Neoadjuvant Pembrolizumab and High-Dose IFNα-2b in Resectable Regionally Advanced Melanoma

Adjuvant therapy with immune checkpoint inhibitors (ICI) is now standard of care in resected stage III or IV melanoma, and targeted therapy (TT) is an alternative option for patients with a BRAF V600E/K mutation (1, 2). Neoadjuvant therapy may provide several advantages: debulking of disease prior to surgery, earlier treatment of micrometastases, and tissue analysis at time of surgery to correlate treatment response with potential biomarkers. Furthermore, phase I and II studies suggest that neoadjuvant therapy is safe, does not lead to development of unresectable disease or delays in definitive surgical management, and is potentially superior or at least noninferior to adjuvant therapy in regards to relapse-free survival (RFS), including in patients with in-transit metastases (3–14).

Pathologic complete response (pCR), defined as the absence of viable tumor cells by histologic examination, is associated with reduced recurrence and increased overall survival (OS) in breast cancer (15). Furthermore, it is increasingly accepted as a significant prognostic marker in melanoma (6, 16–22). In a pooled analysis of 184 patients treated with neoadjuvant ICI (n = 133) or TT (n = 51), none of the patients with a pCR following ICI recurred at a median follow-up of 10 months (5).

Multiple immunotherapy agents, including combinations, have been evaluated in the neoadjuvant setting. Neoadjuvant pembrolizumab resulted in a 30% complete or near complete (<10% viable tumor) pathologic response rate after a single treatment dose (8). Paired administration of PD-1/PD-L1 axis blockers with CTLA-4 inhibitors has been shown to improve pCR (45% vs. 25%) but at the cost of significantly increased toxicity [73% vs. 8% treatment-related adverse events (trAE; ref. 12)]. Alternative ICI neoadjuvant dosing regimens adopting a reduced dose of ipilimumab while increasing the dose of nivolumab have sought to minimize toxicity while maintaining pathologic response (4).

There is evidence that ICI and IFNα, which engage multiple immune compartments, may also improve response rates (9, 23–25). In the adjuvant setting, high-dose IFNα has been shown to improve both RFS and OS (26, 27). IFNα enhances class I expression (28) and directly activates innate and adaptive immune responses, including CD4⁺ T, CD8⁺ T cells, and natural killer cells (29, 30). In experimental models, it is required by dendritic cells to mediate tumor rejection (31–33). Furthermore, the combination of PD-1/PD-L1 blockade and IFNα has been shown to be superior to either alone in B16 melanoma-bearing mice, and in vitro IFNα exposure has been shown to increase PD-L1 expression in human melanoma cells (34). In patients with unresectable melanoma, the combination of pembrolizumab and pegylated IFNα-2b resulted in a 60.5% objective response rate (ORR; ref. 25).

In this pilot phase Ib/II study (ClinicalTrials.gov identifier: NCT02339324) of neoadjuvant pembrolizumab and high-dose IFNα-2b (HDI), we evaluated the safety, efficacy, and immune correlates of combination therapy in patients with high-risk surgically resectable stage III or IV melanoma.

This multi-center, open-label, phase Ib/II trial enrolled patients with resectable stage III/IV PD-1-naïve melanoma [T_x-4 N_1b-3M_0–1; American Joint Committee on Cancer (AJCC) 7th edition]. Key eligibility criteria included age ≥18 years with histologically confirmed mucosal or cutaneous melanoma, measurable disease per RECIST version 1.1 (RECIST v1.1), surgically resectable disease (confirmed by surgical oncology prior to treatment start), and an Eastern Cooperative Oncology Group performance status of 0 or 1. Patients who relapsed following adjuvant ipilimumab and had prior immune-related adverse events (irAE) could enroll if these had resolved ≤ grade 1. Patients requiring prednisone ≤10 mg/day or equivalent were eligible. Patients were excluded if they had active autoimmune disease requiring systemic immune suppression (excluding asthma, atopy, type I diabetes, hypothyroidism, and vitiligo). Approval to treat patients was obtained from the UPMC Hillman Cancer Center (Pittsburgh, PA) Institutional Review Board (IRB; no. 19020212), Roswell Park Cancer Institute (Buffalo, NY; no. 00005890), and Hershey Penn State IRB (no. 00002662). The authors attest that written informed consent was obtained from all patients involved in the study.

This clinical trial enrolled 31 patients, of whom 30 were evaluable. The treatment plan consisted of three phases: induction, definitive surgery, and maintenance. During the induction portion, patients received pembrolizumab 200 mg i.v. every 3 weeks for two doses, starting the first week of IFN administration, given concurrently with HDI at 20 MU/m²/day i.v. for 5 of 7 consecutive days for 4 weeks, followed by 10 MU/m²/day subcutaneously every other day, three times per week for 2 weeks. The maintenance phase (following recovery from surgery) consisted of pembrolizumab 200 mg i.v. every 3 weeks given concurrently with IFN at 10 MU/m²/day subcutaneously every other day, three times a week for 46 additional weeks. Dose delays of both agents were permitted. Dose reductions were permitted for HDI only. Pembrolizumab was either given or skipped. Dose-limiting toxicities (DLT) were defined as grade 3 or greater AEs within 28 days of the first treatment cycle. Grade 3 fatigue was excluded from the DLT definition. Patients were treated until disease recurrence, intolerable toxicity or for up to 1 year, whichever occurred first.

The primary objective of this study was to assess the safety profile of combination therapy with HDI and pembrolizumab. Secondary objectives included investigator-assessed radiologic ORR by RECIST v1.1, pCR rate, RFS, OS, and correlative analyses.

Radiographic imaging (PET or CT) was performed at baseline, at week 6 (after completion of the induction phase and before definitive surgery), and every 12 weeks during the maintenance phase. Baseline MRI brain was required at enrollment. During follow-up, patients underwent imaging every 3 months up until year 2, every 6 months years 2–5, and planned for every year thereafter for up to 15 years. Patients who developed recurrent melanoma were followed for survival and subsequent treatment. Response assessments followed RECIST v1.1. trAEs were evaluated using the NCI Common Terminology Criteria for Adverse Events version 4.0. Pathologic response was evaluated by three board certified pathologists who were blinded to the assessment of the other pathologists. If there was a discrepancy, a 4th pathologist reviewed the case and the majority evaluation was utilized. pCR was defined as no evidence of viable tumor by histologic assessment. A major pathologic response was defined as <10% residual melanoma in the surgical specimen.

R version 3.6.1 was used for the analysis of demographic, safety, and efficacy data. Toxicities that were possibly, probably, or definitely related to the study regimen are included in the analysis. Kaplan–Meier method was used for the analysis of time-to-event endpoint. Fisher exact tests were used to assess the association between response and exposure to prior adjuvant therapy. Cohen κ statistics was used to measure the agreement between radiographic response and pathologic response.

When evaluating the fluorescence IHC (FIHC) data, pretherapy included baseline data for all samples (n = 11). A Wilcoxon test was used to determine statistical significance for baseline versus surgery paired samples (n = 8) and unpaired t test evaluating pCR and non-pCR samples (n = 14) using GraphPad Prism v 8.1.2. Flow cytometry assessments employed paired t test for evaluating baseline and post-treatment samples from tumor-infiltrating lymphocytes (TIL) and ANOVA in addition to paired Student t test for evaluating peripheral blood mononuclear cells (PBMC) where baseline, 6-week, and 12-week biomarker assessments were possible, with P < 0.05 considered significant. To evaluate significant biomarker changes in OS, patients were classified into a low OS group and a high OS group using the median of the OS. To assess statistical significance of different biomarkers to patient response, t test was applied to compare the two groups and those biomarkers with a two-tailed P value below 0.05 were considered to be of statistical significance.

Tumor surgical, core, or punch biopsies were obtained pretreatment and tissue was obtained at the time of definitive surgery. Blood was collected at baseline, at weeks 6 and 12, at 6 and 12 months, and at time of disease recurrence. The tumor samples were formalin fixed and paraffin embedded, and portions were prepared for single-cell suspensions of tumor and TILs by enzymatic digestion. For PBMCs, blood was drawn into heparin-containing tubes and for serum into tubes without anticoagulant at baseline and at 6 weeks, 12 weeks, 6 and 12 months, and at disease recurrence. The samples were processed by the UPMC Hillman Cancer Center (Pittsburgh, PA) Immunologic Monitoring Lab and PBMC were isolated by Ficoll gradient and cryopreserved for batched testing according to standard operating procedures. The liquid nitrogen (PBMC) and −80°C (serum) freezers were continuously monitored for temperature.

Flow cytometry was performed on PBMC and on TIL. Briefly, up to 4 × 10⁶ cryopreserved PBMCs or tumor tissue cells were thawed quickly in a 37°C water bath and washed with prewarmed RPMI medium containing 10% FBS. Cells were stained with fixable viability dye eFluor506 (Thermo Fisher Scientific) at a dilution of 1:400 in wash buffer (PBS containing 0.1% sodium azide and 2% FBS) followed by staining with fluorochrome-tagged antibodies for approximately 30 minutes at room temperature in the dark, as described previously (35). After incubation, cells were washed once in wash buffer and fixed using 0.5% formalin buffer or subjected to intracellular staining. For intracellular staining to detect Ki-67 expression, PBMCs were first stained with surface antibody cocktails followed by permeabilization and staining for Ki-67 according to the manufacturer's instructions (Foxp3/Transcription Factor Staining Buffer Set, Thermo Fisher Scientific). For characterization of different immune cell subsets, the following antibodies were used CD3 (UCHT1), CD4 (RPA-T4), CD8 (SK1), CD5 (L17F21), CD19 (SJ25C1), CD25 (M-A251), CD28 (CD28.2), CD38 (HIT2), CD45 (HI30), CD45RA (HI100), CD45RO (UCHL1), CD183 (1C6/CXCR3), CD194 (1G1), CD197 (150503) CD279 (EH12.1), CD366 (7D3), HLA-DR (G46-6), and Ki-67 (B56) from (BD Biosciences). Additional antibodies were obtained from BioLegend, including CD27 (O323), CD134 (ACT35), CD196 (G034E3), or from Thermo Fisher Scientific, CD127 (eBioRDR5), CD223 (3DS223H), CD278 (ISA-3) and fixable viability dye (FVD-eF506). Stained Samples were acquired in a BD LSRFortessa X-20 equipped with 5 lasers (BD Biosciences) and data were analyzed using FlowJo software (FlowJo LLC).

For data analysis, after exclusion of debris, doublets, and dead cells, B cells were gated on the basis of the expression of CD19 and T cells were gated on the basis of the expression of CD3. T cells were further gated for CD4⁺ and CD8⁺ subsets. Both CD4⁺ and CD8⁺ cells were subsequently analyzed for the expression of various markers to define Th cell subsets, memory T-cell subsets, and checkpoint inhibitor expression. Gate placement for all checkpoint molecules was set based on naïve T cells with a summary of gating strategy for different populations shown in Supplementary Fig. S1.

Multiplexed FIHC analyses were performed to detect PD-1 and PD-L1 expression, lymphoid infiltrates (CD3, CD4, CD8, Foxp3) and CD11b, IDO1, HLA-DR in the context of tumor. PD-1/PD-L1/S100 and CD11b/HLA-DR/IDO1/S100 staining was performed as described previously (36). Image analysis was performed using AQUA (Navigate BioPharma, Inc.) to determine the percent of all DAPI cells PD-1⁺, PD-L1⁺, or the proportion of PD-1⁺ cells in close proximity to PD-L1⁺ cells, defined as the interaction score, and CD11b⁺, HLA-DR⁺, IDO1⁺, or IDO1⁺HLA-DR⁺S100⁺ cells.

The CD4, CD8, CD25, FoxP3, Ki67, cytokeratin panel was performed using a fully automated staining protocol on the Bond Rx (Leica). Slides were dewaxed using the Bond Rx followed by antigen retrieval in ER2 (Leica) buffer at 95°C for 20 minutes. Primary antibodies were incubated for 1 hour, detected with either EnVision+ horseradish peroxidase (HRP) Mouse or EnVision+ HRP Rabbit for 30 minutes and slides were heat cycled in ER1 (Leica) buffer for 20 minutes at 95°C after each round of primary, secondary, and Opal fluorophore staining. Slides were stained with 1:100 dilution of mouse anti-CD4 (4B12, Agilent), detected with Opal 520 (Akoya Biosciences), 1:400 dilution of mouse anti-CD8 (C8/144B, Agilent), detected with Opal 620 (Akoya Biosciences), 1:100 dilution of rabbit anti-FoxP3 (D2W8E, Cell Signaling Technology), detected with Opal 540 (Akoya Biosciences), 1:400 dilution of rabbit anti-CD25 (SP176, Sigma-Aldrich), detected with Opal 570 (Akoya Biosciences), 1:1,000 dilution of mouse anti-Ki67 (MIB-1, Agilent), detected with Opal 650 (Akoya Biosciences), and 1:400 dilution of mouse anti-cytokeratin (AE1/AE3, Agilent), detected with Opal 690, and finally incubated for 10 minutes with spectral DAPI (Akoya Biosciences). AQUAnalysis was used to determine the percent of all DAPI cells CD4⁺, CD8⁺, CD25⁺, FoxP3⁺ or Ki67⁺. T cells were identified as either CD4⁺ or CD8⁺. Regulatory T cells (Treg) were defined as CD25⁺FoxP3⁺CD4⁺ cell populations.

A total of 31 patients were enrolled from March 2015 to June 2018. Baseline characteristics are listed in Table 1. On central pathology review, 1 patient was found to have sarcoma (rather than melanoma) and was thus taken off study and excluded from analysis. An additional patient with melanoma was enrolled, resulting in 30 eligible patients. The median age was 59 years (range, 26–83 years). A total of 14 patients (47%) had stage IIIB, 9 (30%) had stage IIIC, and 7 patients had stage IV disease (23%) by AJCC 7th edition. A total of 4 patients (13%) had in-transit disease. A total of 17 patients (53%) had recurrent disease after prior definitive surgery. A total of 6 patients (20%) had received prior adjuvant therapy, 4 (13%) with HDI, 1 with ipilimumab (3%), and 1 with HDI and ipilimumab (3%). Three of these patients recurred at an interval of at least 3 years, and 2 patients recurred at an interval of 1 year from completion of prior adjuvant therapy. All patients were anti-PD-1 naïve.

A median of 18 doses of HDI (range, min 8–max 20) were given during the 4-week induction period. A total of 12 patients (40%) required HDI dose reduction during induction. A total of 22 patients (73%) had HDI discontinued (either during induction or maintenance); 21 for toxicity and 1 for progressive disease (PD). During HDI maintenance, a median of 44.5 doses were given (range, min 0–max 139), and 16 (53%) required dose reduction (12 had one dose reduction and 4 had two dose reductions). A median of 16 doses of pembrolizumab were completed (range, min 2–max 18). Nine (30%) discontinued pembrolizumab due to toxicity, and 4 (13%) for recurrence of disease. All patients underwent definitive surgical resection as planned and on schedule.

All patients experienced at least one trRAEs of any grade, as detailed in Table 2. The most common trAEs of any grade were fatigue in 30 (100%), elevated aspartate aminotransferase (AST) in 24 (80%), hypophosphatemia in 23 (77%), and fever in 19 (63%). The most common grade 3 TRAEs were hypophosphatemia in 13 (43%), fatigue in 11 (37%), and elevated creatine kinase (CPK) in 6 (20%). Grade 4 toxicities included hyperglycemia, elevated lipase, elevated CPK, and lymphopenia (1 each, 3%). One grade 5 event occurred following a viral prodrome, 6 months after discontinuing study therapy. Autopsy revealed pneumonia and myocarditis, and this event was not attributed to treatment.

All 30 patients were evaluated for efficacy, and all 30 patients underwent surgery as planned. On restaging scans at 6 weeks (before surgery), the radiographic ORR per RECIST 1.1 was 73.3% [95% confidence interval (CI): 55.5–85.8]. A total of 7 (23%) had a complete radiographic response (CR),15 (50%) had a partial response (PR), 7 (23%) had stable disease, and 1 (3%) had PD. There were no differences in response rate by exposure to prior adjuvant therapy (P = 0.3). All patients underwent restaging with CT (rather than PET/CT) scans.

Pathologic examination at time of surgery confirmed complete pathologic response in 13 patients (43%; 95% CI, 27–61; Fig. 1). Four additional patients (13%) had a major pathologic response, with less than 10% residual disease. Thirteen patients were pathologic nonresponders (>10% residual pathologic disease), including the 3 patients with mucosal melanoma. There were no differences in pCR seen when analyzed by prior exposure to adjuvant therapy. There was little association between ORR and pCR (Cohen κ = 0.024).

The median follow-up time for RFS was 29.17 months (17.27–36.8), and median follow-up time for OS was 37.87 months (33.2–43.47). Neither median OS (Fig. 2A) or RFS (Fig. 2B) have been reached. Five patients (17%) had recurrent disease, with a median time to recurrence of 14.5 months. None of the patients achieving a pCR have recurred. Of the 4 patients with a major pathologic response, 1 patient had recurrent disease and has died, and 3 patients remain without evidence of disease. At data cutoff, 5 patients had died. One patient died without evidence of disease at age 85, of unknown etiology. One patient died of pneumonia following a viral prodrome 6 months after completion of study therapy. Autopsy was performed and showed evidence of myocarditis, which was attributed to viral pneumonia and was not attributed to treatment. Three patients died of progressive disease after treatment on subsequent systemic therapy. Of the 3 patients with mucosal melanoma, all remain without evidence of disease.

In patients with residual pathologic disease at time of surgery, IHC was performed on 13 paired samples, at baseline and from the surgical specimen. Treatment was associated with a significant increase in the % of CD8 T cells (P = 0.04) in the tumor microenvironment (TME; Fig. 3A). There was also an increase in the % of T cells (P = 0.1), including CD4⁺ (P = 0.3), though this did not reach statistical significance. No significant differences were observed when separating the paired data according to recurrence status. The % of Tregs (P = 0.03) and CD11b + myeloid cells (P = 0.047) were also significantly increased (Fig. 3B and C). No significant differences were observed when separating the paired data according to recurrence status. At the time of surgery, PD-1–expressing nontumor cells were increased (P = 0.04), and PD-L1–expressing nontumor cells were also increased (P = 0.02; Fig. 4A and B). The PD-1/PD-L1 interaction score was significantly increased (P = 0.008) with treatment (Fig. 3C). Similar trends were noted when evaluating the paired patient samples, regardless of recurrence. Tumor cells expressing IDO1 and HLA-DR⁺ did not change significantly after treatment (P = 0.2). We evaluated T-cell exhaustion markers on TILs by flow cytometry both pre- and post-neoadjuvant therapy. CD8⁺ T cells expressing both PD-1 and TIM-3 were significantly decreased with treatment (P = 0.014), as were CD4⁺ PD1⁺TIM-3⁺ cells (P = 0.001; Fig. 5A and B). No significant changes in LAG-3 expression were noted.

We sought to determine the biologic correlates of pCR. IHC and flow cytometry on tumor samples were performed. In 14 samples (5 with pCR, and 9 without pCR) higher baseline levels of nontumor cell PD-1 (Fig. 6A) and a higher PD-1/PD-L1 interaction score (Fig. 6B) were associated with pCR (P = 0.01 and 0.002, respectively). Higher baseline values of HLA-DR on nontumor cells was also associated with pCR (P = 0.008; Fig. 6C).

We investigated the impact of treatment on the immune compartment in peripheral blood at baseline and on therapy (at 6 weeks and at 12 weeks). Treatment was associated with decreased CD4⁺PD1⁺ cells (P = 0.0003) at weeks 6 and 12, and a dramatic increase in CD8⁺Ki-67⁺ (P = 0.0006) and CD8⁺PD1⁺Ki-67⁺ (P = 0.002) cells at week 6. Marked increases in other activated T-cell phenotypes were seen with treatment, including CD4⁺ICOS⁺ (P = 0.0054), and CD8⁺CD38⁺HLA-DR⁺ (P = 0.0005) cells (Supplementary Fig. S2). We did not note any association of circulating parameters measured and pCR.

The results of this phase Ib/II trial demonstrate significant clinical activity of the combination of pembrolizumab and HDI in the neoadjuvant setting. The ORR of 73.3% and 43% pCR rate compare favorably with the results of previously reported neoadjuvant trials of HDI in melanoma as monotherapy, and in combination with ipilimumab, as well as neoadjuvant studies that have tested ipilimumab, anti-PD1 antibodies and other combinations (8, 9, 11, 14, 37). Neoadjuvant HDI monotherapy using the standard FDA-approved regimen given intravenously for 4 weeks (as tested here) had an ORR of 55% and pCR of 15% (37). Neoadjuvant ipilimumab monotherapy showed an ORR of 9%, with 0% pCR in a subsequent trial (14). Combining ipilimumab and HDI resulted in a higher preoperative radiological response rate of 36%, and pCR of 32% (9). With the advent of anti-PD1, pembrolizumab was evaluated in the neoadjuvant setting, showing a 30% complete or near complete (<10% viable tumor) pathologic response rate after a single treatment dose (8). A phase II study compared neoadjuvant nivolumab (3 mg/kg; Arm A) with neoadjuvant ipilimumab (3 mg/kg) plus nivolumab (1 mg/kg; Arm B; ref. 12). Arm A was associated with pCR and ORR both of 25%, compared with pCR 45% and ORR 73% in Arm B (12). Combination neoadjuvant ipilimumab (3 mg/kg) and nivolumab (1 mg/kg) was tested in a second study (OpAcin) and was also associated with a high pathologic response rate, though 90% of patients experienced one or more grade 3/4 adverse events, illustrating the need to evaluate alternative less toxic combination regimens in the neoadjuvant setting (11). More recently, the phase II OPACIN-NEO trial determined that the regimen consisting of two doses of ipilimumab 1 mg/kg and nivolumab 3 mg/kg was favored for further evaluation based on lower toxicity and comparable efficacy with the more toxic dosing regimen utilizing a higher ipilimumab and a lower nivolumab dose, with a 20% grade 3/4 irAE rate and a pathologic response rate of 77% (4). Importantly, none of the 13 patients with a pCR had recurred after a median follow-up of 17.6 months, confirming the importance of pCR as a potential predictive biomarker of durable clinical benefit in patients with melanoma, also supported by other reports (5). It is also interesting to note that of the 4 patients with a major pathologic response, 3 patients remain without evidence of disease, suggesting that a major pathologic response may also have predictive significance.

The median RFS in this study has not been reached at a median follow-up of 29.17 months. While this compares favorably with other reported adjuvant studies, it is difficult to draw any conclusions given our small sample size. At a minimum follow-up of 18 months, the 12-month RFS in Checkmate-238 was 70.5% in the nivolumab group and 60.8% in the ipilimumab group (HR, 0.65; 97.56% CI: 0.51–0.83; P < 0.001; ref. 38), with the RFS benefit sustained at 24 (39) and 48 months (40). In Keynote-054, at 3-year median follow-up, RFS was 64% in the pembrolizumab arm and 44% in the placebo group (HR, 0.56; 95% CI: 0.47–0.68; ref. 41).

In this study, a high proportion of patients required HDI dose reduction, both during induction and maintenance therapy. Indeed, this regimen was associated with high rates of AEs, the most common grade 3 AEs being hypophosphatemia and fatigue. Hypophosphatemia has been reported in up to 29% of patients treated with pembrolizumab, and fatigue is frequently reported with HDI. We did not observe any DLTs. Only four grade 4 adverse events were reported. One patient died 6 months after completing therapy, following a viral illness. Autopsy revealed pneumonia and myocarditis, and the patient's death was not attributed to treatment-related toxicity. However, given other reports in the literature of immune-related cardiotoxicity with PD1 and/or CTLA4 blockade we cannot rule out the possibility of a late immune-related toxicity, which is rare but possible with ICIs (42). Overall, though this regimen is associated with significant fatigue and constitutional symptoms, as would be expected with HDI, the combination does not appear to have unexpected toxicities not known with HDI or pembrolizumab. On the other hand, our combination demonstrated high ORR and pCR rates [surpassing that of HDI monotherapy (37) or anti-PD1 monotherapy (8, 12)] in spite of HDI dose reductions and a significant portion of patients (43%) eventually discontinuing pembrolizumab prior to the 1 year limit. The rate of pembrolizumab discontinuation was higher in this study than would be expected. This may be due to significant constitutional symptoms with HDI, lowering each patient's threshold to withstand further toxicity, and the difficulty of assigning attribution with combination therapy.

Mechanistically, treatment significantly increased CD8⁺ T cells, Treg, and myeloid cells in the TME, in line with prior reports (8, 12, 37). The correlation between proliferation of TIL with Treg and myeloid cells suggests early and rapid upregulation of immunoregulatory feedback loops within the TME. Interestingly, intratumoral Ki-67⁺ by IHC was not significantly changed, whereas in the peripheral blood, a dramatic increase in CD4⁺PD1⁺, CD8⁺Ki-67⁺, and CD8⁺PD1⁺Ki-67⁺ was noted. This is similar to observations in prior reports of increased T-cell activation in the periphery at 3 weeks following a dose of neoadjuvant pembrolizumab, without a consistent increase in Ki-67 in the intratumoral compartment (8). These observations may indicate that reinvigoration of T cells in the tumor occurs early, with rapid feedback mechanisms to dampen the immune response by week 6 (including increased Treg and myeloid cells). It is also possible that CD4⁺ and CD8⁺ T cells (with or without PD-1) are reinvigorated in the periphery with systemic neoadjuvant therapy, before infiltrating the tumor. Intratumoral PD-1 and PD-L1 expression were increased with treatment, as was the PD-1/PDL1 interaction score, which has been shown to be associated with improved response to anti-PD1 immunotherapy (36). Similarly, in this study, an increased PD-L1/PD-L1 interaction score correlates with pCR. Furthermore, increased HLA-DR⁺ expression is associated with a higher likelihood with pCR, suggesting that higher T-cell activation at baseline is associated with improved clinical outcomes.

In conclusion, the combination of neoadjuvant pembrolizumab and HDI appears to have a manageable safety profile and is active in patients with resectable melanoma, with evidence of robust immune modulation within the tumor and in the peripheral blood. An increased PD-1/PD-L1 interaction score and increased HLA-DR expression are associated with pCR, which appears to be a robust prognostic biomarker.

Y.G. Najjar reports grants from Merck during the conduct of the study, as well as grants from BMS, Pfizer, and Merck outside the submitted work. Y. Lin reports grants from Merck during the conduct of the study. D. Davar reports grants from BMS, Checkmate Pharmaceuticals, Cellsight Technologies, GSK/Tesaro, and Arcus and personal fees from Medical Education Network outside the submitted work; in addition, D. Davar has a patent for 10504-059PV1 pending to Compositions and Methods for Treating Cancer. R.I. Neves reports grants and personal fees from Castle Biosciences and Regeneron; grants from Replimune; and personal fees from Sanofi/Genzyme and Novartis outside the submitted work. L.H. Butterfield reports the following scientific advisory board member or consulting meeting relationships, unrelated to the current work, during the period of the project: Stemimmune/Calidi, SapVax, NextCure, Replimmune, Western Oncolytics, and Torque. M.S. Ernstoff reports grants from BMS and Merck outside the submitted work. I. Puzanov reports personal fees from Amgen, Merck, and Iovance outside the submitted work. J. Bordeaux reports personal fees from Navigate Biopharma Services during the conduct of the study, as well as personal fees from Navigate Biopharma Services outside the submitted work. I.B. Summitt reports personal fees from Navigate Biopharma during the conduct of the study, as well as personal fees from Navigate BioPharma outside the submitted work. J.O. Bender reports personal fees from Navigate Biopharma during the conduct of the study, as well as personal fees from Navigate Biopharma outside the submitted work. J.Y. Kim reports personal fees from Navigate BioPharma Services, Inc. during the conduct of the study, as well as personal fees from Navigate BioPharma Services, Inc. outside the submitted work. G. Sarikonda reports personal fees from Navigate BioPharma Services during the conduct of the study, as well as personal fees from Navigate BioPharma Services outside the submitted work. J. Tsau reports personal fees from Navigate BioPharma during the conduct of the study, as well as personal fees from Navigate BioPharma outside the submitted work. Z. Alfonso reports personal fees from Navigate Biopharma during the conduct of the study, as well as personal fees from Navigate Biopharma outside the submitted work. C. Laing reports personal fees from Navigate Biopharma during the conduct of the study, as well as personal fees from Navigate Biopharma outside the submitted work. J.M. Kirkwood reports grants and personal fees from Amgen, BMS, Checkmate Pharmaceuticals, Lovance Biotherapeutics, and Novartis Pharmaceuticals; personal fees from Harbour BioMed, Istari Oncology, OncoSec, Scopus BioPharma, and Pfizer; and grants from Castle Biosciences and Immunocore LLC outside the submitted work. A.A. Tarhini reports grants from Bristol Myers Squibb and Merck during the conduct of the study, as well as grants from Merck, Bristol Myers Squibb, Genentech-Roche, Clinigen, and OncoSec, and personal fees from Merck, Bristol Myers Squibb, Genentech-Roche, Clinigen, OncoSec, Novartis, Array Biopharma/Pfizer, Eisai, BioNTech, and EMD Serono outside the submitted work. No disclosures were reported by the other authors.

Y.G. Najjar: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, validation, investigation, methodology, writing–original draft, project administration, writing–review and editing. D. McCurry: Data curation, formal analysis, writing–original draft, project administration, writing–review and editing. H. Lin: Formal analysis. Y. Lin: Data curation, formal analysis, methodology, writing–original draft, writing–review and editing. Y. Zang: Formal analysis, investigation, methodology. D. Davar: Investigation, project administration, writing–review and editing. A. Karunamurthy: Data curation, investigation. J.J. Drabick: Data curation, investigation, project administration, writing–review and editing. R.I. Neves: Investigation, project administration, writing–review and editing. L.H. Butterfield: Data curation, investigation, writing–review and editing. M.S. Ernstoff: Investigation, project administration, writing–review and editing. I. Puzanov: Data curation, investigation, project administration, writing–review and editing. J.J. Skitzki: Data curation, investigation, project administration, writing–review and editing. J. Bordeaux: Data curation, software, formal analysis, writing–review and editing. I.B. Summitt: Software, formal analysis, validation, writing–review and editing. J.O. Bender: Software, formal analysis, validation, writing–review and editing. J.Y. Kim: Software, formal analysis, supervision, writing–original draft, writing–review and editing. B. Chen: Data curation, formal analysis, validation, investigation, methodology, writing–review and editing. G. Sarikonda: Data curation, formal analysis, validation, investigation, methodology, writing–review and editing. A. Pahuja: Data curation, formal analysis, validation, investigation, methodology, writing–review and editing. J. Tsau: Software, formal analysis, methodology, writing–original draft, writing–review and editing. Z. Alfonso: Data curation, formal analysis, validation, methodology, writing–original draft, project administration, writing–review and editing. C. Laing: Data curation, formal analysis, validation, investigation, methodology, writing–review and editing. J.F. Pingpank: Resources, project administration. M.P. Holtzman: Resources, project administration. C. Sander: Data curation, project administration, writing–review and editing. A. Rose: Resources, data curation, supervision. H.M. Zarour: Project administration, writing–review and editing. J.M. Kirkwood: Supervision, project administration, writing–review and editing. A.A. Tarhini: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, validation, investigation, visualization, methodology, project administration, writing–review and editing.

The drug and financial support for the study was provided by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ. Hillman Fellows for Innovative Cancer Research Program funded by the Henry L. Hillman Foundation (to Y.G. Najjar); Cancer Center Support grant P30CA04790. Skin SPORE CCSG for IMCPL (to L.H. Butterfield).

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