| Literature DB >> 31730012 |
Satya Das1, Douglas B Johnson2.
Abstract
Although immune checkpoint inhibitors (ICIs) have transformed the treatment landscape for patients with many advanced malignancies, only 15-60% of patients respond, leaving a broad swath of patients who do not derive benefit. Identifying biomarkers to optimally identify patients who will benefit from ICIs is a major research focus for the oncology community. Thus far, predictive biomarker research has focused on tumor signatures such as microsatellite instability, programmed death-ligand 1 (PD-L1) expression and tumor mutational burden; clinical biomarkers have been far less studied. One potential clinical biomarker for ICI response in patients is immune-related adverse event (IRAE) onset.IRAEs are thought to represent bystander effects from activated T-cells and it is plausible that patients responding to ICIs would have greater likelihood of autoimmune toxicities (e.g. due to a more competent/treatment-responsive immune system, or cross-reactivity between tumor and host tissue). Earlier studies in melanoma patients however, suggested no association between IRAE onset and anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) antibody efficacy. In contrast, a growing body of literature suggests IRAE onset is predictive of anti-programmed cell death protein 1 (PD-1) and anti-PD-L1 antibody response across a variety of solid tumors. Most of these studies report that patients who experienced IRAEs demonstrate marked improvements in progression-free survival, overall survival and overall response rate compared to those lacking toxicity.Key questions regarding the association between IRAE onset and ICI efficacy remain. The most pertinent of these involve whether the association is only relevant for patients treated with anti-PD-1 and anti-PD-L1 antibodies and whether IRAE site, severity, timing of onset and management influence ICI efficacy. Herein, we discuss the seminal studies which have begun to address these questions and have shaped the narrative about the predictive value of IRAE onset for patients on ICIs, in this review.Entities:
Keywords: Anti-cytotoxic T-lymphocyte-associated protein 4; Anti-programmed cell death protein 1; Anti-programmed death-ligand 1; Autoimmunity and anti-tumor effect; Immune checkpoint inhibitor efficacy; Immune-related adverse events
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Year: 2019 PMID: 31730012 PMCID: PMC6858629 DOI: 10.1186/s40425-019-0805-8
Source DB: PubMed Journal: J Immunother Cancer ISSN: 2051-1426 Impact factor: 13.751
Fig. 1Mechanisms of Response Dependent and Response Independent Autoimmune Toxicity from Immune Checkpoint Inhibitors. On top left is a depiction of myocardial cells expressing shared antigens with the tumor which leads to autoimmunity. On bottom left is a depiction of IL-6 production from T-cell activation resulting in attack on enterocytes. On top right is a depiction of encephalitis as a result of an anti-viral response being unleashed by ICI treatment. On bottom right is a depiction of endogenous CTLA-4 expression on the pituitary gland leading to T-cell attack after anti-CTLA-4 treatment. Abbreviations: APC, antigen presenting cell; TCR, T-cell receptor; CTLA-4, cytotoxic T-lymphocyte-associated protein 4; PD-1, programmed cell death protein 1; PD-L1, programmed death-ligand 1; Ag, antigen; MHC, major histocomptability complex; Pit, pituitary gland
Studies Comparing Outcomes in Advanced Malignancy Patients on Treatment with Anti-Programmed Cell Death Protein 1 (PD-1) and Anti-Programmed Death-Ligand 1 (PD-L1) Antibodies
| Study | Disease | Number of Patients | Checkpoint Inhibitor(s) Used | Survival Endpoints Between Patients With and Without IRAES | Response Endpoints Between Patients With and Without IRAEs |
|---|---|---|---|---|---|
| Grangeon et al. [ | NSCLC | 270 | Anti-PD-1 and anti-PD-L1 | OS (HR 0.29; 95% CI 0.18–0.46; p = .001), PFS (HR 0.42; 95% CI 0.32–0.57; | ORR (22.9% vs 5.7%, |
| Ricciuti et al. [ | NSCLC | 195 | Nivolumab | OS (HR 0.33; 95% CI 0.23–0.47; | ORR (43.5% vs 10%, |
| Riudavets et al. [ | NSCLC, UCC and melanoma | 178 | Nivolumab, pembrolizumab and atezolizumab | OS (37.3 vs 7.8 months, | Not provided |
| Sato et al.a [ | NSCLC | 38 | Nivolumab | PFS (HR 0.1; 95% CI .02–.37; | ORR (63.6% vs 7.4%, |
| Weber et al. [ | Melanoma | 576 | Nivolumab | PFS (no significant differences between either group; HR or | ORR (48.6% vs 17.8%, |
| Indini et al. [ | Melanoma | 173 | Anti-PD-1 | OS (HR 0.39; 95% CI 0.18–0.81; | ORR (HR 1.95; 95% CI 0.91–4.15; |
| Elias et al. [ | RCC | 90 | Anti-PD-1 | OS (HR 0.38; 95% CI 0.18–0.79; p = .01) and TTNT (HR 0.48; 95% CI 0.28–0.83; | Not provided |
| Verzoni et al. [ | RCC | 389 | Nivolumab | OS (HR .57; 95% CI .35–.93; | Not provided |
| Maher et al. [ | UCC | 1747 | Atezolizumab or pembrolizumab | OS (HR 0.53; 95% CI 0.43–0.66) | Not provided |
| Morales-Berera et al. [ | UCC | 52 | Anti-PD-1 or anti-PD-L1 | OS (21.91 vs 6.47 months, | DCR (79% vs 36.3%, |
| Das et al. [ | GI | 61 | Anti-PD-1 monotherapy or in combination | OS (32.4 vs 8.5 months, | Not provided |
| Masuda et al. [ | Gastric | 65 | Nivolumab | OS (HR .17, | Not provided |
| Foster et al. [ | HNSCC | 114 | Anti PD-1 | OS (12.5 vs 6.8 months, | ORR (30.6% vs 12.3%, |
Abbreviations: NSCLC non-small cell lung cancer, UCC urothelial cell carcinoma, RCC renal cell carcinoma, GI gastrointestinal, HNSCC head and neck squamous cell carcinoma, IRAEs immune related adverse events, OS overall survival, PFS progression-free survival, ORR overall response rate, DCR disease control rate, HR hazard ratio, CI confidence interval, TTNT time to next treatment, vs versus
aProspective study