Phosphoproteomic Screen Identifies Potential Therapeutic Targets in Melanoma

Published OnlineFirst April 26, 2011; DOI: 10.1158/1541-7786.MCR-10-0512

Molecular Cancer Signaling and Regulation Research

Kathryn Tworkoski1, Garima Singhal1, Sebastian Szpakowski2, Christina Ivins Zito1, Antonella Bacchiocchi3, Viswanathan Muthusamy3, Marcus Bosenberg3, Michael Krauthammer1, Ruth Halaban3, and David F. Stern1

Abstract Therapies directed against receptor tyrosine kinases are effective in many cancer subtypes, including lung and breast cancer. We used a phosphoproteomic platform to identify active receptor tyrosine kinases that might represent therapeutic targets in a panel of 25 melanoma cell strains. We detected activated receptors including TYRO3, AXL, MERTK, EPHB2, MET, IGF1R, EGFR, KIT, HER3, and HER4. Statistical analysis of receptor tyrosine kinase activation as well as ligand and receptor expression indicates that some receptors, such as FGFR3, may be activated via autocrine circuits. Short hairpin RNA knockdown targeting three of the active kinases identified in the screen, AXL, HER3, and IGF1R, inhibited the proliferation of melanoma cells and knockdown of active AXL also reduced melanoma cell migration. The changes in cellular phenotype observed on AXL knockdown seem to be modulated via the STAT3 signaling pathway, whereas the IGF1R-dependent alterations seem to be regulated by the AKT signaling pathway. Ultimately, this study identifies several novel targets for therapeutic intervention in melanoma. Mol Cancer Res; 9(6); 801–12. 2011 AACR.

Introduction melanoma cell proliferation and survival (4–9). The use of RTK-directed therapeutics in melanoma has, however, Next generation cancer therapies that target receptor been limited by the lack of available information about tyrosine kinases (RTK) have a major impact on the dis- active RTKs in this disease. ease-free progression and survival of patients with breast To identify potential RTK therapeutic targets in mela- cancer and non–small cell lung carcinoma (NSCLC). RTK noma, we surveyed the expression of all 58 human RTKs inhibitors in clinical use include the antibodies trastuzumab and their agonists in a panel of 24 low-passage melanoma for HER2-positive breast cancer and cetuximab in epidermal cell strains and 1 commercially available melanoma cell line. growth factor receptor (EGFR)-positive colorectal cancer. The functional activation of 42 human RTKs was also Small molecule kinase inhibitors also target EGFR in examined and used to identify which RTKs are most NSCLC (Erlotinib), and KIT or platelet-derived growth frequently and intensely activated in melanoma. Short factor receptor (PDGFR) in gastrointestinal stromal tumors hairpin RNA (shRNA)-mediated knockdown of AXL, (Imatinib). HER3, and IGF1R, 3 of the RTKs identified in the screen, The incidence of melanoma has steadily risen in the resulted in decreased melanoma cell proliferation. AXL United States over the past 30 years, yet individuals with knockdown also reduced melanoma cell migration and late-stage melanoma have a median survival time of only these cellular responses seem to be regulated by the STAT3 9 months (1–3). Imatinib has been used to treat melanomas signaling pathway. These data identify new candidates for with mutationally activated KIT, whereas experimental therapeutic intervention in melanoma. studies show that targeting RTKs such as MET and insulin-like growth factor 1 receptor (IGF1R) may inhibit Materials and Methods

Cell culture 1 2 Authors' Affiliations: Department of Pathology, Graduate Program in Yale University (YU)-designated and WW165 melanoma Computational Biology and Bioinformatics, and 3Department of Derma- tology, Yale University School of Medicine, New Haven, Connecticut cell strains were derived from primary and metastatic lesions Note: Supplementary data for this article are available at Molecular Cancer as described (10). Melanoma tumors were excised as part of Research Online (http://mcr.aacrjournals.org/). patient clinical care and were collected with the partici- G. Singhal, S. Szpakowski, and C.I. Zito contributed equally to the study. pants’ informed written consent according to HIPAA Corresponding Author: David F. Stern, BML 348 310 Cedar Street, New (Health Insurance Portability and Accountability Act) reg- Haven, CT 06510. Phone: 203-785-4832; Fax: 203-785-7467; E-mail: ulations with the approval of the Yale Human Investigation [email protected] Committee. Primary and metastatic melanoma cell strains doi: 10.1158/1541-7786.MCR-10-0512 were used prior to passage 20. Most melanoma cells were 2011 American Association for Cancer Research. cultured in OptiMEM (Invitrogen) supplemented with 5%

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FBS and 1% penicillin/streptomycin (basal medium). The iScript cDNA Synthesis Kit from BioRad by using 0.8 mgof WW165 primary melanoma and YUHEIK mucosal mel- RNA per reaction. Universal TaqMan Master Mix (Applied anoma cells were grown in basal medium supplemented Biosystems) was used to conduct quantitative real-time with 0.1 mmol/L IBMX (3-isobutyl-1-methylxanthine; PCR (qRT-PCR) by using a 1 to 10 dilution of the resulting Sigma-Aldrich). Normal human melanocytes from new- cDNA. The following primers were used following the born foreskins (NBMEL) and discarded adult skin manufacturer's protocols: AXL (Hs0024357_m1), HER3 (RMP32F) were grown in basal medium supplemented (Hs00951455_m1), and glyceraldehyde 3 phosphate dehy- with 16 nmol/L 12-O-tetradecanoyl phorbol-13-acetate, drogenase (GAPDH; Hs99999905_m1; Applied Biosys- 0.1 mmol/L 3-isobutyl-1-methylxanthine, 2.5 nmol/L cho- tems). Relative mRNA expression was determined with the m 0 D lera toxin, 1 mol/L Na3VO4, and 0.1 mmol/L N6,2 -O- Ct method by using GAPDH as the reference gene. Gene dibutyryladenosine 30,50-cyclic monophosphate (Sigma- expression values for tumor RNAs were normalized to a Aldrich), termed TICVA (11). HEK293T cells from the negative control. A single RNA preparation was analyzed for American Type Culture Collection (ATCC) were grown in each microdissected tumor, and duplicates for each tumor Dulbecco's modified Eagle's medium containing 10% FBS, block. 1% penicillin/streptomycin, and 1% HEPES. MDA-MB- 231 cells, MDA-MB-453 cells, and BT474 cells (ATCC) Cell lysis, RTK arrays, immunoblotting, and were grown in RPMI containing 10% FBS and 1% hierarchical clustering penicillin/streptomycin. Where indicated, cells were starved in 0.1% serum prior to lysis, and pervanadate (50 mmol/L final) was added for 20 Gene expression analysis minutes before lysis. Cells were lysed in NP-40 lysis buffer Whole genome gene expression analysis was based on [1% NP-40, 150 mmol/L NaCl, 50 mmol/L Tris (pH 7.4), 5 data generated by the Yale SPORE in Skin Cancer (12). mmol/L EDTA, 10% glycerol with complete EDTA-free Briefly, NimbleGen human whole genome expression protease inhibitor tablets (Roche) and phosphatase inhibitor microarrays (array 2005-04-20_Human_60mer and array cocktails 1 and 2 (Sigma-Aldrich) added immediately before 2006-08-03_HG18_60mer) were used for hybridization cell lysis]. Cell lysates (250 mg) were analyzed with the Human of cDNA from normal melanocytes and melanoma cells Phospho-RTK Array Kit (R&D Systems); array maps at at NimbleGen Systems Iceland LLC, Vínlandsleið 2-4, http://www.rndsystems.com/pdf/ary001.pdf. Protein sam- 113 Reykjavik, Iceland (currently Roche Applied Science, ples were prepared for electrophoresis by addition of 5 Basel, Switzerland) and by the Yale W.M. Keck Founda- Laemmli sample buffer, and immunoblotting was carried tion Biotechnology Resource as described (12). The out on nitrocellulose membranes blocked in 5% milk in microarray data from melanoma cell lines (YUCAS, Tris-buffered saline Tween-20 (1.5 mol/L NaCl, 0.2 mol/L YUCOT, YUDOSO, YUGOE, YUHEF, YUHUY, Tris-HCl, 0.05% Tween 20). Membranes were incubated YUKIM, YUKSI, YULAC, YUPLA, YUROB, YUROL, with antibodies in 5% milk or 5% bovine serum albumin YUSIV,YUTICA,YUZOR,WW165,andYUHEIK) overnight at 4C: anti-pHER3, anti-pIGF1R, anti-IGF1R, and 4 independent normal melanocytes cell cultures anti-pKIT, anti-MERTK, anti-pMET, anti-MET, anti- (NBMEL1-3 and RMP32F) were used to determine a pSTAT3, anti-STAT3, anti-pAKT, anti-AKT (Cell Signaling gene expression call (expressed/nonexpressed) and a mean Technology), anti-HER3, anti-GAPDH (Santa Cruz Bio- RTK expression value. An expression call threshold technology), anti-TYRO3 (Abcam), and anti-KIT (Dako). (761.0) was determined by Stat4 library in R. Briefly, Secondary antibodies conjugated to horseradish peroxidase parameters of a bimodal normal distribution were esti- were used at a 1:10,000 dilution for 1 hour at room tem- mated separating the gene expression intensity data into perature prior to development (Thermo Scientific). m ¼ m ¼ noise ( noise 279.9) and signal ( signal 2,360.6). Nonsupervised hierarchical clustering was done by manu- Genes were considered expressed if their observed inten- ally determined phospho-array data values ranging from 0 m sity value (x)wasgreaterthanthe signal 1SDsignal (i.e., (background) to 5 (maximum phosphorylation; Tables 1 x > 761.0). To assess correlation between RTK activation and 2). Clustering of RTK data was done by Pearson's and ligand expression, we obtained a list of 473 known correlation with complete linkage along sample and protein receptors ligands pairs from the Database of Ligand– dimensions. Receptor Partners (13). The list was manually augmented with additional literature-derived receptor-ligand pairs. Immunoprecipitation Within our dataset 118 receptor-ligands pairs were used HER3 immunoprecipitation (IP) was done with 1 mg to correlate ligand expression (determined by NimbleGen protein and 800 ng HER3 antibody sc-7390 (Santa Cruz); array) with RTK phosphorylation (determined phospho- KIT IP with 300 mg protein and 1 mg A4502 (Dako); MET RTK Array). IP with 550 mg protein and 1mg MET antibody sc-10 (Santa RNA from snap-frozen melanoma tumors was extracted Cruz); IGF1R IP with 500 mg protein and 100 ng antibody directly from frozen tumor blocks (YUCOT, YUSIV, and 3027 (Cell Signaling Technology) at 4C overnight. Then, YUSTE) or after microdissection of snap-frozen tumors 12 mL of a 50% slurry of protein A/G beads (Thermo (YUDOSO and YULAC). RNA was isolated by the RNeasy Scientific) was added to each IP for 1 hour. Beads were Mini Kit from Qiagen and reverse transcribed with the washed twice with NP-40 lysis buffer and once with

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Table 1. Survey of tyrosine phosphorylated receptors by RTK capture array analysis in untreated melanoma cell lines

Breast Without PV Cancer Melanomas and Normal Newborn Melanocytes NRAS BRAF

ND* WT BRAF /NRAS V600K V600K Q61R Q61R Q61K V600E V600E V600E V600E V600E V600E V600K V600K V600K YURIF WW165 BT474 MB231 MB453 NBMEL YUGOE YUHEF YUHEIK YUHOIN YUKIM YUNIGE YUPLA YUROB YUROL YUSIV YUZOR YUCAS YUTICA YUDOSO YUCOT YUGEN8 YUHUY YUSAC2 YUSIK YUSTE YUKSI YULAC YUMAC EGFR5050 1 53 0 21130012 0 2032 0 1153113 HER24050 0 00 0 00000000 0 0010 0 0000000 HER33000 0 30 0 01004002 2 2010 0 2010000 HER40000 0 10 0 30001000 0 0010 0 0150110 FGFR13000 0 00 0 00000000 0 0000 0 0000000 FGFR2a0010 0 00 0 00000000 0 0010 0 0000010 FGFR30001 1 13 0 50010002 2 3343 0 2100000 FGFR40000 0 00 0 00000000 0 0000 0 0000000 InsulinR0000 3 03 1 50000004 3 3033 3 4300013 IGF1R0003 5 53 1 52354555 5 5055 3 5535555 AXL 4330 0 00 3 00500000 0 0000 0 0010000 TYRO31005 3 03 4 42155054 1 0043 3 4535555 MERTK1001 0 10 0 30000000 0 0010 0 0000000 MET 0011 0 10 0 40000004 0 0000 0 0000030 MST1R0000 1 13 0 00011000 2 1012 0 0001001 PDGFRa0000 0 00 0 00000010 0 0000 0 0000000 PDGFRb0000 0 10 0 01000000 0 0000 0 0000010 KIT 0000 0 15 0 00000000 0 0000 0 0000010 FLT-30000 0 00 0 00000000 0 0000 0 0000000 M-CSFR2000 0 00 0 00000000 0 0010 0 0000000 RET 0000 0 00 0 00000000 0 0010 0 0400030 ROR10000 0 00 0 00000003 0 0010 0 0001000 ROR20000 0 00 0 00000000 0 0000 0 0000000 TIE-10000 0 00 0 00000000 0 0000 0 0100000 TIE-21000 0 03 0 20010000 0 0010 0 0000000 TRKA0000 0 00 0 20000000 0 0000 0 0100000 TRKB0000 0 00 0 00000000 0 0000 0 0000000 TRKC0000 0 00 0 00000000 0 0000 0 0000000 VEGFR10000 0 00 0 00000000 0 0000 0 0100000 VEGFR20000 0 00 0 00000000 0 0000 0 0000000 VEGFR30000 0 10 0 30000000 3 3000 0 0000030 MUSK0000 0 00 0 30000000 0 0000 0 0000000 EPHA10000 0 00 0 00000000 0 0000 0 0000000 EPHA20000 0 00 0 00000000 0 0000 0 0000000 EPHA30000 0 00 0 00000000 0 0000 0 0000000 EPHA40000 0 00 1 00010000 0 0000 0 0000000 EPHA60000 0 00 0 00000000 0 0000 0 0000000 EPHA70000 0 00 0 00100000 0 0000 0 0000000 EPHB10000 0 00 0 00000000 0 0000 0 0000010 EPHB20000 1 12 1 20011012 3 3233 0 0103100 EPHB40000 0 00 0 00000000 0 0000 0 0000000 EPHB60000 0 00 0 00000000 0 0000 0 0000000

NOTE: Summary of receptor activations in breast cancer cell lines, melanoma cell lines, and newborn melanocytes. Signal intensity was visually scored on a scale from 0 (background) to 5 (most intense). Melanoma cells are grouped by NRAS/BRAF status. aBRAF and NRAS not determined (ND) for breast cancer cell lines. Abbreviation: PV, Pervanadate.

salt-Tris buffer (0.1 mol/L NaCl; 10 mmol/L Tris-HCl, pH shRNA and lentiviral infection 7.4), then incubated at 100C for 8 minutes in 2.5 shRNA targeting AXL [RHS3979-9568950, AXL 1 (14) and Laemmli sample buffer. RHS3979-9568949, AXL 2), HER3 (RHS3979-9630819;

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Table 2. Survey of tyrosine phosphorylated receptors by RTK capture array analysis in pervanadate- treated melanoma cell lines

With PV Melanomas and Normal Newborn Melanocytes NRAS BRAF

WT BRAF /NRAS Q61R Q61R Q61K V600E V600E V600E V600E V600E V600E V600K V600K V600K V600K V600K NBMEL YUGOE YUHEF YUHEIK YUHOIN YUKIM YUNIGE YUPLA YUROB YUROL YUSIV YUZOR YUCAS YUTICA YUDOSO YUCOT YUGEN8 YUHUY YUSAC2 YUSIK YUSTE YUKSI YULAC YUMAC YURIF WW165 EGFR00535005305520000 0 00000000 HER211035041110014413 4 01000013 HER315550550550555555 5 55555505 HER431405410334011314 3 11450110 FGFR100000000000001200 0 00000000 FGFR2a30000000000002200 0 00000000 FGFR341304411430145355 5 13311031 FGFR400000000000000000 0 00000000 InsulinR45250301110343344 3 53300101 IGF1R55554335443555545 5 55555533 AXL00304005001113301 0 10110101 TYRO300000010000113203 5 31133101 MERTK10300320010011023 3 11003103 MET45555233033053025 0 01303153 MST1R51553400330113543 5 13103313 PDGFRa00000000000000000 0 00000000 PDGFRb00000000000300000 0 00000000 KIT50350100000000000 5 01003553 FLT-331301301130133323 3 31111311 M-CSFR00001000000000000 0 00000000 RET01201000000000001 0 00100101 ROR101000000000000000 0 00000000 ROR200000000000000000 0 00000000 TIE-100000000000000200 0 00000000 TIE-200300200010001321 0 00000001 TRKA00001000000000000 0 00000001 TRKB00200200000000000 0 10000000 TRKC00200000000000310 0 10000000 VEGFR100000000000000000 0 00010000 VEGFR200000000000000000 0 00000000 VEGFR331301301130133523 3 11111311 MUSK00000000000000200 0 00000000 EPHA100000000000000000 0 00000000 EPHA200003201000300000 0 00100000 EPHA300000000000000000 0 00000000 EPHA410100000110000002 3 31000101 EPHA600000000000000000 0 00000000 EPHA710001000000000000 0 10000001 EPHB100000000000000000 0 00000000 EPHB211201000000020001 0 10003101 EPHB410000000000000000 0 00000000 EPHB610000000000000000 0 00000000

NOTE: Summary of RTK activation in melanoma cell lines and newborn melanocytes scored as described in Table 1.

ref. 15), IGF1R (TRCN0000121300; ref. 16), empty vector Cell proliferation pLKO control (RHS4080; Open Biosystems), and a Cells were plated in duplicate clear-bottom 96-well plates scrambled shRNA control (plasmid 1864; Addgene) were at a density of 1,000 cells per well in 100 mL of OptiMEM. used. Lentivirus stocks were produced by cotransfecting 293T Approximately 6 hours after plating, cells were incubated cells with pMD2.G and psPAX2 (Addgene) by using with lentivirus in OptiMEM containing 4 mg/mL polybrene FuGENE6 (Roche), with supernatants collected daily for for 20 hours. Immediately following infection, a T0 time 3 days and pooled (Addgene protocol). Experimental infec- point was taken by incubating one plate with CellTiter-Glo, tions were conducted at a multiplicity of infection of 5. per the manufacturer's instructions (Promega). Relative cell

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accumulation was calculated by dividing the value for the yet CSF1R was rarely phosphorylated (Tables 1 and 2; T72 time point by the value for the T0 time point. Assays Supplementary Tables S1 and S2). The same trend was were repeated 4 times, with a representative plot shown for also observed for EPHA2 in melanoma cell lines and each. FGFR1 in normal melanocytes. Of the 42 RTKs analyzed via phospho-arrays, IGF1R, HER3, and MET were fre- Cell migration quently activated and transcribed above the expression Cell lines were stably infected with scrambled shRNA or threshold in melanoma cell lines. Phosphorylation of other AXL shRNA and were seeded at 30,000 cells/well in 24-well RTKswasmorevariableincomparisonwithRNAexpres- plates with 8-mm filter inserts (BD Biosciences) in Opti- sion, suggesting the importance of other modulators such MEM with 0.1% FBS. OptiMEM with 5% FBS was used as growth factors or active coreceptors. Pervanadate treat- as a chemoattractant. Cell lines were analyzed in triplicate, ment generally increased the number of RTKs activated with a representative graph chosen for each. and expressed above the threshold (Supplementary Tables S1 and S2). Results RTK activation patterns were variable, even among cell lines with BRAF and NRAS activating mutations. Such Transcriptional profiling of melanoma cell lines mutations occur in 44% and 12%, respectively, of the We used transcription profiling to identify RTKs com- melanoma cultures analyzed in this report. Examples of monly expressed in melanoma cell lines and in normal array variability are found in pervanadate-treated NBMEL, melanocytes. Of the 58 human RTK genes, 43 RTKs were which have higher levels of phosphorylated macrophage transcribed above a conservatively chosen expression thresh- stimulating 1 protein receptor (MST1R) than melanoma old in at least one melanocyte culture, and 53 RTKs were cell lines YUHEIK and YULAC (Fig. 1B). Similarly, above the threshold in at least one melanoma cell line YUHEIK cells showed more activated EGFR than either (Supplementary Tables S1 and S2). Some RTKs, including newborn melanocytes or YULAC cells, whereas YULAC IGF1R, MET, and TYRO3, were highly expressed in most cells had lower activation of KIT and higher activation of melanomas and normal melanocytes, whereas fibroblast IGF1R (Fig. 1B). Despite these differences, the insulin growth receptor 2 (FGFR2), EGFR, and ROS1 were rarely, receptor family (IR, IGF1-R), EGFR family (especially if ever, detected above the expression threshold in either EGFR and HER3), MET family (MET and RON), and melanoma cells or melanocytes. AXL and HER3 were TAM family (TYRO3, AXL, and MERTK) were com- expressed at higher levels in melanoma cells than in mel- monly activated in melanoma cultures (Tables 1 and 2). A anocytes, but KIT and MERTK expression was lower in ranking of receptor activation across all melanoma cell melanoma cells compared with melanocytes (Supplemen- strains was determined by summing the phosphorylation tary Tables S1 and S2). intensities for each individual RTK (Supplementary Table S3). Interestingly, the 15 RTKs with the highest Survey of active RTKs in melanoma overall activation included receptors that had not been Generally, the abundance of RTK mRNA does not previously reported to be active in melanoma, including predict functional activity; although RTKs such as TYRO3, AXL, MERTK, and EPHB2 (Supplementary HER2 and MET are frequently activated via gene ampli- Table S3). RTKs such as EGFR, FGFR3, IR, IGF1R, fication and overexpression, mutationally activated RTKs and TYRO3 were frequently activated with and without can be potent oncogenes when expressed at low levels (17– pervanadate treatment whereas HER3, MET, and RON 18).Becausetyrosine(Tyr)phosphorylation is indicative were more commonly detected after pervanadate treatment, of the signaling activity of RTKs (19), we surveyed perhaps reflecting faster turnover of phosphotyrosine by receptor activation by using phospho-arrays that capture endogenous phosphatases (Tables 1 and 2). The frequency 42 RTKs from cell lysates and are probed with anti- of detection of phosphorylated EGFR and TYRO3 phosphotyrosine (anti-PTyr). To enhance the endogenous decreased with pervanadate treatment, possibly indicating PTyr signals, cells were also analyzed after treatment with a biological change such as heterologous desensitization pervanadate, a tyrosine phosphatase inhibitor. Pervana- through activation of other RTKs. date treatment significantly enhanced the cell lysate signals In both pervanadate-treated and untreated cultures, it was seen on the phospho-RTK arrays, but did not greatly alter common to find multiple phosphorylated RTKs (Tables 1 the pattern of RTK activation (Fig. 1A). Phospho-array and 2). Nonsupervised clustering was used to evaluate controls included breast cancer BT474 and MDA-MB- possible co-associations (Supplementary Tables S4 and 453 cells, which are known to express active HER2, and S5). Without pervanadate, there was some co-association MDA-MB-231 cells, which express little or no active of IGF1R and TYRO3 phosphorylation, with a subgroup HER3, but have substantial amounts of AXL (Table 1; showing common activation with IR, FGFR3, and EPHB2 refs. 20–22). (Supplementary Table S4). With pervanadate treatment, As expected, RTK mRNA levels were only loosely activation of multiple RTKs across cell lines was more correlated with receptor activation. For instance, colony- common (Supplementary Table S5). Recently, a related stimulating factor 1 receptor (CSF1R) mRNA levels were set of primary array data analyzing 15 separate melanoma high in both melanoma cell lines and normal melanocytes, lines was reported. This dataset identified active RTKs such

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AB YUDOSO with PV no PV with PV NBMEL YUHEIK YULAC EGFR Figure 1. Analysis of RTK MST1R phosphorylation. A, comparison of MST1R YUDOSO cell lysates incubated in the absence (left) or presence (right) of pervanadate (PV) prior to FGFR2a KIT lysis. Each pair of vertical spots represents one receptor. Paired spots in the 4 corners are positive RET PTyr controls, and appear darker IGF1R at left because of the longer film TYRO3 exposure time required for the lower signals without pervanadate treatment. B, comparison of RTK activation profiles among C without PV D with PV pervanadate-treated NBMEL, YUHEIK, and YULAC cells. Spots representing specific receptors are boxed in each panel. C and D, lysates from nontreated (C) and YUCAS YUDOSO YUHEF YUKSI YULAC YUPLA YURIF YUSIK IgG YUCAS YUDOSO YUHEF YUKSI YULAC YUPLA YURIF YUSIK pervanadate-treated (D) pAXL pAXL TCL melanoma cell lines were analyzed AXL AXL by immunoblotting for total and IP pHER3 pHER3 Tyr-phosphorylated receptors. TCL HER3 HER3 Total cell lysates (TCL) were IP pIGF1R pIGF1R analyzed by immunoblotting with TCL IGF1R IGF1R anti-RTK and anti–phospho-RTK IP pKIT TCL pKIT antibodies. RTK IP were analyzed TCL KIT KIT with anti–phospho-RTK, with pMET pMET control immunoglobulin (IgG) IP as IP TCL MET MET negative control. All immunoblots TYRO3 TYRO3 have been cropped. MERTK MERTK TCL GAPDH GAPDH

as HER3, IGF1R, and TYRO3 in non-pervanadate–treated RTK activation in melanoma samples, but these results were not validated (23). To identify receptors that might be activated through autocrine circuits or overexpression, we compared the Validation of array data phosphorylation levels determined by phospho-array ana- We focused on validating TYRO3, MERTK, AXL, lysis to the transcriptional levels of the RTKs and their HER3, MET, KIT, and IGF1R because they were either respective ligands. In untreated cell lines, a few RTK among the most common or most novel active RTKs phosphorylations correlated with ligand mRNA expression identified and because they represent attractive cancer including FGFR3::FGF13, AXL::GAS6, and HER4 with therapeutic targets (Fig. 1C and D). With the immuno- assorted ligands (Supplementary Table S6). Similarly, in blotting reagents available, we were able to determine the pervanadate-treated cells, moderate correlations were found abundance of TYRO3 and MERTK, but could not assess between RTK phosphorylation and ligand expression for their phosphorylation status for comparison with the phos- AXL::GAS6, EPHA2::EFNA3, and FGFR3::FGF13. In pho-array data. Although high levels of phosphorylation in both datasets, receptor phosphorylation was moderately pervanadate-treated cells permitted analysis of total cell associated with RTK mRNA expression for AXL, whereas lysates, immunoprecipitated phosphorylated RTKs could ERBB4 and EGFR also showed correlations in untreated also be detected in untreated cells. The pattern of receptor cells and KIT mRNA expression was correlated with KIT activation in the melanoma cell lines analyzed in Figure 1 activation in pervanadate-treated samples (Supplementary did not vary substantially with pervanadate treatment Table S6). (Fig. 1C and D). We considered the immunoblots more The small number of cases for which receptor phosphor- accurate in the instances where the arrays did not correlate ylations were identified in association with high ligand with the immunoblots. Hence, the RTK arrays provided a expression represent candidates for autocrine loops. Here, useful, but imprecise, indication of which RTKs are active the limited sensitivity of the RTK arrays coupled with the in a given cell line. possible chronic downregulation of ligand-activated RTKs

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means that there may be many false-negatives. Additionally, period of 24 to 48 hours and immunoblotting was used to elevated expression can move the designated RTK above measure the presence of total and phosphorylated IGF1R phospho-array threshold for detection, which may skew the (Fig. 2A). The persistence of IGF1R phosphorylation indi- results of our screen. The co-associations of RTK phos- cates that serum IGF1 is not the primary factor influencing phorylation with high receptor mRNA levels may, however, IGF1R activation. identify cases for which RTK overexpression contributes to The high prevalence of IGF1R activation in our panel of receptor activation. melanoma cell lines suggested that it might be functionally The strongest correlations were found in comparison important. Four melanoma cell lines characterized by phos- of receptor and ligand mRNA expression levels. For a phorylated IGF1R were infected with empty vector subset of RTK/ligand pairs, including FGFR3 with (pLKO), scrambled shRNA (SC), or shRNA against IGF1R several of its ligands, PDGFRb::PDGFb, AXL::GAS6, (Tables 1 and 2; Fig. 2B). IGF1R knockdown corresponded and ERBB4::neuregulin 3 (NRG3) NRG3, there were with decreased cell proliferation and a reduction in AKT strong associations of mRNA levels (Supplementary signaling, in accordance with earlier studies (ref. 6; Fig. 2B Table S6). These RTK/ligand pairs represent candidates and C). for autocrine activation, although for some pairs subcellular AXL and HER3 were selected for further validation of the compartmentalization or the need for proteolytic activation data generated by the phospho-array screen. We focused on of prohormones may limit RTK activity. these 2 receptors because they are relatively unexamined in the context of melanoma pathogenesis and because TAM RTK knockdown influences melanoma cell family members are poorly characterized in cancers in proliferation, migration, and signaling general. Lentiviral vectors encoding shRNA directed against The phospho-array survey identified IGF1R as active in AXL or HER3 were used to knock down the respective most of the melanoma cell lines (Tables 1 and 2). Because receptors singly and in combination (Fig. 3A). The cells were maintained in medium supplemented with growth of YURIF cells, which do not express AXL or serum, which is rich in ligand IGF1, we explored whether HER3 (Tables 1 and 2; Fig. 1C and D), was not affected IGF1R phosphorylation was affected by serum concentra- by lentiviral-mediated knockdown of either RTK (Fig. 3B). tion. Three melanoma cell lines were serum-starved for a In contrast, knockdown of AXL or HER3 strongly inhibited

A B YUHEF YUKSI Figure 2. IGF1R activation in YUKSI YULAC YUTICA melanoma cell signaling and proliferation. A, melanoma cell mock pLKO SC IGF1R lines were maintained in 0.1% mock pLKO SC IGF1R FBS or 5% FBS for 24 or 48 hours pIGF1R pIGF1R prior to lysis. Lysates were IGF1R IGF1R analyzed for phospho-IGF1R, 5FBS 24 h 0.1FBS 24 h 5FBS 48 h 0.1FBS 48 h 5FBS 24 h 0.1FBS 24 h 5FBS 48 h 0.1FBS 48 h 5FBS 24 h 0.1FBS 24 h 5FS 48 h 0.1FBS 48 h pAkt pAkt IGF1R, and the GAPDH loading pIGF1R Akt Akt control. Three biological replicates IGF1R GAPDH GAPDH GAPDH are shown. Image J analysis was YULAC YUTICA used to quantify phospho-IGF1R pIGF1R relative to GAPDH for each IGF1R sample. Average ratios 1SDfor GAPDH mock pLKO SC IGF1R the samples shown, from left to pIGF1R mock pLKO SC IGF1R pIGF1R pIGF1R right, are as follows: 0.78 0.29, IGF1R IGF1R IGF1R 1.1 0.08, 0.79 0.29, 0.81 GAPDH pAkt pAkt 0.16, 0.76 0.07, 0.76 0.01, Akt Akt 0.77 0.09, 0.69 0.24, 0.81 GAPDH GAPDH 0.26, 0.81 0.21, 0.50 0.01, 0.47 0.26. B, expression of phospho-IGF1R, IGF1R, C Cell proliferation phospho-AKT, and AKT in 8.00 melanoma cells infected with 7.00 lentiviruses encoding backbone 6.00 only (pLKO), scrambled shRNA

(SC), or shRNA for IGF1R. All 0 5.00 Mock immunoblots have been cropped /T 4.00 pLKO 72 to improve readability. C, growth T 3.00 SC of lentivirus-infected cells 2.00 IGF1R assessed over a 72-hour period by 1.00 using the CellTiter-Glo Luminescent Cell Viability Assay. 0.00 YUHEF YUGEN8 YULAC YUTICA

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proliferation of YUDOSO cells (Fig. 3B), which express and E). These alterations in proliferation and migration active AXL and HER3 (Fig. 1C and D). A milder reduction correlated with a slight reduction in phospho-STAT3 in proliferation was obtained by targeting active HER3 in (Fig. 3A). Knockdown of active AXL in YUSIV, YUSTE, YUROL cells (Tables 1 and 2; Fig. 3B). YUKSI cells, which and YUTICA melanoma cells evoked a more pronounced express AXL but have low AXL activity (Tables 1 and 2; decrease in cell proliferation, cell migration, and STAT3 Figs. 1C and D, and 3A), displayed only slight reductions in phosphorylation (Tables 1 and 2; Fig. 3A, D, and E). proliferation and migration upon AXL knockdown (Fig. 3D Sporadic reductions in phospho-AKT were also observed

A B YUDOSO YUROL Cell proliferation 7.00 Mock 6.00 pLKO 5.00 SC

0 AXL mock pLKO SC AXL HER3 AXL+HER3 mock pLKO SC HER3 4.00 /T Axl HER3 HER3 72

T 3.00 HER3 GAPDH AXL+HER3 GAPDH 2.00 YUSIV YUKSI 1.00 0.00 YUDOSO YURIF mock pLKO SC AXL mock pLKO SC AXL pAxl pAxl Axl Axl C pSTAT3 pSTAT3 Cell proliferation 5.00 STAT3 STAT3 GAPDH GAPDH 4.00 Mock

YUSTE YUTICA 0 3.00 pLKO /T SC 72

T 2.00 HER3 mock pLKO SC AXL mock pLKO SC AXL pAxl pAxl 1.00 Axl Axl 0.00 pSTAT3 pSTAT3 YUROL STAT3 STAT3 GAPDH GAPDH

D E Cell proliferation Cell migration

5.00 120

100 4.00 Mock

pLKO 80 Mock

0 3.00 SC /T 60 SC

72 AXL T 2.00 AXL % Migration 40

1.00 20 0 0.00 YUKSI YUSIV YUSTE YUTICA YUKSI YUSIV YUSTE YUTICA

Figure 3. Impact of AXL and HER3 knockdown on cell proliferation, migration, and signaling. A, expression of phospho-AXL (pAXL), AXL, HER3, phospho-STAT3 (pSTAT3), and STAT3 with GAPDH loading control in melanoma cells infected with empty backbone (pLKO), scrambled shRNA (SC), or shRNA for AXL and/or HER3. Immunoblots have been cropped. B–D, growth of lentivirus-infected cells assessed over a 72-hour period by the CellTiter-Glo Luminescent Cell Viability Assay. Melanoma cells are grouped on the basis of the viruses used; cell lines in the same panel were generally analyzed in different experiments. E, migration of melanoma cells infected with control (SC) or AXL shRNA lentivirus relative to mock-infected cells. AXL knockdown was achieved by AXL 1 shRNA sequence.

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on AXL knockdown (data not shown). Further validation of these effects was obtained by targeting AXL by using a A second shRNA in 4 melanoma cell lines (Supplementary AXL expression 9,000 Fig. S1). These results support the biological relevance of 8,000 AXL and HER3 in melanoma cells and substantiate the 7,000 6,000 importance of targeting activated receptors. 5,000 4,000 3,000 Melanoma cell lines predict presence of RTKs in 2,000

negative control 1,000 tumors tomRNA relative 0 To verify that expression of the RTKs identified in our RIF-cell screen is not a cell culture artifact, snap-frozen tissues SIV-tumor NBMEL-cell COT-tumor LAC-tumor STE-tumor DOSO-tumor derived from the same original tumors were analyzed via B qRT-PCR. AXL mRNA was identified by transcriptional ERBB3 expression profiling in YUDOSO, YUSIV, and YUSTE, but not in 600 YUCOT melanoma cells (Table 3). AXL mRNA and 500 protein were variably detected in YULAC cells (Fig. 1C 400 and D; Table 3). qRT-PCR analysis of frozen tumor tissues 300 revealed that YUDOSO, YUSIV, YUSTE, and YULAC 200

negative control 100 tumors all express AXL, but the YUCOT tumor did not mRNA to relative (Fig. 4A). Similarly, HER3 mRNA was detected by tran- 0 or cell mor scriptional profiling of the YUCOT, YULAC, YUDOSO, tumor tumor SIV-tum MB231- NBMEL-cell COT-tumor LAC-tu STE- YUSIV, and YUSTE melanoma cell strains as well as by DOSO- qRT-PCR analysis of tissue from the corresponding tumors (Table 3; Fig. 4B). Figure 4. Analysis of RTK mRNA in tumor samples. A and B, relative As expected, there was no direct correlation between the expression of AXL and ERBB3 mRNA from tumors. AXL and HER3 activity of an RTK in a cell line (Tables 1 and 2) and the expression were measured by qRT-PCR and normalized to GAPDH, and presence of mRNA in the corresponding tumor (Fig. 4A the resulting expression is shown relative to negative controls for AXL and B). Nonetheless, activated AXL and HER3 were only (YURIF) and HER3 (MB231). detected in melanoma cell lines for which the tumors expressed the corresponding receptors. The differences in rank expression of the RTKs in tumors versus cell lines may analysis of a reference set of melanoma cell lines and corre- reflect tumor to cell strain differences, tumor heterogeneity, sponding tumor tissue that will eventually encompass tran- or differential infiltration by nontumor cells in the tumor scription profiling, epigenetic analysis, copynumber analysis, microenvironment. transcriptome and exome resequencing, and drug response profiling. We found that the insulin receptor family (IGF1R, Discussion IR), MET family (MET, MST1R), EGFR family (EGFR, HER3, HER4), and TAM family (TYRO3, AXL, MERTK) We report here the first broad survey of functionally were commonly activated in melanoma (Tables 1 and 2). activated RTKs in a panel of early-passage melanoma cell IGF1R was frequently and strongly activated in our strains. This survey represents one facet of an integrated panel of cell strains, and this activation did not seem to

Table 3. Receptor expression and activation in cell lines

Activation Transcriptional Activation of Transcriptional of AXL on array expression of AXL HER3 on array expression of ERBB3 Cell line PV þPV PV þPV

NBMEL 0 0 842 0 1 943 YUCOT 0 0 466 0 5 15,164 YUDOSO 0 3 2,500 2 5 21,188 YULAC 0 0 425 0 5 12,623 YUSIV 0 1 8,327 0 0 9,717 YUSTE 0 1 8,351 0 5 10,251

NOTE: Whole genome RNA expression values determined for AXL (NM_021913) and ERBB3 (HER3; NM_001982) in melanoma cell lines. Receptor activation values are from RTK capture array analyses of pervanadate-treated (þPV) and nontreated (PV) cells.

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be serum-dependent (Tables 1 and 2; Fig. 2A). A previous TAM family was activated in the majority of the melanoma report showed that knockdown of IGF1R can greatly reduce cell lines, even without pervanadate treatment (Tables 1 and melanoma cell growth and that targeting IGF1R reduced 2). Further, activation of AXL and MERTK may have some signaling through both the AKT and the mitogen-activated degree of mutual exclusivity, because AXL and MERTK protein kinase pathways (6). Our data also support the activation rarely occurred concurrently in the melanoma cell notion that knockdown of IGF1R may reduce cell growth lines. in an AKT-dependent manner (Fig. 2). Activation of Suppression of TYRO3 reduces melanoma cell prolifera- IGF1R promotes liver metastases in uveal melanoma and tion, sensitizes cells to chemotherapeutics, decreases colony activated IGF1R, along with activated HER3, is known to formation, and reduces tumor formation and growth (34). contribute to Herceptin resistance in breast cancer (24–27). Further, AXL is required for GAS6-dependent uveal mel- Signaling through IGF1R also compensates for therapeutic anoma cell survival (36). In our study, knockdown of inhibition of mTOR in breast and prostate cancer cells (28). activated AXL noticeably affects cell proliferation in a It is possible that activated IGF1R might serve an analogous primary cutaneous melanoma line (YUDOSO), 3 meta- role in melanoma and it will therefore be important static cutaneous lines (YUGEN8, YUSIV, YUSTE), and 2 to determine the mechanism of IGF1R activation in cutaneous lines that had metastasized to the lung (YUHEF, melanoma. YUTICA; Fig. 3; Supplementary Fig. S1). Targeting AXL A recent study showed that HER4 may be somatically in a subset of these cell lines also reduces cell migration mutated in up to 19% of melanomas, and our survey reveals (Fig. 3). It appears that this decrease in migration and frequent activations of the EGFR family members in proliferation correlates with a reduction in STAT3 signaling melanoma (29). While this work was in progress, elevated (Fig. 3; Supplementary Fig. S1). Thus, AXL signaling may HER3 expression and activation was reported in melanoma contribute to the constitutive activation of STAT3 that is cells relative to normal melanocytes, with knockdown of frequently observed in human melanoma cell lines and HER3 reducing melanoma cell proliferation, migration, tumors (37). and invasion (30–31). Reduced HER3 expression was also Some of the RTKs identified by our screen (IGF1R, correlated with reduced phospho-AKT and increased p27 MET, and KIT) have been previously described in mela- expression (31). The findings presented here are consistent nomas. Others, including HER3, HER4, members of the with these reports, because our melanoma cell strains TAM family, EPHB2, and MST1R, have either not been frequently show higher HER3 activation and mRNA than reported as active, or are poorly characterized in this disease. melanocytes (Tables 1 and 2; Supplementary Tables S1 and These findings have therapeutic implications because some S2) and because HER3 knockdown reduces melanoma cell of the receptors identified in the melanoma cell lines, proliferation (Fig. 3). It has been proposed that activation of specifically AXL and HER3, were found in the correspond- HER3 by NRG1 contributes to melanoma development ing tumor tissue (Table 3; Fig. 4). Targeting AXL in a cell and progression (30), but we did not identify a correlation line that either does not express phosphorylated AXL between HER3 activation and the expression of ligands (YUKSI) or in a cell line that does not express the receptor NRG1 or NRG2 (Supplementary Table S6). One explana- at all (YURIF) had little to no effect on cell behavior (Fig. 3). tion may be that NRG1 is important in early stages of Interestingly, targeting the activated receptors appears to be melanoma but its expression does not persist in later stages; effective regardless of NRAS and BRAF mutation status. this is consistent with the reported higher frequency of Both IGF1R and AXL knockdown alters cell behavior in activated HER3 in primary compared with metastatic BRAF/NRAS wild-type (WT) cells (YUHEF, YUSIV), melanomas (30). The phospho-RTK array analysis also NRAS mutant cells (YUDOSO, YUTICA), and BRAF reveals coactivation of MET with EGFR family members mutant (YUGEN8, YUKSI, YULAC, YUSTE) melanoma such as HER3 (Tables 1 and 2). Because coordinate cell lines. Although HER3 knockdown was not examined in activation of MET with ERBBs often modulates resistance a BRAF mutant line, it is effective in NRAS (YUDOSO) to EGFR inhibitors in NSCLC, combined inhibition of mutant and WT (YUROL) cell lines (Fig. 3). These find- MET and ERBBs may be beneficial for a subset of mela- ings are important because expression and activation of nomas as well (32). RTKs was largely independent of mutation status, and The TAM receptor family is well-studied in inflamma- because activation of nonmutated RTKs is a common tion but is not yet completely characterized in carcinogen- mechanism of resistance in tumor cells attacked with esis. Previous work shows that AXL mRNA is elevated in RTK or pathway-directed therapeutics (38). In fact, in a melanomas relative to normal melanocytes, in agreement nonbiased survey of protein kinase cDNAs for the ability to with our transcriptional data (Supplementary Tables S1 and promote melanoma cell resistance to the activated BRAF S2; ref. 33). Although TYRO3 and MERTK were reported inhibitor PLX4720, AXL was identified as the RTK best to be preferentially expressed in melanomas, we found that able to rescue cell proliferation (39). Another study identi- TYRO3 is highly expressed in both melanocytes and mel- fied upregulation and activation of PDGFRb receptor as a anomas and that MERTK expression is, on average, lower in route to resistance in BRAF mutated melanoma treated with melanoma cells compared with normal melanocytes (Sup- PLX4032 (40). Perhaps coexpression of ligand–receptor plementary Tables S1 and S2; refs. 33–35). Interestingly, conjugate pairs, as we found for several RTKs including the phospho-arrays revealed that at least one member of the PDGFRb, foreshadows routes to resistance.

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These findings document variability in RTK expression peutic opportunities for driver inhibition while improving and activation among melanomas. Identification of cancer our ability to prevent therapeutic resistance. drivers by gene mutation analysis is attractive because the technology is accurate and sensitive and because muta- Disclosure of Potential Conflicts of Interest tions in protein kinases and other signaling proteins can have strong predictive value. Nonetheless, carcinogenic No potential conflicts of interest were declared. alterations in RTKs and signaling pathways are also Acknowledgments induced by changes in expression, subcellular localization, and proteolysis of ligands. Because RTKs are mainly Fibroblasts, melanocytes, and melanoma cell lines, as well as the NimbleGen gene regulated through protein–protein interactions and pro- expression data were provided by the Specimen Resource Core of the Yale SPORE in tein modifications, functional analyses that measure pro- Skin Cancer. We thank James McCusker for hierarchical clustering analysis. tein changes continue to provide important insights into Grant Support cancer at the discovery and treatment levels. For instance, one of the early indications of anaplastic lymphoma kinase This work was funded in part by the NSF Graduate Research Fellowship Program (ALK) activation in a subset of lung cancers was derived (K. Tworkoski), the Harry J. Lloyd Charitable Trust (D.F. Stern), and the Yale fromamassspectrometrysurveyoflungcancertumors SPORE in Skin Cancer, funded by the National Cancer Institute Grant 1 P50 CA121974 (R. Halaban, principal investigator). and cell lines (41). The fact that HER3, AXL, and IGF1R The costs of publication of this article were defrayed in part by the payment of page knockdown was effective regardless of NRAS and BRAF charges. This article must therefore be hereby marked advertisement in accordance status suggests that inhibition of RTKs may be valuable in with 18 U.S.C. Section 1734 solely to indicate this fact. combination with RAF or MEK inhibitors (Fig. 3). The Received November 15, 2010; revised March 17, 2011; accepted April 13, 2011; RTKs identified in this survey may provide new thera- published OnlineFirst April 26, 2011.

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Phosphoproteomic Screen Identifies Potential Therapeutic Targets in Melanoma

Kathryn Tworkoski, Garima Singhal, Sebastian Szpakowski, et al.

Mol Cancer Res 2011;9:801-812. Published OnlineFirst April 26, 2011.

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