ReviewImmune checkpoint inhibitors and diabetes: Mechanisms and predictors
Section snippets
PD-1/PD-L1 inhibitors: the breakthrough and the glitch
Immune checkpoint inhibitors (CPI) include inhibitors for PD-1 and its ligand (PD-L1) [14], [15], [16], [17], [18]. PD-1 is normally expressed on the surface of activated T-cells enabling them to interact with PD-L1 and other receptors on the surface of antigen-presenting cells as well as tumour cells [19]. This interaction will result in the neutralization of T-cells and unresponsiveness. The neutralization of T-cells will render them unresponsive towards tumour cells allowing them to evade
Role of immunity in diabetes: the sabotaging traitor
Immunity plays a key role in the pathogenesis of diabetes. Both T1D and T2D are supported by improper host immune response. T1D is precipitated due to improper insulin secretion by pancreatic β-cells because of its T cell-mediated destruction [22]. The second arm of the immune system i.e. B cells are also involved in this process through the secretion of autoantibodies. There are 4 main autoantibodies involved in the destruction of β-cells and the development of T1D namely Islet Cell Antibodies
T1D as an adverse effect for checkpoint inhibitors: the hint
Although clinical trials of PD-1 and PD-L1 inhibitors showed very promising therapeutic potentials as anti-tumours, they revealed immune-related adverse effects disturbing the metabolic homeostasis [27], [28]. One of the adverse effects that has been reported from animal and clinical studies is T1D [29], [30], [31]. Although diabetes development secondary to CPI is not very common (0.9% in the 6 year period examined by Stamatouli et al. 2018), however, this number is still considered clinically
PD-1/PD-L1 in type 1 diabetes: A researcher and mouse game
Given the importance of highlighting the cellular and molecular mechanisms behind the onset of secondary type 1 diabetes observed with immune checkpoint inhibition, several experimental animal models were developed. The mechanism behind T1D development as a secondary result to immune checkpoint inhibition, is thought to be the same as the antitumor mechanism of these therapeutic agents [27]. A finding that makes it extremely difficult to avoid diabetic ketoacidosis onset with the use of
The genetics story
The susceptibility to secondary T1D can be deduced by genotyping, with the largest influence imparted by the HLA genotype. It has been shown that patients heterozygous for the MHC I HLA loci show better outcomes when treated with immune checkpoint inhibitors [52]. Similarly, spontaneous T1D is associated with HLA-DR4, DR3, DQ2 and DQ8 genotypes. From these, HLA-DR4 genotype was shown to be the predominant genotype in T1D as a CPI adverse effect as it was present in 42% of the patients (χ2 test,
Biomarkers for secondary insulin dependent diabetes: the tattletales
In an effort to discover biomarkers for the high risk group for predisposition to T1D when treated with CPI, a recent clinical study has reported an association between T1D and elevated levels of circulating peripheral T helper cells (Tph) that are negative for CXC motif chemokine receptor type 5 and positive for programmed cell death protein 1-positive (CXCR5−PD-1hi). This was found both before and following the diagnosis of T1D [63]. The Tph CXCR5−PD-1hi cells can be used as a biomarker for
CPIs and type 2 diabetes: two for the price of one
It is intuitive that CPI are associated with several autoimmune disorders including T1D because they are involved in immune regulation. However, the incidence of T1D tempted researchers to investigate if CPI can predispose T2D as well. In a retrospective study, Gauci et al. reported occurrence of type 1 and type 2 diabetes in patients treated with PD-1 and CTLA-4 inhibitors [27], [66]. Their study included all the patients that attended the Oncodermatology clinics of Saint Louis Hospital in
Conclusion
Immune checkpoint inhibitors are being used in combinations to give a better antitumor effects, however, a combination therapy might be associated with a higher risk of autoimmune diabetes development [32]. While the incidence of diabetes is a rare side effects for CPI monotherapy, CPIs are usually used in combinations which increases the incidence of this adverse effect. This fact underscores the importance of the identification of biomarkers that can predict the susceptibility of certain
Author contributions
NY and MN performed the literature review and wrote the manuscript. GD helped in the revision of the review. AAE conceived and designed the review article. All authors approved the final version of the review.
Role of the funding source
This content is solely the responsibility of the authors. The funding sources had no involvement in any aspect of the research.
Conflict of interest
None.
Acknowledgments
NY and MN are supported by a doctoral fellowship from the American University of Beirut, Faculty of Medicine. AAE is supported by the American University of Beirut Medical Practice Plan regular research grant.
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The Authors Equally Contributed to the Write-Up of this Review Manuscript.