IL-10 Signaling Elicited by Nivolumab-Induced Activation of the MAP Kinase Pathway Does Not Fully Contribute to Nivolumab-Modulated Heterogeneous T Cell Responses.

Immune checkpoint inhibitor (ICI) therapy has revolutionized anti-cancer treatment for many late-stage cancer patients. However, ICI therapy has thus far demonstrated limited efficacy for most patients, and it remains unclear why this is so. Interleukin 10 (IL-10) is a cytokine that has been recognized as a central player in cancer biology with its ability to inhibit anti-tumor T cell responses. Recent studies suggest that IL-10 might also exert some intrinsic anti-tumor T cell responses, and clinical studies using recombinant IL-10 alone or in combination with ICI are underway. This paradoxical effect of IL-10 and its underlying mechanisms impacting ICI-modulated T cell responses remain poorly understood. In this study, using an in vitro mixed lymphocyte reaction assay, we found that treatment with ICIs such as the anti-programmed cell death receptor-1 (PD-1) mAb nivolumab elicits a strong expression of IL-10. While neutralization of IL-10 signaling with an anti-IL-10 specific mAb significantly decreases the production of IFN-γ by T cells in a cohort of donor cells, the opposite effect was observed in other donor cells. Similarly, neutralization of IL-10 signaling significantly decreases the expression of T cell activation markers Ki67 and CD25, as well as the production of Granzyme B in a cohort of donor cells, whereas the opposite effect was observed in others. Furthermore, we found that nivolumab and IL-10 differentially modulate the signal transducer and activator of transcription 3 (STAT3) and AKT serine-threonine kinase pathways. Finally, we found that nivolumab activates the mitogen-activated protein kinase (MAPK) pathway, which in turn is responsible for the observed induction of IL-10 production by nivolumab. These findings provide new insights into the mechanisms underlying anti-PD-1-modulated T cell responses by IL-10, which could lead to the discovery of novel combination treatments that target IL-10 and immune checkpoint molecules.

Exploring the Potential Use of a PBMC-Based Functional Assay to Identify Predictive Biomarkers for Anti-PD-1 Immunotherapy.

The absence of reliable, robust, and non-invasive biomarkers for anti- Programmed cell death protein 1 (PD-1) immunotherapy is an urgent unmet medical need for the treatment of cancer patients. No predictive biomarkers have been established based on the direct assessment of T cell functions, the primary mechanism of action of anti-PD-1 therapy. In this study, we established a model system to test T cell functions modulated by Nivolumab using anti-CD3 monoclonal antibody (mAb)-stimulated peripheral blood mononuclear cells (PBMCs), and characterized T cell functions primarily based on the knowledge gained from retrospective observations of patients treated with anti-PD-1 immunotherapy. During a comprehensive cytokine profile assessment to identify potential biomarkers, we found that Nivolumab increases expression of T helper type 1 (Th1) associated cytokines such as interferon-γ (IFN-γ) and interleukin-2 (IL-2) in a subset of donors. Furthermore, Nivolumab increases production of Th2, Th9, and Th17 associated cytokines, as well as many proinflammatory cytokines such as IL-6 in a subset of donors. Conversely, Nivolumab treatment has no impact on T cell proliferation, expression of CD25, CD69, or Granzyme B, and only modestly increases in the expansion of regulatory T cells. Our results suggest that assessment of cytokine production using a simple PBMC-based T cell functional assay could be used as a potential predictive marker for anti-PD-1 immunotherapy.

Validity and power considerations on hypothesis testing under minimization.

Minimization, a dynamic allocation method, is gaining popularity especially in cancer clinical trials. Aiming to achieve balance on all important prognostic factors simultaneously, this procedure can lead to a substantial reduction in covariate imbalance compared with conventional randomization in small clinical trials. While minimization has generated enthusiasm, some controversy exists over the proper analysis of such a trial. Critics argue that standard testing methods that do not account for the dynamic allocation algorithm can lead to invalid statistical inference. Acknowledging this limitation, the International Conference on Harmonization E9 guideline suggests that 'the complexity of the logistics and potential impact on analyses be carefully evaluated when considering dynamic allocation'. In this article, we investigate the proper analysis approaches to inference in a minimization design for both continuous and time-to-event endpoints and evaluate the validity and power of these approaches under a variety of scenarios both theoretically and empirically. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Summary of US Food and Drug Administration Chimeric Antigen Receptor (CAR) T-Cell Biologics License Application Approvals From a Statistical Perspective.

The approval of tisagenlecleucel and axicabtagene ciloleucel in 2017 marked a milestone in the development of oncology therapies. Since 2017, the breakthrough in treatment or even cure of previously intractable diseases represented by this new class of cancer treatments has continued with subsequent chimeric antigen receptor T (CAR T)-cell approvals. To date, the US Food and Drug Administration has approved five autologous CAR T-cell products for seven indications. A feature of autologous CAR T-cell products that differentiates them from traditional oncology drugs is that they need to be manufactured specifically for each patient. This feature has implications in study design, statistical analyses, and interpretation of study results. In this article, we share our experiences in the statistical review of CAR T-cell products and provide considerations for the design and statistical analyses of CAR T-cell trials. We also describe how the newly adopted estimand framework for clinical trials can help clarify nuanced issues in CAR T-cell trial design.

Graphical Analyses in the Regulatory Evaluation of Gene Therapy Applications.

The Center for Biologics Evaluation and Research (CBER) at the US Food and Drug Administration (FDA) regulates gene therapies, among other products. The approval of four gene therapy products since 2017 represents a significant milestone for a new class of treatments with the potential to treat or cure diseases, particularly rare diseases, that were previously considered incurable. Several factors have contributed to the recent rapid development of gene therapies including advances in genetics to facilitate target-detection, advances in vectors, and regulatory incentives such as breakthrough therapy designation, priority review and market exclusivity. The patient population affected by a rare disease is typically small, heterogeneous and geographically dispersed. As a result, clinical trials on a rare disease have unique features in terms of study design, subject enrollment, data analyses and interpretation of study results. Given that the patient population affected is small for rare diseases, providing substantial evidence of effectiveness and evidence of safety in trials for rare disease presents challenges. In this paper, we share our experiences in the statistical review of three gene therapy products that have been approved by FDA CBER. Our motivation in writing this paper is to encourage the use of appropriate analysis strategies for other similar small trials, with a focus on data visualization strategies.

Missing data handling methods in medical device clinical trials.

One of the major problems in the analysis of clinical trials is missing data caused by patients dropping out before study completion. The issue of missing data can result in biased treatment comparisons and can impact the interpretation of study results. Since the missing data mechanism is unknown and unverifiable in most situations, regulatory agencies often request various sensitivity analyses for handling missing data to evaluate the robustness of study results. This article discusses methods used to handle missing data in medical device clinical trials, focusing on tipping-point analysis as a general approach for the assessment of missing data impact. Tipping points are outcomes that result in a change of study conclusion. Such outcomes can be conveyed to clinical reviewers to determine if they are implausibly unfavorable. The analysis aids clinical reviewers in making judgment regarding treatment effect in the study. Three examples with a reasonably representative range of missing data rate are included to illustrate the methods referred.

FDA Approval Summary: Axicabtagene Ciloleucel for Relapsed or Refractory Large B-cell Lymphoma.

In October 2017, the FDA granted regular approval to axicabtagene ciloleucel, a CD19-directed chimeric antigen receptor (CAR) T-cell therapy, for treatment of adult patients with relapsed or refractory large B-cell lymphoma after two or more lines of systemic therapy. Efficacy was based on complete remission (CR) rate and duration of response (DOR) in 101 adult patients with relapsed or refractory large B-cell lymphoma (median 3 prior systemic regimens) treated on a single-arm trial. Patients received a single infusion of axicabtagene ciloleucel, preceded by lymphodepleting chemotherapy with cyclophosphamide and fludarabine. The objective response rate per independent review committee was 72% [95% confidence interval (CI), 62-81], with a CR rate of 51% (95% CI, 41-62). With a median follow-up of 7.9 months, the median DOR was not reached in patients achieving CR (95% CI, 8.1 months; not estimable, NE), whereas patients with partial remission had an estimated median DOR of 2.1 months (95% CI, 1.3-5.3). Among 108 patients evaluated for safety, serious adverse reactions occurred in 52%. Cytokine release syndrome and neurologic toxicities occurred in 94% and 87% of patients, respectively, leading to implementation of a risk evaluation and mitigation strategy.

FDA Approval Summary: Tisagenlecleucel for Treatment of Patients with Relapsed or Refractory B-cell Precursor Acute Lymphoblastic Leukemia.

Tisagenlecleucel (Kymriah; Novartis Pharmaceuticals) is a CD19-directed genetically modified autologous T-cell immunotherapy. On August 30, 2017, the FDA approved tisagenlecleucel for treatment of patients up to 25 years of age with B-cell precursor acute lymphoblastic leukemia (ALL) that is refractory in second or later relapse. Approval was based on the complete remission (CR) rate, durability of CR, and minimal residual disease (MRD) <0.01% in a cohort of 63 children and young adults with relapsed or refractory ALL treated on a single-arm trial (CCTL019B2202). Treatment consisted of fludarabine and cyclophosphamide followed 2 to 14 days later by a single dose of tisagenlecleucel. The CR rate was 63% (95% confidence interval, 50%-75%), and all CRs had MRD <0.01%. With a median follow-up of 4.8 months, the median duration of response was not reached. Cytokine release syndrome (79%) and neurologic events (65%) were serious toxicities reported in the trial. With implementation of a Risk Evaluation and Mitigation Strategy, the benefit-risk profile was considered acceptable for this patient population with such resistant ALL. A study of safety with 15 years of follow-up is required as a condition of the approval.See related commentary by Geyer, p. 1133.

BRAF and MEK inhibitors differentially affect nivolumab-induced T cell activation by modulating the TCR and AKT signaling pathways.

Immune checkpoint inhibitors (ICIs) such as the anti-PD-1 antibody Nivolumab, achieve remarkable clinical efficacy in patients with late stage cancers. However, only a small subset of patients benefit from this therapy. Numerous clinical trials are underway testing whether combining ICIs with other anti-cancer therapies can increase this response rate. For example, anti-PD-1/PD-L1 therapy combined with MAP kinase inhibition using BRAF inhibitors (BRAFi) and/or MEK inhibitors (MEKi) are in development for treatment of late stage melanomas. However, the benefits and underlying mechanisms of these combinatorial therapies remain unclear. In the current study, we assess the effects of MAPK inhibition on Nivolumab-induced T cell responses. Using an in vitro mixed lymphocyte reaction assay, we demonstrate that Nivolumab-induced T cell activation is highly heterogeneous. While BRAFi inhibits Nivolumab-induced cytokine production, T cell proliferation, activation markers (CD69, CD25), and Granzyme B in a substantial proportion of donor pairs, a small subset of donor pairs shows an additive effect. MEKi alone significantly inhibits Nivolumab-induced T cell activation; the addition of BRAFi significantly enhances this inhibitory effect. Mechanistically, the effects of BRAFi and/or MEKi on Nivolumab-induced T cell activation may be due to alteration of the activation of the AKT and T cell receptor (TCR) signaling pathways. Our results suggest that MAPK inhibition may not provide a clinical benefit for most melanoma patients being treated with anti-PD-1 therapy.

CBER's Experience With Adaptive Design Clinical Trials.

There is considerable interest among pharmaceutical and other medical product developers in adaptive clinical trials, in which knowledge learned during the course of a trial affects ongoing conduct or analysis of the trial. When the FDA released a draft Guidance document on adaptive design clinical trials in early 2010, expectations were high that it would lead to an increase in regulatory submissions involving adaptive design features, particularly for confirmatory trials. A 6-year (2008-2013) retrospective survey was performed within the Center for Biologics Evaluation and Research (CBER) at the FDA to gather information regarding the submission and evaluation of adaptive design trial proposals. We present an up-to-date summary of adaptive design proposals seen in CBER and provide an overview of our experiences. We share our concerns regarding the statistical issues and operational challenges raised during the review process for adaptive design trials. We also provide general recommendations for developing proposals for such trials. Our motivation in writing this paper was to encourage the best study design proposals to be submitted to CBER. Sometimes these can be adaptive, and sometimes a simpler design is most efficient.

Mixed noninferiority margin and statistical tests in active controlled trials.

In an active controlled noninferiority trial without a placebo arm, one of the major considerations is the selection of the noninferiority margin. Although the ICH E10 guideline provides general principles for the selection of appropriate noninferiority margins, there are no established rules or gold standards for the selection of noninferiority margins in active control trials. Hung et al. (2003) proposed a margin selection based on relative risk. However, with relative risk, it is difficult to adjust for covariates. On the other hand, Chow and Shao (2006) proposed a method for selecting noninferiority margins based on treatment difference. The determination of noninferiority margin based on either a test for treatment difference or a test for relative risk would be critical. In this paper, we propose a method for noninferiority testing with the use of a mixed null hypothesis. The mixed null hypothesis consists of a margin based on treatment difference and a margin based on relative risk. Both noninferiority margins will simultaneously satisfy the principles as described in the ICH E10 guideline. Statistical tests for mixed noninferiority margin are also derived. An example concerning the efficacy of a test therapy to an active control on a clinical adverse event in the target patient population with cardiovascular disease is presented to illustrate the proposed method. Simulation studies were also conducted to assess the type I error rate and the power.