Metastatic Melanoma Patient–Derived Xenografts Respond to MDM2 Inhibition as a Single Agent or in Combination with BRAF/MEK Inhibition

The American Cancer Society estimates that there will be over 96,000 new cases of melanoma in the United States in 2019, with an estimated 7,230 deaths. The World Health Organization estimates nearly 300,000 melanoma skin cancers occur globally each year with the highest rates in Australia and New Zealand (1). The incidence of melanoma has risen rapidly over the past 30 years, especially in those over 50 years of age, which places melanoma as the fifth most common form of new cancer diagnoses. For the period between 2006–2015, the incidence rate increased by 3% per year (2). While new cancer diagnosis rates continue to rise, the 5-year survival rate continues to improve (1). This improvement in survival reflects the recent emphasis in early detection combined with improvements in therapies, such as targeted and immune therapy.

Advances in metastatic melanoma treatment followed the identification and classification of melanoma driver mutations, particularly mutations in BRAF described in 2002 (3). Characterization of driver mutations paved the way for new treatment strategies focused on small-molecule inhibitors targeting specific proteins involved in the melanoma pathogenesis (4–6). The most common oncogenic driver mutations are in the MAPK pathway where BRAF mutations occur in approximately 50% of melanomas and NRAS mutations in 15%–20% of melanomas, with neither BRAF nor NRAS mutations occurring concomitantly. Activating mutations in NRAS occur at either codon 12 or codon 61, or less frequently codon 13. Mutations at codon Q61, resulting in the Q61R/K/L substitutions, disrupts the GTPase activity of RAS, resulting in a constitutively active conformation, whereas mutations at codon G12 or G13 affect the Walker A-motif of the protein, thus decreasing its sensitivity to GTPase-accelerating proteins (7). BRAF-activating mutations resulting in V600E/K/M account for nearly 90% of all the BRAF mutations in melanomas. Inhibitors of BRAF^V600E/K/M were developed including dabrafenib, vemurafenib, and encorafenib, and were successful in phase III clinical trials (8–10). MEK kinases (MEK1 and MEK2), which function immediately downstream of BRAF, also have been studied as potential therapeutic targets for inhibition, especially in combination with BRAF inhibition. Three BRAF–MEK inhibitor combinations (dabrafenib–trametinib, vemurafenib–cobimetinib, and encorafenib–binimetinib) were successful in phase III clinical trials (11–17). Treatment of patients with wild-type BRAF has proved more difficult, especially for those with NRAS mutations. There are currently no therapies that directly target mutant NRAS; however, MEK inhibitors (trametinib, binimetinib, and pimasertib) have been shown to have some effect in wild-type BRAF and mutant NRAS melanoma (18, 19).

The suboptimal response rates for targeted therapies, particularly within tumors not expressing the BRAF^V600 mutation, have led to increased interest in other therapeutic options, including combination therapies targeting different pathways. The p53 tumor suppressor protein is one such option. In contrast to many other cancers, over 80% of human melanomas express TP53^WT, but p53 degradation can be enhanced through overexpression of the murine double minute (MDM) proteins, MDM2 or MDMX (20–23). Loss or mutation of CDKN2A in approximately 40% of melanoma tumors results in loss of function of the MDM2 inhibitor, p14/p19, thus increasing MDM2-mediated degradation of p53. (24). In the past several years, several molecules have been developed to interrupt the interaction between p53 and MDM2. These include the cis-imidazolines “Nutlins” (RG7112 and RG7388), the spirooxindoles (MI-77301 and MK-8242), as well as other recently developed compounds such as CGM097, HDM201, and the piperidinone, AMG 232/KRT-232 (25, 26). Interestingly, KRT-232 was shown to have antitumor activity in cell and animal models of melanoma with BRAF and KRAS mutations. These studies showed that KRT-232 treatment led to increased p53, CDKN1A, MDM2, and PUMA proteins in TP53 wild-type cells (SJSA-1, HCT116), but not in TP53-mutant HT-29 cells. KRT-232 also has been reported to be an effective MDM2 inhibitor in glioblastoma cell lines, patient-derived stem cells (27), and a wide variety of TP53^WT, but not mutant TP53 tumor cell lines (28, 29).

In this study, we tested the antitumor efficacy of combining KRT-232 with BRAF and MEK inhibitors using melanoma patient–derived xenograft models (PDX). We utilized a well-characterized panel of melanoma PDX tumors, which represented an array of BRAF and NRAS genotypes. Others have demonstrated that melanoma PDX tumors accurately model the disease and respond to targeted therapies (30–32). When KRT-232 was tested as a single agent, only tumors that expressed wild-type BRAF^V600 (6/15 or 40%) had slower growth rates in response to KRT-232 compared with vehicle-treated mice. The remaining nine PDX tumors were synergistically responsive to KRT-232 in combination with BRAF and MEK inhibition. These studies demonstrate that KRT-232 is an effective potential agent for the treatment of melanoma tumors that are either BRAF^WT or Pan^WT (BRAF^WT, NRAS^WT, NF1^WT). Furthermore, KRT-232 is an effective agent in combination with dabrafenib and trametinib for the treatment of BRAF^V600MUT tumors.

KRT-232 (AMG 232), navitoclax, dabrafenib, and trametinib were provided by the NCI.

Animal studies were approved by the Vanderbilt University Institutional Animal Care and Use Committee (IACUC; M1600236). NSG mice (NOD.Cg-Prkdc^scid Il2rg^tm1Wjl/SzJ) were purchased from Jackson Labs and Athymic Nude mice (Hsd: Athymic Nude-Foxn1nu) were purchased from Envigo. PDX tumors were established and propagated as described previously (33). The mice were all 3- to 6-month-old females weighing 20–26 grams. KRT-232 and navitoclax were prepared in 5% DMSO and 95% corn oil and administered five days a week by oral gavage in a total volume of 100–200 μL based upon the weight of the mouse. Corn oil with 5% DMSO was used as the vehicle control. Dabrafenib and trametinib were prepared in 0.5% hydroxypropyl methylcellulose. At least 5 mice per treatment group were used, with each mouse bearing 2 tumors. Mouse body weight was measured daily for gavage dosing and recorded twice a week and tumor measurements were taken twice a week with microcalipers. Tumor volume was estimated as 0.5 × length × width × width. Treatment began when tumors reached 50–100 mm³ volume on average and continued until tumors reached 15 mm in diameter or became perforated. At the end of the experiment, the final weight of the tumors was recorded, and tumors were either flash-frozen for reverse-phase protein analysis (RPPA) or fixed in 10% buffered formalin for paraffin embedding. PDX models 1577, 1668, 1767, 1595, 2316, and 2252 were provided to the Patient-Derived Models Repository at NCI-Frederick. All models were established according to the recommended Minimal Information Standard (34).

DNA from patient tumor or early passage (P2) PDX tumor (PDX1577, 1668, 2316, and 2552) and from leukocytes isolated from peripheral blood from the PDX donor were submitted for quality control and DNA sequencing using the Human Comprehensive Cancer Panel (QIAGEN Sciences). Identification of tumor-associated somatic mutations and copy-number alterations was performed using the QIAGEN NGS Data Analysis Web Portal. A color-coded map of genetic alterations in PDXs was constructed using OncoPrinter available through cBioPortal (35, 36).

DNA extraction from tumor tissue was achieved using standard phenol: chloroform extraction methods and ethanol precipitation or using the DNeasy Blood and Tissue Kit. For a subset of tumors with high melanin content, the DNA was further purified using the Qiagen DNeasy PowerClean Pro Cleanup K Kit (QIAGEN Sciences). DNA from matching blood samples, when available, was extracted using the QIAamp DNA Mini and Blood Mini Kit. DNA from matched patient blood (when available), P0 (patient's original tumor), and passage two of PDX tumors (P2A and P2B) were subject to short tandem repeat (STR) profiling leveraging the PowerPlex 16 HS System (Promega). A total of 16 STR loci (D351358, TH01, D18551, Penta E, D55828, D135317, D75820, D165539, CSF1P0, Dmelogenin, vWA, D851179, TPOX, FGA) were coamplified in each sample. PDX specimens were considered a match to the patient specimen when one allele from each 16 STR locus was present in the P0 and P2 specimen. The amelogenin alleles for all the specimens match the patient sex that was reported.

IHC analyses were performed using the Leica Bond Max IHC stainer. All steps besides dehydration, clearing, and coverslipping were performed on the Bond Max. Slides were deparaffinized and heat-induced antigen retrieval was performed on the Bond Max using their Epitope Retrieval 2 solution for 30 minutes. The sections were incubated with Ready-to-Use antibody as indicated below. The Bond Refine Polymer detection system was used for visualization. Slides were then dehydrated, cleared, and coverslipped. IHC slides were scanned at the Digital Pathology Shared resource. The automated quantification of the percentages of the Ki67-positive cells was performed by Leica Biosystems' Digital Image Hub, using the software available with the Leica SCN400 Slide Scanner. The following antibodies were used: anti-p53 (PA0057, Leica Biosystems) for 30 minutes, anti-MelanA (PA0233, Leica) for 15 minutes, anti-Ki67 (RM47-26, StatLab) for 30 minutes, and anti-SOX10 (PA0813, Cell Marque) for 1 hour.

Flash-frozen tumor tissue was processed in RIPA buffer using a Precellys Homogenizer. Lysates were analyzed with a 382 antibody panel. For each condition, three independent tumors were analyzed from three PDX tumors, resulting in nine samples analyzed for each treatment. The only exception to this was for the KRT-232 + dabrafenib + trametinb treatment of PDX1351 where only two independent tumors were analyzed. RPPA data was analyzed after a log₂ transformation. All comparisons were performed on the basis of a mixed-effect model to account for the correlation structure with the measured data from the sample PDX. Using model-based (least-square) means, the average adjusted difference (log₂FC: fold change in a log₂ scale) between treatments (or groups) was estimated and compared using the Wald test. Bonferroni correction was used to adjust for multiple testing. Changes in protein expression were considered to be significant (shown in red) based upon two criteria: the significance of the change [false discovery rate (FDR) < 0.05] and the degree of change [when log₂(FC) = ± 0.4]. A heatmap was used for the visualization of proteins with significantly different expression across treatments. Hierarchical clustering analysis using Ward's distance was used to measure the dissimilarity between two clusters of observations.

For a comparison of more than two groups, one-way ANOVA with pairwise t test comparison was used. For in vivo experiments, tumor volume or tumor weight were analyzed on the natural log scale to better meet the normality assumption. The mixed-effects model with post hoc tests was used to compare the difference in tumor growth or tumor weight between treatments. P value was adjusted using the Bonferroni method. With pairwise comparison, the P value was adjusted using the Bonferroni method to correct for inflated type I error (the higher the change for a false positive). For each PDX, initial statistical and data analysis was based on all treatment groups, which included three experimental agents tested individually and in combination compared with vehicle controls, but data analyses are presented based upon the statistical analysis for the subset of experimental agents. For synergy analysis, a mixed-effect model with individual effect and interactive effect was used to assess treatment differences in tumor volume over days. Each observation was classified according to the PDXs. Tukey adjusted P value was used for multiple comparisons. All tests of statistical significance were two-sided. Unless otherwise noted in the manuscript, we use the word “significant” to represent statistical significance (***, P < 0.001; **, P < 0.01; *, P < 0.05). Analyses were performed using R version 3.4.3 (37, 38).

Melanoma PDXs were established from melanoma tumors obtained from patients who were referred for surgical resection or biopsy. From a larger set of PDX tumors, 15 PDXs (Table 1A) were chosen for this study to approximately represent the range of mutations found in melanoma tumors. The patient population was 47% male and 53% female, represented ages from 29 to 77, and were largely American Joint Committee on Cancer (AJCC; ref. 39) stage IV (although two patients had locally advanced stage III melanoma: PDX2316 and 2552). The prior systemic therapies are listed in Table 1A, in the order in which they were received. Four patients were not treated systemically before resection (PDX2195, 2252, 1668, and 2316). The remaining 11 patients had tumor progression after targeted therapy or immunotherapy; both patients with BRAF^V600 mutations treated with dabrafenib and trametinib had progression on therapy.

Except for patient 2316, all tumors were screened by either SNaPshot analysis or in the case of patient 2552 by Onkosight as standard of care in the clinic (40). SNaPshot analyses indicated that three tumors (1129, 1668, and 1767) were BRAF^WT, NRAS^WT, and NF1^WT for specific mutations in the nucleotides queried. To further understand the genetic make-up of the PDX tumors utilized in this study, either the original patient tumor or in the case of PDX1577, 1668, 2316, and 2552, second-passage PDX aliquots were analyzed using a comprehensive cancer next-generation sequencing (NGS) panel that targets exonic regions of genes with known associations to cancer. In all cases, the mutations noted in the patients' tumors by SNaPshot and Onkosight sequencing were confirmed by NGS in the laboratory.

NGS provided additional genetic information relevant to this study. The UV carcinogenic etiology of melanoma results in melanoma having among the highest prevalence of somatic mutation across all cancer types (41). The number of mutations between samples sequenced was variable. PDX1767 had the fewest nonsynonymous mutations (NSM), with 295 high-confidence variants at a mean read depth in the target region of 83, while PDX1668 had the most NSMs with 2,352 high-confidence variants at a mean read depth of 199 (Supplementary Table S1A and S1B). Neither of these tumors had hotspot mutations in BRAF and NRAS. For two of the tumors where no mutations were identified by SNaPshot (1129 and 1668), NGS identified additional mutations in driver genes. For PDX1668, NGS identified a loss of the stop codon in NF1, and two mutations in BRAF, S147N and N140T, with unknown significance. Further analysis of PDX1129 by NGS identified two mutations in BRAF (D549N and K483T). While the BRAF p.D549N is of unknown significance, it has been previously identified in the NZM41 cell line and in other melanomas, colorectal and lung carcinomas, and hairy cell leukemia (42–45). PDX2316 also was retrospectively analyzed by NGS and was found to lack mutations in BRAF and NRAS, although mutations in NF1, CDKN2A, MTOR, and KIT were detected. The tumors used in this study closely mimic the expected distribution of mutations within the driver mutation genes BRAF, NRAS, and NF1, with 53% exhibiting mutated BRAF^V600 and 13% exhibiting mutated NRAS^Q61 mutations. Furthermore, PDX2316 was BRAF^WT and NRAS^WT and PDX1767 was BRAF^WT, NRAS^WT, and NF1^WT.

Given the high number of tumor variants, we queried the cBioPortal for Cancer Genomics (35, 36) to identify the 10 most frequently mutated genes in melanoma. The dataset included 1,414 patient/case sets for melanoma, including acral, desmoplastic, and lentigo maligna, but not uveal melanoma. The distribution of occurrence of mutations in these top 10 genes is shown in Table 1A and Supplementary Table S1B and the hotspot mutations identified in the PDX panel are listed. A hotspot in the cBioPortal is defined as, “this mutated amino acid was identified as a recurrent hotspot (statistically significant) and a three-dimensional clustered hotspot in a population-scale cohort of tumor samples of various cancer types using a previously described methodology (46, 47)”. Close attention was paid to mutations and copy-number variations (CNV) within the TP53 locus since MDM2 is an important negative regulator of p53 (Table 1B; Supplementary Table S1B). By far, the most prevalent TP53 variant was the P72R polymorphism, which was present in all the PDXs, except PDX9164. Four PDX tumors (PDX9164, 1839, 2252, and 0807) had nonsynomonous mutations (NSM) in the TP53 locus. PDX9164, PDX1839, and PDX2252 had mutations resulting in early translation termination and PDX2252 also had decreased TP53 copy number (CNV could not be determined for PDX9164). PDX0807 had two TP53 mutations, an insertion at codon 138 (A—ADG), and an NSM at codon T140 (T—S). The mutations in PDX0807 occurred at a low frequency (26%–27%). In addition to these NSMs, PDXs 1668, 1839, and 1946 had mutations within TP53 splice sites. While the exact nature and frequency of these mutations is not reported in the NGS data, these three PDX tumors also had a loss of heterozygosity in the TP53 locus. All mutations and CNVs within the 10 focus genes and MDM2, regardless of SnpEff scores (48), for each PDX are listed in Supplementary Table S1B. Interestingly, copy-number alterations, but not mutations, were noted for MDM2.

Eight PDX tumors were characterized by STR analysis to confirm that the resulting PDX tumors were derived from the patient sample (Supplementary Fig. S1A). The STR profiles demonstrate that each analyzed PDX was derived from the primary specimen. As reported previously (49), mouse PDX tumors undergo genetic evolution, and in accordance with this, there were changes noted between the STR profiles of the human tumor sample and the PDX, with occasional loss of an allele, consistent with clonal selection.

For each PDX tumor, pathology and melanoma IHC markers were confirmed relative to the patient diagnosis of melanoma by a clinical pathologist. Representative results are shown for PDXs 2552, 1767, 1668, and 1595 (Supplementary Fig. S1B). The markers used for melanocytic differentiation were Melan-A/Mart 1 and SOX10. Also, patient tumors (P0) and the second-passage PDX (P2) were stained by hematoxylin and eosin (H&E) and for Ki-67, to determine the mitotic rate. All melanoma tumors and resulting PDXs were positive for SOX10 (50) while a subset was positive for Melan-A, consistent with prior results (51). In addition to the correlation between SOX10 and Melan-A expression between the tumor sample and PDX P2 passage, we also saw a correlation with melanin expression, as shown for PDX1767. PDX tumors derived from tumors with high expression of melanin also had high expression of melanin in the PDX. Likewise, if a tumor did not express detectable melanin, the PDX did not either, as shown for PDX2552 and PDX1668. PDX1595 had a low but detectable level of melanin as did the patient tumor. All tumors and patient-derived PDXs stained positive for Ki-67.

To evaluate the effects of KRT-232 on the melanoma PDX panel, 50 mg/kg KRT-232, which is comparable with a human dose of 250 mg, was administered by oral gavage to the mice once the PDX tumor reached a volume of 50–100 mm³. Mice were treated 5 days/week and treatment was continued until one or more tumors reached the endpoint size limit defined by the IACUC protocol (1.5 cm diameter). We compared the KRT-232 response to an FDA-approved therapy, either dabrafenib (30 mg/kg) and trametinib (1 mg/kg) or trametinib alone (for NRAS-mutant tumors) administered by oral gavage 5 days/week, once daily. For mice harboring mutated BRAF^V600 tumors, dabrafenib and trametinib (D+T) were administered in vivo either with or without 50 mg/kg KRT-232 once daily. The response to all drugs was compared with the appropriate vehicle control group. Toxicity was not detected with any treatment group based on aspartate aminotransferase and alanine aminotransferase levels, weight loss, or morbidity. Representative data from these studies for PDX1839, PDX1946, PDX2316, PDX1668, and PDX1595 are shown in Fig. 2 (data from treatment effects on tumor growth for all the PDX tumors are shown in Supplementary Fig. S2). For each drug study, the tumor growth rate was statistically determined, the final tumor weight was measured, and formalin-fixed paraffin-embedded sections were stained and quantified to measure proliferation based on Ki67 expression. To facilitate comparisons between PDX tumors and the responses to therapy, a summary of t-ratios for treatment group comparisons across 15 PDX tumors is shown in Figs. 2 and 3A. The t-ratio is a ratio of the difference in the slope of tumor growth between control and a treatment group relative to its SE, calculated by estimated marginal means based on the mixed-effect model. For each PDX, response to a drug was based on a positive t-ratio greater than 2.6. The lowest positive t-ratio considered was 2.598 for the KRT-232 treatment of PDX0807, which correlated with an adjusted P value of 0.063. Any treatment that resulted in a decreased tumor growth compared with vehicle control is indicated by a positive t-ratio. Likewise, any treatment which resulted in increased tumor growth compared to vehicle control is indicated by a negative t-ratio.

The response to drug treatment could be classified into three distinct categories. Figure 1A, with PDX1839 as an example, represents those PDX tumors that responded to the standard therapy (dabrafenib and trametinib), but not to KRT-232. This group of PDX tumors is referred to as group I. In fact, in the case of PDX1839, in vivo administration of KRT-232 caused a slight, albeit insignificant, increase in growth (Bonferroni adjusted P = 0.138; Fig. 1A). In contrast, dabrafenib and trametinib, an FDA-approved therapy for BRAF^V600-mutated melanoma, did decrease the growth rate of the group I PDX tumors (t-ratio = 5.4741, P_adj <0.001). The combination of KRT-232 with dabrafenib and trametinib resulted in a further reduction in the growth rate compared with KRT-232 alone treatment (t-ratio = 9.00, P_adj < 0.001), but not compared with dabrafenib and trametinib standard therapy (t-ratio = 1.58, P_adj < 0.7). A decrease in tumor size was also observed when comparing the response to KRT-232 alone versus KRT-232 + dabrafenib and trametinib (P_adj = 0.014). Also shown in Fig. 1, Ki67 levels were not affected by in vivo administration of either KRT-232 or dabrafenib and trametinib (P_adj = 0.714 and 0.184, respectively); however, a significant decrease in Ki67 staining compared with the vehicle control was seen with the combination therapy of KRT-232 and dabrafenib and trametinib (P_adj < 0.001). A significant decrease was also observed when comparing the combination therapy (KRT-232 + dabrafenib and trametinib) to KRT-232 alone treatment (P_adj < 0.001), but not when compared with dabrafenib and trametinib therapy (P_adj = 0.999). In summary, in group I PDX tumors, dabrafenib and trametinib has a predominant effect on decreasing melanoma PDX tumor growth while KRT-232 therapy does not inhibit tumor growth in group I PDX tumors.

The second group of tumors (group II) shown in Fig. 1B includes those PDX tumors that did not respond to either KRT-232 or the standard therapy alone but responded synergistically to the combination of KRT-232 and the standard therapy. Group II was comprised of 6 PDX tumors; five of the six PDX tumor lines exhibited BRAF^V600 mutations. The sixth line, PDX 1179, had an NRAS^Q61 mutation and a BRAF copy number of 1.36 (see Supplementary Table S1B). Therefore, PDX 1179 was treated with trametinib but not dabrafenib. As shown in Fig. 1B, as exemplified with PDX1946, neither KRT-232 nor the standard therapy (dabrafenib and trametinib or trametinib alone) resulted in a significant decrease in either growth rate (P_adj = 0.999) or final tumor size for group II PDX tumors. However, in vivo administration of KRT-232 in combination with the standard therapy, resulted in a significant decrease in the tumor growth rate compared with the vehicle control (t-ratio = 3.75, P_adj = 0.002) and a significant decrease in Ki67-positive cells (Fig. 1B; Supplementary Fig. S2).

The third group of PDX tumors (group III), tumors 0807, 1129, 1595, 1668, 1767, and 2316, did respond to KRT-232 alone with growth inhibition (Fig. 1C and D). Two of the lines, PDX2316 and PDX1767, were BRAF^WT and NRAS^WT so mice were treated only with KRT-232. One line, PDX1595, exhibited an NRAS^Q61R mutation, so the mice implanted with this PDX were treated with either KRT-232, trametinib, or the combination. The final three PDX tumor lines, 0807, 1129, and 1668, had BRAF mutations outside the V600 position (Table 1; Fig. 2), so mice carrying these three PDX tumors were treated with KRT-232 alone, combination dabrafenib and trametinib, and the combination of KRT-232 plus dabrafenib and trametinib (except for 1668, which was only treated with KRT-232 alone or combination dabrafenib and trametinib). PDX2316, PDX1668, and PDX1595 are shown as examples of the three different genetic subgroups within the group that responded to KRT-232 [Fig. 1C (PDX2316) and 1D (PDX1595 and PDX1668)]. For PDX2316, PDX1668, and PDX1595, KRT-232 treatment resulted in a significant decrease in tumor growth rate (P_adj < 0.001 for PDX2316 and 1595 and P_adj = 0.018 for PDX1668), and as shown for PDX2316, KRT-232 alone also decreased the final tumor weight (P_adj = 0.042) and the level of Ki67 staining (P_adj < 0.001). When KRT-232 was used in combination with the standard therapy, as shown in Fig. 1D for PDX1595, the standard therapy alone did not affect the growth rate (P_adj = 0.999), except for PDX0807, and there was no further decrease in growth rate comparing the rate with KRT-232 to the combination therapy (P_adj = 0.999). In summary, in group III PDX tumors, KRT-232 had a predominant effect on tumor growth inhibition that was not enhanced by dabrafenib and trametinib therapy.

KRT-232 previously has been shown to increase p53 protein levels in cell lines and mouse xenografts (28, 29). To determine whether KRT-232 was affecting p53 expression and localization in the melanoma PDX models, the p53 protein level was monitored by IHC in two group III PDX tumors that had been treated in vivo with KRT-232 (Fig. 1D). For both PDX1595 and PDX1668, the p53 protein level was very low in tumors from the vehicle-treated mice, but KRT-232 treatment resulted in a substantial increase in p53 protein and nuclear localization. In contrast, neither dabrafenib or trametinib altered p53 levels or localization.

As exemplified in Fig. 1 and summarized in Fig. 2, the 15 PDXs studied here were classified into three subgroups: group I PDXs did not respond to KRT-232, responded to dabrafenib and trametinib, and treatment with the combination of dabrafenib and trametinib and KRT-232 resulted in a small augmentation of tumor growth inhibition. Group II PDXs did not respond to either KRT-232 alone or dabrafenib and trametinib alone but responded to the combination of KRT-232 and dabrafenib and trametinib. Group III PDXs responded to KRT-232 monotherapy, as indicated by the gray shading. A larger t-ratio indicates that there was a larger difference between the treatment group and the comparison group. Interestingly, PDX 1767 was the only PDX with MDM2 amplification, and this PDX had the largest t-ratio when comparing the effect of KRT-232 with vehicle treatment (t-ratio = 5.182). This finding is consistent with prior findings in glioblastoma cell lines, where lines with MDM2 amplification were the most sensitive to KRT-232 (27).

In the group II PDX tumors, the range of t-ratios for the combined treatment with KRT-232 + dabrafenib and trametinib was 3.028 to 8.106, which is suggestive of a synergistic relationship between KRT-232 and dabrafenib and trametinib treatments. The synergistic effect was defined as an interaction between the treatments that causes the total effect of the drugs to be greater than the sum of the individual effects of each drug. This analysis did not include data from PDX1179, because this NRAS^Q61H tumor was treated only with trametinib, in contrast to the other group II PDX tumors that were treated with dabrafenib and trametinib. The analysis showed a significant interaction effect of KRT-232 and dabrafenib and trametinib for four independent PDX tumors over time (P = 0.004) using the mixed-effect model. With model-based means, tumor growth rate with 95% confidence intervals for each treatment was estimated (Fig. 2B). The multiple comparison graph showed that the tumor growth rate in the combination group (KRT-232 + dabrafenib and trametinib) was significantly reduced compared to either the KRT-232 group (Tukey adjusted P < 0.001) or the dabrafenib and trametinib group (Tukey adjusted P < 0.001). There was no difference in the tumor growth rate between KRT-232 alone and dabrafenib and trametinib groups (Tukey adjusted P = 0.696). In other words, the group II PDX tumors did not respond to KRT-232 or dabrafenib and trametinib alone, but when administered together there was synergistic inhibition of tumor growth. The power of this analysis is based on analyzing treatment effectiveness for multiple independent PDX tumors (Fig. 2).

Interestingly, analysis of H&E staining of those PDX tumors that had the highest t-ratios when comparing the effect of KRT-232 treatment to the effect of KRT-232 + dabrafenib and trametinib revealed morphologic differences after KRT-232 + dabrafenib and trametinib therapy (Fig. 3). H&E staining of tumors isolated from vehicle-treated and dabrafenib and trametinib–treated cells revealed that the tumor cells were tightly packed with minimal stroma, were of uniform size and appearance, and had large nuclei with a high mitotic rate and a high Ki67 expression. In contrast, PDX tumors exhibiting a synergistic growth-inhibitory response to KRT-232 and dabrafenib and trametinib were characterized by mostly karyorrhectic nuclei with vacuolar changes around the karyorrhectic debris. This change in histology was only present in PDX tumors where the t-ratio comparing the effect of KRT-232 treatment to the effect of KRT-232 combined with dabrafenib and trametinib was greater than 2.6 (PDX1351 and 1946).

To identify changes in protein expression associated with the synergistic response to KRT-232 and dabrafenib and trametinib in group II tumors, RPPA analysis of protein and phosphoprotein expression was conducted (Fig. 3B). Unexpectedly, protein markers for different modalities of cell death, including bcl-2–like protein 4 (BAX), B-cell lymphoma 2 (BCL2), p53-upregulated modulator of apoptosis (PUMA), PARP, beclin, janus kinase (JAK), induced myeloid leukemia cell differentiation protein (MCL1), and the caspase, STAT, and HSP families of proteins, while present in the antibody panel, were notably absent from the list of positive hits when comparing vehicle-treated PDX tumors with KRT-232 + dabrafenib and trametinib–treated tumors. In contrast, a decreased expression of hypoxia-inducible factor 1 subunit alpha (HIF-1α), monocarboxylate transporter 4 (MCT4), phosphorylated N-myc downstream-regulated gene-1 (pNDRG1), and phosphorylated MAPK (pMAPK) was noted in the KRT-232 + dabrafenib and trametinib treatment group compared with vehicle-treated tumors. Lactate dehydrogenase A (LDHA) was also decreased, although the fold change was small and below the cutoff of log₂(FC) = ± 0.4. The decreased levels of phosphorylated MAPK were expected because these tumors were treated with dabrafenib and trametinib, both of which regulate the phosphorylation of MAPK. In contrast, in response to the combination of KRT-232 and dabrafenib and trametinib, the observed decreased expression of HIF-1α, MCT4, LDHA, and decreased phosphorylation of NDRG was unexpected and indicated treatment-mediated decreased rates of glycolysis (52–54). The change in expression of HIF-1α, pNDRG, and LDHA was only seen in PDX tumors treated with the combination of KRT-232 and dabrafenib and trametinib (group II: PDX1179, 1351, and 2252) where synergy was exhibited. Changes in MCT4 expression were also observed when KRT-232 was used as a single agent (Fig. 4D and E). Furthermore, group I PDX tumors 1839, 2195, and 2252 responded to dabrafenib and trametinib as a single agent, and exhibited decreased phosphorylation of MAPK, but did not exhibit altered expression of HIF-1α, MCT4, or LDHA, nor was there a decrease in phosphorylation of NDRG in response to dabrafenib and trametinib without KRT-232 (Supplementary Fig. S3). These data suggest that the synergistic action of KRT-232 and dabrafenib and trametinib results in metabolic reprogramming of the tumor cells.

To identify potential biomarkers for KRT-232 response, we examined both the genetic mutation and copy-number variation data obtained by NGS and RPPA analysis (Fig. 4). Analysis and comparison of basal (vehicle-treated) protein and phosphoprotein expression in PDX tumors that were either resistant or responsive to KRT-232 did not identify any significant proteins or phosphoproteins (FDR >0.05) that could be used as predictors of KRT-232 responsiveness, as shown in the Volcano Plot comparing vehicle-treated samples from PDX tumors in groups I and II compared with those in group III (Supplementary Fig. S4). While protein expression patterns were not a predictor of KRT-232 responsiveness, the BRAF mutation status was a strong predictor of KRT-232 responsiveness.

The Oncoprint Cluster Analysis shown in Fig. 4 represents the analysis with the 10 most relevant genetic alterations, as discussed in Table 1. No further insights were gained by including all 300 genes analyzed by NGS (data not shown). This analysis indicates that the mutational status of BRAF is highly correlated with responsiveness to KRT-232. Of the 9 PDX tumors that were resistant to KRT-232 (groups I and II), all but one had a V600 mutation in BRAF (Table 1).

In contrast to the high prevalence of V600 BRAF mutations in the PDX tumors that were resistant to KRT-232, all of the PDX tumors that responded to KRT-232 lacked the BRAF^V600 mutation, although other mutations were noted in the BRAF gene. PDX1129 had two coding changes (D594N and K483T) and PDX1668 and 1595 had missense mutations of unknown significance. For PDX1668, the two nonsynonymous BRAF mutations were S147N and N140T, and for PDX1595 the BRAF mutation was P334S. While there are reports of the D594N mutation in melanoma, colorectal, and lung carcinomas and hairy cell leukemia, none of the other mutations have been reported and there are no data on the biological significance of these mutations (43–45). Amplification of the BRAF gene also occurred in the PDX tumors, but occurred in equal percentages in both the PDX tumors that were resistant to KRT-232 (3/9 or 33.3%) and those that were sensitive (2/6 or 33.3%). Statistical analysis of the correlation between the BRAF^V600 mutation and the in vivo effectiveness of KRT-232 in decreasing tumor growth, as measured by the t-ratio, was analyzed using the Wilcoxon rank sum test and Pearson product-moment correlation. The Point–Biserial correlation coefficient (a special case of Pearson correlation coefficient) was −0.7938, with a Bonferroni-adjusted P value of <0.001. A dot plot showing the correlation is shown in Supplementary Fig. S5.

RPPA analysis of group III PDX tumors (1129, 1595, 1668, and 2316) revealed altered levels of six proteins in KRT-232 monotherapy-responsive tumors, based on the limits of an FDR < 0.5 and log₂(FC) > ± 0.4. The p53-inducible p21 protein (CDKN1A) exhibited the most significant increase in expression in response to KRT-232 treatment. The other notable protein induced by KRT-232 was the receptor tyrosine kinase ephrin type-A receptor 2, also known as erythropoietin-producing hepatocellular receptor A2 (EPHA2), which has been reported to play a critical role in oncogenic signaling in many types of solid tumors (55). This increase in EPHA2 was offset by KRT-232–induced decreases in the cell cycle–regulatory protein Cyclin B1 (CCNB1), polo-like kinase 1 (PLK1, which belongs to the CDC5/Polo subfamily), and forkhead box protein M1 (FoxM1; refs. 56, 57). These three proteins are involved in the regulation of M-phase of the cell cycle (refs. 58, 59; Fig. 4D and E). Finally, the MCT4, which releases lactate from glycolytic tumors (60), was decreased by KRT-232 treatment. Altogether, these changes in protein expression in response to KRT-232 should result in a reduction in tumor growth.

Interestingly, RPPA analysis of PDX tumors that did not respond to KRT-232 treatment had a similar increase in p21 expression (Fig. 4B and C), but the increase in p21 was not accompanied by significant changes in the downstream pathways regulated by MDM2 including cell-cycle–regulatory proteins or proteins involved in the regulation of apoptosis (61). Because all these PDX tumors have activating mutations in the MEK/ERK pathway, these data suggest that activation of BRAF or NRAS interferes with the pathways associated with the growth-inhibitory effects of KRT-232.

Detailed analysis of the TP53 status in the panel of 15 melanoma PDX tumors revealed 6 PDXs had either a nonsynonymous mutation in the TP53 gene and/or a loss of heterozygosity (Table 1A and B; Supplementary Table S1B). As shown in Fig. 2A, the PDX tumors with alterations in TP53 status still responded to KRT-232 either as a single agent (PDX0807 and PDX1668) or in combination with dabrafenib and trametinib (PDX2252 and PDX1946), but the response was considerably reduced compared with the TP53^WT tumors and was at the lower limits of significance. For example, PDX0807 and PDX1668, both of which responded to KRT-232 as a single agent had t-ratios of 2.598 and 2.829, respectively, while the TP53^WT PDX tumors in group III (PDX 1595, 2316, 1129, and 1767) had t-ratios greater than 3.5 (Fig. 2), indicating stronger inhibition of tumor growth in TP53^WT tumors.

BRAF^V600-mutant melanoma tumors often develop resistance to MAPK inhibitors like dabrafenib and trametinib. We postulated that dabrafenib and trametinib–resistant tumors might respond to a BCL-2 inhibitor to block tumor growth and proliferation through an alternate pathway. Indeed, it has been demonstrated that combining the MDM2 inhibitor, idasanutlin RG7388, with the BCL-2 inhibitor, ABT-199, provides better therapeutic efficacy than either drug alone in acute myeloid leukemia (AML; ref. 62). To determine whether similar effects occur in melanoma, two BRAF^MUT and two BRAF^WT tumors were treated with navitoclax (100 mg/kg), a BCL-2 inhibitor, either as a single agent or in combination with KRT-232. The summary data for navitoclax treatment are shown in Fig. 5C. Navitoclax slightly enhanced tumor growth for two PDX tumors (PDX1351 and 1577), as indicated by the negative t-ratio. While navitoclax was not effective as a single agent in any PDX tumor, navitoclax in combination with KRT-232 in BRAF^V600E (PDX1351 and 1577) tumors was more effective than either drug alone and resulted in tumor regression in three PDX models, as shown by example for PDX1577 (Fig. 5). Interestingly, the growth of only mutant BRAF^V600E tumors was inhibited by the combination of navitoclax and KRT-232. In BRAF^V600WT tumors (PDX1129 and PDX1668), the effects of KRT-232 and navitoclax were not more effective than KRT-232 alone as indicated by a t-ratio of less than 2.6 when comparing KRT-232 + navitoclax treatment groups to KRT-232 alone. Similar effects were noted in the weights of the final tumors.

While recent therapeutic advances for metastatic melanoma have significantly increased the overall survival of patients with melanoma, a subset of patients does not respond to immunotherapy or targeted therapies. In this study, utilizing a panel of melanoma PDX tumors, we observed that therapy with KRT-232, based upon mutational status of the tumors, either singularly or in combination with dabrafenib and trametinib treatment effectively decreased tumor growth in 100% of the tumors tested. Similar results were obtained in a small phase I/II clinical trial testing KRT-232 with trametinib and/or dabrafenib (NCT02110355), where patients with TP53^WT metastatic cutaneous melanoma were treated with KRT-232 at 120, 180, or 240 mg once daily (7 days of each 3-week cycle) in combination with trametinib (BRAF^nonV600MUT) or dabrafenib and trametinib (BRAF^V600MUT). KRT-232 + trametinib was found to reduce tumor size in 73% of the patients with metastatic cutaneous melanoma expressing BRAF^nonV600MUT, with 13% (2/15) showing a greater than 30% reduction in size according to the RECIST criteria (63). Furthermore, 100% (6/6) of patients with BRAF^V600-mutant melanoma treated with KRT-232 in combination with trametinib or dabrafenib had a reduction in tumor size, with 67% (4/6) of patients having a decrease in tumor size of greater than 30%. On the basis of preliminary results, the KRT-232 MTD was 180 mg, based on observed adverse effects at 240 mg in the KRT-232 + trametinib treatment arm. The incidence of adverse effects was notable, albeit acceptable, with 1 patient having a grade 3 adverse event and all remaining patients have either a grade 1 or grade 2 adverse event (64). Similarly, based on the calculations described by Nair and Jacob (65), the human equivalent dose for 50 mg/kg KRT-232 used in mice is approximately 250 mg KRT-232 for an average 62 kg individual.

In our study, tumors responding to KRT-232 plus dabrafenib and/or trametinib could be classified into three separate groups. Group I consisted of BRAF^V600E-mutant PDX tumors, which responded to dabrafenib and trametinib but not to KRT-232 as a single agent. In combination, these agents further inhibited tumor growth. Group II consisted of BRAF^V600E/M and NRAS^Q61H-mutant tumors that did not respond to either KRT-232 or dabrafenib and/or trametinib alone, but when used in combination, the inhibition of tumor growth was demonstrated to be statistically significant and synergistic. Finally, in group III, the BRAF^V600WT PDX tumors responded to KRT-232 alone with significant inhibition of tumor growth. The mutational status of BRAF was an effective predictor of KRT-232 monotherapy response. In our PDX panel, only those tumors that were BRAF^V600WT were responsive to KRT-232 alone, while tumors with BRAF^V600 mutations (except for PDX1179) were resistant to KRT-232, but responded synergistically to KRT-232 combined with dabrafenib and trametinib.

In another tumor type, acute myeloid leukemia (AML), Pan and colleagues reported that some AML cell lines are sensitive to the MDM2 inhibitor, RG7388 (idasanutlin), which is a more potent second-generation nutlin, while other AML cell lines were resistant (62). As seen with KRT-232, in both the RG7388-sensitive and -resistant cell lines, the protein level of p21 is abundantly induced. Through a series of elegant experiments using RG7388 in combination with a Bcl-2 inhibitor, ABT-199 (venetoclax), they demonstrated that p53 plays a pivotal role in regulating the Ras/Raf/MEK/ERK signaling cascade (62). While Pan and colleagues did not explore the mechanistic role of p53 in regulating the MAPK pathway, others have identified p53-regulated transcription of four phosphatases [wild-type p53-induced phosphatase 1 (Wip1), mitogen-activated protein kinase phosphatase 1 (MKP1), phosphatase of activated cells 1 also known as dual specificity phosphatase 2 (PAC1/DUSP2), and DUSP5] that negatively regulate MAPK signaling (66). While further experiments are needed, we propose that in tumors with BRAF^V600 mutations, activation of p53 through MDM2 inhibition will not inhibit the MAPK pathway; therefore, those tumors with BRAF^V600 mutations are resistant to the effects of KRT-232 and other MDM2 inhibitors. However, in the presence of dabrafenib and trametinib, two inhibitors of the MAPK pathway, inhibition of the constitutively activated MAPK pathway reverses the resistance to MDM2 inhibition, resulting in a decrease in MAPK T202/Y204 phosphorylation. The MAPK pathway is also a key regulator of the transcription factor MYC through both phosphorylation and transcription control (67–70). While our RPPA panel did not include p-Myc or N-Myc, NDRG1 (an N-Myc downstream–regulated gene) was decreased by KRT-232 plus dabrafenib and trametinib treatment. In addition, Myc has been shown to stabilize HIF-1α (71). Consistent with the concept that KRT-232 plus dabrafenib and trametinib treatment downregulates Myc-mediated transcription, we observed a decrease in HIF-1α in KRT-232 plus dabrafenib and trametinib–treated BRAF^V600 tumors. Therefore, our studies suggest that the treatment of melanoma PDX tumors expressing the activating BRAF^V600 mutation with the combination of KRT-232 + dabrafenib and trametinib, modulates MYC and HIF-1. These proteins play a key role in the regulation of the Warburg phenomenon (72–75) and are key regulators of the glycolytic switch in tumors (76).

It has also been reported that like dabrafenib and trametinib, Bcl-2 inhibitors can overcome the resistance to MDM2 inhibitors (62). Preclinical studies have shown that mice implanted with OCL-AML3 leukemic cells that are resistant to both the MDM2 inhibitor, RG7388, and the Bcl-2 inhibitor, ABT-199, exhibited enhanced overall survival with the two agents combined. Similarly, we observed that treatment of BRAF^V600-mutant PDX tumors PDX1351 and 1577 (that are resistant to KRT-232) with KRT-232 combined with navitoclax significantly inhibited tumor growth when neither agent was effective alone. These data suggest that, as in AML, cotreatment with Bcl-2 inhibitors can overcome the resistance to MDM2 inhibitors in tumors in which the MAPK pathway is constitutively activated. It is interesting to note that in the PDX tumors that were treated with KRT-232 and navitoclax or KRT-232 and dabrafenib and trametinib, the combination of KRT-232 with navitoclax was more effective and not only inhibited tumor growth but caused tumor regression.

While the combination of KRT-232 plus dabrafenib and trametinib in BRAF^V6000MUT tumors resulted predominantly in a decreased expression of key proteins involved in the regulation of glycolysis, KRT-232 monotherapy treatment of BRAF^V600WT tumors resulted in a decrease in expression of a triad of proteins regulating the G₂–M checkpoint in the cell cycle. The G₂–M DNA damage checkpoint serves to prevent the cell from entering mitosis (M-phase) with genomic DNA damage and the key regulators of this process are FoxM1, PLK1, and Cyclin B1, all of which were decreased by KRT-232 treatment. FoxM1 expression is increased in a variety of solid tumors, including melanoma, and inhibition of FoxM1 leads to a decrease in cell proliferation and migration, metastasis, and angiogenesis. Furthermore, analysis of the TCGA database illustrated that high levels of FoxM1 are related to poor prognosis in most solid tumors (58). p53, both directly and indirectly through p21, has been reported to decrease FoxM1 expression (77, 78). FoxM1 induces the expression of the Cdk1 activators, cyclin B and Cdc25 (79), so a decrease in FoxM1 expression should coincide with a decrease in cyclin B and Cdc25, as we observed in the RPPA data. Interestingly, cyclin B and polo-like kinases (PLK) are proposed as critical transcriptional targets of FoxM1 at the G₂–M transition and PLK1 phosphorylates FoxM1 to further activate it as a transcription factor (59, 80). Therefore, KRT-232, through the p53-dependent inhibition of FoxM1 expression, has a direct effect in regulating the G₂–M checkpoint.

It is important to note that the tumors used in this study were heterogeneous and all PDX tumors included some mouse and potentially human stromal tissue. The lack of homozygosity for driver mutations likely reflected the heterogeneous nature of tumors instead of the presence of nontumor tissue within our samples because the NGS panel was specific for human genes, although we cannot fully rule out a contribution of stroma to wild-type allele detection (Supplementary Fig. S1B). Similar heterogeneity was seen with TP53. In this study, we included four PDX tumors with mutations in TP53. Only one of the lines, PDX9164, had a heterozygous TP53 mutation, with a frequency of 1, at codon 192 (Q192*) and this mutation has a FATHMM pathogenic score of 0.93 suggesting it is highly pathogenic. The other mutations occurred at lower frequencies: 0.265 for PDX0807 (A138ADG and T140S); 0.607 for PDX2252 (R196*); and 0.484 and 0.235 for PDX1839 (R306* and Y236H). This heterogeneity complicates the interpretation of the effectiveness of KRT-232 in TP53-mutant versus wild-type tumors. It is interesting to note, however, that while KRT-232 was somewhat effective in melanoma PDX tumors with mutant TP53, the effect was at the lower limit of significance. Furthermore, while TP53^MUT and BRAF^V600 mutant, PDX9164, did not respond to KRT-232 monotherapy, it did respond synergistically to KRT-232 plus dabrafenib and trametinib. Similar results were noted in a phase I trial of RG7112, a member of the Nutlin family of MDM2 inhibitors, in leukemia. In this study, 3 of 19 patients with TP53 mutations showed evidence of response to RG7112 as demonstrated by a decrease in peripheral blast count and one patient was reported to have stable disease for more than 2 years (81). While neither study was designed to specifically address the effectiveness of KRT-232 in TP53-mutant tumors, these data suggest that KRT-232 may have limited effectiveness in TP53-mutant tumors.

We demonstrate here that 60% of melanoma PDX tumors have an inherent resistance to KRT-232 and this correlates with the incidence of BRAF^V600 mutations. In this study, of the eight BRAF^V600-mutant PDX tumors treated with dabrafenib and trametinib, five (62.5%) were resistant to dabrafenib and trametinib. Two of the five resistant PDX tumors came from patients previously treated with dabrafenib and trametinib who had progressed on treatment. In these two MAPKi-resistant PDX tumors, the resistance is undoubtedly acquired. The study of MAPKi-resistant melanoma has been extensively studied and the mechanism of resistance is complex and multifactorial. The causative factors that contribute to MAPKi resistance can be broadly classified into three categories: mutational events and nonmutational events, which are tumor inherent and lead to either MAPK pathway reactivation or activation of a parallel signaling pathway, and changes in the surrounding microenvironment (82–84). On the basis of the pleiotropic nature of drug resistance it is interesting, although not surprising, that the two PDX tumors previously treated with dabrafenib and trametinib remained resistant. It is also interesting that none of the BRAF^V600E-mutant tumors that responded to dabrafenib and trametinib were derived from patients who had prior exposure to dabrafenib and trametinib.

Overall, our results demonstrate the efficacy of the MDM2 antagonist as a single agent or as a part of a therapeutic combination with either MAPK pathway or Bcl-2–targeting agents in preclinical melanoma models. We have previously shown in preclinical studies that melanoma tumors exhibit a limited response to CDK4/6 inhibitors but the addition of an MDM2 antagonist results in significantly increased inhibition of tumor growth (85). Notably, tumors that acquired resistance to the current standard-of-care approaches such as immunotherapy and BRAF/MEK–targeted therapy, are responsive to the MDM2 antagonist given alone or as a part of combination treatment. These findings support the clinical development of MDM2 antagonists as a second-line treatment for metastatic melanoma.

K.B. Dahlman reports receiving other commercial research support from Kadmon Holdings, LLC. G.D. Ayers reports receiving commercial research grants from Incyte. D.B. Johnson is an employee/paid consultant for Array Biopharma, Bristol-Myers Squibb, Jansen, Merck, and Novartis, and reports receiving commercial research grants from Bristol-Myers Squibb and Incyte. No potential conflicts of interest were disclosed by the other authors.

Conception and design: R.L. Shattuck-Brandt, E. Murray, G.D. Ayers, A.E. Vilgelm, A. Richmond

Development of methodology: E. Murray, G.D. Ayers, A.E. Vilgelm

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): R.L. Shattuck-Brandt, C.A. Johnson, J.F. O'Neal, V. Bharti, K.B. Dahlman, M.C. Kelley, R.M. Kauffman, M. Hooks, A. Grau, D.B. Johnson

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): R.L. Shattuck-Brandt, S.-C. Chen, E. Murray, R.N. Al-Rohil, K.B. Dahlman, G.D. Ayers

Writing, review, and/or revision of the manuscript: R.L. Shattuck-Brandt, S.-C. Chen, E. Murray, K.B. Dahlman, G.D. Ayers, R.M. Kauffman, A. Grau, D.B. Johnson, A.E. Vilgelm, A. Richmond

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): R.L. Shattuck-Brandt, E. Murray, C.A. Johnson, C.A. Nebhan, K.B. Dahlman, C. Yan

Study supervision: R.L. Shattuck-Brandt, E. Murray, A. Richmond

Other (tissue/blood sample collection): H. Crandall

Other (interpretation and analysis of results): A. Richmond

Animal husbandry and animal care was performed by the Division of Animal Care, Vanderbilt University Medical Center (https://www.vumc.org/acup/system/files/DAC%20Brochure.pdf). Histology and immunostaining were performed in the Translational Pathology Shared Resource at Vanderbilt University Medical Center, supported by NCI/NIH Cancer Center Support Grant 2P30 CA068485-14 and the Vanderbilt Mouse Metabolic Phenotyping Center Grant 5U24DK059637-13 (https://www.vumc.org/tpsr/30962). The authors wish to acknowledge helpful discussions with Drs. Kelli Boyd and Lauren E. Himmel. Whole slide imaging and quantification of immunostaining were performed in the Digital Histology Shared Resource at Vanderbilt University Medical Center (www.mc.vanderbilt.edu/dhsr). NGS was provided by Vanderbilt Technologies for Advanced Genomics (VANTAGE: http://vantage.vanderbilt.edu/). RPPA analysis was performed at the Reverse Phase Protein Array (Core Facility at MD Anderson Cancer Center). This facility is funded by NCI# CA16672. The DNA extraction was performed in the Vanderbilt Innovative Translational Research Shared Resource supported by the Vanderbilt-Ingram Cancer Center (5P30CA068485-21), the TJ Martell Foundation, and the Robert J. Kleberg, Jr. and Helen C. Kleberg Foundation. Short tandem repeat (STR) profiling was performed by the Interdisciplinary Center for Biotechnology Research at the University of Florida. The authors wish to acknowledge the technical expertise of the Gene Expression and Genotyping Core of the Interdisciplinary Center for Biotechnology at the University of Florida, Gainesville for performing the STR Assay. Human melanoma samples were obtained through the Melanoma BioRepository supported by James C. Bradford Jr. Melanoma Fund. 5P30 CA068485-S3, CA116021 (to A. Richmond), VA SRCS Award (to A. Richmond), NCI-K23CA204726 (to D.B. Johnson), Harry J Lloyd Charitable Trust (to A.E. Vilgelm), BCRF IIDRP-16-001 (to A.E. Vilgelm), NCI-R37CA233770 (to A.E. Vilgelm).

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.