Reciprocal feedback regulation of ST3GAL1 and GFRA1 signaling in breast cancer cells

Accepted Manuscript Reciprocal feedback regulation of ST3GAL1 and GFRA1 signaling in breast cancer cells Tan-chi Fan, Hui Ling Yeo, Huan-Ming Hsu, Jyh-Cherng Yu, Ming-Yi Ho, Wen-Der Lin, Nai-Chuan Chang, John Yu, Alice L. Yu PII:

S0304-3835(18)30484-1

DOI:

10.1016/j.canlet.2018.07.026

Reference:

CAN 14000

To appear in:

Cancer Letters

Received Date: 9 May 2018 Revised Date:

18 July 2018

Accepted Date: 18 July 2018

Please cite this article as: T.-c. Fan, H.L. Yeo, H.-M. Hsu, J.-C. Yu, M.-Y. Ho, W.-D. Lin, N.-C. Chang, J. Yu, A.L. Yu, Reciprocal feedback regulation of ST3GAL1 and GFRA1 signaling in breast cancer cells, Cancer Letters (2018), doi: 10.1016/j.canlet.2018.07.026. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Title Page

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Reciprocal feedback regulation of ST3GAL1 and GFRA1 signaling in breast cancer cells Authors: Tan-chi Fan1, Hui Ling Yeo1,2,3, Huan-Ming Hsu4, Jyh-Cherng Yu4, Ming-Yi Ho1, Wen-Der Lin1,5, Nai-Chuan Chang1, John Yu1, Alice L. Yu1,6,7,*

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Affiliations: 1 Institute of Stem Cell and Translational Cancer Research, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan 2

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Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan 3 Institute of Molecular and Cellular Biology, National Tsing Hua University, Hsinchu, Taiwan 4 General Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan. Department of Biochemistry and Molecular Biology, Chang Gung University, Gueishan, Taoyuan, Taiwan 6 Genomics Research Center, Academia Sinica, Taipei, Taiwan 7

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Department of Pediatrics/Hematology Oncology, University of California in San Diego, San Diego, CA, USA *Correspondence: [email protected]

Running title

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ST3GAL1 regulates GFRA1 signaling Keywords Glycosylation, GFRA1, RET, sialyltransferase

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Contact Information Alice L. Yu Institute of Stem Cell and Translational Cancer Research, Chang Gung Memorial Hospital, Taoyuan, Taiwan Phone: 886-33281200 ext 5218; Fax: 886-33285200 ext 5214 Email: [email protected]

Financial Support This work was supported by the grants from Ministry of Science and Technology in Taiwan, 104-2321-B-182A-003, 105-2321-B-182A-001, and Chang Gung Medical Foundation, OMRPG3C0014. Conflict of Interest Statement The authors declare no conflict of interest related to the contents of this manuscript.

Abstract

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GFRA1 and RET are overexpressed in estrogen receptor (ER)-positive breast cancers. Binding of GDNF to GFRA1 triggers RET signaling leading to ER phosphorylation and estrogen-independent transcriptional activation of ER-dependent genes. Both GFRA1 and RET are membrane proteins which are N-glycosylated but no O-linked sialylation site on GFRA1 or RET has been reported. We found GFRA1 to be a substrate of ST3GAL1-mediated O-linked sialylation, which is crucial to GDNF-induced signaling in ER-positive breast cancer cells. Silencing ST3GAL1 in breast cancer cells reduced GDNF-induced phosphorylation of RET, AKT

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and ERα, as well as GDNF-mediated cell proliferation. Moreover, GDNF induced transcription of ST3GAL1, revealing a positive feedback loop regulating ST3GAL1 and GDNF/GFRA1/RET signaling in breast cancers. Finally, we demonstrated ST3GAL1 knockdown augments anti-cancer efficacy of inhibitors of RET and/or ER.

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Abbreviations GDNF, Glial cell line-derived neurotrophic factor;

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Moreover, high expression of ST3GAL1 was associated with poor clinical outcome in patients with late stage breast cancer and high expression of both ST3GAL1 and GFRA1 adversely impacted outcome in those with high grade tumors.

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GFRA1, GDNF family receptor alpha-1; ER, estrogen receptor; Sp1, Specificity Protein 1; ST3GAL1, ST3 beta-galactoside alpha-2,3-sialyltransferase 1.

1. Introduction ACCEPTED MANUSCRIPT Membrane-associated sialoproteins such as mucin, E-cadherin, and integrins are extensively sialylated glycoproteins which have been shown to modulate cell-cell or cell-extracellular matrix interaction by steric hindrance [1, 2]. Mucin-type proteins are highly expressed in many cancers including breast, ovary, and prostate. Mucin O-glycans begin with covalently α-linked N-acetylgalactosamine (GalNAc) to the -OH of

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serine or threonine, forming Tn antigen. Addition of galactose via β1, 3 linkage to GalNAc gives rise to a core 1 structure named T antigen, and attachment of a branching N-acetylglucosamine to core 1 forms core 2. Mucin O-glycans from normal breast are mostly composed of elongated core 2 structures. It has been shown that Mucin 1 O-glycans from breast cancer cell lines are often truncated with mainly core 1 structures based on mass spectrometry sequencing [3, 4]. Moreover, the principal O-glycan species of

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Mucin 1 from the serum of breast cancer patients were sialylated core 1 type glycans, among which the most abundant glycan was NeuNAcα2-3Galβ1-3GalNAc (sialyl-3T) [5]. This was associated with overexpression of ST3 beta-galactoside alpha-2,3-sialyltransferase 1 (ST3GAL1) causing a change from core 2-based glycans to sialyl-3T on Mucin 1 [6, 7].

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ST3GAL1 catalyzes the transfer of sialic acid in an α2,3 linkage to Galβ1-3-GalNAc-Ser/Thr, and thus terminates further chain elongation, except extension with sialic acids [8]. Altered expression level or activity of this enzyme might lead to changes in the composition and length of O-glycans attached to mucin-type proteins. ST3GAL1 mRNA expression is elevated in primary breast carcinoma cells compared to normal or benign breast tissues [9]. In ductal carcinomas, the expression of ST3GAL1 appeared to correlate to histologic grade. Overexpression of ST3GAL1 in bladder cancer cells decreased expression of several genes involved in DNA repair, which might be associated with increased malignancy [10]. However, very

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little is known about the role of this enzyme in breast cancers. It is believed that glycosylation is cell-type specific. Alteration of specific glycosyltransferase generates glycan microheterogeneity. Therefore, identifying specific targets of glycosyltransferases will help to elucidate how glycans on the cell surface affect the cell behavior. In this study, we identified GDNF receptor

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alpha 1 (GFRA1) to be a target protein of ST3GAL1 in breast cancer cell lines. The GFRA family consists of GFRA1-4, which is glycosylphosphatidylinositol (GPI)-anchored receptors with no transmembrane domain [11]. Glial cell line-derived neurotrophic factor (GDNF) family of ligands (GFL) comprises 4 members; GDNF, artemin, neurturin, and persephim [12]. The GFL family members preferentially interact with one or more

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of the GFRA family. Upon GFL binding to GFRA, the complex will bind and facilitate RET dimerization and subsequent phosphorylation, promoting neuron cell proliferation, migration, differentiation and neurite branching. GDNF preferentially interacts with GFRA1. RET is unable to bind GDNF on its own and GFRA1 is required for GDNF signaling [13, 14]. Higher levels of GFRA1 mRNA are associated with later tumor stage and lymph node metastasis in breast cancers [15], and overexpression of GFRA1 and RET has been reported in ERα-positive breast cancers [16-19]. Importantly, activation of GFRA1/RET signaling leads to ERα phosphorylation at Ser118/Ser167 and estrogen-independent transcriptional activation of ER-dependent genes [17]. This is consistent with the reports that GFRA1/RET signaling is a key determinant of response and resistance to endocrine treatment in ER-positive breast cancers [20] [19]. Based on NetOGlyc 3.1 prediction, there are several O-glycosylation sites on GFRA1 but none on RET [21]. We thus investigated whether O-linked sialylation on GFRA1 may affect GDNF-induced signaling in ER-positive breast cancer cells.

2. Materials and Methods

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2.1 Clinical specimens 114 fresh primary breast cancer tumor and adjacent normal tissue specimens were collected during surgical resections performed at the Tri-Service General Hospital (Taipei, Taiwan). Informed consent was obtained from all subjects before their tissue were deposited. The sample were fully encoded and used

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under a protocol approved by the Institutional Review Board of Human Subjects Research Ethics Committee of the Tri-Service General Hospital and Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan. The clinicopathological information is listed in Supplemental Table 2.

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2.2 Cells, antibodies and reagents AS-B145 and AS-B634 breast cancer cell lines were established in our lab [22]. ZR-75-1 was kindly provided by Dr. Jin-Yuh Shew, Academia Sinica. All other cancer cell lines were purchased from Bioresource Collection and Research Center. MDA-MB-231 and HEK-293were cultured in DMEM plus 10% fetal bovine serum (FBS) (Invitrogen). T47D and ZR-75-1 were cultured in RPMI plus 10% FBS. All other cells were

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maintained in MEM plus 10 % FBS and 10 µg/ml insulin (Sigma). The following antibodies and lectin were used in the study: p-ERK1/2, ERK1/2, p-AKT-S473, AKT, p-JNK, p-RET, p-ERalpha-S167 (Cell Signaling), JNK, Sp1, actin, Lamin A/C (Santa Cruz), GFRA1 (R&D Systems), RET (Abcam), GAPDH (Genetex), ERα (Thermo), p-Ser, p-Thr (Millipore), ST3GAL1 (Sigma), biotinylated Peanut Agglutinin (PNA), agarose bound PNA (Vector

(Academia Sinica).

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Labs) and alkaline phosphatase-conjugated antibodies (Jackson Immunoresearch). The following reagents were used, AKT1/2 kinase inhibitor, LY294002, mithramycin A, Fulvestrant, Tamoxifen (Sigma), Rapamycin, U0126, ERKi (Calbiochem), GDNF (R&D Systems), and Vandetanib (MedChem Express). Control (pLAS.Void) and ST3GAL1 short hairpin RNA (shRNA) (TRCN0000231843) plasmids were purchased from RNAi core

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2.3 Small interference RNA or short hairpin RNA plasmid transfection Control scramble siRNA (sc siRNA) and siRNA oligonucleotides directed against ST3GAL1 were custom-designed and synthesized by Invitrogen. Cells were transfected with siRNA oligonucleotides with Lipofectamine RNAiMAX (Invitrogen) and incubated at 37°C for 48h in complete media, followed by

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washing and culturing for a further 48 h. The sequences of the siRNA oligonucleotides against ST3GAL1 were UCACUCUGAUCUUUGCAGGAACCGG and CCGGUUCCUGCAAAGAUCAGAGUGA. MCF7 and BT474 cells stably expressing ST3GAL1 or control pLAS.Void (pVoid) shRNAs were selected by exposure to puromycin. 2.4 Cell proliferation assay with xCELLigence Forty eight hours after ST3GAL1 siRNA or control transfection, cells were seeded at 8000 cells/well in 200 µl complete media in E-plates (Roche Applied Science). After overnight incubation, cells were subjected to serum starvation for 16 h while being monitored by xCELLigence SP system (Roche Applied Science). Then cells were treated with or without 10 ng/ml GDNF in serum free MEM and cultured for another 48 h. The xCELLigence system recorded cell index (CI) every 2 h. For drug sensitivity assay, cells were seeded at 8000 cells/well in 200 µl complete media in E-plates overnight. Then cells were treated with 0.1 % DMSO (control), indicated concentration of vanditanib and/or

tamoxifen in complete media for another 120 h. The xCELLigence system recorded cell index (CI) every 3 h.

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2.5 Quantitative real-time PCR RNA was isolated using WelPrep RNA kit (Welgene). cDNA was generated from 1000 ng total RNA, using High Capacity cDNA RT Kit (Applied BioSystems). Real-time qPCR was performed with ABI Prism 7300 Sequence Detection System (ABI) using SYBRGreen MasterMix (ABI), and normalized by using GAPDH levels as a reference. Primer sequences were listed in Supplemental Table 1.

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2.6 Immunoprecipitation and Western blotting Cells were lysed with 25 mM Tris-HCl (pH 8.0), 150 mM NaCl, 1 % Bj58, and 2 mM MgCl2, containing

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protease (Roche) and phosphatase inhibitors (Sigma). Cell lysates were immunoprecipitated overnight by incubation with PNA-biotin agarose (Vector) or primary antibodies and subsequent incubation with Protein A/G agarose (Santa Cruz) for 2 h. After washing with lysis buffer, bound proteins were eluted, separated and analyzed by western blotting.

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The agarose bound PNA lectin pull down assay was done using MCF7 cell lysate transfected with control or ST3GAL1 siRNA. The PNA-bound glycoproteins were released by 200 mM Galactose/PBS according to the manufacturer’s protocol. The eluted proteins were analyzed by western blotting using biotinylated PNA or subjected to protein identification by LTQ-FT MS core facility at Academia Sinica. The total cell lysate or immunoprecipitated samples were separated on 4–12% NuPAGE (Invitrogen) and electrophoretically transferred to a PVDF membrane for immunoblotting. The blots were probed with primary antibody, followed by AP-conjugated secondary antibodies. Immunoreactive bands were visualized

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using ECF substrate (GE Healthcare Life Sciences). All western blot images were acquired by Typhoon FLA 9500 (GE Healthcare Life Sciences). For quantification, Gel-Pro V3.1 software was used. 2.7 Chromatin Immunoprecipitation assay

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MCF7 cells were serum-starved overnight, followed by incubation with or without 10 ng/ml GDNF for 2 h. Chromatin Immunoprecipitation (ChIP) was performed according to the instructions provided with the ChIP assay kit (Upstate). For immunoprecipitation, formaldehyde-fixed DNA-protein complex was incubated

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with 2 µg of anti-Sp1 rabbit antibody or control rabbit IgG at 4°C overnight. The DNA regions of interest were amplified using primer pairs (Supplemental Table 4) that spanned the Sp1 sites within the ST3GAL1 promoter region. 2.8 In-gel reductive β-elimination to release O-glycans The immunopurified GFRA1 were run on SDS-PAGE and visualized by coomassie blue staining. The protein bands were then excised from the PAGE and deN-glycosylated by in gel digestion with PNGase F. The released N-glycans were washed sequentially with pure water and 50 % acetonitrile solution. To release O-glycans chemically, the remaining gels were further treated with 1 M sodium borohydride in 100 mM sodium hydroxide solution and incubated overnight at 45°C in an oven. Then, the reductive β-elimination reaction was quenched by adding drops of glacial acetic acid until there was no more hydrogen bubble formation. The solution containing the released O-glycans was aliquoted and desalted by using Dowex 50Wx8 (H+ form) ion exchange resins. Excess borate was removed in a nitrogen blow dryer by co-evaporation with 10% (v/v) acetic acid in methanol. Prior to permethylation and MS analysis, all extracts

were dried in a SpeedVac and kept at -30°C.

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2.9 NanoLC-ESI-MS/MS analysis In order to increase MS detection sensitivity with predictable fragmentation pattern, the released O-glycans were subjected to permethylation. Permethylation was carried out by the use of the NaOH/DMSO slurry method and iodomethane. The permethylated derivatives were extracted by using a

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chloroform/water method, and further purified by ZipTip-C18 tips. NanoLC-ESI-MS/MS analyses of the permethylated O-glycans were carried out on an UltiMate 3000 RSLCnano system (Thermo Scientific Dionex) comprising a homemade pre-column (100 µm x 10 mm packed with ReproSil-Pur basic C18, 2.4 µm) and a homemade capillary column (75 µm x 25 cm packed with ReproSil-Pur basic C18, 1.9 µm), coupled to an

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Orbitrap Fusion (Thermo Scientific) MS system. O-glycans were dissolved in 25 % (v/v) acetonitrile and injected onto trap column with loading buffer (0.1 % formic acid) at a flow rate of 5 μL/min. Online nanoLC separation was conducted in a serially connected analytical column at a constant flow rate of 300 nl/min with a linear gradient of 25–55 % (v/v) acetonitrile (with 0.1 % formic acid) in 45 min. The eluent was

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directly interfaced to a nanoESI source based on liquid junction configuration consisting of an uncoated emitter and a high voltage (in range of 1.6 to 1.8kV) platinum electrode. Data-dependent acquisition was performed in top-speed mode with a 3 sec cycle time, the full scan MS spectrum (m/z 300-1500) was acquired in the Orbitrap at 120,000 resolution (at m/z 200) with automatic gain control (AGC) target value of 4 x 105. MS/MS analyses were performed in higher energy collisional dissociation mode with 15 % normalized collision energy and precursor ion intensity threshold above 50,000 counts in the full scan. MS/MS spectra were acquired in the Orbitrap at 15,000 resolution (at m/z 200) with AGC value of 5 x 104.

2.10 Statistical analysis

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The fragmentation assignment of MS/MS spectra was depicted according to the Domon and Costello nomenclature and manually interpreted.

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Error bars indicate SEM for a minimum of two independent experiments and representative results were shown. *P < 0.05, **P < 0.01, and ***P < 0.001 when compared as indicated. P value was calculated by

3. Results

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using the student t test or one-way ANOVA.

3.1 GFRA1 is a protein target of ST3GAL1 The nonsialylated Galβ1-3GalNAc-Ser/Thr core 1 O-glycan is a ligand for plant lectin peanut agglutinin (PNA) [23]. When this O-glycan is modified by the addition of sialic acid in α2-3 linkage, it will generate trisaccharide sialyl-3T, which is no longer recognized by PNA lectin. Using the lectin blot, several PNA labeling signals ranging from 55 kD to greater than 250 kD were increased in MCF7 cells (Figure 1A), when ST3GAL1 was silenced to 33% of control at RNA level (Figure 1B) and 23% of control at protein level (Figure 1C). Enhanced PNA signaling in ST3GAL1-silenced cells is consistent with the phenotype observed in st3gal1 △/ △ thymocytes [24]. In order to identify ST3GAL1 substrate proteins, cell lysates from control or ST3GAL1 siRNA transfected cells were subjected to precipitation by agarose bound PNA lectin. The PNA bound glycoproteins were analyzed by western blotting using biotinylated PNA (Supplemental Figure 1A), or subjected to protein identification by LTQ-FT MS. The results showed that one of the potential protein

targets of ST3GAL1 is GFRA1 (Supplemental Figure 1B), which is highly expressed in MCF7 cells ACCEPTED MANUSCRIPT (Supplemental Figure 2A). As shown in Figure 1C, the GFRA1 immunoprecipitated from ST3GAL1 silenced cells displayed high PNA binding signaling whereas that from control cells showed negligible PNA binding. ST3GAL1 silencing did not affect expression levels of GFRA1 as shown in the blot. Protein expression levels of GFRA1 and RET in various breast cancer cell lines was analyzed by western blotting. Consistent with the previous finding, GFRA1 and RET were primarily expressed in ER-positive

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breast cancers cell lines (Supplemental Figure 2A). MCF7 cells showed the highest amounts of GFRA1 and RET protein levels among the cell lines we tested. Although there is some cross reactivity of GDNF to GFRA1, GFRA2 and GFRA4 [25], the transcription level of GFRA2/4 was less than 1% of GFRA1 in MCF7 cells as analyzed by qPCR analysis (Supplemental Figure 2B). Thus, GFRA1 was the major GFRA member expressed in MCF7 cells.

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3.2 ST3GAL1 regulates GDNF-mediated GFRA1/RET signaling. It is known that GFRA1 is the preferential receptor for GDNF. To determine whether O-linked

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sialylation on GFRA1 would affect GDNF-induced signaling in ER-positive breast cancer cells, we first assessed GDNF-induced phospho-signals. As shown in Figure 2A, GDNF induced rapid and time-dependent phosphorylation of RET, AKT, ERK1/2, and JNK in MCF7 cells transfected with control scramble siRNA. These phospho-signals were significantly delayed and diminished in ST3GAL1 silenced cells. GDNF also triggered a 2.6 ± 0.1 fold increase in the transcription of EGR1, a known RET target gene [26], which was dampened to 1.77 ± 0.065 (P = 0.019) upon ST3GAL1 silencing (Figure 2B). Similar changes in phospho-signaling were also observed in MCF7 stable clones transfected with shST3GAL1 shRNA plasmid (Supplemental Figure 3A), in

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which ST3GAL1 was knocked down to 39% of control cells as analyzed by qPCR analysis (Supplemental Figure 3C). Reduced phospho-signaling was also observed in BT474 stable clones transfected with shST3GAL1 shRNA plasmid (Supplemental Figure 4A), in which ST3GAL1 was knocked down to 38% of

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control cells (Supplemental Figure 4B). Moreover, GDNF induced a transient increase in Ser118 ERα phosphorylation and thus promoted ERα-dependent transcription of FOS [17], which was suppressed by ST3GAL1 silencing (Figure 2B, Supplemental Figure 3B). These data strongly suggested a functional connection between O-linked sialylation and GDNF-induced ER signaling in breast cancer cells.

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3.3 ST3GAL1 mediated O-linked sialylation of GFRA1 is important for its interaction with RET It has been shown that GFRA1 interacted with RET at the basal level and GDNF induced tripartite complex formation [27]. To decipher whether O-linked sialylation on GFRA1 would alter such hetero-complex formation and thereby regulate GDNF-induced downstream signaling, we performed co-immunoprecipitation (co-IP) between GFRA1 and RET in the presence or absence of GDNF treatment. In the absence of GDNF, Western blotting clearly demonstrated a weak association between RET and GFRA1, which was dampened upon ST3GAL1 silencing (Figure 2C). In the presence of GDNF, GFRA1/RET complex interaction was more pronounced in control cells, as expected. After ST3GAL1 silencing, GDNF-induced GFRA1/RET interaction was significantly reduced in co-IP assays using antibody against either RET or GFRA1. MCF7 expressed two isoforms of RET corresponding to the fully glycosylated form at the plasma membrane (170 kD) and the incompletely glycosylated form in the endoplasmic reticulum (150 kD) [28]. The co-IP assay using antibody against GFRA1 showed that GFRA1 mainly interacted with RET at the plasma

membrane upon GDNF treatment (Figure 2C). These data suggested that O-linked sialylation on GFRA1 ACCEPTED MANUSCRIPT enhanced its interaction with cell surface RET, leading to augmented GDNF-induced downstream signaling. 3.4 ST3GAL1 enhances GDNF-induced cell growth It has been shown that GDNF can stimulate MCF7 cell proliferation and survival [29]. To further investigate the contribution of sialylation on GDNF-induced cell proliferation in vitro, continuous cell

clearly plays an important role in GDNF-signaling in breast cancers.

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growth was monitored by xCELLigence System. When cultured in serum-free media, control MCF7 cells proliferated at a slow rate which was significantly accelerated by adding GDNF. ST3GAL1 silencing clearly reduced cell growth in serum-free media compared to that of control cells. Addition of GDNF was unable to restore the proliferation of ST3GAL1 silenced cells (Figure 2D). Therefore, O-linked sialylation on GFRA1

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3.5 ST3GAL1 knockdown sensitizes cancer cells to inhibitors of RET and ER RET can be effectively inhibited by vandetanib (ZD6474), which is approved by FDA for the treatment

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of locally advanced or metastatic medullary thyroid carcinoma. It has been shown that RET signaling inhibition by vandetanib reduced cell proliferation in luminal breast cancers, for which endocrine therapy such as tamoxifen is commonly used. In addition, inhibition of RET signaling by vandetanib potentiated the efficacy of tamoxifen in ER-positive breast cancers, since RET activation leads to ER phosphorylation and activation [20] [19]. In light of the impact of O- sialylation of GFRA1 on its interaction with RET and downstream signaling including ER phosphorylation, it is likely that ST3GAL1 silencing may enhance the anti-tumor activities of vandetanib or tamoxifen alone, as well as in combination, for ER-positive breast

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cancers. To evaluate such possibility, ST3GAL1 knockdown or control MCF7 cells were treated with vandetanib and/or tamoxifen and cell growth was monitored by xCELLigence System. ST3GAL1 knockdown cells showed increased sensitivity to tamoxifen in cell growth as compared to control pVoid cells (mean normalized cell index reduced from 76% to 39.5%, Figure 2E). Vandetanib alone could also significantly

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suppress the cell growth in control or ST3GAL1 knockdown cells (mean normalized cell index 37.5% vs. 11.3%). Consistent with previous report, growth of control cells treated with combination of vandetanib and tamoxifen was further reduced as compared to vandetanib alone (mean normalized cell index 37.5% vs. 22.5%) [19]. In ST3GAL1 knockdown cells, the response to combination of vandetanib and tamoxifen was

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even more pronounced, as compared to vandetanib alone (mean normalized cell index 11.3% vs. 4.1%). The drug sensitivity was also analyzed in BT474 (Supplemental Figure 5). ST3GAL1 knockdown cells showed increased sensitivity to tamoxifen in cell growth as compared to control cells (mean normalized cell index from 69.5% to 45.2%). Vandetanib alone could significantly inhibit the growth of BT474 control or ST3GAL1 knockdown cells (mean normalized cell index 80.1% vs. 42.8%). The growth of control or ST3GAL1 knockdown cells treated with combination of vandetanib and tamoxifen was further reduced (mean normalized cell index 43.9% vs. 19.3%). These data clearly demonstrated that ST3GAL1 silensing increases drug sensitivity to combination of RET and ER inhibitors in ERα-positive breast cancer cells, suggesting that there is functional crosstalk between ST3GAL1, GFRA1/RET and ER pathways in breast cancer cells. 3.6 Clinical significance of ST3GAL1 and GFRA1 in primary breast cancer samples The correlation among the expression levels of ST3GAL1 and GFRA1 in breast cancers has not been addressed. The transcription levels of ST3Ga1 and GFRA1 in 114 pairs of primary breast cancer and

adjacent normal tissue was determined by RT-PCR to evaluate the prognostic value of these two genes. The ACCEPTED MANUSCRIPT clinical features of the patients are summarized in Supplemental Table 2. Based on ROC curve, the best cutoff values for stratifying high and low gene expression levels were selected for ST3GAL1 (1.027), and GFRA1 (-2.51). A univariate survival analysis revealed a tendency for recurrence in patients with high ST3GAL1/GFRA1 expression, but it did not reach statistical significance (Supplemental Table 3). As expected, patients > 52.8-year (HR:1.99, 95% CI:1.01-3.91, P = 0.046), as well as

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pathological stage 3 and 4 (HR:2.4, 95% CI:1.24-4.61, P = 0.009) were significantly related to relapse-free survival, both were confirmed by a multivariate analysis as a significant independent prognostic variable influencing relapse-free survival. There was a trend for higher expression of ST3GAL1 to be associated with shorter relapse-free survival

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among patients with breast cancers (n=114, P = 0.17, Figure 3A) or grade 3 histology (n=73, P = 0.07, Figure 3B). Among patients with stage 3 and 4 breast cancer, there was a significant correlation of higher mRNA expression of ST3GAL1 with shorter relapse-free survival (n=35, P = 0.029, Figure 3C). When GFRA1 was divided into high or low expression group, the relapse-free survival did not correlate with expression level

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of ST3GAL1 (Figure 3D-E). There was a trend for high expression of both ST3GAL1 and GFRA1 to be associated with poorer relapse-free survival, although it did not reach statistical significance (P = 0.151, Figure 3F). However, Kaplan-Meier graphs showed significant association of high mRNA expression of both ST3GAL1 and GFRA1 with shorter relapse-free survival among patients with grade 3 (P = 0.027, Figure 3G). In stage 2-4 breast cancer, low expression of both ST3GAL1 and GFRA1 is associated with higher relapse-free survival than those with high expression of either or both (P = 0.039, Figure 3H).

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3.7 GDNF stimulates transcription of ST3GAL1 through AKT/Sp1 pathway Unexpectedly we found that GDNF induced a concentration-dependent increase in the transcription of ST3GAL1 up to 2.16 ± 0.004 (P < 0.0001) at 30 ng/ml GDNF, using qPCR analysis (Figure 4A). To decipher the

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signaling pathway connecting GDNF/GFRA1 and ST3GAL1, cells were treated with inhibitors targeting the key downstream effectors of GDNF, followed by qPCR analysis of ST3GAL1. As shown in Figure 4B, only inhibitors of PI3K and AKT1/2 kinases abolished GDNF-induced transcription of ST3GAL1, whereas inhibitors of ER, mTOR, MEK1/2 or ERK1/2 had no impacts (Supplemental Figure 6A). The inhibitory effect

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of these drugs on the phosphorylation status of AKT, ERα, mTOR and MEK1/2 were confirmed by Western blotting, probed with specific phospho antibodies (Supplemental Figure 6B). These data suggested that GDNF-induced transcription of ST3GAL1 was mainly mediated by the PI3K/AKT pathway. It has been shown that the transcription factor Specificity Protein 1 (Sp1) can stimulate the transcription of ST3GAL1 in colorectal cancer cells [30]. To determine whether Sp1 can regulate GDNF-induced transcription of ST3GAL1, we treated MCF7 cells with a Sp1 inhibitor, mithramycin A (MMA), at increasing concentrations [31-33]. Although higher concentrations (0.1, 0.5 µM) of MMA inhibited the basal transcription of ST3GAL1, low concentration (0.01uM) of MMA significantly blocked GDNF-induced transcription of ST3GAL1 without affecting the basal transcription of ST3GAL1 (Figure 4C), suggesting Sp1 might regulate the GDNF-induced upregulation of ST3GAL1. Three Sp1 sites were identified at positions between -730 and -130 of the ST3GAL1 promoter [30] (Figure 5A). To delineate which site(s) were involved in the regulation of GDNF-induced ST3GAL1 transcription, ChIP assay was performed. In the presence of GDNF, amplification of primer pair 1 (-252/-130)

sequence was detected in the immunoprecipitates using anti-Sp1 antibody, but not control antibody ACCEPTED MANUSCRIPT (Figure 5B). In the absence of GDNF, there was no amplification of either primer pair 1 (-252/-130) or 2 (-773/-650) surrounding the Sp1-binding sites when immunoprecipitated with the anti-Sp1 or control antibodies. These findings indicate that Sp1 binds to sites -175/-205 on ST3GAL1 promoter. 3.8 AKT-induced phosphorylation of Sp1 increases DNA binding activity and ST3GAL1 gene expression

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It has been shown that the transcriptional activity of Sp1 is greatly affected by its nuclear localization and phosphorylation status, which can be mediated by various kinases including PI3K, AKT, ERK and PKCZ [34-36]. To determine if GDNF modulates the subcellular distribution of Sp1, the cytosolic and nuclear fractions of MCF7 cells harvested at 0 to 120 min after exposure to GDNF were analyzed by western blotting. As shown in Supplemental Figure 7, GDNF did not facilitate Sp1 translocation into the nucleus, in

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contrast to the expected increase in ERα translocation [17]. Next, to determine whether GDNF treatment could enhance Sp1 phosphorylation, phospho-Sp1 was characterized by immunoprecipitating total Sp1 protein with the anti-Sp1 antibody, followed by probing

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with anti-phospho serine or threonine antibodies. Figure 5C-D showed that GDNF clearly stimulated the serine- and threonine-phosphorylation on Sp1. Moreover, treating cells with AKT1/2 inhibitor significantly blocked GDNF-induced serine-phosphorylation on Sp1 (Figure 5D). Most importantly, ChIP assays showed that AKT1/2 inhibitor abrogated GDNF-induced amplification of primer set 1 (-252/-130) surrounding the Sp1-binding site on ST3GAL1 promoter (Figure 5E). These data clearly demonstrated that GDNF promoted phosphorylation of Sp1 transcription factor via PI3K/AKT activation, leading to enhanced binding of Sp1 to the ST3GAL1 promoter region (-252/-130) and upregulation of ST3GAL1. Taken together, our findings

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demonstrated the presence of a positive feedback loop between ST3GAL1 and GDNF/GFRA1 signaling. 3.9 NanoLC-MS/MS identifies O-glycans on GFRA1 In order to elucidate which O-glycans on GFRA1 were affected by the down regulation of ST3GAL1,

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endogenous GFRA1 and overexpressed HA tagged GFRA1 from control (sc) or ST3GAL1 siRNA (si) transfected MCF7 cells were immunopurified by using anti-GFRA1 antibody. After separation on SDS-PAGE and staining with Coomassie Brilliant Blue, protein bands were excised from gels. N-glycans were first enzymatically removed by PNGase F treatment in gels and then O-glycans were chemically released by

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alkaline reductive β-elimination approach. The released O-glycans were then subjected to permethylation, MALDI-TOF MS profiling and MS/MS-analysis, and quantitative nanoLC-ESI-MS/MS analysis. MALDI-TOF MS analyses indicated that O-glycans of GFRα1 were composed of core 1, core 2 and their monosialyl-, disialyl-derivatives (data not shown). However, due to the constraint of small amount of endogenous GFRA1, O-glycans from endogenous samples yielded few signals in MS profiles. Moreover, MALDI-TOF MS/MS analysis of sialyl-T glycans showed a mixed MS/MS spectrum including fragment ions derived from sialyl-3T and sialyl-6T structures. In order to quantitatively analyze O-glycan isomers and elucidate substrate specificity of ST3GAL1, nanoLC-ESI-MS/MS analyses of permethylated O-glycans from HA-GFRA1 samples were performed. As shown by the extracted-ion chromatographs (EICs) (Figure 6A), HA-GFRA1 mainly expressed core 1 structures with their mono- and di-sialylated derivatives, which is consistent with the results of MALDI-TOF analyses. EICs clearly demonstrated that both sialyl-3T and sialyl-6T glycans were present on HA-GFRA1, and the relative abundance of these glycans was affected by expression of ST3GAL1. The LC-MS signals representing sialyl-3T and sialyl-6T glycans were identified in well-resolved peaks at the

retention times (RT) 31.2 and 33.6, respectively (Figure 6A). Both the ESI-MS/MS spectra showed ACCEPTED MANUSCRIPT predominant dissociation of sialyl linkage, which produced B and Y fragment ions at m/z 376 and 498 respectively, and their subsequent fragments with neutral loss of CH3OH at m/z 344, 312 and 466 (Figure 6B). Additionally, the MS/MS spectra from the early peak at RT 31.2, composed of diagnostic fragment ions including di-substituted HexNAc alditol (YY’) at m/z 280, Z and Z’ fragment ions at m/z 637 and 480, all indicated that the trisaccharide precursor molecule has a branching structure at the reducing end,

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consistent with sialyl-6T (Figure 6B). The MS/MS spectrum from a later peak at RT 33.6 also displayed predominant fragment ions from the sialyl linkages; however, the diagnostic ions of sialyl-6T were lost with the emergence of other paired B/Y fragment ions at m/z 580 and 294 respectively, and Z fragment ions at m/z 276, indicating a linear structure composed of a terminal NeuAc-Hex and a mono-substituted HexNAc

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at the reducing end, which was sialyl-3T (Figure 6B). Other major O-glycans of GFRA1 identified included core 1 related glycans, such as T-antigen (peak at RT 23.8), disialyl-T (RT 37.3); core 2 branching structures, including galactosyl-core 2 (RT 31.2), monosialylated galactosyl-core 2 isomer (RT 37.0 and 37.4) and disialyl-galactosyl-core 2 (RT 41.2); with minor elongated core 1 structures (RT 32.8) and their sialylated

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derivatives (RT 37.9). Calculation of the ratio of relative abundance of core 1 and 2 related glycans by integrating peak areas from EICs (Figure 6C) revealed that the core 1 related structures were the major glycoform (92.6 and 85.9% in sc and si, respectively) on HA-GFRA1 expressed in MCF-7 cells. The core 1 elongation and the core 2 branching O-glycans were the minor structures, representing 7.4% and 14.1% in sc and si samples, respectively. The results of nanoLC-MS O-glycan profile analysis showed that knockdown of ST3GAL1 significantly down regulated the expression of sialyl-3T (62.4 to 36.1%) and disialyl-T (12.7 to 9.9%) but increased the

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level of T antigen (11.4 to 22.6%) (Table 1), which was consistent with the PNA lectin staining experiment (Figure 1D). It is interesting that the amount of sialyl-6T increased by nearly 3 fold (6.0 to 17.2%), which may have contributed to the upregulation of precursor T antigens (almost 2 fold) after ST3GAL1 silencing. Moreover, ST3GAL1 silencing augmented total core 1 elongation and core 2 branching structures (7.4 to

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14.1%). This was reflected by increases in core 1 related structures, including elongated core 1 glycans (0.2 to 0.5%) and their sialylated forms (0.2 to 0.6%), and core 2 related structures, including galactosyl-core 2

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(0.8 to 3.1%), sialyl-galactosyl-core 2 (1.0 to 3.9%) and disialyl-galactosyl-core 2 (1.9 to 2.7%), with the exception of a slight decrease in sialyl-(galactosyl-)core 2 (3.4 to 3.3%) structure. 4. Discussion

Although overexpression of ST3GAL1 has been reported to promote mammary tumorigenesis [37], little is known about its function and its protein targets. In this study, we identified GFRA1 as a substrate of ST3GAL1, which mediated its O-linked sialylation, facilitating its interaction with RET, thereby regulating the phosphorylation and downstream signaling of GDNF/GFRA1/RET pathway in breast cancer cells. On the other hand, we showed that GDNF upregulated the transcription of ST3GAL1, which was mediated bySp1 phosphorylation via the PI3K/AKT pathway as confirmed by ChIP assay. This is the first report demonstrating a positive feedback loop that links GDNF/GFRA1/RET signaling and O-linked sialylation in breast cancer cells (Figure 7). GFRA1 consists of three cysteine-rich extracellular domains and attach to the membrane by a GPI-anchor. The region corresponding to the second and third domains has been shown to contribute to

ligand binding as well as to interaction with RET [38]. The predicted O-glycosylation sites on GFRA1 are ACCEPTED MANUSCRIPT located at the C-tail domain near the extracellular juxtamembrane region but their functions have yet to be determined. It has been shown that sialylation and fucosylation are capable of regulating receptor activity [39, 40]. For example, loss of ST6Gal-I mediated N-linked sialylation on EGFR augmented EGF-induced EGFR phosphorylation and ERK activation in colon cancer cells [41]. Increasing sialylation and α1,3-fucosylation on the other hand, suppressed EGFR dimerization and tyrosine phosphorylation in lung cancer cells [39].

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The α2,3-sialylation of α2 subunits was required for the integrin α2β1-dependent cell adhesion to collagen type I in prostate cancer cells [42]. The nanoLC-MS/MS-based O-glycan profiling and detailed structural elucidation demonstrates the addition of α2,3 sialylation to the core structures (Galβ1-3GalNAc-Ser/Thr) on O-glycans of GFRA1 are

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ST3GAL1-mediated. Additionally, these data clearly illustrated that downregulation of ST3GAL1 enhanced the expression of core 1 elongation and core 2 branching O-glycans, which indicated that ST3GAL1-mediated core sialylation would affect the downstream O-glycosylation pathway. Recently, Goodman et al. showed that zGFRA1 N62D, an N-linked glycosylation site mutant, displayed

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similar zGFRA1/zGDNF/zRET complex binding affinity as wild-type zGFRA1, suggesting N-linked glycosylation is not essential for this complex assembly [43]. However, the contribution of O-linked glycosylation was not addressed. They also described a flower-shaped structure of a hRET ectodomain/hGDNF/rGFRA1 complex [43]. The homotypic interactions of RET CRD (membrane-proximal cysteine-rich) domains were stabilized by a flanking C-tail region of GFRA1. Based on NetOGlyc-3.1 prediction, there are 4 consecutive O-glycosylation sites on the GFRA1 C-tail region [21]. Our co-IP data showed that interaction of GFRA1 with RET at the plasma membrane decreased upon ST3GAL1 silencing

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(Figure 2). Here we provided the first evidence that O-linked α2,3-sialylation of GFRA1 contributed to GDNF-induced interaction with RET and thus the downstream signaling in breast cancer cells. Surprisingly, we found that GDNF could upregulate ST3GAL1 mRNA, which was not in the list of GDNF-responsive genes in MCF7 cells reported by Morandi et al. [20]. This omission of ST3GAL1 from their

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gene list probably reflects the high cut-off value of ≥ 11 used in their analysis. Here, we demonstrated that AKT activation played a crucial role in GDNF-induced transcription of ST3GAL1, via phosphorylation of Sp1, leading to its enhanced DNA binding to ST3GAL1 promoter. There are three potential Sp1 binding sites located in the region between -730 and -130 of the ST3GAL1 promoter [30]. Our ChIP assay data clearly

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demonstrated that Sp1 binds to the ST3GAL1 promoter region (-252/-130). Although Sp1 has been shown to be overexpressed in breast cancers [44], GDNF did not affect the transcription or translation of Sp1 (Supplemental Figure 7), but rather it enhanced the Ser/Thr phosphorylation on Sp1. Several transcription factors have been linked to regulation of ST3GAL1 in cancer cells. For example, NF-kappaB has been linked to tumor necrosis factor alpha (TNFα)-induced transcription of ST3GAL1 in colon cancer [45]. In breast cancer cells, we found that NF-kappa B inhibitor did not suppress GDNF-induced transcription of ST3GAL1, while IL8 was inhibited as expected (data not shown). c-Myc has been linked to the EGF-induced transcription upregulation of ST3GAL1 in colon cancer cells [26]. However, we did not find c-myc binding to ST3GAL1 promoter upon GDNF treatment using ChIP assay (data not shown). GFRA1 is located in a chromosome region which is more frequently amplified in basal-like BRCA1-mutated tumors than basal-like BRCA1 non-mutated tumors [46], indicating that GFRA1 might also play an important role in basal-like breast cancers. Recently, several studies showed that GDNF triggers

SRC family kinase activation in RET-deficient neurons and cell lines, uncoupling the requirement of RET ACCEPTED MANUSCRIPT co-expression in the cells [47, 48]. Therefore, the signaling pathway linking GFRA1 in RET-deficient breast cancers remains to be further investigated. Studies have shown that RET overexpression in ER-positive breast cancers [16-19] is associated with poor prognosis in patients [49]. Since RET activation by ligand leads to ER phosphorylation and activation, RET signaling inhibition by vandetanib could potentiate the inhibitory effect of tamoxifen in ER-positive

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breast cancers [20] [19], as observed in our study. Here, we demonstrated that ST3GAL1 knockdown not only diminished the ligand-induced RET and ER phosphorylation but augmented the cytotoxicity of RET and ER inhibitors (Figure 2). Moreover, we show that high expression of both ST3GAL1 and GFRA1 is associated with poor prognosis in patients with high grade breast cancer. In this context, targeting ST3GAL1 might provide another strategy to overcome resistance to endocrine treatment of ER-positive breast cancer

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overexpressing ST3GAL1/GFRA1. In conclusion, we have demonstrated that O-sialylation changes on GFRA1 mediated by ST3GAL1 were associated with GDNF-induced downstream signaling and breast cancer cell proliferation, which in turn promoted the transcription of ST3GAL1. These findings not only provide a

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possible mechanistic explanation for the reported upregulation of ST3GAL1 transcripts in breast cancers [9] but also point to the targeting of ST3GAL1 as a new strategy to enhance responses to endocrine treatment of breast cancer . Acknowledgements We thank Hsiao-Wei Wu for her excellent scientific illustration, and Dr. Jin-Yuh Shew for providing ZR-75-1 cells.

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Table 1. Identified O-glycans on HA-GFRA1. ACCEPTED MANUSCRIPT The relative abundance of the individual glycoform is given in percentage (%) of the total sum of integrated peak areas in the nanoLC-MS analyses of extracted-ion chromatograms. H: hexose; N: N-acetylhexose; S: N-acetylneuraminic acid; -itol: alditol; sc: control siRNA; si: ST3GAL1 siRNA. * Protonated molecules, [2+] doubly-charged molecules. O-glycan

Structure Mass-to-charg Retention Relative abundance e ratio (Composition) time (%) (m/z)* sc si

sialyl-3T

512.31

23.8

11.4

22.6

NeuAcα6(Galβ3)GalNAc (S1H1N1-itol)

873.48,

31.2

6.0

17.2

33.6

62.4

36.1

37.3

12.7

9.9

7.4

14.1

32.8

0.2

0.5

661.86

37.9

0.2

0.6

961.53

31.2

0.8

3.1

[2+]

37.0

3.4

3.3

[2+]

37.4

1.0

3.9

[2+]

41.2

1.9

2.7

NeuAcα3Galβ3GalNAc (S1H1N1-itol)

disialyl-T

NeuAcα3Galβ3(NeuAcα6)GalNAc (S2H1N1-itol) total core 1 elongation & core 2 branching Galβ4GlcNAcβ3Galβ3GalNAc (H2N2-itol) sialyl-elongated core 1 NeuAcα3Galβ4GlcNAcβ3Galβ3GalNAc (S1H2N2-itol) galactosyl-core 2 Galβ4GlcNAcβ6(Galβ3)GalNAc (H2N2-itol) sialyl-(galactosyl-)core 2 NeuAcα3Galβ3(Galβ4GlcNAcβ6)GalNAc (S1H2N2-itol) sialyl-galactosyl-core 2 NeuAcα3Galβ4GlcNAcβ6(Galβ3)GalNAc (S1H2N2-itol) disialyl-core 2 NeuAcα3Galβ4GlcNAcβ6(NeuAcα3Galβ3)GalNAc (S2H2N2-itol)

[2+]

437.24 873.48,

[2+]

437.24

[2+]

617.83

961.53

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elongated core 1

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sialyl-6T

Galβ3GalNAc (H1N1-itol)

SC

T (core 1)

[2+]

661.86 661.86 842.44

Figure legends ACCEPTED MANUSCRIPT Figure 1. Identification of GFRA1 as a ST3GAL1 target protein. (A) Cell extracts from MCF7 cells transfected with control or ST3GAL1 siRNA were separated and immunoblotted with PNA lectin. (B) ST3GAL1 mRNA expression was determined by qPCR analysis and expression of GAPDH was used as internal control. (C) Cell extracts from MCF7 cells transfected with control or ST3GAL1 siRNA were separated and immunoblotted with anti-ST3GAL1 antibody. The expression

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of actin was used as internal control. Numbers underneath immunoblots represent normalized protein amount. (D) Cell extracts from MCF7 cells transfected with control or ST3GAL1 siRNA were immunoprecipitated with GFRA1 antibody and immunoblotted with biotinylated PNA lectin or GFRA1 antibody. The PNA or GFRA1 expression level from ST3GAL1 siRNA transfected cell lysates was normalized to control siRNA transfected cell lysates. Numbers underneath immunoblots represent normalized protein amount. sc: scramble siRNA control; si: ST3GAL1 siRNA. ***P < 0.001.

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Figure 2. ST3GAL1 regulates GDNF-mediated phosphorylation signaling and cell growth in MCF7 cells.

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(A) Cells were transfected with control or ST3GAL1 siRNA, followed by 10 ng/ml GDNF incubation at the indicated times. Cell extracts were immunoblotted with indicated antibodies. Representative images are shown. The intensity of each phosphoprotein was normalized to total individual protein. The relative fold of each phosphoprotein/total protein was presented as histograms with SD. Multiple comparisons after two-way ANOVA were used for analysis. (B) Specific gene expression was determined by qPCR analysis and expression of GAPDH was used as internal control. The data represent the mean of three experiments. (C) Control or ST3GAL1 siRNA transfected MCF7 cells were serum-starved overnight, followed by incubation

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with 10 ng/ml GDNF for 15 min. GFRA1 and RET were co-immunoprecipitated from cell lysates as shown by western blotting analysis. In the left panel, the intensity of co-immunoprecipitated GFRA1 was normalized to immunoprecipitated RET first, and then normalized to the ratio of co-immunoprecipitated GFRA1/RET of control cells without GDNF treatment. In the right panel, the intensity of co-immunoprecipitated RET was

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normalized to immunoprecipitated GFRA1 first, and then normalized to the ratio of co-immunoprecipitated RET/GFRA1 of control cells. Numbers underneath immunoblots represent normalized protein amount. Images shown are representative of three experiments. (D) Control or ST3GAL1 siRNA transfected MCF7 cells cultured in serum free media with or without GDNF were monitored for three days using the

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xCELLigence System. Lines are means of six replicates. (E) Cell growth of control pVoid or ST3GAL1 shRNA transfected MCF7 cells treated with DMSO (control), vandetanib (10 µM) and/or tamoxifen (10 µM) were monitored for 72 h using xCELLigence System. Images shown are representative of three experiments. sc: control scramble siRNA; si: ST3GAL1 siRNA; p: control pVoid shRNA; sh: ST3GAL1 shRNA; Tam: tamoxifen; Van: vandetanib. *P < 0.05; **P < 0.01; ***P < 0.001. Figure 3. Higher expression of ST3GAL1 correlates with poorer outcome in patients with stage 3-4 breast cancer. Kaplan-Meier graphs of relapse-free survival (RFS) for breast cancer were shown in relation to mRNA expression levels of ST3GAL1 and GFRA1. Expression levels of ST3GAL1, GFRA1 were stratified to high and low, according to ROC analysis. High expression of ST3GAL1 (red) and low expression of both ST3GAL1 (blue) in relation to RFS are shown in 114 patients with breast cancer (A), 73 patients with grade 3 breast cancer (B), and 35 patients with stage 3-4 breast cancer (C). (D) Low expression of ST3GAL1 and high expression of GFRA1 (blue) vs high expression of ST3GAL1 and high expression of GFRA1 (red) in relation to

RFS are shown in 82 patients with breast cancer. (E) Low expression of ST3GAL1 and low expression of ACCEPTED MANUSCRIPT GFRA1 (blue) vs high expression of ST3GAL1 and low expression of GFRA1 (red) in relation to RFS are shown in 32 patients with breast cancer. High expression of both ST3GAL1 and GFRA1 (red), low expression of both ST3GAL1 and GFRA1 (blue) and others (green) in relation to RFS are shown in 114 patients with breast cancer (F), and 74 patients with grade 3 breast cancer (G). (H) Low expression of both ST3GAL1 and GFRA1 (blue) and others (red) in relation to RFS is shown in 80 patients with stage 2-4 breast cancer. The log-rank (Mantel-Cox) test P values are shown.

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Figure 4. GDNF stimulated ST3GAL1 transcription via an AKT-dependent pathway. (A) MCF7 cells were serum-starved overnight, followed by incubating with indicated concentration of GDNF

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for 2 h. ST3GAL1 mRNA levels relative to GAPDH mRNA level were determined by qPCR analysis. (B) Cells were serum-starved overnight and then treated with indicated inhibitors for 30 min, followed by adding GDNF in the presence of control (DMSO) or the following inhibitors, LY294002 (PI3K) and AKT1/2i. ST3GAL1 mRNA levels relative to GAPDH mRNA level were determined by qPCR analysis.

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(C) Serum starved cells were treated with different concentration of Sp1 inhibitor, MMA for 30 min, followed by adding GDNF for indicated times. ST3GAL1 mRNA levels relative to GAPDH mRNA level were determined by qPCR analysis. *P < 0.05; **P < 0.01; ***P < 0.001. Figure 5. GDNF stimulated Sp1 binding to the ST3GAL1 promoter through the AKT Pathway. (A) Structure of the ST3GAL1 gene promoter and locations of PCR primer pairs used to amplify the ST3GAL1 promoter region spanning the Sp1 binding sites for ChIP assays. (B) MCF7 cells were serum-starved

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overnight and treated with or without GDNF for 2 h. The precleared chromatin was immunoprecipitated with control rabbit IgG or anti-Sp1 rabbit antibodies. ST3GAL1 promoter sequences containing Sp1 sites were detected by PCR amplification of the ChIP DNA using specific primer pairs. Total chromatin before immunoprecipitation was used as input control. Arrow: the PCR product using p1 primers. The lower band

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of the p1 PCR products is primer dimer. (C and D) Serum-starved cells were treated with or without AKT1/2 inhibitor for 30 min, followed by GDNF treatment for another 2 h. Sp1 total proteins were immunoprecipitated using anti-Sp1 antibodies from cell lysates, followed by western blotting. Phosphorylation on Sp1 were immunoblotted with (C) anti-phospho threonine of (D) anti-phospho serine

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antibodies and total Sp1 protein was immunoblotted using anti-Sp1 antibodies. (E) The precleared chromatin was immunoprecipitated with anti-Sp1 rabbit antibodies. ST3GAL1 promoter sequences containing Sp1 sites were detected by PCR using specific primers. Total chromatin before immunoprecipitation was used as input control. Arrow: the PCR product using p1 primers. Representative images are shown. p1: primer pair 1; p2: primer pair 2. Figure 6. NanoLC-ESI-MS/MS analyses of O-glycan profiles on HA-GFRA1 purified from MCF7 cells. (A) Extracted-ion chromatographs (EIC) of O-glycan profiles on HA-GFRA1 purified from control (sc) and ST3GAL1 (si) siRNA transfected MCF7 cells. The peak intensities were reconstituted by molecular mass at 2+

m/z 512.31, 873.48, 437.24 ([M+2H] ), 617.83 and 842.44 within 10 ppm mass tolerance, which represented O-glycan structures of T antigen, siayl-3/6T, disialyl-T and disialyl-core 2 as shown. The colored symbol and nomenclature for glycan structure representation followed the instructions provided by the Consortium for Functional Glycomics (Varki et al., 2015). (B) ESI-MS/MS spectra indicated that structural

isomers of sialyl-6T and sialyl-3T were separated at retention time (RT) 31.2 and 33.6, respectively. The ACCEPTED MANUSCRIPT left-pointing blue arrows represent fragment ions with subsequential neutral-loss of CH3OH. The fragmentation was annotated according to the Domon and Costello nomenclature (Domon and Costello, 1988). (C) Relative abundance of O-glycans derived from HA-GFRA1 purified from control or ST3GAL1 siRNA transfected MCF7 cells. The relative abundance of each glycoform is given as a percentage (%) of the total sum of integrated peak areas from the EICs as shown in Table 1. Total intensity of core 1 elongation and core 2 branching O-glycans were added as shown.

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Figure 7. Proposed model showing the signaling network between ST3Ga1 and GDNF/GFRA1/RET in breast cancer cells.

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Based on previous reports and our data from this study, we propose the following model: In GFRA1/RET-positive MCF7 cells, ST3GAL1 silencing greatly impedes GDNF-induced phosphorylation and activation of downstream kinases signaling, which leads to a decreased cell proliferation rate. Furthermore, activation of PI3K/AKT contributes to phosphorylation and increased promoter binding activity of Sp1 on

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ST3GAL1 promoter to enhance the transcription of ST3GAL1, suggesting positive feedback regulation between ST3GAL1 and GFRA1 receptor in breast cancer cells.

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ACCEPTED MANUSCRIPT Highlights ST3GAL1 silencing inhibits GDNF-induced activation of downstream kinases ST3GAL1-mediated O-linked sialylation of GFRA1 promotes its interaction with RET GDNF upregulates transcription of ST3GAL1 by Sp1 through GFRA1/RET/PI3K/AKT pathway

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ST3GAL1 knockdown augments anti-cancer efficacy of inhibitors of RET and/or ER

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The authors declare that they have no conflict of interest.