Broad and Thematic Remodeling of the Surfaceome and Glycoproteome on Isogenic Cells Transformed with Driving Proliferative Oncogenes

Broad and thematic remodeling of the surfaceome and glycoproteome on isogenic cells transformed with driving proliferative oncogenes

Kevin K. Leunga,1 , Gary M. Wilsonb,c,1, Lisa L. Kirkemoa, Nicholas M. Rileyb,c,d , Joshua J. Coonb,c, and James A. Wellsa,2

aDepartment of Pharmaceutical Chemistry, University of California, San Francisco, CA 94143; bDepartment of Chemistry, University of Wisconsin–Madison, Madison, WI 53706; cDepartment of Biomolecular Chemistry, University of Wisconsin–Madison, Madison, WI 53706; and dDepartment of Chemistry, Stanford University, Stanford, CA 94305

Edited by Benjamin F. Cravatt, Scripps Research Institute, La Jolla, CA, and approved February 24, 2020 (received for review October 14, 2019)

The cell surface proteome, the surfaceome, is the interface for tumors. For example, lung cancer patients with oncogenic EGFR engaging the extracellular space in normal and cancer cells. Here mutations seldom harbor oncogenic KRAS or BRAF mutations we apply quantitative proteomics of N-linked glycoproteins to and vice versa (9). Also, recent evidence shows that oncogene reveal how a collection of some 700 surface proteins is dra- coexpression can induce synthetic lethality or oncogene-induced matically remodeled in an isogenic breast epithelial cell line senescence, further reinforcing that activation of one oncogene stably expressing any of six of the most prominent prolifera- without the others is preferable in cancer (10, 11). tive oncogenes, including the receptor tyrosine kinases, EGFR There is also substantial evidence that cell surface glycosy- and HER2, and downstream signaling partners such as KRAS, lation is altered in cancer. Incomplete or truncated synthesis, BRAF, MEK, and AKT. We find that each oncogene has some- extended branching, core fucosylation, and sialylation of cell sur- what different surfaceomes, but the functions of these proteins face glycans are hallmarks of tumor cells, and alter physiological are harmonized by common biological themes including up- mechanisms of cell–cell adhesion, communication, and immune regulation of nutrient transporters, down-regulation of adhesion system recognition (12–18). Over the past decade, chemical molecules and tumor suppressing phosphatases, and alteration glycoproteomics has revealed specific examples of altered gly- in immune modulators. Addition of a potent MEK inhibitor cosylation and heterogeneity of glycans on particular proteins that blocks MAPK signaling brings each oncogene-induced sur- (19). However, we do not know how expression of different faceome back to a common state reflecting the strong depen- oncogenes globally alters glycosylation on the individual proteins dence of the oncogene on the MAPK pathway to propagate at a proteome-wide scale. Very recently, hybrid-type electron signaling. Cell surface protein capture is mediated by covalent transfer dissociation (ETD) methods, such as activated ion ETD tagging of surface glycans, yet current methods do not afford sequencing of intact glycopeptides. Thus, we complement the Significance surfaceome data with whole cell glycoproteomics enabled by a recently developed technique called activated ion electron trans- The cell surface proteome (surfaceome) mediates interactions fer dissociation (AI-ETD). We found massive oncogene-induced between the cell and the extracellular environment and is a changes to the glycoproteome and differential increases in com- major target for immunotherapy in cancer. Here, we compared plex hybrid glycans, especially for KRAS and HER2 oncogenes. how six neighboring proliferative oncogenes cause large and Overall, these studies provide a broad systems-level view of bidirectional change in expression of some 700 surface pro- how specific driver oncogenes remodel the surfaceome and the teins. These large changes converge to common functional glycoproteome in a cell autologous fashion, and suggest pos- consequences that are reversed by small-molecule inhibition sible surface targets, and combinations thereof, for drug and of the MAPK pathway. We further complemented the sur- biomarker discovery. faceome analysis with bottom-up glycoproteomics enabled oncogenes | glycoproteomics | surfaceome | MAPK signaling pathway by activated ion electron transfer dissociation and found a dynamic regulation of the glycoproteome. This large-scale he cell surface proteome, or surfaceome, is the main inter- comparative study provides important insights for how onco- Tface for cellular signaling, nutrient homeostasis, and cellular genes remodel isogenic cells in a cell autologous fashion and adhesion, and defines immunologic identity. To survive, cancer suggests opportunities for antibody drug discovery in cancer. cells adjust to promote increased nutrient import, progrowth signaling, and evasion of immunological surveillance, among others Author contributions: K.K.L., G.M.W., L.L.K., N.M.R., J.J.C., and J.A.W. designed research; (1). There are some 4,000 different membrane proteins encoded K.K.L., G.M.W., and L.L.K. performed research; K.K.L. and G.M.W. analyzed data; and K.K.L., G.M.W., L.L.K., and J.A.W. wrote the paper.y in the human genome (2, 3), yet antibodies to only about two Competing interest statement: K.K.L., L.L.K, and J.A.W. received research funding from dozen cell surface targets have been approved for therapeu- Celgene Corporation but no personal financial gain or equity.y tic intervention, prompting the need to discover novel tumor This article is a PNAS Direct Submission.y specific antigens (4, 5). This open access article is distributed under Creative Commons Attribution-NonCommercial- Recent surfaceome studies in an isogenic MCF10A breast NoDerivatives License 4.0 (CC BY-NC-ND).y epithelial cell line transformed with oncogenic KRAS have iden- Data deposition: All of the proteomics datasets have been deposited to ProteomeX- tified more than two dozen up-regulated surface proteins that change Consortium (proteomecentral.proteomexchange.org) via the PRIDE partner function in a cell autologous fashion to promote increased cell repository (identifier PXD017039). Interactive illustrations of several figures are also proliferation, metastasis, metabolic activity, and immunologic available in a data browser (https://wellslab.ucsf.edu/oncogene surfaceome).y suppression (6–8). Many of the most powerful oncogenes are 1 K.K.L. and G.M.W. contributed equally to this work.y linked to KRAS and the MAPK pathway including overactiva- 2 To whom correspondence may be addressed. Email: [email protected] tion of receptor tyrosine kinases, such as EGFR and HER2, or This article contains supporting information online at https://www.pnas.org/lookup/suppl/ mutations in BRAF or RAS (Fig. 1A). It is well known that doi:10.1073/pnas.1917947117/-/DCSupplemental.y these neighboring oncogenes are mutually exclusive in human First published March 23, 2020.

7764–7775 | PNAS | April 7, 2020 | vol. 117 | no. 14 www.pnas.org/cgi/doi/10.1073/pnas.1917947117 Downloaded by guest on September 30, 2021 Downloaded by guest on September 30, 2021 i.1. Fig. uooosfsinb sn sgncclssal transformed al. cell et stably Leung a cells in isogenic proteome using surface by cell pro- fashion specific the a autologous how took alter compare deliberately oncogenes to We liferative vascularization, approach metabolism. stroma, reductionist and the epigenome, simplistic system, on stage, depending immune origin, varies the of and Cells. type complex highly MCF10A cell is Oncogene-Transformed biology of Tumor Analysis for Phenotypic consider to Results combinations or in of importance targets surface immunotherapy. inhibition oncogene-induced central highlight These upon its proteins surfaceome. emphasizing reversed the pathway, remodeling massively MAPK molecules. were the adhesion nutrient common effects of of revealed expression These expression decreased protein and and increased and proteins of common transporters including surface sets induced themes, down-regulated These biological oncogene cell and glycans. up- each Using associated of glycoproteomics that glycoproteome. sets AI-ETD found and unique and 24) we (23, surfaceome (21), (CSC) capture the epithelial surface isogenic alter noncancerous common cell a in expressed stably phosphomimetic (KRAS proteins surface cell of transformation. states oncogenic glycosylation upon altered the gran- corresponding to provide and can ularity techniques backbone These peptide mass (20–22). modification the tandem glycan both sequence-informative link generate that due to spectra (EThcD), profiling, ability glycoproteomic activation their for to supplemental forerunners as in with emerged (PD0325901) inhibitor have ETD MEK KRAS nM by 100 and followed with MEKi, treatment to (AI-ETD) sensitive by least lines be cell to all in appears for HER2 schematic growth with of the transformed Suppression as cells (D) MCF10A 1. order factors. day same growth on (n of the viability growth absence to Cell in the respectively. normalized factors, presented and growth assay are without viability and images cell with that control EV Note MCF10A of morphologies. growth cellular EGFR diverse studied, induces oncogenes (C MCF10A proliferative of six transformation of Oncogenic relationship schematic signaling CD AB

C1Aclssal rnfre ihlniiu ihtedfeetocgnsgo needn fgot atr ryadbaklnsidct cellular indicate lines black and Gray factor. growth of independent grow oncogenes different the with lentivirus with transformed stably cells MCF10A ) Normalized cell growth eew drs o egbrn rvroncogenes driver neighboring how address we Here 0 1 2 3 4 14 Simpliﬁed (A) pathway. MAPK the in oncogenes proliferative neighboring with transformed cells MCF10A for morphologies and rates Growth phospho- G12V mimetic MEK 2 E2overexpression, HER2 , 36 Day MEK 5 S218D/S222D EV AKT BRAF MEK EGFR KRAS GF EV HER2 n yityae AKT) myristoylated and , EGFR

Normalized cell growth with MEK inhibition L858R 0.0 0.5 1.0 1.5 2.0 mt etr(EV) vector Empty , 1 MCF10A BRAF 2 V600E 3 Day , 4 L858R BRAF and HER2 1 with transformed (Fig. cells KRAS landscape factors, growth proteomic of factors, absence in growth the varied of differences cells absence the of transformed in indicative the cultured when of other each each of from morphologies the ably, (AKT AKT phosphomimetic autologous overexpression, signaling: cell HER2 proliferative in neighbors a are that oncogenes in prevalent cells isogenic compare in fashion. to surfaceomes is glycoproteomes their intent remodel and Our oncogenes nontu- lines. driving not aberrations neighboring cell is how cancer chromosomal does it advanced other and of is or tumors; survival, typical amplifications it for common gene factors biology, most harbor for growth cell like point requires mammary starting origin morigenic, of does neutral epithelial diversity certainly a of the MCF10A as recapitulate Although cell used cannot (25–28). spontaneously parental often one studies the is our even oncogene chose it as or because we MCF10A all line, epithelial reasons, con- of breast practical culturing representative immortalized For type, is type. cell context cer single or No dition, oncogenes. different with .TeHR-and of HER2- The absence 1C). the (Fig. in degrees proliferated transformed various oncogenes stably to six cells factors the MCF10A growth of the of any morphology all the with Unlike dramatic line, cells. most cell of clusters parental the stacked had vertically displaying oncogenes, change, five other the with transformed Cells AKT inhibition. growth contact-dependent of Transformation 5 etvrswsue osal rnfr C1Aclswt six with cells MCF10A transform stably to used was Lentivirus Oncogenic E2oeepeso,KRAS overexpression, HER2 , 6 myr G12V V600E hc inl hog aallptwyrltv to relative pathway parallel a through signals which , EGFR BRAF EV MEK KRAS AKT HER2 )wsmaue ahdyfr6db elie-l luminescent CellTiter-Glo by d 6 for day each measured was 3) = rwt oflec,wieclsharboring cells while confluence, to grew and , myr Fg 1A (Fig. ) MEK MEK PNAS EGFR S218D/S222D DD | and i o ec oflec,indicative confluency, reach not did pi ,2020 7, April G12V L858R .Remark- S1). Fig. Appendix, SI BRAF , (MEK , KRAS V600E G12V | DD MEK , o.117 vol. n AKT and G12V ,admyristoylated and ), , DD BRAF n AKT and , myr | o 14 no. . EGFR V600E .In B). myr | L858R the , 7765 (B) . A. ,

BIOCHEMISTRY KRASG12V-transformed cells proliferated most rapidly in the between the HER2 and KRASG12V cell lines. This same analy- absence of growth factors, and were even comparable to or faster sis also showed striking compensating regulation, where HER2 than the untransformed MCF10A cultured in the presence of is down-regulated in the EGFR oncogene-expressing cell line. growth factors. The HER2 and KRASG12V cells also lifted off Despite detailed differences at the individual target level, the plates much more readily than the others, suggesting reduced these harmonized into common biological processes when adhesion phenotype. viewed by Gene Set Enrichment Analysis (GSEA) (Fig. 2E). These oncogenes can drive multiple branched pathways, yet For example, glycosylation and carbohydrate metabolism were it was previously shown that inhibition of the MAPK pathway similarly altered features for all of the oncogenes (Fig. 2F), with the potent and selective MEK inhibitor (PD032590, MEKi) consistent with numerous reports that altered glycosylation cor- significantly reverses the surfaceome changes of MCF10A cells relates with the development and progression of cancer (35–37). transformed with KRASG12V (6). Indeed, MEKi substantially In addition, we see strong down-regulation of proteins involved hampered growth for all cell lines either in the absence or in differentiation and adhesion, reflecting cell attachment and presence of growth factors (Fig. 1D and SI Appendix, Fig. S2). migration (SI Appendix, Fig. S9A). There were also large changes Overexpression of HER2 was most resistant to MEKi, followed in some cell surface phosphatases involved in down-regulation by KRASG12V and AKTmyr, whereas cells containing EGFRL858R, of receptor tyrosine kinases (SI Appendix, Fig. S9B). These specific heatmaps reinforce the general division between cluster 1 BRAFV600E, or MEKDD were most sensitive to MEKi. and cluster 2. Due to the complexity of this data type, a data browser was made to view each individual gene set identified Differential Expression of Oncogene-Induced Surfaceomes in (https://wellslab.ucsf.edu/oncogene surfaceome). MCF10A Cells. We next probed how the cell surfaceome is altered in the oncogene-transformed cells compared to the empty vector MEK Inhibition Induces Common Surfaceome Changes. The (EV) control. N-glycosylation is present on >85% of cell surface MAPK pathway is a central driver of cell proliferation and has proteins (29) and can be exploited to capture the N-glycosylated been a major therapeutic target in cancer. Indeed, MEKi signif- proteins using a biotin hydrazide enrichment method (CSC) (24, icantly impedes the growth of all of the oncogene-transformed 30). Here, we utilized a CSC protocol coupled with stable iso- cells either in the absence (Fig. 1D) or presence of growth fac- tope labeling by amino acids in cell culture (SILAC) to compare tors (SI Appendix, Fig. S2). To determine how MEKi alters the the surfaceomes from the oncogene-transformed MCF10A cells surfaceome of the oncogene-transformed cells, we compared the to the EV control (SI Appendix, Figs. S3 and S4) (31). We iden- proteomic landscape of each oncogenic cell line in the presence tified and quantified a total of 654 cell surface proteins across and absence of MEKi. The proteomics dataset identified and the six oncogenic cell lines (Fig. 2A). Remarkably, the expres- quantified a total of 772 proteins, including an intersection of 492 sion for 43% of the aggregate surface proteins (280 of 654) proteins with the EV dataset discussed above, for a total of 934 was altered by at least twofold for the oncogene-transformed proteins quantified between the two experiments. (Fig. 3 A–C). cell lines relative to EV control, reflecting significant remodel- In large measure, MEKi reversed the effects of the oncogenes ing of the surfaceomes. In each of the six datasets, we observed and remarkably induced a more common state between all of at least twofold changes for 100 to 150 different surface pro- the cell lines, including the EV control. For example, in con- teins (Fig. 2A and SI Appendix, Fig. S5 A–F); these changes trast to the uninhibited datasets where 43% of proteins were were evenly split between up- and down-regulated sets, reflecting differentially regulated by more than twofold in the oncogene- bidirectional remodeling (SI Appendix, Fig. S6). Many of the dif- expressing cells, only 17% of the proteins (129 of 772) were ferentially expressed proteins overlapped, but each cell line had a altered by more than twofold in the presence of MEKi (Fig. 3A substantial number of uniquely differentially regulated proteins, and SI Appendix, Fig. S6A). These changes were mostly bidi- presumably resulting from slight differences in signaling between rectional, except for BRAF and EGFR cell lines where MEK each oncogene. Although it is well known that correlations inhibition has skewness >1 or <−1 (SI Appendix, Fig. S6B). between protein and RNA levels are not often strongly corre- Of the proteins detected, 18 proteins were commonly changed lated (6, 32, 33), we were prompted to determine whether the across all oncogenes, as opposed to 3 in the absence of MEK most common changes were observed in previous studies. Down- inhibition (Fig. 3A and SI Appendix, Fig. S5 G–M). The similar- regulation of BCAM and NRCAM transcription, in particular, ity can be seen by hierarchical clustering of the MEKi datasets was found in patient samples harboring the same oncogenic sig- showing common changes across all cell lines (Fig. 3B). The natures in a number of cancers types of epithelial origin (Fig. 2 B Pearson correlation between the six oncogenes and the untrans- and C). Using the 17 TCGA provisional dataset from The Cancer formed control were also higher, in general (SI Appendix, Fig. Genome Atlas (TCGA) with carcinoma (epithelial origin) anno- S7B). MEKi in KRASG12V and HER2 are still most closely cor- tation (34), activating oncogenic signature was defined as G12 or related. GSEA of the MEKi data indicated a general common Q61 mutation in KRAS, L858 or amplification of EGFR, V600E phenotypic reversal with down-regulation of membrane trans- mutation in BRAF, or amplification of HER2. Transcriptional porters, metabolism, and up-regulation of cell adhesion proteins up-regulation of MME, however, was not found in any of the consistent with a decrease in cancer-associated phenotypes such dataset searched, suggesting regulation at the translational level as cellular proliferation and metastasis (Fig. 3C and SI Appendix, or additional factors at play. Fig. S9 C and D). At a global level, there were greater similarities between G12V Integration of the oncogenic transformation and MEKi particular oncogenes. For example, cells harboring KRAS datasets show 20 protein targets symmetrically flip from being and HER2 clustered more closely together (cluster 1), and significantly up- to down-regulated or visa versa in at least three those containing BRAFV600E, AKTmyr, EGFRL858R, and MEKDD of the cell lines, suggesting that the expression of these proteins clustered together (cluster 2) as seen either in the upset plot is strongly dependent on the MAPK signaling pathway (Fig. 3D). (Fig. 2A) or a heatmap with hierarchical clustering (Fig. 2D). One such target, PODXL, appears to be stringently regulated The Pearson correlation coefficients were also higher within by the MAPK pathway. Using the same informatics approaches rather than across the two clusters (SI Appendix, Fig. S7A). One described above, transcription of PODXL was also found to of the striking findings was the up-regulation of HER2 expres- be strongly up-regulated in several cancer types of epithelial sion in the KRASG12V-transformed cells but not in cluster 2 origin (Fig. 3E). Additionally, 75 targets that were markedly transformed cells (SI Appendix, Fig. S8), which may help to up- or down-regulated revert to a median level of expression explain the stronger similarity in oncogene-induced surfaceomes upon treatment with MEKi in at least three cell lines (Fig. 3F).

7766 | www.pnas.org/cgi/doi/10.1073/pnas.1917947117 Leung et al. Downloaded by guest on September 30, 2021 Downloaded by guest on September 30, 2021 en tal. et Leung oncogene-transformed six the for proteins 2 E). (Fig. membrane the 2 identify specific cluster to pro- in sought of thus especially up-regulation We glycosylation, systematic in 38– show (35, involved data cancer teins GSEA for biomarker our a and as 40), known been Glycoproteome. long the has to sylation Changes Large Induce Oncogenes the of inhibition by blunted largely pathway. biolog- be MAPK common can alter which that processes, cause surfaceome ical of oncogenes the six outside to changes the pathways profound Overall, sug- circuitous independent). MME, by (MEKi as maintained MAPK such are MEKi, they upon gesting up-regulated targets further oncogene-induced are of handful that a were there Interestingly, at available also is GO identified (down- C5 set MySigDB negative gene using and each performed for red, was Heatmap GSEA in cluster. and oncogenes shown ratio, other peptide is the SILAC (up-regulation) in median by up-regulated size preranked are effect data were ( normalized Proteins expression collection. blue. and Positive set in Genomic cells. shown gene HER2. is KRAS-transformed size of and effect amplification normalized HER2- or regulated) BRAF, between as in clustering (E defined mutation ( show cells. was annotation. V600E signature KRAS-transformed terms origin) EGFR, oncogenic (epithelial and carcinoma Activating of HER2- with (gray). amplification dataset between genes down-regulated provisional or similarities these TCGA mutation and are in 17 L858 proteins the mutations bars, from (blue) no KRAS, obtained upward down-regulated to in were number and compared the mutation total (blue) (red) Q61 by The EGFR Up-regulated bar. or and graph. indicated each BRAF, G12 bar below HER2, are dots horizontal KRAS, solid (red) cell the in black by oncogene-transformed signature proteins the indicated oncogenic six by up-regulated are all indicated line graph, are log among cell groups as bar down-regulated each overlapping defined or vertical for specific up- proteins The the bars. regulated commonly In downward differentially were the of control. proteins by three indicated EV are only the (blue) and proteins to line, compared cell when each to lines unique are proteins regulated 2. Fig. EF DE AB lse lse 2 cluster 1 cluster 60 40 e Size Set 20

aydifferentially Many (A) themes. functional common have but detail in diverse are that surfaceome the in changes large cause oncogenes Proliferative KRAS 0

HER2 20 2 40

fl change) (fold BRAF AKT 60 Intersection Size EGFR KRAS HER2 BRAF of signiﬁcantly up- or down- MEK F AKT rtisivle ngyoyain(O0705 r onrgltdi h RSadHR lse bu) hl h aeproteins same the while (blue), cluster HER2 and KRAS the in down-regulated are (GO:0070085) glycosylation in involved Proteins ) EGFR regulated protein expression 30 20 10 10 20 30 40

MEK 0 ●

> SILAC enrichment ratio ● ● and 1 -2 -1 0 1 2 ● ● ● ● ● ● ● ● N ● P ● gyoyainmdﬁain on modiﬁcations -glycosylation ● ● value KRAS NRCAM BCAM, Down-regulated: ● ● ● ● ● ● ●

HER2 ● ● ● ● < BRAF ● ● prgltd MME Up-regulated: ● ● ● ● ● ● ● ● CMad(C and BCAM (B) 0.05. AKT ● ● ● ●

EGFR ● ● ● ● ● ●

MEK ● ● ● ● ● ● ● ● GO_REGULATION_OF_ANATOMICAL_STRUCTURE_MORPHOGENESIS GO_REGULATION_OF_CELL_MORPHOGENESIS GO_REGULATION_OF_CELL_MORPHOGENESIS_INVOLVED_IN_DIFFERENTIATION GO_POSITIVE_REGULATION_OF_NEURON_PROJECTION_DEVELOPMENT GO_REGULATION_OF_CELL_PROJECTION_ORGANIZATION GO_REGULATION_OF_AXONOGENESIS GO_REGULATION_OF_NEURON_PROJECTION_DEVELOPMENT GO_POSITIVE_REGULATION_OF_NEURON_DIFFERENTIATION GO_NEGATIVE_REGULATION_OF_CELLULAR_COMPONENT_ORGANIZATION GO_REGULATION_OF_CELL_DEVELOPMENT GO_NEGATIVE_REGULATION_OF_CELL_DEVELOPMENT GO_POSITIVE_REGULATION_OF_CELLULAR_COMPONENT_BIOGENESIS GO_GROWTH_FACTOR_BINDING GO_ANCHORED_COMPONENT_OF_MEMBRANE GO_PHOSPHATASE_ACTIVITY GO_DEPHOSPHORYLATION GO_SYNAPTIC_MEMBRANE GO_POSTSYNAPSE GO_CELL_PROJECTION_MEMBRANE GO_REGULATION_OF_METAL_ION_TRANSPORT GO_TRANSFERASE_ACTIVITY_TRANSFERRING_GLYCOSYL_GROUPS GO_TRANSFERASE_ACTIVITY_TRANSFERRING_HEXOSYL_GROUPS GO_NEGATIVE_REGULATION_OF_TRANSPORT GO_REGULATION_OF_BODY_FLUID_LEVELS GO_ENDOSOMAL_PART GO_BASEMENT_MEMBRANE GO_EXTRACELLULAR_MATRIX_COMPONENT GO_GLYCOPROTEIN_METABOLIC_PROCESS GO_CARBOHYDRATE_METABOLIC_PROCESS GO_GLYCOSYLATION ● ● ● ● ● ● ● ● o 0erce eest dnie yGE ftepoemc aae sn eeOntology Gene using dataset proteomics the of GSEA by identified sets gene enriched 30 Top ) ● ● ● ● ● ● omlzdefc size effect Normalized 2- 2 1 0 -1 -2 ● ● ● ● ● ● ● ● ● ● ● ● ● Glyco- ● ● ● ● ● ● ● ● ● ● ● ● RA r infiatydw-euae cosvroscrioawt activating with carcinoma various across down-regulated significantly are NRCAM ) ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● htwr o dnie cosec ftetrebiological three the of S11 ). Fig. each Appendix, (SI removed across were line glycopeptides cell identified each (44); for replicates engine not search were Byonic that the robust using afford assignments made Spectral to were (21). shown glycopeptides intact recently of was fragmentation and activation (43). vibrational and S10) dissociation Fig. radical-driven combines Appendix, fragmentation (SI (LC- AI-ETD AI-ETD spectrometry with mass coupled and tandem MS/MS) - chromatography liquid using the (41, processed respectively We glycans, 42). capturing complex-type for means and complementary high-mannose-type a provide using chromatogra- that liquid glycoproteomes (HILIC) interaction phy hydrophilic the and enriched ConA lectin we the control. EV coverage, the with maximal and For themselves among compare to lines cell evclSumu elCarcinoma Cell Squamous Cervical C ugSumu elCarcinoma Cell Squamous Lung ie eaoellrCarcinoma Hepatocellular Liver spaelAdenocarcinoma Esophageal spaelAdenocarcinoma Esophageal acetcAdenocarcinoma Pancreatic ooetlAdenocarcinoma Colorectal ooetlAdenocarcinoma Colorectal tmc Adenocarcinoma Stomach rsaeAdenocarcinoma Prostate ugAdenocarcinoma Lung Cholangiocarcinoma irrhlcutrn fsraem hne revealed changes surfaceome of clustering Hierarchal D) PNAS https://wellslab.ucsf.edu/oncogene N gyortoe nbooia triplicate biological in -glycoproteomes | pi ,2020 7, April 5101520 051015 log log | 2 o.117 vol. NCMRSEM+1) (NRCAM 2

KRAS RSEM+1) (BCAM HER2 BRAF

| AKT o 14 no. surfaceome. EGFR MEK DPY19L4 ST6GALNAC2 GCNT2 GALNT11 EXT2 TMEM5 FUT10 GXYLT2 ST6GAL1 GALNT3 ST3GAL1 FUT11 MUC16 B3GALT6 ST3GAL6 GCNT4 B3GALNT1 DAG1 MAGT1 GCNT1 GALNT1 EXT1 MAN2A2 POMT1 MGAT5 TUSC3 GNPTAB MAN2A1 B4GALT3 DPY19L3 STT3B MGAT4A POMK NAGPA NPC1 ST3GAL2 GALNT18 FKTN ST3GAL4 EDEM1 B3GALNT2 ALG9 B4GAT1 GALNT10 RPN1 POMT2 GXYLT1 STT3A RPN2 MGAT4B B3GNT5 B4GALT5 B3GNT2 A4GALT | 7767 SILAC enrichment ratio

-2 -1 0 1 2

BIOCHEMISTRY AB10

Intersection Size 5 upon MEK inhibition of signiﬁcantly up- or down- regulated protein expression 10

BRAF_MEKi

EV_MEKi

ATK_MEKi

EGFR_MEKi EV_MEKi AKT_MEKi

MEK_MEKi MEK_MEKi BRAF_MEKi HER2_MEKi KRAS_MEKi HER2_MEKi EGFR_MEKi

KRAS_MEKi SILAC enrichment ratio

-40 -20 0 20 40 -2 -1 0 1 2 Set size

GO_DIVALENT_INORGANIC_CATION_HOMEOSTASIS TMEM179B C GO_RECEPTOR_MEDIATED_ENDOCYTOSIS F LMBRD1 GO_REGULATION_OF_MULTI_ORGANISM_PROCESS OSTM1 GO_ENDOSOME ERAP1 GO_VACUOLE A4GALT GO_AMIDE_BINDING MCOLN1 LAMP1 GO_ANCHORED_COMPONENT_OF_MEMBRANE NPC1 GO_ENZYME_REGULATOR_ACTIVITY HGSNAT GO_RESPONSE_TO_ACID_CHEMICAL ACP2 GO_CELL_CELL_CONTACT_ZONE STIM1 GO_CELLULAR_RESPONSE_TO_NITROGEN_COMPOUND PTTG1IP CD164 GO_REGULATION_OF_CELL_CYCLE TTYH3 GO_ORGANIC_ANION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY CD63 GO_ANION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY APLP2 GO_GASTRULATION APP GO_FORMATION_OF_PRIMARY_GERM_LAYER JKAMP LAMB2 GO_ORGANIC_ACID_TRANSMEMBRANE_TRANSPORTER_ACTIVITY SLC2A1 GO_ANION_TRANSMEMBRANE_TRANSPORT HM13 GO_SECONDARY_ACTIVE_TRANSMEMBRANE_TRANSPORTER_ACTIVITY TMEM106B GO_SODIUM_ION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY TMEM9B GO_ORGANIC_ACID_TRANSMEMBRANE_TRANSPORT NOTCH2 GO_ORGANIC_ANION_TRANSPORT NCEH1 CPD GO_ANION_TRANSPORT TMEM259 GO_SODIUM_ION_TRANSPORT CLPTM1 GO_REGULATION_OF_VASCULATURE_DEVELOPMENT LAMB1 GO_MORPHOGENESIS_OF_A_BRANCHING_STRUCTURE SUN1 GO_BRANCHING_MORPHOGENESIS_OF_AN_EPITHELIAL_TUBE IMPAD1 TSPAN3 GO_SYMPORTER_ACTIVITY B3GNT2 GO_SOLUTE_CATION_SYMPORTER_ACTIVITY HSPG2 GO_AMINO_ACID_TRANSMEMBRANE_TRANSPORTER_ACTIVITY CHST3 TMED9 TMX3 MME 16 ADGRL3 -2 -1 0 1 2 E TSPAN13 Normalized effect size GPM6B CNTN3 EV_MEKi GGT5 AKT_MEKi MEK_MEKi 14 PTPRM BRAF_MEKi HER2_MEKi KRAS_MEKi EGFR_MEKi CDH2 ICAM1 UGT8 ERBB3 D 12 TMEM132A LAMC2 CD33 SLC6A14 SDC1 LAMA3 ITFG3 PCDHGC3 SLCO4A1 10 NUP210 NT5E MPPE1 LAMB3 CELSR2

(PODXL RSEM+1) ADCY3

SLC7A1 2 8 MST1R SLC6A15 ACVR1 PODXL log KIRREL STEAP4 SLC7A5 CPM 6 EFNB3 SLC26A2 UNC5B SUSD5 HLA-F SEMA4D PTPRF BCAM PTPRS TSPAN1 EPCAM TACSTD2 F3 MSLN ITGB6 GPC1 L1CAM l Carcinoma LMF2 SLC22A5 GALNT3 ST3GAL1 PCDH1

AKT DSE

MEK Thyroid Carcinoma i i i i i i BRAF HER2 KRAS EGFR t Invasive Carcinoma AKT MEK BRAF HER2 KRAS EGFR AKT_MEKi _MEK _MEK _MEK _MEK _MEK _MEK MEK_MEKi Breas Stomach Adenocarcinoma BRAF_MEKi HER2_MEKi KRAS_MEKi EGFR_MEKi Pancreatic Adenocarcinoma Esophageal Adenocarcinoma AKT MEK HER2 BRAF KRAS EGFR

Uterine Corpus Endometria

Fig. 3. Inhibition of MEK led to similar perturbations of the surfaceome regardless of oncogenic transformation. (A) The majority of differentially regulated surface proteins were either completely unique (highlighted in yellow) or completely common (bar 3) to all seven cell lines upon MEK inhibitor treatment compared to control treatment. 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 [FC]) > 1 and P value < 0.05. (B) Hierarchal clustering of surfaceome changes shows MEK inhibition treatment affected each cell line similarly. (C) Top 30 enriched gene sets identified by GSEA of the proteomics dataset using Gene Ontology terms show similarities between all cell lines, indicating that unique changes could be functionally redundant. 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 ratio, and GSEA was performed using MySigDB C5 GO gene set collection. Heatmap for each gene set identified is also available at https://wellslab.ucsf.edu/oncogene surfaceome.(D) MEK-dependent regulation

of protein expression induced by oncogenic transformation. Proteins shown were differentially regulated by oncogene (either log2(FC) > 1 or log2(FC) < −1 in oncogene vs. EV) and were then reversed (flipped log2(FC) < −1 and log2(FC) > 1 in MEK inhibition vs. respective cell line) in at least three cell lines. (E) PODXL is significantly up-regulated across various carcinoma with activating oncogenic signature in KRAS, HER2, BRAF, and EGFR (red) compared to no mutations in these genes (gray). Activating oncogenic signature was defined as G12 or Q61 mutation in KRAS, L858 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. (F) MEK-independent regulation of protein expression induced by oncogenic transformation. Proteins shown were differentially regulated by

oncogene (either log2(FC) > 1 or log2(FC) < −1 in onco vs. EV) and were then reverted to a median level but not reversed (ﬂipped log2(FC) < −1 and log2(FC) > 1 in MEK inhibition vs. respective cell line) in at least three cell lines.

Combining ConA and HILIC enrichments allowed for sam- described in Materials and Methods (Fig. 4 and SI Appendix, pling of different glycan classes, and the aggregated results Fig. S12). Of this total, 189 were redundant glycan–glycosite of intact N-glycoproteomic analyses identiﬁed a total of pairs, that is, glycoforms that resulted from miscleaved or dif- 2,648 unique N-glycopeptides that passed conservative ﬁltering ferentially oxidized peptides, leaving a total of 2,459 unique

7768 | www.pnas.org/cgi/doi/10.1073/pnas.1917947117 Leung et al. Downloaded by guest on September 30, 2021 Downloaded by guest on September 30, 2021 ann lcppie ahhvn h aesrcua yethat type structural same the having con- each phosphomannose 17 glycopeptides with only taining class found fucosylated We the structures. of different 226 42 and class gly- structures, sialylated different the complex/hybrid 54 of 314 with 210 structures, different including: 28 with glycans copeptides complex more had then destinations and S13 surface Fig. Golgi cell Appendix, or to granular, (SI ER lysosomal, either from their to transition on off split based they classes as structural state six maturation into categorized be can cans (45). UniPort in glycoyslated be to previously the predicted were or Of 324 known only fragmentation. glycosites, in-source detected of experimentally artifacts 785 not and biology the that protein indicated of glycoforms heterogeneity unique the yet heterogene- Similar significant glycosylation. in reflecting ity glycans, different 3.1 average, eiuswt ih(aet)adlw(el ubro nqegyasaehglgtd h otCtriu la,N1,hshg lcndvriydistance diversity glycan al. high et Leung has N818, glyan, C-terminus most residues. The highlighted. asparagine are other glycans all unique to of distance number similar (teal) has low and most and the (magenta) is (C high type with identified. glycan residues glycans High-mannose categorize protein (B) to in uniport. (E heterogeneity in used P15144). reported of are previously view types not additional glycan glycosites an common protein of of six percentage (Bottom ) of high macroheterogeneity and a total (Top) represents A chart identified. pie glycan A common lines. cell six all across 4. Fig. 767 remaining different 9 The of any structures. contain to paucimannose high-mannose-type trimmed found 8 were 1,636 210 of and identified man- glycans any We high containing 4B). glycopeptides (Fig. mature mannose sialylated least and and fucosylated the complex/hybrid, finally phosphomannose, from paucimannose, maturation to nose, of gradation a each average, on Thus, glycoproteins. 480 1.6 of had total glycoprotein 785 a to on map found glycoforms These 4A). (Fig. glycoforms 1,000 1,500 2,000 2,500 AB D

Unique Glycans 500 nttl eietfid12dfeetgya tutrs h gly- The structures. glycan different 142 identified we total, In 10 20 30 40 50 60 0 0 0246810 nqegyas lcpoen,gyoie,adgyoom identified glycoforms and glycosites, glycoproteins, glycans, Unique (A) lines. cell all from identified glycoproteome MCF10a the of overview global A eotdi UniProt in Reported apn lcndvriyo tutr fAPP(rti aaBn D4Y)rvassailrglto fgyoyainpten.Asparagine patterns. glycosylation of regulation spatial reveals 4FYR) ID Bank Data (Protein ANPEP of structure on diversity glycan Mapping ) Glycans 142 obndData Combined lcstso Protein on Glycosites Glycoproteins 480 N 4) h i lcnctgre represent categories glycan six The (46). ) lne lcsts n ahst a,on had, site each and glycosites, -linked Glycosites N 785 gyoyaini rvnlreyby largely driven is -glycosylation Glycoforms y=x 2,459 N gyoyain h rti ihtems eeoeosgyoomwsAPP(nPoK ceso no. accession (UniProtKB ANPEP was glycoform heterogenous most the with protein The -glycosylation. N cte lto nqegyasvru ubro lcstsfrec rti provides protein each for glycosites of number versus glycans unique of plot scatter A (D) -glycosylation. N E -glycopeptides N -glycosites Phosphomannose Complex/Hybrid Paucimannose ihMannose High Fucosylated Sialylated

H L

Type o i

g w

G G

l l y y

a n n

D D

i i

v v cdi o ifrnilyrgltda h lbllvlsonby shown level S14 global Fig. the Appendix, sialic (SI that at staining shown regulated lectin also SNA differentially have not we is acid, Since acid sialic A). S14 Fig. label Appendix, techniques (SI staining CSC surface lectin cell ConA with the of vali- on associated means glycans by have high-mannose especially of we expression and the Furthermore, surface dated find (50–52). cell to transformation the surprising oncogene at not high-mannose abundant that surface is seen is cell It have with others Golgi. as associated early proteins modifications or high-mannose ER these the pro- from in originating cessing structures paucimannose or mannose over high Thus, the (47–49). lysosomes of in 60% found typically proteins on are nrae eeoeet fgyasrltv oternme of number their to relative glycans significantly show of of proteins heterogeneity number some num- the however, increased and the has; protein between it given trend glycans a unique general on a identified glycosites is of There ber sites. five over of of gly- have site the number one of only 70% the have about Additionally, coproteins considerably; varies detected. protein per glycans glycosites, glycosites different Some but broad. 39 structure, was to glycan sites these position one as on only such glycans with of observed range were 45% the Approximately sites 4C). the (Fig. site of given any at structures glycan

e e

r r

s s

i i t t different of number the in heterogeneity signiﬁcant found We

y y Example P COOH NH2 N 75( glycoforms) (3 N735 glycoforms) (8 N681 glycoforms) (1 N625 glycoforms) (19 N265 glycoforms) (39 N234 glycoforms) (25 N128 88(5glycoforms) (25 N818 Identified Glycans gyoetdsietfidcnandls mature less contained identified -glycopeptides 54 28 42 N 1 9 8 24o mnppiaeN(NE) a up had (ANPEP), N aminopeptidase on -234 PNAS Glycopeptides h ayn ere fmicroheterogeneity of degrees varying The ) Identified | 1,636 314 210 226 210 17 pi ,2020 7, April N N818 gyoyain u bu 10% about but -glycosylation, 39Å 33.9 79Å 37.9 C | lcsts/Protein / Glycosites 75N681 N735 B). o.117 vol. 18Å 41.8 lcn Site / Glycans 58Å 45.8 48Å 34.8 N128 57Å 45.7 N234 N | N265 -glycosylation o 14 no. N625 | ≥5 4 3 2 1 7769

BIOCHEMISTRY total glycosites (Fig. 4D). The most extreme glycan diversity was A 400 B R2 observed on ANPEP, on which 59 unique glycans were identi- 1 EV ﬁed across eight glycosites (Fig. 4E). Interestingly, the glycosites 300 with higher glycan diversity mapped to speciﬁc regions on the KRAS three-dimensional structure of ANPEP. One face of the protein 200 containing a cluster of four asparagines (at positions 128, 234, HER2

265, and 818) had high glycan diversity ranging from 19 to 39 glycopeptides of all quantiﬁed 100 Intersection Size different glycan structures per glycosite, while the opposite face MEK 0.5

containing three clustered asparagines (at positions 625, 681, and 0 BRAF 735) had much lower diversity, ranging between 1 and 8 differ- HER2 AKT ent glycan structures per site. This suggests topological bias of KRAS EGFR EGFR glycosylation on the folded protein structure. MEK BRAF We next applied quantitative analysis to compare the different EV AKT 600 300 0 0 oncogene-transformed cell lines in terms of their glycoproteome Quantified landscapes and changes between them and the EV control. Glycopeptides EV KRASHER2 MEK BRAF EGFR AKT We observed hundreds of glycopeptides that were signiﬁcantly C 150 and differentially expressed (q < 0.05) upon oncogenic transformation relative to the EV control (SI Appendix, Fig. S15). 100 In general, the volcano plots were symmetric, reﬂecting bidi- 50

rectional changes, and the fold changes ranged from 50-fold expression down-regulated to 50-fold up-regulated, representing signiﬁcant Intersection Size 0

regulated glycopeptide 25

remodeling of the glycoproteome. Changes in glycosylation were of signiﬁcantly up- or down- HER2_EV

greater than changes in surface protein expression, which range AKT_EV

from twofold to eightfold (SI Appendix, Fig. S5). We quanti- EGFR_EV ﬁed about 600 glycopeptides in each dataset, of which two-thirds KRAS_EV are shared in all datasets (Fig. 5A). There was high quantita- MEK_EV tive reproducibility of the glycopeptide measurements based on BRAF_EV the close hierarchical clustering of the three biological repli- 100 0100 200 Differentially Expressed cates (Fig. 5B), tight clustering by principal component analysis, Glycopeptides 300 and low (<30%) median CV from the EV control cell line (SI D 250 Appendix, Fig. S16). MEKDD and BRAFV600E had the greatest 200 150 glycoproteome similarity, while EV was the farthest removed 100

from all of the oncogenes. Glycopeptides 50 0 The UpSet plot in Fig. 5C displays significant glycopeptide dif- High Mannose ferential expression that is shared and unique to each cell line. Paucimannose G12V MCF10A transformed with the KRAS oncogene resulted in Phosphomannose the largest set of uniquely changing glycopeptides; 154 of the 234 Sialyated differentially expressed glycopeptides in the KRASG12V cell line Complex/Hybrid were unique to KRASG12V transformation. Some of these were Fucosylated highly protein specific. For example, 28 of the 154 glycopeptides uniquely differentially expressed by KRASG12V were identified AKT BRAF EGFR MEK HER2 KRAS -15% 0 15% from ANPEP, and all were up-regulated upon oncogenic trans- Difference from Distribution of All Glycopeptides formation, as was the protein itself (SI Appendix, Fig. 17). Other glycopeptides from ANPEP were differentially expressed in dif- Fig. 5. Quantitative glycopeptide measurements across mutant cell lines. ferent sets of cell lines. In fact, 51 of 69 glycopeptides from (A) An UpSet plot shows glycopeptide identifications that are unique to or shared between datasets. (B) Pairwise Pearson correlations from all replicate ANPEP were differentially expressed in at least one cell line; 12 DD V600E ANPEP glycopeptides were significantly up-regulated in HER2, analyses illustrate clustering between MEK and BRAF glycoproteome. G12V (C) An UpSet plot displays the shared and unique glycopeptides that are sig- and 5 were shared between HER2 and KRAS . nificantly differentially expressed upon oncogenic transformation (q < 0.05) V600E L858R DD BRAF , EGFR , and MEK shared the most over- as assessed by linear models for microarray data (LIMMA) with Bonferroni- lap of significantly changing glycopeptides between any group adjusted P values. (D) A heatmap displays the differences in glycan type of three cell lines (Fig. 5C); 24 glycopeptides belonged to distribution for up- and down-regulated glycopeptides across cell lines. this intersection: 12 were overexpressed and 12 were underexpressed upon oncogenic transformation. Laminin subunit alpha- see whether general trends emerged. The heatmap in Fig. 5D 3 (LAMA3) and N-acetylglucosamine-6-sulfatase were most displays the differential glycome composition of glycopeptides represented in the overexpressed and underexpressed group, changing more than twofold upon oncogenic transformation respectively. Four glycopeptides from each protein were iden- compared to EV control. We, again, observe greatest sim- tified and significantly differentially expressed in these three V600E L858R DD cell lines. Six glycopeptides were significantly differentially ilarity between BRAF , EGFR , and MEK cell expressed across all six cell lines, three of which were identi- lines, which have an increased proportion of high-mannose glycans in up-regulated glycopeptides. In contrast, HER2 fied from galectin-3 binding protein (Gal-3BP), and all were G12V down-regulated glycopeptides modified with high-mannose gly- and KRAS expressed fewer up-regulated high-mannose- cans (SI Appendix, Fig. S18). To explore this dataset, a data modified glycopeptides and showed an increased proportion browser was made to view each individual glycopeptide identified of complex/hybrid-type glycopeptides. Further inspection re- (https://wellslab.ucsf.edu/oncogene surfaceome). vealed that nearly all of the up-regulated glycopeptides with We explored the glycan composition of differentially a complex/hybrid glycan from the cell lines harboring HER2 expressed glycopeptides to capture a broader view of differential (12 of 12) and KRASG12V (13 of 18) mapped to ANPEP. This glycosylation in the oncogene-transformed cell lines and to protein was also up-regulated on the KRASG12V surfaceome

7770 | www.pnas.org/cgi/doi/10.1073/pnas.1917947117 Leung et al. Downloaded by guest on September 30, 2021 Downloaded by guest on September 30, 2021 en tal. et Leung sms omnyse nbes acrptet,a 3 com- 13% at patients, cancer overexpression breast HER2 in epithe- oncogenes, seen breast commonly these most normal among is and, from cells, derived signaling lial is their reflecting MCF10A probably redundancy. sup- HER2, EGFR of whereas expression HER2, presses of derives KRAS expression and KRAS-induced HER2 from between similarity and the aggressive, of much less believe was 2 Cluster included adhesion. reduced HER2 and containing ation sur- 1, rates, Cluster growth and on glycans. overexpression based associated groups and two faceomes into clustered they and down-regulated and remodeling. surface up- cell bidirectional between reflecting divided proteins, evenly twofold, oncogene the than Each of 40% phenotype. about where transformed surfaceome, detected the cell in changes cancer large caused a character- morphologies of cell istic different factors growth somewhat of to absence produced the led and in oncogenes degrees, these varying to coarse- of growth, a each rapid at with them Transformation under- between level. to differences grain begin and to similarities the representatives, stand well-known chose we types, AKT Six the expression, by Induced Themes Oncogenes. Biological and Phenotypes and Common expressed proteins the them. decorate in that both glycans the surfaceome, profound the induced indepen- oncogenes in six that these changes of a find each to of we expression leading Overall, dent instability, contain background. genomic often other idiosyncratic cause or they more may transformed because that lesions already lines, genetic are cell this which immortalized picked onco- lines artificially of We cell myriad cancer senescence. a with over loss oncogene-induced cultured functional without be the to genes cells where allows MCF10A, p16INK4a line, of cell immortalized readily spontaneously epithelial be the breast to chose studies We permits oncogenes, (56–58). that prac- reproduced between materials a to comparison are access immune, isogenic renewable models host allowing culture reality of cell tical hetero- presence Nonetheless, variation, the metabolism. genetic and expression, context, of complexity cellular oncogene clearly the in geneity, is recapitulate vary is system not that This surfaceome does tumors fashion. the and autologous approximation the how cell an of determine a each in to with remodeled oncogenes transformed stably different line six cell epithelial talized observed with consistent these and that exclusivity. overall, simi- mutual find outcomes in functional we harmonize lar However, differences surfaceome (55). pathways oncogene-induced oncogenes signaling collateral these and between in loops feedback differences manifestation reported in significant previously terminal differences with find consistent a We patterns, expression is can- pathways. detailed surfaceome from signaling onco- these tumors The these of in (9). that exclusivity patients shown mutual cer exhibit have MAPK typically the studies neigh- genes through Genetic and in proliferation prevalent node. remodels drive six signaling surfaceome that by the model oncogenes how autologous boring cell study cell simplified we cancer a Here promote aberrant to (1). involves processes survival biological that multiple phenomenon in complex changes a is Oncogenesis Discussion in implicated been 54). previously (53, within has tumorigenesis heterogeneity and glycan data, of glycoproteomic degree the highest the displayed (6), hr eeipratdfeecsbtenteoncogenes, the between differences important were There immor- an from starting approach, reductionist a took We myr aemn ainsta ol aedfeetpheno- different have could that variants many have ) N EGFR gyortishdatrdepeso ee ymore by level expression altered had -glycoproteins EGFR lhuhtesxocgnsw tde HR over- (HER2 studied we oncogenes six the Although L858R L858R KRAS , BRAF , KRAS G12V V600E a otagesv nprolifer- in aggressive most was , G12V , , MEK BRAF DD V600E and , , MEK AKT DD myr and , We . eeso AC,spotn u rtoi eut htshow that results proteomic heightened our expresses col- supporting that activity LAMC2, shown MAPK of been high levels also with has cancer It model orectal (71). vivo up- adenocarcinoma in an lung be in epithelial– of invasion promote to and to [EMT] find shown transition been mesenchymal we previously and 2A mediat- has (Figs. LAMC2 in mutants types 3D). oncogenic roles of tumor majority important the various across play regulated in to metastasis known are ing PODXL, that LAMB3, dataset, MME, LAMA3, play our LAMC2, and which targets, Within five interactions. surface, identified cell–cell through cell we mediating the are of on functionalities role molecules the acquired adhesion these the in acquire of inva- changes cells to Many leading tumor (70). thus tissues, and sion surrounding cancer, the penetrate with to patients ability for death of Molecules. Adhesion in Alteration signaling. tumor-suppressive of removal the cells signify oncogene-transformed carcinoma all may hepatocellular in of expression model decreased shown a in and vivo in previously (69), arrest suppressor in been tumor has cycle a an BCAM be cell Lastly, to in inducing (68). progression phase through G2/M tumor cancer, the bladder halt of to a model as shown has UNC5B perhaps been Similarly, metastasis. cells, recently and across growth oncogene-transformed expression promote the to in means decrease of marked majority a Both the 67). show (66, proteins contexts these cancer of tumor numerous as in importance proteins their has suppressor emphasizing inactiva- particular, signaling, the EGFR in through of 2A PTPRS, metastasis tion (Figs. decreased and with BCAM PTPRF associated of and been expression UNC5B, The PTPRS, suppressors 3D). PTPRF, tumor involved other proteins as and surface such phosphatases of tyrosine down-regulation receptor general in a is data Suppressors. and Tumor Phosphatases Tyrosine Receptor of Down-Regulation General data. pathway proteomics our MAPK with mes- consistent upon is SLC7A1 decreases which that (65), level inhibition shown including expression been have types, RNA has cancer Others senger many (64). SLC7A1 across cancer (63). up-regulated colorectal cancer be colorectal to shown metastatic previously Height- in been has vasopressin. transporter seen hormone and this of prostaglandins transport- expression in as ened assists such that hormones family part transporter ing a anion SLCO4A1, organic of the up-regulation show of data Our growth cells. increased these and for glycolysis anaerobic cells, transporter- facilitate oncogene-transformed glucose would all as which in known up-regulated significantly division also is SLC2A1, and 1, that growth find We accelerated (62). deprivation promoting methionine toward thereby cells to cancer glycolysis, shifts preferentially sensitivity Effect Warburg extreme The (61). an exhibit KRAS-transformed that cells showing studies recent This pref- with cells. consistent HER2-transformed a is and dramatic as KRAS- shows both acts and in transporter SLC6A15 up-regulation acid 3D). amino (Fig. methionine STEAP4 erential inhibi- and down-regulation MEK SLC22A5 SLC7A1, and of upon SLC6A15, MF12/melanotransferrin, SLC2A1, reverse and of SLCO4A1, that up-regulation transport including proteins tion, solute to is in observed involved we changes Expression. oncogene-induced Transporter nounced in Alterations S20). Fig. Appendix, (SI slight EGFR a with and exclusivity KRAS, mutual and a BRAF indicates between 60) exclusivity (59, oncogenic mutual types strong of cancer func- all comparison oncogene across to silico occurrence reflecting mutational in relative patients, Further exclusivity cancer redundancies. Each mutual breast tional S19). in remarkable Fig. 1.7% others Appendix, shows AKT1, the (SI also for MEK1 5% these for EGFR, of 0.6% for and 2.8% BRAF, KRAS, for for 2% to pared nte motn hm on ihnour within found theme important Another PNAS | pi ,2020 7, April eatssi h edn cause leading the is Metastasis | n ftems pro- most the of One o.117 vol. | o 14 no. | 7771 and and

BIOCHEMISTRY reversal upon MEK inhibition (72). PODXL had increased is an α-1,3-focusyltransferase, and FUTs are critical for the expression in all six mutant cell lines, and has been implicated production of LewisX and Sialyl LewisX antigens which are in increasing the aggressiveness of breast and prostate cancer hallmarks of invasion (87). In fact, the most aggressive of our through the induction of both MAPK and PI3K signaling (73). oncogene cell lines (HER2 and KRAS) are significantly up- PODXL is also a glycoprotein with extensive mucin-type O- regulated in complex hybrid-type glycans for which these are glycosylation, the overexpression of which can lead to increased members, and especially noteworthy for ANPEP. EXT2 forms metastatic potential through increased cell cycle progression via a heterodimer with EXT1 in the Golgi functioning as a glyco- the PI3K and MAPK axes (74–76). MME, known as neprilysin, syl transferase involved in catalyzing the formation of heparin, was found up-regulated in all six oncogenic mutants compared to a substrate that contributes to structural stability of the extra- the EV control. While the function of MME has not been stud- cellular matrix, thereby mediating processes such as adhesion, ied in great detail, it is considered to be an adverse prognostic immune infiltration, and signaling (88). Unsurprisingly, alter- marker for patients with lung adenocarcinoma (77) and has been ations in heparan sulfate formation have been shown to have found to play an important role in the growth and progression emerging roles in oncogenesis, of which EXT2 is a primary facil- of colorectal cancers (78). MME was also found significantly up- itator (89). GALNT11 is a protein involved in the initiation of regulated in surfaceomics studies of isogenic cells expressing the mucin-type O-glycosylation, a well-known marker that is overex- tubular sclerosis gene associated with bladder cancer (79). Inter- pressed in cancer (90–92). MUC-1 is also a very important drug estingly, MME is up-regulated across all oncogenes in both the target for immunotherapy (93–96). Interestingly, a common sub- oncogene and MEKi datasets, suggesting that MME expression strate for this family of enzymes, PODXL, is also up-regulated is not regulated through the MAPK or PI3K axis. This height- across all oncogenic cell lines (see above), suggesting a possible ened expression of MME in all oncogenic contexts presents an mechanism by which increased GALNT11 promotes progrowth opportunity for future research into synthetic lethality studies phenotypes in these cell lines. GCTN2 is a glycosyltransferase with MME inhibition in combination with MEKi or other MAPK (97), and specifically implicated in the transition from na¨ıve to targets. germinal center B cell (98). ST6GalNAc2 is a sialyltransferase that catalyzes attachment of Immune Modulation. Another prominent cause of cancer pro- GalNAc to core glycans and is paradoxically up-regulated in all gression is the evasion of immune surveillance. This can be of the oncogene cell lines. A genome-wide short hairpin RNA achieved by overexpressing proteins that have a net immuno- screen in mice for genes that suppress metastasis identified and suppressive effect or by down-regulating proteins that increase validated ST6GalNAc2 as the strongest metastasis suppressor. immune activation. Here, we identified three differentially reg- ST6GalNAc2 is strongly down-regulated in estrogen receptor- ulated proteins, NT5E, HLA-F, and DSE, that play important negative breast cancer tumors. Silencing of ST6GalNAc2 pro- roles in immune functions (Fig. 3D). NT5E, which was up- motes binding of Galectin-3 and retention of tumor cells to sites regulated in all the proliferative oncogene cell lines, promotes of metastasis. Galectin-3 is a member of S-type lectins and a immunosuppression through the production of adenosine from known modulator of tumor progression (99) by enhancing aggre- AMP, which can decrease the capacity of natural killer cells gation of tumor cells during metastasis and preventing anoikis to produce immune-activating IFN molecules and prevents the (100–102). Galectin-3 binds to terminal fucose on glycans of clonal expansion of cytotoxic T cells in the surrounding tumor Gal-3BP which ST6GalNAc2 blocks via sialylation (102). We tissue (80). Conversely, HLA-F and DSE (also known as der- found that all glycopeptides from the eight glycosites Gal-3BP matan sulfate epimerase) were down-regulated in all oncogene- were down-regulated up to 50-fold in all cell lines (SI Appendix, expressing cell lines, and both play a role in immune system Fig. S18). activation and tumor rejection, through activation of NK cells Our glycoproteomic analyses show that protein N- or cytotoxic T cells, respectively, in the tumor microenviron- glycosylation is dramatically changed upon oncogenic trans- ment (81, 82). Both NT5E and HLA-F are down-regulated upon formation, and that distinct genetic drivers of oncogenesis MEKi (Fig. 3D). promote unique changes to the glycoproteome. The majority of differentially expressed glycopeptides were unique to individual V600E Down-Regulation by Shedding. Proteolytic cleavage of proteins cell lines. We observed greatest similarity between BRAF , at the cell surface leads to ectodomain shedding and the exis- EGFRL858R, and MEKDD, which has been consistent through- tence of neo N termini. The loss of ectodomains would lead out different analyses of these cell lines (Fig. 5B). There to decreased peptide detection by LC-MS/MS. We identified were significant differences between the oncogene cluster 1 four surface proteins reduced in detection, MSLN, TACSTD2, (KRASG12V/HER2) and cluster 2 (EGFRL858R/BRAFV600E/ NRCAM, and GPC1, that are known to undergo proteolysis MEKDD/AKTmyr). Specifically, we found differential increase in to enhance the growth and metastasis of cancer (83–85). In complex hybrid glycans and decrease in high mannose in cluster particular, NRCAM, which had lower surface levels in all six 1 and just the opposite for cluster 2. oncogenic mutants, is a cell–cell adhesion molecule; it is known There is abundant evidence to suggest that high-mannose-type to be shed by proteolysis, and the shed form stimulates cell pro- glycans are present at the cell surface and, furthermore, that liferation via the AKT pathway (86). Perhaps unsurprisingly, cancerous cells display increased abundance of high-mannose NRCAM did not exhibit a renormalization of expression levels glycans at their cell surface (52, 103). A similar observation after MEK inhibition, due to its exclusive function through the was reported in the glycomic comparison of transformed versus AKT pathway. human embryonic stem cells (hESCs), where high-mannose glycans were observed at significantly higher abundance on plasma Changes in Glycosylation Machinery and Protein N-glycosylation. membranes of hESCs (50). Together, these observations help to Alterations in glycosylation are common features of cancer explain the similarities between cancerous cells and hESCs, such cells (35) which can result from a variety of factors, including as the regulation of tumor suppressor genes and the ability to changes in expression of glycosyltransferases, availability of sugar self-renew (104). This is consistent with our studies, although nucleotide substrates, alteration in expression of substrate pro- we cannot exclusively rule out that some of the high-mannose teins, or changes to the tertiary structure of the protein substrate glycans we observe are coming from proteins in route to the that disrupt transfer of the glycan. We find that glycosyl transmembrane. ferases FUT10, EXT2, GALNT11, GCTN2, and ST6GALNAC2 Our data suggest glycosylation is quite heterogeneous, possibly are highly up-regulated across all oncogenic cell lines. FUT10 reflecting incomplete maturation. The most stunning example in

7772 | www.pnas.org/cgi/doi/10.1073/pnas.1917947117 Leung et al. Downloaded by guest on September 30, 2021 Downloaded by guest on September 30, 2021 3 .Hkmr,Tmrmlgac endb bratgyoyainadsph- and glycosylation aberrant by defined malignancy Tumor branched Hakomori, 1-6 Beta S. Dennis, 13. W. J. Demetrio, M. Auger, M. Sagman, U. that Fernandes, Evidence B. Varmus, H. 12. Lee-Lin, Q. S. Zejnullahu, K. Lockwood, W. W. Unni, M. A. 11. senescence Oncogene-induced Bergo, O. M. Karlsson, C. Liu, M. Sayin, I. V. Cisowski, J. 10. 4 .E ua,S .Cna,C .Broz,Gyoay niern eel a reveals engineering Glycocalyx Bertozzi, R. C. Canham, M. S. Hudak, E. J. 14. ie oei nignss(4,udrcr t motnein importance its underscore (54), angiogenesis KRAS iden- in previously ANPEP’s role in with tified combined way data, These one pathway. represents our dramati- data in which not expression glycoproteomic ANPEP was and inhibition. expression surfaceomic MEK its in by influenced and up-regulated cally most analyses, was surfaceomic ANPEP in 5D). also (Fig. and HER2 ANPEP lines gly- in up-regulated S13). complex/hybrid were within that Fig. copeptides representation through Appendix, greatest progression (SI the steady-state showed pathway observed its we secretion of maturation, of the glycan representation N234 When of close site structures. order a glycan in was different arranged example are 29 across extreme these found level most we protein where The an ANPEP, the lines. ANPEP, at cell for up-regulated was most also glycosylation peptidase in heterogeneity amino of data our en tal. et Leung hallmarks simplified the of a to many in recapitulate lines we Even cell model, changes. isogenic cell oncogene-induced autologous in and These the cells. conducted growth cancer isolate deliberately cell of were properties increased well-known studies with are sup- consistent that tumor invasion suppres- is and proteins immune which adhesion pressors, and of down-regulation involved glycosylation, and proteins sors transport, We surface metabolite together. of can in not up-regulation tumors although observe common oncogenes, commonly that different observations these with express consistent expression. is cellular sug- specific This themes the and of biological redundancy protein common functional the gesting observe both we at the oncogenes level, of given glycopeptide many to While specific glycoproteome. are and changes remod- surfaceome autologous the large-cell in eling cause neighbor- six oncogenes how proliferative of study ing comparative large-scale a provide We Conclusions its patterns. given heterogeneous cells, in and metabolism diverse glycan highly of biomarker sensitive very a .D aaa,R .Wibr,Hlmrso acr h etgeneration. next The cancer: of Hallmarks Weinberg, A. R. Hanahan, D. 1. .Cne eoeAlsRsac ewr,Cmrhniemlclrpoln flung of profiling molecular Comprehensive Network, Research Atlas Genome Cancer 9. Ying H. 8. Ye X. 7. Suc- Martinko antibodies: Therapeutic J. A. Baty, 6. D. Weiss, E. Regenmortel, Van M. ’high-hanging Chames, the of P. Pursuit drugs: 5. antibody generation Next Lazar, A. from G. Carter, proteins J. membrane P. integral of 4. analysis Genome-wide Heijne, von G. Wallin, E. 3. Gonzalez R. 2. lgschrdsa akro uo rgeso nhmnbes n colon and breast human metabolism. ingo(glyco)lipid in progression tumor of marker neoplasia. a EGFR as and KRAS oligosaccharides oncogenic of exclusivity adenocarcinoma. mutual lung in the mutations underlies lethality synthetic BRAF. and KRAS oncogenic of (2015). nature 1328–1333 exclusive mutual the underlies adenocarcinoma. metabolism. glucose anabolic surface. cell proteins. (2016). KRasG12V the of signature cell-surface molecular distinct essential and upregulated (2018). to future. bodies the for hopes and (2009). limitations cesses, Discov. Drug Rev. fruit.’Nat. organisms. eukaryotic and archaean, eubacterial, (2010). pluripotency. cell stem human embryonic (2011). 674 ilcbsdmcaimfrN elimmunoevasion. cell NK (2014). for mechanism Siglec-based oprtv rtoiso oe C1AKaG2 elln eel a reveals line cell MCF10A-KRasG12V model a of proteomics Comparative al., et KRAS G12V noei rsmitispnrai uostruhrglto of regulation through tumors pancreatic maintains Kras Oncogenic al., et ac Res. Canc. pstv uos NE lcslto a ev as serve may glycosylation ANPEP tumors. -positive cenn h amla xrclua rtoefrrgltr of regulators for proteome extracellular mammalian the Screening al., et G12V agtn A rvnhmncne el ihanti- with cells cancer human driven RAS Targeting al. , et Nature 1–2 (1991). 718–723 51, iegsfo te ebr fteMAPK the of members other from diverges 4–5 (2014). 543–550 511, 9–2 (2018). 197–223 17, ac Res. Canc. Cell 5–7 (2012). 656–670 149, eLife 3951 (1996). 5309–5318 56, –3(2015). 1–23 4, rc al cd c.U.S.A. Sci. Acad. Natl. Proc. rti Sci. Protein r .Pharmacol. J. Br. a.Ce.Biol. Chem. Nat. Oncotarget 0913 (1998). 1029–1038 7, KRAS eLife 3552–3557 107, 86948–86971 7, KRAS Oncogene 220–233 157, Cell G12V e31098 7, 69–75 10, 646– 144, G12V cell 35, 9 .K aaipa,C .Broz,Ceia glycoproteomics. Chemical Bertozzi, R. C. Palaniappan, immunity. K. in K. acids sialic 19. of roles Multifarious Gagneux, P. Varki, A. 18. a as editing glycocalyx Kannagi Precision R. Bertozzi, 17. R. C. Vukojicic, P. Woods, C. E. Xiao, H. anti- large 16. induce vaccines cancer Whole-cell Gildersleeve, C. J. Schrump, S. D. Xia, L. 15. 8 .D Soule D. H. 28. Qu Y. Cδ 27. kinase Protein Reyland, Martins M. E. M. M. Ohm, 26. M. A. Carter, J. C. Allen-Petersen, L. B. 25. Wollscheid B. 24. Bausch-Fluck D. high-throughput het- between balance 23. site-specific A Glycoproteomics: Capturing Heck, R. J. Coon, A. Franc, J. V. Yang, J. Y. Westphall, 22. S. M. Hebert, S. A. Riley, M. N. 21. Liu Q. M. 20. atb h itcnlg riigGatT2G084.NMR gratefully K00CA21245403. N.M.R. Grant GM008349. NIH Cen- T32 from in National Grant support supported Training acknowledges was (The Biotechnology G.M.W. thank GM108538 the Systems). to by Complex Grant Biology wishes of part P41 Biology Chemical J.J.C. Quantitative from funding. for and funding ter for Chemistry generous UCSF for to at NIH GM064337 indebted T32 post- is Grant Celgene for discussions. Training L.L.K. Research and Health R35GM122451 helpful funding. of Grant Institutes and doctoral NIH Canadian from thanks instrumentation K.K.L. funding Lodge for Corporation. for Jean constructs grateful and Wisconsin lenti is Shishkova, the of J.A.W. Evgenia of Westphall, University some Michael for at and (UCSF) lines, Francisco cell San and California, of versity ACKNOWLEDGMENTS. meth- and S1–25. SILAC-based Datasets materials in Detailed using included are quantification. line ods label-free cell was line using respective cell quantified surfaceome oncogene-transformed each each and of d, in Glycoproteome 3 quantification. compared for MEK control were nM sulfoxide 100 changes inhibition dimethyl with treated or For was PD032590 quantification. line inhibitor SILAC-based cell oncogene-transformed using was each control unless study, line EV cell protocols oncogene-transformed to established each to compared of according Surfaceome cultured stated. were otherwise cells MCF10A All Methods and Materials PDF. single a and S1–S20, Figs. Appendix. SI eea grsaeas vial nadt rwe ( https:// browser data a in (proteomecentral. available repository also of partner wellslab.ucsf.edu/oncogene are illustrations figures Consortium Interactive PRIDE several PXD017039). the (identifier accessible via ProteomeXchange proteomexchange.org) to Archival. Data settings. tumor complex more in follow among pursue to differences to tools opportunities antibody and provides provides and similarities oncogenes work neighboring the the the believe into redun- We insights functionally surfaceome. important but the to complex changes by dant driven cells transformed of (2016). immunotherapy. cancer for strategy (2016). iecn n uo yoi:Cusi h non erhfrnwtmrmarkers. tumor Sci. new for search ongoing the in Sci. Clues Canc. hypoxia: tumor and silencing glycoproteins. and carbohydrates to responses body aie ua rateihla elln,MCF-10. line, cell epithelial breast (1990). human talized cells. epithelial map. interaction chemical-genetic correlates cancer. negatively breast and human in tumorigenesis prognosis gland with mammary ErbB2-driven for glycoproteins. required surface cell N-linked (2009). of cation One analysis. in-depth and analysis. N-glycoproteome (2019). large-scale with erogeneity identification. glycopeptide Commun. intact for Nat. spectrometry mass one-step and control quality (2016). 14306 63 (2012). 16–36 1253, 0234(2015). e0121314 10, vlaino C1Aa eibemdlfrnra ua mammary human normal for model reliable a as MCF10A of Evaluation al., et 8–9 (2010). 586–593 101, Gyo20ealspeiinNgyortoiswt comprehensive with N-glycoproteomics precision enables 2.0 pGlyco al., et lee xrsino lcngnsi acr nue yepigenetic by induced cancers in genes glycan of expression Altered al., et slto n hrceiaino pnaeul immor- spontaneously a of characterization and Isolation al., et 3 (2017). 438 8, ikn uo uain odu epne i quantitative a via responses drug to mutations tumor Linking al., et IApni,Splmna aeil n Methods, and Materials Supplemental Appendix, SI LSOne PLoS assetoercietfiainadrltv quantifi- relative and identification Mass-spectrometric al., et assetoercdrvdcl ufc rti Atlas. protein surface cell spectrometric-derived mass A al., et l rtoisdtsthsbe deposited been has dataset proteomics All IAppendix SI ecito fDtst S1 Datasets of Description rnsBiotechnol. Trends etakPoesrSua adoaha tUni- at Bandyopadhyay Sourav Professor thank We PNAS 0325(2015). e0131285 10, | n upeetr aaaeaalbeas available are data supplementary and , ac Discov. Canc. surfaceome). pi ,2020 7, April rc al cd c.U.S.A. Sci. Acad. Natl. Proc. Oncogene 9–0 (2017). 598–609 35, 5–6 (2015). 154–167 5, 3611 (2014). 1306–1315 33, | a.Biotechnol. Nat. elCe.Biol. Chem. Cell o.117 vol. ac Res. Canc. to a.Commun. Nat. S25 hm Rev. Chem. | sicue as included is 10304–10309 113, o 14 no. n.N .Acad. Y. N. Ann. 6075–6086 50, 1515–1525 23, 378–386 27, 14277– 116, 1311 10, | 7773 PLoS is

BIOCHEMISTRY 29. R. Apweiler, H. Hermjakob, N. Sharon, On the frequency of protein glycosylation, as 61. G. De Sanctis, M. Spinelli, M. Vanoni, E. Sacco, K-Ras activation induces differential deduced from analysis of the SWISS-PROT database. Biochim. Biophys. Acta 1473, 4–8 sensitivity to sulfur amino acid limitation and deprivation and to oxidative and anti- (1999). oxidative stress in mouse fibroblasts. PLoS One 11, e0163790 (2016). 30. D. Bausch-Fluck et al., The in silico human surfaceome. Proc. Natl. Acad. Sci. U.S.A. 62. M. V. Liberti, J. W. Locasale, The Warburg Effect: How does it benefit cancer 115, E10988–E10997 (2018). cells?Trends Biochem. Sci. 41, 211–218 (2016). 31. K. K. Leung et al., Multiomics of azacitidine-treated AML cells reveals variable and 63. V. Buxhofer-Ausch et al., Tumor-specific expression of organic anion-transporting convergent targets that remodel the cell-surface proteome. Proc. Natl. Acad. Sci. polypeptides: Transporters as novel targets for cancer therapy. J. Drug Delivery 2013, U.S.A. 116, 695–700 (2019). 863539 (2013). 32. E. Lundberg et al., Defining the transcriptome and proteome in three functionally 64. Y. Lu et al., Overexpression of arginine transporter CAT-1 is associated with accumu- different human cell lines. Mol. Syst. Biol. 6, 450 (2010). lation of L-arginine and cell growth in human colorectal cancer tissue. PLoS One 8, 33. B. Schwanhausser¨ et al., Global quantification of mammalian gene expression control. e73866 (2013). Nature 473, 337–342 (2011). 65. M. D. Calder, P. H. Watson, A. J. Watson, Culture medium, gas atmosphere and 34. Cancer Genome Atlas Research Network et al., The Cancer Genome Atlas pan-cancer MAPK inhibition affect regulation of RNA-binding protein targets during mouse analysis project. Nat. Genet. 45, 1113–1120 (2013). preimplantation development. Reproduction 142, 689–698 (2011). 35. S. S. Pinho, C. A. Reis, Glycosylation in cancer: Mechanisms and clinical implications. 66. T. B. Davis et al., PTPRS regulates colorectal cancer RAS pathway activity by Nat. Rev. Canc. 15, 540–555 (2015). inactivating Erk and preventing its nuclear translocation. Sci. Rep. 8, 9296 (2018). 36. A. Varki, R. Kannagi, B. Toole, P. Stanley, “Glycosylation changes in cancer” in Essen- 67. X. Tian, C. Yang, L. Yang, Q. Sun, N. Liu, PTPRF as a novel tumor suppressor through tials of Glycobiology, A. Varki et al., Eds. (Cold Spring Harbor Laboratory Press, 2015), deactivation of ERK1/2 signaling in gastric adenocarcinoma. OncoTargets Ther. 11, pp. 597–609. 7795–7803 (2018). 37. L. Mockl¨ et al., Quantitative super-resolution microscopy of the mammalian 68. C. Kong et al., Overexpression of UNC5B in bladder cancer cells inhibits proliferation glycocalyx. Dev. Cell 50, 57–72 (2019). and reduces the volume of transplantation tumors in nude mice. BMC Canc. 16, 892 38. B. Adamczyk, T. Tharmalingam, P. M. Rudd, Glycans as cancer biomarkers. Biochim. (2016). Biophys. Acta 1820, 1347–1353 (2012). 69. H. Akiyama et al., The FBI1/Akirin2 target gene, BCAM, acts as a suppressive 39. Y. Mechref, Y. Hu, A. Garcia, A. Hussein, Identifying cancer biomark- oncogene. PLoS One 8, e78716 (2013). ers by mass spectrometry-based glycomics. Electrophoresis 33, 1755–1767 70. T. A. Martin, L. Ye, A. J. Sanders, J. Lane, W. G. Jiang, “Cancer invasion and metasta- (2012). sis: Molecular and cellular perspective” in Metastatic Cancer: Clinical and Biological 40. R. Peracaula, S. Barrabes,´ A. Sarrats, P. M. Rudd, R. de Llorens, Altered gly- Perspectives, R Jandial, Ed. (Landes Bioscience, 2013). cosylation in tumours focused to cancer diagnosis. Dis. Markers 25, 207–218 71. Y. W. Moon et al., LAMC2 enhances the metastatic potential of lung adenocarcinoma. (2008). Cell Death Differ. 22, 1341–1352 (2015). 41. S. M. Totten, C. L. Feasley, A. Bermudez, S. J. Pitteri, Parallel comparison of 72. C. Blaj et al., Oncogenic effects of high MAPK activity in colorectal cancer mark N-linked glycopeptide enrichment techniques reveals extensive glycoproteomic progenitor cells and persist irrespective of RAS mutations. Canc. Res. 77, 1763–1774 analysis of plasma enabled by SAX-ERLIC. J. Proteome Res. 16, 1249–1260 (2017). (2017). 73. S. Sizemore, M. Cicek, N. Sizemore, K. P. Ng, G. Casey, Podocalyxin increases the 42. C. Zhang et al., Evaluation of different N-glycopeptide enrichment methods for aggressive phenotype of breast and prostate cancer cells in vitro through its N-glycosylation sites mapping in mouse brain. J. Proteome Res. 15, 2960–2968 interaction with ezrin. Canc. Res. 67, 6183–6191 (2007). (2016). 74. J. S. Nielsen, K. M. McNagny, The role of podocalyxin in health and disease. J. Am. 43. N. M. Riley, M. S. Westphall, A. S. Hebert, J. J. Coon, Implementation of activated ion Soc. Nephrol. 20, 1669–1676 (2009). electron transfer dissociation on a quadrupole-orbitrap-linear ion trap hybrid mass 75. M. J. Paszek et al., The cancer glycocalyx mechanically primes integrin-mediated spectrometer. Anal. Chem. 89, 6358–6366 (2017). growth and survival. Nature 511, 319–325 (2014). 44. M. Bern, Y. J. Kil, C. Becker, Byonic: Advanced peptide and protein identification 76. E. C. Woods et al., A bulky glycocalyx fosters metastasis formation by promoting G1 software.Curr. Protoc. Bioinformatics 2012, 1–22 (2012). cell cycle progression. eLife 6, e25752 (2017). 45. UniProt Consortium, The universal protein resource (UniProt) in 2010. Nucleic Acids 77. K. Leithner et al., Hypoxia increases membrane metallo-endopeptidase expression in Res. 38, 142–148 (2010). a novel lung cancer ex vivo model—Role of tumor stroma cells. BMC Canc. 14, 40 46. K. J. Yarema, C. R. Bertozzi, Characterizing glycosylation pathways. Genome Biol. 2, (2014). reviews0004.1 (2001). 78. T. J. Jang, J. B. Park, J. I. Lee, The expression of CD10 and CD15 is progressively 47. S. Kornfeld, I. Mellman, The biogenesis of lysosomes. Annu. Rev. Cell Biol. 5, 483–525 increased during colorectal cancer development. Korean J. Pathol. 47, 340–347 (2013). (1989). 79. J. Wei, et al., Profiling the surfaceome identifies therapeutic targets for cells with 48. W. M. Rohn, Y. Rouille,´ S. Waguri, B. Hoflack, Bi-directional trafficking between the hyperactive mTORC1 signaling. Mol. Cell. Proteomics 19, 297–307 (2020). trans-Golgi network and the endosomal/lysosomal system. J. Cell Sci. 113, 2093–2101 80. Zw. Gao, K. Dong, H.-z. Zhang, The roles of CD73 in cancer. BioMed Res. Int. 2014, (2000). 460654 (2014). 49. Y. Rouille,´ W. Rohn, B. Hoflack, Targeting of lysosomal proteins. Semin. Cell Dev. Biol. 81. C. L. Dulberger et al., Human leukocyte antigen F presents peptides and regu- 11, 165–171 (2000). lates immunity through interactions with NK cell receptors. Immunity 46, 1018–1029 50. H. J. An et al., Extensive determination of glycan heterogeneity reveals (2017). an unusual abundance of high mannose glycans in enriched plasma mem- 82. W. C. Liao et al., DSE regulates the malignant characters of hepatocellular carcinoma branes of human embryonic stem cells. Mol. Cell. Proteomics 11, M111.010660 cells by modulating CCL5/CCR1 axis. Am. J. Cancer Res. 9, 347–362 (2019). (2012). 83. R. Kawahara et al., Mass spectrometry-based proteomics revealed Glypican-1 as a 51. C. I. A. Balog et al., N-glycosylation of colorectal cancer tissues: A liquid chromatog- novel ADAM17 substrate. J. Proteomics 151, 53–65 (2017). raphy and mass spectrometry-based investigation. Mol. Cell. Proteomics 11, 571–585 84. A. Morello, M. Sadelain, P. S. Adusumilli, Mesothelin-targeted CARs: Driving T cells to (2012). solid tumors. Canc. Discov. 6, 133–146 (2016). 52. S. Holst et al., N-glycosylation profiling of colorectal cancer cell lines reveals 85. T. Stoyanova et al., Regulated proteolysis of Trop2 drives epithelial hyperplasia and association of fucosylation with differentiation and caudal type home- stem cell self-renewal via β-catenin signaling. Genes Dev. 26, 2271–2285 (2012). box 1 (CDX1)/Villin mRNA expression. Mol. Cell. Proteomics 15, 124–140 86. M. Conacci-Sorrell et al., The shed ectodomain of Nr-CAM stimulates cell proliferation (2016). and motility, and confers cell transformation. Canc. Res. 65, 11605–11612 (2005). 53. X. Dong et al., Modification of the amino terminus of a class II epitope confers resis- 87. A. Blanas, N. M. Sahasrabudhe, E. Rodr´ıguez, Y. van Kooyk, S. J. van Vliet, Fucosylated tance to degradation by CD13 on dendritic cells and enhances presentation to T cells. antigens in cancer: An alliance toward tumor progression, metastasis, and resistance J. Immunol. 164, 129–135 (2000). to chemotherapy. Front. Oncol. 8, 39 (2018). 54. R. Pasqualini et al., Aminopeptidase N is a receptor for tumor-homing 88. A. Nagarajan, P. Malvi, N. Wajapeyee, Heparan sulfate and heparan sulfate peptides and a target for inhibiting angiogenesis. Canc. Res. 60, 722–727 proteoglycans in cancer initiation and progression. Front. Endocrinol. 9, 483 (2000). (2018). 55. A. V. Vaseva et al., KRAS suppression-induced degradation of MYC is antag- 89. E. H. Knelson, J. C. Nee, G. C. Blobe, Heparan sulfate signaling in cancer. Trends onized by a MEK5-ERK5 compensatory mechanism. Canc. Cell 34, 807–822 Biochem. Sci. 39, 277–288 (2014). (2018). 90. R. A. R. Villacis et al., Contribution of rare germline copy number variations and com- 56. S. Domcke, R. Sinha, D. A. Levine, C. Sander, N. Schultz, Evaluating cell lines mon susceptibility loci in Lynch syndrome patients negative for mutations in the as tumour models by comparison of genomic profiles. Nat. Commun. 4, 2126 mismatch repair genes. Int. J. Canc. 138, 1928–1935 (2016). (2013). 91. M. G. Libisch et al., GALNT11 as a new molecular marker in chronic lymphocytic 57. S. Rockwell, In vivo-in vitro tumour cell lines: Characteristics and limitations as models leukemia. Gene 533, 270–279 (2014). for human cancer. Br. J. Canc. Suppl. 4, 118–122 (1980). 92. M. R. M. Hussain, D. C. Hoessli, M. Fang, N-acetylgalactosaminyltransferases in cancer. 58. J. L. Wilding, W. F. Bodmer, Cancer cell lines for drug discovery and development. Oncotarget 7, 54067–54081 (2016). Canc. Res. 74, 2377–2384 (2014). 93. S. Bafna, S. Kaur, S. K. Batra, Membrane-bound mucins: The mechanistic basis for 59. E. Cerami et al., The cBio cancer genomics portal: An open platform for alterations in the growth and survival of cancer cells. Oncogene 29, 2893–2904 exploring multidimensional cancer genomics data. Canc. Discov. 2, 401–404 (2010). (2012). 94. A. D. Posey et al., Engineered CAR T cells targeting the cancer-associated tn- 60. J. Gao et al., Integrative analysis of complex cancer genomics and clinical profiles glycoform of the membrane mucin MUC1 control adenocarcinoma. Immunity 44, using the cBioPortal. Sci. Signal. 6, pl1 (2013). 1444–1454 (2016).

7774 | www.pnas.org/cgi/doi/10.1073/pnas.1917947117 Leung et al. Downloaded by guest on September 30, 2021 Downloaded by guest on September 30, 2021 8 .J ee,A .Lne,C rnl .Ntck,Bcl ilc—eso inln and signaling on siglecs—News cell developmental B Nitschke, L. the Brandl, C. of Linder, T. A. Expression Meyer, J. Fukuda, S. 98. M. Mattei, G. M. Bierhuizen, F. M. 97. 9 .T i,G .Rbnvc,Glcisa ouaoso uorprogression. tumour of modulators as Galectins Rabinovich, A. G. Liu, T. F. 99. cancer: in Vassilaros immunotherapy S. mucin-1 on 96. Update Mitchell, P. Loveland, B. Rivalland, G. 95. en tal. et Leung nie yacoe ua DAecdn ebro beta-1,6-N- a of member a encoding binding. ligand cDNA with interplay its mannan-MUC1. human oxidized cloned a using family. gene by patients acetylglucosaminyltransferase antigen cancer I breast II stage in Immunotherapy study apy Canc. perspective. clinical A 94 (2005). 29–41 5, pt 5ya lnclflo-po io hs I immunother- III phase pilot a of follow-up clinical 15-year to Up al., et 1718 (2013). 1177–1182 5, xetOi.Bo.Ther. Biol. Opin. Expert rn.Immunol. Front. ee Dev. Genes 7318 (2015). 1773–1787 15, 80(2018). 2820 9, 6–7 (1993). 468–478 7, a.Rev. Nat. 0.S Hua, S. 103. Lin W. T. 102. Grassadonia A. 101. 0.M hcltn omlse el n acrse el:Smlraddifferent. and Similar cells: stem cancer and cells stem Normal Shackleton, M. 104. Lafert S. Ulmer, A. T. Nagle, B. R. Bair, L. E. 100. ac Biol. Canc. proﬁling. N-glycan membrane metastasis. and aggregation (2015). cell cancer metastasis. expression. (2006). promatrilysin 293 induces and cancer prostate in expressed is ifrnito fcne eloii n oeua utp yplasma by subtype molecular and origin cell cancer of Differentiation al., et aetn3bnigpoenadglci- neato nbreast in interaction galectin-1 and protein binding Galectin-3 al., et 59 (2010). 85–92 20, lccn.J. Glycoconj. 0 Mc2B)adglcisi uo rgeso and progression tumor in galectins and BP) (Mac-2 90K al., et 5–5 (2002). 551–556 19, PNAS .Poem Res. Proteome J. | pi ,2020 7, April ,G .Bwe,9KMc2bnigprotein binding 90K/Mac-2 Bowden, T. G. e, ´ .A.Ce.Soc. Chem. Am. J. 6–6 (2014). 961–968 13, | o.117 vol. | 9685–9693 137, o 14 no. Prostate 283– 66, | Semin. 7775

BIOCHEMISTRY