Purpose:

A phase Ib/II clinical trial was conducted to evaluate the safety and efficacy of the combination of all-trans retinoic acid (ATRA) with pembrolizumab in patients with stage IV melanoma.

Patients and Methods:

Anti–PD-1 naïve patients with stage IV melanoma were treated with pembrolizumab plus supplemental ATRA for three days surrounding each of the first four pembrolizumab infusions. The primary objective was to establish the MTD and recommended phase II dose (RP2D) of the combination. The secondary objectives were to describe the safety and toxicity of the combined treatment and to assess antitumor activity in terms of (i) the reduction in circulating myeloid-derived suppressor cell (MDSC) frequency and (ii) progression-free survival (PFS).

Results:

Twenty-four patients were enrolled, 46% diagnosed with M1a and 29% with M1c stage disease at enrollment. All patients had an ECOG status ≤1, and 75% had received no prior therapies. The combination was well tolerated, with the most common ATRA-related adverse events being headache, fatigue, and nausea. The RP2D was established at 150 mg/m2 ATRA + 200 mg Q3W pembrolizumab. Median PFS was 20.3 months, and the overall response rate was 71%, with 50% of patients experiencing a complete response, and the 1-year overall survival was 80%. The combination effectively lowered the frequency of circulating MDSCs.

Conclusions:

With a favorable tolerability and high response rate, this combination is a promising frontline treatment strategy for advanced melanoma. Targeting MDSCs remains an attractive mechanism to enhance the efficacy of immunotherapies, and this combination merits further investigation.

See related commentary by Olson and Luke, p. 1167

This article is featured in Highlights of This Issue, p. 1161

Translational Relevance

Myeloid-derived suppressor cells (MDSC) limit the efficacy of immune checkpoint inhibitors (ICI), including anti–PD-1. We sought to target MDSCs using the differentiating agent all-trans retinoic acid (ATRA) to enhance the efficacy of the anti–PD-1 antibody pembrolizumab in anti–PD-1 naïve patients with stage IV melanoma. In this phase I/II clinical trial, we found that the combination was well tolerated, and the recommended phase II dose was established. The combination effectively lowered the number of circulating MDSCs. The median progression-free survival was 20.3 months. When compared with prior clinical trials with single-agent pembrolizumab, or clinical trials testing combinations of ICIs, the combination of ATRA and pembrolizumab has a favorable overall response rate (ORR) of 71%, with 50% of patients experiencing a complete response. These results provide initial evidence for the safety and efficacy of this approach in the frontline setting for patients with stage IV melanoma.

Although immune checkpoint inhibitors (ICI) have improved the outlook for many patients with melanoma, a significant proportion of patients exhibit resistance to these therapies. A variety of mechanisms have been associated with resistance to ICIs (1). One resistance mechanism of particular interest is the accumulation of a heterogeneous population of immunosuppressive myeloid lineage cells called myeloid-derived suppressor cells (MDSC; refs. 2, 3). MDSCs are potent suppressors of antitumor immunity and represent a significant obstacle to the success of ICI treatment in several cancer types (3, 4). Therefore, overcoming the suppressive activity of MDSCs has the potential to enhance the efficacy of ICIs.

MDSCs diminish the efficacy of ICIs by inhibiting several different mechanisms, including direct cell:cell interactions as well as through the production of immunosuppressive factors (3–6). By secreting high levels of the immunosuppressive cytokines IL10, TGFβ, and generating reactive oxygen species (ROS) MDSCs inhibit antitumor immunity (3–6). In addition, MDSCs secrete arginase-1 (ARG1) and indoleamine 2,3-dioxygenase 1 (IDO1), depleting important nutrients required for effective T-cell functions (3–6). By inhibiting the functions of CD8+ T cells, MDSCs eliminate a highly effective mechanism of antitumor immunity, as CD8+ T cells express the targets of ICIs and are important effectors of ICI activity.

MDSCs are distinguished from other myeloid cells based on the expression of HLA-DR and are characterized by their highly immunosuppressive functions (4, 5). MDSCs can be divided into three subpopulations: Monocytic MDSCs (MO-MDSCs, CD14+CD15), polymorphonuclear-like MDSCs (PMN-MDSCs, CD14CD15+Lox1+), and early MDSCs (eMDSC, CD14CD15; refs. 4, 5). Because of their immature nature, MDSCs are susceptible to modification or reduction by differentiating agents such as all-trans retinoic acid (ATRA; refs. 4, 6, 7). ATRA, a vitamin A derivative, is part of the standard-of-care therapy for acute promyelocytic leukemia. Although the mechanism resulting in ATRA-mediated MDSC differentiation is still under investigation, ATRA has been shown to decrease both the frequency and function of MDSCs through activation of ERK1/2, upregulation of glutathione synthase, and generation of glutathione (7). Increased glutathione production decreases production of ROS and results in subsequent terminal differentiation of MDSCs (7).

In previous clinical trials combining ATRA with a dendritic cell vaccine (8), IL2 (9), or the anti–CTLA-4 ICI ipilimumab (6), ATRA decreased the frequency of circulating MDSCs and improved the antitumor functions of T cells. In addition, our prior clinical trial combining ipilimumab with ATRA found that the 150 mg/m2 dose of ATRA appeared to be safe and well tolerated (6). Thus, in the current clinical trial, we hypothesized that combining ATRA with the anti–PD-1 mAb pembrolizumab, would decrease the frequency of MDSCs and thereby improve the efficacy of pembrolizumab. The timing and initial dose of ATRA in relation to pembrolizumab was determined on the basis of our prior experience with ATRA in similar patient populations (6). The primary objective of this study was to establish the MTD and recommended phase II dose (RP2D) of ATRA in patients with metastatic melanoma treated with pembrolizumab. The secondary objectives were to describe the safety and toxicity of combined treatment with pembrolizumab and ATRA in patients with melanoma and to assess the antitumor activity in terms of (i) the reduction in MDSC frequency and suppressive function in peripheral blood of patients with metastatic melanoma and (ii) progression-free survival (PFS). Further experimental post hoc analyses included overall response rate (ORR), disease control rate (DCR), clinical benefit rate (CBR), PFS at six months (six-month PFS rate), and overall survival (OS).

Study design and patients

This open label, phase I/II clinical trial in 24 patients with stage IV melanoma was conducted at the University of Colorado Cancer Center (ClinicalTrials.gov #NCT03200847). Eligible patients were over the age of 18 and had not been previously treated with anti–PD-1 therapy. Other inclusion/exclusion criteria are listed in Supplementary Table S1. The primary endpoints were to establish the MTD and RP2D and evaluate the effect on MDSCs at RP2D. Secondary endpoints were safety, ORR, DCR, and PFS according to RECIST v1.1.

A fixed dose regimen was selected for this study, 200-mg Q3W pembrolizumab plus the supplemental treatment of 150 mg/m2 ATRA (brand name VESANOID) orally for three days surrounding each of the first four infusions of pembrolizumab (days −1, 0, and +1) for a total of 12 days of ATRA treatment. The dose selected is based on extensive simulations performed using the population pharmacokinetic (PK) model of pembrolizumab showing that the fixed dose of 200 mg every three weeks will provide exposures that (i) are optimally consistent with those obtained with the 2 mg/kg dose every three weeks, (ii) will maintain individual patient exposures in the exposure range established in melanoma as associated with maximal efficacy response, and (iii) will maintain individual patients exposure in the exposure range established in melanoma that is well tolerated and safe. ATRA is a standard treatment for patients with acute promyelocytic leukemia, it has also been used to treat patients with solid tumors. We have selected the dose of ATRA based on two prior clinical trials that combined ATRA with other treatments based on the PK and effects on MDSCs observed in these trials (7, 8).

The study design includes a safety lead in with 12 patients. If there are four or fewer dose-limiting toxicities (DLT; defined in Supplementary Table S3) in the first 12 patients, the dose will be considered as the RP2D, and remaining 12 patients will be accrued to the study to further evaluate the safety of the dose. However, if there are more than four DLTs among the first 12 patients, the dose of ATRA will be de-escalated. In our prior trial combining three days of ATRA (150 mg/m2/d) around administration of ipilimumab, we noted headache as a significant common side effect that resolved with discontinuation of the ATRA (6). The de-escalation design was intended to aim for the effect on MDSC's yet allow for a dose reduction for side effects with the hope of still observing at least some effect on the intended target of MDSC's. The treatment effect of the RP2D on MDSCs will also be evaluated.

The study protocol and all amendments were reviewed and approved by the Colorado Multiple Institutional Review Board (COMIRB #16–1080). The trial was conducted in compliance with the International Conference on Harmonization Good Clinical Practice guidelines and the Declaration of Helsinki. All patients provided written informed consent.

Primary objective

To identify the MTD and RP2D of the combination of pembrolizumab and ATRA.

Secondary objectives

To describe the safety and toxicity of combined treatment with pembrolizumab and ATRA in patients with melanoma. To assess the antitumor activity in terms of (i) the reduction in MDSC frequency and suppressive function (measured as a continuous variable) in peripheral blood of patients with advanced melanoma undergoing pembrolizumab and ATRA combination therapy, (ii) and PFS.

Exploratory objective

To determine the clinical outcomes with tumor-specific T-cell responses.

Procedures

A total of 12 subjects with a cohort size of six were tested during the safety lead in. If more than two subjects experience DLTs within the first six subjects, the next lower dose level of ATRA will be given to the subsequent cohort. If four or fewer subjects experience DLTs among the 12 subjects during the safety lead in, the remaining subjects will continue the same dose level. However, if more than four DLTs occur among the first 12 patients, the dose of ATRA will be de-escalated. A Pocock-type boundary was used to continuously monitor for toxicity (10), where the toxicity probability was set at 25%, and the desired probability of early stopping was set at 0.05. The RP2D was established at 200-mg Q3W pembrolizumab plus the supplemental treatment of 150 mg/m2 ATRA orally for three days surrounding each of the first four infusions of pembrolizumab (days −1, 0, and +1), with patients continuing pembrolizumab for up to two years or until confirmed disease progression or unacceptable toxicity (Fig. 1A). All patients received the RP2D.

Figure 1.

Clinical trial design and efficacy measures. A, Schematic depiction of the treatment and correlative sample collection schedule implemented in this clinical trial. B, Waterfall plot depicting best overall responses (BOR) according to RECIST v1.1 criteria. C, Spider plot depicting changes in target lesion size over time. D, Comparisons of best overall response, overall response rate, and disease control rate. E, Survival curve showing the probability of progression-free survival analyzed using the Kaplan–Meier method, with data censored at first sign of progression, death, or last known follow-up. F, Representative images from CT scans showing responses in the labeled organs.

Figure 1.

Clinical trial design and efficacy measures. A, Schematic depiction of the treatment and correlative sample collection schedule implemented in this clinical trial. B, Waterfall plot depicting best overall responses (BOR) according to RECIST v1.1 criteria. C, Spider plot depicting changes in target lesion size over time. D, Comparisons of best overall response, overall response rate, and disease control rate. E, Survival curve showing the probability of progression-free survival analyzed using the Kaplan–Meier method, with data censored at first sign of progression, death, or last known follow-up. F, Representative images from CT scans showing responses in the labeled organs.

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Assessments

Primary outcome measures included safety assessments. Safety assessments included numbers of patients experiencing DLTs (serious) adverse events, and changes from baseline clinical laboratory parameters. Adverse events were categorized and monitored according to CTCAE v4 guidelines. The secondary objectives were to describe the safety and toxicity of combined treatment with pembrolizumab and ATRA and to assess the antitumor activity in terms of (i) the reduction in circulating MDSCs and (ii) PFS. Exploratory efficacy assessments included: ORR, DCR, CBR, PFS at six months, and OS. Efficacy assessments were measured by standard-of-care clinical imaging, interpreted by a certified radiologist, and verified by the treating physician. Radiologic responses were categorized on the basis of RECISTv1.1 criteria.

Sample collection

Peripheral blood from each patient was collected into tubes containing acid citrate dextrose anticoagulant (BD Biosciences). Research blood draws were performed at four time points: Pre-treatment (0–30 days before the first ATRA administration), draw 2 (day 21), draw 3 (day 63), and post-ATRA treatment (84–130 days), as illustrated in Fig. 1A. Each research blood draw corresponded with standard-of-care clinical blood testing, including complete blood counts with automated differential count.

Flow cytometric analysis of circulating MDSCs

Peripheral blood was collected, and plasma was removed after centrifugation at 340 × g for 10 minutes. Peripheral blood mononuclear cells (PBMC) were isolated by Ficoll (Cytiva) density centrifugation. Freshly isolated PBMCs were stained using the following fluorescently labeled mAbs: APC-Lineage (CD3, CD19, CD20, and CD56), BV570-CD45 (clone HI30, RRID:AB_2563426), BV421-CD11b (clone ICRF44, RRID: AB_11219589), APC-Cy7-CD14 (clone HCD14, RRID: AB_830693), PE-Cy7-CD15 (clone W6D3, RRID: AB_2561670), FITC-CD33 (clone HIM3–4, RRID: AB_314344), PerCP-Cy5.5-HLA-DR (clone L243, RRID: AB_893567), PE-Lox1 (clone 15C4, RRID: AB_2562181; BioLegend). Live/dead discrimination was performed using Zombie Red dye (BioLegend). Stained cells were analyzed using the Beckman Coulter Gallios flow cytometer at the University of Colorado Cancer Center Flow Cytometry Shared Resource. Data were analyzed using FlowJo software Version 10.7 (Treestar, RRID:SCR_008520).

T-cell response assay

PBMCs were isolated as described above and incubated for five hours in the presence of 1 μg/mL of NyESO1, tyrosinase, and gp100 peptide pools (PROIMMUNE) with FITC-anti-CD107a (clone H4A3, BioLegend, RRID: AB_1186036) and 1X Protein Transport Inhibitor (eBioscience) in RPMI-1640 containing 10% FBS (Gemini Bio-Products), 2 mmol/L l-glutamine (Mediatech), 100 μg/mL streptomycin (Mediatech), 100 IU/mL penicillin (Mediatech), 25 mmol/L HEPES (Mediatech). After incubation, the cells were washed and stained with APC-Cy7-CD8 (clone HIT8a, RRID:AB_10613636), PerCP-Cy5.5-CD19 (clone HIB19, RRID:AB_2073119), PerCP-Cy5.5-HLA-DR (clone L243, RRID: AB_893567), and Zombie Red (BioLegend). The cells were then washed, fixed, and permeabilized using the BD Biosciences Cytoperm/Cytofix (AB_2869008) kit per the manufacturer's protocol, and stained with BV421-IFNγ (clone 4S.B3, BioLegend, RRID: AB_2561398). Flow cytometric analysis was performed, and data analyzed as above.

T-cell suppression assay

The suppressive function of MDSCs was determined as previously described (11). Total MDSCs were isolated using stepwise magnetic bead isolation. T cells for stimulation were negatively selected using the Miltenyi Biotec Pan T-Cell Isolation Kit according to the manufacturer's protocol. To purify MDSCs, in a separate aliquot, T cells were first positively selected using CD3 microbeads (Miltenyi Biotec), followed by removal of B cells (CD19 microbeads, Miltenyi Biotec), and NK cells (CD56 microbeads, Miltenyi Biotec). Remaining unlabeled cells were then separated on the basis of HLA-DR (HLA-DR microbeads, Milteny Biotec), with HLA-DR MDSCs and HLA-DR+ mature myeloid cells. All separations were performed on a Miltenyi Biotec AutoMACS Pro separator.

T cells from the pan T-cell isolation kit were first labeled with 5 μmol/L carboxyfluorescein succinimidyl ester (CFSE, Sigma-Aldrich). Labeled T cells were stimulated using plate bound anti-CD3 (clone OKT3, Biolegend, RRID: AB_571927, 5 μg/mL) and soluble anti-CD28 (clone 28.2, BioLegend, AB_314304, 5μg/mL) in complete RPMI as described above in round bottom 96-well plates. T cells were mixed with HLA-DR+ cells or HLA-DR MDSCs at a 1:1 ratio with 105 T cells and 105 of either population of myeloid cells. Unstimulated T cells and stimulated T cells were included as controls.

After 96 hours of incubation, cells were stained with PerCP-Cy5.5 anti-CD3 (Clone SK7, RRID: AB_10640736), Pacific Blue anti-CD4 (clone OKT4, RRID:AB_1595438), APC-Cy7 anti-CD8 (clone HIT8a, RRID: AB_2044006), and Zombie Red from BioLegend. Flow cytometric analysis was analyzed as above. Only samples with sufficient cell numbers to perform this assay with all controls were included in this analysis.

Circulating cytokine analysis

The concentrations of IL1β, IL2, IL4, IL6, IL8, IL10, IL12p70, IL13, TNFα, and IFNγ in the plasma were measured using the V-PLEX Proinflammatory Panel 1 Human Kit (Meso Scale Discovery) according to the manufacturer's protocol. The concentrations of each cytokine were quantified on a QuickPlex SQ 120 instrument (Meso Scale Discovery) located in the Human Immune Monitory Shared Resource at the University of Colorado School of Medicine.

Statistical analysis

The primary goal of this phase I/II study is to characterize the safety and establish the RP2D. The dose selected was based on the PK and effects on MDSCs observed in previous trials (4, 6, 7). A total of 24 evaluable subjects provide a two-sided 95%-exact confidence interval with a width no wider than 0.37 if the true toxicity rate is at most 25%.

The study is powered on the endpoint of MDSCs, as this is the primary rationale for combining ATRA with pembrolizumab. Our previous study showed that the mean reduction of MDSCs was 16.5 with a variance of 121 among four subjects. Because of the small sample size, we assume conservatively that the mean reduction is 70% and the variance is 30% more than the observed values, resulting in a mean reduction of 11.58 and a variance of 157.3. We assume that the response rate of this study is no lower than 50%, thus we will have twelve or more responding subjects among the 24 enrolled. These twelve subjects provide 83% power to detect a mean reduction of 11.58 with a variance of the reduction of 157.3 using a paired t test with a two-sided alpha of 0.05.

Comparison of pre- and post-ATRA treatment data was performed using the Wilcoxon signed-rank test. Comparisons across more than two timepoints were performed using a mixed effects model with Greenhouse–Geisser correction and Dunnet's multiple comparisons test. All statistical tests were performed using GraphPad Prism version 9.2.0 or SAS version 9.4 (RRID:SCR_008567).

Data availability

The datasets used in the current analysis are available from the corresponding authors upon reasonable request.

Patients

A total of 24 patients were enrolled in this prospective, single arm, single institution clinical trial between 10/31/2017 and 07/30/2020 (Table 1). At enrollment, the median age was 66 years (42 – 94), median BMI was 28.5 (19 – 36), and 87% (n = 21) of the patients were male. All patients had an ECOG performance status ≤1, and 17% (n = 4) had elevated lactate dehydrogenase levels on the date of informed consent. Among enrolled patients, 75% (n = 18) had received no previous treatment for melanoma, with 13% (n = 3) receiving prior ipilimumab, 4% (n = 1) receiving prior radiotherapy (brain metastases ∼3 years before enrollment), 8% (n = 2) receiving prior plaque brachytherapy, and none of the patients receiving prior targeted therapy (Table 1). Sixty-seven percent (n = 16) of patients had a cutaneous primary melanoma, 8% (n = 2) had a uveal primary melanoma, 4% (n = 1) had a mucosal primary melanoma, and 21% (n = 5) had an unknown primary melanoma. BRAF V600 mutations were observed in 50% (n = 12) of patients, and NRAS mutations were observed in 20% (n = 5) of patients. The median time from initial melanoma diagnosis to trial screen was 11.5 months (range, 0 – 62 months). At trial screen, the patients had an average of two metastatic sites with the most common sites of metastases being lung (50%, n = 12), lymph node (38%, n = 9), soft tissue (33%, n = 8), and liver (17%, n = 4). At the time of enrollment, the average sum of the longest axis of target lesions for RECIST v1.1 assessment was 51 mm (8 – 163 mm). Follow-up began at the time of enrollment, lasting until death, withdrawal due to enrollment in a different clinical trial, change in treatment, or data cutoff value, with a median duration of follow-up at the time of data cutoff value of 15 months (3 – 35 months), whichever occurred first.

Table 1.

Patient demographics and disease characteristics at baseline.

CharacteristicAll patients (n = 24)
Median age (y; range) 66 (42–94) 
Male sex, n (%) 21 (87) 
Median BMI (range) 28.5 (19–36) 
ECOG performance status, n (%) 
 0 14 (58) 
 1 10 (42) 
Median time from diagnosis to trial screen (mo; range) 11.5 (0–62) 
Median follow-up (mo; range)a 15 (3–34) 
Elevated LDH level, n (%) 4 (17) 
Prior therapies, n (%) 
 Ipilimumab 3 (13) 
 Radiation 1 (4) 
 Plaque brachytherapy 2 (8) 
No prior therapies 18 (75) 
Primary melanoma subtype, n (%) 
 Cutaneous 16 (67) 
 Uveal 2 (8) 
 Mucosal 1 (4) 
 Unknown 5 (21) 
BRAFV600 mutational status, n (%) 
 WT 9 (38%) 
 Mutant 12 (50%) 
 Undetermined 3 (12%) 
Sites of metastasis at trial screen, n (%) 
 Lung 12 (50%) 
 Lymph nodes 9 (38%) 
 Soft tissue 8 (33%) 
 Liver 4 (17%) 
 Adrenal gland 2 (8%) 
 Subcutaneous 2 (8%) 
 Skin 2 (8%) 
 Brain 2 (8%) 
 Breast 1 (4%) 
 Bone 1 (4%) 
M stage, n (%) 
 M1a 11 (46%) 
 M1b 4 (17%) 
 M1c 7 (29% 
 M1d 2 (8%) 
CharacteristicAll patients (n = 24)
Median age (y; range) 66 (42–94) 
Male sex, n (%) 21 (87) 
Median BMI (range) 28.5 (19–36) 
ECOG performance status, n (%) 
 0 14 (58) 
 1 10 (42) 
Median time from diagnosis to trial screen (mo; range) 11.5 (0–62) 
Median follow-up (mo; range)a 15 (3–34) 
Elevated LDH level, n (%) 4 (17) 
Prior therapies, n (%) 
 Ipilimumab 3 (13) 
 Radiation 1 (4) 
 Plaque brachytherapy 2 (8) 
No prior therapies 18 (75) 
Primary melanoma subtype, n (%) 
 Cutaneous 16 (67) 
 Uveal 2 (8) 
 Mucosal 1 (4) 
 Unknown 5 (21) 
BRAFV600 mutational status, n (%) 
 WT 9 (38%) 
 Mutant 12 (50%) 
 Undetermined 3 (12%) 
Sites of metastasis at trial screen, n (%) 
 Lung 12 (50%) 
 Lymph nodes 9 (38%) 
 Soft tissue 8 (33%) 
 Liver 4 (17%) 
 Adrenal gland 2 (8%) 
 Subcutaneous 2 (8%) 
 Skin 2 (8%) 
 Brain 2 (8%) 
 Breast 1 (4%) 
 Bone 1 (4%) 
M stage, n (%) 
 M1a 11 (46%) 
 M1b 4 (17%) 
 M1c 7 (29% 
 M1d 2 (8%) 

aFollow-up was defined as the time from trial enrollment until one of the following: death, withdrawal due to enrollment in a different clinical trial or change in treatment, 2 years after completing treatment (2-year regiment), or data cutoff value, whichever occurred first.

Safety

The mean duration of exposure to treatment was 8 months (2–24 months) from the date of the first dose of ATRA to the off-treatment date. Grade 3 or 4 adverse events that were attributed to pembrolizumab by the investigators occurred in 4 (17%) patients, and grade 3 or 4 events that were attributed to ATRA occurred in 1 (4%) patient (Table 2). The rate of permanent discontinuation of a study drug because of treatment-related adverse events was 25% (n = 6). Four patients (17%) discontinued the study due to pembrolizumab-related side effects; two patients (8%) experienced immune-related (IR) colitis, one patient (4%) experienced IR hepatitis, and one patient (4%) experienced polymyalgia rheumatica-like myalgias, and two patients discontinued the study due to ATRA-related side effects, including intolerable headaches (n = 1, 4%) and stroke (n = 1, 4%).

Table 2.

Most commonly occurring treatment-related adverse events.

PembrolizumabATRA
EventAnyGrade 3 or 4AnyGrade 3 or 4
 Number of patients with event (%) 
Any adverse event 24 (100) 11 (46) 24 (100) 11 (46) 
Treatment-related adverse event 24 (100) 4 (17) 24 (100) 1 (4) 
General disorders 
 Fatigue 16 (67) 1 (4) 11 (46) 
 Decreased appetite 2 (8) 
Eye and nervous system disorders 
 Headache 2 (8) 22 (92) 
 Meningitis/stroke 1 (4) 1 (4) 
Gastrointestinal disorders 
 Nausea 4 (17) 7 (29) 
 Diarrhea 5 (21) 1 (4) 2 (8) 
 Dry mouth 4 (17) 4 (17) 
 Gastroesophageal reflux disease 2 (8) 
Skin and subcutaneous tissue disorders 
 Rash maculopapular 5 (21) 4 (17) 
 Pruritus 2 (8) 
Hepatic disorders 
 Aspartate aminotransferase increased 4 (17) 2 (8) 
 Alanine aminotransferase increased 3 (13) 1 (4) 
Hematologic and lymphatic disorders 
 Anemia 4 (17) 2 (8) 
Endocrine disorders 
 Hypothyroidism 2 (8) 
 Adrenal insufficiency 1 (4) 
PembrolizumabATRA
EventAnyGrade 3 or 4AnyGrade 3 or 4
 Number of patients with event (%) 
Any adverse event 24 (100) 11 (46) 24 (100) 11 (46) 
Treatment-related adverse event 24 (100) 4 (17) 24 (100) 1 (4) 
General disorders 
 Fatigue 16 (67) 1 (4) 11 (46) 
 Decreased appetite 2 (8) 
Eye and nervous system disorders 
 Headache 2 (8) 22 (92) 
 Meningitis/stroke 1 (4) 1 (4) 
Gastrointestinal disorders 
 Nausea 4 (17) 7 (29) 
 Diarrhea 5 (21) 1 (4) 2 (8) 
 Dry mouth 4 (17) 4 (17) 
 Gastroesophageal reflux disease 2 (8) 
Skin and subcutaneous tissue disorders 
 Rash maculopapular 5 (21) 4 (17) 
 Pruritus 2 (8) 
Hepatic disorders 
 Aspartate aminotransferase increased 4 (17) 2 (8) 
 Alanine aminotransferase increased 3 (13) 1 (4) 
Hematologic and lymphatic disorders 
 Anemia 4 (17) 2 (8) 
Endocrine disorders 
 Hypothyroidism 2 (8) 
 Adrenal insufficiency 1 (4) 

Note: All adverse events assessed using CTCAE v.4.

The most common adverse events of any grade likely related to ATRA were headache (n = 22, 92%), fatigue (n = 11, 46%), nausea (n = 7, 29%), vomiting (n = 5, 21%), dry mouth (n = 4, 17%), and dry skin (n = 4, 17%; Table 2). The most common adverse events of any grade likely related to pembrolizumab were fatigue (n = 16, 67%), diarrhea (n = 5, 21%), rash maculo-papular (n = 5, 21%), and dry mouth (n = 4, 17%). Of the events related to ATRA, one patient experienced a grade 4 event, and of the events related to pembrolizumab, all were grade 3 or lower. A full description of all adverse events observed during the study can be found in Supplementary Table S2.

Of the 24 patients in the study, only one patient (4%) experienced a DLT (as defined in Supplementary Table S3) at the dose of 150 mg/m2 ATRA + 200 mg Q3W pembrolizumab. Therefore, this dose was determined to be the RP2D and MTD, and all patients received this dose.

Efficacy

With a median follow-up time of 15 months (3–34 months), the ORR was 71% (n = 17) and the DCR was 88% (n = 21; Figs. 1B and 2D, Table 3). At the time of data cutoff value, the six-month PFS rate for all patients was 63% and the median PFS (calculated from treatment start date to data cutoff value) was 20.3 months (95% CI, 5.2–12.9; Fig. 2E). Using RECIST v1.1 criteria, complete responses (CR) were observed in 50% (n = 12) of patients, partial responses (PR) in 21% (n = 5), stable disease (SD) in 17% (n = 4), and progressive disease (PD) or clinical PD (CPD) observed in 12% (n = 3; Fig. 1B and D).

Figure 2.

The combination of ATRA and pembrolizumab decreases the number of circulating PMN-MDSCs. A, Representative flow cytometric gating strategy to identify and quantify circulating MDSC subsets. B, The suppressive function of MDSCs depicted as a percentage of change in T-cell proliferation from T cells stimulated with anti-CD3/CD28 comparing HLA-DR+ myeloid cells (DR+) with MDSCs. Connecting lines indicate paired analysis from each patient. C, Comparisons of the number of circulating MDSC subsets in pre-treatment (pre-TX) and post-ATRA blood samples, from all patients (pts), responding (R) patients, and non-responding (NR) patients. Connecting lines indicate paired analysis from each patient. D, Summary of the percentage of change from pre- to post-ATRA timepoints in myeloid cell populations. E, Comparisons of number of circulating HLA-DR+ mature myeloid cells in all patients (pts), responding (R) patients, and non-responding (NR) patients. Colored box denotes the time when the patients were being treated with ATRA. *, P < 0.05; **, P < 0.01; ****, P < 0.001. Cycle 2 day 0 (C2D0), cycle 4 day 0 (C4D0).

Figure 2.

The combination of ATRA and pembrolizumab decreases the number of circulating PMN-MDSCs. A, Representative flow cytometric gating strategy to identify and quantify circulating MDSC subsets. B, The suppressive function of MDSCs depicted as a percentage of change in T-cell proliferation from T cells stimulated with anti-CD3/CD28 comparing HLA-DR+ myeloid cells (DR+) with MDSCs. Connecting lines indicate paired analysis from each patient. C, Comparisons of the number of circulating MDSC subsets in pre-treatment (pre-TX) and post-ATRA blood samples, from all patients (pts), responding (R) patients, and non-responding (NR) patients. Connecting lines indicate paired analysis from each patient. D, Summary of the percentage of change from pre- to post-ATRA timepoints in myeloid cell populations. E, Comparisons of number of circulating HLA-DR+ mature myeloid cells in all patients (pts), responding (R) patients, and non-responding (NR) patients. Colored box denotes the time when the patients were being treated with ATRA. *, P < 0.05; **, P < 0.01; ****, P < 0.001. Cycle 2 day 0 (C2D0), cycle 4 day 0 (C4D0).

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Table 3.

Summary of investigator-assessed clinical efficacy parameters.

ParameterAll patients (n = 24)
Best overall response, n (%) 
 Complete response (CR) 12 (50%) 
 Partial response (PR) 5 (21%) 
 Stable disease (SD) 4 (17%) 
 Progressive disease (PD) 2 (8%) 
 Clinical progressive disease (CPD)a 1 (4%) 
Median treatment duration (mo; range)b 8 (2–24) 
Median duration of response (mo; range)c 11 (0.4–34) 
Clinical benefit rate (CBR), n (%)d 14 (58%) 
Objective response rate (ORR), n (%)e 17 (71%) 
Disease control rate (DCR), n (%)f 21 (88%) 
Median follow-up time (mo; range) 15 (3–34) 
Median PFS (mo) 20.3 
6-Month PFS rate, n (%)g 15 (63%) 
Progressive disease (PD)h 12 (50%) 
 On treatmenti 10 (42%) 
  Median time to progression (mo; range) 4 (1–10) 
 Off treatmentj 2 (8%) 
  Median time to progression (mo; range) 15 (9–20) 
Survival rate 75% 
ParameterAll patients (n = 24)
Best overall response, n (%) 
 Complete response (CR) 12 (50%) 
 Partial response (PR) 5 (21%) 
 Stable disease (SD) 4 (17%) 
 Progressive disease (PD) 2 (8%) 
 Clinical progressive disease (CPD)a 1 (4%) 
Median treatment duration (mo; range)b 8 (2–24) 
Median duration of response (mo; range)c 11 (0.4–34) 
Clinical benefit rate (CBR), n (%)d 14 (58%) 
Objective response rate (ORR), n (%)e 17 (71%) 
Disease control rate (DCR), n (%)f 21 (88%) 
Median follow-up time (mo; range) 15 (3–34) 
Median PFS (mo) 20.3 
6-Month PFS rate, n (%)g 15 (63%) 
Progressive disease (PD)h 12 (50%) 
 On treatmenti 10 (42%) 
  Median time to progression (mo; range) 4 (1–10) 
 Off treatmentj 2 (8%) 
  Median time to progression (mo; range) 15 (9–20) 
Survival rate 75% 

Note: Response to therapy was assessed on the basis of RECIST v1.1 criteria.

Abbreviations: CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease; CPD, clinical progressive disease; CBR, clinical benefit rate; ORR, objective response rate; DCR, disease control rate; PFS, progression-free survival.

aProgression without a scan (physician diagnosed progression based on symptoms before scan).

bDefined as time between first ATRA dose and last treatment dose (pembrolizumab or ATRA).

cDefined as measured from the time at which CR or PR criteria are first met until the first date of PD.

dDefined as the proportion of patients demonstrating CR, PR, or SD for a minimum of four months from date of first CR, PR, or SD.

ePatients who achieved a best overall response of CR or PR.

fPatients who achieved a best overall response of CR, PR, or SD.

gPatients without progression at six months from the date of the first treatment.

hPatients diagnosed with PD or CPD.

iPatients who progressed while on treatment.

jPatients who progressed after coming off treatment.

In patients who responded to therapy (CR or PR; n = 17), the median duration of response was 11 months (0.4–34 months; Fig. 1C, and Table 3). At the time of data cutoff value, 12 patients (50%) were still responding to therapy. Overall, 58% (n = 14) had clinical benefit (CR, PR, or SD for a minimum of four months from their initial radiographically demonstrated response) from the combination. Responses to therapy were observed across metastatic sites, including lung, brain (previously untreated), skin, adrenal gland, and lymph nodes (Fig. 1F). Of the 58% (n = 14) of patients that showed clinical benefit, 11 patients had a known driver mutation (BRAF, n = 6; NRAS, n = 4; BRAF+NRAS, n = 1; mutational analysis was unavailable from two patients; Supplementary Table S4). In addition, of patients who showed clinical benefit, 10 were diagnosed with cutaneous primary melanomas, and four were melanomas of unknown primary. Finally, of the patients who showed clinical benefit, 14% (n = 2) received prior ipilimumab monotherapy and 86% (n = 12) received no prior therapies. Alternatively, of the patients who progressed while off treatment (n = 2, 8%), both patients experienced a BOR of SD. Median OS was not reached; however, the OS rate (calculated from treatment start date to data cutoff value) was 71%, with a one-year OS of 80%.

MDSC analysis

MDSCs were identified in PBMCs as CD45+CD3CD19CD56CD11b+CD33+HLA-DR−/low cells (Fig. 2A). There is strong evidence in the literature and from our group showing that this population and its subsets are highly suppressive of T-cell proliferation (3–6, 12–14), and pre-treatment blood samples showed that this was also the case in our patient cohort (Fig. 2B) Paired analysis comparing pretreatment (Pre-TX) with post-ATRA timepoints showed sustained decreases in absolute numbers of circulating total MDSCs (CD45+CD3CD19CD56CD11b+CD33+HLA-DR−/low) four to six weeks after stopping ATRA (Fig. 2C). This was more striking in responding patients (CR or PR; n = 17), where the average percentage of change was −49%, compared with non-responders (SD or PD; n = 6), where the average percentage of change was +110% (P = 0.017; Fig. 2C and D). Although the absolute numbers of PMN-MDSCs were not significantly different when comparing all patients, circulating PMN-MDSCs (CD45+Lox1+CD15+; Fig. 2A) decreased in responding patients (percentage of change −46%), but not in non-responders (percentage of change +427%; P = 0.003; Fig. 2C and D) compared at the Pre-TX and Post-ATRA timepoints. No statistically significant changes were observed in the frequency of MO-MDSCs in either responders or non-responders (Fig. 2C and D).

To assess whether the decrease in MDSC populations was due to ATRA-mediated differentiation into mature HLA-DR+ myeloid cells (6), we measured the frequency of HLA-DR+ myeloid cells (CD45+CD3CD19CD56CD11b+CD33+HLA-DR+; Fig. 2A). We observed a statistically significant increase in HLA-DR+ myeloid cells at the cycle 2 day 0 (C2D0) timepoint (P = 0.008, study day 21) and a trend toward increased levels at the C4D0 timepoint (P = 0.087, study day 63), whereas no differences were observed at the post-ATRA timepoint, when the patients were no longer on ATRA (Fig. 2D). This was driven by increased numbers of HLA-DR+ myeloid cells in the responding but not in the non-responding patients (Fig. 2E).

Multiplex cytokine analysis

To determine whether the decreases in MDSCs were associated with alterations in the concentrations of circulating cytokines, we performed multiplex cytokine analysis. We found that concentrations of IL6 and IL10 were elevated while patients were on ATRA but returned to normal levels after the completion of ATRA treatment (Fig. 3A). IL-12p70 and TNFα were also significantly increased but rose over time and were not associated with ATRA treatment (Fig. 3A). There were no statistically significant differences or trends in the circulating concentrations of the other cytokines measured (IL1B, IL2, IL4, IL8, IL13, and IFNγ; Supplementary Fig. S1A).

Figure 3.

The combination of ATRA and pembrolizumab promotes cytokine production and tumor-specific T-cell activation. A, Analysis of circulating cytokine concentrations. B, Comparisons of the frequency of tumor antigen-specific (NyESO, tyrosinase, and gp100) T cells, identified as CD8+CD107+IFNγ+ T cells. C, Analysis of the number of circulating white blood cell populations from clinical complete blood count (CBC) testing. Colored box denotes the time when the patients were being treated with ATRA. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

Figure 3.

The combination of ATRA and pembrolizumab promotes cytokine production and tumor-specific T-cell activation. A, Analysis of circulating cytokine concentrations. B, Comparisons of the frequency of tumor antigen-specific (NyESO, tyrosinase, and gp100) T cells, identified as CD8+CD107+IFNγ+ T cells. C, Analysis of the number of circulating white blood cell populations from clinical complete blood count (CBC) testing. Colored box denotes the time when the patients were being treated with ATRA. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001.

Close modal

Tumor-specific T-cell analysis

Because we have previously observed that targeting MDSCs with ATRA improves the activation of circulating tumor-specific T cells (6), we compared the frequency of tumor antigen (NY-ESO-1, tyrosinase, gp100)-specific T cells between pre-TX and post-ATRA timepoints in responding versus non-responding patients. We found a trend toward modest increases in antigen specific CD8+ T cells in responding patients but not in non-responding patients (Fig. 3B; Supplementary Fig. S1B).

Other hematologic alterations

As in our previous study (6), ATRA significantly reduced the number of circulating eosinophils (Fig. 3C). This observation was expected as ATRA prevents the differentiation of eosinophil hemopoietic precursors into mature eosinophils by downregulating the expression of the IL5 receptor (15). In addition, we noted a significant increase in the number of circulating neutrophils associated with the timing of ATRA treatment (Fig. 3C). No changes in the number of circulating lymphocytes were noted (Fig. 3C). No other clinically significant changes were noted from the clinical laboratory testing (Supplementary Fig. S2).

Improving ICI-response rates remains an important goal in the immunoncology field. Because MDSCs are an important mediator of resistance to ICIs (3–6), targeting these highly immunosuppressive cells in combination with ICIs is a rational therapeutic combination. In this single arm, single institution clinical trial we found that the combination of ATRA and pembrolizumab was safe and well tolerated. Furthermore, the combination effectively lowers the frequency of circulating MDSCs. This is the first time this combination has been tested in patients with metastatic melanoma, and the encouraging clinical outcomes found, point to the importance of MDSCs in ICI responses and the potential of this combination as an effective first line therapy for patients with metastatic melanoma.

The primary objective of this study was to determine the MTD and RP2D of this combination. These were established to be 150 mg/m2 ATRA + 200-mg Q3W pembrolizumab. Regarding the safety and tolerability of the combination (secondary study objective), we observed that 21% (n = 5) of patients experienced grade 3 or 4 treatment-related adverse events. The most common treatment-related adverse event of any grade was headache (92%, n = 22), which was limited to and corresponded with the three-day course of ATRA treatment. Overall, this combination was well tolerated, with 25% (n = 6) of patients discontinuing treatment due to treatment-related adverse events, a rate similar to that reported for pembrolizumab monotherapy (16). Of note, one patient presented with a complex multifactorial picture of encephalitis complicated by a history of cerebral microangiopathy. The ATRA was discontinued as it was felt that it may have contributed to the onset of their symptoms, which eventually resolved. In addition, one patient elected to discontinue ATRA due to intolerable headache.

The median PFS in this study was 20.3 months (secondary study objective). Further exploratory post hoc analysis showed that the ORR was 71%, with 50% of patients achieving a CR. The responses were durable, with the median duration of response lasting 11 months. These results are notably higher than previously published clinical trials using single-agent pembrolizumab (16). When observed in the context of other currently available immunotherapies in similar patient populations, such as combination ipilimumab (anti–CTLA-4) and nivolumab (anti–PD-1; ref. 17) or relatlimab (anti-Lag3) and nivolumab (18), the favorable safety profile, high response rate, and extended median PFS make this a promising combination therapy in the frontline setting for patients with stage IV melanoma. Although the continued addition of new ICIs to current combinations promotes enhanced immune cell activation, this can have the unintended effect of increasing the risk of treatment-limiting immune-related adverse events. Furthermore, the use of ATRA may particularly benefit patients with high frequencies of MDSCs who may be more prone to ICI-resistance. Therefore, targeting the multiple immunosuppressive functions of MDSCs using this approach offers the potential for improved responses while decreasing the risk of treatment limiting and often life altering autoimmune toxicities.

Although we noted high response rates in both cutaneous and melanomas of unknown primary, the combination was less effective in patients diagnosed with rare melanoma subtypes (uveal or mucosal). Uveal melanomas are noted for their low ICI response rates, with low mutational burden and predisposition for liver metastasis making them particularly difficult to treat (19–21). However, it is important to clearly state that the current study was not powered to compare response rates across melanoma subtype or metastatic sites, and larger clinical trials specifically designed to test these hypotheses will be required to make final conclusions.

Targeting MDSCs is an attractive way to enhance the efficacy of ICIs, with few significant side effects (22–25). In the present study, we found that the combination of ATRA and pembrolizumab effectively reduced the frequency of total MDSCs, mainly driven by a significant reduction in circulating PMN-MDSCs (secondary study objective). This was more apparent in patients who responded to the therapy than those who did not. The PMN-MDSC population is highly immunosuppressive and plays an important role in ICI resistance (4, 26). We did not observe statistically significant changes in the frequency of circulating MO-MDSCs. This may be due to the changes in MO-MDSCs being more observable in the tumor microenvironment (13). However, as the present study did not include tumor biopsies, this hypothesis will be tested in future studies. The decrease in circulating MDSCs corresponded with an increase in HLA-DR+ myeloid cells during the ATRA treatment portion of the study. Pre-treatment levels of these cells have previously been observed to strongly correlate with responses to ICIs (27). ATRA may increase their frequency, promoting antitumor immunity as proposed in this prior study (27).

The levels of several circulating cytokines have been associated with differential clinical outcomes in patients with metastatic melanoma (12, 28, 29). Although the changes we observed were modest, the levels of circulating IL6 and IL10 increased during the time when patients were on ATRA and returned to near baseline levels during the pembrolizumab monotherapy portion of the study. We also observed consistent, but small, increases in the concentrations of IL-12p70 and TNFα that remained elevated after ATRA completion. These cytokines have mixed associations with responses to ICIs reported in the literature. IL6 and IL10 in particular can be associated with both positive and negative outcomes (12, 28–30). Our previous work suggests that high levels of IL6 are associated with MDSC accumulation (12). However, other results show that changes in IL6 levels can be associated with positive clinical outcomes (31). Likewise, although IL10 is an immunosuppressive cytokine produced by MDSCs (4), high levels of IL10 have been correlated with positive ICI responses and clinical outcomes (30, 32). Separate previous reports have found that ATRA can induce IL6 (33) and IL10 (34) expression in multiple cell types involved in antitumor immunity, limiting our ability to determine the source of these cytokines in the circulation of these patients. The mechanisms by which this combination may alter the expression and circulating concentrations of these cytokines and the cell types that are producing them, merits further investigation.

In addition to its effects on MDSCs, ATRA has been shown to activate the innate immune-sensing pathway in several types of tumor cells, including melanoma (35). In addition, activation of the innate immune-sensing pathway can induce the expression of many cytokines, including IL6, IL10, IL12, and TNFα (36, 37) that we found to be increased in the circulation of the patients in this study. Although the current study was not designed to analyze this pathway, it is possible that the dual action of targeting MDSCs and inducing a more immunogenic tumor microenvironment may account for the high response rates in this patient cohort. Future studies that include on treatment tumor biopsies will be required to test this hypothesis.

Overall, this pilot study demonstrates that the combination of ATRA and pembrolizumab appears to be a promising approach to enhance the efficacy of anti–PD-1 and further supports the role of MDSCs in preventing effective antitumor immunity. Several new therapies designed to target tumor-induced MDSCs are currently entering clinical trials (38–40). These include therapies that induce MDSC differentiation (39), target MDSC chemotaxis (38), and those that target the suppressive functions of MDSCs (IL10, TGFβ, Arg1, and IDO1; refs. 40–42). In addition, a recent study found that adding radiotherapy to ATRA and anti–PD-1 therapy may be an effective mechanism to further induce the differentiation of MDSCs toward a pro-inflammatory, antitumor myeloid cell phenotype (43).

Several study limitations were noted. First, this is a single-arm study lacking pembrolizumab monotherapy as a control, limiting the investigators’ ability to analyze the contributions of each compound to clinical responses or the correlative analyses (Supplementary Table S5). Of note, previous studies have observed reductions in circulating MDSCs in patients treated with single-agent anti–PD-1 (44–46). Second, the low numbers of patients from a single institution and relatively short follow-up time limit the generalizability to the larger melanoma population. Furthermore, most patients in the current study had a low disease burden, received few prior treatments, and none had previously received anti–PD-1 therapies, possibly accounting for the high ORR and CR rates. Future studies will include more heavily pretreated patients and patients from multiple institutions to test the generalizability of these results. In addition, there are many previously reported limitations in the RECIST v1.1 criteria used to measure clinical responses (47, 48). Some of these limitations may account for some of high response rates observed in this study. Although the current proof-of-principal study only had sufficient funding to treat patients with ATRA during the first four cycles of pembrolizumab, future studies will extend the treatment duration. Finally, although the study was originally intended to investigate changes in MDSC-suppressive functions at each investigational timepoint, the decrease in overall MDSC numbers limited our ability to perform the T-cell suppression assays at the timepoints indicated in our clinical trial protocol. Future studies will include later blood draw timepoints to assess the repopulation and functional status of circulating MDSCs following discontinuation of ATRA.

R.P. Tobin reports grants from Merck and Co. Inc. during the conduct of the study. T.M. Medina reports other support from Merck during the conduct of the study. K.D. Lewis reports grants and personal fees from Merck and Roche during the conduct of the study as well as grants and personal fees from Regeneron and grants from Iovance, Ultimavacs, and Array outside the submitted work. M.D. McCarter reports grants from Merck during the conduct of the study. No disclosures were reported by the other authors.

R.P. Tobin: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, validation, investigation, visualization, methodology, writing–original draft, project administration, writing–review and editing. D.T. Cogswell: Data curation, investigation, visualization, writing–original draft, writing–review and editing. V.M. Cates: Data curation, investigation, writing–original draft, writing–review and editing. D.M. Davis: Data curation, investigation, writing–original draft, writing–review and editing. J.S.W. Borgers: Validation, visualization, writing–original draft, writing–review and editing. R.J. Van Gulick: Resources, data curation, writing–original draft, writing–review and editing. E. Katsnelson: Validation, visualization, writing–original draft, writing–review and editing. K.L. Couts: Resources, validation, methodology, writing–original draft, writing–review and editing. K.R. Jordan: Conceptualization, methodology, writing–original draft, writing–review and editing. D. Gao: Conceptualization, data curation, formal analysis, validation, writing–original draft, writing–review and editing. E. Davila: Validation, writing–original draft, writing–review and editing. T.M. Medina: Resources, data curation, formal analysis, validation, writing–original draft, writing–review and editing. K.D. Lewis: Resources, data curation, formal analysis, validation, writing–original draft, writing–review and editing. R. Gonzalez: Resources, data curation, validation, writing–original draft, writing–review and editing. R.W. McFarland: Resources, data curation, formal analysis, validation, writing–original draft, writing–review and editing. W.A. Robinson: Conceptualization, resources, data curation, formal analysis, validation, writing–original draft, writing–review and editing. M.D. McCarter: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, validation, visualization, methodology, writing–original draft, project administration, writing–review and editing.

This study (ClinicalTrials.gov # NCT03200847) was funded by Merck & Co Inc. (MISP 54054; to M.D. McCarter). Further funding support was provided to the University of Colorado Cancer Center under NCI Cancer Center support grant P30CA046934. We are grateful to the patients and their families for their participation in the study; the funders; and all investigators and their teams who participated in the trial.

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

1.
Morrison
C
,
Pabla
S
,
Conroy
JM
,
Nesline
MK
,
Glenn
ST
,
Dressman
D
, et al
.
Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
.
J Immunother Cancer
2018
;
6
:
32
.
2.
Tobin
RP
,
Davis
D
,
Jordan
KR
,
McCarter
MD
.
The clinical evidence for targeting human myeloid-derived suppressor cells in cancer patients
.
J Leukoc Biol
2017
;
102
:
381
91
.
3.
Weber
R
,
Fleming
V
,
Hu
X
,
Nagibin
V
,
Groth
C
,
Altevogt
P
, et al
.
Myeloid-derived suppressor cells hinder the anticancer activity of immune checkpoint inhibitors
.
Front Immunol
2018
;
9
:
1310
.
4.
Veglia
F
,
Sanseviero
E
,
Gabrilovich
DI
.
Myeloid-derived suppressor cells in the era of increasing myeloid cell diversity
.
Nat Rev Immunol
2021
;
21
:
485
98
.
5.
Groth
C
,
Hu
X
,
Weber
R
,
Fleming
V
,
Altevogt
P
,
Utikal
J
, et al
.
Immunosuppression mediated by myeloid-derived suppressor cells (MDSCs) during tumour progression
.
Br J Cancer
2019
;
120
:
16
25
.
6.
Tobin
RP
,
Jordan
KR
,
Robinson
WA
,
Davis
D
,
Borges
VF
,
Gonzalez
R
, et al
.
Targeting myeloid-derived suppressor cells using all-trans retinoic acid in melanoma patients treated with Ipilimumab
.
Int Immunopharmacol
2018
;
63
:
282
91
.
7.
Nefedova
Y
,
Fishman
M
,
Sherman
S
,
Wang
X
,
Beg
AA
,
Gabrilovich
DI
.
Mechanism of all-trans retinoic acid effect on tumor-associated myeloid-derived suppressor cells
.
Cancer Res
2007
;
67
:
11021
8
.
8.
Iclozan
C
,
Antonia
S
,
Chiappori
A
,
Chen
DT
,
Gabrilovich
D
.
Therapeutic regulation of myeloid-derived suppressor cells and immune response to cancer vaccine in patients with extensive stage small cell lung cancer
.
Cancer Immunol Immunother
2013
;
62
:
909
18
.
9.
Mirza
N
,
Fishman
M
,
Fricke
I
,
Dunn
M
,
Neuger
AM
,
Frost
TJ
, et al
.
All-trans-retinoic acid improves differentiation of myeloid cells and immune response in cancer patients
.
Cancer Res
2006
;
66
:
9299
307
.
10.
Ivanova
A
,
Qaqish
BF
,
Schell
MJ
.
Continuous toxicity monitoring in phase II trials in oncology
.
Biometrics
2005
;
61
:
540
5
.
11.
Davis
RJ
,
Silvin
C
,
Allen
CT
.
Avoiding phagocytosis-related artifact in myeloid-derived suppressor cell T-lymphocyte suppression assays
.
J Immunol Methods
2017
;
440
:
12
8
.
12.
Tobin
RP
,
Jordan
KR
,
Kapoor
P
,
Spongberg
E
,
Davis
D
,
Vorwald
VM
, et al
.
IL6 and IL8 are linked with myeloid-derived suppressor cell accumulation and correlate with poor clinical outcomes in melanoma patients
.
Front Oncol
2019
;
9
:
1223
.
13.
Tcyganov
E
,
Mastio
J
,
Chen
E
,
Gabrilovich
DI
.
Plasticity of myeloid-derived suppressor cells in cancer
.
Curr Opin Immunol
2018
;
51
:
76
82
.
14.
Bronte
V
,
Brandau
S
,
Chen
SH
,
Colombo
MP
,
Frey
AB
,
Greten
TF
, et al
.
Recommendations for myeloid-derived suppressor cell nomenclature and characterization standards
.
Nat Commun
2016
;
7
:
12150
.
15.
Upham
JW
,
Sehmi
R
,
Hayes
LM
,
Howie
K
,
Lundahl
J
,
Denburg
JA
.
Retinoic acid modulates IL5 receptor expression and selectively inhibits eosinophil–basophil differentiation of hemopoietic progenitor cells
.
J Allergy Clin Immunol
2002
;
109
:
307
13
.
16.
Hamid
O
,
Robert
C
,
Daud
A
,
Hodi
FS
,
Hwu
WJ
,
Kefford
R
, et al
.
Five-year survival outcomes for patients with advanced melanoma treated with pembrolizumab in KEYNOTE-001
.
Ann Oncol
2019
;
30
:
582
8
.
17.
Hodi
FS
,
Chesney
J
,
Pavlick
AC
,
Robert
C
,
Grossmann
KF
,
McDermott
DF
, et al
.
Combined nivolumab and ipilimumab versus ipilimumab alone in patients with advanced melanoma: 2-year overall survival outcomes in a multicentre, randomised, controlled, phase 2 trial
.
Lancet Oncol
2016
;
17
:
1558
68
.
18.
Tawbi
HA
,
Schadendorf
D
,
Lipson
EJ
,
Ascierto
PA
,
Matamala
L
,
Castillo
Gutierrez E
, et al
.
Relatlimab and nivolumab versus nivolumab in untreated advanced melanoma
.
N Engl J Med
2022
;
386
:
24
34
.
19.
Algazi
AP
,
Tsai
KK
,
Shoushtari
AN
,
Munhoz
RR
,
Eroglu
Z
,
Piulats
JM
, et al
.
Clinical outcomes in metastatic uveal melanoma treated with PD-1 and PD-L1 antibodies
.
Cancer
2016
;
122
:
3344
53
.
20.
Bol
KF
,
Ellebaek
E
,
Hoejberg
L
,
Bagger
MM
,
Larsen
MS
,
Klausen
TW
, et al
.
Real-world impact of immune checkpoint inhibitors in metastatic uveal melanoma
.
Cancers
2019
;
11
:
1489
.
21.
Chua
V
,
Mattei
J
,
Han
A
,
Johnston
L
,
LiPira
K
,
Selig
SM
, et al
.
The latest on uveal melanoma research and clinical trials: updates from the cure ocular melanoma (CURE OM) science meeting (2019)
.
Clin Cancer Res
2021
;
27
:
28
33
.
22.
Sarhan
D
,
Cichocki
F
,
Zhang
B
,
Yingst
A
,
Spellman
SR
,
Cooley
S
, et al
.
Adaptive NK cells with low TIGIT expression are inherently resistant to myeloid-derived suppressor cells
.
Cancer Res
2016
;
76
:
5696
706
.
23.
Limagne
E
,
Richard
C
,
Thibaudin
M
,
Fumet
JD
,
Truntzer
C
,
Lagrange
A
, et al
.
Tim-3/galectin-9 pathway and mMDSC control primary and secondary resistances to PD-1 blockade in lung cancer patients
.
Oncoimmunology
2019
;
8
:
e1564505
.
24.
Bae
J
,
Accardi
F
,
Hideshima
T
,
Tai
YT
,
Prabhala
R
,
Shambley
A
, et al
.
Targeting LAG3/GAL-3 to overcome immunosuppression and enhance antitumor immune responses in multiple myeloma
.
Leukemia
2021
;
36
:
138
54
.
25.
Murciano-Goroff
YR
,
Warner
AB
,
Wolchok
JD
.
The future of cancer immunotherapy: microenvironment-targeting combinations
.
Cell Res
2020
;
30
:
507
19
.
26.
Condamine
T
,
Dominguez
GA
,
Youn
JI
,
Kossenkov
AV
,
Mony
S
,
Alicea-Torres
K
, et al
.
Lectin-type oxidized LDL receptor-1 distinguishes population of human polymorphonuclear myeloid-derived suppressor cells in cancer patients
.
Sci Immunol
2016
;
1
:
aaf8943
.
27.
Krieg
C
,
Nowicka
M
,
Guglietta
S
,
Schindler
S
,
Hartmann
FJ
,
Weber
LM
, et al
.
High-dimensional single-cell analysis predicts response to anti–PD-1 immunotherapy
.
Nat Med
2018
;
24
:
144
53
.
28.
Laino
AS
,
Woods
D
,
Vassallo
M
,
Qian
X
,
Tang
H
,
Wind-Rotolo
M
, et al
.
Serum interleukin-6 and C-reactive protein are associated with survival in melanoma patients receiving immune checkpoint inhibition
.
J Immunother Cancer
2020
;
8
:
e000842
.
29.
Berraondo
P
,
Sanmamed
MF
,
Ochoa
MC
,
Etxeberria
I
,
Aznar
MA
,
Perez-Gracia
JL
, et al
.
Cytokines in clinical cancer immunotherapy
.
Br J Cancer
2019
;
120
:
6
15
.
30.
Oft
M
.
IL10: master switch from tumor-promoting inflammation to antitumor immunity
.
Cancer Immunol Res
2014
;
2
:
194
9
.
31.
Reitter
EM
,
Ay
C
,
Kaider
A
,
Pirker
R
,
Zielinski
C
,
Zlabinger
G
, et al
.
Interleukin levels and their potential association with venous thromboembolism and survival in cancer patients
.
Clin Exp Immunol
2014
;
177
:
253
60
.
32.
Yamazaki
N
,
Kiyohara
Y
,
Uhara
H
,
Iizuka
H
,
Uehara
J
,
Otsuka
F
, et al
.
Cytokine biomarkers to predict antitumor responses to nivolumab suggested in a phase 2 study for advanced melanoma
.
Cancer Sci
2017
;
108
:
1022
31
.
33.
Alatshan
A
,
Kovacs
GE
,
Aladdin
A
,
Czimmerer
Z
,
Tar
K
,
Benko
S
.
All-trans retinoic acid enhances both the signaling for priming and the glycolysis for activation of NLRP3 inflammasome in human macrophage
.
Cells
2020
;
9
:
1591
.
34.
Wang
X
,
Allen
C
,
Ballow
M
.
Retinoic acid enhances the production of IL10 while reducing the synthesis of IL12 and TNF-alpha from LPS-stimulated monocytes/macrophages
.
J Clin Immunol
2007
;
27
:
193
200
.
35.
Bolis
M
,
Paroni
G
,
Fratelli
M
,
Vallerga
A
,
Guarrera
L
,
Zanetti
A
, et al
.
All-trans retinoic acid stimulates viral mimicry, interferon responses, and antigen presentation in breast-cancer cells
.
Cancers
2020
;
12
:
1169
.
36.
Duewell
P
,
Steger
A
,
Lohr
H
,
Bourhis
H
,
Hoelz
H
,
Kirchleitner
SV
, et al
.
RIG-I-like helicases induce immunogenic cell death of pancreatic cancer cells and sensitize tumors toward killing by CD8(+) T cells
.
Cell Death Differ
2014
;
21
:
1825
37
.
37.
Heidegger
S
,
Wintges
A
,
Stritzke
F
,
Bek
S
,
Steiger
K
,
Koenig
PA
, et al
.
RIG-I activation is critical for responsiveness to checkpoint blockade
.
Sci Immunol
2019
;
4
:
eaau8943
.
38.
Bilusic
M
,
Heery
CR
,
Collins
JM
,
Donahue
RN
,
Palena
C
,
Madan
RA
, et al
.
Phase I trial of HuMax-IL8 (BMS-986253), an anti–IL-8 monoclonal antibody, in patients with metastatic or unresectable solid tumors
.
J Immunother Cancer
2019
;
7
:
240
.
39.
Sharma
MD
,
Rodriguez
PC
,
Koehn
BH
,
Baban
B
,
Cui
Y
,
Guo
G
, et al
.
Activation of p53 in immature myeloid precursor cells controls differentiation into Ly6c(+)CD103(+) monocytic antigen-presenting cells in tumors
.
Immunity
2018
;
48
:
91
106
.
40.
Ciardiello
D
,
Elez
E
,
Tabernero
J
,
Seoane
J
.
Clinical development of therapies targeting TGFbeta: current knowledge and future perspectives
.
Ann Oncol
2020
;
31
:
1336
49
.
41.
Tang
K
,
Wu
YH
,
Song
Y
,
Yu
B
.
Indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors in clinical trials for cancer immunotherapy
.
J Hematol Oncol
2021
;
14
:
68
.
42.
Steggerda
SM
,
Bennett
MK
,
Chen
J
,
Emberley
E
,
Huang
T
,
Janes
JR
, et al
.
Inhibition of arginase by CB-1158 blocks myeloid cell-mediated immune suppression in the tumor microenvironment
.
J Immunother Cancer
2017
;
5
:
101
.
43.
Rao
E
,
Hou
Y
,
Huang
X
,
Wang
L
,
Wang
J
,
Zheng
W
, et al
.
All-trans retinoic acid overcomes solid tumor radioresistance by inducing inflammatory macrophages
.
Science Immunology
2021
;
6
:
eaba8426
.
44.
Pico de Coana
Y
,
Wolodarski
M
,
van der Haar Avila
I
,
Nakajima
T
,
Rentouli
S
,
Lundqvist
A
, et al
.
PD-1 checkpoint blockade in advanced melanoma patients: NK cells, monocytic subsets and host PD-L1 expression as predictive biomarker candidates
.
Oncoimmunology
2020
;
9
:
1786888
.
45.
Sun
SH
,
Benner
B
,
Savardekar
H
,
Lapurga
G
,
Good
L
,
Abood
D
, et al
.
Effect of immune checkpoint blockade on myeloid-derived suppressor cell populations in patients with melanoma
.
Front Immunol
2021
;
12
:
740890
.
46.
Weber
J
,
Gibney
G
,
Kudchadkar
R
,
Yu
B
,
Cheng
P
,
Martinez
AJ
, et al
.
Phase I/II study of metastatic melanoma patients treated with nivolumab who had progressed after ipilimumab
.
Cancer Immunol Res
2016
;
4
:
345
53
.
47.
Grimaldi
S
,
Terroir
M
,
Caramella
C
.
Advances in oncological treatment: limitations of RECIST 1.1 criteria
.
Q J Nucl Med Mol Imaging
2018
;
62
:
129
39
.
48.
Shafiei
A
,
Bagheri
M
,
Farhadi
F
,
Apolo
AB
,
Biassou
NM
,
Folio
LR
, et al
.
CT evaluation of lymph nodes that merge or split during the course of a clinical trial: limitations of RECIST 1.1
.
Radiol Imaging Cancer
2021
;
3
:
e200090
.