Purpose:

The surface receptor MET is highly expressed on primary uveal melanoma; MET inhibitors demonstrated early clinical signals of efficacy in slowing uveal melanoma growth. The primary objective of our study was to compare the progression-free survival rate at 4 months (PFS4) of patients with uveal melanoma treated with cabozantinib or chemotherapy.

Patients and Methods:

Patients with metastatic uveal melanoma and RECIST measurable disease were randomized 2:1 to receive either cabozantinib (arm 1) versus temozolomide or dacarbazine (arm 2) with restaging imaging every two cycles. Cross-over from arm 2 to cabozantinib after progression was allowed (arm 2X). Available tumor specimens were analyzed by whole-exome sequencing (WES) and results were correlated with outcome.

Results:

Forty-six eligible patients were accrued with 31, 15, and 9 in arms 1, 2, and 2X, respectively. Median lines of prior therapy, including hepatic embolization, were two. Rates of PFS4 in arm 1 and arm 2 were 32.3% and 26.7% (P = 0.35), respectively, with median PFS time of 60 and 59 days (P = 0.964; HR = 0.99). Median overall survival (OS) was 6.4 months and 7.3 months (P = 0.580; HR = 1.21), respectively. Grade 3–4 Common Terminology Criteria for Adverse Events were present in 61.3%, 46.7%, and 37.5% in arms 1, 2, and 2X, respectively. WES demonstrated a mean tumor mutational burden of 1.53 mutations/Mb and did not separate OS ≤ or >1 year (P = 0.14). Known mutations were identified by WES and novel mutations were nominated.

Conclusions:

MET/VEGFR blockade with cabozantinib demonstrated no improvement in PFS but an increase in toxicity relative to temozolomide/dacarbazine in metastatic uveal melanoma.

This article is featured in Highlights of This Issue, p. 759

Translational Relevance

Uveal melanoma is a rare subset of all melanomas with particularly poor outcomes in the metastatic setting. There is no clear standard-of-care therapy for metastatic disease as these melanomas lack BRAF mutations and only rarely respond to immune checkpoint blockade. Primary uveal melanoma overexpresses MET kinase, with preclinical studies suggesting inhibition of proliferation with MET blockade. Cabozantinib is a MET/VEGFR2 kinase inhibitor and a randomized discontinuation phase I study of cabozantinib suggested a preliminary benefit in metastatic uveal melanoma. We performed a national, rare tumor, randomized phase II study comparing cabozantinib with chemotherapy, observing no confirmed objective responses or differences in progression-free or overall survival between treatment arms. Whole-exome sequencing of available tumor tissue demonstrated known mutations such as GNAQ/11, SF3B1, and BAP1 similar to what has been observed in primary disease.

Melanoma arising in the uveal tract (iris, ciliary body, and choroid) is the most common intraocular malignancy although an uncommon type of all melanomas (1). Following management of primary uveal melanoma, patients retain an approximately 50% risk of metastasis. Metastasis has preferential hepatic tropism with median survival of 6–12 months following distant disease (1). To date there are no systemic therapies that have demonstrated a consistent benefit for metastatic uveal melanoma including immune checkpoint inhibitors (2, 3) and targeted therapies (4), and therefore hepatic tumor embolization or alkylating chemotherapy (temozolomide or dacarbazine) remain default approaches (1).

As opposed to cutaneous melanoma (5), uveal melanomas lack mutations of B-RAF, N-RAS, and c-KIT; however, the majority carry a mutation in either the G-protein α-subunit q (GNAQ) or 11 (GNA11; ref. 6). GNAQ/GNA11 signaling is thought to drive phospholipase C and other downstream targets to stimulate MAPK (7). Beyond the G-α pathway, several other genes have also been identified as recurrently dysregulated or overexpressed. These include the tumor suppressor BAP1, RNA splicing factor SF3B1, the transcription initiation factor EIF1AX, and the phospholipase C regulator PCLB4 in the rare non-GNAQ/GNA11–mutated uveal melanoma (7).

In addition to recurrently mutated genes, overexpression of the receptor tyrosine kinase MET is described in primary uveal melanoma in up to 83% of assayed samples (8). MET expression has been associated with a significantly higher risk of death from metastatic disease (9) and MET expression influences melanoma-specific mortality (10). MET being an influencing factor in liver metastasis in uveal melanoma is logical given that the MET ligand, hepatocyte growth factor (HGF), is produced in significant quantities in the liver. The migratory ability of uveal melanoma cells is promoted by HGF and enhances motility and invasion in uveal melanoma murine models (11). MET blockade by short hairpin RNA or selective inhibitors demonstrated significant inhibition of tumor cell proliferation, inhibition of cell migration, and reduction in metastases (8, 12, 13).

Cabozantinib is small-molecule inhibitor of multiple receptor tyrosine kinases, notably including MET and VEGFR2, as well as additional targets including RET, AXL, KIT, and TIE-2 (14). Cabozantinib has been approved for or demonstrated significant activity in medullary thyroid, renal cell, as well as hepatocellular carcinoma and has demonstrated bone-centric activity in diseases such as castration-resistant prostate cancer and osteosarcoma (14–16). Cabozantinib was investigated in melanoma via a randomized discontinuation study including 23 patients with uveal melanoma (17). These patients were described to have substantial tumor burden with median sum of the longest diameter of target lesions of 11.9 cm and hepatic metastases were present in 70%. While no responses were observed in these patients, 61% of patients had stable disease at week 12 with a median progression-free survival (PFS) of 4.8 months. The rate of PFS at 6 months was 41%, 6 patients stayed on treatment for >10 months and overall survival (OS) was 12.6 months. Two patients with bone metastases, who had a baseline bone scan, experienced partial resolution of their bone lesions during treatment with cabozantinib. Here we describe Alliance for Clinical Trials in Oncology A091201, a randomized phase II trial of the multiple TKI cabozantinib that also inhibits MET and VEGFR2 compared with temozolomide or dacarbazine in patients with metastatic uveal melanoma.

Patient eligibility

The trial was reviewed and approved by the NCI Central Institutional Review Board (IRB) or the IRB of each participating site (ClinicalTrials.gov Identifier: NCT01835145). All patients had to meet eligibility criteria including, but not limited to: histologically confirmed metastatic uveal melanoma, Eastern Cooperative Oncology Group (ECOG) performance status (0–1), RECIST version 1.0 measurable disease, any number of prior therapies except MET/VEGFR2 inhibitors or alkylating chemotherapy, and no increased risk of thrombosis, hemorrhage, or pancreatitis, as well as standard biochemical parameters including hepatic liver enzymes up to five times the upper limit of normal. Each participant signed an IRB-approved, protocol-specific, informed written consent document. This trial was conducted in accordance with Declaration of Helsinki and institutional guidelines.

Trial design

A091201 was a randomized phase II trial evaluating cabozantinib (arm 1) versus temozolomide or dacarbazine (arm 2) in patients with metastatic uveal melanoma. Patients were randomized 2:1 toward arm 1 with stratification factors including prior exposure to MEK inhibitor and site of metastasis (liver vs. other). Patients in arm 2 had the potential to cross-over to treatment with cabozantinib (arm 2X) after progression on chemotherapy by RECIST criteria, or resolution of dose-limiting toxicity; these patients were required to meet all eligibility criteria at the time of cross-over, as prespecified in the study protocol. The primary objective was to evaluate whether cabozantinib could improve the 4-month progression-free survival (PFS4) in patients with uveal melanoma from 15%, as previously described for temozolomide (18), to 40% with cabozantinib. A one-sided, two-group, χ2 test of equal proportions with a 10% type I error was pursued. A total sample size of 66 evaluable patients was proposed with 81% power to detect a difference in PFS4 rates of 0.25 (0.40 vs. 0.15). A futility stopping rule was included so that accrual would stop in the event that fewer than 6 of the first 22 patients were progression free at 4 months. Accrual did not stop while assessing the futility stopping rule. The proportion of progression-free patients at the 4-month restaging is presented with a 90% exact binomial confidence interval (CI). PFS was defined as the time from the start of treatment until disease progression or death from any cause; OS was defined as the time from the start of treatment until death from any cause. The distributions of OS and PFS are presented using the method of Kaplan–Meier with 90% confidence intervals estimated using log(−log(endpoint)) methods. Descriptive statistics (means, SDs, medians, ranges, and percentages) are reported for baseline clinical and demographic data.

Secondary endpoints included PFS, OS, RECIST response rate, and safety assessment of each arm. Adverse events were scored on the basis of the NCI's Common Terminology Criteria for Adverse Events (v4.0). The trial accrual proceeded from September 18, 2013 to April 21, 2016.

Data collection and statistical analyses were conducted by the Alliance Statistics and Data Center. Data quality was ensured by review of data by the Alliance Statistics and Data Center and by the study chairperson following Alliance policies.

This randomized phase II therapeutic trial was monitored at least twice annually by the Alliance Data and Safety Monitoring Board, a standing committee composed of individuals from within and outside of the Alliance.

Whole-exome sequencing and analysis

To inform drug development in metastatic uveal melanoma, baseline metastatic tumor samples (n = 19; one lung and 18 liver) were studied by whole-exome sequencing (WES) in exploratory fashion following trial completion. Formalin-fixed, paraffin-embedded (FFPE) tumor biopsies were collected and reviewed first for diagnostic confirmation and grade tumor percentage by pathologists at the University of Chicago (Chicago, IL). Tumor DNA were isolated from tumor samples using the QIAGEN AllPrep DNA/RNA FFPE Kit (Qiagen), and the integrity and quantification were evaluated on an Agilent 2100 Bioanalyzer (Agilent Technologies) and qubit (Thermo Fisher Scientific), respectively. DNA (200 ng) was used for whole exome + UTR capture using the Agilent SureSelect Human All Exon V6 plus UTR Kit (Agilent Technologies). Hundred-bp paired-end sequencing reads were generated on an Illumina HiSeq 4000 Instrument (Illumina) at the University of Chicago Functional Genomics Facility.

The raw sequencing data were analyzed following previously described protocols (19). In brief, the quality of raw reads was assessed by FastQC (v0.11.5), and preprocessed to trim adaptors and merge 3′ overlapping mates using FLASh (v1.2.11). Clean reads were aligned to human reference genome (GRCh38) by BWA-MEM (v0.7.17), followed by duplicate read removal, low mapping quality alignment (<30) removal, and base quality score recalibration by GATK4 (v4.0.10.1). Putative somatic mutations [single-nucleotide variants (SNV) and small insertions/deletions (indels)] were detected by somatic variant caller GATK4-MuTect2. Stringent filters were applied to the variant calls that passed the default setting of MuTect2 to further remove potential germline variants identified as those present at allele frequency ≥ 0.0001 in 1000 Genomes Project, the NHLBI Grand Opportunity Exome Sequencing Project, or the Exome Aggregation Consortium on non–The Cancer Genome Atlas samples. Variants that passed all filters were carried on for annotation using ANNOVAR (April 2018 release). The tumor mutational mutation burden was calculated by the number of mutations that were predicted to cause protein sequencing change, including nonsynonymous/stopgain/stoploss SNVs, frameshift/nonframeshift indels, and variants that modify splicing sites.

Baseline patient characteristics

A total of 46 eligible patients were enrolled in this trial, including 31 in arm 1 and 15 in arm 2. One patient in arm one was deemed ineligible after being enrolled because their initial aspartate aminotransferase (AST) value was outside the range required by the protocol; this patient was not included in the trial outcome analyses. Nine patients proceeded from arm 2 into arm 2X to receive cabozantinib.

Patient baseline characteristics for each cohort are described in Table 1. The median age for entire cohort was 62.5 years (range: 30–86) with 56.5% male and median performance status 0. The median disease-free interval (i.e., time between primary diagnosis and metastatic date) for arm 1 was 41.0 months (range 0–355.8 months) and arm 2 was 47.8 months (range of 0.2–263.3 months) with overall median of 42.7 months. Liver metastases were present in 44 patients (95.7%); 21 patients (45.7%) had liver-only disease. Baseline lactate dehydrogenase (LDH) was above the upper limit of normal in 29 patients (63%). Other common sites of disease included lung (41.3%) and bone (21.7%). All patients had undergone prior surgery or radiation to the primary lesion and median lines of therapy in the metastatic setting was two. Prior treatment included ipilimumab in 26% of patients, anti-PD1 antibodies in 17% (no patients received ipilimumab plus nivolumab), and hepatic arterial embolization in 13%.

Table 1.

Patient characteristics.

A091201 patient characteristics
12Total
(n = 31)(n = 15)(N = 46)P
Age    0.2409 
 Median 60.0 67.0 62.5  
Gender    0.7406 
 M 17 (54.8%) 9 (60.0%) 26 (56.5%)  
Race     
 White 31 (100.0%) 15 (100.0%) 46 (100.0%)  
ECOG performance status    0.1571 
 0 23 (74.2%) 8 (53.3%) 31 (67.4%)  
 1 8 (25.8%) 7 (46.7%) 15 (32.6%)  
Prior treatment with a MEK inhibitor    0.4819 
 No 30 (96.8%) 15 (100.0%) 45 (97.8%)  
Site of metastatic disease    0.5924 
 Liver (only) 15 (48.4%) 6 (40.0%) 21 (45.7%)  
 Other site 16 (51.6%) 9 (60.0%) 25 (54.3%)  
Elevated LDH    0.1094 
 Yes 22 (71.0%) 7 (46.7%) 29 (63.0%)  
Liver    0.3145 
 Yes 29 (93.5%) 15 (100.0%) 44 (95.7%)  
Bone    0.8423 
 No 24 (77.4%) 12 (80.0%) 36 (78.3%)  
Prior systemic therapya    0.7661 
 Yes 11 (35.5%) 6 (40.0%) 17 (37.0%)  
Prior HAE    0.9676 
 Yes 4 (12.9%) 2 (13.3%) 6 (13.0%)  
A091201 patient characteristics
12Total
(n = 31)(n = 15)(N = 46)P
Age    0.2409 
 Median 60.0 67.0 62.5  
Gender    0.7406 
 M 17 (54.8%) 9 (60.0%) 26 (56.5%)  
Race     
 White 31 (100.0%) 15 (100.0%) 46 (100.0%)  
ECOG performance status    0.1571 
 0 23 (74.2%) 8 (53.3%) 31 (67.4%)  
 1 8 (25.8%) 7 (46.7%) 15 (32.6%)  
Prior treatment with a MEK inhibitor    0.4819 
 No 30 (96.8%) 15 (100.0%) 45 (97.8%)  
Site of metastatic disease    0.5924 
 Liver (only) 15 (48.4%) 6 (40.0%) 21 (45.7%)  
 Other site 16 (51.6%) 9 (60.0%) 25 (54.3%)  
Elevated LDH    0.1094 
 Yes 22 (71.0%) 7 (46.7%) 29 (63.0%)  
Liver    0.3145 
 Yes 29 (93.5%) 15 (100.0%) 44 (95.7%)  
Bone    0.8423 
 No 24 (77.4%) 12 (80.0%) 36 (78.3%)  
Prior systemic therapya    0.7661 
 Yes 11 (35.5%) 6 (40.0%) 17 (37.0%)  
Prior HAE    0.9676 
 Yes 4 (12.9%) 2 (13.3%) 6 (13.0%)  

Abbreviation: HAE, hepatic arterial embolization.

aIncludes three treatments of hepatic immunoembolization not captured in HAE (all three in arm 1).

Treatment outcome

Outcomes for response, median PFS, PFS2, PFS4, and OS are described in Table 2. One patient in arm 1 had an unconfirmed RECIST response and best overall response for all patients who underwent a restaging imaging scan after treatment initiation are shown in Supplementary Fig. S1.

Table 2.

Clinical outcomes by response, PFS, PFS4, and OS.

ArmResponsePFS (median)Progression free at 2 monthsProgression free at 4 monthsOS
0/31a 60 days 41.9% 32.3% 6.4 months 
0/15 59 days 46.7% 26.7% 7.3 months 
ArmResponsePFS (median)Progression free at 2 monthsProgression free at 4 monthsOS
0/31a 60 days 41.9% 32.3% 6.4 months 
0/15 59 days 46.7% 26.7% 7.3 months 

aOne unconfirmed response was observed in arm 1 with cabozantinib.

Of the 31 patients randomized to arm 1, 10 met the primary endpoint of PFS4 (32.3%) compared with 4 of 15 randomized to arm 2 (26.7%; P = 0.350). Of the first 22 patients treated in arm 1, 5 were progression free at 4 months and the futility stopping rule was triggered although accrual continued during analysis. PFS for arm 1 and arm 2 are shown in Fig. 1. No difference in median PFS was observed between arm 1 at 60 days (95% CI, 56–162 days) compared with arm 2 at 59 days (95% CI, 56–152 days; P = 0.964; HR, 0.99; 95% CI, 0.51–1.86). The trial was terminated by the Alliance Data and Safety Monitoring Board for futility after the interim analysis.

Figure 1.

PFS of cabozantinib versus temozolomide (TMZ)/dacarbazine.

Figure 1.

PFS of cabozantinib versus temozolomide (TMZ)/dacarbazine.

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There remained 6 patients alive at analysis with a median follow-up time of 2.1 years (range 1.9–2.3 years). Four of these patients were randomized to the cabozantinib arm and the other 2 were randomized to the temozolomide/dacarbazine arm. The median OS in arm 1 was 191 days (6.4 months; 95% CI, 168–314) versus 218 days (7.3 months; 95% CI, 170–NA days) in arm 2 with log-rank test indicating no difference (P = 0.580; HR, 1.21; 95% CI, 0.62–2.34). Kaplan–Meier analysis of OS is shown in Fig. 2.

Figure 2.

OS of cabozantinib versus temozolomide (TMZ)/dacarbazine.

Figure 2.

OS of cabozantinib versus temozolomide (TMZ)/dacarbazine.

Close modal

Of the 9 patients who proceeded from arm 2 to arm 2X, the median PFS, as measured from the time of cross-over to progression, was 63.5 days and rate of PFS4 was 33.3%.

Treatment-related adverse events

Adverse event reporting is summarized by high-grade adverse events in Table 3 and all events appear, by arm, in Supplementary Table S1. All patients described adverse events irrespective of attribution; grade 3–4 adverse events were 71.0% and 66.7% in arms 1 and 2, respectively. Common attributable grade 3–4 events included fatigue, increased AST or alanine aminotransferase and thromboembolic events. Grade 3 or higher adverse events were present in 51.6% and 20.0% in arms 1 and 2, respectively. Of the 9 patients who proceeded from arm 2 to arm 2X to receive cabozantinib, grade 3 or higher adverse events were present in 33.3% of patients. The median percentage of predicted dose delivered by arm was 87%, 100%, and 100% for arm 1, 2, and 2X, respectively. For patients in each arm who experienced Grade 3–4 toxicity the median percentage of dose was 67%, 100%, and 65%.

Table 3.

High-grade adverse events.

N (%)
Patients with at least one: Arm 16 (51.6) 
Grade 3+ adverse event  
 3 (20.0) 
 2X 3 (33.3) 
Grade 4+ adverse event 1 (3.2) 
 2 (13.3) 
Grade 3+ hem adverse event 2 (13.3) 
Grade 4+ hem adverse event 2 (13.3) 
Grade 3+ non-hem adverse event 16 (51.6) 
 1 (6.7) 
 2X 3 (33.3) 
Grade 4+ non-hem adverse event 1 (3.2) 
N (%)
Patients with at least one: Arm 16 (51.6) 
Grade 3+ adverse event  
 3 (20.0) 
 2X 3 (33.3) 
Grade 4+ adverse event 1 (3.2) 
 2 (13.3) 
Grade 3+ hem adverse event 2 (13.3) 
Grade 4+ hem adverse event 2 (13.3) 
Grade 3+ non-hem adverse event 16 (51.6) 
 1 (6.7) 
 2X 3 (33.3) 
Grade 4+ non-hem adverse event 1 (3.2) 

Abbreviation: Hem, hematologic; non-hem, nonhematologic.

WES results

Baseline metastatic tumor samples (n = 19; one lung and 18 liver) were studied by WES to determine the number and frequency of genetic alterations, as summarized in Fig. 3A. Within the G protein–coupled receptor (GPCR) signaling pathway, mutations in GNA11/Q were enriched (20). Other previously described mutations found in uveal melanoma populations include SF3B1 (37%, n = 7) and BAP1 (26%, n = 5). Mutations not well-described previously were also identified, although without matched normal DNA; these are pending validation and are presented for exploratory purposes (Supplementary Fig. S2). This includes mutations in GOLGA6L10 (32%, n = 6), PKD1L3 (26%, n = 5), and FAM228B (16%, n = 3). The total tumor mutational burden (TMB) was also calculated for each sample and demonstrated a TMB of 46 ± 4 (mean ± SEM); this did not separate OS ≤ or >1 year (P = 0.14; Fig. 3B). Noting that somatic mutations per megabase (mut/Mb) has become a more conventional reporting method for TMB, a mean TMB of 1.53 mut/Mb was calculated using previously described standardization methods (21).

Figure 3.

Somatic mutations in uveal melanoma cases by WES. A, Profiles of recurrent nonsynonymous somatic mutations (NSSM) in uveal melanoma tumor including previously literature identified genes. Each column represents a separate case. Above each column is the mutational burden of each case as assessed by the total number of NSSMs per tumor. B, TMB in patients with OS ≤ or > 1 year. Mann–Whitney U test was used in B.

Figure 3.

Somatic mutations in uveal melanoma cases by WES. A, Profiles of recurrent nonsynonymous somatic mutations (NSSM) in uveal melanoma tumor including previously literature identified genes. Each column represents a separate case. Above each column is the mutational burden of each case as assessed by the total number of NSSMs per tumor. B, TMB in patients with OS ≤ or > 1 year. Mann–Whitney U test was used in B.

Close modal

Outcomes for patients with metastatic uveal melanoma are poor and no systemic therapies are clearly associated with a benefit (1). On the basis of the observation of high expression of the MET receptor in uveal melanoma (12), we performed a randomized phase II study investigating the clinical activity of the MET inhibitor cabozantinib as compared with chemotherapy. We observed no confirmed RECIST quality responses to either cabozantinib or chemotherapy and noted no difference in PFS or OS, with the clinical trial being discontinued at interim futility analysis.

These results come as somewhat of a surprise given previous early phase trial experience evaluating cabozantinib in patients with uveal melanoma, where a median PFS of greater than 4 months was described previously (17). The results are in-line with previously published PFS for chemotherapy in metastatic uveal melanoma (18). These results also may call into question whether pursuing therapeutic targets based on data from the primary setting (i.e., MET) should be prioritized in trials of metastatic disease. Noting the randomized discontinuation design of the previous trial, a major point of difference may concern patient selection, with A091201 predominately drawing from the community practice setting as opposed to referral center phase I programs in the prior study. The baseline patient characteristics in A091201 suggested a poor risk group with nearly all patients having liver metastases and high levels of LDH. In addition, rates of adverse events with cabozantinib may have been higher in the community practice setting, where at the time of the trial there was less experience using cabozantinib. In the study, patients treated in arm 1 experienced more toxicity (measured by grade 3–4 events) relative to arm 2. It appears that patients treated in arm 1 received lower drug exposure than anticipated and this could have affected the efficacy results.

Prior to and during the study accrual period, data emerged suggesting MEK inhibition as a useful therapeutic modality in uveal melanoma (22), and it was therefore deemed necessary to stratify patients within the study by previous MEK inhibitor therapy. This turned out, not to be necessary, as only 1 patient had previous MEK inhibitor treatment and subsequent studies have called into question the broad applicability of MEK inhibition for metastatic uveal melanoma (4). In addition, we observed that rates of liver-directed treatments, such as hepatic arterial embolization, appeared to be lower than would generally be expected. These points raise the peculiarities of designing clinical trials in rare patient populations where treatment at academic centers may follow different practice patterns relative to the community setting. Accrual to the study was slower than expected because of the rise of immune checkpoint blockade in melanoma, although it is noted that any possible benefit of checkpoint immunotherapy in uveal melanoma is quite modest (2, 3).

Relative to future trials in uveal melanoma, a general cross-study comparison to note is the similarity of PFS for therapies that have been deemed to be clinically ineffective. In A091201 the median PFS was nearly identical between experimental and control groups at approximately 2 months (n = 46 patients). In the SUMIT trial of selumetinib plus dacarbazine versus dacarbazine plus placebo, a median PFS was observed to be 2.8 (n = 97 patients) versus 1.8 months (n = 32 patients), respectively (HR 0.78; 95% CI, 0.48–1.27; P = 0.32) (4). Therefore, a reasonable historical comparison from randomized clinical trials of metastatic uveal melanoma could be considered to be a weighted median of 2.4 months (175 patients A091201 and SUMIT) or 1.9 months (78 patients A091201 plus patients treated with dacarbazine plus placebo in SUMIT). As mentioned above, accrual to A091201 was slow as it became unclear to the field during the study period (and remains so) what an appropriate control arm therapy should be for metastatic uveal melanoma. Chemotherapy is historically ineffective in uveal melanoma (1) and there was reticence among some investigators surrounding the dacarbazine/temozolomide treatment arm, yet checkpoint immunotherapy is only modestly effective. While combined checkpoint therapy has, to date, provided a modest benefit with response rates ranging from 10%–17% in single-arm phase II studies, it is more toxic than single agent checkpoint blockade (23). Given the number of patients treated across A091201 and SUMIT with consistent PFS outcomes, perhaps single arm designs for future studies could be explored to limit the number of patients accrued to treatments that the community deems as ineffective.

Cabozantinib is an inhibitor of a broad spectrum of tyrosine kinases, including but not limited to MET, VEGFR2, RET, AXL, KIT, and TIE-2 (14) and this kinome spectrum may provide insight on uveal melanoma tumor dependencies and combination strategies to prioritize. Clinical trials have reported promising outcomes of patients treated on single arm phase II studies of angiogenesis-targeting approaches such as sunitinib (24). However, a randomized phase II study of sunitinib versus chemotherapy did not demonstrate significant clinical activity (25). As cabozantinib is a more potent inhibitor of VEGFR2, the results of A091201 would suggest deprioritization of VEGF(R) blockade in uveal melanoma as monotherapy. Recent studies of cabozantinib in combination with anti-PD1 immunotherapy in genitourinary malignancies have suggested a benefit, even in non-T-cell–inflamed tumor types such as penile cancer (26, 27). The proposed immunologic mechanisms of this additive benefit could include impact on T-cell trafficking via inhibition of VEGF (28), innate immunity via TAM (Tyro3, Axl, and Mer) kinases (29) and others. The majority of uveal melanoma have been described as non-T-cell–inflamed (7, 30) and on the basis of these arguments, the combination of cabozantinib with immunotherapy might be considered in metastatic uveal melanoma as well. Particularly, it is of interest to consider combination strategies beyond checkpoint blockade with novel immunotherapeutics such as engineered T-cell receptor anti-CD3 anti-gp100 bispecific molecules (31) or tumor-infiltrating lymphocytes (32).

This study represents one of few cohorts of metastatic uveal melanoma samples to be characterized by WES. The mutational patterns are in part consistent with prior descriptions of primary uveal melanoma tumor samples. For example, mutations in the GPCR signaling pathway were most common: GNA11 occurred more frequently than GNAQ, and in a mutually exclusive pattern (20). Mutations in SF3B1 and BAP1 were also common; BAP1 mutations occurred exclusively in the presence of SF3B1 wild-type tumors as has previously been reported in the analyses of primary uveal melanoma samples (33). Other mutations that have not been well-described in uveal melanoma were also observed in exploratory fashion and will be of interest as larger data sets of metastatic uveal melanoma are characterized.

Whereas cutaneous melanoma is known to have a high rate of somatic mutations with a total TMB > 400, the TMB for this study cohort was low at 46 ± 4 (mean ± SEM; ref. 27). As a biomarker, TMB has also been explored in cutaneous melanoma where, when combined with IFNγ gene expression signatures, a high mutational burden increased the prognostic power to predict a prolonged relapse-free survival in stage III melanoma. However, on its own TMB failed to distinguish responders and nonresponders to BRAF/MEK-targeted therapies (34, 35). Similarly, in this study cohort, TMB failed to differentiate OS > 1 year to OS ≤1, suggesting that TMB as a singular biomarker may not accurately predict survival in uveal melanoma.

In summary, this randomized phase II study demonstrated no improvement of PFS or OS for cabozantinib as compared with chemotherapy in patients with metastatic uveal melanoma. Toxicities were substantial, although they might be less, now that cabozantinib has obtained broad usage in thyroid, kidney, and liver malignancies. Clinical outcomes were similar to other recent randomized studies in uveal melanoma, potentially suggesting a historical reference point for patients treated outside of major referral centers. Although little future seems likely as monotherapy, exploratory studies in genitourinary cancers (36) suggest a possible utility for cabozantinib in combination with immunotherapy even in non-T-cell–inflamed tumors potentially including uveal melanoma.

J.J. Luke is an employee/paid consultant for TTC Oncology, 7 Hills, Actym, Alphamab Oncology, Mavu, Pyxis, Springbank, Tempest, Abbvie, Akrevia, Arrau, Astellas, AstraZeneca, Bayer, Bristol-Myers Squibb, Compugen, EMD Serono, Ideaya, Immunocore, Incyte, Janssen, Jounce, Leap, Merck, Mersana, Novartis, RefleXion, and Vividion, and reports receiving commercial research grants from Array, CheckMate, Evelo, Merck, and Palleon. B.R. Bastos is an advisory board member/unpaid consultant for Exelixis. M.O. Butler is an employee/paid consultant for Merck, Sanofi, Bristol-Myers Squibb, Novartis, and Immunocore, and reports receiving commercial research grants from Merck and Takara. D. Hogg is an employee of Bristol-Myers Squibb, Merck, EMD Serono, and Novartis. No potential conflicts of interest were disclosed by the other authors.

The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Conception and design: J.J. Luke, J.B. Allred, B.R. Bastos, P.N. Munster, G.K. Schwartz

Development of methodology: J.J. Luke, J.B. Allred, R. Bao, B.R. Bastos, P.N. Munster, G.K. Schwartz

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): J.J. Luke, J.B. Allred, Y. Zha, T. Carll, M.O. Butler, D. Hogg, G.K. Schwartz

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): J.J. Luke, D.J. Olson, J.B. Allred, C.A. Strand, R. Bao, T. Carll, B.W. Labadie, M.O. Butler, G.K. Schwartz

Writing, review, and/or revision of the manuscript: J.J. Luke, D.J. Olson, J.B. Allred, C.A. Strand, R. Bao, Y. Zha, T. Carll, B.W. Labadie, B.R. Bastos, M.O. Butler, G.K. Schwartz

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): J.J. Luke, D.J. Olson, R. Bao, T. Carll, G.K. Schwartz

Study supervision: J.J. Luke, P.N. Munster, G.K. Schwartz

Research reported in this article was supported by the NCI of the NIH under Award Numbers U10CA180821, U10CA180882, and U24CA196171 (to the Alliance for Clinical Trials in Oncology), and U10CA180836, UG1CA189960, and U10CA180863 (CCTG). J.J. Luke acknowledges Department of Defense Career Development Award (W81XWH-17-1-0265), NCI Cancer Clinical Investigator Team Leadership Award (P30 CA014599), the Arthur J. Schreiner Family Melanoma Research Fund, the J. Edward Mahoney Foundation Research Fund, Brush Family Immunotherapy Research Fund, and Buffet Fund for Cancer Immunotherapy. D.J. Olson acknowledges the Clinical Therapeutics Training Grant (NIH/NIGMS T32GM007019). This work is also supported in part by funds from Exelixis (https://acknowledgments.alliancefound.org).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Luke
JJ
,
Triozzi
PL
,
McKenna
KC
,
Van Meir
EG
,
Gershenwald
JE
,
Bastian
BC
, et al
Biology of advanced uveal melanoma and next steps for clinical therapeutics
.
Pigment Cell Melanoma Res
2015
;
28
:
135
47
.
2.
Luke
JJ
,
Callahan
MK
,
Postow
MA
,
Romano
E
,
Ramaiya
N
,
Bluth
M
, et al
Clinical activity of ipilimumab for metastatic uveal melanoma: a retrospective review of the Dana-Farber Cancer Institute, Massachusetts General Hospital, Memorial Sloan-Kettering Cancer Center, and University Hospital of Lausanne experience
.
Cancer
2013
;
119
:
3687
95
.
3.
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
.
4.
Carvajal
RD
,
Piperno-Neumann
S
,
Kapiteijn
E
,
Chapman
PB
,
Frank
S
,
Joshua
AM
, et al
Selumetinib in combination with dacarbazine in patients with metastatic uveal melanoma: a phase III, multicenter, randomized trial (SUMIT)
.
J Clin Oncol
2018
;
36
:
1232
9
.
5.
Luke
JJ
,
FLaherty
KT
,
Ribas
A
,
Long
GV
. 
Optimizing clinical outcomes in advanced-stage melanoma with targeted agents and immunotherapies
.
Nat Rev Clin Oncol
2017
;
14
:
463
82
.
6.
Zuidervaart
W
,
van Nieuwpoort
F
,
Stark
M
,
Dijkman
R
,
Packer
L
,
Borgstein
AM
, et al
Activation of the MAPK pathway is a common event in uveal melanomas although it rarely occurs through mutation of BRAF or RAS
.
Br J Cancer
2005
;
92
:
2032
8
.
7.
Robertson
AG
,
Shih
J
,
Yau
C
,
Gibb
EA
,
Oba
J
,
Mungall
KL
, et al
Integrative analysis identifies four molecular and clinical subsets in uveal melanoma
.
Cancer Cell
2017
;
32
:
204
20
.
8.
Abdel-Rahman
MH
,
Boru
G
,
Massengill
J
,
Salem
MM
,
Davidorf
FH
. 
MET oncogene inhibition as a potential target of therapy for uveal melanomas
.
Invest Ophthalmol Vis Sci
2010
;
51
:
3333
9
.
9.
Mallikarjuna
K
,
Pushparaj
V
,
Biswas
J
,
Krishnakumar
S
. 
Expression of epidermal growth factor receptor, ezrin, hepatocyte growth factor, and c-Met in uveal melanoma: an immunohistochemical study
.
Curr Eye Res
2007
;
32
:
281
90
.
10.
Economou
MA
,
All-Ericsson
C
,
Bykov
V
,
Girnita
L
,
Bartolazzi
A
,
Larsson
O
, et al
Receptors for the liver synthesized growth factors IGF-1 and HGF/SF in uveal melanoma: intercorrelation and prognostic implications
.
Acta Ophthalmol
2008
;
86
:
20
5
.
11.
Rusciano
D
,
Lorenzoni
P
,
Burger
MM
. 
Expression of constitutively activated hepatocyte growth factor/scatter factor receptor (c-met) in B16 melanoma cells selected for enhanced liver colonization
.
Oncogene
1995
;
11
:
1979
87
.
12.
Wu
X
,
Zhou
J
,
Rogers
AM
,
Janne
PA
,
Benedettini
E
,
Loda
M
, et al
c-Met, epidermal growth factor receptor, and insulin-like growth factor-1 receptor are important for growth in uveal melanoma and independently contribute to migration and metastatic potential
.
Melanoma Res
2012
;
22
:
123
32
.
13.
Surriga
O
,
Rajasekhar
VK
,
Ambrosini
G
,
Dogan
Y
,
Huang
R
,
Schwartz
GK
. 
Crizotinib, a c-Met inhibitor, prevents metastasis in a metastatic uveal melanoma model
.
Mol Cancer Ther
2013
;
12
:
2817
26
.
14.
Markowitz
JN
,
Fancher
KM
. 
Cabozantinib: a multitargeted oral tyrosine kinase inhibitor
.
Pharmacotherapy
2018
;
38
:
357
69
.
15.
Fioramonti
M
,
Fausti
V
,
Pantano
F
,
Iuliani
M
,
Ribelli
G
,
Lotti
F
, et al
Cabozantinib affects osteosarcoma growth through a direct effect on tumor cells and modifications in bone microenvironment
.
Sci Rep
2018
;
8
:
4177
.
16.
Fioramonti
M
,
Santini
D
,
Iuliani
M
,
Ribelli
G
,
Manca
P
,
Papapietro
N
, et al
Cabozantinib targets bone microenvironment modulating human osteoclast and osteoblast functions
.
Oncotarget
2017
;
8
:
20113
21
.
17.
Daud
A
,
Kluger
HM
,
Kurzrock
R
,
Schimmoller
F
,
Weitzman
AL
,
Samuel
TA
, et al
Phase II randomised discontinuation trial of the MET/VEGF receptor inhibitor cabozantinib in metastatic melanoma
.
Br J Cancer
2017
;
116
:
432
40
.
18.
Bedikian
AY
,
Papadopoulos
N
,
Plager
C
,
Eton
O
,
Ring
S
. 
Phase II evaluation of temozolomide in metastatic choroidal melanoma
.
Melanoma Res
2003
;
13
:
303
6
.
19.
Matson
V
,
Fessler
J
,
Bao
R
,
Chongsuwat
T
,
Zha
Y
,
Alegre
M-L
, et al
The commensal microbiome is associated with anti–PD-1 efficacy in metastatic melanoma patients
.
Science
2018
;
359
:
104
8
.
20.
Van Raamsdonk
CD
,
Griewank
KG
,
Crosby
MB
,
Garrido
MC
,
Vemula
S
,
Wiesner
T
, et al
Mutations in GNA11 in uveal melanoma
.
N Engl J Med
2010
;
363
:
2191
9
.
21.
Chang
H
,
Sasson
A
,
Srinivasan
S
,
Golhar
R
,
Greenawalt
DM
,
Geese
WJ
, et al
Bioinformatic methods and bridging of assay results for reliable tumor mutational burden assessment in non-small-cell lung cancer
.
Mol Diagn Ther
2019
;
23
:
507
20
.
22.
Carvajal
RD
,
Sosman
JA
,
Quevedo
JF
,
Milhem
MM
,
Joshua
AM
,
Kudchadkar
RR
, et al
Effect of selumetinib vs. chemotherapy on progression-free survival in uveal melanoma: a randomized clinical trial
.
JAMA
2014
;
311
:
2397
405
.
23.
Piulats Rodriguez
JM
,
De La Cruz Merino
L
,
Espinosa
E
,
Alonso Carrión
L
,
Martin Algarra
S
,
López-Castro
R
, et al
Phase II multicenter, single arm, open label study of nivolumab in combination with ipilimumab in untreated patients with metastatic uveal melanoma (GEM1402.NCT02626962)
.
Ann Oncol
2018
;
29
:
mdy289.003
.
24.
Mahipal
A
,
Tijani
L
,
Chan
K
,
Laudadio
M
,
Mastrangelo
MJ
,
Sato
T
. 
A pilot study of sunitinib malate in patients with metastatic uveal melanoma
.
Melanoma Res
2012
;
22
:
440
6
.
25.
Sacco
JJ
,
Nathan
PD
,
Danson
S
,
Lorigan
P
,
Nicholson
S
,
Ottensmeier
C
, et al
Sunitinib versus dacarbazine as first-line treatment in patients with metastatic uveal melanoma
.
J Clin Oncol
31:15s, 2013 (suppl; abstr 9031).
26.
Nadal
R
,
Mortazavi
A
,
Stein
MN
,
Pal
SK
,
Lee
DK
,
Parnes
HL
, et al
Clinical efficacy of cabozantinib plus nivolumab (CaboNivo) and CaboNivo plus ipilimumab (CaboNivoIpi) in patients (pts) with chemotherapy-refractory metastatic urothelial carcinoma (mUC) either naïve (n) or refractory (r) to checkpoint inhibitor (CPI)
.
J Clin Oncol
36:15s, 2018 (suppl; abstr 4528).
27.
Spranger
S
,
Luke
JJ
,
Bao
R
,
Zha
Y
,
Hernandez
KM
,
Li
Y
, et al
Density of immunogenic antigens does not explain the presence or absence of the T-cell-inflamed tumor microenvironment in melanoma
.
Proc Natl Acad Sci U S A
2016
;
113
:
E7759
E68
.
28.
Fukumura
D
,
Kloepper
J
,
Amoozgar
Z
,
Duda
DG
,
Jain
RK
. 
Enhancing cancer immunotherapy using antiangiogenics: opportunities and challenges
.
Nat Rev Clin Oncol
2018
;
15
:
325
40
.
29.
Akalu
YT
,
Rothlin
CV
,
Ghosh
S
. 
TAM receptor tyrosine kinases as emerging targets of innate immune checkpoint blockade for cancer therapy
.
Immunol Rev
2017
;
276
:
165
77
.
30.
Johnson
DB
,
Bao
R
,
Ancell
KK
,
Daniels
AB
,
Wallace
DE
,
Sosman
JA
, et al
Response to anti-PD1 in uveal melanoma without high volume liver metastasis
.
J Natl Compr Cancer Netw
2019
;
17
:
114
7
.
31.
Sato
T
,
Nathan
PD
,
Hernandez-Aya
LF
,
Sacco
JJ
,
Orloff
MM
,
Truscello
J
, et al
Intra-patient escalation dosing strategy with IMCgp100 results in mitigation of T-cell based toxicity and preliminary efficacy in advanced uveal melanoma
.
J Clin Oncol
35:15s, 2017 (suppl; abstr 9531).
32.
Chandran
SS
,
Somerville
RPT
,
Yang
JC
,
Sherry
RM
,
Klebanoff
CA
,
Goff
SL
, et al
Treatment of metastatic uveal melanoma with adoptive transfer of tumour-infiltrating lymphocytes: a single-centre, two-stage, single-arm, phase 2 study
.
Lancet Oncol
2017
;
18
:
792
802
.
33.
Decatur
CL
,
Ong
E
,
Garg
N
,
Anbunathan
H
,
Bowcock
AM
,
Field
MG
, et al
Driver mutations in uveal melanoma: associations with gene expression profile and patient outcomes
.
JAMA Ophthalmol
2016
;
134
:
728
33
.
34.
Yan
Y
,
Robert
C
,
Larkin
J
,
Ascierto
PA
,
Dreno
B
,
Maio
M
, et al
Genomic features of complete responders (CR) versus fast progressors (PD) in patients with BRAFV600-mutated metastatic melanoma treated with cobimetinib + vemurafenib or vemurafenib alone
.
Ann Oncol
2016
;
27
:1111O.
35.
Long
GV
,
Hauschild
A
,
Santinami
M
,
Atkinson
VG
,
Mandala
M
,
Chiarion-Sileni
V
, et al
Updated relapse-free survival (RFS) and biomarker analysis in the COMBI-AD trial of adjuvant dabrafenib + trametinib (D + T) in patients (pts) with resected BRAF V600–mutant stage III melanoma
.
Ann Oncol
2018
;
29
:mdy424-053.
36.
Apolo
AB
,
Mortazavi
A
,
Stein
MN
,
Pal
SK
,
Davarpanah
NN
,
Parnes
HL
, et al
A phase I study of cabozantinib plus nivolumab (CaboNivo) and ipilimumab (CaboNivoIpi) in patients (pts) with refractory metastatic urothelial carcinoma (mUC) and other genitourinary (GU) tumors
.
J Clin Oncol
35:6s, 2017 (suppl; abstr 293).