Older patients with melanoma (>50 years old) have poorer prognoses and response rates to targeted therapy compared with young patients (<50 years old), which can be driven, in part, by the aged microenvironment. Here, we show that aged dermal fibroblasts increase the secretion of neutral lipids, especially ceramides. When melanoma cells are exposed to the aged fibroblast lipid secretome, or cocultured with aged fibroblasts, they increase the uptake of lipids via the fatty acid transporter FATP2, which is upregulated in melanoma cells in the aged microenvironment and known to play roles in lipid synthesis and accumulation. We show that blocking FATP2 in melanoma cells in an aged microenvironment inhibits their accumulation of lipids and disrupts their mitochondrial metabolism. Inhibiting FATP2 overcomes age-related resistance to BRAF/MEK inhibition in animal models, ablates tumor relapse, and significantly extends survival time in older animals.
These data show that melanoma cells take up lipids from aged fibroblasts, via FATP2, and use them to resist targeted therapy. The response to targeted therapy is altered in aged individuals because of the influences of the aged microenvironment, and these data suggest FATP2 as a target to overcome resistance.
See related commentary by Montal and White, p. 1255..
This article is highlighted in the In This Issue feature, p. 1241
INTRODUCTION
Melanoma, like many other cancers, is a disease of aging, with incidence rising rapidly with age, and survival worsening even when controlling for tumor grade and stage (1). Melanoma is the rarest yet deadliest form of skin cancer, with an estimated 6,850 deaths in the United States in the year 2020 alone (2). In contrast to other cancers, such as breast and lung cancers, where incidence has been steadily decreasing, melanoma incidence has been on the rise for the past 40 years and has increased by 3% from 2006 to 2015 in men and women older than 50, with a median age of diagnosis of 62 (3). In addition, older patients have more metastases, worse overall survival, and worse response to targeted therapy relative to their younger counterparts (4–6).
Targeted therapy in melanoma centers on targeting the MAPK kinase signaling pathway, as mutations in the BRAF oncogene drive melanoma in a majority of patients. Although patients with melanoma initially respond to the standard of care of targeted therapy (BRAF and MEK inhibitors), resistance soon develops in most patients. One of these well-established mechanisms of resistance is metabolic reprogramming, characterized by lower glycolytic and bioenergetic metabolism (7). Specifically, in melanoma it has been shown that cells utilize glutamine or fats to escape therapy. In a recent study, BRAF-mutant melanoma was shown to rely on oxidative phosphorylation for therapy escape. This forced the cancer cells to rely on glycolysis instead of oxidative phosphorylation via mitochondrial DNA depletion and sensitized the melanoma cells to BRAF inhibition (8). In addition, these cells have different metabolic dependencies, which involve inflammatory lipid metabolism through PGE2 or mitochondrial phosphatidylcholine (PC) activity (7).
To determine the underlying mechanisms of age-related tumor progression and response to therapy, we have engineered artificial skin reconstructs built from dermal fibroblasts taken from individuals in their 20s (young) or 60s (aged). We have recently discovered that aged dermal fibroblasts play a significant role in driving melanoma metastasis and poorer response to targeted therapy (4) in cell culture experiments, syngeneic mouse models of melanoma, and melanoma patient samples (4). In this study, we show that that melanoma cells require fatty acids secreted by aged fibroblasts to escape targeted therapy.
Fatty acid uptake and subsequent fatty acid oxidation (FAO) play important roles in tumor cell survival and metastasis (9). In tumors that are not heavily dependent upon glycolysis, FAO is thought to be the most critical bioenergetic pathway. Because therapy-resistant melanomas have been shown to switch to a less glycolytic pathway, we hypothesize that fatty acid uptake may play a role in the bioenergetics of these cells as well, and contribute to the observed age-dependent resistance of tumor cells to targeted therapy. The uptake of fatty acids in melanoma cells occurs through fatty acid transporters, in particular a family that consists of fatty acid transporters 1–6 (FATP1–6). FATP1 has previously been implicated in melanoma progression, where it was found that adipocytes transfer lipids to the melanoma cells through FATP1, driving invasion and metastasis (10). Here, we find that FATP2 expression is consistently upregulated in tumor cells in an aged microenvironment and represents the only member of the FATP family to significantly correlate with patient age. FATP2 is critical for esterification of long chain fatty acids into triglycerides (TG), and acts as both a synthetase and transporter of fatty acids. Our data identify that targeting FATP2 ablates the uptake of lipids and renders melanoma cells in an aged microenvironment sensitive to targeted therapy. Overall, these data support the critical importance of understanding the role of the aged microenvironment in the efficacy of treatment for patients with melanoma.
RESULTS
In this study, we examined the metabolic changes in the aged microenvironment and how they affect tumor cells. We found that aged fibroblasts have increased levels of neutral lipids as defined by BODIPY 505/515 staining and higher fatty acid synthase (FASN) than young fibroblasts (Supplementary Fig. S1A). We quantified and confirmed this increase in BODIPY by flow cytometry (Supplementary Fig. S1B). To examine this further, we performed lipidomics analysis of young (<35) and aged (>55) fibroblasts, as well as the lipid secretome of these fibroblasts. We show here the simplified lipidomes, and complete lipidomes are available upon request. In analyzing the fibroblasts themselves, we found that although the overall levels of lipid classes did not differ significantly among young and aged fibroblasts, individual lipid species differed extensively (Fig. 1A). We found 257 of 853 identified lipid species differed significantly (>1.5-fold change with an FDR < 10%), with 129 elevated and 128 decreased lipid species in aged fibroblasts (Fig. 1B). Most of the greatest increases were in phosphatidylglycerols (PG) that contained at least one polyunsaturated fatty acid (PUFA), and overall the vast majority of PGs and all lysophosphatidylglycerols (LPG) that significantly increased had a PUFA. Furthermore, the vast majority of PC and phosphatidylethanolamine species that significantly decreased had ether-linked fatty acids. This is particularly intriguing as peroxisomes are required for the biosynthesis of ether-linked phospholipids, and we have previously published that reactive oxygen species (ROS) are increased in the aged tumor microenvironment. Furthermore, molecules that regulate ROS such as SOD3 and peroxiredoxin were decreased (4). These results suggest that peroxisome function may be impaired in aged fibroblasts, consistent with previous work on age-related diseases (11). Other noteworthy changes included ceramides, where most ceramides (11/14) and all glycosylceramides (6/6) that changed were increased in the aged fibroblasts, and we explore this further below.
Because our interests are focused on the microenvironment conferred by the lipid secretome of fibroblasts and its subsequent effects on tumor cells, we next profiled the lipids in young and aged fibroblast conditioned media (CM). Here, we identified 134 lipids and found that 15 changed significantly between CM from young and aged fibroblasts (>1.5-fold change and FDR < 10%). The most significant enrichment was for lipids from the ceramide class (including glycosylceramides; Fig. 1C and D). This is curious, given that previous studies have shown that during aging keratinocytes decrease their ability to make sphingolipids (12, 13), including ceramides, which are critical for maintaining the water impermeability of the skin. These findings suggest that dermal fibroblasts may attempt to compensate for the decline in keratinocyte-produced ceramides by increasing ceramide production. Whether or not fibroblast-derived ceramides are as effective as those produced by keratinocytes remains to be investigated.
To determine whether melanoma cell lipid levels were affected by lipids in their immediate microenvironment, melanoma cells were treated in vitro with aged fibroblast CM and examined for lipid accumulation. Melanoma cells increased their levels of lipids as compared with the same cells treated with young fibroblast CM (Fig. 1E; quantification in Supplementary Fig. S1C, and additional cell lines, including BRAF-mutant lines, Supplementary Fig. S1D and S1E, and NRAS-mutant lines, Supplementary Fig. S1F and S1G). Tumors in aged mice in vivo also had elevated lipid levels as demonstrated by perilipin staining (Supplementary Fig. S1H). To determine whether the source of lipids in the melanoma cells was because of the increased fatty acid synthesis in the melanoma cells, or whether the lipids in the melanoma cells were directly transported from the aged fibroblasts, we took multiple approaches. We first treated melanoma cells with an acetyl CoA carboxylase inhibitor, ND646 (to inhibit fatty acid synthesis), in the presence of either young or aged fibroblast CM. We found that melanoma cells treated with ND646 in either media alone or with young fibroblast CM underwent significant cell death (Fig. 1F). In contrast, when we repeated this experiment in the presence of aged fibroblast CM, cell death was significantly decreased, suggesting that the melanoma cells in the aged media did not depend on fatty acid synthesis as the only source of endogenous lipids (Fig. 1F). We then knocked down FASN in the aged fibroblasts (Supplementary Fig. S1I) and showed that they no longer synthesized lipids as effectively (Supplementary Fig. S1J). Melanoma cells incubated in the CM of FASN-deficient fibroblasts no longer stained positive for lipids (Fig. 1G; additional lines in Supplementary Fig. S1K, quantified in Supplementary Fig. S1L), suggesting that at least some of the lipids accumulating in melanoma cells might be fibroblast-derived. In addition, we treated young and aged fibroblasts with the orange-red fluorescent C 12-fatty acid BODIPY 558/568 (Thermo Fisher Scientific), a synthetic precursor of fluorescent phospholipids (14). We trypsinized and washed the fibroblasts several times to ensure that any unincorporated fluorescent BODIPY was eliminated, and then incubated the BODIPY-labeled fibroblasts with GFP-tagged melanoma cells and visualized them over time. We observed that melanoma cells took up more BODIPY 558/568 from the aged fibroblasts than from the young (Fig. 1H, final timepoint; Supplementary Fig. S1M, Supplementary Movies SM1 and SM2). We also observed that when using CM from the young and aged fibroblasts a similar uptake could be seen, suggesting that the lipids are being secreted by aged fibroblasts and taken up by the melanoma cells, and do not require direct cell-to-cell contact (Supplementary Fig. S1N).
Because melanoma cells were thriving despite accumulating excess lipid, this suggested that the fatty acids were being packaged into neutral lipids such as TGs. To determine whether this was the case, we first stained melanoma cells exposed to young and aged fibroblast CM with LipoTox dyes that can distinguish between phospholipids (green) and neutral lipids (red). We found that both phospholipids and neutral lipids were increased in melanoma cells exposed to aged but not young fibroblast CM (Supplementary Fig. S2A), and TG synthesis was also increased (Supplementary Fig. S2B). This was further confirmed by our lipidomics data, where we treated the melanoma cells with young and aged fibroblast CM, and then analyzed the lipidome of the melanoma cells. As with the fibroblasts alone, melanoma cell size was significantly enlarged when exposed to aged CM (Supplementary Fig. S2C), and normalizing to total protein minimized any observed changes (Supplementary Fig. S2D). However, when normalized to cell volume, the melanoma cell intracellular lipidome largely reflected the changes observed in the fibroblast lipid secretome and highlighted an accumulation of neutral lipids such as ceramides, and TGs (Fig. 1I).
To determine how lipids were being transported into the melanoma cells from the fibroblast media, we examined the expression of fatty acid transporters and identified FATP2 as the fatty acid transporter most affected by the aged microenvironment. FATP2 is primarily responsible for the transport of very long chain fatty acid (15, 16), and has the dual function of facilitating the import of exogenous fatty acid (17) and the activation of fatty acid by its intrinsic acyl-CoA synthase activity, which is a key step in the production and utilization of lipids (18, 19). Melanoma cells exposed to aged fibroblast, but not young fibroblast, CM upregulated their levels of FATP2 (Fig. 2A). FATP1 has previously been implicated in melanoma metastasis (10), but showed no age dependency in its expression in our studies. Using The Cancer Genome Atlas (TCGA) database, we analyzed FATP family members 1–6 in primary melanomas and found FATP2 to be very significantly increased in primary melanomas in aged individuals (Fig. 2B), whereas FATP1, 3, 4, and 5 were not significantly different between young and aged (Fig. 2C). FATP6, although reaching significance (higher in aged), is not highly expressed in melanoma and is specific to cardiac tissue. Because melanoma metastasizes to the heart, it is interesting that FATP6 is elevated in a small subset of primary melanomas. Other fatty acid transporters, such as CD36, were not significantly upregulated in an age-specific manner. To further examine the specificity of FATP2 in age-dependent accumulation of lipids, we knocked down FATP2 in melanoma cells (Supplementary Fig. S3A) and decreased the accumulation of lipids in melanoma cells exposed to aged fibroblast CM (Fig. 2D, top; additional cell lines in Supplementary Fig. S3B). Conversely, knockdown of FATP1 in melanoma cells (Supplementary Fig. S3C) did not affect lipid accumulation in an aged microenvironment (Fig. 2D, bottom; additional cell lines in Supplementary Fig. S3D, quantified in Supplementary Fig. S3E).
We built artificial skin reconstructs as described previously (4) using either young or aged fibroblasts to create a young or aged microenvironment for the same melanoma cell lines. We found that FATP2 was increased in the melanoma cells grown in aged skin reconstructs (Fig. 2E). We also examined FATP2 expression in tumors in aged mice and found increased FATP2 as compared with tumors in young mice (Fig. 2F). This observed effect could also be recapitulated using lipofermata (19), a drug that specifically targets FATP2. Upon treatment with lipofermata, lipid accumulation was decreased both in melanoma cells in an aged microenvironment (Fig. 2G; quantified in Supplementary Fig. S3F) and in Yumm1.7 tumors grown intradermally in aged mice (Fig. 2H). These data point to a key mechanistic role for FATP2 in the age-dependent accumulation of lipids in melanoma cells.
Clinically, there also has been much interest in targeting FASN in tumors, and FASN inhibition has been shown to inhibit tumor regrowth after antiangiogenic therapy (20). There are data suggesting that melanoma cells alter metabolism to resist therapy (21), and our previous data showed that aged fibroblasts can promote therapy resistance of melanoma cells in the absence of mutational changes (4). Furthermore, recent data suggest that BRAF inhibition itself can affect lipogenesis (22). We therefore asked whether lipid accumulation in melanoma cells in the aged microenvironment contributed to therapy resistance. We grew BRAFV600E-mutant melanoma cells in 3-D spheroids in young and aged fibroblast CM, and treated them with 3 μmol/L PLX4720 (BRAF inhibitor) together with 500 nmol/L PD0325901 (MEK inhibitor), the standard treatment for malignant melanoma. We found that melanoma cells in the aged microenvironment did not respond as effectively to the treatment as those in a young microenvironment (Fig. 3A). However, when we pretreated with 5 μmol/L lipofermata, we could completely sensitize melanoma cells in an aged microenvironment to the PLX/PD combination (Fig. 3A, bottom; additional melanoma lines, Supplementary Fig. S4A). Genetic knockdown of FATP2 phenocopied these results (Fig. 3B). Lipofermata did not affect the PO 4–ERK signaling pathway (Supplementary Fig. S4B), suggesting that lipids were not affecting resistance by preventing the drug from reaching its target. Next, we examined the metabolic activity of the cells, because oxidative metabolism plays a critical role in governing the resistance of melanoma cells to BRAF/MEK inhibition (21, 23). Here, we found dramatic differences between the oxygen consumption rate (OCR) of melanoma cells incubated in young versus aged media. Melanoma cells incubated in aged media upregulated levels of CPT1, (Fig. 3C), an enzyme which is responsible for the transfer of the long chain acyl group of the Acyl-CoA ester to carnitine, generating acyl-carnitine. This allows for the transport of fatty acids into the mitochondrial matrix for β-oxidation, which in turn is critical for resistance of melanoma cells to BRAF/MEK inhibition. Etomoxir is a drug which specifically targets CPT1, and, using a Seahorse assay to measure OCRs, we treated melanoma cells with etomoxir in the presence or absence of young or aged fibroblast CM. We found that melanoma cells treated with aged CM increased their OCR significantly as compared with melanoma cells treated with young CM, which increased their OCR very slightly (Fig. 3D). Treatment of the latter cells with etomoxir did little to affect the OCRs, suggesting that CPT1-mediated FAO likely did not play a role, but treatment of melanoma cells in aged CM with etomoxir dramatically reduced their OCR, suggesting a strong reliance on the activity of CPT1 (Fig. 3D).
To next determine whether blocking FATP2 could also affect the OCR in melanoma cells cultured in aged CM, we treated melanoma cells with lipofermata in the aged fibroblast CM and in the presence or absence of BRAF/MEK inhibitors. This revealed that BRAF/MEK inhibition reduced the OCR of melanoma cells in aged CM, but not to the extent of either lipofermata alone, or lipofermata in combination with BRAF/MEK inhibitors (Fig. 3E), suggesting that inhibiting FATP2-mediated transport of lipids into the melanoma cells can affect their mitochondrial activity, making them less able to resist targeted therapy. We analyzed a small cohort of patients (n = 8) after BRAF/MEK inhibitor treatment for the expression of FATP2, and compared it with their overall survival time, post-treatment. FATP2 expression was markedly elevated in patients who succumbed to disease in a shorter time frame (Fig. 3F). Even in this tiny cohort the relationship between FATP2 and survival was significant (P = 0.03), but the number of samples was too small to get a sense of whether age was a factor as well. We also examined patient-derived xenografts that were initially sensitive to BRAF/MEK inhibition, then relapsed, for FATP2 expression before and after treatment. We found that in cases where tumors acquired resistance to the BRAF/MEK combination, FATP2 expression increased dramatically, even if they were negative for FATP2 prior to treatment (Fig. 3G). Therefore, given the ability of lipofermata to maintain sensitivity to BRAF/MEK inhibition, we asked whether treating resistant melanoma cells with lipofermata would resensitize them to BRAF/MEK inhibitors. We created Yumm1.7 melanoma cells that were resistant to the BRAF/MEK inhibitor combination (Yumm1.7CR cells), and then grew them in spheroid assays. The cells in the vehicle control conditions remained resistant to the PLX/PD combination, whereas adding lipofermata sensitized the cells to the combination therapy (Fig. 3H).
Because our LC/MS data identified ceramides as one of the most differentially expressed groups of fatty acids, we wanted to analyze whether ceramides specifically contributed to therapy resistance. To calculate ceramide concentration, we used an internal standard on the LC/MS that contains a heavy labeled ceramide, as well as four additional heavy ceramides, all of which gave similar MS signals per pmole. Lipoprotein-depleted media (1.4 ng/mL of ceramides) were used to grow fibroblasts, and cells grown in young media (usually 8.1 ng/mL of ceramides) were reconstituted to a final concentration of 14.8 ng/mL of ceramides (concentration in aged media). Treatment of cells grown in ceramide-supplemented media showed an increased resistance to treatment with BRAF/MEK inhibitors both in a 2-D trypan blue viability assay (Fig. 3I) and in a 3-D spheroid assay (Fig. 3J). Together, these data suggest that inhibiting FATP2-mediated transport of lipids could overcome resistance to targeted therapy, which we observe in melanoma cells in an aged microenvironment by disrupting mitochondrially mediated mechanisms of therapy resistance.
To examine the role of FATP in vivo, we took both a pharmacologic and a genetic approach. First, we injected Yumm1.7 BRAF V600E-mutant melanoma cells intradermally into C57/BL6 mice either 8 weeks or 52 weeks of age, and then treated half of each group with 200 mg/kg PLX4720 (BRAF inhibitor) plus 7 mg/kg PD0325901 (MEK inhibitor). We saw that in young mice, tumors responded to the PLX/PD combination, recurring only after a long lag time of 55 days (Fig. 4A). Aged mice, on the other hand, initially responded but quickly relapsed after 10 to 15 days (Fig. 4B, teal line). Lipofermata treatment on its own did not affect tumor growth at all in young mice, but in aged mice, tumors initially responded to lipofermata, then quickly relapsed, after 10 to 15 days (Fig. 4B, gold line). However, whereas the combination of all three drugs did not further suppress tumor growth in young mice (Fig. 4A, red line), in aged mice the triple combination ablated tumor growth (Fig. 4B, red line). This is reflected in the survival curves (Fig. 4C and D). The combination was well tolerated in both young and aged mice as reflected in the mouse body weights (Supplementary Fig. S5A). Post-relapse analysis revealed that in tumors that recurred on BRAFi/MEKi, FATP2 staining was elevated compared with control-treated mice, but not in the lipofermata-alone condition, which maintained loss of FATP2 expression (Supplementary Fig. S5B).
We hypothesized that the difference in response to lipofermata alone in young versus aged mice might be due to effects on other cell populations, such as myeloid-derived suppressor cells (MDSC), in the tumor microenvironment. In support of this concept, Veglia and colleagues showed that lipofermata can inhibit the activity of MDSCs, rendering the tumors more susceptible to immune-mediated clearing (24). Indeed, tumors in aged mice have more polymorphonuclear-MDSCs, providing in part an explanation for these data (Supplementary Fig. S5C). To test this hypothesis and to determine the effects of FATP2 inhibition on the tumor cells alone, we created melanoma cells in which we could knock down FATP2 expression in an inducible manner. We implanted these cells in young and aged mice, and then treated with the PLX/PD combination in the presence or absence of doxycycline to silence FATP2 expression (Supplementary Fig. S5D). We found that downregulation of FATP2 expression specifically in melanoma cells did not affect the growth of tumors in either young or aged mice (Fig. 4E and F), confirming that the observed effect of lipofermata alone in the aged mice is likely microenvironmental. As with the lipofermata experiment, young mice responded well to the PLX/PD combination (Fig. 4E, teal line), and depleting FATP2 had no further effect (Fig. 4E, red line). However, in the aged mice, depletion of FATP2 in melanoma cells in combination with BRAF/MEK inhibition (BRAFi/MEKi) was still able to ablate tumors and sustain tumor regression (Fig. 4F, red line). Survival curves for these experiments are shown in Fig. 4G and H. Together, these data confirm that FATP2 ablation may have the ability to overcome resistance to targeted therapy in aged patients.
DISCUSSION
Overall, our data suggest that inhibiting FATP2-dependent accumulation of lipids can overcome therapy resistance. Although our data indicate that these lipids are coming from aged fibroblasts, melanoma cells can also take up lipids from other sources such as adipocytes (10). Regardless of the source, the melanoma cells are able to take up lipids and use them to promote aggressive behavior such as metastasis (10) or therapy resistance, as we showed here. We show that, of the lipids identified, ceramides may play a specific role. This is intriguing, because FATP2 plays a dual role as both a fatty acid transporter and an Acyl-CoA synthetase. Acyl-CoA synthetase catalyzes the conversion of long chain fatty acids to fatty Acyl-CoAs. Because it has been shown that cancer cells escape treatment by the conversion of ceramides into acylceramides, we used LC/MS to infer the presence of acylceramides by comparing ceramide levels in lipid extract before and after saponification. Cer(d18:1_16:0), Cer(d18:2_16:0), and Cer(d18:1_18:0) were >1.5 times increased after mild saponification, suggesting the presence of acylceramides with these ceramide backbones (Supplementary Fig. S6A). This reaction, as well as the packaging of fatty acids into neutral TGs, which we showed is increased in melanoma cells exposed to the aged tumor microenvironment (Supplementary Fig. S2D), requires diacyl glycerol transferase 2 (DGAT2). We show that DGAT2 is upregulated in melanoma cells in the aged tumor microenvironment (Supplementary Fig. S6B). These results would need further exploration, and are merely correlative at this time.
The data in Fig. 1A–D show that there were no differences in the intracellular amounts of TG in fibroblasts nor were there any differences in the secreted amounts of TG in CM from aged and young fibroblasts. However, there is an accumulation of neutral lipids in melanoma cells only in aged CM. Because total TG levels were the same regardless of the CM, it is likely that the fatty acids are mobilized from multiple sources including neutral lipids, phospholipids, and free fatty acids, and that it is the specific ability of FATP2 to capture and metabolize these mobilized fatty acids, which directs them into de novo synthesized TG that then accumulates as lipid droplets. Together, these data are highly suggestive of a dual role for FATP2 in melanoma, in its capacity both as a transporter and as an Acyl-CoA synthetase, as has been shown (17).
It is a point of interest that the lipids we see in the melanoma cells are packaged into TGs. Large-scale epidemiologic studies have linked increased TG levels with increased risk of multiple different cancers, including prostate, ovarian, and lung cancers (25, 26). For melanoma specifically, data from the metabolic cancer study (Me-Can) showed that patients with increased serum TGs had an increased risk of melanoma (relative risk adjusted to body mass index is 1.24; ref. 25). Our study shows that TG accumulation in melanoma cells also increases the resistance to targeted therapy. These data suggest that targeting TG levels (27, 28), which increase in older patients, could enhance response to targeted therapy in this population of patients with increased resistance to MAPK inhibition. Macrophages may be particularly susceptible to TGs, as it has been shown that during aging, the ability of macrophages to hydrolyze and utilize TGs is decreased, because of the loss of catecholamine-induced lipolysis. Depletion of NLRP3, an important mediator of the inflammasome, can restore catecholamine-induced lipolysis, decreasing TG levels within macrophages (29). Together, these data hint that not only targeted therapies but also potential immunotherapies may be affected by lipid accumulation in patients with melanoma, and point once again to the critical role of the aged microenvironment in melanoma pathogenesis. Lipofermata, in this context, is an exciting drug because it inhibits FATP2 not only in the tumor in aged individuals, but also in the immunosuppressive microenvironment, potentially increasing the susceptibility of these tumors not only to targeted therapy but also to immunotherapy.
METHODS
1205 Lu, 1205-GFP, WM793, WM793-GFP, WM983B, and WM164 melanoma cell lines were maintained in Tu2% [MCDB153 (Sigma)/Liebovitz L-15 (Cellgro; 4:1 ratio) supplemented with 2% FCS and 1.6 mmol/Lol/L CaCl 2] and transferred to DMEM (Invitrogen), supplemented with 5% FBS prior to CM experiments. WM1361A and WM1366 were maintained in RPMI with 5% FCS. Dermal fibroblast cell lines were obtained from Biobank at Coriell Institute for Medical Research (Camden, NJ). The fibroblasts were cultured in DMEM (Invitrogen) supplemented with 10% FCS. Yumm1.7 murine melanoma cells were cultured in DMEM supplemented with 10% FCS. Keratinocytes were maintained in keratinocyte serum-free medium supplemented with human recombinant EGF 1–53 and Bovine Pituitary Extract (Invitrogen). All cell lines were cultured at 37°C in 5% CO 2 and medium was replaced as required. Cell stocks were fingerprinted using AmpFLSTR Identifiler PCR Amplification Kit from Life Technologies at The Wistar Institute Genomics Facility. Although it is desirable to compare the profile with the tissue or patient of origin, our cell lines were established over the course of 40 years, long before acquisition of normal control DNA was routinely performed. However, each short tandem repeat (STR) profile was compared with our internal database of more than 200 melanoma cell lines, as well as control lines, such as HeLa and 293T. STR profiles are available upon request. Cell culture supernatants were Mycoplasma tested using Lonza MycoAlert Assay at the University of Pennsylvania Cell Center Services (Philadelphia, PA).
Western Blot Analysis
Cell lines were plated and collected with RIPA buffer. Protein was measured with Qubit Assay Kit (#Q33212, Thermo Fisher Scientific) and 30 μg protein was boiled and loaded into 4%–12% gel at 160 V and transferred onto polyvinylidene difluoride membranes. Blots were blocked with 5% milk for an hour and primary antibody was incubated overnight at 4°C. The next day, membranes were washed with TBS with 0.1% Tween and incubated with secondary antibody for an hour at room temperature. Membranes were then washed and developed using chemiluminescence-based detection reagents (#PI80196, Thermo Fisher Scientific). Chemiluminescence was detected using ImageQuant LAS 4000 (GE Healthcare Life Sciences).
Antibodies
Antibodies were purchased from the following commercial vendors and used in the following dilutions: FATP2 (1:1,000, Invitrogen), FASN (1:1,000, Cell Signaling Technology), GAPDH (1:10,000, Cell Signaling Technology), β-Actin (1:10,000, Novus Biologicals), NB600-501 (Abcam), CD36 (1:1,000, Novus Biologicals), FATP1 (1:1,000, ABNOVA), pERK (1:3,000, Cell Signaling Technology), ERK (1:3,000, Cell Signaling Technology), HSP90 (1:10,000, Cell Signaling Technology), and CPT1 (1:1,000, Cell Signaling Technology).
Lipidomics
Dermal fibroblasts were cultured for 24 hours in DMEM with 2.5% lipoprotein-depleted FBS (Kalen Biomedical). Melanoma cells were incubated for 48 hours in control media or CM from young/aged fibroblasts cultured for 48 hours in DMEM with 10% FBS. Three biological replicates were analyzed per experiment. Fibroblasts and melanoma cells were washed with cold PBS and scraped into cold methanol. Cold methanol was added to fibroblast CM at five times the volume. All samples were spiked with the Splash Lipidomix of deuterium-labeled lipids (Avanti Polar Lipids), and lipids were initially extracted with chloroform/methanol/0.88% sodium chloride 2:1:1 and reextracted with synthetic organic phase, as described previously (30). Ultra-high performance liquid chromatography (UHPLC)-electrospray-tandem mass spectrometry was performed in positive and negative ion modes on a Thermo Fisher Scientific Q Exactive HF-X Mass Spectrometer and Vanquish Horizon UHPLC System. Gradient liquid chromatography separation used an Accucore C30 Column (2.1 mm × 150 mm, Thermo Fisher Scientific) with 50:50 acetonitrile/water and 88:10:2 isopropanol/acetonitrile/water solvents, both containing 5 mmol/L ammonium formate and 0.1% formic acid. MS1 scans were acquired at 120k resolution, and data-dependent MS2 scans were acquired for the top 20 ions at 15k resolution with 0.4 m/z isolation width and 20/30/40 stepped Normalized Collision Energy. Lipid species were identified and quantified using LipidSearch 4.2 (Thermo Fisher Scientific). For all datasets, lipid species were filtered by adduct and grade, and MS peak areas were normalized to the Splash Lipidomix deuterated lipid standard of the same class where available. No further normalization was performed for CM as equal volumes were processed. Cellular lipidomes were further normalized by total lipid MS signal for each sample to correct for variations in total biomass content. Finally, for some comparisons, melanoma cell lipids were normalized to cell volume. Cell volume was calculated using quantitative microscopy and Huygens software. Representative data are shown in Supplementary Fig. S2D. For lipid species, statistical analysis was performed using Perseus 1.6.7.0 (31, 32). Data were log 2-transformed, and comparisons were performed using permutation-based FDR with s0 = 0.1 and 250 randomizations. For lipid classes, normalized peak areas were summed for each lipid species in a given class, and comparisons were performed using the Student t test.
Lipidomic Heat Maps
For the melanoma cells, MS1 signal was normalized to area and cell volume was used for analysis. Zero intensity values were floored to minimum detected intensity across all samples and protein groups and log 2-transformed. Two sample t test was used to estimate significance of difference between groups, and correction for multiple testing was done using Benjamini–Hochberg method. Results passing FDR < 5% cutoff were considered significant. Lipid molecule name with main ion was used as a unique identifier, and the most significant isobars were considered to resolve duplicates. Enrichment of lipid classes was done for lipids significantly changed at least 5-fold (fibroblasts) or 2-fold (melanoma cells), and significance was estimated using Fisher exact test.
shRNA, Lentiviral Production, and Infection
FASN and FATP2 short hairpin RNA (shRNA) were obtained from the TRC shRNA library available at The Wistar Institute (Philadelphia, PA; TRCN0000150501 and TRCN0000153400). For FASN (sh1 and 2), we used shFASN_0312 and shFASN_03125. For FATP2 (sh1 and 5), we used shFATP2_42973 and shFATP2_42977. For FATP1 (sh1 and sh2), we used shFATP1_038184 and shFATP1_038185. Lentiviral production was performed according to the protocol suggested by the Broad Institute (Cambridge, MA). Briefly, 293T cells were plated at 70% confluency and cotransfected with shRNA plasmid and the lentiviral packaging plasmids (pCMV-dR8.74psPAX2 and pMD2.G). pLKO.1 empty vector was used as a control. For transduction, cells were treated with lentivirus overnight and allowed to recover for 24 hours before selection using puromycin (1 μg/mL).
Organotypic 3-D Skin Reconstructs
Organotypic 3-D skin reconstructs were generated by plating 6.4 × 10 4 fibroblasts in each insert on top of the acellular layer (BD Biosciences #355467 and Falcon #353092) and incubating for 45 minutes at 37°C in a 5% CO 2 tissue culture incubator. DMEM containing 10% FBS was added to each well of the tissue culture trays and incubated for 4 days. Reconstructs were then incubated for 1 hour at 37°C in Hank's Balanced Salt Solution (HBSS) containing 1% dialyzed FBS (wash media). Washing media were removed and replaced with reconstruct media I. Keratinocytes (4.17 × 10 5) and melanoma cells (8.3 × 10 4) were added to the inside of each insert. Media were changed every other day until day 18 when reconstructs were harvested, fixed in 10% formalin, paraffin embedded, sectioned, and stained.
Drug Treatment
PLX4720 was obtained from SelleckChem and dissolved in DMSO (stock 10 mmol/L). Cells were treated for 48 hours and analyzed. After optimization, 3 μmol/L was the final concentration utilized for the experiments. PD0325091 was obtained from SelleckChem and dissolved in DMSO (stock 100 mmol/L). Cells were treated for 48 hours and analyzed. After optimization, 500 nmol/L was the final concentration utilized for the experiments. Lipofermata was obtained from ChemBridge Corps and dissolved in 30% Kolliphor (C5135, Sigma Aldrich). Cells were treated with 5 μmol/L for 48 hours and analyzed. ND646 from MedChemExpress was solubilized in DMSO (stock 10 μmol/L) for a final concentration of 4 nmol/L.
3-D Spheroid Assays
Melanoma cells (5,000) were plated in 1.5% agar and spheroids were allowed to form for 3 days. Spheroids were then embedded in rat-tail collagen (Life Technologies). The next day, cell lines were treated with unconditioned media, young CM, and aged CM in presence or absence of PLX4720, PD0325901, or lipofermata. Cell viability was measured using the LIVE/DEAD Viability/Cytotoxicity Kit (L3224, Invitrogen). Briefly, spheroids were washed with PBS and stained with calcein-AM and ethidium homodimer-1. The dyes were diluted in PBS and 300 μL of the solution was added on the spheroid wells for 1 hour at 37°C. The spheroids were washed in PBS and imaged using a Nikon TE2000 inverted microscope.
In Vivo Allograft Assays
All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC #1122mg/mL503X_0) and were performed in an Association for the Assessment and Accreditation of Laboratory Animal Care–accredited facility. For lipofermata experiments, Yumm1.7 (5 × 10 5) cells overexpressing mCherry were injected subcutaneously into aged (>300 days old) and young (6 weeks old) C57BL/6 mice (Taconic). Mice were treated as follows with lipofermata (2 mg/kg, twice a day for the first 2 weeks and then once daily) or 30% kolliphor as control. For inducible FATP2 deletion, Yumm1.7 mCherry (5 × 10 5) cells were infected with a TRIPZ inducible lentiviral FATP2 shRNA. This FATP2 shRNA lentiviral vector was designed with a reversible Tet-inducible vector that controls gene silencing. These cells were injected subcutaneously into aged (>300 days old) and young (6 weeks old) C57BL/6 mice (Taconic), and FATP2 expression was controlled by the administration of tetracycline (2 mg/kg).
Tumor sizes were measured every 2 days using digital calipers, and tumor volumes were calculated using the following formula: volume = 0.5 × (length × width 2). Time-to-event (survival) was determined by a 5-fold increase in baseline volume (∼750 mm 3) or was limited by the development of skin necrosis. Mice were euthanized and tumor tissue was preserved. Half of the tissue was embedded in paraffin and the other half in optimal cutting temperature compound (OCT) and flash-frozen for sectioning. All reagents injected in live mice were tested for endotoxin levels at University of Pennsylvania Cell Center Services (Philadelphia, PA) using The Associates of Cape Cod LAL test.
Seahorse Assay
Melanoma cells were incubated with young or aged CM for 72 hours. After that cells were counted with trypan blue and plated at an optimal density (30,000 cells/well) in XF96 cell culture plate (Agilent Technologies). The next day, cells were washed with seahorse buffer and seahorse media were added at pH 7.4. Cartridge was loaded with appropriate treatments, 1 μmol/L for oligomycin, 1.5 μmol/L for FCCP, and 0.5 μmol/L for rotenone and antimycin A. Etomoxir was also loaded at a final concentration of 40 μmol/L when utilized. For the analysis of how BRAFi/MEKi, lipofermata, and/or triple combination affected the melanoma cells in the aged microenvironment, we cultured melanoma cells with aged CM for 48 hours after cells were treated with either BRAFi/MEKi, lipofermata, and or the combination of all. After 48 hours, cells were trypsinized and counted with trypan blue. Viable cells were plated in the XF96 well plate and the treated with (i) 1 μmol/L oligomycin, (ii) 1.5 μmol/L FCCP, and (iii) 0.5 μmol/L rotenone and antimycin A. For each assay, individual measurements were measured followed by injections of treatment. Cells were standardized by protein concentration at the end of the experiment.
IHC
Skin reconstructs and mouse tumor samples were paraffin-embedded and sectioned. Paraffin-embedded sections were rehydrated through a series of xylene and different concentrations of alcohol, which was followed with a rinse in water and washing in PBS. Slides were put with an antigen retrieval buffer (#3300, Vector Laboratories) and steamed for 20 minutes. Slides were then blocked in a peroxide-blocking buffer (#TA060H2O2Q, Thermo Fisher Scientific) for 15 minutes, followed by protein block (#TA-060-UB, Thermo Fisher Scientific) for 5 minutes, and incubated with the primary antibody of interest, which was prepared in antibody diluent (S0809, Dako). Slides were kept in a humidified chamber at 4°C overnight. The next day, samples were washed with PBS and incubated in biotinylated anti-rabbit (Abcam) followed by streptavidin-horseradish peroxidase solution at room temperature for 20 minutes. Samples were then washed with PBS and incubated with AEC (3-amino-9-ethylcarboazole) chromogen for 10 minutes (#TA060SA, Thermo Fisher Scientific). Slides were then washed with water and incubated in Mayer hematoxylin (MHS1, Sigma) for 1 minute, rinsed with water, and mounted in Aquamount (#143905, Thermo Fisher Scientific).
Immunofluorescence and Quantification
Samples were fixed with 4% paraformaldehyde for 15 minutes at room temperature. After samples were washed with PBS, they were incubated with BODIPY 493/503 or BODIPY 505/515 (1:3,000, Thermo Fisher Scientific), LipidTOX Red Neutral Lipid Stain (1:125), or LipidTOX Green Phospholipidosis (1×) for 15 minutes at room temperature or 30 minutes for LipidTOX reagents. Samples were then washed with PBS and stained with DAPI (Invitrogen, 1:5,000) for 5 minutes. After samples were washed with PBS, they were mounted in Prolong Gold antifade reagent. For tumors, tissue was OCT embedded and sectioned. Frozen slides were fixed in 4% formalin for 15 minutes. Slides were then rinsed with 60% isopropanol, followed by Oil Red O in 0.5% isopropanol (#01319, Sigma Aldrich) staining for 15 minutes and rinsed with 60% isopropanol. Next, samples were stained with hematoxylin, rinsed with water, and mounted in Aquamount. Lipid droplet (BODIPY stain) intensity was quantified with Adobe Photoshop software. Channels were separated and melanoma cells’ intensity was quantified across different culture conditions. Values were then compared between conditions using unpaired t test.
Cell Death Assay
Melanoma cells were cultured with control media, young CM, or aged CM in the presence or absence of ND646. After 24 hours, cell viability was quantified with trypan blue.
TG Kit
Melanoma cells (1.5 × 10 5) were plated in a 6-well plate. The next day, cells were treated with young CM, aged CM, or DMEM. After 48 hours, cells were trypsinized, washed with PBS, and resuspended in NP40. Cells were then plated in a 96-well plate, and TGs were measured using Triglycerides Quantification Assay Kit (#ab65336, Abcam) according to the manufacturer's protocol. For fibroblasts, cells were plated in 6-well plates and CM were collected after 48 hours and added to a 96-well plate for analysis. The plates were measured using the ELX 808 Ultra microplate reader at 570 nm.
Lipid Transfer Experiment
Aged and young fibroblasts cells were seeded onto 4-well EZ MilliCell Slides (EMD Millipore PEGZ0416). Lipids in aged or young fibroblasts were labeled with 5 μmol/L BODIPY 558/568 C-12 for 4 hours. After 4 hours, extracellular BODIPY was removed from the cells by washing three times with 1 × HBSS with 0.2% fatty acid–free BSA. After washing, GFP + human melanoma cells were seeded on top of labeled aged or young fibroblasts for 24 hours, and imaged for the entire time to generate a video. For lipid transfer with CM, we again labeled fibroblasts with 5 μmol/L BODIPY 558/568 C-12 for 4 hours. Next, we took the CM of young and aged fibroblasts and cultured the GFP + human melanoma cells with this media for an additional 4 hours. Cells were then fixed and imaged using confocal microscopy, where BODIPY-laden GFP + melanoma cells could be observed. Images were captured on a Leica TCS SP5 II Scanning Laser Confocal System.
qRT-PCR
Melanoma cells were treated with young CM or aged CM and RNA was extracted using TRIzol (Invitrogen) and RNeasy Mini Kit (Qiagen) per protocol instructions. RNA (1 μg) was used to prepare cDNA using iscript DNA Synthesis Kit (#1708891, Bio-Rad). cDNA was diluted 1:5 before use for further reactions. Each 20 μL well reaction comprised 10 μL Power SYBR Green Master Mix (4367659, Invitrogen), 1 μL cDNA, and 1 μL primer.
FATP1:
F′-TGACAGTCGTCCTCCGCAAGAA
R′-CTTCAGCAGGTAGCGGCAGATC
Final concentration used was 0.5 μmol/L. Standard curves were generated for all primers and each set of primers was normalized to an 18S primer pair, acquired from Invitrogen (AM1718).
TCGA Database Analysis
The RNA-sequencing and clinical datasets for skin cutaneous melanoma were downloaded from TCGA (http://cancergenome.nih.gov/). Normalized mRNA expression was analyzed by quartiles. Patient ages were grouped into categories (≤ 50, and ≥ 50 years).
Acylceramides
Acylceramides were quantified indirectly by comparing ceramide levels in lipid extracts before and after mild saponification. Briefly, lipid extracts were saponified using 0.2 N KOH in methanol for 60 minutes at 37°C. KOH was neutralized with HCl. Lipids were extracted with 2:1:1 chlorofom:methanol:0.88% NaCl and analyzed as described for global lipid profiling. Identified ceramides were quantitatively compared with the same ceramides identified in global lipid profiling, and putative acylceramides were defined as having a saponified:global lipid ratio greater than 1. Ratios were compared between conditions using the Student t test.
Disclosure of Potential Conflicts of Interest
A.R. Goldman reports grants from NIH during the conduct of the study. M.R. Webster reports grants from NCI during the conduct of the study. H.-Y. Tang reports grants from NCI of the NIH (award number R50CA221838) during the conduct of the study. K.T. Flaherty has served on the board of directors for Clovis Oncology, Strata Oncology, Vivid Biosciences, and Checkmate Pharmaceuticals as well as the scientific advisory boards of X4 Pharmaceuticals, PIC Therapeutics, Sanofi, Amgen, Asana, Adaptimmune, Fount, Aeglea, Shattuck Labs, Tolero, Apricity, Oncoceutics, Fog Pharma, Neon, Tvardi, xCures, Monopteros, and Vibliome, as a consultant to Lilly, Novartis, Genentech, BMS, Merck, Takeda, Verastem, Boston Biomedical, Pierre Fabre, and Debiopharm, reports personal fees from Genentech (consultant), grants and personal fees from Novartis (consultant) and Sanofi (scientific advisory board), personal fees from Array BioPharma (consultant), Bristol-Myers Squibb (consultant), and Merck (consultant) during the conduct of the study, Clovis Oncology (board of directors), Strata Oncology (board of directors), Vivid Biosciences (board of directors), Checkmate Pharmaceuticals (board of directors), X4 Pharmaceuticals (scientific advisory board), PIC Therapeutics (scientific advisory board), Amgen (scientific advisory board), Asana Biosciences (scientific advisory board), Adaptimmune (scientific advisory board), Fount (scientific advisory board), Aeglea (scientific advisory board), Shattuck Labs (scientific advisory board), Tolero (scientific advisory board), Apricity (scientific advisory board), Oncoceutics (scientific advisory board), Fog Pharma (scientific advisory board), Neon Therapeutics (scientific advisory board), Tvardi (scientific advisory board), xCures (scientific advisory board), Monopteros (scientific advisory board), Vibliome (scientific advisory board), Takeda (consultant), Verastem (consultant), Boston Biomedical (consultant), Pierre Fabre (consultant), and Debiopharm (consultant) outside the submitted work. X. Xu reports personal fees and other funding from CureBiotech Inc (co-founder) and other funding from Exio Bioscience (co-founder) outside the submitted work. D.I. Gabrilovich reports grants from Cour Therapeutics, MiNA Therapeutics, GInnovation, Janssen, and Syndax, grants and personal fees from Merck, personal fees from Trex, Takeda, AstraZeneca, Third Rock Ventures, Shattuck Lab, and Quentis outside the submitted work. I.A. Blair reports grants from NIH, and personal fees from Takeda Pharmaceuticals, Calico, and PTC Therapeutics during the conduct of the study. D.W. Speicher reports grants from NIH during the conduct of the study. No potential conflicts of interest were disclosed by the other authors.
Authors’ Contributions
G.M. Alicea: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, validation, investigation, visualization, methodology, writing-original draft, project administration, writing-review and editing. V.W. Rebecca: Data curation, validation, investigation, visualization, methodology, writing-original draft, writing-review and editing. A.R. Goldman: Investigation, visualization, methodology, writing-review and editing. M.E. Fane: Investigation, visualization, methodology, writing-review and editing. S.M. Douglass: Investigation, visualization, methodology, writing-review and editing. R. Behera: Investigation, methodology, writing-review and editing. M.R. Webster: Investigation, methodology. C.H. Kugel III: Investigation, methodology. B.L. Ecker: Investigation, methodology. M.C. Caino: Investigation, methodology. A.V. Kossenkov: Software, investigation, visualization, methodology. H.-Y. Tang: Software, formal analysis, visualization, methodology. D.T. Frederick: Resources, formal analysis, visualization. K.T. Flaherty: Resources. X. Xu: Resources, investigation, visualization. Q. Liu: Formal analysis, investigation, visualization. D.I. Gabrilovich: Formal analysis, writing-review and editing. M. Herlyn: Resources, writing-reviewand editing. I.A. Blair: Resources, writing-review and editing. Z.T. Schug: Formal analysis, investigation, methodology, writing-review and editing. D.W. Speicher: Formal analysis, investigation, methodology, writing-review and editing. A.T. Weeraratna: Conceptualization, resources, formal analysis, supervision, funding acquisition, validation, investigation, methodology, writing-original draft, project administration, writing-review and editing.
Acknowledgments
We thank the outstanding Core Facilities of the Wistar Institute, supported by P30CA010815 and Johns Hopkins Kimmel Cancer Center, P30CA00697356; A.T. Weeraratna and Q Liu were supported by R01CA174746 and R01CA207935, R01CA223256. X. Xu, Q. Liu, M. Herlyn, and A.T. Weeraratna were also supported by P01 CA114046. I.A. Blair was supported by P30ES013508. M.R. Webster was supported by K99CA208012. A.T. Weeraratna was also supported by U01CA227550, the Wistar Science Discovery Fund, the Melanoma Research Foundation, a Melanoma Research Alliance/L'Oréal Paris-USA Women in Science Team Science Award, a Bloomberg Distinguished Professorship, and the EV McCollum Endowment. M. Herlyn was supported by a gift from the Adelson Medical Research Foundation. D.W. Speicher was supported by P50CA174523. Lipidomic analysis was performed on a Q-Exactive HF hybrid quadrupole-orbitrap mass spectrometer and Vanquish Horizon ultra-high performance liquid chromatography System (Thermo Fisher Scientific) purchased with NIH grant S10 OD023586. H.-Y. Tang was supported by R50CA221838. We thank Drs. Chi Van Dang, Dario Altieri, and Brian Keith (Wistar Institute) and Celeste Simon (University of Pennsylvania) for critical reading of the manuscript and Fred Keeney of the Wistar Institute Imaging Core for help with image analysis.
The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.