Skip to main content
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2023 Jul 12;318(1):51–60. doi: 10.1111/imr.13242

Rheumatic complications of checkpoint inhibitors: Lessons from autoimmunity

Gary Reynolds 1,2,
PMCID: PMC10952967  PMID: 37435963

Summary

Immune checkpoint inhibitors are now an established treatment in the management of a range of cancers. Their success means that their use is likely to increase in future in terms of the numbers of patients treated, the indications and the range of immune checkpoints targeted. They function by counteracting immune evasion by the tumor but, as a consequence, can breach self‐tolerance at other sites leading to a range of immune‐related adverse events. Included among these complications are a range of rheumatologic complications, including inflammatory arthritis and keratoconjunctivitis sicca. These superficially resemble immune‐mediated rheumatic diseases (IMRDs) such as rheumatoid arthritis and Sjogren's disease but preliminary studies suggest they are clinically and immunologically distinct entities. However, there appear to be common processes that predispose to the development of both that may inform preventative interventions and predictive tools. Both groups of conditions highlight the centrality of immune checkpoints in controlling tolerance and how it can be restored. Here we will discuss some of these commonalities and differences between rheumatic irAEs and IMRDs.

Keywords: arthritis, autoimmunity, checkpoint inhibitors, CTLA4, immunotherapy, PD1, rheumatology

1. INTRODUCTION

Immune checkpoint inhibitors (ICIs) are a therapeutic class of treatments that reinvigorate immune responses to tumor neoantigens. Their use has resulted in improved outcomes in a range of cancers and they are capable of inducing durable remission in some cases. The first in class therapy was ipilimumab which targets the CTLA4 axis and was approved for the treatment of melanoma in 2011. 1 Following this initial success the range of indications has expanded with a further seven treatments targeting PD1/PDL1 receiving FDA approval. 2 As of January 2023, there were 1610 active or recruiting clinical trials in checkpoint inhibitors (ClinicalTrials.gov) with 156 of these at Phase III/IV. Given this it is likely that the range of immune checkpoints targeted and the number of patients receiving checkpoint inhibitor therapies will increase significantly over the next decade. However, a significant barrier to their broader application is the development of immune‐mediated adverse events (irAEs). These comprise a heterogeneous group of treatment‐associated effects mediated by autoreactive immune responses that are distinct from the side‐effects of conventional treatments. They can affect nearly any organ and are considered an aberrant off‐target response by an excessively activated immune system. 3 They are very common, occurring in nearly 80% of patients treated with combination therapy 4 and many patients develop more than one toxicity. 5

Among these complications are a range of rheumatic toxicities that includes inflammatory arthritis, keratoconjunctivitis sicca, xerostomia, a polymyalgia‐like illness, and myositis. In contrast to severe complications such as myocarditis, rheumatic irAEs are rarely fatal. However, they are disabling, they can limit treatment efficacy, they can become chronic and they are likely to become more common. Furthermore, while rates of rheumatic irAEs with current therapies targeting the CTLA4 and PD1/PDL1 pathway are low at around 5%, both primary human immunodeficiencies and animal models suggest modulating different immune checkpoints may produce different patterns of autoimmune complications, potentially with higher rates and severity of rheumatic diseases. Rheumatic irAEs share superficial similarities with common immune‐mediated rheumatic diseases (IMRDs) such as rheumatoid arthritis (RA), psoriatic arthritis (PsA), Sjogren's syndrome (SS), and polymyalgia rheumatica (PMR), for example in clinical presentation, that make it tempting to group them together. Indeed, in the absence of robust characterization and evidence, applying lessons from IMRDs to rheumatic irAEs has been an effective approach to guide management. However emerging evidence highlights that they are clinically and immunologically distinct processes. 6 Despite this, they highlight the importance of immune checkpoints in self‐tolerance and there are intriguing commonalities in the factors that lead to the development of both (Figure 1). Here we will discuss these, reviewing the parallels and differences between them that may help us understand how they develop.

FIGURE 1.

FIGURE 1

Common mechanisms underlying rheumatic irAEs and IMRDs. Multiple factors that are known to contribute to the development of common IMRDs have been shown to predispose to the development of rheumatic irAEs, including genetic and environmental factors. Similarly there are shared alterations in peripheral immunity that herald the development of both.

2. PARALLELS IN THE DEVELOPMENT OF IMRDS AND RHEUMATIC IRAES

In contrast to rheumatic irAEs, the clinical presentation of IMRDs usually represents the culmination of decades of subclinical altered immunity in genetically predisposed individuals. 7 , 8 Many IMRDs have a preclinical phase characterized by detectable self‐reactive responses, for example circulating auto‐antibodies against citrullinated peptides in RA (anti‐citrullinated peptide antibodies, ACPAs) and against nuclear components in Sjogren's and SLE (anti‐nuclear antibodies, ANA), that are present many years before the onset of disease. In seronegative conditions such as psoriatic arthritis it is harder to define this preclinical phase of autoreactivity but, for example, there is a median period of 8 years between the onset of psoriasis and the development of psoriatic arthritis suggesting a similarly prolonged period of subclinical autoreactivity. 9 The development of rheumatic irAEs is more abrupt, with a median time of onset across all irAEs from initiation of 63 days. 10 However, this delay, and the fact that not everyone develops an irAE, demonstrates that ICI treatment is a necessary but not sufficient condition for the development of these complications. A better understanding of the additional risk factors that result in complications is important for assessing risk and tailoring therapy in future.

2.1. Genetics

Genetic factors contribute significantly to the development of IMRDs with heritability estimates of around 40%–60% for RA, SLE, and Sjogren's syndrome. 11 , 12 , 13 Genome wide association studies (GWAS) have helped to identify many of the variants that convey protection or risk of developing these conditions. Of the non‐HLA variants detected these generally fall in distal regulatory regions and individually have small effect sizes. The complexity of the genetic basis of IMRDs makes it challenging to identify individuals at risk of developing disease to initiate preventative strategies such as lifestyle changes or immunomodulatory therapy. Polygenic risk scores (PRS) attempt to overcome this by summarizing the effect of all variants to provide an overall estimate of the genetic contribution to an individual's disease risk. These are complex and require large datasets, e.g., a recent RA PRS included 276,020. 14 Despite this it is hoped that the same approach might be taken to predict individuals at risk of developing complications from ICI therapy. Like IMRDs, there is almost certainly a genetic predisposition, but the challenge of developing analogous PRSs may be even more daunting than for IMRDs. For example, conceivably the genetic risk variants that predispose to ipilimumab‐induced colitis are quite different to those that predispose to nivolumab‐induced arthritis. There may be hope that, much like there are common risk variants across autoimmune conditions such as CTLA4, TNF, and PTPN22, 15 there are shared variants that predict ICI toxicity that can form the basis of a predictive score. Supporting this notion, a SNP in the IL7 gene was associated with the presence of any form or grade of ICI toxicity in a study of 1751 patients, 16 although this gene does not appear as a hit for IMRDs across GWAS. Similarly, early studies suggest that, much like IMRDs, different HLA alleles appear to predispose to different organ‐specific toxicities (reviewed in Ref. 17). In IMRDs it is theorized that HLA variants possess different binding affinities for self‐antigens; notably for example shared epitope alleles of RA having greater affinity for citrullinated peptides. The association of specific HLA variants with irAEs could similarly imply targeting of common autoantigens in individual rheumatic irAEs. As more detailed characterization of the genetic basis of rheumatic irAEs is developed, it will be interesting to see how it overlaps with that of IMRDs, if at all. Similarly, given the correlation between the development of irAEs and ICI efficacy, it will be important to determine the correlation between variants that predispose to toxicity and those that predict ICI efficacy.

2.2. Environment

The contribution of the environment to the development of IMRDs is complex and multifactorial. It includes variables such as diet, obesity, smoking, and infection. A commonality among some of these factors is that they can promote inflammation and neoantigen formation. In RA, mucosal inflammation induced by smoking in the lungs or periodontitis in the oral cavity upregulates the enzyme PAD which leads to the formation of citrullinated peptides. In SLE, UV light induces cellular apoptosis and inflammation leading to defective clearance and the generation of antibody responses to nuclear components such as double stranded DNA. Cocaine use results in nasal mucosal inflammation and a clinical picture that resembles vasculitis, including the development of antineutrophil cytoplasmic antibodies.

In contrast to rheumatic irAEs, which develop subacutely, these factors are generally presumed to influence IMRD development over long periods. However, there are some common risk factors, for example, both smoking and obesity increases the risk of irAE development. 18 , 19 A more immediate source of inflammation and neoantigen formation that may drive breach of tolerance may be the tumor microenvironment itself. Tumors with low levels of inflammation, as defined by the level of T‐cell infiltration, are described as “cold” and have poorer responses to ICIs. Mutations result in altered peptides that generate neoantigens and enhance the inflammatory response. Neoantigen generation as quantified by mutational burden of the primary tumor has been posited as a predictor of efficacy of ICI response, 20 although evidence is mixed depending on definitions used. 21 Conventional cytotoxic chemotherapy can enhance ICI responses, presumably as it can induce cell death and neoantigen formation within otherwise cold tumors. 22 Given this, it might be hypothesized that tumor mutational burden would be associated with higher rates of rheumatic irAEs, as they contain the requisite environment of inflammation and neoantigen formation for their development of IMRDs. Meta‐analysis of anti‐PD1 responses potentially supports this with a correlation between rates of irAE and median number of somatic mutations per megabase in the tumor type. 23

Microbiome is a key environmental factor influencing IMRD development, ICI efficacy and irAE development. It is potentially more amenable to preventative intervention than other risk factors. Promisingly fecal microbiota transplant has demonstrated efficacy in both improving efficacy of ICI therapy and in the treatment of ICI‐induced colitis. 24 However, the host‐microbiome interactions responsible for this efficacy are unclear and across studies multiple taxa and species have been implicated in the development of response and toxicity with ICIs which makes tailoring therapy difficult. Generally, overall diversity of species appears to be important in determining outcomes, with high diversity of gut microbiota associated with a response to ICI treatment and antibiotic therapy with adverse outcomes. The same effect is seen in IMRD development with reduced gut microbiome diversity associated with the development of RA, 25 SLE, 26 psoriatic arthritis, 27 and different forms of vasculitis. 28 As for ICI response and toxicity, although individual species have been associated with different types and stages of IMRDs, there is minimal consistent overlap between them. 29 Interestingly, different organ involvement of irAEs is associated with different patterns of gut microbiota, with multiple Streptococcus and Lactobacillus species specifically associated with the development of ICI‐arthritis rather than other toxicities. 30 Although these associations are preliminary, species from the same genera have been associated with RA development. 31

2.3. Aging

The risk of autoimmunity generally increases with age for many conditions, including RA. Aging itself is associated with a complex of immune alterations including raised inflammatory cytokines and declines in the diversity and increases in clonality of naive CD4 and CD8 T cells, a process termed “inflammaging”. 32 , 33 It might be posited that this would predispose to irAE development, and in murine models irAEs were commoner in older mice. 34 Despite this, preliminary studies do not suggest a heightened risk in older people. 35 Pediatric patients (<21 years old) treated with ipilimumab for solid organ tumors developed irAEs at a similar rate to adults. 36 This may depend on the ICI and toxicity itself though, as in another study arthritis was notably commoner in older people. 37

3. IMMUNE PHENOTYPING OF RHEUMATIC IRAES

3.1. T cells

To date there have been limited analyses of the immune profile of rheumatic irAEs. What is known so far suggests the mechanisms responsible for irAEs are different from those responsible for IMRDs, supporting the notion from epidemiological and clinical data that these are distinct conditions. In contrast there appear to be surprising similarities between irAE toxicities across organs. In irAE‐arthritis there is an expansion of PDCD1 hi CXCL13 + CD8A + T cells. These T cells are activated (expressing IFNG and HAVCR2), proliferative, and are more clonal. 38 , 39 Phenotypically similar activated PDCD1 hi CXCL13 + CD8A + T cells have been found to be enriched in irAE‐colitis, 40 again expressing high IFNG and HAVCR2 but, in contrast to those in irArthritis, also coexpressing Th17 cytokines IL17A and IL26. The same population is enriched in checkpoint inhibitor pneumonitis, again overexpressing IL17A and IFNG but also here expressing CSF2. 41 Notably this conserved transcriptional signature of CD8 T cells is seen across tumors in response to checkpoint inhibitor therapy and is predicted to mark clonal responses to tumor neo‐antigens, with a similar phenotype identified within tumors and sites of metastasis. 42 Alongside recognized prognostic indicators like mutational burden, CD8‐derived CXCL13 within tumors is an independent predictor of checkpoint inhibitor sensitivity. 43 To date a meta‐analysis of cell states across irAEs or with their IMRD equivalents has not been made but it will be interesting to determine the degree of conservation between and across them.

In contrast there are parallels between the changes that take place in the T‐cell repertoire between rheumatic irAEs and IMRDs prior to clinical presentation. The mechanism of anti‐PD1 treatment is to invigorate existing T‐cell clones, and this induces a detectable oligoclonal expansion in the periphery with an overall reduction in diversity. 44 However, findings vary between studies and measures of diversity are highly donor dependent so it is difficult to convert this observation into a tractable biomarker. In IMRDs the same pattern is a feature of pre‐ or early IMRDs with a reduction in diversity associated with oligoclonal expansions a feature of Sjogren's, 45 PMR/GCA, 46 and early RA. 47 This likely represents affinity maturation and epitope spreading of the autoantibody responses leading to responses with greater specificity for targeted self‐antigens and at the same time antibodies recognizing a broader range of self‐antigens. 48 , 49

3.2. B cells

Despite the prominence of the naive B‐cell homing cytokine CXCL13 in irAE expression data, rheumatic irAEs are notable for the lack of B‐cell infiltrates. Many IMRDs are associated with autoantibodies that not only indicate the diagnosis but also help to stratify conditions by treatment responsiveness, organ involvement and prognosis. Histologically target organs of IMRDs, including RA synovium and ANCA‐vasculitis affected lungs, contain tertiary lymphoid structures that facilitate responses against local antigens. 50 , 51 By contrast rheumatic irAEs such as arthritis have limited B cell infiltration. 38 , 39 Labial salivary gland biopsies from irAE‐induced exocrine gland dysfunction superficially share a similar pattern of lymphocytic inflammation to Sjogren's, but they are notable for the reduced or absent level of CD20+ B cells. 52 Plasma cells are present in muscle in inclusion body myositis and polymyositis, with evidence of affinity maturation with IgM to IgG isotype class switching, clonal expansion and somatic mutation within muscle. 53 In contrast, in irAE myositis, there is a near absence of B cells and a predominance of CD8+ T cells. 54 Notably, although B‐cell infiltration in irAEs is limited, in many primary tumors B cells and plasma cells are not only present but also positively correlate with response to treatment. 55

3.3. Cytokine profiles

The development of targeted biologic therapies for the management of IMRDs has helped to reveal the cytokine networks underlying different conditions. In inflammatory arthritis for example, whereas IL6 blockade is effective in RA, it is ineffective in psoriatic arthritis. Similarly whereas anti‐IL17/23 treatment is effective in psoriatic arthritis, it is not effective in RA. Anti‐TNF therapy is effective in both psoriatic arthritis and RA but, in predisposed individuals, can induce the development of SLE. This highlights the importance of developing a robust taxonomy of inflammatory arthritis and other IMRDs using criteria such as serology, clinical presentation and associated clinical features. Currently most patients with rheumatic irAEs are treated with corticosteroids, as these are fast acting and broadly effective in inflammatory conditions. For some conditions, such as PMR, vasculitis and myositis, corticosteroids remain the mainstay of therapy as for their irAE mimics. However, corticosteroids have significant adverse side‐effects and, with the advent of targeted biologic therapies, long‐term therapy with them is avoided in IMRDs where possible. Second‐line treatment for many rheumatic irAEs is conventional DMARDs such as methotrexate and sulfasalazine. Methotrexate works through multiple mechanisms including inhibition of NF‐kB and increasing T‐cell sensitivity to apoptosis, 56 and it is broadly effective in a range of IMRDs (and other forms of autoimmunity) so its efficacy in irAE arthritis does distinguish it. However, as there is a high risk of irAE‐arthritis persistence after cessation of treatment (around 49% at 6 months), 57 there is likely to be greater use of more targeted therapies in future. To date multiple agents have shown efficacy, including anti‐TNF, 58 anti‐IL6R (tocilizumab), 59 and tofacitnib (JAK inhibitor), 60 but numbers are small. There is evidence to suggest the IL17/23 axis is active in irAE‐arthritis with enrichment of Th17 cells, but there has been a reticence to target this pathway because of a concern that it can negatively affect anti‐tumor immunity. 61 A potential outcome from the increased use of targeted therapies may be to highlight underlying heterogeneity underlying shared clinical presentations of rheumatic irAEs. For example anti‐PD1/PDL1 monotherapy commonly causes a small joint arthritis whereas in combination with anti‐CTLA4 a large joint mono/oligoarthritis is more common. 62 Patients on combination CTLA4/PD1 therapy have higher levels of CD4+IL17+ T cells in both peripheral blood and synovial fluid than those on monotherapy, potentially indicating differentially active cytokine networks. 39 Conceivably, as with IMRDs, these different presentations are driven by different cytokine networks with different responses to treatment.

4. CTLA4—A CENTRAL PATHWAY IN RHEUMATIC DISEASE AND CANCER

CTLA4 was the first immune checkpoint to be targeted for cancer immunotherapy. CTLA4 is a significant GWAS loci in many autoimmune conditions including RA, Grave's disease, Type I diabetes mellitus, vitiligo, and alopecia areata. 63 In CTLA4‐deficient mice, alongside multiorgan inflammation particularly of the heart and lungs, mice occasionally develop arthritis and vasculitis. 64 Interestingly, as with rheumatic irAEs, the immune infiltrate in CTLA4 deficiency is predominantly T cells with relatively few B cells. In human CTLA4 deficiency, inflammatory arthritis occurs in around 14% of individuals (though notably other autoimmune complications are more common). 65 As with irAE‐arthritis, while psoriatic arthritis and RA can occur in these patients, generally the inflammatory arthritis that develops is a clinically distinct entity. 66 Abatacept, a CTLA4 fusion protein, was approved for use in rheumatoid arthritis in 2008 (5 years before the approval of ipilimumab 67 ) and, following this, has subsequently demonstrated efficacy in many diverse IMRDs including psoriatic arthritis, juvenile idiopathic arthritis (JIA), myositis, 68 giant cell arteritis (GCA) 69 and ANCA vasculitis. 70 Overall these data suggest that CTLA4 plays a central role in maintaining tolerance and, consistent with this, rates of irAEs are higher for the CTLA4‐targeting therapy ipilimumab than for other checkpoint inhibitors that target PD1/PD‐L1.

CTLA4 is upregulated upon activation by CD4+ and CD8+ T cells and constitutively expressed by Tregs. Its ligands, CD80 and CD86, which are the targets of abatacept, are more broadly expressed by antigen presenting cells, B cells, monocytes/macrophages, and tumor cells. This means that it is an oversimplification to state that abatacept has the opposite therapeutic effect of ipilimumab. Ipilimumab is thought to function by lifting the block on co‐stimulation of naive T cells, although this is debated. 71 In support of this Ipilimumab does not alter existing antiviral and anti‐tumor responses, but instead promotes new anti‐melanoma responses and a broadening of the TCR repertoire. 44 , 72 In contrast, modulation of naive responses is less likely to be the mechanism of action of abatacept. It is as effective as other biologic agents such as anti‐TNFs in established IMRDs, long after initial priming has taken place. 73 In collagen‐induced arthritis abatacept is still effective at ameliorating inflammation in the absence of CD4+ T cells in established disease. 74

The function of CTLA4 in other cell types is less well understood than its action at the stage of initial naive T‐cell priming in secondary lymphoid organs. This mechanism makes it an attractive tool to modulate nascent immune responses through targeting CTLA4 in early or preclinical IMRDs such as RA and Sjogren's. Clinical trials of abatacept in very early disease have taken place with the outcome of preventing or delaying the development of disease or inducing remission. 75 , 76 , 77 To date this approach has been disappointing; while there is an increasing rates of patients maintaining drug‐free remission, an effect that appears to be due to true immune modulation rather than simply anti‐inflammatory effects as it easily outlasts the effect of abatacept treatment (half‐life 14 days), the effects are small (14% vs. 8%), with the vast majority continuing to develop chronic disease. However, given the potential to prevent long‐term, disabling disease, there is ongoing enthusiasm in exploring whether better targeting of immune checkpoints, patient selection or the stage of disease could transform the trajectory of autoimmunity.

In this model of ipilimumab function, T cells specific for tumor neoantigens are present but due to the suppressive function of CTLA4 in secondary lymphoid organs fail to generate appropriate anti‐tumor responses. Given this, there would be understandable anxiety that abatacept would suppress normal tumor surveillance. Reassuringly longitudinal data collected across multiple national registries of biologic rheumatic drugs in real‐world cohorts do not highlight a risk signal for cancer with abatacept treatment. 78 , 79 , 80 Abatacept is avoided with live vaccines but patients with RA on abatacept are able to mount reasonable vaccine responses 81 and have a lower risk of infection than with other biologics. 82

5. TARGETING DIFFERENT IMMUNE CHECKPOINTS: NEW FORMS OF RHEUMATIC IRAES?

Currently only the CTLA4 and PD1/PDL1 immune checkpoints are therapeutically targeted for the treatment of cancer. However, there are more than 30 different molecules that are considered immune checkpoints. These vary in distribution by cell type, activation status, and organ and their action can be activating or inhibitory. This diversity allows fine tuning of the immune response and, in a system in which around 4% of T cells are self‐reactive in the absence of regulatory T cells, 83 vital to maintain self‐tolerance. Following the success of CTLA4 and PD1/PDL1 therapies, there has unsurprisingly been interest in targeting other immune checkpoints including BTLA, VISTA, TIM‐3, and CD47 as well as co‐stimulatory molecules such as CD137, OX40, and GITR 84 with the hope that targeting other immune checkpoints may result in lower rates of toxicity or greater efficacy in a given cancer. The accumulated outcome data from anti‐CTLA4 and anti‐PD1/PDL1 trials have highlighted that targeting different immune checkpoints results in different rates of treatment efficacy and irAEs, but also that the patterns and clinical picture of the irAEs that develop differ. To date, in comparison to other forms of irAE, rheumatic irAEs are comparatively unusual, and generally seronegative with highest rates of inflammatory arthritis, polymyalgia and exocrine gland dysfunction. Presentations of irAEs that resemble potentially organ‐ and life‐threatening conditions like lupus or vasculitis are thankfully rare. As clinical trials progress our understanding of how targeting these different immune checkpoints influences the range of clinical presentations that can develop. However at this stage, with the recognition of the limitation of preclinical models to predicting irAEs, there are some indications of the pattern of rheumatic irAEs that could develop with these novel therapies.

5.1. VISTA

VISTA is an inhibitory checkpoint molecule expressed by lymphocytes, but also more broadly and at higher levels on myeloid cells. VISTA deficiency results in spontaneous development of cutaneous and systemic lupus‐like disease accompanied by ANA and anti‐double‐stranded DNA antibodies in non‐predisposed BALB/c mice. 85 In contrast, although lupus can be exacerbated when CTLA4 is disrupted or induced in susceptible strains, it does not spontaneously occur and while glomerulonephritis and arthritis develop in PD‐1 knockout mice, this is not associated with the development of anti‐dsDNA antibodies. 86 Interestingly, as well as immune cells VISTA is expressed at high levels of keratinocytes where it regulates IFN‐I production. Cutaneous UV exposure is an important trigger for SLE and it has been proposed that inhibiting VISTA may predispose to exacerbations or de novo development of SLE. 87 Currently anti‐VISTA therapies for cancer are at preclinical or Phase I stages of testing. 88 , 89

5.2. TIM3

TIM3 is an inhibitory molecule that is broadly expressed across immune cells. It has multiple ligands including the alarmin HMGB1. In the presence of cell lysis, for example in the cancer microenvironment, immunogenic nucleic acids are released. TIM3 interacts with HMGB1 to prevent the recruitment of nucleic acids into endosomes, thereby suppressing immune activation. 90 Consistent with this, loss of TIM3 through a germline mutation in HAVCR2 results in the development of antibodies to double stranded DNA, which are usually a specific marker for SLE. 91 Such germline mutations are present in around 60% of cases of subcutaneous panniculitis‐like T‐cell lymphoma, a condition associated with lupus‐like features in around 20% of cases. Reassuringly, phase II trials in metastatic lung cancer have demonstrated a side‐effect profile similar to that of pembrolizumab, although to date the nature of any irAEs, including whether any lupus‐like complications develop, has not been reported. 92 Similarly germline loss of inhibitory TIM3 can result in a severe systemic inflammatory condition called haemophagocytic lymphohistiocytosis (HLH) that can complicate rheumatic diseases such as adult onset Still's disease, but this has not been reported with anti‐TIM3 therapy to date.

5.3. CD40/CD40L

The CD40/CD40L costimulatory pathway is an important checkpoint in both IMRDs and cancer. SNPs in CD40 are associated with the risk of rheumatoid arthritis, SLE, ankylosing spondylitis and Kawasaki disease across multiple GWAS studies. 63 It is expressed by APCs and B cells (among other cell types) and, through interactions with the latter, is important for the generation and maturation of antibody responses through germinal centre formation, isotype switching, and somatic hypermutation. Inhibiting this pathway is an attractive target for RA and the more intractable Sjogren's syndrome, and there are ongoing clinical trials in both. In Sjogren's, treatment with anti‐CD40 therapies have shown initial efficacy with a significant reduction in the GC‐associated chemokine CXCL13. 93

In contrast, CD40 targeting therapies are being employed in cancer because of its role in activation and maturation of DCs. Tumors with minimal T‐cell infiltration are generally resistant to checkpoint immunotherapy, including common tumors of the breast, ovary, and prostate. CD40 agonistic therapies appear to be able to overcome this resistance in murine models 94 and in Phase I trials, neoadjuvant treatment with a CD40 agonist antibody promoted mature DCs and T‐cell infiltration. 95 Surprisingly, given its central role in both cancer and autoimmunity, although data is limited there are no trial reports of malignancy or irAEs to date. 96

6. PERSISTENCE OF RHEUMATIC IRAES

The anti‐tumor immune response induced by checkpoint inhibitors can induce a long‐lasting, durable remission and at higher rates than other systemic therapies. 97 This anti‐tumor response can persist after withdrawal of treatment suggesting a permanent remodeling of the immune response. 98 , 99 Furthermore this response can be long‐lasting; there is evidence that IFNg‐producing tumor‐associated clones persist up to 9 years after cessation of treatment. 100 In this situation a reinvigorated T‐cell response is capable of clearing the tumor and, having been primed, can provide ongoing surveillance to prevent recurrence. Unfortunately this desirable persistent loss of tolerance to the tumor is mirrored by persistent loss of tolerance to self in some irAEs. Mechanistically chronic irAEs can be subdivided into two groups. First, those that are the result of “burnout”, where cells expressing the targeted antigen are effectively ablated. 101 Among rheumatic irAEs and IMRDs, respectively, exocrine gland dysfunction and Sjogren's are examples where irreversible loss or damage or gland function leads to symptoms such as xerostomia that do not respond to immunosuppression. Alternatively both can result in a state of smoldering inflammation where chronic, non‐resolving disease is the norm, such as arthritis. Rates of persistence vary but following treatment with anti‐PD1 around 43% of patients develop a chronic irAE (defined as lasting >12 weeks), with arthritis having one of the highest rates of persistence (49%). 102 Although cessation of ICI treatment can lead to cessation of the irAE, once breach of tolerance has occurred it may persist; recurrence of the same toxicity upon rechallenge is common. 103 , 104 , 105 The factors that influence this balance between a transient, self‐resolving immune response and sustained autoreactivity are pertinent to clinical scenarios such as vaccination and autoimmunity.

Prevention of chronicity of IMRDs is an area of huge clinical interest. Strong evidence suggests early and aggressive anti‐inflammatory treatment improves outcomes and improves the chances of entering remission. 106 Reductions in inflammation can be induced pharmacologically or, in preclinical disease, through interventions such as smoking cessation and weight loss. It remains unclear whether systemic inflammation can influence prognosis with ICI treatment with mixed results, though in some cases suggesting that high basal levels of IL6 and TNF, and their reduction with treatment, correlate with partial or complete response. 107 In agreement with this there is evidence that treatment of irAE‐arthritis with biologic therapies, particularly anti‐TNF therapy, shortens the time to cancer progression, presumably preventing development of robust and persistent memory. 108

7. CONCLUDING REMARKS

We are at an early point in the characterization of rheumatic irAEs, to determine a nomenclature and classification analogous to IMRDs. There remain numerous unanswered questions about their causes, their heterogeneity, and how they relate to IMRDs. It is unclear the extent to which the efficacy of immunotherapy in cancer can be separated from these complications; however, and they are likely to become an increasingly prevalent clinical challenge. They highlight the centrality of immune checkpoints, conserved across species for millions of years of evolution, 109 at the intersection of tolerance and reactivity across the most important challenges in human health. As they develop there will be more shared learning between rheumatic irAEs and IMRDs as they help to shed light on the fundamental mechanisms of tolerance.

CONFLICT OF INTEREST STATEMENT

The authors have no conflict of interest to declare.

ACKNOWLEDGMENTS

The author is funded by Wellcome (WT214539/Z/18/Z) and by the National Institute for Health Research Newcastle Biomedical Research Centre based at Newcastle Hospitals Foundation Trust and Newcastle University. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health.

Reynolds G. Rheumatic complications of checkpoint inhibitors: Lessons from autoimmunity. Immunol Rev. 2023;318:51‐60. doi: 10.1111/imr.13242

This article is part of a series of reviews covering Immune‐Related Adverse Events appearing in Volume 318 of Immunological Reviews.

DATA AVAILABILITY STATEMENT

No data available.

REFERENCES

  • 1. Hodi FS, O'Day SJ, McDermott DF, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med. 2010;363(8):711‐723. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Marin‐Acevedo JA, Kimbrough EO, Lou Y. Next generation of immune checkpoint inhibitors and beyond. J Hematol Oncol. 2021;14(1):45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Martins F, Sofiya L, Sykiotis GP, et al. Adverse effects of immune‐checkpoint inhibitors: epidemiology, management and surveillance. Nat Rev Clin Oncol. 2019;16(9):563‐580. [DOI] [PubMed] [Google Scholar]
  • 4. Villa‐Crespo L, Podlipnik S, Anglada N, et al. Timeline of adverse events during immune checkpoint inhibitors for advanced melanoma and their impacts on survival. Cancers. 2022;14(5):1237. doi: 10.3390/cancers14051237 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Shankar B, Zhang J, Naqash AR, et al. Multisystem immune‐related adverse events associated with immune checkpoint inhibitors for treatment of non–small cell lung cancer. JAMA Oncol. 2020;6(12):1952‐1956. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Cappelli LC, Thomas MA, Bingham CO 3rd, Shah AA, Darrah E. Immune checkpoint inhibitor‐induced inflammatory arthritis as a model of autoimmune arthritis. Immunol Rev. 2020;294(1):106‐123. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Gravallese EM, Firestein GS. Rheumatoid arthritis – common origins, divergent mechanisms. N Engl J Med. 2023;388(6):529‐542. [DOI] [PubMed] [Google Scholar]
  • 8. Bourn R, James JA. Preclinical lupus. Curr Opin Rheumatol. 2015;27(5):433‐439. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Tillett W, Charlton R, Nightingale A, et al. Interval between onset of psoriasis and psoriatic arthritis comparing the UK clinical practice research datalink with a hospital‐based cohort. Rheumatology. 2017;56(12):2109‐2113. doi: 10.1093/rheumatology/kex323 [DOI] [PubMed] [Google Scholar]
  • 10. Ghisoni E, Wicky A, Bouchaab H, et al. Late‐onset and long‐lasting immune‐related adverse events from immune checkpoint‐inhibitors: an overlooked aspect in immunotherapy. Eur J Cancer. 2021;149:153‐164. [DOI] [PubMed] [Google Scholar]
  • 11. Deapen D, Escalante A, Weinrib L, et al. A revised estimate of twin concordance in systemic lupus erythematosus. Arthritis Rheum. 1992;35(3):311‐318. [DOI] [PubMed] [Google Scholar]
  • 12. MacGregor AJ, Snieder H, Rigby AS, et al. Characterizing the quantitative genetic contribution to rheumatoid arthritis using data from twins. Arthritis Rheum. 2000;43(1):30‐37. [DOI] [PubMed] [Google Scholar]
  • 13. Kuo CF, Grainge MJ, Valdes AM, et al. Familial risk of Sjögren's syndrome and co‐aggregation of autoimmune diseases in affected families: a nationwide population study. Arthritis Rheumatol. 2015;67(7):1904‐1912. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Ishigaki K, Sakaue S, Terao C, et al. Multi‐ancestry genome‐wide association analyses identify novel genetic mechanisms in rheumatoid arthritis. Nat Genet. 2022;54(11):1640‐1651. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Serrano NC, Millan P, Páez MC. Non‐HLA associations with autoimmune diseases. Autoimmun Rev. 2006;5(3):209‐214. [DOI] [PubMed] [Google Scholar]
  • 16. Groha S, Alaiwi SA, Xu W, et al. Germline variants associated with toxicity to immune checkpoint blockade. Nat Med. 2022;28(12):2584‐2591. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Chin IS, Khan A, Olsson‐Brown A, Papa S, Middleton G, Palles C. Germline genetic variation and predicting immune checkpoint inhibitor induced toxicity. NPJ Genom Med. 2022;7(1):73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Chennamadhavuni A, Abushahin L, Jin N, Presley CJ, Manne A. Risk factors and biomarkers for immune‐related adverse events: a practical guide to identifying high‐risk patients and rechallenging immune checkpoint inhibitors. Front Immunol. 2022;13:779691. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Leiter A, Carroll E, De Alwis S, et al. Metabolic disease and adverse events from immune checkpoint inhibitors. Eur J Endocrinol. 2021;184(6):857‐865. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Zheng M. Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better. J Immunother Cancer. 2022;10(1):e003087. doi: 10.1136/jitc-2021-003087 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Jardim DL, Goodman A, de Melo Gagliato D, Kurzrock R. The challenges of tumor mutational burden as an immunotherapy biomarker. Cancer Cell. 2021;39(2):154‐173. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. McGranahan N, Furness AJS, Rosenthal R, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016;351(6280):1463‐1469. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Bomze D, Ali OH, Bate A, Flatz L. Association between immune‐related adverse events during anti–PD‐1 therapy and tumor mutational burden. JAMA Oncol. 2019;5(11):1633‐1635. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Wang Y, Wiesnoski DH, Helmink BA, et al. Author correction: fecal microbiota transplantation for refractory immune checkpoint inhibitor‐associated colitis. Nat Med. 2019;25(1):188. [DOI] [PubMed] [Google Scholar]
  • 25. Chen J, Wright K, Davis JM, et al. An expansion of rare lineage intestinal microbes characterizes rheumatoid arthritis. Genome Med. 2016;8(1):43. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Hevia A, Milani C, López P, et al. Intestinal dysbiosis associated with systemic lupus erythematosus. MBio. 2014;5(5):e01548‐14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Scher JU, Ubeda C, Artacho A, et al. Decreased bacterial diversity characterizes the altered gut microbiota in patients with psoriatic arthritis, resembling dysbiosis in inflammatory bowel disease. Arthritis Rheumatol. 2015;67(1):128‐139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Sun B, He X, Zhang W. Findings on the relationship between intestinal microbiome and vasculitis. Front Cell Infect Microbiol. 2022;12:908352. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Vural M, Gilbert B, Üstün I, Caglar S, Finckh A. Mini‐review: human microbiome and rheumatic diseases. Front Cell Infect Microbiol. 2020;10:491160. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. McCulloch JA, Davar D, Rodrigues RR, et al. Intestinal microbiota signatures of clinical response and immune‐related adverse events in melanoma patients treated with anti‐PD‐1. Nat Med. 2022;28(3):545‐556. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Chen Y, Ma C, Liu L, et al. Analysis of gut microbiota and metabolites in patients with rheumatoid arthritis and identification of potential biomarkers. Aging. 2021;13(20):23689‐23701. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Qi Q, Liu Y, Cheng Y, et al. Diversity and clonal selection in the human T‐cell repertoire. Proc Natl Acad Sci USA. 2014;111(36):13139‐13144. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Ferrucci L, Fabbri E. Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty. Nat Rev Cardiol. 2018;15(9):505‐522. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Bouchlaka MN, Sckisel GD, Chen M, et al. Aging predisposes to acute inflammatory induced pathology after tumor immunotherapy. J Exp Med. 2013;210(11):2223‐2237. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Samani A, Zhang S, Spiers L, et al. Impact of age on the toxicity of immune checkpoint inhibition. J Immunother Cancer. 2020;8(2):e000871. doi: 10.1136/jitc-2020-000871 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Merchant MS, Wright M, Baird K, et al. Phase I clinical trial of ipilimumab in pediatric patients with advanced solid tumors pediatric phase I ipilimumab. Clin Cancer Res. 2016;22(6):1364‐1370. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Betof AS, Nipp RD, Giobbie‐Hurder A, et al. Impact of age on outcomes with immunotherapy for patients with melanoma. Oncologist. 2017;22(8):963‐971. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Wang R, Singaraju A, Marks KE, et al. Clonally expanded CD38hi cytotoxic CD8 T cells define the T cell infiltrate in checkpoint inhibitor‐associated arthritis. bioRxiv . 2021. doi: 10.1101/2021.10.19.464961 [DOI] [PMC free article] [PubMed]
  • 39. Kim ST, Chu Y, Misoi M, et al. Distinct molecular and immune hallmarks of inflammatory arthritis induced by immune checkpoint inhibitors for cancer therapy. Nat Commun. 2022;13(1):1970. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Thomas MF, Slowikowski K, Manakongtreecheep K, et al. Altered interactions between circulating and tissue‐resident CD8 T cells with the colonic mucosa define colitis associated with immune checkpoint inhibitors. bioRxiv . 2021. doi: 10.1101/2021.09.17.460868 [DOI]
  • 41. Franken A, Van Mol P, Vanmassenhove S, et al. Single‐cell transcriptomics identifies pathogenic T‐helper 17.1 cells and pro‐inflammatory monocytes in immune checkpoint inhibitor‐related pneumonitis. J Immunother Cancer. 2022;10(9):e005323. doi: 10.1136/jitc-2022-005323 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Pai JA, Chow A, Sauter JL, et al. Regional and clonal T cell dynamics at single cell resolution in immune checkpoint blockade. bioRxiv . 2021. doi: 10.1101/2021.09.27.461389 [DOI]
  • 43. Litchfield K, Reading JL, Puttick C, et al. Meta‐analysis of tumor‐ and T cell‐intrinsic mechanisms of sensitization to checkpoint inhibition. Cell. 2021;184(3):596‐614.e14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Gangaev A, Rozeman EA, Rohaan MW, et al. Differential effects of PD‐1 and CTLA‐4 blockade on the melanoma‐reactive CD8 T cell response. Proc Natl Acad Sci USA. 2021;118(43):e2102849118. doi: 10.1073/pnas.2102849118 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Lu C, Pi X, Xu W, et al. Clinical significance of T cell receptor repertoire in primary Sjogren's syndrome. EBioMedicine. 2022;84:104252. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Martinez‐Taboada VM, Goronzy JJ, Weyand CM. Clonally expanded CD8 T cells in patients with polymyalgia rheumatica and giant cell arteritis. Clin Immunol Immunopathol. 1996;79(3):263‐270. [DOI] [PubMed] [Google Scholar]
  • 47. Waase I, Kayser C, Carlson PJ, Goronzy JJ, Weyand CM. Oligoclonal T cell proliferation in patients with rheumatoid arthritis and their unaffected siblings. Arthritis Rheum. 1996;39(6):904‐913. [DOI] [PubMed] [Google Scholar]
  • 48. Ioan‐Facsinay A, Onnekink C. Epitope spreading of the anti‐citrullinated protein antibody response occurs before disease onset and is associated with the disease course of early arthritis. Ann Rheum Dis. 2010;69:1554‐1561. [DOI] [PubMed] [Google Scholar]
  • 49. Sherer Y, Gorstein A, Fritzler MJ, Shoenfeld Y. Autoantibody explosion in systemic lupus erythematosus: more than 100 different antibodies found in SLE patients. Semin Arthritis Rheum. 2004;34(2):501‐537. [DOI] [PubMed] [Google Scholar]
  • 50. Pipi E, Nayar S, Gardner DH, Colafrancesco S, Smith C, Barone F. Tertiary lymphoid structures: autoimmunity goes local. Front Immunol. 2018;9:1952. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51. Fonseca VR, Romão VC, Agua‐Doce A, et al. The ratio of blood T follicular regulatory cells to T follicular helper cells marks ectopic lymphoid structure formation while activated follicular helper T cells indicate disease activity in primary Sjögren's syndrome. Arthritis Rheumatol. 2018;70(5):774‐784. [DOI] [PubMed] [Google Scholar]
  • 52. Warner BM, Baer AN, Lipson EJ, et al. Sicca syndrome associated with immune checkpoint inhibitor therapy. Oncologist. 2019;24(9):1259‐1269. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. Greenberg SA, Bradshaw EM, Pinkus JL, et al. Plasma cells in muscle in inclusion body myositis and polymyositis. Neurology. 2005;65(11):1782‐1787. [DOI] [PubMed] [Google Scholar]
  • 54. Touat M, Maisonobe T, Knauss S, et al. Immune checkpoint inhibitor‐related myositis and myocarditis in patients with cancer. Neurology. 2018;91(10):e985‐e994. [DOI] [PubMed] [Google Scholar]
  • 55. Laumont CM, Banville AC, Gilardi M, Hollern DP, Nelson BH. Tumour‐infiltrating B cells: immunological mechanisms, clinical impact and therapeutic opportunities. Nat Rev Cancer. 2022;22(7):414‐430. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56. Cronstein BN, Aune TM. Methotrexate and its mechanisms of action in inflammatory arthritis. Nat Rev Rheumatol. 2020;16(3):145‐154. [DOI] [PubMed] [Google Scholar]
  • 57. Braaten TJ, Brahmer JR, Forde PM, et al. Immune checkpoint inhibitor‐induced inflammatory arthritis persists after immunotherapy cessation. Ann Rheum Dis. 2020;79(3):332‐338. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58. Chan KK, Bass AR. Monitoring and management of the patient with immune checkpoint inhibitor‐induced inflammatory arthritis: current perspectives. J Inflamm Res. 2022;15:3105‐3118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59. Kim ST, Tayar J, Trinh VA, et al. Successful treatment of arthritis induced by checkpoint inhibitors with tocilizumab: a case series. Ann Rheum Dis. 2017;76(12):2061‐2064. [DOI] [PubMed] [Google Scholar]
  • 60. Murray K, Floudas A, Murray C, et al. First use of tofacitinib to treat an immune checkpoint inhibitor‐induced arthritis. BMJ Case Rep. 2021;14(2):e238851. doi: 10.1136/bcr-2020-238851 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61. Esfahani K, Miller WH Jr. Reversal of autoimmune toxicity and loss of tumor response by interleukin‐17 blockade. N Engl J Med. 2017;376(20):1989‐1991. [DOI] [PubMed] [Google Scholar]
  • 62. Cappelli LC, Brahmer JR, Forde PM, et al. Clinical presentation of immune checkpoint inhibitor‐induced inflammatory arthritis differs by immunotherapy regimen. Semin Arthritis Rheum. 2018;48(3):553‐557. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63. Sollis E, Mosaku A, Abid A, et al. The NHGRI‐EBI GWAS catalog: knowledgebase and deposition resource. Nucleic Acids Res. 2023;51(D1):D977‐D985. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64. Tivol EA, Borriello F, Schweitzer AN, Lynch WP, Bluestone JA, Sharpe AH. Loss of CTLA‐4 leads to massive lymphoproliferation and fatal multiorgan tissue destruction, revealing a critical negative regulatory role of CTLA‐4. Immunity. 1995;3(5):541‐547. [DOI] [PubMed] [Google Scholar]
  • 65. Arkwright P, Gabrysch A, Olbrich P, et al. Phenotype, penetrance, and treatment of 133 CTLA‐1 4‐insufficient individuals. J Allergy Clin Immunol. 2018;142(6):1932‐1946. doi: 10.1016/j.jaci.2018.02.055 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66. Lévy E, Stolzenberg MC, Bruneau J, et al. LRBA deficiency with autoimmunity and early onset chronic erosive polyarthritis. Clin Immunol. 2016;168:88‐93. [DOI] [PubMed] [Google Scholar]
  • 67. Moreland LW, Alten R, Van den Bosch F. Costimulatory blockade in patients with rheumatoid arthritis: a pilot, dose‐finding, double‐blind, placebo‐controlled clinical trial evaluating CTLA‐4Ig and LEA29Y eighty‐five days after the first infusion. Arthritis Rheum. 2002;46:1470‐1479. doi: 10.1002/art.10294 [DOI] [PubMed] [Google Scholar]
  • 68. Tjärnlund A, Tang Q, Wick C, et al. Abatacept in the treatment of adult dermatomyositis and polymyositis: a randomised, phase IIb treatment delayed‐start trial. Ann Rheum Dis. 2018;77(1):55‐62. [DOI] [PubMed] [Google Scholar]
  • 69. Langford CA, Cuthbertson D, Ytterberg SR, et al. A randomized, double‐blind trial of abatacept (CTLA‐4Ig) for the treatment of giant cell arteritis. Arthritis Rheumatol. 2017;69(4):837‐845. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70. Langford CA, Monach PA, Specks U, et al. An open‐label trial of abatacept (CTLA4‐IG) in non‐severe relapsing granulomatosis with polyangiitis (Wegener's). Ann Rheum Dis. 2014;73(7):1376‐1379. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71. Liu Y, Zheng P. Preserving the CTLA‐4 checkpoint for safer and more effective cancer immunotherapy. Trends Pharmacol Sci. 2020;41(1):4‐12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72. Kvistborg P, Philips D, Kelderman S, et al. Anti‐CTLA‐4 therapy broadens the melanoma‐reactive CD8+ T cell response. Sci Transl Med. 2014;6(254):254ra128. [DOI] [PubMed] [Google Scholar]
  • 73. Kremer J, Westhovens R. Abatacept improves American College of Rheumatology responses and disease activity score 28 remission rates in both recent‐onset and more established rheumatoid arthritis: results from the AIM trial. Arthritis Rheum. 2005;52:S562‐S563. [Google Scholar]
  • 74. Jansen DT, el Bannoudi H, Arens R, et al. Abatacept decreases disease activity in the absence of CD4+ T cells in a collagen‐induced arthritis model. Arthritis Res Ther. 2015;17(1):220. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 75. Emery P, Durez P, Dougados M, et al. Impact of T‐cell costimulation modulation in patients with undifferentiated inflammatory arthritis or very early rheumatoid arthritis: a clinical and imaging study of abatacept (the ADJUST trial). Ann Rheum Dis. 2010;69(3):510‐516. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 76. Emery P, Burmester GR, Bykerk VP, et al. Evaluating drug‐free remission with abatacept in early rheumatoid arthritis: results from the phase 3b, multicentre, randomised, active‐controlled AVERT study of 24 months, with a 12‐month, double‐blind treatment period. Ann Rheum Dis. 2015;74(1):19‐26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 77. Meiners PM, Vissink A, Kroese FGM, et al. Abatacept treatment reduces disease activity in early primary Sjögren's syndrome (open‐label proof of concept ASAP study). Ann Rheum Dis. 2014;73(7):1393‐1396. [DOI] [PubMed] [Google Scholar]
  • 78. Montastruc F, Renoux C, Dell'Aniello S, et al. Abatacept initiation in rheumatoid arthritis and the risk of cancer: a population‐based comparative cohort study. Rheumatology. 2019;58(4):683‐691. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79. Simon TA, Smitten AL, Franklin J, et al. Malignancies in the rheumatoid arthritis abatacept clinical development programme: an epidemiological assessment. Ann Rheum Dis. 2009;68(12):1819‐1826. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 80. de Germay S, Bagheri H, Despas F, Rousseau V, Montastruc F. Abatacept in rheumatoid arthritis and the risk of cancer: a world observational post‐marketing study. Rheumatology. 2020;59(9):2360‐2367. [DOI] [PubMed] [Google Scholar]
  • 81. Alten R, Bingham CO 3rd, Cohen SB, et al. Antibody response to pneumococcal and influenza vaccination in patients with rheumatoid arthritis receiving abatacept. BMC Musculoskelet Disord. 2016;17:231. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82. Chen SK, Liao KP, Liu J, Kim SC. Risk of hospitalized infection and initiation of abatacept versus tumor necrosis factor inhibitors among patients with rheumatoid arthritis: a propensity score‐matched cohort study. Arthritis Care Res. 2020;72(1):9‐17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 83. Richards DM, Ruggiero E, Hofer AC, et al. The contained self‐reactive peripheral T cell repertoire: size, diversity, and cellular composition. J Immunol. 2015;195(5):2067‐2079. [DOI] [PubMed] [Google Scholar]
  • 84. Vaddepally RK, Kharel P, Pandey R, Garje R, Chandra AB. Review of indications of FDA‐approved immune checkpoint inhibitors per NCCN guidelines with the level of evidence. Cancers. 2020;12(3):738. doi: 10.3390/cancers12030738 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 85. Han X, Vesely MD, Yang W, et al. PD‐1H (VISTA)–mediated suppression of autoimmunity in systemic and cutaneous lupus erythematosus. Sci Transl Med. 2019;11(522):eaax1159. [DOI] [PubMed] [Google Scholar]
  • 86. Nishimura H, Nose M, Hiai H, Minato N, Honjo T. Development of lupus‐like autoimmune diseases by disruption of the PD‐1 gene encoding an ITIM motif‐carrying immunoreceptor. Immunity. 1999;11(2):141‐151. [DOI] [PubMed] [Google Scholar]
  • 87. Peters Z, Mendyka L, Shan S, et al. Immune checkpoint VISTA regulates type I interferon (IFN‐I) production and controls UV light triggered skin IFN‐I response. Arthritis Rheumatol. 2022;74:1129‐1130. [Google Scholar]
  • 88. Thakkar D, Paliwal S, Dharmadhikari B, et al. Rationally targeted anti‐VISTA antibody that blockades the C‐C' loop region can reverse VISTA immune suppression and remodel the immune microenvironment to potently inhibit tumor growth in an Fc independent manner. J Immunother Cancer. 2022;10(2):e003382. doi: 10.1136/jitc-2021-003382 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 89. Guillaudeux T, Iadonato S, Tarcha E, Philips C. KVA 12.1 a novel fully human anti‐VISTA antibody: clinical trial design in monotherapy and in combination with an anti‐PD1 antibody. J Immunother Cancer. 2021;9(Suppl 2):268. doi: 10.1136/jitc-2021-SITC2021.268 [DOI] [Google Scholar]
  • 90. Chiba S, Baghdadi M, Akiba H, et al. Tumor‐infiltrating DCs suppress nucleic acid–mediated innate immune responses through interactions between the receptor TIM‐3 and the alarmin HMGB1. Nat Immunol. 2012;13(9):832‐842. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 91. Gayden T, Sepulveda FE, Khuong‐Quang DA, et al. Germline HAVCR2 mutations altering TIM‐3 characterize subcutaneous panniculitis‐like T cell lymphomas with hemophagocytic lymphohistiocytic syndrome. Nat Genet. 2018;50(12):1650‐1657. [DOI] [PubMed] [Google Scholar]
  • 92. Peters S, Lim SM, Granados A. 57O Randomized double‐blind phase II trial (PERLA) of dostarlimab (dostar)+ chemotherapy (CT) vs pembrolizumab (pembro)+ CT in metastatic non‐squamous NSCLC: primary results. Immuno Oncol. 2022;16(Suppl 1):100162. doi: 10.1016/j.iotech.2022.100162 [DOI] [Google Scholar]
  • 93. Fisher BA, Szanto A, Ng WF, et al. Assessment of the anti‐CD40 antibody iscalimab in patients with primary Sjögren's syndrome: a multicentre, randomised, double‐blind, placebo‐controlled, proof‐of‐concept study. Lancet Rheumatol. 2020;2(3):e142‐e152. [DOI] [PubMed] [Google Scholar]
  • 94. Ngiow SF, Young A, Blake SJ, et al. Agonistic CD40 mAb‐driven IL12 reverses resistance to anti‐PD1 in a T‐cell–rich tumor. Cancer Res. 2016;76(21):6266‐6277. [DOI] [PubMed] [Google Scholar]
  • 95. Byrne KT, Betts CB, Mick R, et al. Neoadjuvant selicrelumab, an agonist CD40 antibody, induces changes in the tumor microenvironment in patients with resectable pancreatic cancer. Clin Cancer Res. 2021;27(16):4574‐4586. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 96. Vonderheide RH. CD40 agonist antibodies in cancer immunotherapy. Annu Rev Med. 2020;71:47‐58. [DOI] [PubMed] [Google Scholar]
  • 97. Pons‐Tostivint E, Latouche A, Vaflard P, et al. Comparative analysis of durable responses on immune checkpoint inhibitors versus other systemic therapies: a pooled analysis of phase III trials. JCO Precis Oncol. 2019;3:1‐10. [DOI] [PubMed] [Google Scholar]
  • 98. Jansen YJL, Rozeman EA, Mason R, et al. Discontinuation of anti‐PD‐1 antibody therapy in the absence of disease progression or treatment limiting toxicity: clinical outcomes in advanced melanoma. Ann Oncol. 2019;30(7):1154‐1161. [DOI] [PubMed] [Google Scholar]
  • 99. Robert C, Ribas A, Hamid O, et al. Durable complete response after discontinuation of pembrolizumab in patients with metastatic melanoma. J Clin Oncol. 2018;36(17):1668‐1674. [DOI] [PubMed] [Google Scholar]
  • 100. Han J, Zhao Y, Shirai K, et al. Resident and circulating memory T cells persist for years in melanoma patients with durable responses to immunotherapy. Nat Cancer. 2021;2(3):300‐311. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 101. Johnson DB, Nebhan CA, Moslehi JJ, Balko JM. Immune‐checkpoint inhibitors: long‐term implications of toxicity. Nat Rev Clin Oncol. 2022;19(4):254‐267. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 102. Patrinely JR Jr, Johnson R, Lawless AR, et al. Chronic immune‐related adverse events following adjuvant anti‐PD‐1 therapy for high‐risk resected melanoma. JAMA Oncol. 2021;7(5):744‐748. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 103. Abu‐Sbeih H, Ali FS, Naqash AR, et al. Resumption of immune checkpoint inhibitor therapy after immune‐mediated colitis. J Clin Oncol. 2019;37(30):2738‐2745. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 104. Pollack MH, Betof A, Dearden H, et al. Safety of resuming anti‐PD‐1 in patients with immune‐related adverse events (irAEs) during combined anti‐CTLA‐4 and anti‐PD1 in metastatic melanoma. Ann Oncol. 2018;29(1):250‐255. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 105. Dolladille C, Ederhy S, Sassier M, et al. Immune checkpoint inhibitor rechallenge after immune‐related adverse events in patients with cancer. JAMA Oncol. 2020;6(6):865‐871. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 106. Smolen JS, Breedveld FC, Burmester GR, et al. Treating rheumatoid arthritis to target: 2014 update of the recommendations of an international task force. Ann Rheum Dis. 2016;75(1):3‐15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 107. Wang M, Zhai X, Li J, et al. The role of cytokines in predicting the response and adverse events related to immune checkpoint inhibitors. Front Immunol. 2021;12:670391. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 108. Bass AR, Abdel‐Wahab N, Reid PD, et al. Comparative safety and effectiveness of TNF inhibitors, IL6 inhibitors and methotrexate for the treatment of immune checkpoint inhibitor‐associated arthritis. Ann Rheum Dis. 2023;82:920‐926. doi: 10.1136/ard-2023-223885 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 109. Flies AS, Darby JM, Lennard PR, et al. A novel system to map protein interactions reveals evolutionarily conserved immune evasion pathways on transmissible cancers. Sci Adv. 2020;6(27):eaba5031. doi: 10.1126/sciadv.aba5031 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

No data available.


Articles from Immunological Reviews are provided here courtesy of Wiley

RESOURCES