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Kevin oncogenes proliferative with driving transformed cells and isogenic surfaceome on the glycoproteome of remodeling thematic and Broad www.pnas.org/cgi/doi/10.1073/pnas.1917947117 and drug oncogenes for pos- thereof, suggest combinations and and discovery. fashion, biomarker targets, of autologous the surface view cell and sible surfaceome a systems-level the in broad remodel oncogenes. glycoproteome oncogenes a HER2 driver provide specific and how studies KRAS for these com- especially Overall, in glycans, increases differential hybrid oncogene-induced and plex massive glycoproteome found the to We changes (AI-ETD). trans- a electron dissociation by ion activated fer enabled the called glycoproteomics technique complement afford cell developed we recently whole not with Thus, do data glycopeptides. methods propagate surfaceome covalent current intact to by yet of mediated pathway glycans, sequencing is surface MAPK capture depen- of the protein strong tagging on surface the Cell oncogene reflecting inhibitor signaling. the state MEK sur- common of oncogene-induced potent a dence each to a brings back of signaling faceome MAPK Addition blocks alteration modulators. that and up- immune phosphatases, including suppressing in tumor themes adhesion and of biological molecules some- down-regulation transporters, has common nutrient proteins of oncogene these by regulation of each harmonized KRAS, functions that the as are find but such surfaceomes, We different partners AKT. 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Benjamin by Edited 94305 CA Stanford, University, Stanford 53706; WI Madison, .I swl nw that known well human is in It exclusive mutually 1A). are (Fig. or oncogenes RAS HER2, neighboring and or EGFR these BRAF as overactiva- such in including kinases, are mutations pathway tyrosine oncogenes MAPK receptor powerful of the tion and most KRAS the to immunologic of linked cell Many and increased (6–8). activity, promote suppression metabolic to that fashion proteins metastasis, autologous surface proliferation, cell up-regulated a dozen in two function than iden- have more KRAS oncogenic tified with transformed line tumor cell epithelial novel therapeu- discover for to two 5). need approved (4, about antigens the been only specific prompting to have intervention, antibodies targets yet tic surface 3), cell (2, genome dozen encoded human proteins the membrane different in 4,000 some are others among There surveillance, (1). immunological sig- of progrowth evasion import, and cancer nutrient naling, increased survive, promote To to adjust identity. cells immunologic defines and adhesion, T eateto hraetclCeity nvriyo aiona a rnic,C 94143; CA Francisco, San California, of University Chemistry, Pharmaceutical of Department eetsraem tde na sgncMF0 breast MCF10A isogenic an in studies surfaceome Recent ecl ufc rtoe rsraem,i h aninter- cellular main and homeostasis, the nutrient is signaling, surfaceome, cellular for or face proteome, surface cell he | glycoproteomics a,2 a,1 c eateto imlclrCeity nvriyo icni–aio,Mdsn I576 and 53706; WI Madison, Wisconsin–Madison, of University Chemistry, Biomolecular of Department ayM Wilson M. Gary , | surfaceome | N AKsgaigpathway signaling MAPK b,c,1 lne lcpoen to glycoproteins -linked iaL Kirkemo L. Lisa , a ihlsM Riley M. Nicholas , doi:10.1073/pnas.1917947117/-/DCSupplemental. at online information supporting contains article This 2 also are figures several 1 (https://wellslab.ucsf.edu/oncogene partner of browser ProteomeX- data illustrations PRIDE a to in Interactive deposited available the PXD017039). been via have (identifier datasets repository (proteomecentral.proteomexchange.org) proteomics Consortium the of change All deposition: Data oeiaie ies . C BY-NC-ND) (CC 4.0 NoDerivatives License distributed under is article access open This Submission.y Direct PNAS a is equity. y article from or This gain funding financial research personal received no J.A.W. but and Corporation and L.L.K, Celgene K.K.L., data; statement: analyzed interest G.M.W. paper.Competing y and the wrote K.K.L. J.A.W. and research; L.L.K., performed G.M.W., K.K.L., research; L.L.K. designed J.A.W. and and G.M.W., J.J.C., K.K.L., N.M.R., L.L.K., G.M.W., K.K.L., contributions: Author tapoem-iesae eyrcnl,hbi-yeelectron ETD ion hybrid-type activated as recently, different such methods, Very of (ETD) dissociation scale. expression transfer proteome-wide how a proteins know individual at the on not proteins glycosylation alters do particular globally oncogenes on we gly- glycans However, chemical altered of (19). decade, of heterogeneity examples past and specific cosylation the revealed Over has glycoproteomics (12–18). immune recognition and communication, physiological system alter adhesion, and cell–cell cells, of tumor synthesis, mechanisms of truncated hallmarks sur- are cell or glycans of face sialylation Incomplete and fucosylation, cancer. core branching, in extended altered is lation 11). (10, cancer in oncogene preferable one is others of the activation oncogene without that that reinforcing oncogene-induced shows further or evidence senescence, lethality recent synthetic induce Also, can (9). coexpression mutations versa BRAF vice or KRAS and oncogenic harbor EGFR oncogenic seldom with mutations patients cancer lung example, For tumors. owo orsodnemyb drse.Eal [email protected] Email: addressed. be may correspondence whom work.y To this to equally contributed G.M.W. and K.K.L. ugssopruiisfratbd rgdsoeyi cancer. in and discovery fashion drug autologous antibody cell for a opportunities in suggests cells large-scale onco- isogenic how remodel This for genes a insights glycoproteome. important found provides the study and comparative of dissociation transfer regulation sur- electron enabled dynamic ion the glycoproteomics activated complemented bottom-up by further with We analysis pathway. faceome inhibition MAPK functional small-molecule the common by of reversed to pro- are converge that surface changes consequences 700 large some These of teins. expression and in large change cause bidirectional oncogenes a proliferative neighboring is compared six we and how Here, cancer. environment in immunotherapy extracellular for the target major and cell interactions the mediates between (surfaceome) proteome surface cell The Significance hr sas usata vdneta elsraeglycosy- surface cell that evidence substantial also is There b eateto hmsr,Uiest fWisconsin–Madison, of University Chemistry, of Department b,c,d ohaJ Coon J. Joshua , . y raieCmosAttribution-NonCommercial- Commons Creative d eateto Chemistry, of Department y b,c https://www.pnas.org/lookup/suppl/ and , NSLts Articles Latest PNAS surfaceome ).y | f12 of 1

BIOCHEMISTRY AB

MCF10A Oncogenic Transformation

Empty vector (EV)

MEK phospho- mimetic CD HER2 4 2.0 HER2 EV GF AKT KRAS 3 1.5 EGFR KRAS MEK MEK 2 BRAF 1.0 EV AKT BRAF 1 EV 0.5 EGFR with MEK inhibition Normalized cell growth

0 Normalized cell growth 0.0 142 365 1 2 3 4 5 6 Day Day

Fig. 1. Growth rates and morphologies for MCF10A cells transformed with neighboring proliferative oncogenes in the MAPK pathway. (A) Simplified signaling schematic relationship of six proliferative oncogenes studied, EGFRL858R, HER2 overexpression, KRASG12V, BRAFV600E, MEKDD, and AKTmyr.(B) Oncogenic transformation of MCF10A induces diverse cellular morphologies. Note that images are presented in the same order as the schematic in A. (C) MCF10A cells stably transformed with lentivirus with the different oncogenes grow independent of growth factor. Gray and black lines indicate cellular growth of MCF10A EV control with and without growth factors, respectively. Cell growth (n = 3) was measured each day for 6 d by CellTiter-Glo luminescent cell viability assay and normalized to viability on day 1. (D) Suppression of growth for all cell lines by treatment with 100 nM MEK inhibitor (PD0325901) in the absence of growth factors. MCF10A cells transformed with HER2 appears to be least sensitive to MEKi, followed by KRASG12V and AKTmyr.

(AI-ETD) and ETD with supplemental activation (EThcD), with different oncogenes. No single cell type, culturing con- have emerged as forerunners for glycoproteomic profiling, due dition, or context is representative of all or even one can- to their ability to generate sequence-informative tandem mass cer type. For practical reasons, we chose the spontaneously spectra that link both the peptide backbone and corresponding immortalized breast epithelial MCF10A as our parental cell glycan modification (20–22). These techniques can provide gran- line, because it is often used as a neutral starting point for ularity to the altered glycosylation states of cell surface proteins oncogene studies (25–28). Although MCF10A certainly does upon oncogenic transformation. not recapitulate the diversity of mammary cell biology, it is Here we address how neighboring driver oncogenes of epithelial origin like most common tumors; it is nontu- (KRASG12V, HER2 overexpression, EGFRL858R, BRAFV600E, morigenic, requires growth factors for survival, and does not phosphomimetic MEKS218D/S222D, and myristoylated AKT) harbor gene amplifications or other chromosomal aberrations stably expressed in a common noncancerous isogenic epithelial typical of advanced cancer cell lines. Our intent is to compare cell alter the surfaceome and glycoproteome. Using cell how neighboring driving oncogenes remodel their surfaceomes surface capture (CSC) (23, 24) and AI-ETD glycoproteomics and glycoproteomes in isogenic cells in a cell autologous (21), we found that each oncogene induced common and fashion. unique sets of up- and down-regulated surface proteins and Lentivirus was used to stably transform MCF10A cells with six prevalent oncogenes that are neighbors in proliferative signaling: associated glycans. These sets of protein revealed common L858R G12V V600E biological themes, including increased expression of nutrient HER2 overexpression, EGFR , KRAS , BRAF , the S218D/S222D DD transporters and decreased expression of adhesion molecules. phosphomimetic MEK (MEK ), and myristoylated myr These effects were massively reversed upon inhibition of AKT (AKT ) (Fig. 1A and SI Appendix, Fig. S1). Remark- the MAPK pathway, emphasizing its central importance in ably, the morphologies of each of the transformed cells varied remodeling the surfaceome. These oncogene-induced surface from each other when cultured in the absence of growth factors, proteins highlight targets or combinations to consider for indicative of differences in proteomic landscape (Fig. 1B). In immunotherapy. the absence of growth factors, cells transformed with HER2 and KRASG12V grew to confluence, while cells harboring EGFRL858R, Results BRAFV600E, and MEKDD did not reach confluency, indicative Phenotypic Analysis of Oncogene-Transformed MCF10A Cells. of contact-dependent growth inhibition. Cells transformed with Tumor biology is highly complex and varies depending on the AKTmyr, which signals through a parallel pathway relative to cell type of origin, stage, epigenome, stroma, vascularization, the other five oncogenes, had the most dramatic morphology the immune system, and metabolism. We deliberately took a change, displaying vertically stacked clusters of cells. Unlike the simplistic reductionist approach to compare how specific pro- parental cell line, all of the MCF10A cells stably transformed liferative oncogenes alter the cell surface proteome in a cell with any of the six oncogenes proliferated in the absence of autologous fashion by using isogenic cells stably transformed growth factors to various degrees (Fig. 1C). The HER2- and

2 of 12 | www.pnas.org/cgi/doi/10.1073/pnas.1917947117 Leung et al. Downloaded by guest on September 27, 2021 Downloaded by guest on September 27, 2021 en tal. et Leung KRAS ,wihmyhl to help may which surfaceomes S8), oncogene-induced in Fig. similarity stronger , Appendix the explain (SI expres- cells HER2 of transformed the up-regulation in the One was A). S7 within sion Fig. findings Appendix , higher striking (SI 2D). the also clusters of two (Fig. plot were the clustering across upset coefficients than hierarchical the rather correlation with in heatmap Pearson either a The seen and or as 2A) 1), 2) (Fig. (cluster (cluster together together clustered closely more containing those clustered harboring HER2 cells example, and For oncogenes. particular the of play. any level at translational in factors the additional found or at not regulation suggesting was Transcriptional searched, however, dataset HER2. MME, of of amplification up-regulation or V600E EGFR, BRAF, of in amplification or mutation or L858 G12 KRAS, as in defined mutation was Q61 signature oncogenic anno- activating origin) (34), (epithelial tation carcinoma with (TCGA) 2 Atlas (Fig. Genome origin epithelial of sig- types cancers and oncogenic of same number the a harboring particular, in natures samples in patient transcription, in the NRCAM found was whether and determine BCAM Down- studies. of to previous corre- regulation prompted in correlations observed strongly were were that changes often we common not most 33), known are 32, well levels (6, RNA lated is and it protein between Although oncogene. between signaling each in differences slight proteins, from regulated resulting presumably differentially uniquely a of had line number cell substantial dif- each the but overlapped, of proteins Many expressed S6). ferentially Fig. pro- Appendix , reflecting (SI surface sets, remodeling down-regulated different bidirectional and up- 150 between split to evenly were observed 100 2A we for datasets, (Fig. six changes teins the twofold of remodel- least each 654) significant oncogene-transformed In at reflecting of surfaceomes. the control, the (280 for of EV proteins ing to twofold relative surface least lines at aggregate expres- cell by the the altered Remarkably, across of 2A). proteins was 43% (Fig. surface for lines cell iden- 654 cell sion We of oncogenic (31). total six S4) and a the S3 quantified Figs. and Appendix, (SI tified control EV cells compare the iso- MCF10A to to oncogene-transformed stable (SILAC) the with culture from cell coupled surfaceomes in the protocol acids amino CSC by a labeling tope utilized (24, we (CSC) Here, method enrichment 30). hydrazide the biotin capture a to using exploited proteins be can and (29) proteins vector empty the control. to (EV) in compared cells oncogene-transformed Surfaceomes the in Oncogene-Induced Cells. of MCF10A Expression Differential or absence BRAF followed MEKi, the to in resistant by most either was 1D HER2 lines (Fig. of Overexpression factors cell growth all of presence for growth hampered cells MCF10A with of changes pathway transformed surfaceome MAPK MEKi) the (PD032590, the inhibitor reverses MEK of significantly selective inhibition and potent that the shown with previously was it reduced suggesting others, phenotype. the adhesion than of readily more presence and much plates the HER2 the in The factors. cultured growth MCF10A faster untransformed or to the comparable even than were and factors, growth of absence tagoa ee,teewr rae iiaiisbetween similarities greater were there level, global a At yet pathways, branched multiple drive can oncogenes These KRAS .Uigte1 CApoiinldtstfo h Cancer The from dataset provisional TCGA 17 the Using C). G12V V600E G12V tasomdclspoieae otrpdyi the in rapidly most proliferated cells -transformed or , KRAS N and enx rbdhwtecl ufcoei altered is surfaceome cell the how probed next We and MEK gyoyaini rsn on present is -glycosylation BRAF AKT KRAS G12V i.S5 Fig. Appendix, SI DD tasomdclsbtnti lse 2 cluster in not but cells -transformed V600E myr eems estv oMEKi. to sensitive most were G12V hra el containing cells whereas , , AKT 6.Ide,MK substantially MEKi Indeed, (6). KRAS myr and , EGFR G12V i.S2 ). Fig. Appendix, SI A–F 5 fcl surface cell of >85% el lolfe off lifted also cells L858R ;teechanges these ); N and , -glycosylated EGFR KRAS MEK L858R G12V DD B , pntetetwt Eii tlattrecl ie Fg 3 F (Fig. lines expression cell of three level least markedly at median in were a MEKi that with to epithelial treatment revert targets upon of down-regulated 75 types to or Additionally, cancer found up- 3E). several also (Fig. in was origin up-regulated PODXL strongly of approaches be informatics transcription regulated same stringently above, the be Using described pathway. to MAPK appears the PODXL, by 3D). target, (Fig. proteins pathway such these signaling of MAPK One the expression on the three dependent that strongly least suggesting is at lines, being in cell versa from the visa flip of or down-regulated symmetrically to targets up- protein significantly 20 show datasets S9 3C (Fig. Fig. metastasis such and phenotypes proliferation cancer-associated cellular as in decrease proteins a adhesion trans- with cell consistent of membrane common up-regulation general of and metabolism, a down-regulation porters, indicated with data reversal MEKi phenotypic the Fig. of Appendix, GSEA (SI related. general The in in MEKi higher, 3B). S7B). also untrans- (Fig. the were lines and control oncogenes cell datasets formed six the MEKi all between the across correlation of Pearson MEK changes clustering hierarchical of common by absence showing seen the be in can 3 ity to changed 3A opposed commonly (Fig. as inhibition were oncogenes, proteins all 18 MEK across detected, where proteins lines the cell Of skewness EGFR and has were BRAF inhibition 3A 772) for (Fig. MEKi except of of rectional, (129 presence the proteins in the twofold and than of oncogene- more were by 17% the proteins altered in only con- of twofold cells, in 43% than expressing example, more where by For datasets regulated control. of uninhibited differentially EV all the between the to state including trast common lines, more cell a the induced remarkably and 934 of 3 total (Fig. a experiments. two for the above, between discussed quantified and dataset proteins 492 EV identified of the intersection dataset an with including proteins proteomics proteins, 772 of The total presence a MEKi. the quantified in of line absence cell oncogenic and the each alters of the MEKi landscape fac- compared how we proteomic growth cells, determine of oncogene-transformed To the presence of S2). or surfaceome Fig. 1D) Appendix, oncogene-transformed (Fig. (SI the absence tors of the in all either of signif- cells has MEKi growth Indeed, and the cancer. proliferation impedes in Changes. cell icantly target of therapeutic Surfaceome driver major a central been Common a is pathway Induces MAPK Inhibition MEK ewe h E2and HER2 the between rwe a aet iwec niiulgn e identified data set a gene type, individual data each this of view complexity to (https://wellslab.ucsf.edu/oncogene the made 1 to was cluster Due browser between 2. division spe- cluster general These and the B). S9 reinforce Fig. down-regulation heatmaps Appendix , (SI in cific kinases involved tyrosine phosphatases receptor surface of cell and some attachment in cell reflecting Appendix (SI involved adhesion, migration proteins and of down-regulation differentiation strong 2F in see (35–37). cancer (Fig. we of addition, progression oncogenes In and cor- the development glycosylation the altered of with that relates reports all numerous for 2E). with were consistent features (Fig. when metabolism (GSEA) altered carbohydrate processes Analysis and similarly glycosylation Enrichment biological example, Set For common Gene by into viewed harmonized these line. cell oncogene-expressing HER2 EGFR where the regulation, in down-regulated compensating is striking showed also sis nerto fteocgnctasomto n MEKi and transformation oncogenic the of Integration oncogenes the of effects the reversed MEKi measure, large In ept ealddfeecsa h niiultre level, target individual the at differences detailed Despite .Teecagswr otybidi- mostly were changes These S6A). Fig. Appendix, SI C and D). KRAS and G12V .Teewr lolrechanges large also were There S9A). Fig. , i.S5 Fig. Appendix, SI KRAS or >1 n E2aesilms lsl cor- closely most still are HER2 and G12V i.S6B). Fig. , Appendix (SI <−1 surfaceome). ellns hssm analy- same This lines. cell NSLts Articles Latest PNAS G–M and .Tesimilar- The ). IAppendix, SI | A–C). f12 of 3 The ). ),

BIOCHEMISTRY 40 ABStomach Adenocarcinoma 30 Up-regulated: MME Pancreatic Adenocarcinoma Down-regulated: BCAM, NRCAM 20 Lung Squamous Cell Carcinoma 10 Esophageal Adenocarcinoma

0 Colorectal Adenocarcinoma

10 5101520 log (BCAM RSEM+1) Intersection Size 2 20

30 C of significantly up- or down-

regulated protein expression Prostate Adenocarcinoma HER2 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Lung Adenocarcinoma Liver Hepatocellular Carcinoma EGFR ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Esophageal Adenocarcinoma AKT ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Colorectal Adenocarcinoma BRAF ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Cholangiocarcinoma ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● MEK Cervical Squamous Cell Carcinoma KRAS ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 051015 60 40 20 0 20 40 60 log (NRCAM RSEM+1) Set Size 2 DE F FUT10 GO_GLYCOSYLATION TMEM5 GO_CARBOHYDRATE_METABOLIC_PROCESS EXT2 GALNT11 GO_GLYCOPROTEIN_METABOLIC_PROCESS GCNT2 ST6GALNAC2 GO_EXTRACELLULAR_MATRIX_COMPONENT DPY19L4 GO_BASEMENT_MEMBRANE A4GALT

B3GNT2 2 B4GALT5 GO_ENDOSOMAL_PART B3GNT5 GO_REGULATION_OF_BODY_FLUID_LEVELS MGAT4B 1 RPN2 GO_NEGATIVE_REGULATION_OF_TRANSPORT STT3A 0 GXYLT1

GO_TRANSFERASE_ACTIVITY_TRANSFERRING_HEXOSYL_GROUPS POMT2 -1 RPN1

2 GO_TRANSFERASE_ACTIVITY_TRANSFERRING_GLYCOSYL_GROUPS GALNT10 B4GAT1 -2 GO_REGULATION_OF_METAL_ION_TRANSPORT ALG9 SILAC enrichment ratio B3GALNT2 1 GO_CELL_PROJECTION_MEMBRANE EDEM1 GO_POSTSYNAPSE ST3GAL4 FKTN 0 GO_SYNAPTIC_MEMBRANE GALNT18 ST3GAL2 GO_DEPHOSPHORYLATION NPC1 NAGPA -1 GO_PHOSPHATASE_ACTIVITY POMK MGAT4A GO_ANCHORED_COMPONENT_OF_MEMBRANE STT3B -2 GO_GROWTH_FACTOR_BINDING DPY19L3

SILAC enrichment ratio B4GALT3 GO_POSITIVE_REGULATION_OF_CELLULAR_COMPONENT_BIOGENESIS MAN2A1 GNPTAB GO_NEGATIVE_REGULATION_OF_CELL_DEVELOPMENT TUSC3 MGAT5 GO_REGULATION_OF_CELL_DEVELOPMENT POMT1 MAN2A2 GO_NEGATIVE_REGULATION_OF_CELLULAR_COMPONENT_ORGANIZATION EXT1 GO_POSITIVE_REGULATION_OF_NEURON_DIFFERENTIATION GALNT1 GCNT1 GO_REGULATION_OF_NEURON_PROJECTION_DEVELOPMENT MAGT1 DAG1 GO_REGULATION_OF_AXONOGENESIS B3GALNT1 GCNT4 GO_REGULATION_OF_CELL_PROJECTION_ORGANIZATION ST3GAL6 B3GALT6 GO_POSITIVE_REGULATION_OF_NEURON_PROJECTION_DEVELOPMENT MUC16 FUT11 GO_REGULATION_OF_CELL_MORPHOGENESIS_INVOLVED_IN_DIFFERENTIATION ST3GAL1 GO_REGULATION_OF_CELL_MORPHOGENESIS GALNT3 ST6GAL1 AKT

MEK GO_REGULATION_OF_ANATOMICAL_STRUCTURE_MORPHOGENESIS GXYLT2 BRAF HER2 KRAS EGFR AKT AKT MEK MEK HER2 BRAF HER2 KRAS BRAF KRAS EGFR cluster 1 cluster 2 EGFR -2 -1 0 1 2 Normalized effect size

Fig. 2. Proliferative oncogenes cause large changes in the surfaceome that are diverse in detail but have common functional themes. (A) Many differentially regulated proteins are unique to each cell line, and only three proteins were commonly up- or down-regulated among all six oncogene-transformed cell lines when compared to the EV control. In the vertical bar graph, up-regulated proteins (red) are indicated by the upward bars, and down-regulated proteins (blue) are indicated by the downward bars. The specific overlapping groups are indicated by the black solid dots below each bar. The total number of differentially regulated proteins for each cell line are indicated by the horizontal bar graph. Up-regulated (red) and down-regulated (blue) proteins are

defined as log2(fold change) > 1 and P value < 0.05. (B) BCAM and (C) NRCAM are significantly down-regulated across various carcinoma with activating oncogenic signature in KRAS, HER2, BRAF, and EGFR (blue) compared to no mutations in these genes (gray). Activating oncogenic signature was defined as G12 or Q61 mutation in KRAS, L858 mutation or amplification of EGFR, V600E mutation in BRAF, or amplification of HER2. Genomic and expression data were obtained from the 17 TCGA provisional dataset with carcinoma (epithelial origin) annotation. (D) Hierarchal clustering of surfaceome changes revealed similarities between HER2- and KRAS-transformed cells. (E) Top 30 enriched gene sets identified by GSEA of the proteomics dataset using Gene Ontology terms show clustering between HER2- and KRAS-transformed cells. Positive normalized effect size (up-regulation) is shown in red, and negative (down- regulated) normalized effect size is shown in blue. Proteins were preranked by median SILAC peptide ratio, and GSEA was performed using MySigDB C5 GO gene set collection. (F) Proteins involved in glycosylation (GO:0070085) are down-regulated in the KRAS and HER2 cluster (blue), while the same proteins are up-regulated in the other oncogenes cluster. Heatmap for each gene set identified is also available at https://wellslab.ucsf.edu/oncogene surfaceome.

Interestingly, there were a handful of oncogene-induced targets cell lines to compare among themselves and with the EV control. that are further up-regulated upon MEKi, such as MME, sug- For maximal coverage, we enriched the glycoproteomes using gesting they are maintained by circuitous pathways outside of the lectin ConA and hydrophilic interaction liquid chromatogra- MAPK (MEKi independent). Overall, the six oncogenes cause phy (HILIC) that provide a complementary means for capturing profound changes to the surfaceome that alter common biolog- high-mannose-type and complex-type glycans, respectively (41, ical processes, which can be largely blunted by inhibition of the 42). We processed the N-glycoproteomes in biological triplicate MAPK pathway. using liquid chromatography - tandem mass spectrometry (LC- MS/MS) and coupled with AI-ETD (SI Appendix, Fig. S10) (43). Oncogenes Induce Large Changes to the Glycoproteome. Glyco- AI-ETD fragmentation combines radical-driven dissociation and sylation has long been known as a biomarker for cancer (35, 38– vibrational activation and was recently shown to afford robust 40), and our GSEA data show systematic up-regulation of pro- fragmentation of intact glycopeptides (21). Spectral assignments teins involved in glycosylation, especially in cluster 2 (Fig. 2E). were made using the Byonic search engine (44); glycopeptides We thus sought to identify the N-glycosylation modifications on that were not identified across each of the three biological specific membrane proteins for the six oncogene-transformed replicates for each cell line were removed (SI Appendix, Fig. S11).

4 of 12 | www.pnas.org/cgi/doi/10.1073/pnas.1917947117 Leung et al. Downloaded by guest on September 27, 2021 Downloaded by guest on September 27, 2021 nBA,o mlfiaino E2 eoi n xrsindt eeotie rmte1 CApoiinldtstwt acnm eihla origin) (epithelial carcinoma with dataset provisional TCGA 17 the from mutation log obtained V600E were EGFR, log of data amplification (either expression or oncogene L858 and KRAS, in Genomic mutation HER2. Q61 (F or of annotation. G12 as amplification defined or was BRAF, signature oncogenic in Activating (gray). genes these in mutations (E en tal. et Leung results aggregated the and unique 2,648 classes, intact glycan of different of pling log (either oncogene log by (flipped GO negative regulated reversed C5 differentially then and MySigDB were were using red, and shown performed in EV) Proteins was vs. shown GSEA transformation. oncogene at is and oncogenic in available ratio, (up-regulation) by also −1 SILAC is induced size median identified expression effect by set protein preranked gene normalized of each of were Positive number for Proteins redundant. Heatmap are blue. total collection. in functionally proteins The set shown be (blue) gene bar. is could down-regulated each size changes and effect below proteins normalized (red) unique dots (down-regulated) down-regulated Up-regulated that solid and graph. indicating black bars, bar lines, the horizontal upward cell by (C the the indicated similarly. by by line are treatment indicated indicated inhibitor cell groups are MEK are overlapping line upon log (red) specific cell lines as proteins each The cell defined up-regulated seven for bars. all proteins graph, downward to regulated bar the 3) differentially by vertical (bar common indicated the completely are In or (blue) treatment. yellow) in control (highlighted to unique compared completely either were proteins surface 3. Fig. OX ssgicnl prgltdars aiu acnm ihatvtn noei intr nKA,HR,BA,adEF rd oprdt no to compared (red) EGFR and BRAF, HER2, KRAS, in signature oncogenic activating with carcinoma various across up-regulated significantly is PODXL ) obnn oAadHLCercmnsalwdfrsam- for allowed enrichments HILIC and ConA Combining 2 (FC) h aoiyo ifrnilyregulated differentially of majority The (A) transformation. oncogenic of regardless surfaceome the of perturbations similar to led MEK of Inhibition > nMKihbto s epciecl ie na es he ellines. cell three least at in line) cell respective vs. inhibition MEK in 1 N E-needn euaino rti xrsinidcdb noei rnfrain rtissonwr ifrnilyrgltdby regulated differentially were shown Proteins transformation. oncogenic by induced expression protein of regulation MEK-independent ) 2 fl hne[FC]) change (fold gyortoi nlssietfidattlof total a identified analyses -glycoproteomic N gyoetdsta asdcnevtv filtering conservative passed that -glycopeptides o 0erce eest dnie yGE ftepoemc aae sn eeOtlg em hwsmlrte ewe all between similarities show terms Ontology Gene using dataset proteomics the of GSEA by identified sets gene enriched 30 Top ) 2 (FC) > AB D C rlog or 1 -40 -20 KRAS KRAS_MEKi size Set >

HER2 HER2_MEKi 0 and 1 20

2 BRAF BRAF_MEKi (FC) AKT_MEKi 40 Intersection Size AKT of significantly up- or down- EGFR_MEKi EGFR_MEKi KRAS_MEKi HER2_MEKi EGFR BRAF_MEKi regulated protein expression MEK_MEKi ATK_MEKi EV_MEKi P < MEK MEK_MEKi upon MEK inhibition 10 value 10

EV_MEKi 5 noc s V n eete eetdt einlvlbtntrvre flpe log (flipped reversed not but level median a to reverted then were and EV) vs. onco in −1 KRAS_MEKi 0 5 GO_AMINO_ACID_TRANSMEMBRANE_TRANSPORTER_ACTIVITY GO_SOLUTE_CATION_SYMPORTER_ACTIVITY GO_SYMPORTER_ACTIVITY GO_BRANCHING_MORPHOGENESIS_OF_AN_EPITHELIAL_TUBE GO_MORPHOGENESIS_OF_A_BRANCHING_STRUCTURE GO_REGULATION_OF_VASCULATURE_DEVELOPMENT GO_SODIUM_ION_TRANSPORT GO_ANION_TRANSPORT GO_ORGANIC_ANION_TRANSPORT GO_ORGANIC_ACID_TRANSMEMBRANE_TRANSPORT GO_SODIUM_ION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY GO_SECONDARY_ACTIVE_TRANSMEMBRANE_TRANSPORTER_ACTIVITY GO_ANION_TRANSMEMBRANE_TRANSPORT GO_ORGANIC_ACID_TRANSMEMBRANE_TRANSPORTER_ACTIVITY GO_FORMATION_OF_PRIMARY_GERM_LAYER GO_GASTRULATION GO_ANION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY GO_ORGANIC_ANION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY GO_REGULATION_OF_CELL_CYCLE GO_CELLULAR_RESPONSE_TO_NITROGEN_COMPOUND GO_CELL_CELL_CONTACT_ZONE GO_RESPONSE_TO_ACID_CHEMICAL GO_ENZYME_REGULATOR_ACTIVITY GO_ANCHORED_COMPONENT_OF_MEMBRANE GO_AMIDE_BINDING GO_VACUOLE GO_ENDOSOME GO_REGULATION_OF_MULTI_ORGANISM_PROCESS GO_RECEPTOR_MEDIATED_ENDOCYTOSIS GO_DIVALENT_INORGANIC_CATION_HOMEOSTASIS HER2_MEKi omlzdefc size effect Normalized BRAF_MEKi 2 1 0 -1 -2 < AKT_MEKi irrhlcutrn fsraem hne hw E niiintetetafce each affected treatment inhibition MEK shows changes surfaceome of clustering Hierarchal (B) 0.05. EGFR_MEKi

MEK_MEKi SLC22A5 GPC1 MSLN TACSTD2 PTPRS PTPRF HLA-F UNC5B CPM STEAP4 PODXL SLC6A15 SLC7A1 LAMB3 NT5E SLCO4A1 LAMA3 SLC6A14 LAMC2 UGT8 2 (FC) <

Breas E n log and −1 t Invasive Carcinoma log (PODXL RSEM+1) Esophageal Adenocarcinoma 2 10 12 14 16 6 8 Pancreatic Adenocarcinoma

https://wellslab.ucsf.edu/oncogene Stomach Adenocarcinoma

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HER2_MEKi ratio enrichment SILAC E-eedn regulation MEK-dependent (D) surfaceome. BRAF_MEKi -2 AKT_MEKi KRAS_MEKi EGFR_MEKi -1 HER2_MEKi MEK_MEKi BRAF_MEKi 0 DSE PCDH1 ST3GAL1 GALNT3 LMF2 L1CAM ITGB6 F3 EPCAM TSPAN1 BCAM SEMA4D SUSD5 SLC26A2 EFNB3 SLC7A5 KIRREL ACVR1 MST1R ADCY3 CELSR2 MPPE1 NUP210 PCDHGC3 ITFG3 SDC1 CD33 TMEM132A ERBB3 ICAM1 CDH2 PTPRM GGT5 CNTN3 GPM6B TSPAN13 ADGRL3 MME TMX3 TMED9 CHST3 HSPG2 B3GNT2 TSPAN3 IMPAD1 SUN1 LAMB1 CLPTM1 TMEM259 CPD NCEH1 NOTCH2 TMEM9B TMEM106B HM13 SLC2A1 LAMB2 JKAMP APP APLP2 CD63 TTYH3 CD164 PTTG1IP STIM1 ACP2 HGSNAT NPC1 LAMP1 MCOLN1 A4GALT ERAP1 OSTM1 LMBRD1 TMEM179B AKT_MEKi 1 EGFR_MEKi 2

Fg and 4 (Fig. MEK_MEKi

NSLts Articles Latest PNAS EV_MEKi 2 (FC) > 2 rlog or 1 IAppendix SI (FC) < | and −1 2 (FC) f12 of 5 < ,

BIOCHEMISTRY glycoforms (Fig. 4A). These glycoforms map to 785 N-glycosites are on proteins typically found in lysosomes (47–49). Thus, over found on a total of 480 glycoproteins. Thus, on average, each 60% of the N-glycopeptides identified contained less mature glycoprotein had 1.6 N-linked glycosites, and each site had, on high mannose or paucimannose structures originating from pro- average, 3.1 different glycans, reflecting significant heterogene- cessing in the ER or early Golgi. It is not surprising to find ity in glycosylation. Similar yet unique glycoforms indicated that these high-mannose modifications associated with cell surface the heterogeneity of protein N-glycosylation is driven largely by proteins as others have seen that high-mannose N-glycosylation the biology and not artifacts of in-source fragmentation. Of the is abundant at the cell surface and especially associated with 785 experimentally detected glycosites, only 324 were previously oncogene transformation (50–52). Furthermore, we have vali- known or predicted to be glycoyslated in UniPort (45). dated the expression of high-mannose glycans on the cell surface In total, we identified 142 different glycan structures. The gly- by means of ConA lectin staining (SI Appendix, Fig. S14A). Since cans can be categorized into six structural classes based on their CSC techniques label sialic acid, we have also shown that sialic maturation state as they transition from ER to Golgi and then acid is not differentially regulated at the global level shown by split off to either lysosomal, granular, or cell surface destinations SNA lectin staining (SI Appendix, Fig. S14B). (SI Appendix, Fig. S13) (46). The six glycan categories represent We found significant heterogeneity in the number of different a gradation of maturation from the least mature high man- glycan structures at any given site (Fig. 4C). Approximately 45% nose, to paucimannose, phosphomannose, complex/hybrid, and of the sites were observed with only one glycan structure, but finally fucosylated and sialylated (Fig. 4B). We identified 1,636 the range of glycans on these sites was broad. Some glycosites, mannose glycopeptides containing any of 8 high-mannose-type such as position N-234 on aminopeptidase N (ANPEP), had up glycans and 210 were found trimmed to contain any of 9 different to 39 different glycans detected. Additionally, the number of paucimannose structures. The remaining 767 N-glycopeptides glycosites per protein varies considerably; about 70% of the gly- had more complex glycans including: 210 complex/hybrid gly- coproteins have only one site of N-glycosylation, but about 10% copeptides with 28 different structures, 314 of the sialylated class have over five sites. There is a general trend between the num- with 54 different structures, and 226 of the fucosylated class with ber of glycosites identified on a given protein and the number of 42 different structures. We found only 17 phosphomannose con- unique glycans it has; however, some proteins show significantly taining glycopeptides each having the same structural type that increased heterogeneity of glycans relative to their number of

Glycans / Site ABType Example Identified Identified C 2,500 Glycoforms Glycans Glycopeptides 2,459 High Mannose 8 1,636 2,000 1 Paucimannose Reported in UniProt 9 210 2 1,500 3 Complex/Hybrid 28 210 4 Glycosites / Protein ≥5 1,000 Fucosylated 42 226 Glycosites 785 Glycoproteins 500 Sialylated 54 314 480 Glycans P Phosphomannose 1 17 142 0 Combined Data D 60 E

h Glycan Div Hig ersity NH2 50 N128 N128 (25 glycoforms) N234 37.9 Å 40 N234 (39 glycoforms) 41.8 Å N265 N265 (19 glycoforms) 34.8 Å

30 N818

45.7 Å 20 Unique Glycans N625 (1 glycoforms) 45.8 Å N681 (8 glycoforms) 33.9 Å N625 N735 (3 glycoforms) 10 N818 (25 glycoforms) N735 N681 y=x 0 L ity 0246810 ow Glycan Divers COOH Glycosites on Protein

Fig. 4. A global overview of the MCF10a glycoproteome identified from all cell lines. (A) Unique glycans, glycoproteins, glycosites, and glycoforms identified across all six cell lines. A pie chart represents a high percentage of glycosites not previously reported in uniport. (B) High-mannose glycan type is the most common glycan identified. A total of six common glycan types are used to categorize glycans identified. (C) The varying degrees of microheterogeneity (Top) and macroheterogeneity (Bottom) of protein N-glycosylation. (D) A scatter plot of unique glycans versus number of glycosites for each protein provides an additional view of heterogeneity in protein N-glycosylation. The protein with the most heterogenous glycoform was ANPEP (UniProtKB accession no. P15144). (E) Mapping glycan diversity on structure of ANPEP (Protein Data Bank ID 4FYR) reveals spatial regulation of glycosylation patterns. Asparagine residues with high (magenta) and low (teal) number of unique glycans are highlighted. The most C-terminus glyan, N818, has high glycan diversity distance and has similar distance to all other asparagine residues.

6 of 12 | www.pnas.org/cgi/doi/10.1073/pnas.1917947117 Leung et al. Downloaded by guest on September 27, 2021 Downloaded by guest on September 27, 2021 lcslto nteocgn-rnfre ellnsadto and lines cell oncogene-transformed the differential in of view broader glycosylation a capture to glycopeptides data expressed a dataset, this explore identified glycopeptide To individual (https://wellslab.ucsf.edu/oncogene each view S18). to were made Fig. was browser all identi- Appendix, and gly- were (SI high-mannose (Gal-3BP), which cans with protein of modified differentially three glycopeptides binding down-regulated significantly lines, galectin-3 cell from were three six fied glycopeptides all these across in Six expressed expressed lines. iden- differentially were cell significantly protein group, and each underexpressed from tified and glycopeptides Four overexpressed respectively. the to in belonged and represented glycopeptides underex- (LAMA3) alpha- were 24 subunit 12 3 Laminin and transformation. 5C); oncogenic overexpressed upon (Fig. were pressed 12 group lines intersection: any cell this between three glycopeptides changing of significantly of lap from and HER2 glycopeptides between shared 69 were HER2, 12 5 of in line; and up-regulated cell 51 significantly one fact, were least glycopeptides at In ANPEP in expressed lines. differentially cell were ANPEP of dif- in sets expressed differentially ferent were ANPEP ( from trans- itself glycopeptides protein oncogenic the upon was up-regulated as were formation, all and ANPEP, by from glycopeptides 154 expressed the differentially of 28 uniquely example, For specific. protein highly to unique were the 234 in the glycopeptides of 154 expressed glycopeptides; differentially changing line. uniquely of cell set each largest the to the unique with and transformed shared MCF10A is that expression ferential removed farthest the oncogenes. the was of SI ( all EV from line while cell similarity, control EV glycoproteome the S16). from Fig. repli- CV Appendix, analysis, biological median component (<30%) three principal low by the and clustering tight quantita- of 5B), high clustering (Fig. cates was on hierarchical based There close measurements 5A). glycopeptide the (Fig. the quanti- of datasets reproducibility We all tive two-thirds S5). which in of Fig. shared dataset, each Appendix, are in glycopeptides (SI 600 about eightfold range fied which to expression, twofold protein surface from in changes were 50-fold than glycosylation in greater from Changes glycoproteome. ranged the bidi- of significant changes remodeling representing reflecting up-regulated, fold 50-fold S15). symmetric, the to Fig. down-regulated were and Appendix, plots changes, (SI volcano rectional control the EV general, the In control. to relative EV significantly (q formation were the expressed that and differentially glycopeptides and of them hundreds between observed We changes glycoproteome and their of landscapes terms in lines cell oncogene-transformed of bias topological structure. suggests differ- protein folded This 8 the and site. on 1 glycosylation per between structures ranging glycan diversity, ent lower 39 much and to had 681, 19 625, face 735) positions opposite from (at the asparagines ranging clustered while three diversity glycosite, containing 234, per glycan 128, structures high positions glycan had different (at 818) asparagines and four the 265, of protein on the cluster of regions a face specific containing One ANPEP. to of mapped structure diversity three-dimensional identi- glycosites glycan the were Interestingly, higher glycans 4E). with unique (Fig. glycosites 59 eight which across was fied on diversity glycan ANPEP, extreme on most observed The 4D). (Fig. glycosites total en tal. et Leung eepoe h lcncmoiino differentially of composition glycan the explored We BRAF 5C Fig. in plot UpSet The different the compare to analysis quantitative applied next We V600E , EGFR KRAS N MEK aeyguoaie6slaaewr most were -acetylglucosamine-6-sulfatase L858R G12V and , DD rnfrain oeo hs were these of Some transformation. ipassgicn lcppiedif- glycopeptide significant displays and KRAS < MEK BRAF .5 pnocgnctrans- oncogenic upon 0.05) surfaceome). .Other 17). Fig. Appendix, SI KRAS DD G12V KRAS hrdtems over- most the shared V600E noeersle in resulted oncogene G12V KRAS G12V a h greatest the had eeidentified were . G12V elline cell i.5. Fig. oprdt Vcnrl e gi,osregets sim- greatest observe again, We, transformation between control. oncogenic ilarity EV upon to twofold glycopeptides 5D compared than Fig. of more in composition heatmap glycome changing The differential emerged. the trends displays general whether see lines. cell across glycopeptides down-regulated and Bonferroni- up- with for distribution (LIMMA) data microarray for adjusted models linear by assessed (q as transformation oncogenic upon expressed differentially nificantly (C or MEK replicate between to all clustering from unique illustrate correlations analyses are Pearson that Pairwise (B) identifications datasets. glycopeptide between shared shows plot UpSet An (A) rti a lou-euae nthe on up-regulated HER2 also harboring was lines with protein cell and glycopeptides 12) the up-regulated of from the (12 glycan of re- complex/hybrid all inspection a proportion nearly Further that increased glycopeptides. vealed HER2 an complex/hybrid-type showed contrast, of and In high-mannose glycopeptides modified of glycopeptides. proportion up-regulated and increased in an have glycans which lines, Glycopeptides D C A 600 ifrnilyExpressed Differentially Quantified nUStpo ipastesae n nqegyoetdsta r sig- are that glycopeptides unique and shared the displays plot UpSet An )

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BIOCHEMISTRY (6), displayed the highest degree of glycan heterogeneity within pared to 2% for KRAS, 2.8% for EGFR, 5% for AKT1, 1.7% the glycoproteomic data, and has previously been implicated in for BRAF, and 0.6% for MEK1 (SI Appendix, Fig. S19). Each tumorigenesis (53, 54). of these also shows remarkable mutual exclusivity relative to the others in breast cancer patients, reflecting oncogene func- Discussion tional redundancies. Further in silico comparison of oncogenic Oncogenesis is a complex phenomenon that involves aberrant mutational occurrence across all cancer types (59, 60) indicates a changes in multiple biological processes to promote cancer cell strong mutual exclusivity between BRAF and KRAS, and a slight survival (1). Here we study how the surfaceome remodels in mutual exclusivity with EGFR (SI Appendix, Fig. S20). a simplified cell autologous model by six prevalent and neigh- boring oncogenes that drive proliferation through the MAPK Alterations in Transporter Expression. One of the most pro- signaling node. Genetic studies have shown that these onco- nounced oncogene-induced changes we observed is to proteins genes typically exhibit mutual exclusivity in tumors from can- involved in solute transport that reverse upon MEK inhibi- cer patients (9). The surfaceome is a terminal manifestation tion, including up-regulation of SLC2A1, SLC6A15, SLC7A1, of these signaling pathways. We find significant differences in SLCO4A1, and MF12/melanotransferrin, and down-regulation detailed expression patterns, consistent with previously reported of SLC22A5 and STEAP4 (Fig. 3D). SLC6A15 acts as a pref- differences in feedback loops and collateral signaling pathways erential methionine amino acid transporter and shows dramatic between these oncogenes (55). However, we find that these up-regulation in both KRAS- and HER2-transformed cells. This oncogene-induced surfaceome differences harmonize in simi- is consistent with recent studies showing that KRAS-transformed lar functional outcomes overall, and consistent with observed cells exhibit an extreme sensitivity to methionine deprivation mutual exclusivity. (61). The Warburg Effect preferentially shifts cancer cells toward We took a reductionist approach, starting from an immor- glycolysis, thereby promoting accelerated growth and division talized epithelial cell line stably transformed with each of the (62). We find that SLC2A1, also known as glucose transporter- six different oncogenes to determine how the surfaceome is 1, is significantly up-regulated in all oncogene-transformed cells, remodeled in a cell autologous fashion. This system is clearly which would facilitate anaerobic glycolysis and increased growth an approximation and does not recapitulate the complexity of for these cells. Our data show up-regulation of SLCO4A1, a part tumors that vary in cellular context, genetic variation, hetero- of the organic anion transporter family that assists in transport- geneity, oncogene expression, the presence of host immune, ing hormones such as prostaglandins and vasopressin. Height- and metabolism. Nonetheless, cell culture models are a prac- ened expression of this hormone transporter has been previously tical reality allowing isogenic comparison between oncogenes, seen in metastatic colorectal cancer (63). SLC7A1 has been renewable access to materials that permits studies to be readily shown to be up-regulated across many cancer types, including reproduced (56–58). We chose the spontaneously immortalized colorectal cancer (64). Others have shown that SLC7A1 mes- breast epithelial cell line, MCF10A, where the functional loss senger RNA expression level decreases upon MAPK pathway of p16INK4a allows cells to be cultured with a myriad of onco- inhibition (65), which is consistent with our proteomics data. genes without oncogene-induced senescence. We picked this over cancer cell lines which are already transformed or other General Down-Regulation of Receptor Tyrosine Phosphatases and artificially immortalized cell lines, because they often contain Tumor Suppressors. Another important theme found within our genetic lesions that may cause genomic instability, leading to a data is a general down-regulation of surface proteins involved more idiosyncratic background. Overall, we find that indepen- in receptor tyrosine phosphatases and other tumor suppressors dent expression of each of these six oncogenes induced profound such as PTPRF, PTPRS, UNC5B, and BCAM (Figs. 2A and changes in the surfaceome, both in the proteins expressed and 3D). The expression of PTPRF and PTPRS, in particular, has the glycans that decorate them. been associated with decreased metastasis through the inactiva- tion of EGFR signaling, emphasizing their importance as tumor Common Phenotypes and Biological Themes Induced by the Six suppressor proteins in numerous cancer contexts (66, 67). Both Oncogenes. Although the six oncogenes we studied (HER2 over- of these proteins show a marked decrease in expression across expression, EGFRL858R, KRASG12V, BRAFV600E, MEKDD, and myr the majority of the oncogene-transformed cells, perhaps as a AKT ) have many variants that could have different pheno- means to promote growth and metastasis. Similarly, UNC5B has types, we chose well-known representatives, to begin to under- recently been shown to halt tumor progression in an in vivo stand the similarities and differences between them at a coarse- model of bladder cancer, through inducing cell cycle arrest in grain level. Transformation with each of these oncogenes led to the G2/M phase (68). Lastly, BCAM has been previously shown rapid growth, to varying degrees, in the absence of growth factors to be a tumor suppressor in a model of hepatocellular carcinoma and produced somewhat different cell morphologies character- (69), and decreased expression in all oncogene-transformed cells istic of a cancer cell transformed phenotype. Each oncogene may signify the removal of tumor-suppressive signaling. caused large changes in the surfaceome, where about 40% of the detected N-glycoproteins had altered expression level by more Alteration in Adhesion Molecules. Metastasis is the leading cause than twofold, evenly divided between up- and down-regulated of death for patients with cancer, and tumor cells acquire the proteins, reflecting bidirectional cell surface remodeling. ability to penetrate the surrounding tissues, thus leading to inva- There were important differences between the oncogenes, sion (70). Many of these acquired functionalities are through and they clustered into two groups based on growth rates, sur- changes in adhesion molecules on the cell surface, which play faceomes and associated glycans. Cluster 1, containing HER2 the role of mediating cell–cell interactions. Within our dataset, overexpression and KRASG12V, was most aggressive in prolifer- we identified five targets, LAMC2, LAMA3, LAMB3, PODXL, ation and reduced adhesion. Cluster 2 was less aggressive, and and MME, that are known to play important roles in mediat- included EGFRL858R, BRAFV600E, MEKDD, and AKTmyr. We ing metastasis in various tumor types and we find to be up- believe much of the similarity between HER2 and KRAS derives regulated across the majority of oncogenic mutants (Figs. 2A and from KRAS-induced expression of HER2, whereas EGFR sup- 3D). LAMC2 has previously been shown to promote epithelial– presses expression of HER2, probably reflecting their signaling mesenchymal transition [EMT] and invasion in an in vivo model redundancy. MCF10A is derived from normal breast epithe- of lung adenocarcinoma (71). It has also been shown that col- lial cells, and, among these oncogenes, HER2 overexpression orectal cancer with high MAPK activity expresses heightened is most commonly seen in breast cancer patients, at 13% com- levels of LAMC2, supporting our proteomic results that show

8 of 12 | www.pnas.org/cgi/doi/10.1073/pnas.1917947117 Leung et al. Downloaded by guest on September 27, 2021 Downloaded by guest on September 27, 2021 en tal. et Leung Protein and Machinery Glycosylation in Changes the through function exclusive its levels pathway. to expression unsurprisingly, AKT due of Perhaps inhibition, renormalization MEK a (86). after exhibit pro- pathway not cell AKT did stimulates NRCAM form the shed the six via known and is all In liferation proteolysis, it by in (83–85). molecule; shed levels adhesion be cancer cell–cell to surface a of lower is proteolysis mutants, metastasis had oncogenic undergo and which to NRCAM, growth known particular, the are enhance that TACSTD2, lead to identified MSLN, GPC1, would detection, We and in ectodomains LC-MS/MS. NRCAM, reduced of by proteins exis- loss surface detection the The four peptide and termini. decreased shedding N ectodomain to neo to of leads surface tence cell the at Shedding. by Down-Regulation microenviron- tumor upon down-regulated the are 3D). HLA-F (Fig. in system and MEKi NT5E cells respectively, immune Both NK 82). in cells, (81, of ment role T activation a cytotoxic through rejection, play or tumor both and and der- activation as lines, oncogene- all known cell in (also down-regulated expressing tumor DSE were surrounding epimerase) and the sulfate HLA-F matan in cells Conversely, cells killer (80). T the tissue cytotoxic natural prevents of of and expansion molecules capacity clonal IFN the immune-activating produce up- decrease to can from was promotes adenosine which lines, which of AMP, cell production NT5E, oncogene the 3D). proliferative through immunosuppression the (Fig. important all functions play in that regulated immune DSE, in and reg- HLA-F, roles differentially NT5E, three proteins, increase identified be immuno- ulated that we can net Here, proteins activation. a down-regulating This immune by have surveillance. or that effect immune proteins suppressive of overexpressing by evasion achieved the is gression Modulation. Immune MAPK studies other or lethality MEKi targets. with synthetic combination an in into presents inhibition MME height- research contexts with This oncogenic future axis. all for PI3K in opportunity or MME of MAPK expression the ened through expression regulated MME the that not both suggesting is in datasets, oncogenes MEKi all and across oncogene up-regulated Inter- is (79). cancer MME bladder estingly, with the associated expressing gene cells sclerosis isogenic progression up- tubular of and significantly studies found growth surfaceomics also in the was regulated MME in (78). role cancers prognostic important colorectal adverse of an been an play has be and to (77) to adenocarcinoma found stud- considered lung been with is patients not it for has marker detail, MME great of in function the ied While to compared control. neprilysin, mutants EV as oncogenic the six known all MME, in (74–76). up-regulated found axes was MAPK via and progression PI3K cycle mucin-type increased the cell to increased extensive lead through can potential with which metastatic of glycoprotein (73). overexpression signaling a the PI3K glycosylation, cancer also and prostate MAPK is and both implicated PODXL of been breast induction increased has of the and aggressiveness had through lines, the cell PODXL increasing mutant (72). in six all inhibition in MEK expression upon reversal r ihyu-euae cosalocgnccl ie.FUT10 lines. cell oncogenic all trans- across glycosyl up-regulated that highly find ST6GALNAC2 are and We GCTN2, glycan. GALNT11, EXT2, the FUT10, substrate ferases of protein the transfer of disrupt structure pro- tertiary that the substrate to including of changes or expression factors, teins, in of cancer alteration variety substrates, sugar a of of nucleotide availability from glycosyltransferases, features of result expression in common can changes which are (35) glycosylation cells in Alterations nte rmnn as fcne pro- cancer of cause prominent Another rtoyi laaeo proteins of cleavage Proteolytic N -glycosylation. O- eetn nopeemtrto.Tems tnigeapein example stunning the most The to maturation. incomplete route reflecting in proteins high-mannose from the coming of are some although membrane. observe that studies, to we out our ability rule glycans with the exclusively consistent and cannot is genes we This suppressor tumor (104). of self-renew such regulation hESCs, the and cells as to cancerous help between similarities observations the these plasma explain Together, on (50). abundance hESCs higher of observation significantly membranes gly- at similar high-mannose observed where A were versus (hESCs), cans transformed 103). cells of stem (52, comparison embryonic glycomic human the surface that in high-mannose reported cell furthermore, of was and, their abundance surface at increased cell glycans display the cells at cancerous present are glycans 2. cluster cluster for in opposite mannose the high just in and 1 decrease There and glycans 5B). hybrid 1 complex (Fig. cluster oncogene lines MEK the cell between these (KRAS differences of significant analyses were different out between similarity greatest EGFR oncogenesis observed We individual of lines. to of cell unique majority drivers were The glycopeptides glycoproteome. genetic expressed trans- the differentially to distinct oncogenic changes unique that upon promote and changed dramatically formation, is glycosylation IAppendix, (SI lines cell Gal-3BP all glycosites in S18). 50-fold eight Fig. We to the up (102). of from down-regulated sialylation glycopeptides were glycans all via on that blocks fucose found ST6GalNAc2 terminal anoikis which preventing to and Gal-3BP a binds metastasis and Galectin-3 during lectins (100–102). cells S-type tumor aggre- enhancing of of by (99) gation member progression tumor a of sites modulator is to known cells Galectin-3 tumor pro- of metastasis. ST6GalNAc2 retention of and of Galectin-3 of Silencing binding receptor- tumors. motes estrogen cancer in breast suppressor. down-regulated negative metastasis strongly and strongest is identified the ST6GalNAc2 RNA metastasis as hairpin suppress that ST6GalNAc2 short genes validated genome-wide for A mice all lines. in in screen cell up-regulated paradoxically oncogene is the and of glycans core to GalNAc na from (98). transition glycosyltransferase cell the B a in center is germinal implicated GCTN2 specifically lines. and cell (97), these progrowth possible promotes in a GALNT11 phenotypes suggesting increased up-regulated above), which also (see by is lines mechanism PODXL, cell enzymes, oncogenic all of across family this drug sub- for important common a very strate Interestingly, a (93–96). also immunotherapy is for of MUC-1 target initiation (90–92). the cancer in in pressed involved protein have a facil- mucin-type to primary is a GALNT11 shown is EXT2 (89). been which itator of have oncogenesis, alter- formation in roles sulfate Unsurprisingly, emerging heparan (88). adhesion, in signaling extra- as ations and the such of infiltration, processes stability mediating immune structural thereby heparin, glyco- to matrix, of a contributes cellular formation as that the functioning substrate catalyzing Golgi a in the involved in forms transferase are EXT2 EXT1 syl these ANPEP. with up- which for heterodimer significantly for noteworthy a are especially glycans our and KRAS) hybrid-type of members, complex and aggressive are most in (HER2 which the regulated lines fact, antigens cell In LewisX (87). oncogene Sialyl invasion and of hallmarks LewisX of production an is u aasgetgyoyaini ut eeoeeu,possibly heterogeneous, quite is glycosylation suggest data Our high-mannose-type that suggest to evidence abundant is There u lcpoemcaaye hwta protein that show analyses glycoproteomic Our of attachment catalyzes that sialyltransferase a is ST6GalNAc2 DD 13fcslrnfrs,adFT r rtclfrthe for critical are FUTs and α-1,3-focusyltransferase, L858R G12V /AKT and , gyoyain elkonmre hti overex- is that marker well-known a O-glycosylation, HR)adcutr2(EGFR 2 cluster and /HER2) myr .Seicly efuddfeeta nraein increase differential found we Specifically, ). MEK DD hc a encnitn through- consistent been has which , NSLts Articles Latest PNAS L858R /BRAF BRAF | ¨ v to ıve f12 of 9 V600E V600E N - / ,

BIOCHEMISTRY our data of heterogeneity in glycosylation was for ANPEP, an of transformed cells driven by complex but functionally redun- amino peptidase also up-regulated at the protein level across dant changes to the surfaceome. We believe the work provides most cell lines. The most extreme example was site N234 of important insights into the similarities and differences among ANPEP, where we found 29 different glycan structures. When the neighboring oncogenes and provides opportunities to pursue these are arranged in order of glycan maturation, we observed antibody tools to follow in more complex tumor settings. a close representation of its steady-state progression through the secretion pathway (SI Appendix, Fig. S13). ANPEP also Data Archival. All proteomics dataset has been deposited showed the greatest representation within complex/hybrid gly- to ProteomeXchange Consortium (proteomecentral. copeptides that were up-regulated in HER2 and KRASG12V cell proteomexchange.org) via the PRIDE partner repository lines (Fig. 5D). ANPEP was most up-regulated in KRASG12V accessible (identifier PXD017039). Interactive illustrations of in surfaceomic analyses, and its expression was not dramati- several figures are also available in a data browser (https:// cally influenced by MEK inhibition. ANPEP expression in our wellslab.ucsf.edu/oncogene surfaceome). surfaceomic and glycoproteomic data represents one way in SI Appendix. SI Appendix, Supplemental Materials and Methods, which KRASG12V diverges from other members of the MAPK Figs. S1–S20, and Description of Datasets S1 to S25 is included as pathway. These data, combined with ANPEP’s previously iden- a single PDF. tified role in angiogenesis (54), underscore its importance in G12V KRAS -positive tumors. ANPEP glycosylation may serve as Materials and Methods a very sensitive biomarker of glycan metabolism in cells, given its All MCF10A cells were cultured according to established protocols unless highly diverse and heterogeneous patterns. otherwise stated. Surfaceome of each oncogene-transformed cell line was compared to EV control using SILAC-based quantification. For inhibition Conclusions study, each oncogene-transformed cell line was treated with 100 nM MEK We provide a large-scale comparative study of how six neighbor- inhibitor PD032590 or dimethyl sulfoxide control for 3 d, and surfaceome ing proliferative oncogenes cause large-cell autologous remod- changes were compared in each respective cell line using SILAC-based eling in the surfaceome and glycoproteome. While many of the quantification. Glycoproteome of each oncogene-transformed cell line was changes are specific to given oncogenes at both the protein and quantified using label-free quantification. Detailed materials and meth- glycopeptide level, we observe common biological themes sug- ods are included in SI Appendix, and supplementary data are available as Datasets S1–25. gesting functional redundancy of the specific cellular expression. This is consistent with observations that common tumors can ACKNOWLEDGMENTS. We thank Professor Sourav Bandyopadhyay at Uni- express these different oncogenes, although not together. We versity of California, San Francisco (UCSF) for some of the lenti constructs commonly observe up-regulation of surface proteins involved and cell lines, and Michael Westphall, Evgenia Shishkova, and Jean Lodge at University of Wisconsin for instrumentation and helpful discussions. in metabolite transport, glycosylation, and immune suppres- J.A.W. is grateful for funding from NIH Grant R35GM122451 and Celgene sors and down-regulation of adhesion proteins and tumor sup- Corporation. K.K.L. thanks Canadian Institutes of Health Research for post- pressors, which is consistent with increased cell growth and doctoral funding. L.L.K. is indebted to Chemistry and Chemical Biology invasion that are well-known properties of cancer cells. These Training Grant T32 GM064337 at UCSF for funding. J.J.C. wishes to thank NIH for generous funding from P41 Grant GM108538 (The National Cen- studies were deliberately conducted in isogenic cell lines to ter for Quantitative Biology of Complex Systems). G.M.W. was supported in isolate the oncogene-induced changes. Even in a simplified part by the Biotechnology Training Grant T32 GM008349. N.M.R. gratefully autologous cell model, we recapitulate many of the hallmarks acknowledges support from NIH Grant K00CA21245403.

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