Kinase Regulation of Human MHC Class I Molecule Expression on Cancer … · After informed consent on Memorial Sloan Kettering Cancer Center (MSKCC) Institutional Review Board–approved

Research Article

Kinase Regulation of Human MHC Class IMolecule Expression on Cancer CellsElliott J. Brea1,2, Claire Y. Oh1,2, Eusebio Manchado3, Sadna Budhu4, Ron S. Gejman1,2,George Mo1, Patrizia Mondello1, James E. Han1,2, Casey A. Jarvis1, David Ulmert1,Qing Xiang5, Aaron Y. Chang1,2, Ralph J. Garippa5, Taha Merghoub4,Jedd D.Wolchok2,4, Neal Rosen1,2, Scott W. Lowe2,3,6, and David A. Scheinberg1,2

Abstract

The major histocompatibility complex I (MHC-1) presentsantigenic peptides to tumor-specific CD8þ T cells. The regulationof MHC-I by kinases is largely unstudied, even though manypatients with cancer are receiving therapeutic kinase inhibitors.Regulators of cell-surface HLA amounts were discovered using apooled human kinome shRNA interference–based approach.Hitsscoring highly were subsequently validated by additional RNAiand pharmacologic inhibitors. MAP2K1 (MEK), EGFR, and RETwere validated as negative regulators of MHC-I expression andantigen presentation machinery in multiple cancer types, acting

through an ERK output–dependent mechanism; the pathwaysresponsible for increased MHC-I upon kinase inhibition weremapped. Activated MAPK signaling in mouse tumors in vivosuppressed components of MHC-I and the antigen presentationmachinery. Pharmacologic inhibition of MAPK signaling alsoled to improved peptide/MHC target recognition and killing byT cells and TCR-mimic antibodies. Druggable kinases may thusserve as immediately applicable targets for modulating immu-notherapy for many diseases. Cancer Immunol Res; 4(11); 936–47.�2016 AACR.

IntroductionMajor histocompatibility complex class I molecules (MHC-I)

generally present short peptides from either foreign or nativeintracellular proteins on the cell surface in an HLA-restrictedmanner for recognition by CD8þ T cells via their T-cell receptor(TCR; ref. 1). MHC-I is an essential protein for CD8þ cytotoxicT-cell responses, effective vaccination, adoptive T-cell therapies,hematopoietic stem cell transplantation, and organ rejection,among many important physiologic processes and therapeu-tic manipulations. In addition, recently developed therapeuticTCR-based constructs and TCR-mimic antibodies are directedto MHC/peptide complexes (2–5).

Although immunotherapies for cancer, infectious disease,and autoimmune disease continue to gain use as effectivetherapeutic strategies, the mechanisms underlying the controlof presentation of foreign antigens or self-tumor antigens areonly partially understood and currently not exploited clinically(6). Reduced cell-surface presentation of tumor antigens onMHC-I is an important obstacle to effective immunotherapy

with adoptively transferred T cells, TCR constructs, tumorvaccines, and TCR-mimic antibodies (7–12).

We hypothesized that signaling pathways driven by kinasesmay also regulate surface MHC-I expression and that these couldidentified in loss- or gain-of-function genetic screens usingspecific antibodies to detect MHC-I cell-surface expression.Previously, a genome-wide screen provided evidence that reg-ulators of MHC-II could be identified by RNAi knockdown (13).We decided to target a mesothelioma cell line for our proofof concept, due to its robust expression of HLA and the needfor more effective therapies for this disease. Moreover, immu-notherapies, such as the CTLA-4 blocking antibody tremelimu-mab, that rely on antigen presentation on MHC-I, are currentlybeing tested in mesothelioma (14). To identify signaling path-ways that regulate HLA expression in this model, we conductedan shRNA screen of currently annotated human kinases, as itaffords the immediate possibility of targeting identified kinasesfor which inhibitors already exist. Among "hits" identified inthe screen were kinases that negatively regulate HLA, includingMAP2K1 (MEK1) and EGFR. In addition, we discovered thatDDR2 and MINK1 increase surface MHC-I. These pathways, theeffects of their inhibition, and the positive consequences ofinhibition on MHC antigen presentation, TCR-based recogni-tion of the MHC/peptide complexes and subsequent killingwere explored. The use of loss- and gain-of-function screens touncover regulators of MHC-I could have broad implications forunderstanding and treating multiple diseases with pathophys-iology related to antigen presentation.

Materials and MethodsCell lines and culture conditions

After informed consent on Memorial Sloan Kettering CancerCenter (MSKCC) Institutional Review Board–approved protocols,

1Molecular Pharmacology Program, Memorial Sloan Kettering CancerCenter New York, New York. 2Weill Cornell Medicine, New York, NewYork. 3Cancer Biology and Genetics Program, Memorial Sloan Ketter-ing Cancer Center New York, New York. 4Immunology Program,Memorial Sloan Kettering Cancer Center New York, New York. 5RNAiCore Facility, Memorial Sloan Kettering Cancer Center NewYork, NewYork. 6Howard Hughes Medical Institute, New York, New York.

Note: Supplementary data for this article are available at Cancer ImmunologyResearch Online (http://cancerimmunolres.aacrjournals.org/).

Corresponding Author: David A. Scheinberg, Sloan Kettering Institute, 417 East68th Street, New York, NY 10021. Phone: 646-888-2190; Fax: 646-422-0296;E-mail: [email protected]

doi: 10.1158/2326-6066.CIR-16-0177

�2016 American Association for Cancer Research.

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peripheral blood mononuclear cells (PBMC) from HLA-typedhealthy donors and patients were obtained by Ficoll densitycentrifugation. The sources for obtaining the human mesothelio-ma cell lines JMN and Meso34 are described previously and wereverified as unique cell lines by IMPACT sequencing (Supplemen-tary Table S1; ref. 3). HEK293T, PC9, SKMEL5, UACC257, SW480,CFPAC1, H827, H1975, H1299, and A549 were obtained fromATCC between the years 2012 and 2016 and were not furthervalidated.TheTPC1cellwasobtained fromtheDr. JamesFagin lab,where the cell line was validated by IMPACT sequencing, and usedfrom 2014 to 2016 (MSKCC). The B16-F10 melanoma line wasoriginally obtained from I. Fidler (MD Anderson Cancer Center),and used from 2015 to 2016, and was not further validated. Celllines were maintained 2 to 3 months in RPMI supplemented with10% FBS and 2 mmol/L L-glutamine unless otherwise mentioned.HEK293Twere grown inDulbecco'smodifiedmediawith10%FBSand 2 mmol/L L-glutamine. Cells were checked regularly formycoplasma.

ADCCThe HLA-A�02:01–positive mesothelioma cell lines JMN and

Meso34, along with the melanoma cell line SK-MEL5, were usedin the ADCC assay as a target. Antibodies (3 mg/mL) ESKM (15),PRAME, or its isotype control hIgG1 were incubated with targetcells and fresh healthy donor PBMCs at different effector/targetratios for 6 hours, along with indicated doses of vehicle ortrametinib inRPMI supplementedwith10%FBS. The supernatantwas harvested, and the cytotoxicity wasmeasured by a 51Cr releaseassay (Perkin Elmer).

Clonogenic killing assayB16F10 cells were treated with either 0.1%DMSO or 1 mmol/L

trametinib for 72 hours. B16F10 cells (1� 104) were then used astargets and in vitro–activated Pmel T cells (5 � 104) as effectorsisolated from the spleen of pmel (GP100) B6.Cg-Thy1a/Cy Tg(TcraTcrb)8Rest/J mice (The Jackson Laboratory).

Pooled RNAi screeningA custom shRNA library targeting the full complement of

526 human kinases was designed using miR30-adapted DSIRpredictions refined with "sensor" rules (six shRNAs per gene)and constructed by PCR-cloning a pool of oligonucleotidessynthesized on 12k customized arrays (Agilent Technologiesand CustomArray) as previously described (16). The list ofgenes was obtained from KinBase Database (http://kinase.com/human/kinome/) and was manually curated. After sequenceverification, 3,156 shRNAs (5–6 per gene) were combined withpositive control HLA-A– and negative-control Renilla–targetingshRNAs at equal concentrations in one pool. JMN mesotheli-oma cells stably expressing the Tet-On rt-TA3 gene were used.This pool was subcloned into the TRMPV-Neo vector andtransduced in triplicates into Tet-on JMN mesothelioma cancercells using conditions that predominantly lead to a singleretroviral integration and represent each shRNA in a calculatednumber of at least 1,000 cells (Fig. 1A). Transduced cells wereselected for 6 days using G418 (1 mg/mL; Invitrogen); at eachpassage more than 3 � 107 cells were maintained to preservelibrary representation throughout the experiment. After induc-tion, T0 samples were obtained (�3 � 107 cells per replicate,n ¼ 3) and cells were subsequently cultured in the presence of

doxycycline (2 mg/mL) to induce shRNA expression. After 4days (Tf), about 3 � 106 shRNA-expressing (dsRedþ/Venusþ)cells were sorted for each replicate using a FACSAriaII (BDBiosciences). DAPI-negative, dsRedþ/Venusþ cells were sortedby FACS into three populations of BB7 low, BB7 middle, andBB7 high binding (Fig. 1). Genomic DNA from Tf samples wasisolated by two rounds of phenol extraction using PhaseLocktubes (50) followed by isopropanol precipitation. Deep-sequencing template libraries were generated by PCR amplifi-cation of shRNA guide strands as previously described (16).Libraries were analyzed on an Illumina Genome Analyzer at afinal concentration of 8 pmol/L; 50 nucleotides of the guidestrand were sequenced using a custom primer (miR30EcoRISeq,TAGCCCCTTGAATTCCGAGGCAGTAGGCA). Hits with lowerthan 100 reads from the Illumina HiSeq were eliminated be-cause they were not above background.

Relative representations of each individual shRNA were deter-mined and compared in each given sorted population. Weseparated hits phenotypically into negative regulators (the pop-ulation 1 SD below the mean fluorescence intensity) or positiveregulators (the population 1 SD above the mean fluorescenceintensity) of HLA-A�02:01. The ratio of the shRNA rankingbetween the high and low population was compared, with ahigh ratio indicating a putative negative regulator of surface HLA-A�02:01. The scoring criteria for a gene being a negative regulatorof HLA-A�02:01 was based on having two or more shRNAconstructs score in the top 5% for fold difference in relativerepresentation between BB7 high population and BB7 low pop-ulation, with other constructs scoring within 1 SD of the meanfold change. The gene products with at least two shRNA sequencesin the top 5% ratio were selected for further validation by othermethods. The same discovery pipeline was used for identifyingpositive regulators of HLA-A�02:01. For validation, the LT3GEPIRshRNA vector was used (ref. 17; Supplementary Table S2). Cellswere transduced and selected with puromycin, then inducedwith doxycycline (2 mg/mL) for 96 hours before evaluating BB7,W6/32, ESK, or PRAME expression by flow cytometry.

AntibodiesAntibodies used for flow cytometry and Western blot analy-

sis are described in Supplementary Table S3. Monoclonal anti-bodies (mAb) used for flow cytometry were specific forHLA-A02 (BB7.2), pan–HLA-ABC (W6/32), WT1 peptide RMFbound to HLA-A02 (ESK1), PRAME peptide ALY bound toHLA-A02 (Pr20), H2-Kb (AF6-88.5.5.3), and H2-Kq (KH114).Other antibodies used in this report are also listed in Supple-mentary Table S3.

Real-Time PCRTotal RNA was extracted using Qiagen RNA Easy Plus

(Qiagen; #74134) after cells were treated for 48 hours withindicated inhibitor. RNA was converted into cDNA using qScriptcDNA SuperMix (Quanta Biosciences Gaithersburg). Real-timeassays were conducted using TaqMan real-time probes (Life Tech-nologies) for human HLA-A (Hs01058806_g1), beta-2 micro-gobulin (b2M) (Hs00187842_m1), TAP1 (Hs00388677_m1),TAP2 (Hs00241060_m1), and TBP (Hs00427620_m1) with50 ng cDNA. For assessment of gene expression using RT-PCRPerfeCTa. FastMix. II (Quanta), reactions were carried out intriplicates using standard thermocycling conditions (2 minutesat 50�C, 10 minutes at 95�C, 40 cycles of 15 seconds at 95�C, and

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1 minute at 60�C). TBP was used as an internal control, and theDDCT method was used for relative mRNA calculations.

Promoter-based studiesGLuc luciferase promoter was obtained from Genecoepia

(GeneCoepia Rockville) with the b2M promoter cloned upstreamof the GLuc enzyme. Normalization was done to SEAP (under theconstitutively active SV40 promoter). Cells were seeded at 5E3cells/well and treated with indicated drugs for 72 hours. Lumi-nescence quantitation was assayed using the Secrete-Pair DualLuminescence Assay Kit (GeneCoepia Rockville).

Flow cytometric studiesCell lineswere seeded in triplicate in a 6-well tissue culture plate

at a density of 1E5 cells/well and allowed to adhere overnight. Thenext day, cells were treated with either vehicle control (0.1%DMSO), drugs, or inhibitors at indicated concentrations. Cellswere then isolated at 72 hours after inhibitor treatment andwashed with PBS. Cells were subsequently stained with BB7.2(HLA-A02–specific mAb), W6/32 (HLA-ABC–specific mAb), orAF6-88.5.5.3 (H2-Kb

–specific mAb; Ebiosciences). Cells werestained with propidium iodide for viability. Cells were analyzedon BD Accuri C6 flow cytometer.

Overexpression of b2MHuman b2M cDNA was cloned into the MSCV Puromycin

vector.

Overexpression of mutant EGFR and NRASThe pBABE retroviral vector encoding either EGFR harboring

the L858R mutation was used to stably transduce the H1299 cellline using HEK293T/Amphoteric cells and were selected in puro-mycin (2.5 mg/mL) for 5 days. EGFR L858R was a gift fromMatthew Meyerson, (Dana-Farber Cancer Institute, Boston, Mas-sachusetts) (Addgene plasmid # 11012).

For overexpression of NRAS, the pBABE NRAS Q61K plasmidwas used to transduce H827 cells similar to described above andselected in puromycin (2 mg/mL). pBabe N-Ras 61K was a giftfrom Channing Der (Addgene plasmid # 12543).

Small-molecule inhibitor studiesCompounds were obtained from SelleckChem. Drugs were

used at subcytostatic doses by titration using the Cell Titer Gloassay (Promega). All drugs were used in vitro at indicated doses in1% DMSO. Experiments were performed at least twice withsimilar results, and data shown are representative.

siRNA knockdownThe JMN cell line was treated with a control scrambled siRNA,

or siRNA against STAT1, STAT3, and RelA. Cells were treated withthe indicated drug 24 hours after siRNA knockdown for 72 hoursbefore assaying for surface HLA-A by flow cytometry. shRNAconstruct details are given in Supplementary Table S2.

Transgenic EGFR L858R mouse modelFVB CC10-rtTA/EGFR-L858Rmice were obtained as a kind gift

from the Harold Varmus lab (Weill Cornell Medicine). Micewere bred in accordance with the MSKCC institutional reviewboard under protocol 96-11-044. Mice used for the experimentwere heterozygous for CC10-rtTA and EGFR-L858R as detectedby quantitative PCR genotyping. At 4 to 6 weeks of age, mice

were put on doxycycline via food pellets (625 mg/kg; Harlan-Teklad) for >6 weeks. Mice were imaged by anesthetizing under2% isoflurane and lung field images were acquired on a Bruker4.7T Biospec scanner (Bruker Biospin Inc.) magnetic resonanceimager (MRI) in the small animal imaging core at the MSKCC.Images were analyzed with Osirix Imaging Software. Lung cancerin mice was confirmed to have reticulonodular appearances andconsolidations by axial and coronal MR images, consistent withprevious data published on the transgenic mice (18).

Mice were sacrificed once confirmed to have lung tumors (non-induced control mice were also used, which genotypically wereidentical but did not receive dox diet). The lungs were isolatedand treated with collagenase IV in HBSS with Ca2þ and Mg2þ for1 hour 37�C. Cells were then collected, blocked with mouse FcRblock (Miltenyi), counted, and stained with mouse CD45(30-F11; Biolegend), human EGFR (AY13 clone; Biolegend), andmouse H2-Kq (KH114, clone Abcam) antibodies. Flow cytometryanalysis was performed on Fortessa (BD Biosciences).

CC10/L858R microarray dataExpression data from tissue isolated from WT and EGFR

L858R transgenic mice were obtained from a previous study(GSE17373) and were selected for statistically significant data(P < 0.05) for PDCD1 (PD-1), CD274 (PD-L1), TAP1, TAP2,H2-Kd, and b2M gene expression between tumor-bearing EGFRL858R lung tissue and normal lung tissue (19, 20).

ResultsPooled shRNA screen identified gene products regulatingsurface HLA-A�02:01

Loss- or gain-of-function screens serve as starting points foridentifying new regulators of protein expression and function.We used an shRNA library against the 526 currently annotatedhuman kinases to perform a custom-pooled screen. For eachgene, six shRNA constructs were cloned into the TRMPV ret-roviral vector, a tetracycline regulated vector that couples amir30-based shRNA to a red fluorescent protein, which allowseasy tracking and sorting of cells' productively expressing anshRNA (Fig. 1A; ref. 16). Knockdown of HLA-A�02:01 by use ofan shRNA to this gene product in the same vector was tested as apositive control and caused strong knockdown by both Westernblot analysis and flow cytometry (Fig. 1B).

The amount of MHC-I and antigen presentation on surfaceHLA-A�02:01 is an important determinant of efficacy for certainimmunotherapies (21). We decided to use the human meso-thelioma cell line JMN as the target for these studies, which hasstable HLA-A�02:01 expression and which has been used as atarget of MHC-I–directed therapies in vitro and in vivo (3). As atool to show the impact of HLA modulation on antigenrecognition and potential for TCR-based killing, we used TCRmimic antibodies that recognize peptide/MHC-I complexes.Knockdown of HLA-A substantially decreased the killing effi-cacy of the TCR mimic antibody ESKM against the JMN meso-thelioma cell line (Supplementary Fig. S1). JMN was analyzedfor presence of a predefined subset of mutations using the MSKIMPACT platform (Supplementary Table S1). No mutationsor significant copy-number alterations were observed in theHLA-A�02:01 or b2M genes.

The JMN cell line was screened with an shRNA library againstthe human kinome, as described in Materials and Methods, for

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genes acting as negative or positive regulators of surface HLA-A,detected by flow cytometry with the HLA-A�02:01–specific mAbBB7.2 and fluorescence-activated cell sorting was used to sortpopulations based on HLA expression (illustrated as in Fig. 1C).The top 5 hits are listed (Supplementary Table S4).

Based on this analysis, MAP2K1 and EGFR were identified asimportant negative regulators of surface HLA-A�02:01. We choseto further investigate EGFR andMEK because of the availability ofclinically approved drugs targeting these kinases both in NSCLCand metastatic melanoma, respectively (22), as well as extensiveuse of immunotherapy.

EGFR is a receptor tyrosine kinase that binds epidermal growthfactor and is frequently found to be activated by mutation in

NSCLC. Activated EGFR signals through multiple downstreampathways, including the MAPK pathway. shRNA constructsagainst MAP2K1 and EGFR showed a large increase in relativerepresentation in the BB7-high sorted population versus theBB7-low population, indicative of a negative regulator of HLA-A�02:01 surface expression (Fig. 1D). We validated each of thesegenes with independent shRNA knockdown to the gene productsand saw significant increases in HLA-A�02:01 by flow cytometry(Fig. 1E). These effects were seen not only with HLA-A�02:01 butalsowith total HLA-A, B, andC, suggesting coordinated control ofall HLA surface expression, as measured with the W6/32 mAb(Supplementary Fig. S4). These findings were reproduced inmultiple mesothelioma cell lines (Supplementary Fig. S3A and

Figure 1.

Screen for kinase regulators of surface HLA. A, a TRMPV-inducible shRNA retroviral vector was used for transducing JMN (HLA-A�02:01–positivehuman mesothelioma line). TRE is the Tet-responsive element, which drives expression of the fluorophore dsRed and the shRNA hairpin. The constitutivePGK promoter drives the Venus fluorophore along with Neomycin resistance cassette. B, Western blot and flow cytometry data showing knockdown ofHLA-A using a TRMPV retroviral system with a positive control shRNA to HLA-A02. The shRen is a negative control shRNA designed against the Renillagene. C, schema depicting the workflow pipeline for the screen of regulators of surface HLA-A. D, waterfall plot showing distribution of shRNAconstructs against MAP2K1 and EGFR as log fold difference between the BB7-high sorted population and BB7-low sorted population. E, shRNA knockdownof MAP2K1 and EGFR in JMN cells validates them as a negative regulator of surface HLA-A. BB7.2 is an mAb specific for HLA-A02. shRNA againstRenilla was used as a negative control, whereas an shRNA against HLA-A was used as a positive control. The screen was done in triplicate. Inhibitionexperiments were performed at least twice with similar results, and data shown are representative. The Student t test was done to compare each shRNA geneknockdown MFI to the shRen control (� , �0.05; ��, �0.01; �� , �0.001; �� , �0.0001).






S3B). The RET protooncogene was also identified as a potentialtarget, but was not further studied at this time because noinhibitor of adequate specificity was available (SupplementaryFig. S3C).

We identified examples of positive genetic regulators ofHLA-A, including two putative positive regulators DDR2 andMINK1 (Supplementary Table S4; Supplementary Fig. S4A andS4B), and confirmed their activity as well using siRNA knock-down (Supplementary Fig. S4C). Therefore, the kinase screendiscovered multiple positive and negative regulators of HLAexpression, each of which in principle could be explored furtherfor mechanism and clinical utility. The top five negative regu-lators evaluated were confirmed by additional study, whereasthree of the five top positive regulators were validated (Sup-plementary Table S2).

The MAPK pathway regulates MHC-IMultiple potent small molecule inhibitors exist for EGFR

and MEK, with several already FDA approved, and otherscurrently in clinical trials for various cancers (22). Of note,the initial screen was performed in a cell line with EGFRactivation and an identified EGFR mutation (SupplementaryTable S1; ref. 23). We tested, in multiple cell lines, the ability ofinhibitors to phenocopy the loss of kinase expression leadingto increased HLA-A expression seen with shRNA. Cell-surfaceHLA-A�02:01 expression increased in response to MEK inhi-bition for 72 hours with the selective MEK inhibitor trametinibin mesothelioma cell lines with activated MAP kinase signaling(Fig. 2A). JMN and PC9, a non–small cell lung carcinoma(NSCLC) cell line with an activating EGFR mutation (delE746–A750), responded to the EGFR inhibitor afatinib, where-as the Meso34 cell line without an EGFR mutation did notrespond to afatinib at the same dose, demonstrating selectivityfor activation mutations in the MAPK pathway leading to aresponse to HLA-A upregulation (Supplementary Table S1).We detected an effect of MAP kinase pathway inhibition onupregulation of HLA-A in the context of gain-of-functionmutations or activation of other targets in the MAP kinasepathway, such as the KRAS G12V mutation in the SW480 andCFPAC-1 cell lines, the RET/PTC1 gene rearrangement in theTPC1 thyroid cell line, and the BRAF V600E mutation seen inthe UACC257 and SK-MEL-5 melanoma cell lines (Fig. 2A).The MEKi trametinib did not affect surface HLA-A expressionon normal PBMC cells, showing that this effect is specificallyseen in cells with activated signaling.

To confirm that the increased HLA expression on thecell-surface had important functional significance for enhanc-ed presentation of antigens, we quantified the cell-surfaceMHC/peptide epitope density by use of TCR-mimic mAbselective for two well-validated tumor-associated epitopespresented by HLA-A�02:01, a WT1 peptide and a PRAME300 peptide (24, 25). Consistent with the increased surfaceHLA-A�02:01 expression, we also observed increased bindingof the two TCR-mimic antibodies upon inhibition of MEKand EGFR (Fig. 2B).

We confirmed the regulatory activity of the pathway in again-of-function experiment by further stimulating the ERKpathway with EGF. The binding of EGF to the EGFR suppressedsurface HLA-A and HLA-A, -B, -C, providing additional confir-mation of the importance of the MAPK pathway in regulatingsurface MHC (Fig. 2C).

The mechanism by which the MAP kinase pathway sup-presses HLA-A was unknown. Given that many cancers haveactivating mutations in specific genes in the MAP kinase path-way, we investigated inhibition of the identified hits in celllines harboring mutations in EGFR, or downstream in Ras. Weused a panel of NSCLC cell lines with activating mutations inEGFR, such as the delE746–A750 in H827, or L858R/T790Mmutation in H1975. The delE746–A750 confers sensitivity toerlotinib, whereas the T790M confers resistance to erlotinib andto other first-generation EGFR inhibitors, but is sensitive toafatinib (26). We also used EGFR wild-type NSCLC lines withdownstream mutations, such as activating NRAS Q61K inH1299 or KRAS G12S in A549.

Use of the EGFRi erlotinib and afatinib upregulated surfaceMHC-I if the cell line had the sensitizing mutation, whereas allresponded to trametinib MEKi (Fig. 2D and E). The sensitivity toEGFRi erlotinib and afatinib upregulating surface MHC-I was notobserved with downstream activating RAS mutations. Expressionof the activating EGFR mutation L858R suppressed MHC-I inH1299 NRAS Q61K mutant cell lines (Fig. 2F).

H827 responded more strongly to EGFRi by erlotinib thanMEKi by trametinib, despite their similar suppression of pERK, adownstreammarker of MEK activity. The combination MEKi andEGFRi was equivalent to EGFRi alone (Fig. 2G). We introducedthe NRAS Q61K mutation, shown to cause resistance to EGFRiand persistent activation of the MAPK pathway in H827. Use ofthe EGFRi still had an effect on surface MHC-I despite no changein pERK output on the H827 NRAS Q61K cell line (Fig. 2H). Thiscould be due to activation of parallel signaling pathways in EGFR-mutant cancers or differential stimulationof ERK. Thus, theMAPKpathway is not the only determinant of EGFR-mediated regula-tion of surface MHC-I. Given that both EGFR and MEK areinvolved in signaling via the MAP kinase pathway, these datavalidate the importance of this pathway in regulating surfaceHLA-A and MHC-I.

IFNg is a well-known regulator of MHC-I via the JAK/STATpathway (27, 28). We asked whether a combination of IFNg withthe kinase inhibitors would have additive effects on HLA expres-sion (Supplementary Fig. S5A–S5C). Both IFNg and afatinib (inEGFR-mutant H1975 lung cancer cells), and IFNg and trametinib(in Braf-mutant SK-MEL5 andUACC257melanoma cells), alone,each increased expression of cell-surface HLA molecules, as mea-sured by antibodies to HLA-A�02:01 or pan–HLA-A, -B, and -C.The combination of the IFNg and the drug had greater effects thaneither alone, consistent with the involvement of two differentpathways. PCR analysis of TAP1 showed that this internal com-ponent of the antigen presentation machinery was also upregu-lated by IFNg by 10- to 25-fold in all three cell lines. b2-Micro-globulin was also upregulated 4- to 7-fold with IFNg treatment inall three lines. There wereminimal increases in these two proteinsin response to the two kinase inhibitors in H1975 andUACC257.However, in SK-MEL5, trametinib increased both proteins aloneand was additive with interferon gamma.

HLA-E is another component of the antigen presentationpathway that presents MHC molecule–bound peptides and maybe involved in downregulating NK cell immune responses tocancers (29). IFNg and afatinib (in EGFR-mutant lung cancercells) did not affect HLA-E levels (Supplementary Fig. S5D).Trametinib, in Braf-mutant SK-MEL5 melanoma cells, increasedcell-surfaceHLA-Emolecules, but did not do so inUACC257 cells.IFNg also variably upregulatedHLA-E in the twomelanoma lines,

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and the combination of drugs was more effective in increasingHLA-E in UACC257 cells (Supplementary Fig. S5E and S5F).Although an upregulation ofHLA-Emight be expected to partiallycounter the effects of upregulation of classic MHC seen in thesecells, the net effect was to improve cytolytic activity.

Improving immunotherapy by inhibiting the MAPK pathwayWe next tested the effects of modulating HLA-A�02:01 expres-

sion on the efficacy of immunotherapies that depend onHLA-A�02:01 upregulation and antigen presentation, by use ofpmel-1 T cells expressing a TCR that reacts with gp100 and use of

Figure 2.

Use of selective EGFRi and MEKiincreased cell-surface HLA-Aexpression and tumor antigenpresentation, whereas activation ofEGFR caused downregulation ofMHC-I. A, MEK inhibition and EGFRinhibition for 72 hours with indicatedinhibitors increased HLA-A (BB7binding) by flow cytometry in JMN,Meso34, PC-9, UACC257, SK-MEL-5,SW480, and TPC1 cell lines. DMSO(1%) was used as a vehicle control.B, binding of TCR-mimic antibodies topeptide /MHC epitopes. In blue, use ofESK antibody to a peptide derivedfrom the oncoprotein WT1 that ispresented on HLA-A0201. Bindingincreased after inhibition of EGFR andMEK for 72 hours in JMN, Meso34, andTPC1. In red, the PRAME TCR-mimicantibody to an epitope of PRAMEtumor antigen presented on HLA-A0201 on SKMEL5 cells. Experimentalset-up was similar to A. C, treatmentof JMN with 10 nmol/L EGF for 72hours, causing activation of thedownstream MAPK pathway, led todecreased surface HLA-A and totalHLA-ABC. D, use of EGFRi erlotinib,along with MEKi trametinib, on H827(EGFR E746del-A750 mutation),H1975 (L858R/T790M), H1299 (EGFRwt, NRASQ61K), and A549 (EGFRwt/KRAS G12S) to alter surface HLA-ABCexpression. The Student t test wasdone to compare each treatment tovehicle control. �P values annotatedas in Fig. 1. E, Western blot analysisshowing degree of inhibition of theMAP kinase pathway on a panel ofNSCLC cell lines using 1% DMSO (D),100 nmol/L erlotinib (E), 100 nmol/Lafatinib (A), or 500 nmol/L trametinib(T). F, H1299 cells were transducedwith retroviral vectors expressingEGFR L858R and were analyzed forsurface pan–HLA-ABC using W6/32.Activation of EGFR is demonstratedby Western blot. G, EGFR inhibitionupregulated surface HLA-ABC morethan MEKi, despite equivalentinhibition of pERK output. H, EGFRiupregulated MHC-I despitedownstream mutations causingconstitutive MAPK activation. TheNRAS Q61K mutation was introducedinto H827 and cells were treated withEGFRi or MEKi as done in 2G.Experiments were performed 2 to 4times with similar results, and datashown are representative.






two different TCR-mimic antibodies whose function also dependon peptide/MHC-I expression. The TCR-mimic antibodies ESKM,which targets a peptide fromWT1 in the context of HLA-A�02:01,and Pr20m, which targets a peptide from PRAME, were used aseasily quantifiable surrogate tools for measuring the potentialtherapeutic consequences of upregulation ofHLA-A�02:01–basedantigen targets as a consequence of MEK inhibition. The cytotox-icity of ESKM against the JMN andMeso34 humanmesotheliomacell lines were increased by MEK inhibition with trametinib(Fig. 3A and B), which was used at a noncytotoxic dose (Supple-mentary Fig. S6). Increased cytotoxicity of the Pr20m mAb wasalso observed with use of the MEKi trametinib in the SK-MEL-5human melanoma cell line, validating this observation withmultiple targets in multiple cell lines (Fig. 3C).

Finally, specific killing by T cells increased after upregulatingMHC-I withMEKi. The pmel-1 gp100–specificmouse T cells weremore effective at killing of the gp100-positive target B16F10melanoma cells following trametinib treatment, which correlat-ed with pERK inhibition and MHC-I upregulation (Fig. 3D–F;ref. 30). Therefore, improved recognition as a result of theincreased expression of MHC-I and its presented peptides usingthree different target antigens by TCR or TCR mimics had signif-icant consequences for cytotoxic activity.

Mechanism of MAPK regulation of MHC-IWe hypothesized that the inhibition of the MAP kinase path-

way might act on other components of the antigen presentationmachinery in addition to MHC-I molecules, thus allowingincreased epitope expression in the more abundant cell-surfaceHLA molecules. Indeed, EGFR and MEK inhibition produced anincrease in mRNA gene expression of HLA-A along with other key

components of the antigen presentation pathway and MHC-Istructure, such as TAP1, TAP2, and b2M (Fig. 4A). The JMN andMeso34 cells at t¼1hourwere sensitive to trametinib at doses lessthan 10 nmol/L as previously reported, but required higher dosesto sustain inhibition of pERK at t ¼ 72 hours due to strongfeedback (Supplementary Fig. S7A vs. S7B). Doses of trametinibwere chosen over the IC50 of MEK by using pERK as a readout ofMEK inhibition at 72 hours (Supplementary Fig. S7B and S7C).These data correlated with previous findings that BRAF-mutantcell lines are the most sensitive to MEK inhibition, when com-pared with BRAF wild-type cell lines harboring further upstreammutations (31). A time course showed maximal inhibition ofMEK at 3 hours, with maximal increases of HLA-A and b2M at 72hours (Supplementary Fig. S8). Surface HLA-A increased in adose-dependent manner with increasing MEK inhibition in bothmelanoma and mesothelioma (Fig. 4B). The phenotypesobserved are unlikely from off-target effects of the drug, giventhe dose response on pERK expression and the plateau of the doseresponse of surface HLA-A.

Antibodies against pERK, alongwith total ERK1/2, were used toshowdose-responsive increases in response to trametinib inverse-ly correlated with HLA-A protein expression. The increase of b2Mmuch greater than that of HLA complexes in multiple cell lines,consistent with the gene expression data (Fig. 4C). EGFRi witherlotinib also caused a dose-dependent increase in HLA-A andb2M (Fig. 4D). Because b2M is required for surface presentation ofHLA-A, -B, and -C and stability of theMHC-Imolecules on the cellsurface, we investigated the potential role of b2M in controllingcell-surface HLA-A expression. Overexpression of b2M increasedcell-surface HLA-A and pan–HLA-ABC, phenocopying the effectof MEK inhibition (Fig. 4E), which was regulated by multiple

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Improving cytolysis efficacy by up-regulating cell-surface MHC-I. A, antibody dependent cellular cytotoxicity assay was performed on the JMNhuman mesothelioma cell line. Cells were incubated for 72 hours with either vehicle control or trametinib and subsequently exposed to eitherisotype antibody or ESKM in ADCC assay B, ADCC assay on Meso34 (human mesothelioma). Experimental set-up was similar to 3A. C, ADCC assayon SKMEL5 (human melanoma) using TCR-mimic mAb PRAME against the PRAME epitope, experimental setup similar to 3A. D, B16F10 cells wereexposed to pmel-1 (gp100)–specific TCR T cells for 24 hours, then killing was assessed using a clonogenic assay described previously. E, B16F10pERK protein, as measured by pERK intracellular staining, in cells treated with vehicle or 1 mmol/L trametinib. F, B16F10 MHC-I expression assessedby flow cytometry after treatment with 1 mmol/L trametinib for 72 hours. Experiments were performed 2 to 4 times with similar results, and data shownare representative.

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Figure 4.

MAPK signaling suppresses antigenpresentation machinery and MAPKinhibition broadly upregulates antigenpresentation machinery. A, MEK and EGFRinhibition for 48 hours led to increasedHLA-A, along with TAP1, TAP2, and b2M inJMN, Meso34, SK-MEL-5 and UACC257,H827, and PC9. B, dose-dependentincrease in surface HLA-A with increasingMEKi in JMN and SKMEL5. Cells wereanalyzed by flow cytometry at 72 hours. C,MEK inhibition leads to increasing amountsof HLA-A and b2M protein. Cells weretreated with indicating amounts oftrametinib (MEKi) for 72 hours and specificantibodies to the indicated proteins wereblotted. D, EGFR inhibition led toincreasing HLA-A and b2M protein.Experimental set-up similar to C. E,overexpression of b2M led to increasedsurface HLA-A and HLA-ABC. F, treatmentof JMN with trametinib for 72 hours led toincreased activity on the HLA-A and b2Mpromoters. The HLA-A and b2M promoterwas cloned upstream of the GaussianLuciferase gene. SEAP under the CMVpromoter was used as a normalizationfactor. G, knockdown of STAT1, on JMNcells treated with MEKi demonstrates rolein mediating surface HLA-A upregulation.JMN cells were transfected with siRNAagainst the genes shown and treated witheither DMSO or 1 mmol/L trametinib 24hours after siRNA transfection, thenassayed by flow cytometry for surfaceHLA-A expression 72 hours aftertreatment. Experiments were performed2 to 4 times with similar results, and datashown are representative.






regulatory domains in the promoter region, including the ISREsite, E box, and NF-kB sites. Using a luciferase-based promoterassay, we demonstrated that upon addition of MEKi, a dose-dependent increase in activity on the HLA-A and b2M promoterswas observed (Fig. 4F). Knockdowns of STAT1, STAT3, and RelA(a component of the NF-kB complex) were performed on JMNcells, alongwith treatment withMEKi. STAT1 knockdown had thelargest inhibition of upregulation of surface HLA-A after MEKi,suggesting a role for STAT1 in responses to MEKi (Fig. 4G).

MAPK activation causes in vivo suppression of MHC-I andincreased PD-1/L1

We confirmed that these observations on MHC regulationand antigen presentation machinery were not limited to in vitro

models. Microarray profiling of the lung bearing tumors fromtransgenic EGFR L858R, which activates the MAPK pathway,compared with normal lungs, demonstrated suppression ofmouse MHC-I and antigen presentation components H2-K/Dand b2M, thereby confirming the effects of this pathway in vivo(Fig. 5A; ref. 19). Upregulation of PD-1 and PD-L1 markers inthe tumors was also observed as previously published (20).

Expression of EGFR L858R in the transgenic mice, givendoxycycline for >6 weeks, was demonstrated by increasedbinding of a human EGFR-specific fluorescently labeled mAb(Fig. 5B). Mice were confirmed to have development of lungadenocarcinoma by MR, with development of a reticulonod-ular infiltrate in the lung, consistent with previous publica-tions (18). The CD45�hEGFRþ population in the lung in the

Figure 5.

Activation of the MAPK pathway via activating EGFR mutations causes in vivo suppression of MHC-I in addition to upregulation of checkpoint blockade.A, unsupervised hierarchical clustering microarray expression profiling analysis of lung tumors from CC10/L858R mice with EGFR L858R tumor–bearinglungs (right, black) or normal lungs (left, green) focusing on H2-KD, b2M, TAP1, TAP2, PD-L1(PDCD1), and PD-1 (CD274) gene expression. B, flowcytometry data of FVB CC10-rtTA/TetO EGFR L858R-expressing mice. Mice were induced with doxycycline for >6 weeks before sacrificed (mice E–G).Control mice were kept on normal diet, but genotypically identical (A–D). Lungs were isolated and stained with markers for CD45 (pan-leukocyte), hEGFR,and H2-Kq (MHC-I). C, the CD45� lung population was stained with mouse H2-kq–specific mAb. CD45�hEGR� population shows higher MHC-I expressionthan the CD45�hEGFRþ population. Representative MRI images of mouse lungs are shown for two samples.

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EGFR L858R–expressing mice demonstrated decreased bind-ing of a MHC-I–specific mAb by flow cytometry, when com-pared with a wild-type mouse that did not express the EGFRL858R mutation (Fig. 5C).

DiscussionImmunotherapy of cancer is emerging as a successful and

important component of treatment. MHC molecules presentingantigens are the target of multiple therapeutic strategies thatinvolve vaccines, T cells, or TCRs, TCR-mimic antibodies, or T-cellcheckpoint blockade. The last, a highly effective recent example incancer therapy, appears to require presentation of neoantigens onMHC-I on the surface of cancer cells (32–34).Most immunothera-pies have focused on enhancing intrinsic effector cellmechanismsformodulating the immune response, either by directly activatingthe effector T cells or by relieving their suppression. In distinctcontrast, here we propose an alternative approach, whereby theantigenic targets on the cancer cells themselves are modulated toimprove TCR-based killing. The ability to regulate such responsesby selectively affecting target cells could have an important impacton both disease and therapy.Wepropose that kinases are a readilydruggable pathway that might be used in conjunction withimmunotherapy to enhance efficacy. The beneficial effect of thecombination of immunotherapy with kinase inhibition wasshown in mouse models of combined PD-1/PD-L1 blockadewith MEKi (35). A second model, of adoptive T-cell therapy incombination with MEKi in BRAF-mutant murine melanoma, hasdemonstrated superiority to single agents alone (36). Our workhas provided a new understanding of another mechanism whythese combination therapies may be more effective, whereinupregulated MHC-I and antigen presentation on the target cells,essential for the adaptive immune response, improves TCR-basedrecognition and killing. Indeed, many of the patients treatedcurrently with immunotherapies also receive kinase inhibitortherapies as distinct treatments.

The loss- and gain-of-function screen described here allowedunbiased interrogation of the currently annotated human kinasesfor their regulation of cell-surface MHC-I. We then exploredmechanistically how such kinase regulators could be inhibitedfor altering surface expression ofMHC-I, as away of validating thescreen, understanding the process, and also for extending thefindings to functional modulation of a model immunotherapyproof of concept that directly depends onMHC-I presentation. Inthis case, we were able to specifically isolate the MHC as the soletarget of the therapy by use of therapeutic TCR-mimic antibodiesdirected to antigens presented by MHC.

This study also provides support for the use of a flowcytometry–based loss-of-function pooled shRNA screen in thestudy of the regulation of other cell-surface molecules, andpotentially intracellular antigens as well. This technique willallow many laboratories without robotics and high-throughputflow cytometry equipment to investigate pathways that can beeasily perturbed with loss-of-function RNAi screens or othertechniques, such as CRISPR loss of function.

Here, we have demonstrated the effect of the MAPK pathwayon MHC-I, in vitro and in vivo. However, therapeutic applica-tions in humans of the combination of available immunothera-pies and pharmacologic kinase inhibition, to increase MHC-Isurface expression and antigen presentation, will be compli-cated and difficult to predict, because T cells and NK cells also

rely on similar kinase signaling pathways for activation. Morework needs to be done to determine optimal pathways orschedules or doses to target MHC in tumor cells specifically,while sparing signaling pathways of the effector cells (37).Some studies suggest conflicting effects of MEKi on T-celleffector function, which may be dependent on the tumor modelevaluated (38, 39). These effects cannot be simply modeled inmice. Empirically derived optimal dosing and schedules will beneeded in in vivo models and in humans to show that use ofkinase inhibition to regulate immunotherapy has therapeuticbenefits, while sparing immune effector cells of the detrimentaleffects (39–41). These investigations will be complicated by theeffects of some of the drugs on the cellular effectors themselves,the variable effects on the cancer cells depending on theirspecific mutations, the time frames required to upregulate theresponses (about 3 days in the experiments here) and the timerequired for the effects to wash out of the cancer cells and theeffectors.

The data provide a mechanistic explanation of how MHC-I isregulated by the MAPK pathway. MHC-I mRNA expression isregulated through upstream enhancer elements, with involve-ment of the NF-kB transcription factor (42, 43). MHC-I is alsoinduced by TNF, IL1, IFNb, and IFNg , which upregulates HLA-Avia the JAK/STAT pathway (27, 28). The CIITA transcription factorcan also act on MHC-I gene expression (44). IFNg can increaseMHC-I and antigen presentation, but thus far its use has hadlimited applications (45). We show here that combining thekinase inhibitors with IFNg in vitro can have additive effects onHLA expression, TAP1, and b2M. This may be of benefit in vivo asIFNg may be elaborated locally at tumor sites from tumor-infil-trating lymphocytes at steady state or in response to other immu-notherapies, such as checkpoint blockade.

MEK has been proposed by others to be a regulator of MHC-Iexpression. EGFR inhibition can augment MHC-I and MHC-IIexpression in keratinocytes (46). MEK was previously identi-fied as a negative regulator of HLA-A�02:01 in esophageal andgastric cancer by Mimura and colleagues (47). We validatedthese targets in the screen as important negative regulators ofMHC-I and discovered a mechanistic role of the MAP kinasepathway in regulating surface levels of MHC-I. Our data direct-ly link to immune-oncologic applications in humans, bydemonstrating potent upregulation of MHC-I in a wide varietyof cancers, including melanoma and NSCLC, which are cur-rently the subject of FDA-approved therapies which dependupon on antigen presentation, such as checkpoint blockadewith mAbs ipilibumab, pembrolizumab, and nivolibumab. Inaddition, by demonstrating that an FDA-approved MEKi upre-gulated MHC-I, the results support the clinical testing ofcombination therapies, which could advance this concept intohuman therapy. We characterized these effects on MHC-I incells with activating mutations in the MAP kinase pathway withvarious genotypic lesions, such as activating EGFR mutations,BRAF mutations, and RAS mutations. Finally, we also showedthe mechanism was active in RET-translocated thyroid cancer.The sum of these data supports the importance of MAPKpathway in regulating MHC-I quite broadly, while providingnew mechanistic insights.

Finally, our findings are immunologically significant. Upregu-lation induced by MEK inhibition resulted in superior cytotoxicactivity of TCR-mimic antibodies (directed to specific MHC-pre-sented antigens) and TCR-based therapy with a pmel-specific






murine T-cell model. We further show, in a transgenically engi-neered mouse model in vivo, that activating this pathway reducesexpression of the components of the antigen presentationmachinery, along with MHC-I. This gain-of-function experimentis crucial to proving that activation of MAPK can cause decreasedMHC-I in vivo.

Activating EGFR mutations may contribute to immuneescape, due to PD-L1 expression (20). Downregulation ofMHC-I, which was observed from our study, may also contrib-ute to this finding. While demonstrating combination therapywith EGFRi and checkpoint blockade would be rational, thetransgenic EGFR mice have shown dramatic tumor reductionand cures with EGFRi as monotherapy, leaving little window toshow synergism in currently existing mouse models with check-point blockade (18). Our data also suggest that using combi-nation therapy with MAP kinase inhibition can be powerful,not only as a direct cancer therapy to prevent growth but alsoindirectly to promote immunotherapy.

HLA genes are a risk factor for autoimmune diseases such asankolysing spondylitis and multiple sclerosis (48–50). In addi-tion to upregulation by certain kinases, we showed downregula-tion of MHC-I through new kinase targets. These targets are notcurrently addressed by immunosuppressive therapies, whichinhibit the effector arm of the immune response with concom-itant toxicity. These new targets warrant additional investigationinto altering the course of autoimmune diseases by investigatingthe efficacy of specific kinase inhibitors and developing appro-priate mouse models.

A requirement of many immunotherapies therapies, partic-ularly checkpoint blockade, is the availability of recognizableantigens that are presented on MHC-I. Tumors can decreaseMHC-I expression, to avoid immune system detection of therare neoantigens created in tumors by mutations, and increaseinhibitory receptor expression. By modulating expression ofthese limited antigens, improved clinical efficacy may be seenwith certain immunotherapies in conjunction with currentFDA-approved small molecules targeting EGFR and MEK. Theinhibition of kinase pathways also caused a more generalupregulation of the antigen presentation machinery, includingTap (responsible for transporting peptides) and b2M (respon-sible for stabilizing MHC-I). Many of the recently approvedimmunotherapies, such as blockade of CTLA-4 or PD-1, releasethe T-cell inhibition promoted by target tumor cells. Theseimmunotherapies provide a promising approach to addressing

multiple malignancies. By rationally combining them withtargeted small-molecule inhibitors, novel synergistic treatmentstrategies may be developed.

Disclosure of Potential Conflicts of InterestD.A. Scheinberg has ownership interest in patent applications and is a

consultant/advisory boardmember for Eureka. Nopotential conflicts of interestwere disclosed by the other authors.

Authors' ContributionsConception and design: E.J. Brea, C.Y. Oh, E. Manchado, T. Merghoub,J.D. Wolchok, S.W. Lowe, D.A. ScheinbergDevelopment of methodology: E.J. Brea, C.Y. Oh, E. Manchado, R.J. Garippa,T. Merghoub, S.W. Lowe, D.A. ScheinbergAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): E.J. Brea, C.Y. Oh, E. Manchado, S. Budhu, G. Mo,P. Mondello, J.E. Han, C.A. Jarvis, Q. Xiang, A.Y. ChangAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): E.J. Brea, C.Y. Oh, S. Budhu, R.S. Gejman, G. Mo,J.E. Han, D. Ulmert, R.J. Garippa, A.Y. Chang, J.D. Wolchok, N. Rosen,D.A. ScheinbergWriting, review, and/or revision of the manuscript: E.J. Brea, C.Y. Oh,E. Manchado, J.E. Han, J.D. Wolchok, N. Rosen, S.W. Lowe, D.A. ScheinbergAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): C.Y. Oh, P. Mondello, J.E. Han, D. Ulmert,D.A. ScheinbergStudy supervision: E.J. Brea, D.A. ScheinbergOther (RNA interference studies): R.J. Garippa

AcknowledgmentsWe thank T. Dao, L. Dubrovsky, D. Pankov, P Lito, D. Solit, E. Pamer,

R. Brentjens, M.Will, A. Lujambia, and A. Scott for their helpful discussions. Wealso thank Y. Li and A. Younes for use of their equipment.

Grant SupportThe study was supported by NIH grant R01 CA 55349 (D.A. Scheinberg),

P01 CA23766 (D.A. Scheinberg), Diversity Research Supplement for theP01CA023766 (E.J. Brea and D.A. Scheinberg), MARF (D.A. Scheinberg),P30 CA008748, NCI Grant NIHT32CA062948 (C.Y. Oh), NIGMST32GM07739 (E.J. Brea and R.S. Gejman), MSKCC's Experimental Thera-peutics Center, and the Lymphoma Foundation and Tudor and Gladesfunds. NIH F30 CA200327 (R.S. Gejman).

The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely to indicatethis fact.

Received July 25, 2016; revised August 23, 2016; accepted September 1, 2016;published OnlineFirst September 28, 2016.

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2016;4:936-947. Published OnlineFirst September 28, 2016.Cancer Immunol Res Elliott J. Brea, Claire Y. Oh, Eusebio Manchado, et al. Cancer CellsKinase Regulation of Human MHC Class I Molecule Expression on

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