bind cofactors and/or glycosaminoglycans to maximize protease inhibition, which can vastly increase inhibitory potential [7].
The native form of serpins has low thermal stability indicating that it is not the most stable conformation; rather, native serpins are metastable. However, not all serpins undergo this transition. Serpins can transition to the latent form from the active form and back to the active form from the latent form. The latent form does not possess inhibitory activity but it can convert to the active form through denaturation and refolding [4]. Consequently, it can be considered a control mechanism in regulating homeostasis for certain serpins [3]. Alternatively, the latent state caused by a mutation can be pathological [3].
The delta form is an intermediate conformation between latent and native state where the RCL inserts into the A β sheet and one of the helices unwinds and completes hydrogen bonding of the β sheet [3]. Little is known about the function of this conformation; however, it is likely that this favors polymeric or latent conformation transition rather than native. The polymeric form has a loop sheet mechanism whereby the RCL that would be inserted into the same serpin is instead inserted into the A β sheet of another serpin forming a long chain of these molecules [3]. However, this mechanism of polymerization has recently been challenged in favor of that of a domain-swapping model [8]. Serpins are unique in that their native state (active form) is not the most kinetically stable; rather, it is ‘metastable’. By incorporating the RCL into their A β sheet, either by cleavage for inhibition of target protease or spontaneous latency, they become more stable [9]. For an excellent minireview on kinetics of serpins, see Silverman et al. [4].
Evolution
Whereas serpins have highly conserved secondary and tertiary structures upon which they are grouped, they often share little amino acid sequence similarity. They do, however, share a highly conserved core, especially in the shutter domain including Ser56 and Ser53 [10], which is thought to be critical in determining tertiary structure and conformational flexibility.
Due to the numerous, yet distinct, processes regulated by serpins and their widespread functions, serpins offer a unique perspective for protein evolution. Members of the serpin family tend to group phylogenetically by species rather than by function. Therefore, evolution of the serpin family was likely driven by speciation to fill their physiological roles rather than by coevolution with the serine proteases (which group by function) [10]. Numerous serpin genes are also found in clusters on the same chromosomes, reflecting earlier gene-duplication events and potentially indicating a common precursor [11,12]. Interestingly, these genes are functionally divergent, despite their chromosomal proximity [7]. In addition, serpins have distinct patterns of introns and exons. These patterns may contain information regarding phylogenetic signals and be evolutionarily related based on relative intron positioning [13,14].
The distribution of serpins in eukaryotes suggests that they arose early in eukaryotic evolution [1]. Extensive gene clustering indicates that numerous serpins in close proximity on the same chromosome may have arisen as a result of duplications from a common precursor [12]; however, the evolution of these proximal genes gave way to vastly divergent functions.
Intracellular serpins of clade B are ancestral to most extracellular serpins [15,16] and each inhibitory serpin contains a highly conserved hinge region [16] within the RCL. Clade F serpins specifically share ancestry with a sea lamprey serpin. Clade P is specific to plant serpins which form a discrete clade. At the time of divergence between Viridiplantae and fungi/Metazoa groups, there was likely only one serpin gene [16]; however, the ancestral homolog from prokaryote or fungi has not yet been identified [16].
There are eight human serpin pseudogenes listed in Table 2. SERPINA15P has been named in succession for the A clade with the parent gene SERPINA6 according to Ensembl and SERPINE2 is the parent gene for SERPINE4P, again named in sequence of the E clade. There are ten mouse pseudogenes listed (Table 3) which remain uncharacterized.
Clade A serpins are classified as antitrypsin-like, extracellular proteins. They are the largest of the eight clades of extracellular serpins. The SERPINA clade has eleven human genes (1, 3–12) and two pseudogenes.
SERPINA1 is an inhibitory serpin formerly known as antitrypsin. It plays a role in the inhibition of neutrophil elastase [3,17].
SERPINA2 was initially classified as a pseudogene; however, recent evidence indicates that it produces an active transcript that encodes a protein located in the endoplasmic reticulum [18]. A study that sequenced SERPINA2 genes across multiple ethnic groups indicated that in addition to active SERPINA2 protein, there is a haplotype characterized by a partial deletion which has patterns suggestive of positive selection for loss-of-function of SERPINA2 protein. They suggest that the partial pseudogenization in humans may indicate an ongoing process of pseudogenization [19].
SERPINA3 is an inhibitory protein formerly known as antichymotrypsin. It inhibits chymotrypsin and cathepsin G [3,16]. This serpin is normally found in blood, liver, kidney, and lung.
SERPINA4 is an inhibitory protein formerly known as kallistatin (PI4), which inhibits kallikrein [20]. It is expressed in blood, liver, kidney, and heart.
SERPINA5, formerly a protein C inhibitor, inhibits active protein C. It is present in blood, kidney and liver.
SERPINA6 was formerly known as corticosteroid-binding globulin. It is a non-inhibitory protein that binds hormones, i.e., cortisol [16].
SERPINA7, formerly thyroxine-binding globulin, is involved in non-inhibitory thyroid hormone transport. It is expressed in blood, kidney, and heart.
SERPINA8 is now referred to as angiotensinogen (AGT), which is a hormone precursor. It has a distinct serpin domain (phylogenetically unrelated to other clade A members in the current analysis) and a distinct, smaller, agt domain. This particular serpin domain appears to be more closely associated with SERPINF and SERPING [21].
SERPINA9 appears to have a role in naïve B cell maintenance. Formerly called centerin, it is expressed in the plasma and liver.
SERPINA10 is an inhibitory protein responsible for inhibition of activated coagulation factors Z and XI [3]. Formerly known as protein Z-dependent proteinase inhibitor, it is expressed in blood and liver.
SERPINA11 is likely a pseudogene and is uncharacterized.
SERPINA12, formerly vaspin, inhibits kallikrein [22] and plays a role in insulin sensitivity [23]. It appears to be expressed in plasma, platelets, liver and heart.
In the mouse (Table 3), Serpina1 has been expanded to include six members, a–f. Serpina3 has been expanded to include nine members, a–c and f–n. The other clade a members are orthologous to human genes. Serpina8, now known as Agt in the mouse, is vital for the development and function of the renin-angiotensin system [24]. It is orthologous to AGT in humans.
Clade B
Clade B consists of intracellular serpins, including ov-serpins, which are ancestral to the extracellular serpins [16]. Members of this subfamily have shorter C and N termini than typical A members and also lack the secretory signal peptide sequence [4]. There are 13 human genes in clade B and one pseudogene. Serpins in clade B are important in inflammation and immune system function as well as mucous production [25]. SERPINB1, B6, B7, and B9 are involved in immune system function with roles in neutrophil and megakaryocyte development [26,27], as well as in the inhibition of the cytotoxic granule protease granzyme B [28]. SERPINB3 and its close homolog B4 are inhibitors that have roles in mucous production [29] and are expressed in epithelial tissues, such as tongue, tonsils, uterus, cervix, and vagina as well as in the upper respiratory tract and thymus [30].
Despite elusive function, SERPINB3 appears to have a role in apoptotic regulation and immunity, which implicates B3 in tumor metastasis and autoimmunity [30]. SERPINB5 has been shown to inhibit metastasis as a tumor suppressor in breast and prostate cancer [30,31]. In addition, multiple serpins in the B clade have been associated with oral squamous cell carcinoma, specifically SERPINB12, SERPINB13, SERPINB4, SERPINB3, SERPINB11, SERPINB7, and SERPINB2 [32]. Less is known about SERPINB10–B13. However, recent evidence points to a role for SERPINB13 in autoimmune diabetes progression and in inflammation [33].
SERPINB1 is an inhibitor of neutrophil elastase. It was formerly called monocyte neutrophil elastase inhibitor and is expressed ubiquitously.
SERPINB2 inhibits PLAU (uPA). It was formerly called plasminogen activator inhibitor 2 (PAI2) and is expressed in blood, kidney, and liver.
SERPINB3 is a cross-class inhibitor of cathepsin L and V [34]. Formerly referred to as squamous cell carcinoma antigen 1, it is expressed in blood, immune cells, kidney, lung, heart, and brain as well as numerous mucosal cells.
SERPINB4 was formerly known as squamous cell carcinoma antigen 2; it was discovered with SERPINB3 [25]. It is a cross-class inhibitor of cathepsin G and chymase [35] and is found in plasma, platelets, kidney, and heart, as well as saliva.
SERPINB5 is a non-inhibitory protein formerly called maspin. It is likely expressed in blood, kidney, liver, lung, as well as saliva.
SERPINB6, formerly called proteinase inhibitor 6 (PI6), is an inhibitor of granule protease, cathepsin G [36]. It is expressed ubiquitously.
SERPINB7 is involved in mesangial cell proliferation [37]. Formerly called megsin, it is expressed in blood and liver.
SERPINB8 is an inhibitory protein. Formerly called proteinase inhibitor 8 (PI8), it is expressed in blood and heart.
SERPINB9 is an inhibitory protein. Formerly called proteinase inhibitor 9 (PI9), it is expressed in blood, liver, lung, and heart.
SERPINB10 is an inhibitory protein involved in hematopoietic and myeloid development [37]. Formerly called bomapin, it expressed in blood and possibly in the brain.
SERPINB11 is a non-inhibitory serpin in human but retains trypsin inhibitory activity in mice [38]. It appears not to exhibit tissue-specific expression; however, it is expressed in HEK cells.
SERPINB12 is a trypsin inhibitor formerly known as yukopin [39]. It is expressed in blood, kidney, liver, heart, and brain.
SERPINB13, formerly known as hurpin, is expressed in blood, kidney, and saliva.
In clade b, mouse Serpinb1 has been expanded to include three members a–c; Serpinb3 as well as Serpinb6 have each expanded to include four members, a–d. In mice, Serpinb4 is not listed; however, it appears that SERPINB3 and SERPINB4 are equally related to Serpinb3a, Serpinb3b, Serpinb3c, and Serpinb3d, despite the initial theory that Serpinb3d is the mouse homolog of human SERPINB3 and Serpinb3c is the mouse homolog of SERPINB4. Serpinb9 has been expanded to seven members and one pseudogene. Interestingly, Serpinb11 is an active proteinase inhibitor, whereas the human ortholog is inactive.
Clade C
Serpin clade C consists of only one serpin member, SERPINC1, more commonly known as antithrombin. SERPINC1 inhibits coagulation factors IX and X [40]. It is expressed in blood, kidney, liver, lung, heart, brain, as well as saliva.
Serpinc1 gene encodes antithrombin and is orthologous to human SERPINC1.
Clade D
Clade D has one serpin member, SERPIND1, which is an extracellular protein also known as heparin cofactor II [41]. It is an inhibitor of thrombin [42] and is expressed in blood, kidney, liver, and heart.
Serpind1 encodes heparin cofactor II and is orthologous to SERPIND1.
Clade E
Clade E has three members, E1, E2, and E3, all of which are extracellular.
SERPINE1, also known as plasminogen activator inhibitor-1 (PAI1), inhibits thrombin. It is expressed in blood, liver, and heart.
SERPINE2 is a glial-derived nexin that is important in recovery of nerve structure and function [43]. It is expressed in blood, liver, kidney, and brain.
Little is known about the function of SERPINE3.
The mouse genes in clade e (Serpine1–3) are orthologous to human SERPINE1–3.
Clade F
There are two members in SERPIN clade F.
SERPINF1 (or pigment epithelium-derived factor (PEDF)) regulates angiogenesis and is an example of a non-inhibitory serpin. It is also thought to be a neurotrophic factor [16], and appears to be expressed in blood, liver, kidney, heart, and possibly lung.
SERPINF2, also known as α-2-antiplasmin, is an inhibitor of fibrinolysis. It is found in blood, kidney, liver, and heart.
Mouse Serpinf1 and f2 genes are orthologous to the human SERPINF1 and SERPINF2 genes, respectively.
Clade G
Clade G consists of one inhibitory serpin.
SERPING1 is a complement I esterase inhibitor [44] formerly called C1 inhibitor. It is expressed in blood, liver, kidney, lung, heart, and brain.
Mouse Serping1 encodes C1 inhibitor and is orthologous to SERPING1.
Clade H
Clade H consists of one member.
SERPINH1, also known as 47-kDa heat shock protein (HSP47), does not act as a proteinase inhibitor, but rather as a chaperone for collagen [45]. It is expressed in blood, liver and heart.
Mouse Serpinh1 encodes HSP47 and is orthologous to SERPINH1. Knockouts of Serpinh1 in mice are lethal [46] and missense mutations are associated with osteogenesis imperfecta [47].
Clade I
Clade I consists of two extracellular proteins. Serpins in clade I include the following.
SERPINI1 is a neuroserpin inhibitor of PLAT (tPA), PLAU (uPA), and plasmin [48]. It is expressed in liver and possibly plasma.
SERPINI2, previously known as pancipin, has an unknown protein target but may be involved in pancreatic dysfunction [49]. It is found in platelets and plasma as well as the heart.
The genes Serpini1 and Serpini2 encode mouse neuroserpin and pancipin, respectively. These are orthologous to SERPINI1 and SERPINI2 in the human.
Clades J–P
Clades j–p represent viral, nematode, horseshoe crab, blood fluke, and plant serpins [16] and will not be described further in this update.
Serpins associated with disease
Serpin polymorphisms have been associated with in many disease states, including blood clotting disorders, emphysema, cirrhosis, and dementia [15,16,50] as well as tumorigenesis and metastasis.
Mutations in SERPINA1 result in a decrease in circulating α-1-antitrypsin which is associated with emphysema and hepatocellular carcinoma [51]. Serpins are implicated in regulation of the cardiovascular system. For example, SERPINA4 depletion is related to renal and cardiovascular injury [52], SERPINA8 variations are integral to the normal function of the renin-angiotensin system and have been found to regulate blood pressure [53], and a SERPINA10 polymorphism was found to increase the risk of venous thromboembolism [54,55]. SERPINA3 deficiency is associated with emphysema [56].
Many SERPINBs are implicated in immune function and dysfunction. In many of these cases, intracellular serpins cause autoimmune antibody production, inflammation, neutropenia, and cancer metastasis [25]. SERPINC1 deficiency has been correlated with autoimmune disease, especially in patients producing antinuclear antibodies, such as those with systemic lupus erythematosus [30]. Interestingly, a SERPINA6 polymorphism has been associated with chronic fatigue syndrome [57], which is thought to be an immune disorder. SERPINA7 deficiency is associated with hyperthyroidism, and high SERPINA12 levels have been associated with insulin resistance [23].
Mutations in SERPINH1, as well as in SERPINF1, are associated with osteogenesis imperfecta [47,58].
Serpins appear to influence protein aggregation. In this respect, SERPINI1 expression has been correlated with dementia [4]. In addition, SERPINA5 accumulation has been identified in plaques in multiple sclerosis [59] and SERPINA3 polymerization may accelerate onset and severity of Alzheimer’s disease [30].
Many serpins have been implicated in cancer progression including SERPINBs (on the 18q21 locus) in oral squamous cell carcinoma [25]. Breast and prostate cancer metastases are also closely associated with SERPINB5 [60,61]. In addition, SERPINE1 appears to have a role in tumor progression [62] and metastasis [63]. Further, SERPINI2 may play a possible role in breast and pancreatic cancer metastasis [49]. Adult gliomas have significant associations with SERPINI1 [64], although its role is unknown. In addition, SERPINI1 has also been proposed as one of five biomarkers in hepatocellular carcinoma [65]. Another potential biomarker includes SERPINA9, which has been found to be strongly expressed in B cell lymphomas [66].
Mouse models of human disease
There are numerous mouse models used to study the role of SERPINs in disease. Some examples include knockout of Serpinag3 used in studying T cells in immunology [67], hepatic specific knockout of Serpinc1, which exhibits coagulopathy [68], and Agt knockout to study blood pressure regulation and the renin-angiotensin system where adipocyte-specific knockout of agt caused decreased systolic blood pressure [69]. Serpinb1 knockout mice show neutropenia [70].
Gene variants in SERPINS
A large number of human variants of serpin genes have been found. For example, NCBI’s dbSNP database (http://www.ncbi.nlm.nih.gov/snp) has 621 entries for SNPs of SERPINA1 alone (accessed October 2013). In addition, several groups have developed specific databases for individual SERPIN genes. These include databases for SERPINA1[71], SERPINC3[72], and SERPING1[73]. A number of pathologies in humans have been attributed to SERPIN gene variants, and often multiple deleterious mutations are known for each gene. Although a full listing of disease-causing SERPIN mutations is beyond the scope of this review, a sample of their scope is provided here. Mutations in the SERPINA1 gene have been linked with early-onset pulmonary emphysema, neonatal hepatitis, liver cirrhosis, and sometimes panniculitis and vasculitis [74,75]. SERPINA5 mutations have been linked with increased papillary thyroid cancer risk [76], and mutations in SERPINA10 have been linked to pregnancy complications [77]. Predisposition to familial venous thromboembolic disease has been linked to mutations in SERPINC1[78,79]. Finally, SNP variants for the SERPING1 gene have been shown to be associated with hereditary angioedema [80].
Serpins are a large class of diverse proteins, which contribute to numerous physiological and pathological conditions. Identification of serpins in immunological functions, pathology due to polymerization, and cancer metastasis underscores their diverse functions and physiological and pathological importance, and gene mutations often lead to loss-of-function and pathology in affected individuals. However, there is still much to learn about the functions and evolutionary development of serpins. Because of numerous biological functions and pathological states associated with serpins, further characterization of these proteins and mechanistic information will provide insight into potential biomarker identification and therapeutic targets.
CH carried out the sequence alignments and drafted the manuscript. BJ participated in the sequence alignment and analysis. MM reviewed mouse gene/protein data and the nomenclature for accuracy and completeness. MW reviewed human gene/protein data and nomenclature for accuracy and completeness. DT, GS and DWN reviewed and edited the manuscript. VV designed the study and reviewed data and manuscript. All authors read and approved the final manuscript.
This work was supported, in part, by the following NIH grants: R24 AA022057, NIEHS P30 ES06096, HG000330, U41HG003345 and also by a Welcome Trust grant no. 099129/Z/12/Z. Fellowship assistance for BCJ (F31 AA020728) is acknowledged. We would like to thank Konstandinos Vasiliou for his assistance.
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As nanotechnology progresses from research and development to commercialization and use, it is likely that manufactured nanomaterials and nanoproducts will be released into the environment.
Adverse effects of nanoparticles on human health depend on individual factors such as genetics and existing disease, as well as exposure, and nanoparticle chemistry, size, shape, agglomeration state, and electromagnetic properties. Animal and human studies show that inhaled nanoparticles are lessefficiently removed than larger particles by the macrophage clearance mechanisms in the lung,causing lung damage, and that nanoparticles can translocate through the circulatory, lymphatic, and nervous systems to many tissues and organs, including the brain.
The key to understanding the toxicity of nanoparticles is that their minute size, smaller than cells and cellular organelles, allows them to penetrate these basic biological structures, disrupting their normal function. Examples of toxic effects include tissue inflammation, and altered cellular redox balance toward oxidation, causing abnormal function or cell death. http://arxiv.org/ftp/arxiv/papers/0801/0801.3280.pdf
Some NPs happen to be toxic to biological systems, others are relatively benign, while others confer health benefits. As current knowledge of the toxicology of ‘bulk’ materials may not suffice in reliably predicting toxic forms of nanoparticles, ongoing and expanded study of ‘nanotoxicity’ will be necessary. For nanotechnologies with clearly associated health risks, intelligent design of materials and devices is needed to derive the benefits of these new technologies while limiting adverse health impacts.
Human skin, lungs, and the gastro-intestinal tract are in constant contact with the environment. While the skin is generally an effective barrier to foreign substances, the lungs and gastro-intestinal tract are more vulnerable. These three ways are the most likely points of entry for natural or anthropogenic nanoparticles. Injections and implants are other possible routes of exposure, primarily limited to engineered materials. Due to their small size, nanoparticles can translocate from these entry portals into the circulatory and lymphatic systems, and ultimately to body tissues and organs. Some nanoparticles, depending on their composition and size, can produce irreversible damage to cells by oxidative stress or/and organelle injury.
Are they biocompatible? Do the nanoparticles enter the lymphatic and circulatory systems? If not, do they accumulate in the skin and what are the long-term effects of accumulation? Do they produce inflammation? If they enter the lymphatic and circulatory system, is the amount significant? What are the long-term effects of this uptake? Related to the beneficial antioxidant properties of some nanomaterials, long-term effect need to be studied, in addition to the short-term antioxidant effect. What is the long-
term fate of these nanoparticles? Are they stored in the skin? Do they enter circulation? What happens when the nanoparticles undergo chemical reactions and lose their antioxidant properties?
For a full view of the questions needed to be addressed please visit. http://bdds.fudan.edu.cn/…/fdfa2aa9-df2b-4c9f-a2a5-a33ee29acb76.pdf
The answers to some of these questions are known, and will be presented in the chapter dedicated to nanoparticles toxicity, however most of the remaining questions still remain unanswered.
The immunostimulatory properties of nanoparticles discussed here include their antigenicity, adjuvant properties, inflammatory responses and the mechanisms through which nanoparticles are recognized by the immune system. Since this is a very complicated mechanism , the factors affecting the immune response are summaried here:
Size
Th1/Th2 stimulation
Adjuvent properties
Internalization/phagocytic uptake
Hapten properties
Particle clearance
Charge
Toxicity to immune cells
Binding plasma proteins
Particle clearance
Immune cell stimulation
Hydrophobicity
Interaction with plasma proteins
Internalization/phagocytic uptake
Immune cell stimulation
Particle clearance
Targeting
Immunogenicity
For example: In general, cationic (positively-charged) particles are more likely to induce inflammatory reactions than anionic (negativelycharged) and neutral species. For example, anionic generation- 4.5 PAMAM dendrimers did not cause human leukocytes (white blood cells) to secrete cytokines53 but cationic liposomes induced secretion of cytokines such as TNF, IL-12 and IFNγ. Systemic administration of another cationic nanoliposome alone or in combination with bacterial DNA did not induce cytokine production but increased the expression of DC surface markers, CD80/CD86, which are important in the inflammatory response.
Trace impurities within the nanomaterial formulation can also frequently induce an inflammatory response. Early studies suggest that carbon nanotubes induce inflammatory reactions, but a more recent study shows that they don’t when they are purified.
Another consideration in the inflammatory response is maintaining the Th1/Th2 response — the inflammatory reaction. triggered by Th cells that direct and activate other immune cells such as B and T cells and macrophages to secrete different cytokines. This response is important for protecting against cancer cells and pathogens and to avoid hypersensitivity (undesirable and exaggerated immune response) reactions. Several studies have addressed the influence of nanoparticles on Th1 and Th2 responses. Large (>1 μm) industrialized particles induced the Th1 response, whereas smaller ones (<500 nm) were associated with Th2.
In contrast, some small engineered nanoparticles such as 500 nm PLGA, 270 nm PLGA65, 80 nm and 100 nm nanoemulsions, 95 nm and 112 nm PEG–PHDA nanoparticles, and 123 nm dendrosome induced the Th1 response, while 5mn 5th generation PAMAM dendrimers didn’t cause overall inflammatory reaction in vivo but weakly induced Th2 cytokine production.
Therefore, more structure–activity relationship studies are required to understand how size, surface modification and charge of engineered particles influence the Th1/Th2 balance
Particle stimulation of adaptive (acquired) immunity has also been described. For example, small (<100 nm) polystyrene particles promoted CD8 and CD4 T-cell responses and were associated with higher antibody levels than larger (>500 nm) particles. Understanding the mechanisms requires further investigation, and is important for nanovaccine formulation development.
Phagosome-mediated processing and presentation of nanoparticles may differ from that of ‘canonical’ antigens. Certain biodegradable nanoparticles can be taken up through conventional pathogen-specific routes and can stimulate inflammatory reactions just like pathogens
More mechanistic studies are required to understand how the immune system manages non-biodegradable components of nanoparticles (for example, metallic cores). Many questions remain regarding processing of multi-component and multi functional nanoparticles. Are the individual components (the coating, core, and so on) stable inside the phagosome or do they separate? Are the biodegradable and non-biodegradable components processed together or individually?
Immunotoxicological analysis of new molecular entities is not a straightforward process, and there is no universal guide for immunotoxicity.
Conclusions:
The mechanism of cellular uptake of nanoparticles and the biodistribution depend on the physico-chemical properties of the particles and in particular on their surface characteristics. Moreover, as particles are mainly recognized and engulfed by immune cells special attention should be paid to nano–immuno interactions. It is also important to use primary cells for testing of the biocompatibility of nanoparticles, as they are closer to the in vivo situation when compared to transformed cell lines.
Understanding the unique characteristics of engineered nanomaterials and their interactions with biological systems is key to the safe implementation of these materials in novel biomedical diagnostics and therapeutics.
The main challenge in immunological studies of nanomaterials is choosing an experimental approach that is free of falsepositive or false-negative readouts. The majority of the standard immunotoxicological methods are applicable to nanomaterials. However, as nanoparticles represent physically and chemically diverse materials, the classical methods cannot always be applied without modification, and novel approaches may be required. For example, many nanoparticles absorb in the UV–Vis range and some particles may catalyse enzyme reactions or quench fluorescent dyes commonly used as detection reagents in various end-point or kinetic assays. These and other methodological
challenges in preclinical evaluation of nanoparticles are reviewed in detail elsewhere.
Both ‘classical’ and novel imunotoxicological assessments of nanomaterials clearly need a scrupulous stepwise validation, standardization, and demonstration of their physiological relevance.
Industry, academics, and federal agencies are now collaborating to identify critical parameters in nanoparticles characterization and to establish acceptance criteria for nanomaterial-specific assays.
Ref.
1.Cristina Buzea, Ivan. I. Pacheco Blandino, and Kevin Robbie. Nanomaterials and nanoparticles:Sources and toxicity. Biointerphases vol. 2, issue 4 (2007) pages MR17 – MR172 http://arxiv.org/ftp/arxiv/papers/0801/0801.3280.pdf
2. Marina A. Dobrovolskaia* and Scott E. McNeil. Immunological properties of engineered nanomaterials. Nature Nanotechnology 2007; 2; 469-479. http:// bdds.fudan.edu.cn/…/fdfa2aa9-df2b-4c9f-a2a5-a33ee29acb76.pdf
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