Targeting UGCG overcomes resistance to lysosomal autophagy inhibition

Abstract

Lysosomal autophagy inhibition (LAI) with hydroxychloroquine or DC661 can enhance cancer therapy, but tumor regrowth is common. To elucidate LAI resistance, proteomics and immunoblotting demonstrated that LAI induced lipid metabolism enzymes in multiple cancer cell lines. Lipidomics showed that LAI increased cholesterol, sphingolipids, and glycosphingolipids. These changes were associated with striking levels of GM1⁺ membrane microdomains (GMM) in plasma membranes and lysosomes. Inhibition of cholesterol/sphingolipid metabolism proteins enhanced LAI cytotoxicity. Targeting UDP-glucose ceramide glucosyltransferase (UGCG) synergistically augmented LAI cytotoxicity. While UGCG inhibition decreased LAI-induced GMM and augmented cell death, UGCG overexpression led to LAI resistance. Melanoma patients with high UGCG expression had significantly shorter disease-specific survival. The FDA-approved UGCG inhibitor eliglustat combined with LAI significantly inhibited tumor growth and improved survival in syngeneic tumors and a therapy-resistant patient-derived xenograft. These findings nominate UGCG as a new cancer target, and clinical trials testing UGCG inhibition in combination with LAI are warranted.

Introduction

Autophagy inhibition impairs tumor growth in preclinical cancer models when combined with chemotherapy, MAPK targeted therapy or immunotherapy (1,2). Targeting autophagy at the level of the lysosome is an attractive approach in multiple disorders, including cancer (3,4), but the clinically used lysosomal autophagy inhibitor (LAI) hydroxychloroquine (HCQ) rarely has single-agent anti-tumor activity in pre-clinical models. More potent LAIs like GNS561 and dimeric chloroquines (e.g., DC661) have single-agent antitumor activity in preclinical models (5,6). However, either in preclinical studies of the novel LAIs or in the clinical trials conducted with HCQ combinations in which patients responded, tumor regrowth on continued therapy is common, indicating the development of resistance (5,7–10). We and others have shown that HCQ, GNS561, and DC661 bind to and inhibit the lysosomal enzyme palmitoyl-protein thioesterase 1 (PPT1), and PPT1 KO recapitulates the phenotype of these inhibitors (5,6,11). Therefore, HCQ and its derivatives are targeted therapies and not simply weak bases that affect lysosomal pH. Importantly, DC661 and related optimized derivatives are more cell-penetrant within an acidic tumor microenvironment than HCQ (5). Novel autophagy inhibitors, including LAIs, are entering clinical trials, and new strategies to address LAI resistance will significantly enhance their clinical utility.

Using melanoma as a model, we have found that LAIs induced a small change in the proteome but a large change in the lipidome. Sphingolipid and cholesterol pathways were upregulated and contributed to cell survival in the face of LAI. The increased activity of these lipid metabolism pathways was associated with a striking accumulation of GM1⁺ membrane microdomains (GMM). From these pathways, UGCG emerged as a druggable target for LAI resistance and cancer cell survival.

Results

LAI induces proteome and lipidome changes leading to the accumulation of sphingolipids and cholesterol.

LAI, either by HCQ or DC661, leads to lysosomal dysfunction, but other pathways could be perturbed that contribute to cell death or survival in the face of LAI. To investigate this in an unbiased manner, we performed proteome analysis of A375P melanoma cells treated with either DC661 or HCQ. Out of 4264 cellular proteins identified, DC661 or HCQ treatment significantly increased only 157 and 88 proteins and decreased 34 and 43 proteins, respectively (Figure 1A). Ingenuity pathway analysis (IPA) demonstrated that the most significantly activated pathways (positive z-score) in response to LAI were related to lipid metabolism (Figure 1B). We found that 22 lipid metabolism proteins were significantly upregulated in DC661-treated compared to vehicle-treated cells (Figure 1C). There was almost complete overlap in the patterns of proteins that were increased by DC661 (3 μM) and by higher concentrations of the less potent lysosomal inhibitor HCQ (30 μM), with 12 proteins significantly increased in both groups (Figure 1C). Importantly, these 12 proteins e.g., apolipoprotein B-100 (APOB), UDP-glucose ceramide glucosyltransferase (UGCG), hydroxymethylglutaryl-CoA synthase (HMGCS1), low-density lipoprotein receptor (LDLR), scavenger receptor class B type 1 (SR-B1) are all involved in sphingolipid and cholesterol metabolism. Considering lipid-related proteins (excluding APOB, which is likely from bovine source), DC661 or HCQ treatment produced the largest fold change in UGCG (~7-fold increase) (Figure 1D). Based on these findings, we characterized the global lipidome of A375P cells and found extensive remodeling following DC661 (1380/1917 (72%) of lipids species changed significantly) or HCQ (1410/1917 (73%) of lipids species changed significantly) treatment (Figure S1A–B). In the cells treated with low concentrations of DC661 or high concentrations of HCQ, 19% of the lipid species were changed at least 2-fold (Figure 1E). The most striking treatment-related increases occurred in glycosphingolipids (hexosylceramides), followed by ceramides and sphingomyelins (Figure 1F). Filipin staining demonstrated that DC661 or HCQ treatments significantly increased cholesterol in the plasma membrane and lysosomal-associated membrane protein 1 positive (LAMP-1⁺) lysosomes (Figure 1G). To further confirm the lipid changes specifically in lysosomes, we purified lysosomes using lysosomal immunoprecipitation (Lyso-IP) (12) from DC661- and vehicle-treated A375P cells (Figure 1H) and characterized the lipidome. LAI induced a significant increase in sphingomyelins, ceramides, and cholesterol esters in the lysosomal lipidome (Figure 1I). This increase in cholesterol esters was expected since DC661 raises lysosomal pH (5) and decreased lysosomal acid lipase activity was observed following DC661 treatment (Figure S1C), Altogether, these results demonstrated that LAI causes upregulation of lipid metabolism enzymes and accumulation of sphingolipid and cholesterol species.

Figure 1: LAI leads to the accumulation of sphingolipids and cholesterol.

A-D: LC-MS/MS-based proteome analysis of A375P cells treated with DC661 (3 μM) or HCQ (30 μM) for 24 h. All experiments were done in triplicate. A. Volcano plots with significant changes relative to control (FDR<5% and |FC| ≥1.5) highlighted in red (increase) and blue (decrease). B. Ingenuity pathway analysis of elevated proteins (FDR<5% and |FC| ≥1.5) in DC661 or HCQ-treated cells compared with control samples. The black line is set at threshold 3.0 (p<0.001). Chol: Cholesterol; Zym: Zymosterol; Mva: Mevalonate; GGPP: Geranylgeranyldiphosphate; LXR/RXR/FXR: Liver X Receptor/Retinoid X Receptor/Farnesoid X Receptor. C. Heatmap of lipid metabolism proteins significantly elevated (FDR<5% and |FC| ≥1.5); names in bold indicate proteins which were significantly increased by both DC661 and HCQ. D. Fold change in the lipid metabolism proteins significantly elevated by both DC661 (3 μM) and HCQ (30 μM) (FDR<5% and |FC| ≥1.5) in A375P cells. (E-F) LC-MS/MS-based lipidome analysis of A375P cells treated with DC661 (3 μM) or HCQ (30 μM) for 24 h. E. Volcano plots of A375P lipidome showing significant changed lipid species (FDR<5% and |FC| ≥2) highlighted in red (increase) and blue (decrease) induced by DC661 (3 μM) or HCQ (30 μM) treatments for 24 h. F. Mean peak area +/− standard deviation of lipid classes; SM: sphingomyelin, Cer: ceramide: Hex1Cer: hexosylceramide. The number of species detected in each class is indicated below the label. G. Representative images of filipin staining and quantification. A total of at least 50 single cells were counted from multiple images / experimental group (each dot represents a single cell). Merged images show colocalization (yellow arrows) of filipin and lysosomes (LAMP-1) in A375P cells treated with DC661 (1 μM) or HCQ (30 μM) for 24 h. H. Schema for lysosomal purification by immunoprecipitation (Lyso-IP). I. LC-MS/MS lipidome analysis of lysosomes purified from A375P cells treated with vehicle control or DC661 (3 μM) for 24 h. Mean peak area +/− standard deviation of significantly elevated lipid classes, ChE: cholesterol esters. Mean +/− s.e.m. Scale: 10 μm. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001. One-way ANOVA followed by Dunnett’s multiple comparisons procedure (F); Welch’s t-test (G); Student’s t-test (I).

Cholesterol and sphingolipid salvage pathways confer cytoprotection from LAI.

We sought to determine if the induction of the cholesterol or sphingolipid metabolism pathways was a part of the cytotoxic response to LAI or a compensatory cytoprotective response to LAI-mediated cytotoxicity by investigating the effects of targeting key enzymes in these pathways in combination with DC661 treatment. We first depleted membrane cholesterol with methyl-β-cyclodextrin (MBCD) (13). Co-treatment with DC661 and MBCD significantly decreased the viability of A375P cells compared to DC661 alone (Figure 2A). The addition of water-soluble cholesterol to the medium significantly mitigated the enhanced cytotoxicity elicited by the MBCD and DC661 combination (Figure 2A). We next targeted 3-hydroxy-3-methylglutaryl-coenzyme A (HMGCoA) reductase, which catalyzes the rate-limiting step in de novo cholesterol synthesis, using three clinically relevant statins: simvastatin, atorvastatin, and lovastatin (Figure 2B; S2A–B). No combination of statin and DC661 enhanced cytotoxicity compared to DC661 alone. Since de novo cholesterol synthesis did not play a role in DC661 cytotoxicity, we next targeted extracellular cholesterol uptake, carried out by low-density lipoprotein receptor (LDLR). When LDL particles bind to the LDLR, the complex is internalized into endocytic vesicles and trafficked to the lysosome, where cholesterol is released and made available for use within the cell (14). We used a specific anti-LDLR antibody to prevent the binding of LDL to the LDLR (15). Anti-LDLR antibody + DC661 showed significantly enhanced cytotoxicity compared to isotype control + DC661 (Figure 2C). Since LDLR requires lysosomal accumulation to deliver scavenged cholesterol to the cell, the enhanced cytotoxicity elicited with anti-LDLR and DC661 was initially surprising. We have previously shown that DC661 significantly impairs but does not completely abrogate lysosomal acidification (5). To further investigate this finding, we performed proteomics on isolated lysosomes and found a significantly increased level of LDLR and APOB in the DC661-treated samples (Figure S2C). This suggests that despite lysosomal impairment induced by DC661 (Figure S1C) (5), LDL uptake and trafficking to the lysosome by LDLR was intact, but receptor recycling or degradation was blocked. A lysosome-independent means of scavenging cholesterol occurs through SR-B1, which binds to high-density lipoprotein (HDL) (16). Inhibition of the SR-B1 using the selective chemical inhibitor BLT-1 (17) resulted in a modestly enhanced DC661 cytotoxicity (Figure 2D). Next, we focused on enzymes that regulate sphingolipid metabolism, specifically those responsible for generating ceramides and hexosylceramides, sphingolipid classes that were increased after LAI. Mammalian ceramide pools are maintained by de novo synthesis, which starts with the condensation of palmitoyl-CoA and serine, leading to the formation of the intermediate sphingoid base sphinganine, enabling ceramide synthesis. Alternatively, salvage pathways which include sphingomyelin hydrolysis and glycosphingolipid recycling can lead to ceramide formation (18). Once ceramides are generated, ceramide-modifying enzymes can add complexity to form hexosylceramides and gangliosides. Inhibition of de novo ceramide synthesis using the selective serine palmitoyltransferase inhibitor myriocin did not enhance the cytotoxicity of DC661 (Figure 2E). We next targeted ceramide synthase isoforms 1–6 using a pan-ceramide synthase inhibitor fumonisin-B1 and did not observe a difference in viability between DC661 plus fumonisin-B1 and DC661 alone (Figure 2F). Each ceramide synthase isoform, from ceramide synthase 1 to ceramide synthase 6, synthesizes ceramides with varying fatty acid chains (19) and is involved in both de novo and salvage pathways. Lipidome analysis following DC661 treatment demonstrated a predominant increase in the levels of individual ceramide species with long (C20–26) fatty acid chains (Figure 2G), which are synthesized predominantly by ceramide synthase 2. Therefore, we targeted ceramide synthase 2 using a more potent and specific inhibitor, ST-1074 (20,21). ST-1074 and DC661 enhanced cytotoxicity in A375P cells compared to DC661 alone (Figure 2H). We then targeted sphingomyelin hydrolysis using the acid sphingomyelinase inhibitor siramesine and observed no effect on DC661 toxicity (Figure 2I). In our lipidome analysis, hexosylceramides with longer fatty acid chains were the most significantly increased hexosylceramide species (Figure 2J). Notably, hexosylceramides are glycosphigolipids synthesized by the rate-limiting enzyme UGCG. Combining the UGCG inhibitors Genz-123346 (free base) or its FDA-approved analogue, eliglustat (hemitartarate salt), with DC661 strikingly enhanced the cytotoxicity of DC661 in A375P cells (Figure 2K; S2D). The inhibitor studies reported above were repeated at least three times to compare and confirm the relative augmentation of DC661 cytotoxicity imparted by each inhibitor (Figure 2L). We concluded that inhibition of either cholesterol uptake receptors (LDLR, HDLR) or sphingolipid salvage pathway enzymes (ceramide synthase 2, UGCG) significantly augmented DC661 cytotoxicity (Figure 2L), suggesting these proteins could be part of a resistance mechanism. The cholesterol uptake receptors and sphingolipid metabolism enzymes whose inhibition enhanced DC661-mediated cytotoxicity (LDLR, SR-B1, UGCG, and ceramide synthase 2), increased in a concentration- and time-dependent manner following DC661 treatment (Figure 2M–N).

Figure 2: Inhibition of either cholesterol uptake receptors or sphingolipid salvage pathway enzymes augment DC661 cytotoxicity to A375P cells.

A. MTT assay graph of 3 h pretreatment of 2 mM MBCD followed by addition of DC661 (0.3 μM) or DC661 + water-soluble cholesterol (Chol; 8 μM). B. MTT assay plot with increasing concentrations of DC661 (0.01 to 10 μM), with and without simvastatin. C. MTT assay graph of 2 h pretreatment with Anti-LDL receptor (5 μg/ml) or its isotype control IgG (5 μg/ml) followed by addition of DC661 (0.3 μM). (D-F) Representative MTT assay plots with increasing concentrations of DC661 (0.01 to 10 μM), with and without D, BLT-1, E, Myriocin, and F, Fumonisin B1 (FB1). G. Fold change increase in the average peak area values (3 replicates) of sphingosine (d18:1) ceramide species increased by DC661 and HCQ treatments and synthesized by different isoforms of ceramide synthase (CerS), CerS1–6. H-I. MTT assay plots with increasing concentrations of DC661 (0.01 to 10 μM) with and without H, specific CerS2 inhibitor ST1074 and I, Acid-sphingomyelinase inhibitor, siramesine (Sira). J. Fold change increase in the average total peak area (3 replicates) values of different species of Hex1Cer induced by DC661 and HCQ. K. MTT assay of DC661 (0.01 to 10 μM) with and without UGCG inhibitor, Genz-123346 (Genz). L. Bar graph showing average IC₅₀ values ± s.e.m. of MTT assays from three independent experiments. Dashed line partitions sphingolipid and cholesterol pathways. (M-N) Representative Western blots of whole cell lysates, probed for sphingolipid metabolism proteins and cholesterol uptake receptors whose inhibition significantly augmented DC661 cytotoxicity in MTT assays, after treatment of A375P cells with M, different concentrations of DC661 and N, different durations with DC661 (3 μM). *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001; ns: non-significant. One-way ANOVA followed by Tukey’s (A, C) or Dunnett’s (L) multiple comparisons procedures.

Of the proteins in the cholesterol and sphingolipid salvage pathways whose inhibition augmented DC661 cytotoxicity, we focused on UGCG because UGCG and hexosylceramide levels showed the largest and most significant treatment-related fold changes in the proteomics and lipidomics data, respectively (Figure 1D, F). To determine if UGCG also increases with LAI in other cancer cells, we treated DLD-1, a colorectal cancer cell line; MIA PaCa-2, a pancreatic cancer cell line; A549, a lung cancer cell line and WM4380, a melanoma cell line generated from a BRAF^V600E patient-derived xenograft (PDX), with DC661 and observed a concentration-dependent increase in UGCG (Figure S2E). High concentrations of HCQ, a weaker lysosomal inhibitor, also increased UGCG in A375P cells (Figure S2F). To determine if UGCG levels also increase in response to non-lysosomal autophagy, we treated A375P cells with autophagy inhibitors SBI-0206965 (which targets Unc-51 like autophagy activating kinase 1 (ULK-1)) or SAR405 (which targets vacuolar sorting protein-34 (VPS34)) and found that concentrations which effectively blocked autophagy induction at the level of autophagic vesicles formation did not increase the UGCG levels (Figure S2G–H). Further, unlike DC661 + Genz-123346 or DC661 + eliglustat combination treatments which produced augmented cytotoxicity compared to single agent cytotoxicity in long-term colony formation assays, the addition of Genz-123346 or eliglustat to either SBI-0206965 or SAR405 did not produce augmented cytotoxicity to A375P cells (Figure S2I).

LAI-induced lipid remodeling is associated with the formation of GM1⁺ membrane microdomains (GMM)

Since our proteomics, lipidomics, imaging and chemical inhibition studies pointed to DC661-induced increases in UGCG activity, sphingolipid accumulation, and cholesterol accumulation on plasma membrane and intracellular compartments, we investigated the possibility of these changes reflecting the accumulation of lipid microdomains. Previous work has demonstrated that detergent-resistant, cholesterol (filipin⁺), and a complex glycosphingolipid monosialotetrahexosylganglioside (GM1)-containing lipid microdomains can be identified on lysosomal (22–24) and plasma membranes (25). The detection of GM1 using cholera toxin B-subunit (CTxB) provides a means to visualize the presence of these microdomains (22,26–28). Immunofluorescence microscopy of a labeled CTxB demonstrated increased GM1⁺ signals in both plasma membrane and lysosomes following DC661 and HCQ treatments (Figure 3A; S3A). DC661 or HCQ treatment also increased levels of the prototypical membrane lipid microdomain marker proteins flotillin-1 and flotillin-2 (29) in a concentration-dependent manner in the whole cell lysates of A375P cells (Figure 3B; S3B). Flotillin-1 and flotillin-2 were also found to be significantly increased in the proteome of detergent-resistant membrane fractions of DC661-treated A375P cells (Figure S3C). We next used high-resolution confocal microscopy with deconvolution and the CTxB probe to demonstrate that increased CTxB signal following DC661 treatment was partitioned as microdomains in the plasma membrane and was not diffusely distributed across the membrane (Figure 3C). CTxB⁺ GMM on the plasma membrane also contained flotillin-2 (Figure 3D). Focusing on the lysosomes, both high-resolution confocal microscopy and super-resolution stimulated emission depletion (STED) microscopy with deconvolution demonstrated that following DC661 treatment, increased CTxB signal was arrayed on ~0.5–1 μm (average diameter of a lysosome) circular structures alternating with LAMP-1. These structures suggest that GM1 was not accumulating within the lumen of the lysosome but rather increasing on the surface after LAI (Figure 3E–F). Notably, LAMP-1 has been reported to be a lysosomal membrane protein which is excluded from flotillin⁺ lipid microdomains (28,30,31); therefore, the lack of colocalization at the super-resolution level provides further evidence that the CTxB signal reflects distinct membrane lipid microdomains. Even though CTxB and LAMP-1 do not colocalize at the super-resolution level, their appearance of colocalization (Figure 3A) in standard confocal microscopy reflects the proximity of GMM and LAMP1 on lysosomes. As super-resolution was not necessary for the conclusions drawn in subsequent experiments, we used standard confocal microscopy to detect GMM.

Figure 3: LAI increases GM1⁺ membrane microdomains (GMM).

A. Representative confocal images of A375P cells treated with DMSO (vehicle control) or DC661 (1 μM) for 24 h and probed for GM1 with Alexa Fluor 488 labeled cholera toxin-subunit B (CTxB) and lysosome (LAMP-1 antibody); yellow arrows: colocalization. Mean +/− s.e.m. of Mander’s correlation coefficients for colocalization of LAMP-1 over CTxB from three separate image fields with a total of at least 20 cells / group. B. Immunoblot of lysates from A375P cells treated with different concentrations of DC661 for 24 h and probed for flotillin 1 and 2. In panels C-F, A375P cells were treated with DC661 (1 μM) for 24 h. (C-E) Representative high-resolution confocal images (350–500x magnification and deconvolved) of GM1 (CTxB) with C, membrane (Membrite stain), D, flotillin-2 (maximum intensity projection image of 3 planes), and E, LAMP1. F. Super-resolution STED images (400x magnification and deconvolved) of GM1 (CTxB) and LAMP1. G. A375P cells were given PPT1 siRNA or control scrambled siRNA (Scr siRNA) for 72h and labelled for GM1 (CTxB) and lysosomes (LAMP-1); yellow arrow: colocalization. (H-J) Representative confocal images of H, DLD-1, I, MIA PaCa-2 and J, A549 cancer cells treated with DC661 (0.6 μM for DLD-1, 1 μM for MIA PaCa-2 and A549 cells) for 24 h and were labelled for GM1 (CTxB) and lysosomes (LAMP-1); yellow arrow: colocalization. All images are representative of at least two independent experiments. Scale: 10 μm (A, G-J); 5 μm, inset 0.5 μm (C-F). **P ≤ 0.01, Student’s t-test (A).

PPT1 is the molecular target of chloroquine derivatives (5). Like DC661, knockdown of PPT1 in A375P cells increased GMM formation on plasma membrane and lysosomes (Figure 3G; S3D, S3E). DC661 treatment increased GMM formation on plasma membranes and lysosomes in multiple human cancer cell lines, including PDX-WM4380 (Figure S3F); DLD-1; MIA PaCa-2 and A549 (Figure 3H–J; S3G). Altogether, these results demonstrated that LAI upregulates UGCG and is associated with assembly of GMM in plasma membrane and lysosomes of multiple cancer lines.

UGCG inhibition augments lysosomal membrane permeabilization (LMP) and abrogates DC661-induced GMM formation.

A long-term colony formation assay showed that the combination of DC661 and Genz-123346 significantly reduced colony formation compared to either DC661 or Genz-123346 alone in melanoma, lung, pancreatic, and colon cancer cell lines (Figure 4A). The cytotoxicity of DC661 + Genz-123346 was found to be synergistic in both human (A375P) and mouse (B16-F10) melanoma cell lines, respectively (Figure 4B; S4A). To check the effects of UGCG inhibition on GMMs, A375P cells were treated with vehicle control, DC661, Genz-123346, eliglustat or the combinations and were stained with CTxB. Quantitative analysis of images showed that DC661-induced GMM formation in both the plasma membrane and lysosomes was significantly reduced by the addition of Genz-123346 (Figure 4C), and a similar trend was observed with the DC661 and eliglustat combination (Figure S4B). Further, the addition of Genz-123346 to DC661 abrogated the increased cholesterol level induced by DC661 (Figure S4C). DC661 is known to induce LMP which can be imaged by measuring galectin-3⁺ puncta in cells (5,32) (Figure S4D). In A375P cells, the combinations of DC661 + Genz-123346 or DC661 + eliglustat significantly increased the percentage of galectin-3 puncta-positive cells compared to DC661 alone (Figure 4D; S4E), demonstrating that augmented cytotoxicity in DC661 + UGCG inhibition groups was associated with increase in LMP and the reduction of GMM. Furthermore, this augmented LMP in the DC661 and Genz-123346 combined treatment group was associated with increased lysosomal pH (Figure S4F) and cleaved caspase-3 levels relative to the single treatment groups (Figure 4E; S4G). We investigated if this synergistic toxicity of DC661 and Genz-123346 combination was due to a compensatory rise in ceramides resulting from the inhibition of UGCG. Our lipidomics results showed that although DC661 + Genz-123346 significantly reduced hexosylceramide levels, as expected, there was no significant increase in ceramides levels compared to either DC661 or Genz-123346 (Figure S4H–I), demonstrating that increased ceramide levels due to the combination treatment could not explain the induction of apoptosis, LMP, or cytotoxicity. To complement chemical inhibition of UGCG, we used a siRNA-based genetic approach. Immunoblotting demonstrated an efficient knockdown of UGCG by pooled siRNA (Figure S4J). Like chemical inhibition with Genz-123346, in a long-term colony formation assay of A375P cells, DC661 + UGCG knockdown completely abolished colony formation (Figure 4F). siUGCG reduced GMM (Figure 4G) and significantly augmented DC661-mediated LMP (Figure 4H) compared to DC661 or control scramble siRNA treatment in A375P cells. Also, increased cleaved caspase-3 was observed in A375P cells treated with DC661 and siUGCG (Figure 4I). Taken together, these results demonstrate that UGCG inhibition augments DC661-induced cytotoxicity, LMP and activation of apoptosis, and is associated with a reduction in GMM formation.

Figure 4: Chemical or genetic inhibition of UGCG synergistically augments DC661-mediated cytotoxicity and abrogates DC661 induced GMM formation.

A. 7-day colony formation assays in different cancer lines treated with DC661 (0.3 μM for A375P and 0.1 μM for other lines), Genz-123346 (Genz) (5 μM for B16-F10 and A549; 10 μM for A375P, MIA PaCa2 and DLD-1) or their combination. B. BLISS synergy and antagonism 3D plots of human (A375P) and mouse (B16-F10) melanoma cells treated with indicated combinations of Genz and DC661. (C-D) Representative confocal images of A375P cells or A375P-galectin-3-GFP cells treated with DC661 (1 μM), Genz (20 μM), or combination for 24 h. C. GM1 (CTxB) and lysosomes (LAMP-1); yellow arrow: colocalization. Quantification of CTxB intensity from at least 50 single cells / experimental group (each dot represents a single cell). D. A375P-galectin-3-GFP cells with galectin-3 (Gal3) puncta (white arrows) and quantification. E. Immunoblotting for cleaved caspase-3 (c-csp3) in the lysates of A375P cells. (F- I) For UGCG genetic inhibition, A375P cells or A375P-galectin-3-GFP cells were given UGCG siRNA or control scrambled siRNA (Scr siRNA) for 48 h, followed by treatment with either DMSO or DC661 (1 μM) for 24 h. F. Colony formation assay in A375P cells treated with DC661 (0.6 μM), Genz (10 μM), or combination following the UGCG knockdown as shown in the panel. G. Representative confocal images of cells labelled for GM1 (CTxB) and lysosomes (LAMP-1); yellow arrow: colocalization. H. A375P-galectin-3-GFP cells with Gal3 puncta (white arrows) and quantification. I. Immunoblot of c-csp3 in the whole cell lysates of A375P cells. All experiments were repeated at least twice. Scale: 10 μm (C, G), 20 μm (D, H). *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001; ns: non-significant. Welch’s ANOVA followed by Dunnett’s T3 multiple comparisons procedure (C). In D and H, each dot represents the % of puncta⁺ cells in an image field, a total of 100 cells were counted / group. We did not observe any significant number of puncta⁺ cells in Genz, Scr, and UGCG siRNA alone control groups. We excluded control groups and performed a two-tailed t-test between two groups (D and H).

UGCG is a driver of resistance to LAI

We next determined the effects of UGCG overexpression in A375P cells. Overexpression of UGCG in A375P cells was confirmed using immunoblotting (Figure 5A). UGCG overexpression led to a significant resistance to LAI cytotoxicity in 72 h (Figure 5B) as well as in 7-day cell culture assays (Figure 5C). Further, UGCG overexpression increased the levels of GMM in the plasma membrane and lysosomes (Figure 5D) and decreased DC661-mediated LMP (Figure 5E) and cleaved caspase-3 levels (Figure 5F). To determine if UGCG is a cancer dependency gene, we interrogated the DepMap database (33). UGCG is a dependency gene in multiple cancer cell lines of different lineages, as characterized by CRISPR-mediated knockout of UGCG affecting the survival of these cancer lines (Figure 5G). Across all cancer types, 42/1054 cell lines (3.9%) had a probability of dependency based on a Chronos score ≤ −0.5, and 207/1054 (19.6%) cell lines had a probability of dependency based on a Chronos score ≤ −0.25. Skin cancer cell lines demonstrated the highest incidence of UGCG dependency. In melanoma patients in The Cancer Genome Atlas (TCGA) (n=211), we observed that UGCG expression in lymph node tissue was related to disease-specific survival (Figure 5H). Melanoma patients in the high UGCG expression group had a lower five-year survival rate (55.8%, n=47) compared to patients with low UGCG expression (68.4%, n=164). There were no significant differences in clinicopathological variables among patients with low and high UGCG expression (Supplemental Table S1). In the validation cohort of similar patients (n=130) (GEO database accession GSE65904) (34), the two Kaplan-Meier disease-specific survival curves were significantly different (p=0.03) (Figure 5I; Supplemental Table S2).

Figure 5: UGCG expression in therapy resistance, melanoma cell survival and disease-specific survival of melanoma patients.

(A-F) A375P cells expressing vector (Vector) or a UGCG-DDK plasmid (UGCG) were used. A. Immunoblot in the whole cell lysates confirming overexpression of UGCG. B. 3-day MTT assay with DC661. C. 7-day colony formation assay with DC661 (0.6 μM). In the experiments from D-F, DC661 (3 μM) was used to treat the cells for 24 h. D. GM1 (CTxB) and lysosomes (LAMP-1), and colocalization (yellow). E. Representative images of A375P cells overexpressing UGCG and galectin-3-GFP, white arrows indicate galectin-3 (Gal3) puncta⁺ cells. F. Immunoblot of cleaved caspase-3 (c-csp3). G. Box plots show the chronos score (cancer dependency) for UGCG knock-out in multiple cancer lines (numbers of cell lines shown in the parenthesis) of different lineages (Y-axis) in The Cancer Dependency Map (DepMap). The cell lines (shown by dots) with chronos score <0 (red line) show UGCG dependency. H. Kaplan–Meier survival curves showing the disease-specific survival (years) of melanoma patients in the Training Dataset (n=211) with low and high UGCG levels. I. Kaplan–Meier survival curves showing the disease-specific survival (years) of melanoma patients (n=130) in the validation dataset with low and high UGCG levels. Scale: 10 μm (D), 20 μm (E). *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001; ns: non-significant. Two-way ANOVA followed by Tukey’s multiple comparisons procedure (B). Log-rank (Mantel-Cox) test (B).

UGCG inhibition combined with LAI impairs tumor growth in a syngeneic tumor model

To determine the effects of targeting UGCG in vivo, we first determined the effects of UGCG inhibition on DC661 cytotoxicity in B16-F10 melanoma mouse cells, which we used to generate tumors in immunocompetent C57BL6 mice. Like A375P cells, DC661 treatment increased UGCG levels (Figure 6A), and B16-F10 cells treated with DC661 and Genz-123346 showed significantly increased cytotoxicity compared to DC661 (Figure 6B). DC661-induced changes in UGCG levels were also correlated with increase in membrane lipid microdomain marker proteins, flotillin-1 and flotillin-2 (Figure 6C). To model therapy resistance in vivo, we grew B16-F10 melanoma tumors and did not start treatment until tumors were large (150 mm³). Clinically, large tumors are less likely to respond to targeted therapy or immunotherapy, and our previous preclinical studies demonstrated that this was also true for autophagy inhibition (35,36). We used an FDA-approved highly selective UGCG inhibitor, eliglustat. Though high dose HCQ (60 mg/kg) given daily, low dose DC661 (0.5 mg/kg) given once every two days, or low dose daily eliglustat (30 mg/kg) demonstrated little single-agent efficacy, low dose intermittent DC661 + eliglustat and high dose continuous HCQ + eliglustat demonstrated significant tumor growth inhibition (Figure 6D). At euthanasia, the combination treatment significantly reduced tumor weight and size (Figure 6E–F). Importantly, these combinations were well-tolerated with no significant change in body weight after the treatments were started (Figure 6G), demonstrating that the reliance on UGCG and presumably on sphingolipid metabolism following lysosomal inhibition was more prominent in tumor cells compared to cells of other vital organs. We next measured GMM in the harvested tumor tissue. Concordant with our in vitro findings, while DC661 and HCQ treatment induced GMM formation in the tumor tissues, the combination of eliglustat with either DC661 or HCQ significantly abrogated increased GMM formation (Figure 6H).

Figure 6: Anti-tumor activity of UGCG inhibition and LAI in immunocompetent mice bearing melanoma tumors.

A. Immunoblots of UGCG in the whole cell lysates from B16-F10 cells treated with different concentrations of DC661 for 24 h. B. MTT assay plot of B16-F10 cells treated with DC661 (0.01 to 10 μM) ± Genz-123346 (Genz). C. Immunoblots of flotillin 1 and 2 in the lysates from B16-F10 cells treated with different concentrations of DC661 for 24 h. D. B16-F10 average tumor volumes ± s.e.m. in different cohorts (n=8) of syngeneic C57BL/6J mice, measured every day following the treatment plan. Adjusted P values are shown for measurements on day 9. E. B16-F10 tumor weights at the end of the experiment. F. Representative pictures of animals from each group with tumors shown in red circles, and isolated tumor pictures from each animal with a scale bar of 3 c.m. G. Percent change in the average body weights in each cohort of tumor-bearing animals with respect to the day 1 of treatment, body weights were measured every two days as shown. H. Representative immunofluorescence images and quantification (mean ± s.e.m.) in the tumor tissue sections labelled for GM1 (CTxB) and lysosome (LAMP-1) with their merged pixels shown in yellow. Each circle in the bar represents an animal and the average intensity of fluorescently labelled CTxB, at least 80 cells were counted / animal. Scale: 50 μm. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001; ns, not significant. Two-way ANOVA followed by Tukey’s multiple comparisons procedure (D); Welch’s ANOVA test followed by Dunnett’s T3 multiple comparisons procedure (E); One-way ANOVA followed by Tukey’s multiple comparisons procedure (H).

UGCG inhibition combined with LAI impairs tumor growth and increases survival in xenograft and PDX tumor models

A375P cells were implanted into the flanks of NOD-SCID animals, and mice were randomized to treatment cohorts when tumors reached an average of 100 mm³. Similar to B16-F10 tumors, the eliglustat and DC661 combination produced significant tumor growth inhibition (~80%) in mice bearing A375P tumors compared to either treatment alone (Figure 7A). The eliglustat and DC661 combination significantly prolonged the survival of tumor-bearing mice compared to DC661 alone (median 34 days v. 17 days: Log-rank p-value <0.0001) (Figure 7B). The combination of eliglustat (60 mg/kg) and DC661 (1 mg/kg) was also tolerable in animals for long-term treatment with no significant body weight change after the treatments were started (Figure 7C). To test this combination in a more clinically relevant tumor model, we utilized the PDX-WM4552 cell line, which was derived from a patient who never responded and progressed on the combination of HCQ with the BRAF inhibitor dabrafenib and the MEK inhibitor trametinib in the BAMM trial (NCT02257424) (37). The combination of Genz-123346 and DC661 significantly enhanced the cytotoxicity of DC661 in PDX-WM4552 cells (Figure 7D–E). In PDX-WM4552 cells DC661 treatment increased UGCG levels (Figure S5A), and Genz-123346 treatment completely abrogated DC661 induced GMM formation on plasma membranes and lysosomes (Figure S5B). We previously showed that PDX-WM4552 grown on the flanks of NOD-SCID mice was highly resistant to dabrafenib + trametinib treatment (38). To determine if combined UGCG inhibitor and LAI had activity in this highly therapy refractory tumor model, we generated PDX-WM4552 tumors on the flanks of NOD-SCID mice and randomized mice into treatment cohorts when tumors reached an average size of 135 mm³. Treatment with either DC661 (3 mg/kg, every two days) or eliglustat (30 mg/kg, every day) alone produced minimal tumor growth inhibition, whereas the combination of DC661 and eliglustat produced significant tumor growth inhibition (86%) (Figure 7F). Tumor weight and size when control tumors reached an average volume of 2500 mm³ demonstrated the activity of this combination (Figure S5C–E). DC661 and eliglustat treatment significantly improved survival of mice compared to DC661 alone (median 20 days v. 9 days: Log-rank p-value <0.0011) (Figure 7G). The DC661 and eliglustat combination was tolerable to animals with no significant body weight changes (Figure 7H). Taken together, these findings demonstrate that LAI induces UGCG-dependent lipid remodeling that resists LMP leading to cancer cell survival. These LAI-induced changes were also correlated with increased GMM formation on plasma membrane and lysosomes. The UGCG inhibitor eliglustat reverses the LAI induced changes in glycosphingolipids, abrogates GMM formation, and augments LAI-induced LMP, resulting in cancer cell death (Figure 7I).

Figure 7: UGCG inhibition combined with LAI impairs tumor growth in a xenograft and therapy resistant PDX tumor models.

(A-C) A375P tumors were generated in the flanks of NOD-SCID mice, and animals were treated with either vehicle, DC661 (1 mg/kg, every 2 days), eliglustat (60 mg/kg, every day), or the combination as shown in panel A. A. Tumor volumes (mean ± s.e.m.) in different cohorts (n=10–15) measured every day. Adjusted P values are shown for the measurements on day 18. B. Kaplan–Meier survival curves showing the percentage of tumor-bearing animals that survived in different cohorts (n=10–11). Animals were removed from the study when tumor size reached ~2000 mm³. C. Percent change in the average body weights in each cohort of tumor-bearing animals with respect to day 1 of treatment. Body weights were measured every three days, as shown. D. MTT assay graph for PDX-WM4552 cells treated with DC661 (0 to 0.3 μM) alone or in combination with Genz-123346 (Genz, 20 μM). E. 7-day colony formation assay with DC661 (0.1 μM) and Genz (5 μM) in PDX-WM4552 cells. (F-H) PDX-WM4552 tumors were generated in the flanks of NOD-SCID mice. After tumors reached 135 mm³, mice were treated with either vehicle, DC661 (3 mg/kg), eliglustat (30 mg/kg), or the combination as shown in panel F. F. Tumor volumes (mean ± s.e.m.) in different cohorts (n=8–10) measured every day. Adjusted P values are shown for measurements on day 9. G. Kaplan–Meier survival curves showing the percentage of animals that survived in different cohorts (n=6–9). H. Percent change in the average body weights in each cohort of tumor-bearing animals with respect to day 1 of treatment. Body weights were measured every three days, as shown. I. Graphical sketch illustrating that UGCG-dependent lipid remodeling predominantly increases glycosphingolipids (GSL) level, is associated with the increased formation of GMM on plasma membrane and lysosomes. UGCG upregulation is a druggable resistance mechanism to LAI-induced LMP associated cancer cell death. *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; ****P ≤ 0.0001; ns, not significant. Two-way ANOVA followed by Tukey’s multiple comparisons procedure (A, D and F); Log-rank (Mantel-Cox) test (B and G).

Discussion

HCQ was the first autophagy inhibitor tested as a cancer therapeutic in clinical trials. Single-agent autophagy inhibition with HCQ produced a 0% response rate in a pancreatic cancer clinical trial (39). Even in combination with other standard of care anticancer agents, HCQ showed variable results. In some cases, there were no signs of clinical activity (8,9). There were clear signs of increased response rates in other clinical trials that did not translate into long-term progression-free survival (37,40,41). The finding that PPT1 is the target of HCQ paved the way for the development of novel lysosomal autophagy inhibitors such as DC661 (5) and GNS561 (6). PPT1 inhibition by GNS561 has also been shown to induce LMP-mediated cell death in vitro (6). GNS561 has modest single-agent efficacy in tumor models, and a phase I clinical trial of GNS521 showed no responses in patients with treatment-refractory hepatocellular carcinoma (42). The findings here suggest that UGCG mediated lipid remodeling plays a role in resistance to PPT1 inhibitors. Of note, our limited studies here demonstrated that inhibition of upstream autophagy targets ULK1 or VPS34 did not increase the levels of UGCG, suggesting the compensatory changes in lipid metabolism may be specific to LAI.

While there are few reports suggesting that cancer cells can adapt to genetic autophagy inhibition (e.g., ATG7 knockout) by upregulating an NRF2 dependent antioxidant response (7) or by altering their mitochondrial dynamics and using mitochondrial-derived vesicles to maintain their functional mitochondria (43), the molecular basis of resistance related to LAI remains underexplored. We demonstrated that LAI induced significant changes in a small percentage of the proteome of melanoma cells with increases in proteins involved in autophagy and lipid metabolism. Further, we found that LAI causes a striking remodeling of the cellular lipidome with enrichment in cholesterol and sphingolipids, especially glycosphingolipids, including GM1. These changes are likely due to tumor cells scavenging cholesterol and sphingolipids from the extracellular matrix to increase GMM formation. Alternatively, GMM may not play a causative role in LAI-resistance, and changes in lipid metabolism enzymes and lipid species directed by enzymes such as UGCG may simply facilitate a metabolic adaptation to lysosomal impairment. Regardless of whether or not GMM are critical for lysosomal repair following injury, the ability to measure them on cell surfaces allows the possibility of GMM’s serving pharmacodynamic biomarkers of LAI and/or UGCG inhibitors. We found GMM formation increased in multiple human cancer cell lines following LAI, and were abrogated following UGCG inhibition, suggesting the findings in melanoma models are likely to be applicable broadly across other cancers.

GMM are glycosphingolipid and cholesterol-rich microdomains within lipid membranes. There is a significant controversy over whether GMM can be referred to as lipid rafts, implying a somewhat rigid structure, or are simply transient associations of freely mobile lipid species and proteins within membranes (44). Our super-resolution and standard microscopy experiments together have provided further evidence that the accumulation of GMM observed with DC661 occurs in a domain-like structure can be reversed with UGCG inhibition. However, we acknowledge that this pattern is merely an association and further work is needed to demonstrate whether GMM are mechanistically critical for lysosomal membrane repair. Regardless, the association between GMM and UGCG activity could be translated into bioassay to measure pharmacological UGCG inhibition in clinical trials. Targeting UGCG with eliglustat improves symptoms in Gaucher’s disease (45), a lysosomal storage disorder. Eliglustat is an oral therapy with favorable pharmacokinetics and pharmacodynamics in humans for long-term daily use (45,46). Interestingly, lysosomal accumulation of glucosylceramides in Gaucher’s disease, due to a defect in lysosomal glucocerebrosidase, has been hypothesized to promote cancer growth (47). In a mouse model of Gaucher’s disease that is driven by a mutation in the glucocerebrosidase gene, engraftment of melanoma cells produced larger tumors in comparison to the wild-type animals with melanoma tumor (47). We found that targeting UGCG augmented DC661 cytotoxicity in vitro and in vivo in 3 different melanoma tumor models.

Our findings suggest that pursuing other druggable targets besides UGCG involved in cholesterol and sphingolipid metabolism could augment LAI treatment. In a recent study, SR-B1-dependent HDL uptake was reported as a metabolic vulnerability in renal cancer (48). Chemical inhibition of CerS2, which is involved in both de novo and salvage ceramide synthesis, but not serine palmitoyltransferase, the rate-limiting enzyme of de novo ceramide synthesis, augmented DC661 cytotoxicity in MTT assays, confirming the involvement of salvage but not de novo ceramide synthesis after LAI. Notably, ceramides with longer-chain fatty acids synthesized by CerS2 have also been reported to have anti-apoptotic functions (49), which could contribute to LAI resistance observed in our study. Importantly, ceramides have been found in the LDL or HDL particles which can be imported into the cell by LDLR or SR-B1, respectively (50,51). Further work is needed to nominate other cholesterol and sphingolipid metabolism enzymes as putative therapeutic targets in melanoma and other cancers. Since UGCG was found to be a cancer dependency gene, a UGCG inhibitor could have single-agent activity in multiple cancers, as recently shown in prostate cancer (52). The striking in vivo antitumor activity and tolerability of combined LAI and UGCG inhibition suggests that a clinical trial combining eliglustat with HCQ or a more potent PPT1 inhibitor could be launched.

Materials and Methods

Cell lines and cell culture

The human A375P (CRL-3224), DLD-1 (CCL-221), MIA PaCa-2 (CRL-1420) and A549 (CCL-185), and mouse B16-F10 (CRL-6475) cell lines were purchased from American Tissue Type Collection (ATCC). The human melanoma PDX lines WM4380 and WM4552 were obtained from Meenhard Herlyn, Wistar Institute. All cell lines were tested for Mycoplasma biannually by MycoAlert Mycoplasma Detection Kit (Cambrex Bio Science Rockland, Inc.), and authenticated using short-tandem repeat fingerprinting by University of Pennsylvania Core facilities. The A375P cell line was cultured in RPMI 1640 (Invitrogen, 11875), and other cell lines were cultured in DMEM, supplemented with 10 % fetal bovine serum (F6178, Sigma-Aldrich) and 1X antibiotic antimycotic solution (A5955, Sigma-Aldrich). Cells were grown at 37°C in the presence of 5 % CO2.

Chemicals and reagents

Chemicals purchased included Hydroxychloroquine (HCQ) Sulfate (Spectrum Chemicals, 747–36-4); DC661 (Selleckchem, S8808); Methyl-Beta-Cyclodextrin (332615, Sigma); Cholesterol-Water Soluble (C4951, Sigma); Simvastatin (10010344, Cayman Chemical); BLT-1 (HY-116767, MedChemExpress); Myriocin (63150–5, Cayman Chemical); Fumonisin B1 (62580–1, Cayman Chemical); Siramesine hydrochloride (6740, Tocris Bioscience); Genz-123346 (BioVision, B2286); Eliglustat hemitartarate (HY-14885A, MedChemExpress LLC); Eliglustat hemitartarate (21487, Cayman Chemical); SBI-0206965 (18477, Cayman Chemical); SAR-405 (16979, Cayman Chemical) and LysoSensor^™ Green DND-189 (Thermo Fisher; L7535). ST1074 was synthesized by Holger Stark and Aleksandra Zivkovic (21).

Proteomics

Melanoma A375P cells were seeded in 60 mm dishes at 0.7 × 10⁶ cells per dish. Frozen cell pellets were lysed with 50 mM Tris pH 7.4, 1% SDS, 150 mM NaCl, 1 mM EDTA, 0.15 mM PMSF, 1 μg/ml pepstatin, and 1 μg/ml leupeptin. Samples were processed using previously published methods (53,54). Raw MS data was analyzed using MaxQuant 1.6.5.0 (http://www.maxquant.org) with a Uniprot human sequence database (October 10, 2019) and a common contaminants database including trypsin, keratins, bovine proteins, and mycoplasma (55). Tryptic peptide specificity with a maximum of 2 missed cleavages, fixed modification on cysteine (Carbamidomethylation), and variable methionine oxidation or N-terminal acetylation were used in the search (56). A cutoff of 1% false discovery rate (FDR) was used for peptides and proteins. Match between runs was enabled; proteins were quantified using label-free quantitation (57). Statistical analysis was performed using Perseus 1.6.2.3 (http://www-perseus-framework.org) (58,59). Proteins were required to be identified by at least 3 unique peptides and have 3 valid values (non-zero quantitation) within a sample group, and contaminants and reverse proteins were filtered from the dataset. Missing values were imputed from a normal distribution. Pairwise comparisons between conditions were performed at the protein level using students t-test with permutation-based FDR with s0=0.1 and 250 randomizations. Significant changes were defined as FDR < 5% and an absolute fold change greater than 1.5 (or 2.0). Ingenuity Pathway Analysis (IPA) with default parameters (http://www.ingenuity.com/pa/) was conducted as previously reported (60). Significantly enriched canonical pathways were reported using a threshold of -log (p-value) of 3 (P value < 0.001).

Lipidomics

Melanoma A375P cells were seeded in 60 mm dishes at 0.7 × 10⁶ cells per dish. When cells were at ~50% confluence, they were treated with DMSO (control), DC661 (3 μM), or HCQ (30 μM) for 24 h. Samples were processed according to previously published methods (60). Lipids were identified and quantitated using LipidSearch 4.2 (Thermo Fisher Scientific). The identified lipid species were filtered by expected adducts and identification grade based on class. Peak areas were normalized to the EquiSPLASH standards for supported classes and further normalized based on the total area for each sample to correct for variation in cell number. Log-transformed data was analyzed in Perseus 1.6.2.3 to determine lipid fold changes between conditions (58,59).

Fluorescence microscopy and quantification methods

For cholesterol detection, A375P cells were grown on a polylysine coated 8 well μSlide with #1.5H glass coverslip bottom for high resolution microscopy (80807, ibidi USA). After the treatments, cells were washed with physiological buffered solution (A14291DJ, Thermo Fisher Scientific) and fixed with 4 % paraformaldehyde (19943, Affymetrix) for 15 min. Unused paraformaldehyde was quenched by the 1.5 mg glycine/ml PBS solution for 10 min at room temperature. After washing, cells were stained with 0.05 mg/ml filipin complex (F-9765, Sigma) solution in PBS for 2 h at room temperature. Cells were washed 3X with PBS and anti-LAMP1 antibody was added without permeabilization and incubated overnight at 4°C to probe for lysosomes. After washing off the primary antibody, species-specific Alexa-561 labeled secondary antibody was applied and incubated for 1 h at room temperature. Cells were imaged using Olympus IX71 inverted confocal microscope equipped with Visitech super resolution VT iSIM scan head (Visitech International Ltd.) and Hamamatsu ORCA Flash 4.0 sCMOS camera with the excitation UV laser (405 nm) for filipin and red laser (561 nm) for Alexa-561, with a 60x water-immersion objective.

For GMM and lysosome detection, cells were grown in a polylysine coated 8 well μSlide with #1.5H glass coverslip bottom for high resolution microscopy (80807, ibidi USA). A Vybrant^™ Alexa Fluor^™-488 Lipid Raft Labeling Kit (V34403, Thermo Fisher Scientific) which uses Alexa Fluor^™-488 labelled CTxB (AF-488-CTxB) was used to detect GM1, as per the manufacturer’s protocol. For intracellular GM1 staining, cells were permeabilized after the fixation step of the standard protocol using the 0.1 % Triton X-100 solution in PBS (A14291DJ, Thermo Fisher Scientific) for 10 min and were labelled again with AF-488-CTxB as per the manufacturer’s protocol. For lysosomes, monoclonal LAMP-1 primary antibody (sc-28320, Santa Cruz Biotechnology, Inc.) at 1:50 dilution was added overnight at 4°C after the intracellular AF-488-CTxB staining, followed by the standard protocol of immunofluorescence. For GM1 and lysosomes detection in animal tumors, a part of tumor tissue was flash frozen in O.C.T. compound (Sakura Finetek USA, Inc.) immediately after euthanasia. Vybrant^™ Alexa Fluor^™ 594 Lipid Raft Labeling Kit (V34405, Thermo Fisher Scientific) was used to stain GM1 in the frozen tumor tissue sections following manufacturer’s protocol using AF-594-CTxB at 1:100 dilution. Nuclei were stained using NucBlue reagent (Hoechst 33342) (R37605, Thermo Scientific) as per the manufacturer’s protocol. Secondary antibody: AlexaFluor-594 (A-11032, Thermo Fisher Scientific). Cells were imaged using an Olympus IX71 inverted confocal microscope equipped with Visitech super resolution VT iSIM scan head (Visitech International Ltd.) and Hamamatsu ORCA Flash 4.0 sCMOS camera with a 100x, 1.40 NA oil-immersion objective.

For image quantifications, mean fluorescence background intensity was subtracted from all images before quantifying raw integrated density. Labelled CTxB and filipin intensity quantifications were done on a single cell level using ImageJ/FIJI software (61); raw integrated density of fluorescence was measured separately on plasma membrane and intracellular lysosomes by creating separate regions of interest (ROI) in a cell. A total of at least 50 cells were counted in multiple image fields per condition. Mander’s correlation coefficient for colocalization of LAMP-1 positive lysosomes over AF-488-CTxB was calculated using JACoP (Just Another Colocalization Plugin) (62) plugin of ImageJ/FIJI software in multiple image fields with at least 25 cells in each experimental group.

High-resolution confocal microscopy with deconvolution

A375P cells were grown in an 8-well μslide for high-resolution confocal microscopy (80807, ibidi USA). GM1 and lysosomes (LAMP-1) were labelled similarly as mentioned in the standard confocal microscopy method above. For labelling membrane lipid microdomain markers GM1 and flotillin-2 together, AF-488-CTxB surface labelling was followed by the addition of a monoclonal flotillin-2 primary antibody (610384, BD Transduction Laboratories) at 1:10 dilution for 2 h at 4°C followed by fixation and permeabilization (0.01 % Triton X-100) to label intracellular GM1 and flotillin-2. Secondary antibody: AlexaFluor-555 (A-21422, Thermo Fisher Scientific). For cell membrane detection with AF-488-CTxB labelling, MemBrite Fix 640/660 cell surface staining kit (30097-T, Biotium) was used as per the manufacturer’s instructions. Nuclei were stained using NucBlue (R37605, Thermo Scientific). Images were acquired with a 100x (1.46 NA) oil-immersion objective lens on a laser scanning Leica SP5 confocal microscope. An additional optical zoom factor of 3.5–5.0x was applied and Z-stacks were acquired at 0.17–0.21 μm intervals. The resulting image stacks were processed in Huygens deconvolution software to yield high resolution images.

Super-resolution STED microscopy with deconvolution

A375P cells were grown on STED compatible poly-D-lysine coated precision coverslips (GG-12–15H-PDL, Neuvitro Corporation). GM1 and lysosomes (LAMP-1) were labelled similarly as mentioned in the high-resolution confocal microscopy method above. The nuclei staining was omitted. Coverslips were mounted on a glass slides using ProLong^™ Gold Antifade Mountant (P36930, Thermo Scientific). Images were acquired with 100x/1.4 NA HC PL APO CS2 oil immersion objective lens on a Leica TCS SP8 gated STED microscope using an optical zoom factor: 4x, Z-step size: 120 nm, pixel size: 25 nm and scan speed: 600 Hz with unidirectional scanning. All images were deconvolved using Huygens Professional v. 20.10.0p2. A 4-line averaging was done for both STED channels with the following settings for green channel excitation: 490 nm, 8%-10% laser power, green channel depletion laser 592 nm, total power 40% with 60% towards z depletion, HyD detector using time-gating window 1.2 ns - 6.5 ns, pinhole set to 0.77 A.U. = 116.38 micron, and for red channel excitation: 555 nm, 8% laser power, red channel depletion laser 660 nm, total power 50 with 60% towards z-depletion, HyD detector using time-gating window 1.5 ns - 6.1 ns, pinhole set to 0.7 A.U. = 103.1 micron.

For A375P-Galectin-3 cells and A375P-mcherry-GFP-LC3 reporter cells, pEGFP-hGal3 was a gift from Tamotsu Yoshimori (Addgene plasmid #73080) (63) and was used for creating stable A375P-Galectin-3 line for LMP detection. For LMP, 100 cells in multiple image fields were assessed for % of puncta positive cells. pDEST-CMV mCherry-GFP-LC3B WT plasmid was a gift from Robin Ketteler (Addgene plasmid # 123230) (64) and was used for generating stable A375P-mcherry-GFP-LC3 reporter cells. Images were acquired using Olympus IX71 inverted confocal microscope equipped with Visitech super resolution VT iSIM scan head (Visitech International Ltd.) and Hamamatsu ORCA Flash 4.0 sCMOS camera with a 60x/water objective lens.

For lysosomal lipase assay, LysoLive^™ Lysosomal Acid Lipase Assay Kit (ab253380) was used following manufacturer’s instructions. Briefly, A375P cells were grown in an 8 well μSlide (80807, ibidi USA) and were treated with vehicle control (DMSO), DC661 (1 μM) or Bafilomycin (20 nM) for 24 h followed by 2 h incubation of LipaGreen substrate. Cells were imaged using a 20x air objective lens on a camera based confocal microscope. LipaGreen mean fluorescence raw integrated density was measured from ~400 cells from two independent experiments/group using ImageJ/FIJI software.

Immunoblotting

Treatments were given and cells were collected by scraping. Whole cell lysates were prepared using 1 % SDS lysis buffer (1 % SDS; 50 mM Tris; 150 mM NaCl; 1 mM EDTA; 150 mM PMSF; 1 μg/ml Leupeptin; 1 μg/ml Pepstatin; pH 7.5). Protein concentration was measured using Pierce^™ BCA Protein Assay Kit (23225, Thermo Scientific). 15–30 μg protein was used for SDS-PAGE and was transferred onto a PVDF membrane (1620177, BIO-RAD). Membrane was blocked using 5 % BSA or 5 % non-fat dry milk as per the optimized conditions and incubated with primary antibody overnight at 4 °C. Primary antibodies included β-Actin (3700, Cell Signaling Technology), UGCG (H00007357-M03, Abnova); Flotillin 1 (610820, BD Transduction Laboratories), Flotillin-2 (sc-28320, Santa Cruz Biotechnology), LDLR (AF2148, R&D Systems), CerSyn2 (SAB2101321, Sigma-Aldrich), Cl-Cas-3 (9661, Cell Signaling Technology); SR-B1 (SAB3500048, Sigma-Aldrich); PPT1 (TA800501, Origene). PVDF membranes were washed with 1X TBS-T (CS-9997, Cell Signaling Technology, Inc.) and incubated for 1 h at room temperature with species-specific horseradish peroxidase-conjugated secondary antibody (CS-7076S, CS-7074S, Cell Signaling Technology Inc.; or SC-2304, Santa Cruz Biotechnology, Inc.). Membranes were subsequently washed and developed using Pierce ECL Western Blotting substrate (32106, Thermo Scientific) and autoradiography films (XAR ALF 1318, Lab Scientific, Inc.).

Synergy testing

DC661 and Genz cross-titrations were added to two white 384-well plates (Greiner 781098) using Beckman Coulter ECHO®650 instrument (triplicates per plate). B16F10 (DMEM, 10% FBS, P/S) and A375P (RPMI, 10% FBS, P/S) were trypsinized, washed, counted, and added to each 384-well plate at a density of 500 cells/25 μl per well. Assay plates were incubated at 37°C, 5% CO2 for 72 h. After 72 h, CellTiterGlo solution was prepared (Promega #G7573), and 12 μl was added to each well. The assay plates were placed in an orbital shaker for 15 min, and luminescence signal measured with BMG Labtech ClarioStarPlus plate reader. For normalized % inhibition calculation, the observed lowest viability value (L) on each plate and the average viability value at dose 0 of two drugs (H) on the same plate were used as controls. Using O, stands for the observed viability at a given combined dose level, the normalized % inhibition was calculated as 100-(O-L)/(H-L) *100. Data analysis for drug combination effect was done using Combenefit software with Bliss surface model (65).

Overexpression and knockdown

Human UGCG pcDNA3.1+/C-(k) DYK (OHu61224D) plasmid and negative control vector backbone pcDNA3.1+/C-(K)-DYK were purchased from GenScript USA Inc. Plasmids were transfected (1 μg/ml) into A375P cells using jetPRIME reagent (101000046, Polyplus-transfection) as per manufacturer’s protocol; transfected cells were stably selected using G418 sulphate antibiotic (10131035, Gibco). UGCG overexpression was confirmed by immunblotting using anti-DYKDDDDK tag antibody (2368S, Cell Signaling Technology). For knockdown experiments, human UGCG siRNA (sc-45404) or human PPT1 siRNA (sc-105216) along with negative control scrambled siRNA (sc-44236) were purchased from Santa Cruz Biotechnology and were transfected (40 nM) into A375P cells using jetPRIME reagent (101000046, Polyplus-transfection) as per manufacturer’s protocol.

Lysosomal Immunoprecipitation

Lysosomes were purified using lysosomal immunoprecipitation (Lyso-IP) method (12). A375P cells were infected with pLJC5-Tmem192–3xHA lentivirus and selected using 1 mg/ml puromycin. Approximately 3 ×10⁶ A375-P-Tmem192-HA cells were treated with either 3 μM DC661 or DMSO vehicle control for 24 h in culture conditions. After treatment, cells were washed in PBS, harvested in 0.5 ml cold KPBS (136 mM KCl, 10 mM KH2PO4, pH 7.25), and gently homogenized using 20 strokes in a 2 ml Dounce homogenizer. About 2.5 % of the homogenate was reserved for whole cell lysate analysis and the remainder was centrifuged at 3,000 x g for 2 min at 4 °C to remove cell membrane debris. Homogenate supernatant was then transferred into a clean 1.5 ml tube and was incubated with 50 μl anti-HA beads for 15 min at 4 °C. Samples where then precipitated by placing tubes on DynaMag (12321D, Thermo Fisher Scientific), and rocked gently for 2 min at room temperature. Supernatant was reserved for unbound fraction analysis. The IP fraction was washed 3 times with KPBS containing 8 mM CaCl2 and suspended in PBS for lipidomics analysis.

MTT (3- [4, 5-dimethylthiazol-2-yl]-2, 5 diphenyl tetrazolium bromide) cell viability assay

2,000 cells were plated in triplicates in each well of a 96-well plate and 3-day MTT assays were performed using the Cell viability Kit (11465007001, Roche) following the manufacturer’s protocol. Cells were co-treated with DC661 +/− chemical inhibitors of sphingolipid/cholesterol pathway enzymes. MBCD pre-treatment was given for 3 h followed by co-treatment of the cells with MBCD +/− DC661 +/− water soluble cholesterol. LDL receptor was neutralized by the 2 h pre-treatment with anti-LDLR antibody followed by LDLR +/− DC661 treatment. An isotype antibody (AB-108-C, R&D Systems) was used as the control.

Colony formation assay

1,000 cells per well were seeded into 12-well plates and were treated the next day; cells were kept under the treatment for a total of 7 days. Colonies formed in each well were washed with PBS, fixed with cold methanol at −20°C for 10 min and stained with Crystal violet 1 % aqueous solution (V5265; Sigma).

Analysis of UGCG expression and disease-specific survival among melanoma patients

The analysis of UGCG expression was done using the z-score normalized expression of UGCG downloaded from the Memorial Sloan Kettering Cancer Center’s cBioPortal website based on RNAseqV2 expression data from TCGA patients included in the Pan-Cancer Atlas study (the Learning Dataset). These data were generated by the TCGA Research Network: https://www.cancer.gov/tcga. A Cutpoint for UGCG expression was identified using the Contal and O’Quigley method (66) using the maximum Q statistic based on the log-rank test to find a cutpoint for a biomarker such that the survival curves of the low and high groups are most different. The algorithm has been implemented in a SAS macro % FINDCUT by Mandrekar and Meyers (available from: https://www.lexjansen.com/mwsug/2015/DV/MWSUG-2015-DV-07.pdf) (67). UGCG expression for the Validation Dataset is accessible at NCBI GEO database (accession GSE65904) (34). This analysis used the percentile of the cutpoint from the Learning Dataset to define two groups; the log-rank test was then used to evaluate whether the two disease-specific survival curves were significantly different. Cutpoint identification and survival analyses were done in SAS software Version 9.4.

In vivo mouse studies

C57/BL6 mice were used for B16-F10 syngeneic, and NOD-scid gamma (NSG) mice (Jackson Laboratory) were used for A375P and PDX-WM4552 xenograft studies. Tumor generation, tumor measurement, and tumor harvesting were performed as previously described (38). Briefly, 0.5 ×10⁶ B16-F10, 5 ×10⁶ A375P or 1 ×10⁶ PDX-WM4552 cells were subcutaneously injected with an equal volume of Matrigel (354248, Corning) in the right flank of animals. Tumors were measured using electronic calipers, and tumor volume was calculated as V=LxW²×0.5. For the survival experiment mice were sacrificed when signs of morbidity that met ethical criteria for sacrifice were observed or when the tumor reached to average size of 2000–2500 mm³. All animal experiments were performed in accordance with the protocols approved by the Institutional Animal Care and Use Committee of the University of Pennsylvania. All compounds were administered via intraperitoneal route (100 μl injection volume). Eliglustat (HY-14885A, MedChem Express) and HCQ injections were prepared in PBS. DC661 injections were prepared in a formulation of DMSO: PEG 400: Tween 80: Water (10:10:10:70; V/V).

Statistical analysis

If not described elsewhere, experimental data were analyzed with GraphPad Prism 9 software. Student’s t test was used to evaluate whether the difference between two groups means was statistically significant. The null hypothesis was rejected if the P value was less than 0.05. The ANOVA was used to compare group means when more than two groups were compared. In cases where the group variances were not equal (assessed using Bartlett’s test or Brown-Forsythe’s test), Welch’s t test or Welch’s ANOVA test was used.

Significance.

We discovered UGCG-dependent lipid remodeling drives resistance to LAI. Targeting UGCG with a drug approved for a lysosomal storage disorder enhanced LAI antitumor activity without toxicity. LAI and UGCG inhibition could be tested clinically in multiple cancers.

Data availability

The proteomics data have been deposited into the MassIVE public repository (https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=f98972f2b1c74e6e8e988a5329b5729e ) with accession MSV000089020 and the ProteomeXchange repository (http://proteomecentral.proteomexchange.org) with accession PXD032120.