Human Leukocyte Antigens and Biomarkers in Type 1 Diabetes Mellitus Induced by Immune-Checkpoint Inhibitors

Pathophysiology, diagnosis, and management of immune checkpoint inhibitor-induced diabetes mellitus

Immune Checkpoint Inhibitors (ICIs) have revolutionized cancer treatment, offering hope for patients with various malignancies. However, along with their remarkable anticancer effects, ICIs can also trigger immune-related adverse events (irAEs). One such noteworthy complication is the development of Diabetes Mellitus (DM), which particularly resembles Type 1 Diabetes Mellitus (T1DM). The aim of this review is to provide insights into the epidemiology, pathophysiology, diagnostic issues, and treatment considerations of ICI-induced DM (ICI-DM), emphasizing the importance of early recognition and management to mitigate adverse outcomes. Although still rare, the incidence has increased with the widespread use of ICIs, especially PD-1/PD-L1 blockers (from 0.2% to 1.9%). Factors affecting the development of ICI-DM, such as specific ICIs, patient demographics, and genetic predispositions, are discussed. The complex interplay between immune dysregulation and pancreatic β-cell destruction contributes to diagnostic challenges, with presentations varying from asymptomatic hyperglycemia to diabetic ketoacidosis (DKA). Management strategies prioritize meticulous glycemic and electrolyte regulation along with tailored intravenous insulin therapy in cases of DKA. DM remission is rare, therefore treatment with both long-acting insulin at bedtime and short-acting insulin before meals is needed in longterm. Total daily insulin requirements can be estimated at 0.3-0.4 units/kg/day for most patients as a starting dose.

Durvalumab-induced Type 1 Diabetes in a Patient With Pre-existing GADA-positive Diabetes and Preserved Insulin Secretion

Predicting the onset of type 1 diabetes mellitus (T1D) in patients treated with immune checkpoint inhibitors (ICI) remains challenging. ICI-induced T1D (ICI-T1D) is a rare but serious complication that leads to complete insulin depletion. While diabetes-associated autoantibodies, such as glutamic acid decarboxylase antibodies (GADA), are typically absent in non-ICI-related fulminant T1D, they are relatively common in ICI-T1D. However, it is unclear whether these autoantibodies are detectable before the development of ICI-T1D. We present the case of a 61-year-old man with diabetes who had strongly positive GADA and preserved insulin secretion prior to initiating ICI therapy. Following treatment with durvalumab, he developed ICI-T1D, characterized by complete insulin depletion. Notably, the onset of ICI-T1D was precisely tracked on a daily basis, facilitating the timely initiation of insulin therapy and preventing diabetic ketoacidosis. Although the cost-effectiveness of pretreatment GADA screening and intensive monitoring remains a concern, early detection of diabetes-associated autoantibodies and vigilant glucose monitoring after ICI administration may help predict ICI-T1D and enable early therapeutic intervention.

Immune checkpoint inhibitor-related type 1 diabetes incidence, risk, and survival association

AIM/INTRODUCTION

Although immune checkpoint inhibitor-related type 1 diabetes mellitus (ICI-T1DM) is a rare condition, it is of significant concern globally. We aimed to elucidate the precise incidence, risk factors, and impact of ICI-T1DM on survival outcomes.

MATERIALS AND METHODS

The study is a large retrospective cohort study, performed using the DeSC Japanese administrative claims database comprising 11 million patients. The database population is reportedly similar to the entire population of Japan. Patients administered ICI between 2014 and 2022 were enrolled in the study, including 21,121 patients. The risk factors for ICI-T1DM development and their characteristics were evaluated by logistic regression analysis. Development of a new irAE after the day following the first administration of ICI was set as the study outcome.

RESULTS

ICI-T1DM was observed in 102 (0.48%) of the 21,121 patients after ICI initiation. PD-(L)1 and CTLA-4 combination therapy was associated with an increased risk of ICI-T1DM compared with PD-1 monotherapy (odds ratio [OR], 2.36; 95% confidence interval [CI], 1.21-4.58; P = 0.01). Patients with a prior diagnosis of diabetes mellitus (OR, 1.59; 95% CI, 1.03-2.46; P = 0.04) or hypothyroidism (OR, 2.48; 95% CI, 1.39-4.43; P < 0.01) also exhibited an increased risk of ICI-T1DM. The Kaplan-Meier analysis revealed that patients with ICI-T1DM showed higher survival rates than those without (log-lank test, P < 0.01). Multivariable Cox regression analysis demonstrated that ICI-T1DM development was associated with lower mortality (hazard ratio, 0.60; 95% CI, 0.37-0.99; P = 0.04).

CONCLUSIONS

Collectively, the results of this study demonstrate the precise incidence and risk factors of ICI-T1DM. The development of ICI-T1DM, like other irAEs, is associated with higher survival rates.

Machine-Learning Parsimonious Prediction Model for Diagnostic Screening of Severe Hematological Adverse Events in Cancer Patients Treated with PD-1/PD-L1 Inhibitors: Retrospective Observational Study by Using the Common Data Model

Background/Objectives: Earlier detection of severe immune-related hematological adverse events (irHAEs) in cancer patients treated with a PD-1 or PD-L1 inhibitor is critical to improving treatment outcomes. The study aimed to develop a simple machine learning (ML) model for predicting irHAEs associated with PD-1/PD-L1 inhibitors. Methods: We utilized the Observational Medical Outcomes Partnership-Common Data Model based on electronic medical records from a tertiary (KHMC) and a secondary (KHNMC) hospital in South Korea. Severe irHAEs were defined as Grades 3-5 by the Common Terminology Criteria for Adverse Events (version 5.0). The predictive model was developed using the KHMC dataset, and then cross-validated against an independent cohort (KHNMC). The full ML models were then simplified by selecting critical features based on the feature importance values (FIVs). Results: Overall, 397 and 255 patients were included in the primary (KHMC) and cross-validation (KHNMC) cohort, respectively. Among the tested ML algorithms, random forest achieved the highest accuracy (area under the receiver operating characteristic curve [AUROC] 0.88 for both cohorts). Parsimonious models reduced to 50% FIVs of the full models showed comparable performance to the full models (AUROC 0.83-0.86, p > 0.05). The KHMC and KHNMC parsimonious models shared common predictive features including furosemide, oxygen gas, piperacillin/tazobactam, and acetylcysteine. Conclusions: Considering the simplicity and adequate predictive performance, our simplified ML models might be easily implemented in clinical practice with broad applicability. Our model might enhance early diagnostic screening of irHAEs induced by PD-1/PD-L1 inhibitors, contributing to minimizing the risk of severe irHAEs and improving the effectiveness of cancer immunotherapy.

Immune checkpoint inhibitor-related diabetes mellitus associated with high signal intensity in diffusion-weighted magnetic resonance imaging of the pancreas at an early clinical stage

INTRODUCTION

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment but can give rise to immune-related adverse events such as ICI-related diabetes mellitus (DM).

CASE PRESENTATION

We herein present the case of a 59-year-old Japanese man with malignant melanoma who developed ICI-related DM after 18 months of nivolumab treatment. He experienced marked hyperglycemia and diabetic ketoacidosis without a personal or family history of diabetes. Laboratory findings revealed initial preservation of insulin secretion but a rapid decline in C-peptide levels in the absence of islet autoantibodies. He was therefore diagnosed with ICI-related DM. This case fulfilled the criteria for fulminant type 1 DM but lacked the typical human leukocyte antigen alleles associated with conventional type 1 diabetes. No metastasis or morphological changes were apparent on CT scans of the pancreas, and magnetic resonance cholangiopancreatography did not show dilation or interruption of the main pancreatic duct. However, diffusion-weighted magnetic resonance imaging revealed high signal intensity with low apparent diffusion coefficient values in the pancreas, likely indicative of fibrosis or infiltration of inflammatory cells.

DISCUSSION

This case underscores that ICI-related DM should be considered a potential immune-related adverse event as well as pointing to the benefit of diffusion-weighted imaging for assessment of pancreatic involvement at an early stage of the disease.

HLA investigation in ICI-induced T1D and isolated ACTH deficiency including meta-analysis

OBJECTIVE

Widespread use of immune checkpoint inhibitors (ICIs) in cancer treatment has led to an increase in the number of reported cases of immunotherapy-related endocrinopathies. This study aimed to analyze and compare human leukocyte antigen (HLA) signatures associated with ICI-induced type 1 diabetes (ICI-T1D) and isolated adrenocorticotropic hormone deficiency (ICI-IAD) in patients with both conditions.

METHODS

HLA signatures were examined for their frequencies of occurrence in 22 patients with ICI-T1D without concurrent IAD, including 16 patients from nationwide reports (ICI-T1D group) and 14 patients with ICI-IAD without concurrent T1D (ICI-IAD group). The HLA signatures were also compared for their respective frequencies in 11 patients with ICI-T1D and ICI-IAD, including eight from nationwide reports (ICI-T1D/IAD group).

RESULTS

In the ICI-T1D group, HLA-DRB1*09:01-DQB1*03:03 and DQA1*03:02, which are in linkage disequilibrium with DRB1*09:01-DQB1*03:03 and DRB1*13:02-DQB1*06:04, were susceptible to ICI-T1D, whereas DRB1*15:02-DQB1*06:01 was protective against ICI-T1D. In the ICI-IAD group, DPB1*09:01, C*12:02-B*52:01, and DRB1*15:02-DRB1*06:01, which are in strong linkage disequilibrium, were associated with susceptibility to ICI-IAD. Moreover, DRB1*15:02-DRB1*06:01 was not detected in the ICI-T1D/IAD group.

CONCLUSIONS

This study revealed specific HLA signatures associated with ICI-T1D and ICI-IAD. Moreover, HLA-DRB1*15:02-DRB1*06:01, an ICI-IAD-susceptible HLA haplotype, coincides with the ICI-T1D-protective HLA haplotype, suggesting that the presence of DRB1*15:02-DRB1*06:01 may protect against the co-occurrence of T1D in patients with ICI-IAD.

A case of rapidly progressive insulin-dependent diabetes mellitus without islet autoantibodies developed over two years after the first dose of nivolumab

The case was an 80-year-old Japanese man. He was diagnosed with right renal cell carcinoma when he was 74. After laparoscopic radical nephrectomy, the patient received interferon, sorafenib, axitinib, and nivolumab therapy. The patient developed rapid progressive insulin-dependent diabetes mellitus (DM) after 46 courses of nivolumab monotherapy (772 days from the first nivolumab treatment). Glutamic acid decarboxylase antibody, islet cell cytoplasmic antibody, islet cell antigen-2 antibody, insulin antibody, and zinc transporter 8 antibody were all negative. Human leukocyte antigen (HLA) typing showed DRB1*09:01, DRB1 *13:02, DQB1*03:03, and DQB1 *06:04. Multiple daily insulin injections were started. However, controlling his blood glucose by standard multiple daily insulin injection treatments was difficult. The patient survived more than two years after the onset of immune checkpoint inhibitor-associated DM (ICI-DM). This is a valuable report of late-onset ICI-DM with a detailed patient background and clinical course over two years after the first dose of nivolumab.

Case report: Strong GAD antibody positivity and type 1 diabetes-HLA-susceptible haplotype-DRB1*04:05-DQB1*04:01 in a Japanese patient with immune checkpoint inhibitor-induced type 1 diabetes

Immune checkpoint inhibitors (ICIs) are widely used in cancer treatment; however, they can lead to immune-related adverse events, including immune checkpoint inhibitor-induced type 1 diabetes mellitus (ICI-T1DM). While fulminant T1DM is common in East Asia, ICI-T1DM has predominantly been reported in Western countries. In this report, we present the case of a 66-year-old Japanese man with type 2 diabetes mellitus undergoing dialysis for diabetic nephropathy. The patient was diagnosed with left upper lobe lung cancer, and treatment with nivolumab and ipilimumab was initiated. After 48 days, the patient experienced impaired consciousness and difficulty moving. His blood glucose levels were 815 mg/dL, and metabolic acidosis was detected, leading to a diagnosis of diabetic ketoacidosis. The patient was subsequently treated with continuous intravenous insulin. However, his C-peptide levels rapidly depleted, and new-onset ICI-T1DM was diagnosed. Although most Japanese patients with ICI-T1DM test negative for glutamic acid decarboxylase (GAD) antibodies, this case exhibited a strong positivity. Thus, we reviewed the literature on 15 similar Japanese cases, revealing a mean HbA1c level at onset of 8.7% and a mean time from ICI administration to onset of 9.7 weeks, which was shorter than that in GAD-negative cases. Moreover, human leukocyte antigen typing revealed five cases of DRB1*04:05-DQB1*04:01, including the present case, and one case of DRB1*09:01-DQB1*03:03, both of which were susceptible to T1DM haplotypes. These findings suggest that GAD antibody positivity may be associated with acute onset and disease progression in some cases of Japanese patients with ICI-T1DM. Given that the prediction of new-onset ICI-T1DM is challenging, monitoring GAD antibody levels might be useful. However, further studies with large sample sizes and validation across different racial and ethnic populations are warranted.

Reaching the Diagnosis of Checkpoint Inhibitor-Induced Diabetes Mellitus in Different Clinical Scenarios: A Real-World Application of Updated Diagnostic Criteria

BACKGROUND

Checkpoint inhibitor (CPI)-associated diabetes mellitus (CPI-DM) is a rare immune-related adverse event (irAE) that presents with variable clinical manifestations. Data about its pathogenesis have not yet been adequately studied.

METHODS

Applying the recently updated diagnostic criteria from the American Diabetes Association, we retrospectively reviewed the medical records of all CPI-treated patients referred to our endocrinological unit for managing their endocrine irAEs and analyzed the incidence of CPI-DM, its clinical characteristics, and its management.

RESULTS

Among the 326 CPI-treated patients with endocrine irAEs, 4 patients met the updated criteria for the diagnosis of CPI-DM, representing 1.22% of all endocrine irAEs in our cohort. These four patients presented with distinct clinical scenarios regarding the irAE onset, the underlying malignancy, the administered CPI regimen, and the type of circulating autoantibodies.

CONCLUSION

The variable presentation of CPI-DM and the non-standard sensitivity of the presence of the type 1 DM traditional autoantibodies highlight the need for distinct guidelines and increased awareness of its diagnosis and management.

Review - The impact of pharmacogenetics on the outcome of immune checkpoint inhibitors

The development of immune checkpoint inhibitors (ICIs) has a tremendous effect on the treatment options for multiple types of cancer. Nonetheless, there is a large interpatient variability in response, survival, and the development of immune-related adverse events (irAEs). Pharmacogenetics is the general term for germline genetic variations, which may cause the observed interindividual differences in response or toxicity to treatment. These genetic variations can either be single-nucleotide polymorphisms (SNPs) or structural variants, such as gene deletions, amplifications or rearrangements. For ICIs, pharmacogenetic variation in the human leukocyte antigen molecules has also been studied with regard to treatment outcome. This review presents a summary of the literature regarding the pharmacogenetics of ICI treatment, discusses the most important known genetic variations and offers recommendations on the application of pharmacogenetics for ICI treatment.

Type 1 diabetes mellitus affected by potential toxicity from long-term use of nivolumab

We present a case of type 1 diabetes mellitus (T1DM) that developed in a 53-year-old man after long-term treatment with nivolumab. The patient underwent total gastrectomy for gastric cancer at 40 years of age, and he was started on nivolumab at age 48 years for treatment of a recurrent lesion that proved resistant to standard chemotherapy. Nivolumab treatment resulted in complete response, but, after the 136th infusion of the drug at age 53 years, the patient was hospitalized for sudden onset of diabetic ketoacidosis. He was diagnosed with immune checkpoint inhibitor-induced T1DM (ICI-DM), which developed 1988 days (284 weeks) after initiation of nivolumab. HLA typing revealed disease susceptibility alleles for both fulminant T1DM and ICI-DM. With the increased survival after the ICI treatment, delayed-onset irAEs after long-term use of ICI have been reported; however, delayed-onset ICI-DM remains to be elucidated. This case provides important insight into ICI-DM that develops after prolonged ICI administration, and it suggests that patients should be monitored for ICI-DM regardless of the duration of ICI therapy.

Key Determinants of Immune-Mediated Adverse Reactions to Oncology Drugs

To overcome the epidemiological severity of cancer, developing effective treatments is urgently required. In response, immune checkpoint inhibitors (ICIs) have been revealed as a promising resolution for treatment-resistant cancers across the world. Yet, they have both advantages and disadvantages, bringing therapeutic benefits while simultaneously inducing toxicity, and in particular, immune-mediated adverse drug reactions (imADRs), to the human body. These imADRs can be pathogenic and sometimes lethal, hampering health prediction and monitoring following the provision of ICI treatment. Therefore, it is necessary to collectively identify the determinant factors that contribute to these imADRs induced by ICIs. This article evaluated treatment-, tumor-, and patient-related determinants, and indicated a research gap for future investigations on the pathogenic mechanism of imADRs and translational conversion of determinants into clinical biomarkers to aid pharmacovigilance and cancer therapies.

Autoimmunity in immune checkpoint inhibitor-induced immune-related adverse events: A focus on autoimmune skin toxicity and pneumonitis

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy. However, their use is frequently associated with immune-related adverse events (irAEs) potentially affecting any organ. The mechanisms mediating such irAEs remain poorly understood and biomarkers to predict the development of irAEs are lacking. Growing evidence shows the importance of self-antigens in mediating irAEs during ICI therapy, in particular the well-described melanocyte differentiation antigens in melanoma patients. This review will focus on two novel classes of self-antigens involved in mediating autoimmune skin toxicity and pneumonitis in non-small cell lung cancer patients treated with immunotherapy. T cells specific for these self-antigens are thought to not only mediate irAEs but are thought to simultaneously mediate anti-tumor responses and are therefore associated with both autoimmune toxicity and response to ICI therapy. We further discuss emerging cellular and proteomic immune signatures of irAEs that may serve as biomarkers to help predict which patients are at higher risk of developing these irAEs. The determination of new tumor antigens involved in ICI therapy and the identification of related biomarkers brings us a step forward in the mechanistic understanding of ICIs and will help to monitor patients at higher risk of developing irAEs. Lastly, we discuss the current challenges in collecting research samples for the study of ICI-related mechanisms and in distinguishing between immune signatures of response and those of irAEs.

Clinical characteristics and human leukocyte antigens in patients with immune checkpoint inhibitor-induced type 1 diabetes and pituitary dysfunction: a single center prospective study

PURPOSE

Immune checkpoint inhibitor (ICI) induced type 1 diabetes (T1D) and pituitary dysfunction are life-threatening adverse events, yet there is little clinical data available. We aimed to investigate the clinical characteristics of patients with these adverse events and report their human leukocyte antigen (HLA) profile to determine its relevance.

METHODS

This is a single-center prospective study. We enrolled patients with cancers who were administered ICI and diagnosed as ICI induced T1D (ICI-T1D) and pituitary dysfunction (ICI-PD). Clinical data and extracted DNA from blood samples were collected. HLA typing was performed using next-generation sequencing. We compared our results with those previously reported in healthy controls and investigated the correlation between HLA and the occurrence of ICI-T1D and ICI-PD.

RESULTS

We identified 914 patients treated with ICI in our facility from 1st September, 2017 to 30th June, 2022. Six of these patients developed T1D and 15 developed pituitary dysfunction. The duration from the initiation of ICI treatment to the onset of T1D or pituitary dysfunction averaged 492 ± 196 days and 191 ± 169 days. Among the six patients with T1D, two were positive for anti-GAD antibody. The frequencies of HLA-DR11, -Cw10, -B61, -DRB1*11:01, and -C*03:04 were significantly higher in patients with ICI-T1D than in controls. The frequencies of HLA-DR15 and -DRB*15:02 were significantly higher in patients with ICI-PD than in controls.

CONCLUSION

This study revealed the clinical characteristics of ICI-T1D and ICI-PD and the association between specific HLAs and these adverse events.

A single center case series of immune checkpoint inhibitor-induced type 1 diabetes mellitus, patterns of disease onset and long-term clinical outcome

Background

Type 1 diabetes mellitus (T1DM) is a rare, but serious immune-related adverse event (irAE) of immune checkpoint inhibitors (ICIs). Our goal was to characterize treatment outcomes associated with ICI-induced T1DM through analysis of clinical, immunological and proteomic data.

Methods

This was a single-center case series of patients with solid tumors who received ICIs and subsequently had a new diagnosis of T1DM. ICD codes and C-peptide levels were used to identify patients for chart review to confirm ICI-induced T1DM. Baseline blood specimens were studied for proteomic and immunophenotypic changes.

Results

Between 2011 and 2023, 18 of 3744 patients treated at Huntsman Cancer Institute with ICIs were confirmed to have ICI-induced T1DM (0.48%). Eleven of the 18 patients received anti-PD1 monotherapy, 4 received anti-PD1 plus chemotherapy or targeted therapy, and 3 received ipilimumab plus nivolumab. The mean time to onset was 218 days (range 22-418 days). Patients had sudden elevated serum glucose within 2-3 weeks prior to diagnosis. Sixteen (89%) presented with diabetic ketoacidosis. Three of 12 patients had positive T1DM-associated autoantibodies. All patients with T1DM became insulin-dependent through follow-up. At median follow-up of 21.9 months (range 8.4-82.4), no patients in the melanoma group had progressed or died from disease. In the melanoma group, best responses were 2 complete response and 2 partial response while on active treatment; none in the adjuvant group had disease recurrence. Proteomic analysis of baseline blood suggested low inflammatory (IL-6, OSMR) markers and high metabolic (GLO1, DXCR) markers in ICI-induced T1DM cohort.

Conclusions

Our case series demonstrates rapid onset and irreversibility of ICI-induced T1DM. Melanoma patients with ICI-induced T1DM display excellent clinical response and survival. Limited proteomic data also suggested a unique proteomic profile. Our study helps clinicians to understand the unique clinical presentation and long-term outcomes of this rare irAE for best clinical management.

Amino acid polymorphisms in human histocompatibility leukocyte antigen class II and proinsulin epitope have impacts on type 1 diabetes mellitus induced by immune-checkpoint inhibitors

Introduction

Immune-checkpoint inhibitors are effective in various advanced cancers. Type 1 diabetes mellitus induced by them (ICI-T1DM) is a serious complication requiring prompt insulin treatment, but the immunological mechanism behind it is unclear.

Methods

We examined amino acid polymorphisms in human histocompatibility leukocyte antigen (HLA) molecules and investigated proinsulin epitope binding affinities to HLA molecules.

Results and Discussion

Twelve patients with ICI-T1DM and 35 patients in a control group without ICI-T1DM were enrolled in the study. Allele and haplotype frequencies of HLA-DRB1*04:05, DQB1*04:01, and most importantly DPB1*05:01 were significantly increased in patients with ICI-T1DM. In addition, novel amino acid polymorphisms in HLA-DR (4 polymorphisms), in DQ (12 polymorphisms), and in DP molecules (9 polymorphisms) were identified. These amino acid polymorphisms might be associated with the development of ICI-T1DM. Moreover, novel human proinsulin epitope clusters in insulin A and B chains were discovered in silico and in vitro peptide binding assays to HLA-DP5. In conclusion, significant amino acid polymorphisms in HLA-class II molecules, and conformational alterations in the peptide-binding groove of the HLA-DP molecules were considered likely to influence the immunogenicity of proinsulin epitopes in ICI-T1DM. These amino acid polymorphisms and HLA-DP5 may be predictive genetic factors for ICI-T1DM.

Predictive Biomarkers for Checkpoint Inhibitor Immune-Related Adverse Events

Immune-checkpoint inhibitors (ICIs) are antagonists of inhibitory receptors in the immune system, such as the cytotoxic T-lymphocyte-associated antigen-4, the programmed cell death protein-1 and its ligand PD-L1, and they are increasingly used in cancer treatment. By blocking certain suppressive pathways, ICIs promote T-cell activation and antitumor activity but may induce so-called immune-related adverse events (irAEs), which mimic traditional autoimmune disorders. With the approval of more ICIs, irAE prediction has become a key factor in improving patient survival and quality of life. Several biomarkers have been described as potential irAE predictors, some of them are already available for clinical use and others are under development; examples include circulating blood cell counts and ratios, T-cell expansion and diversification, cytokines, autoantibodies and autoantigens, serum and other biological fluid proteins, human leucocyte antigen genotypes, genetic variations and gene profiles, microRNAs, and the gastrointestinal microbiome. Nevertheless, it is difficult to generalize the application of irAE biomarkers based on the current evidence because most studies have been retrospective, time-limited and restricted to a specific type of cancer, irAE or ICI. Long-term prospective cohorts and real-life studies are needed to assess the predictive capacity of different potential irAE biomarkers, regardless of the ICI type, organ involved or cancer site.

Predictive Biomarkers for Immune-Related Endocrinopathies following Immune Checkpoint Inhibitors Treatment

In recent years, in the context of the increase in the life expectancy of cancer patients, special attention has been given to immunotherapy and, indeed, to immune checkpoint inhibitors. The use of immune checkpoint inhibitors has increased rapidly, and approximately 40% of cancer patients are eligible for this treatment. Although their impact is valuable on cancer treatment, immune checkpoint inhibitors come with side effects, known as immune-related adverse effects. These can affect many systems, including cutaneous, musculoskeletal, cardiovascular, gastrointestinal, endocrine, neural, and pulmonary systems. In this review, we focus on immune-related endocrinopathies that affect around 10% of all treated patients. Endocrine dysfunctions can manifest as hypophysitis, thyroid dysfunction, hypoparathyroidism, insulin-deficient diabetes mellitus, and primary adrenal insufficiency. Currently, there are multiple ongoing clinical trials that aim to identify possible predictive biomarkers for immune-related adverse effects. The design of those clinical trials relies on collecting a variety of biological specimens (tissue biopsy, blood, plasma, saliva, and stool) at baseline and regular intervals during treatment. In this review, we present the predictive biomarkers (such as antibodies, hormones, cytokines, human leukocyte antigens, and eosinophils) that could potentially be utilized in clinical practice in order to predict adverse effects and manage them appropriately.

Risk factors and predictors of immune-related adverse events: implications for patients with non-small cell lung cancer

INTRODUCTION

Immune checkpoint inhibitors (ICI) are now utilized as a standard of care treatment for multiple cancers, including in both the metastatic setting as well as in earlier stages of disease. The identification of unique immune-related adverse events (irAE) that occur during ICI treatment has led to intense research to identify potential risk factors and biomarkers that may assist in clinical decision making. Although initial studies in ICI were primarily in advanced stage disease, the use of ICI in earlier stages of disease as adjuvant therapies requires a better understanding of patient risk stratification to mitigate or prevent serious irAE.

AREAS COVERED

In this review, we set out to describe the current state of research regarding potential risk factors for irAE in patients with non-small cell lung cancer, as well as explore the barriers to understanding irAE. We review data from irAE that occur in large phase 3 trials and prospective studies focusing on irAE, as well as the many retrospective studies that currently form the bulk of our understanding of irAE.

Risk Factors and Biomarkers for Immune-Related Adverse Events: A Practical Guide to Identifying High-Risk Patients and Rechallenging Immune Checkpoint Inhibitors

Immune-related adverse events (irAEs) are a range of complications associated with the use of immune-checkpoint inhibitors (ICIs). Two major classes of ICIs widely used are Cytotoxic T-Lymphocyte Antigen 4 (CTLA4) and Programmed Cell death-1 (PD-1)/Programmed death-ligand 1 (PD-L1) inhibitors. High-grade irAEs are life-threatening and often cause a severe decline in performance status in such that patients do not qualify for any further anticancer treatments. It is difficult to generalize the evidence in the current literature on risk factors or biomarkers for the entire class of ICIs as the studies so far are either disease-specific (e.g., lung cancer or melanoma) or ICI agent-specific (e.g., pembrolizumab, ipilimumab) or irAE-specific (e.g., pneumonitis or gastritis). In this review, risk factors and biomarkers to consider before initiating or monitoring ICI are listed with a practical purpose in day-to-day practice. Risk factors are grouped into demographics and social history, medical history, and medication history, tumor-specific and agent-specific risk factors. A higher risk of irAE is associated with age <60 years, high body mass index, women on CTLA4 and men on PD-1/PD-L1 agents, and chronic smokers. Patients with significant kidney (Stage IV-V), cardiac (heart failure, coronary artery disease, myocardial infarction, hypertension), and lung (asthma, pulmonary fibrosis, and chronic obstructive pulmonary disease) are at a higher risk of respective organ-specific irAEs. Pre-existing autoimmune disease and chronic use of certain drugs (proton pump inhibitors, diuretics, anti-inflammatory drugs) also increase the irAE-risk. Biomarkers are categorized into circulating blood counts, cytokines, autoantibodies, HLA genotypes, microRNA, gene expression profiling, and serum proteins. The blood counts and certain protein markers (albumin and thyroid-stimulating hormone) are readily accessible in current practice. High neutrophil-lymphocyte ratio, eosinophil/monocyte/lymphocyte counts; TSH and troponins at diagnosis and drop in the white count and lymphocyte count can predict irAE. Other biomarkers with limited evidence are cytokines, autoantibodies, HLA genotypes, microRNA, and gene expression profiling. With fast-expanding approvals for ICIs in various cancer types, knowledge on risk factors and biomarkers can help providers assess the irAE-risk of their patients. Prospective disease and agent-specific studies are needed to provide further insight on this essential aspect of ICI therapy.

Flash Glucose Monitoring and Diabetes Mellitus Induced by Immune Checkpoint Inhibitors: An Approach to Clinical Practice

OBJECTIVES

The aim of this study is to investigate in depth diabetes mellitus associated with immune checkpoint inhibitors (DM-ICIs) by analysing a case series. We also evaluated the clinical impact of flash glucose monitoring (FGM) systems in the management of this entity.

METHODS

We conducted an observational cohort study of DM-ICIs diagnosed in two hospitals in Seville (Spain). Patients with a new diagnosis of diabetes mellitus (DM) or with sudden worsening of preexisting DM after starting treatment with ICIs, with a random 5 hour-postprandial C-peptide value of <0.6 nmol/L and without possibility of subsequent withdrawal of insulin treatment, were included.

RESULTS

A total of 7 cases were identified, mostly males (n = 6; 85.7%), with a mean age of 64.9 years. The mean glycated hemoglobin (HbA1c) upon diagnosis was 8.1%, with diabetic ketoacidosis (DKA) observed in 6 cases (85.7%). Subcutaneous flash glucose monitoring (FGM) systems were used in six cases, with a mean follow-up period of 42.7 weeks. During the first 90 days of use, mean average glucose was 167.5 mg/dL, with a coefficient of variation (CV) of 34.6%. The mean time in the range 70-180 mg/dL (TIR) was 59.7%, with a mean time above range (TAR) 181-250 mg/dL of 27.8% and a mean TAR > 250 mg/dL of 10.2%. The mean time below range (TBR) 54-69 mg/dL was 2%, while the mean TBR < 54 mg/dL was 0.3%. The mean glucose management indicator (GMI) was 7.3%. No significant differences were observed in FGM values for the following 90 days of follow-up. A progressive improvement in all parameters of glycaemic control was observed between the first month of FGM use and the sixth month of FGM use. Of note, there was a decrease in mean CV (40.6% to 34.1%, p = 0.25), mean TAR 181-250 (30.3% to 26%, p = 0.49), mean TAR > 250 mg/dL (16.3% to 7.7%, p = 0.09), mean TBR 54-69 mg/dL (5.2% to 2%, p = 0.16), and mean TBR < 54 mg/dL (1.8% to 0.2%, p = 0.31), along with an increase in mean values of TIR 70-180 mg/dL (46.5% to 60.5%, p = 0.09). The lack of statistical significance in the differences observed in the mean FGM values over the follow-up period may be related to the small sample size.

CONCLUSION

DM-ICI is recognised by a state of sudden-onset insulinopenia, often associated with DKA. The use of FGM systems may be a valid option for the effective management of DM-ICIs and for the prevention of severe hyperglycaemic and hypoglycaemic episodes in this condition.