Immunomodulation and cancer: Using mechanistic paradigms to inform risk assessment

Accepted Manuscript Immunomodulation and cancer: Using mechanistic paradigms to inform risk assessment Rafael Ponce, PhD, DABT PII:

S2468-2020(17)30152-3

DOI:

10.1016/j.cotox.2018.06.002

Reference:

COTOX 139

To appear in:

Current Opinion in Toxicology

Received Date: 29 January 2018 Revised Date:

29 May 2018

Accepted Date: 5 June 2018

Please cite this article as: R. Ponce, Immunomodulation and cancer: Using mechanistic paradigms to inform risk assessment, Current Opinion in Toxicology (2018), doi: 10.1016/j.cotox.2018.06.002. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Immunomodulation and cancer: Using mechanistic paradigms to inform risk assessment Rafael Ponce, PhD, DABT Juno Therapeutics, Inc.

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400 Dexter Ave N Seattle, WA 98109

[email protected]

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P: 206-566-5604

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Abstract The use of immunotherapy in the treatment of chronic inflammatory conditions has demonstrated important clinical utility across a range of conditions including organ allograft maintenance and

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autoimmune disorders. However, the observation of increased cancer risk with broadly active immune suppression and concern about increased cancer risk with more targeted immune modulation remain as persistent challenges for clinicians, patients, and regulators. A strong relationship between immune

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status and cancer outcomes in human populations has been established based on the accumulated epidemiology findings in humans with immune deficiencies, clinical observational and biomarker data

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from patients, and mechanistic/experimental data. These data have refined our understanding of the role of the immune system in either promoting or suppressing tumor development and growth, and the reciprocal effects on the immune system driven by the tumor.

The integration of the epidemiological, clinical and mechanistic data have given rise to several modern

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conceptual paradigms that capture the complex interactions between tumors and the immune system. Under the Immunoediting Model, tumors and the host immune system co-evolve, and the selective pressure of the immune system can either eliminate the cancer, establish a state of equilibrium, or lead

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to tumor variants that escape immune surveillance. The Inflammation Model captures the role of chronic inflammation in promoting tumor growth in association with certain cancers. The observation

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of increased B cell malignancies in patients with either immune deficiencies or chronic immune activation likely results from the unique sensitivity of chronically activated B cells to genetic injury (B cell Lymphoma Model). Finally, because a viral etiology has been identified for a number of cancers, alterations in immune-mediated viral surveillance may underlie cancer risk in humans (Oncogenic Virus Model).

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The models described above demonstrate formidable complexity when trying to understand the potential risks associated with alterations in immune status that arise from use of therapeutic immunomodulators. These models can be used to guide our assessments when assessing or predicting

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the risk of cancer associated with immunomodulation, and can be used to guide mechanistic

experiments to understand the role of specific components of immunity in regulating or contributing to

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cancer risk.

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Introduction The relationship between the host immune system and cancer is a subject of intense academic and clinical scrutiny. Only since the end of the last century have we begun to sufficiently understand the

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rules governing the immune-tumor interactions to develop mechanistic models that encompass the cellular, soluble, and molecular interactions that ultimately lead to rejection or tolerance of the tumor. The complexity of these interactions is observed at the level of the myriad factors, derived from both

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the tumor as well as normal cells, which shape the clinical outcome; the dynamic nature of the

interactions observed in both the tumor and the immune response as tumor development progresses;

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and in the contextual nature of the interactions observed between different tumors and the immune system that shape both the immune response and drive selective pressure on the tumor. This context is best appreciated as we observe that the rules governing tumor tolerance or rejection appear to vary across different cancer types and across patients who have nominally similar cancers, likely based on

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individual-specific molecular and genetic backgrounds, and other factors (e.g., environment, comorbidities, prior or concurrent medications affecting immunity/inflammation). These dynamic, complex and contextual interactions between the immune system and tumors have

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challenged development of a unified mechanistic framework for understanding how the immune system contributes to tumor elimination, tolerance, or promotion. Instead, four general models have been

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proposed to explain specific tumor-immune interactions resulting in tumor rejection or tolerance: tumor immunoediting, immune control over oncogenic viruses, chronic inflammation, and chronic B cell stimulation. These models are explained briefly below, with the aim of understanding how they can inform assessments of cancer risk associated with therapeutic immunomodulation.

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Observational data in human populations demonstrate a role for immunity in the host defense against cancer Following the death of a patient with metastatic sarcoma at the end of the 19th century, the surgeon

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William Coley (1862 – 1936) began a review of the clinical case literature for possible courses of

treatment. This review led him to identify a number of case reports of tumor regression following streptococcal erysipelas skin infection. Based on these findings, Coley began clinical research

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investigating various bacterial preparations as a cancer treatment [1, 2]. Over the course of the next 40 years, Coley treated over 1000 patients, and achieved cures in approximately 10% of patients overall,

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and had tumor regressions in as many as half of these patients [3, 4]. Different tumor types have been found to be variously sensitive to the application of these toxins, with sarcomas being more sensitive than other common tumor types, achieving 20-year survival outcomes for 17 of 83 documented cases [4]. However, the validity of his therapies were heavily critiqued at the time due to poor patient follow-

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up and inconsistent preparation and administration of the toxins, which created variability in the outcome and made it difficult for other clinicians to obtain similar results. Moreover, the patients underwent an arduous experience, with a range of severe, potentially life-threatening constitutional

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effects [4-6]. Finally, the absence of a theoretical framework for understanding how the immune system could distinguish tumor cells from healthy cells challenged wide-spread adoption of the method

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[6].

A role for the immune system in host defense against cancer was proposed by Ehrlich in the beginning of the 20th century [7]. Since this proposal, various sources of data have developed that support a role for immune host defense against cancer. Epidemiology data from patients with congenital (primary) immunodeficiencies, therapeutically-induced immunodeficiencies (e.g., organ allograft recipients), and acquired immunodeficiencies (e.g., HIV/AIDS) indicate that immunosuppression and inflammation are both associated with increased cancer risk, and it is possible for a patient to have both

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immunosuppression and inflammation occurring simultaneously. For example, unresolved infections arising from immunosuppression can drive chronic inflammation that can each independently

Epidemiology of cancer in immunosuppressed populations

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contribute to increased cancer risk.

Cancer is the second leading cause of death among humans with congenital immune deficiencies, with pediatric cancer rates ranging up to 10,000-fold higher than those found among age-matched

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populations without these immune disorders. These congenital immune deficiencies encompass a

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spectrum of more than 200 distinct genetic defects in immune function, and have been associated with variably increased risk of hematologic malignancies (predominantly lymphomas) and solid tumors depending on the nature of the specific immune deficiency [8-13]. In addition, various primary immune deficiencies are associated with an increased risk of autoimmunity and unresolved infections, and some of the genetic defects that lead to immunodeficiency have additional complications, such as DNA repair

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disorders, which can each independently contribute to increased cancer risk [14-16]. Immune suppression among organ allograft recipients is associated an increased risk of both hematologic malignancies and solid tumor cancers, with very high increased relative risks (>20-fold) for

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Kaposi’s sarcoma, non-Hodgkin’s lymphoma, and non-melanoma skin cancer and high relative risks (>5fold) for melanoma, leukemia, hepatobiliary, cervical, and kidney cancers. Lower relative risks (>2-fold)

18].

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are observed for more common cancers (colon, breast, lung, stomach, esophagus, pancreas, ovary) [17,

Human immunodeficiency virus (HIV) infection, which results in the progressive loss of CD4+ T cells, results in a marked susceptibility to various infections (i.e., bacterial, fungal, viral, parasitic) and cancer [19-21]. The profile of cancer risks seen amongst patients with HIV/AIDS is generally similar to that seen in patients undergoing therapeutic immunosuppression for organ transplantation, with increasing risk as

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the patient progresses from HIV to AIDS [19, 21]. However, there are exceptions where the cancer risk in HIV patients is higher (i.e., CNS lymphoma, non-Hodgkin’s lymphoma and Kaposi’s sarcoma) or lower (i.e., bladder and thyroid cancers) than that in transplant patients [21].

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Taken as a whole, an increased cancer risk is observed for immunosuppressed populations for cancers associated with both a known a viral etiology and those without, indicating that immune surveillance of oncogenic viruses is not the only basis for the observed increased risk. Indeed, the extremely early

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occurrence of cancer in congenitally immune-deficient populations, often during the first few years of life, the absence of detectable virus in these tumors, and the increased occurrence of unresolved

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infections and/or autoimmunities suggest a role for chronic immune stimulation as an independent factor increasing cancer risk.

Immune surveillance of cancer and cancer immunoediting

The available human epidemiological data are supported by both mechanistic/experimental data, and

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human clinical outcomes and translational data that form the basis of current conceptual models relating immune responses and cancer outcomes. Burnet and Thomas [22, 23] first described the concept of immunological surveillance of tumors based on the presence of uniquely expressed antigens.

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Specifically, Burnet theorized “that somatic mutation may be associated with antigenic change and that immunity may play an important role in the natural history of cancer”, and that “irrespective of how the

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malignant cell is induced…a cell emerges which has a new histocompatibility antigen capable in principle of provoking a homograft rejection reaction” [24]. Immunological surveillance of transformed cells remains a core concept in the modern cancer immunoediting model, which refines the immunosurveillance model to encompass the dynamic interactions between the immune system and cancer that drives selective evolutionary pressure on the tumor [25]. This model captures three phases of tumor-immune system interactions: elimination,

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equilibrium, and escape. Under elimination, tumor eradication may result from the combined actions of innate and adaptive immunity (see Figure 1). Equilibrium may arise under conditions in which the immune system is sufficient to halt tumor outgrowth, but is insufficient to eliminate the tumor; it is

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during this phase that the selective pressure on the tumor by the immune system shapes tumor

antigenicity and drives development of immune-resistant clones. In the end, clinical disease (i.e., tumor escape) occurs as a failure of the immune system to control tumor growth, and can result from tumor-

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mediated expression of factors that allow the transformed cells to evade, suppress or subvert immune surveillance [Figure 2, 26, 27].

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Our understanding of the specific innate and adaptive immune mediators (e.g., cells, co-stimulatory signals, cytokines) that drive selective pressure on the tumor is informed by mechanistic studies of tumor development with genetic immunodeficiency, experimental immunodepletion or immunomodulation in animal models. A number of genetic deficiency models (e.g., Rag2-/-, Stat1-/-,

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IFNg-/-, perforin-/-, TRAIL-/-, GMCSF-/-, IL12rb2-/-) have evaluated spontaneous cancer development, or tumor frequency and survival outcomes following challenge with a carcinogen [reviewed by 28]. Such studies demonstrate a critical role for a robust T-cell mediated adaptive immune response (e.g.,

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dendritic cells, CD4+ and CD8+ T cells, IFN-γ, perforin) and innate immunity (e.g., NK cells, M1 macrophages). The aggregation of these studies have been used to build relational models to depict the

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key immune-associated factors involved in tumor elimination (e.g., Figure 1). The evaluation of the immune composition and distribution in the tumor microenvironment as a predictor of survival outcomes in cancer patients is providing important insights into the contextual nature of patient- and disease-associated factors that influence survival outcomes. A seminal paper by Galon et al. (2006) indicated that the location and density of T cell infiltrates (e.g., CD4+helper T cells, CD8+ cytotoxic T cells, CD45RO memory T cells) in the tumor microenvironment, and expression of effector molecules (e.g., granzymes, IFNγ, Tbet, IRF1, IL-12) were a potentially stronger predictor of

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long-term patient survival when compared to traditional histopathological scoring of colorectal tumors [29, 30]. Since this publication a number of studies have evaluated the ‘immune contexture’ of tumors as predictors of patient survival outcomes. A recent meta-analysis of 23 clinical studies reported that

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patients with high levels of CD8+ and CD3+ tumor-infiltrating lymphocytes (TILs) had better overall survival and disease-free survival (along with CD4+ T cells) compared to those with low levels of these TILs, and conversely high levels of FoxP3+ regulatory TILs had poor prognosis, in hepatocellular

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carcinoma [31]. Similar findings regarding the importance of a TH1-associated TIL phenotype on patient outcomes are available for a number of other cancer types, including oral cancer [32], ovarian cancer

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[33-35], breast cancer [36], and esophageal cancer [37].

Direct evidence demonstrating the pivotal role for T cells in anti-cancer immunity is now available following clinical evidence of improved survival and tumor shrinkage with T cell checkpoint molecules (i.e., anti-CTLA4 and anti-PD-1/PD-L1), approval of CD3-CD19 bispecific molecules to redirect T cell

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responses towards CD19+ tumors, and approval of chimeric antigen receptor (CAR) CD4+ and CD8+ T cells expressing a CD19-targeting scFv fused to an intracellular CD3ζ signaling domain and either CD19 or 4-1BB co-stimulatory domains [38-42]. Although these therapies have extremely promising

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therapeutic activity, their specific modes of action, which involve the potential for systemic immune activation and/or the loss of regulatory tolerance to self-antigens has been observed with a range of

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immune-related adverse events including autoimmunity, acute phase responses, and systemic cytokinemias that can range from moderate to severe, and require consideration given the potency and specialized management [43-45]. The tumor-immunity cycle

The initiation of lasting anti-tumor immunity begins with peripheral uptake, internal processing, and presentation of tumor-specific antigens by tissue resident dendritic cells (DC) to CD4+ and CD8+ T cells.

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This ability to process exogenous tumor antigen for presentation via MHC class I (termed crosspresentation) is critical for the generation of a CD8+ T cell response [46, 47]. Activated DCs migrate to lymph node and transfer antigen to lymphoid tissue-resident DCs, which present antigen and stimulate

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naïve T cells to develop full effector activity [48]. Upon activation, effector CD8+ T cells leave the lymph node, enter the tumor microenvironment, and initiate tumor cell killing [49, 50]. Although these

immune interactions are relatively well described and understood as necessary for the development of

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lasting anti-tumor immunity, there is significant complexity surrounding each of these steps, and tumors exploit pivotal control points to escape anti-tumor immune responses, such as expression or secretion

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of factors that suppress T cell activation or function [28, 51]. The biological and temporal interactions between the immune system and tumors that drive development of a productive anti-tumor immune response are captured under the cancer-immunity cycle [Figure 3, 52]. As depicted, tumor-derived antigens are captured in the periphery, processed, and presented to promote antigen-specific T cell

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activation. These activated T cells can traffic from their site of activation and infiltrate into the tumor to kill antigen-expressing tumor cells. The dying tumor cells can release additional tumor antigens and contribute to a pro-inflammatory environment that both broadens and deepens the immune response

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to the tumor through subsequent rounds of DC and T cell activation. Inflammation as a driver of cancer

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When considered as a whole, the available data summarized briefly above demonstrate a compelling role for innate and adaptive immunity in the elimination of cancer. Innate immune components such as dendritic cells and macrophages have indirect anti-tumor activity by shaping the tumor microenvironment [53]; cytokine release; and activation of and antigen cross-presentation to CD8 T cells following detection of dead tumor cells, or extracellular ATP and DNA [54, 55]. Innate immune cells, such as NK cells and M1 macrophages, can also directly kill and/or phagocytose tumor cells [56, 57].

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However, these data are insufficient to explain observations of increased cancer risk associated with chronic immune system activation, including increased cancer rates in patients with chronic infections or autoimmunity [58-62]. Chronic inflammation has been proposed to promote cancer development

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through various mechanisms, including genotoxic stress (cancer initiation); cellular proliferation and tumor cell survival (cancer promotion); and enhancing angiogenesis, tissue invasion, and epithelialmesenchymal transition [cancer progression, 63, 64]. Chronic inflammation has been proposed to

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establish permissive hypoxic niches that support emergence of transformed cells [65].

Neither silica particles nor asbestos are directly mutagenic, but their carcinogenicity has been associated

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with chronic IL-1β-driven inflammation following activation of the Nalp-3 inflammasome [66]. Chronic infections, such as with Helicobacter pylori (H. Pylori) or Schistosoma haematobium, is associated with increased cancer risk attributable to chronic inflammation [67]. Indeed, among the best models for chronic-inflammation associated cancers are mucosa-associated lymphoid tissue (MALT) lymphomas,

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which arise from chronic antigen stimulation of B cells as a result of either chronic infections (such as with H. pylori) or autoimmune diseases (e.g., Sjogren’s syndrome or Hashimoto thyroiditis), which drive polyclonal B cell proliferation and a proinflammatory environment [68-72].

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That the inflammatory tumor microenvironment contributes to both tumor promotion and host defense via cancer immunoediting has been shown in experimental models, and appears to be highly contextual

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as evidenced by a review of the role of a number of cytokines (e.g., TNF-α, TGF-β, IL-17, and IFN-γ) that have been associated with pro- and anti-tumorigenic roles [see 73, 74, 75].

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The unique susceptibility of the B cell to transformation with immune modulation

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An increased risk of lymphoproliferative disorders, including B cell lymphomas, are observed in immunosuppressed patients [e.g., organ allograft recipients, HIV/AID, congenital immunodeficiencies, 9, 10, 20, 76, 77, 78] and patients that have underlying chronic inflammation [e.g., unresolved infection, autoimmunity, tissue-specific inflammation, 79, 80]. These data indicate a unique susceptibility of B

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cells to transformation with immune system alterations. Epstein-Barr virus infection or antigenic

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stimulation result in B cell proliferation and maturation (somatic hypermutation and class switch recombination) [see 16, 81]. Both somatic hypermutation and class switch recombination are highly regulated phases of B cell maturation that require both random and specific DNA alterations to yield high affinity antibody with appropriate effector functionality [82]. However, during these hypermutable phases of B cell maturation, the B cell genome is at increased risk of inappropriate mutation and/or

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recombination that contribute to oncogenic transformation and lymphoma development [83-85]. Among patients who are immunosuppressed, a variable rate of EBV detection is found in association with lymphoma development, indicating that other factors can contribute to the disease, and a viral

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Oncogenic viruses

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etiology cannot be presumed [16].

A number of viruses have been identified as directly causing cancer risk in human populations and are nearly universally detected in cervical cancer (HPV), Kaposi’s sarcoma (HHV-8}, and Merkel cell carcinoma (Merkel cell polyomavirus, \Matutes, 2007 #1126; Moore, 2010 #1134; Ablashi, 2002 #1125}. For other cancer types, however, viral infection is often associated but cannot be presumed to underlie disease development (e.g., lymphoma and Epstein-Barr virus). Whereas nearly 100% of cervical cancers are associated with HPV infection, HPV infection is found in ~70% of oropharyngeal cancers, and often in

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association with other factors (e.g., tobacco use; http://www.cdc.gov/cancer/hpv/statistics/). In contrast to these direct viral carcinogens, a number of other viruses such as adult T cell

cause cancer, including causing chronic tissue injury/repair [86].

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leukemia/lymphoma (HTLV-1) and hepatitis B and C viruses appear to act through indirect means to

The innate immune system relies on recognition of pathogen-associated molecular patterns to activate proinflammatory anti-viral responses, and to initiate the adaptive anti-viral immune response [87]. Type

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I interferons (IFN-α/β) induced by recognition of viral infection promote cellular anti-viral host defenses, and shape both innate (e.g., NK cell) and adaptive (CD4+ and CD8+ T cell) anti-viral responses, which

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control or eliminate virally-infected cells [88, 89]. Recent data also support a role for type III interferons (IFN-λ) as having a distinct role from type I interferons in antiviral host defense [90]. Therapeutic immunomodulation and cancer risk

In the absence of a unifying model, the mechanistic models described above have been developed to

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explain specific relationships between the immune system and cancer control, elimination, development or promotion. However, what has been established is that the immune system has a context-dependent role in both cancer development and cancer elimination/control. So how shall scientists, clinicians, and

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regulators inform assessments of cancer risk with immunomodulation?

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With the advent of chemotherapeutic immunosuppression in organ transplantation in the early 1960s, reports of increased cancer rates began to accumulate by the late 1960s and early 1970s [91-94]. Concomitantly, mechanistic studies reported increased lymphoma incidence in mouse models involving azathioprine-mediated immunosuppression, including with chronic antigenic stimulation [95, 96]. Standard immunosuppressive regimens to suppress transplant rejection can involve a range of agents (often in combination) including glococorticoids (e.g., prednisolone), calcineurin inhibitors (cyclosporine, tacrolimus), mTOR inhibitors (sirolimus, everolimus), and IMDH inhibitors (e.g., azathioprine,

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mycophenolate mofetil). Based on the extensive patient outcome data, the prescribing information for these agents has been used to establish warnings and precautions regarding the increased risk of cancer development in patients treated with these agents (see Table 2).

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Over time, increasingly targeted therapeutic immunomodulatory drugs have been developed for the treatment of a wide variety of diseases including cancer (e.g., rituximab), multiple sclerosis

(natalizumab), ulcerative colitis and Crohn’s disease (vedolizumab, ustekinumab), rheumatoid arthritis

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(various TNF-α inhibitors) and other inflammatory diseases (Table 2). Whereas the use of broadly active immunosuppressive therapies to maintain tolerance to a transplant has been strongly associated with

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increased cancer risk across multiple studies in patients and animal models, the degree to which targeted immune modulation increases patient cancer risk remains difficult to ascertain. This difficulty is evidenced by review of the warnings and precautions regarding cancer risk in the prescribing information for various approved immune modulatory drugs, which reflect both a precautionary

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approach for some agents in the absence of identified risk and discrepancies across the precautions for agents with similar biological targets.

The challenge of evaluating the cancer risk for specific immunomodulation is exemplified in the

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assessment of cancer risk with TNF-α inhibition [75]. As a key pro-inflammatory cytokine, TNF-α appears to underlie various inflammatory diseases, including autoimmunity. The demonstration that

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TNF-α inhibition can markedly reduce the inflammation and manifestations of disease in patients with these diseases has resulted in approval of five TNF-α inhibitors in the US. As reviewed above, the available data suggest three plausible, possibly overlapping, etiologies affecting cancer risk in autoimmune patients treated with anti-TNF agents: immunosuppression of tumor- and viral-surveillance mechanisms mediated, in part, by TNF-α; suppression of TNF-α that may promote a proinflammatory environment and tumor development/growth; and spontaneous B-cell transformation attributable to the patient’s autoimmunity [16, 75].

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Review of the package inserts for anti-TNF therapeutics indicates concern for increased malignancy risk based on observations of imbalances in cancer findings, particularly lymphoma, in treated patients as compared to the general population (i.e., adalimumab and golimumab); for the remaining inhibitors, a

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precaution is provided based on a class effect as a TNF-α inhibitor (Table 2). However, as discussed above, patients with autoimmune diseases may be at increased risk of B cell lymphomas due to the disease, which confounds an assessment of cancer risk in this population. Although this confounding

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between disease severity and use of disease-modifying drugs is challenging to control for, a review of long-term patient outcomes (based on epidemiological meta-analyses) indicate that use of TNF-a

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inhibition among patients with rheumatoid arthritis is not generally associated with an increased cancer risk (beyond that attributable to disease alone), particularly cancers linked to immune suppression [16, 75]. Taken as a whole, these data demonstrate that whereas a theoretical risk of immune suppressionassociated cancer may be identified based on the underlying mechanism of action for specific

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immunotherapies, this risk should be balanced against the risk of cancer associated with unresolved, chronic inflammation should the patient be left untreated. Although mechanistic in vitro and in vivo studies are useful for identifying the impact of immunomodulation in specific settings, these models

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may not fully capture the complexity that exists in patients chronically treated with these immunomodulators; long-term outcome studies are presently the best tools for informing cancer risk in

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these patients. Conclusions

The review of TNF-α inhibitors reveals the on-going challenge in ascertaining attributable risk of cancer to specific immunotherapies as the immune system has a complex and contextual role in both cancer elimination and promotion. Such complexity limits our ability to establish simple conclusions regarding cancer risk with immunomodulation. Despite these challenges, clinical and epidemiological experience with cancer immunotherapies and multiplexed assessments of the tumor microenvironment are

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informing key factors associated with survival outcomes in cancer patients, and experimental/mechanistic provide important insights into the rules that govern immune surveillance of cancer. Such information can be used to develop a weight-of-evidenced based assessment of cancer

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risk with immunomodulation, which can be augmented over time by long-term patient outcome studies.

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Table 1: Age-adjusted rate ratios for cancer in transplantation recipients compared with the US population, by year after transplantation [reprinted with permission, 18]

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Table 2: Warning and precautions related to cancer risk from prescribing information for therapeutic immunomodulatory agents Immune Target(s)

Agent

Label Warning and Precautions related to cancer risk

Corticosteroids [Transplant rejection prophylaxis, various allergic, inflammatory, and autoimmune conditions] Calcineurin inhibitors [Transplant rejection prophylaxis, psoriasis, rheumatoid arthritis]

Inhibits NF-κB, cytokine production (T cell effector function), B cells, neutrophils and macrophages Cyclophilin binding, inhibits calcineurin inhibition, lymphocyte activation FKBP binding, inhibits calcineurin, T cell activation FKBP binding, inhibits mTOR, IL-2 mediated signal transduction and lymphocyte activation Purine analog, Inhibits lymphocyte replication, CD28mediated T cell costimulation Inhibits lymphocyte replication

prednisone (Sterapred, Rayos, Cadista) budesonide (Entocort EC)

Kaposi’s sarcoma has been reported to occur in patients receiving corticoid therapy, most often for chronic conditions. (e.g., Upjohn Co., Sept, 1995) None. (Perrigo, Apr, 2014)

prednisolone (Millipred)

None. (Watson Laboratories, Sept. 2007)

cyclosporine (Neoral, Sandimmune, Restasis)

Increased risk for development of lymphomas and malignancies, particularly those of the skin. (e.g., Watson Laboratories, June 2012).

Biologics

Inhibits inosine monophosphate dehydrogenase, lymphocyte replication CD20 antagonist

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…increased risk of developing lymphomas and other malignancies, particularly those of the skin. (e.g., Accord Healthcare, May 2011) …increased risk of developing lymphomas and other malignancies, particularly those of the skin. (Wyeth Pharmaceuticals, Dec 2012) None. (Novartis Corp, Sept 2017)

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everolimus (Afinitor, Zortress)

azathioprine (Azasan, Imuran)

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IMDH inhibitors [Transplant rejection prophylaxis, autoimmune conditions]

sirolimus (Rapamune)

leflunomide (Arava)

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mTOR inhibitors [Transplant rejection prophylaxis]

tacrolimus (Astagraf XL, Envarsus XR, Prograf)

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Class [Use]

…increased risk of developing lymphomas and other malignancies, particularly those of the skin. Reports of malignancy include post-transplant lymphoma and hepatosplenic T cell lymphoma…(e.g., Glenmark Pharmaceuticals, Dec 2015)

The risk of malignancy, particularly, lymphoproliferative disorder, is increased with some immunosuppression medications. (Apotex Corp., June 2017)

mycophenolate mofetil (CellCept, Myfortic)

…increased risk of developing lymphomas and other malignancies, particularly those of the skin. (e.g., Mylan Pharmaceuticals, Sept 2015)

rituximab (Rituxan) [B cell cancers, various autoimmune diseases]

None. (Genentech, Feb 2010)

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basiliximab (Simulect) [Transplant rejection prophylaxis]

While neither the incidence of lymphoproliferative disorders nor opportunistic infections was higher in Simulect-treated patients than in placebo-treated patients, patients on immunosuppressive therapy are at increased risk for developing these complications and should be monitored accordingly. (Novartis, Jan 2003)

CD25 (IL-2R) antagonist [ CD80/86 antagonist (blocks T cell activation)

daclizumab (Zinbryta) [multiple sclerosis] abatacept (Orencia) [autoimmunity], belatacept (Nulojix) [Transplant rejection prophylaxis]

None (Biogen, May 2016)

IL-12/IL-23 antagonist

ustekinumab (Stelara) [psoriasis, psoriatic arthritis, Crohn’s disease]

Stelara is an immunosuppressant and may increase the risk of malignancy. Malignancies were reported among subjects who received Stelara in clinical studies. In rodent models, inhibition of IL-12/IL-23p40 increased the risk of malignancy. The safety of Stelara has not been evaluated in patients who have a history of malignancy or who have a known malignancy. (Centocor Ortho Biotech, Sept 2009)

IL-17 antagonist

ixekizumab (Taltz) [plaque psoriasis] secukinumab (Cosentyx) [psoriasis, ankylosing spondylitis, psoriatic arthritis] anakinra (Kineret) [rheumatoid arthritis] tocilizumab (Actemra) [various autoimmune diseases, cytokine release syndrome]

None. (Eli Lilly, July 2017)

adalimumab (Humira) [various autoimmune diseases]

Lymphomas have been observed in patients treated with TNF blocking agents including Humira. In clinical trials, patients treated with Humira had a higher incidence of lymphoma than the expected rate in the general population (see ADVERSE REACTIONSMalignancies). While patients with rheumatoid arthritis, particularly those with highly active disease, may be at a higher risk (up to several fold) for the development of lymphoma, the role of TNF blockers in the development of malignancy is not known. (Abbott Laboratories, Jan 2003)

TNF-α antagonist

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The possibility exists for drugs inhibiting T cell activation, including ORENCIA, to affect host defenses against infections and malignancies since T cells mediate cellular immune responses. The impact of treatment with ORENCIA on the development and course of malignancies is not fully understood…(e.g.,BMS, June 2017)

None. (Novartis, Sept 2017)

None. (Swedish Orphan Biovitrum AB, Sept 2015)

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IL-6R antagonist

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IL-1R antagonist

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IL-17A antagonist

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CD25 (IL-2R) antagonist

The impact of treatment with Actemra on the development of malignancies is not known but malignancies were observed in clinical studies. Actemra is an immunosuppressant, and treatment with immunosuppressants may result in an increased risk of malignancies. (Genentech, Oct 2013)

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[Note from author: Extensive information on various malignancies is provided in this label. Abstracted text is provided for reference.] Malignancies, some fatal, have been reported among children, adolescents, and young adults who received treatment with TNF-blocking agents (initiation of therapy ≤ 18 years of age), of which CIMZIA is a member. Approximately half the cases were lymphomas, including Hodgkin’s and non-Hodgkin’s lymphoma. The other cases represented a variety of different malignancies and included rare malignancies usually associated with immunosuppression and malignancies that are not usually observed in children and adolescents… (UCB , Apr 2016 Lymphoma and other malignancies, some fatal, have been reported in children and adolescent patients treated with TNF blockers, including Enbrel (Amgen, Dec 2012)

etanercept (Enbrel) [various autoimmune diseases]

The incidence of lymphoma was seen more often than in the general U.S. population. Cases of other malignancies have been observed among patients receiving TNF-blockers (Janssen Biotech, Dec, 2011)

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golimumab (Simponi) [rheumatoid arthritis, psoriatic arthritis, and ankylosing spondylitis] infliximab (Remicade) [various autoimmune diseases]

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certolizumab (Cimzia) [Chron’s disease, rheumatoid arthritis, psoriatic arthritis]

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None. (Elan Pharmaceuticals, Jan 2012)

vedolizumab (Entyvio) [ulcerative colitis and Crohn's disease]

None. (Takeda, May 2014)

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natalizumab (Tysabri) [multiple sclerosis and Crohn's disease]

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α4-integrin antagonist (lymphocyte trafficking inhibitor) α4β7-integrin antagonist (lymphocyte trafficking inhibitor)

[Note from author: Extensive information on various malignancies is provided in this label. Abstracted text is provided for reference.] Malignancies, some fatal, have been reported among children, adolescents and young adults who received treatment with TNF-blocking agents (initiation of therapy ≤ 18 years of age), including REMICADE. Approximately half of these cases were lymphomas, including Hodgkin’s and non-Hodgkin’s lymphoma. The other cases represented a variety of malignancies, including rare malignancies that are usually associated with immunosuppression and malignancies that are not usually observed in children and adolescents….Postmarketing cases of hepatosplenic T-cell lymphoma (HSTCL), a rare type of T-cell lymphoma, have been reported in patients treated with TNF blockers including REMICADE. These cases have had a very aggressive disease course and have been fatal. Nov, 2013)

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Figure 1: Mechanistic model of immune-tumor interactions leading to tumor elimination [reprinted with permission, 26].

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Normal cells (blue) are transformed into tumor cells by carcinogens and other genotoxic insults along with the failure of intrinsic tumor suppressor mechanisms (e.g. p53, ATM). These tumor cells express stress-induced molecules such as surface calreticulin, tumor antigens in context of MHC class I molecules, and/or NKG2D ligands recognized by CD8+ effector cells and natural killer (NK) cells, respectively. Dendritic cells (DCs) can also take up and cross-present tumor antigens to T cells including NK T cells (NKT; glycolipid antigens presenting via CD1d). These activated effector cells release IFN-γ that can mediate anti-tumor effects by inhibiting tumor cell proliferation and angiogenesis. CD8+ T cells can induce tumor cell apoptosis by interacting with Fas and TRAIL receptors on tumor cells, or by secreting perforin and granzymes. Effector T cells express co-stimulatory molecules such as CD28, CD137, GITR, OX40 that enhance their proliferation and survival. γδ T cells can also recognize and kill tumors expressing NKG2D ligands (MICA/B in humans). Innate immune cells such as macrophages (M1) and granulocytes also contribute to anti-tumor immunity by secreting TNF-α, IL-1, IL-12 and ROS. In the Elimination phase, the balance is towards anti-tumor immunity due to an increase in expression of tumor antigens, MHC class I, Fas and TRAIL receptor on tumor cells and perforin, granzymes, IFN-α/β/γ, IL-1, IL-12, TNF-α in the tumor microenvironment.

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Figure 2: Mechanistic model of immune-tumor interactions leading to tumor escape [reprinted with permission, 26].

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During the Escape phase of cancer immunoediting, the immune system fails to restrict tumor outgrowth and tumor cells emerge causing clinically apparent disease. In this phase, tumor cells evade immune recognition (loss of tumor antigens, MHC class I or co-stimulatory molecules), express molecules of increased resistance (STAT-3), survival (anti-apoptotic molecule bcl2) and immunosuppression (IDO, TDO, PD-L1, galectin-1/3/9, CD39, CD73, adenosine receptors) and secrete cytokines VEGF, TGF-β, IL-6, M-CSF that enhance angiogenesis. Furthermore, myeloid-derived suppressor cells (MDSCs), M2 macrophages and DCs may also express immunoregulatory molecules such as arginase, iNOS and IDO and secrete immunosuppressive cytokines IL-10 and TGF-β that can inhibit CD8+ proliferation or induce apoptosis. MDSCs and IDO expressing DCs also induces the generation of regulatory T cells. IDO, arginase, CD39 and CD73 are immunoregulatory enzymes whereas IDO catabolize tryptophan to kyneurenine, arginase catabolize L-arginine to ornithine and urea, CD39 metabolise ATP to AMP which can further be metabolised to adenosine by CD73. Adenosine can bind to adenosine receptors — A2aR and A2bR expressed on tumor cells, endothelial cells and immune cells. T cells including Tregs may express inhibitory receptors such as PD-1, CTLA-4, Tim-3 and LAG-3 that suppresses anti-tumor immune response and favor tumor outgrowth. In the Escape phase, the balance is skewed towards tumor progression due to the presence of immunosuppressive cytokines and molecules such as IL-10, TGF-β, VEGF, IDO, PD-L1.

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Figure 3: The cancer immunity cycle [reprinted with permission, 52]

1. 2. 3. 4.

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The generation of immunity to cancer is a cyclic process that can be self-propagating, leading to an accumulation of immune-stimulatory factors that in principle should amplify and broaden T cell responses. The cycle is also characterized by inhibitory factors that lead to immune regulatory feedback mechanisms, which can halt the development or limit the immunity. This cycle can be divided into seven major steps, starting with the release of antigens from the cancer cell and ending with the killing of cancer cells. Each step is described above, with the primary cell types involved and the anatomic location of the activity listed. Abbreviations are as follows: APCs, antigen presenting cells; CTLs, cytotoxic T lymphocytes.

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AUTHOR DECLARATION TEMPLATE ACCEPTED MANUSCRIPT We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome.

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We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us.

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We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property.