A n In Vivo Functional Screen Identiﬁ es …...A n In Vivo Functional Screen Identiﬁ es ST6GalNAc2 Sialyltransferase as a Breast Cancer Metastasis Suppressor Nirupa Murugaesu 1,

RESEARCH ARTICLE

304 | CANCER DISCOVERY�MARCH 2014 www.aacrjournals.org

RESEARCH ARTICLE

An In Vivo Functional Screen Identifi es ST6GalNAc2 Sialyltransferase as a Breast Cancer Metastasis Suppressor Nirupa Murugaesu 1 , Marjan Iravani 1 , Antoinette van Weverwijk 1 , Aleksandar Ivetic 2 , Damian A. Johnson 1 , Aristotelis Antonopoulos 3 , Antony Fearns 1 , Mariam Jamal-Hanjani 1 , David Sims 1 , Kerry Fenwick 1 , Costas Mitsopoulos 1 , Qiong Gao 1 , Nick Orr 1 , Marketa Zvelebil 1 , Stuart M. Haslam 3 , Anne Dell 3 , Helen Yarwood 1 , Christopher J. Lord 1 , Alan Ashworth 1 , and Clare M. Isacke 1

ABSTRACT To interrogate the complex mechanisms involved in the later stages of cancer metastasis, we designed a functional in vivo RNA interference (RNAi) screen

combined with next-generation sequencing. Using this approach, we identifi ed the sialyltransferase ST6GalNAc2 as a novel breast cancer metastasis suppressor. Mechanistically, ST6GalNAc2 silenc-ing alters the profi le of O -glycans on the tumor cell surface, facilitating binding of the soluble lectin galectin-3. This then enhances tumor cell retention and emboli formation at metastatic sites leading to increased metastatic burden, events that can be completely blocked by galectin-3 inhibition. Critically, elevated ST6GALNAC2 , but not galectin-3, expression in estrogen receptor–negative breast cancers signifi cantly correlates with reduced frequency of metastatic events and improved survival. These data demonstrate that the prometastatic role of galectin-3 is regulated by its ability to bind to the tumor cell surface and highlight the potential of monitoring ST6GalNAc2 expression to stratify patients with breast cancer for treatment with galectin-3 inhibitors.

SIGNIFICANCE: RNAi screens have the potential to uncover novel mechanisms in metastasis but do not necessarily identify clinically relevant therapeutic targets. Our demonstration that the sialyltrans-ferase ST6GalNAc2 acts as a metastasis suppressor by impairing binding of galectin-3 to the tumor cell surface offers the opportunity to identify patients with breast cancer suitable for treatment with clinically well-tolerated galectin-3 inhibitors. Cancer Discov; 4(3); 304–17. ©2014 AACR.

See related commentary by Ferrer and Reginato, p. 275.

on June 15, 2020. © 2014 American Association for Cancer Research. cancerdiscovery.aacrjournals.org Downloaded from

Published OnlineFirst February 11, 2014; DOI: 10.1158/2159-8290.CD-13-0287

http://cancerdiscovery.aacrjournals.org/

MARCH 2014�CANCER DISCOVERY | 305

INTRODUCTION

When breast carcinomas remain confi ned to breast tissue, cure rates exceed 90% ( http://seer.cancer.gov/csr/1975_2006/ ). However, if the cancer disseminates throughout the body, long-term survival decreases depending upon the extent of, and the sites of, colonization. Metastases in visceral organs and the brain are the most life threatening, with 5-year sur-vival rates usually less than 20% ( 1 ). There is an urgent need to identify genes that control the different stages of the meta-static process in order to aid in the development of metastatic biomarkers and provide potential targets for the treatment and prevention of metastatic disease ( 2 ).

Authors’ Affi liations: 1 The Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research; 2 Cardiovascular Division, King’s College London, British Heart Foundation Centre for Research Excellence, James Black Centre; and 3 Division of Molecular Biosciences, Imperial College London, London, United Kingdom

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

N. Murugaesu and M. Iravani contributed equally to this work.

Current address for N. Murugaesu and M. Jamal-Hanjani: UCL Cancer Institute, University College London, London, United Kingdom. Corresponding Authors: Clare M. Isacke, The Institute of Cancer Research, 237 Fulham Road, London SW3 6JB, United Kingdom. Phone: 44-20-7153-5510; Fax: 44-20-7153-5340; E-mail: [email protected] ; and Nirupa Murugaesu, UCL Cancer Institute, 72 Huntley Street, London WC1E 6DD, United Kingdom. Phone 44-20-3103-2202; E-mail: [email protected] doi: 10.1158/2159-8290.CD-13-0287 ©2014 American Association for Cancer Research.

Genetic screens, such as those that exploit RNA interfer-ence (RNAi), provide an unbiased approach to the identi-fi cation of genes associated with a phenotype of interest ( 3–6 ). Although cell-based RNAi screens have been highly informative in identifying genes involved in tumor cell survival, migration, and invasion ( 4 , 7–9 ), these in vitro approaches are largely unsuitable for interrogating the later stages of the metastatic process, in particular tumor cell dissemination, tumor cell extravasation from the circula-tion, and colonization of secondary sites. More recent RNAi screens performed in animal models have provided impor-tant new insights into in vivo tumor biology ( 3–6 ); however, there has, to date, been only one published in vivo RNAi





Murugaesu et al.RESEARCH ARTICLE

screen to identify novel determinants of the metastatic process in solid tumors ( 5 ). In contrast to this published study, which used a zero-event model, we have developed an in vivo metastasis short hairpin (sh) RNAi screen combined with massive parallel sequencing to identify enrichment of novel determinants involved in the later stages of breast cancer metastasis. Using this functional approach, we have identifi ed the sialyltransferase ST6GalNAc2 as a novel and clinically relevant metastasis suppressor and uncovered the mechanism by which it promotes tumor cell colonization of secondary tissues.

RESULTS

An In Vivo Screen for Genes that Modulate Metastasis

The aim of this study was to develop an in vivo RNAi screen focused on identifying genes involved in the later stages of the metastatic process. A major benefi t of undertak-ing a pooled shRNA screen combined with next-generation sequencing is the ability to determine the change in repre-sentation of the different shRNAs in the resulting metastatic tumors. The 4T1 mouse mammary tumor cell line inoculated intravenously into syngeneic BALB/c mice was used for the RNAi screen, as it provides a robust model of tumor cell colonization in an immunocompetent setting. As opposed to a zero-event model, this approach allowed us to identify individual shRNAs enriched in the metastatic tumors due to their ability to confer an advantage to tumor cells in the later stages of the metastatic cascade.

In brief, the screen protocol was as follows ( Fig. 1A ): mouse mammary 4T1 tumor cells carrying a luciferase expression construct (4T1-Luc) were infected with pools of virally packaged shRNA-coding constructs of the mouse Cancer 1000 shRNA library, encompassing ∼2,200 indi-vidual constructs designed to target ∼1,000 genes ( 10 ). Cells infected with library pools were inoculated via the tail vein into groups of 3 BALB/c mice, and, 21 days later, tumor-bearing lungs were recovered. Genomic DNA (gDNA) was isolated from the tumor-bearing lungs and from the preinoculation shRNA-infected 4T1-Luc cells, PCR amplifi ed, and subject to massively parallel sequenc-ing. To determine the extent of shRNA enrichment in each tumor-bearing lung sample, and thus the contribution of each gene-silencing effect to the metastatic process, shRNA frequency in the lung samples was compared with shRNA-infected, preinoculation 4T1-Luc cells, and the preinocula-tion 4T1-Luc cells were compared to the original shRNA plasmid preparation.

The sensitivity of pooled RNAi screens is in part deter-mined by the complexity of the shRNA pools used ( 11 ). To determine the optimal pool size, uninfected 4T1-Luc cells (Luc + , GFP − ) and 4T1-Luc cells infected with control shRNA constructs (Luc + , GFP + ) were mixed at defi ned ratios, and 0.5 × 10 6 cells were inoculated into the tail vein of mice. Twenty-one days later, bioluminescent imaging indicated an equivalent level of lung tumor burden in the different groups ( Fig. 1B ). By counting the number of superfi cial GFP + nodules, it was calculated that the lungs contained a minimum of 500 independent metastatic tumors. Further-

more, the observation that the GFP + nodules in the 1:20 and 1:50 dilution samples were scattered evenly throughout the lungs suggested that the majority of tumors arose from individual inoculated cells rather than from locally invad-ing/reseeded lung tumors. To generate statistically powered data, we aimed for at least a 10-fold greater number of lung tumors than number of shRNAs in each pool. Con-sequently, the in vivo screen was performed with 48 pools of the Cancer 1000 library, each containing 48 different shRNA constructs.

On the basis of the criteria described in Methods, 12 hits were identifi ed from the screen ( Fig. 1C ). To validate this screening strategy, shRNAs targeting four of these genes (denoted in bold in Fig. 1C ) were individually retested for their ability to promote tumor-cell colonization of the lung. To mitigate for shRNA off-target effects, cells were also infected with independent targeting shRNAs or non-targeting control (NTC) shRNAs. In each case, targeting shRNAs effi ciently silenced gene expression and, when inoc-ulated into mice, the shRNA knockdown cells signifi cantly increased lung tumor burden as monitored by IVIS ( in vivo imaging system) imaging ( Fig. 2A ; Supplementary Figs. S1A and S1B and S2A).

ST6GalNAc2 as a Novel Metastasis Suppressor in Mouse and Human Breast Cancer Models

Of the hits, ST6GalNAc2 (alpha-N-acetylgalactosaminide alpha-2,6-sialyltransferase 2) was subjected to further inves-tigation. ST6GalNAc2 is a type II transmembrane Golgi-localized enzyme that catalyzes the attachment of sialic acid in an α2-6 linkage to N-acetylgalactosamine (GalNAc) on O -glycans ( 12 ). Although it is well recognized that tumor cells display altered cell surface sialylation ( 13, 14 ), little is known about how variant sialylation can modulate tumor cell behav-ior and, in particular, altered metastatic potential in vivo . 4T1-Luc cells infected with shRNAs targeting St6galnac2 dis-played an increased lung tumor burden as assessed by in vivo and ex vivo IVIS imaging and by lung weight ( Fig. 2A ). His-tologic and quantitative PCR (qPCR) analysis confi rmed the presence of tumors throughout the lungs with no evidence of lung edema ( Fig. 2A , right; Supplementary Fig. S2B) and the retained downregulation of St6galnac2 expression in vivo (Supplementary Fig. S2C). Furthermore, St6galnac2 down-regulation in 4T1-Luc cells ( Fig. 2B ) and parental 4T1 cells (Supplementary Fig. S2D) resulted in increased secondary site colonization in a spontaneous metastasis assay while hav-ing no effect, at any time point examined, on primary tumor growth in vivo or on cell viability and colony-forming ability in vitro (Supplementary Fig. S2E and S2F). This increased tumor burden following St6galnac2 silencing was not specifi c to the lung. Three weeks after intrasplenic inoculation, 4T1-Luc cells with downregulated St6galnac2 expression gave rise to a signifi cantly increased tumor burden in the liver as moni-tored by ex vivo IVIS imaging, liver weight, and histologic analysis ( Fig. 2C ).

To independently and directly validate the metastasis-sup-pressive effect of ST6GalNAc2, an alternative gain-of- function approach was taken. St6galnac2 was stably transfected into human MDA-MB-231 breast cancer cells, which have very low endogenous ST6GALNAC2 expression (Supplementary





An In Vivo Functional RNAi Late-Stage Metastasis Screen RESEARCH ARTICLE

Figure 1. In vivo shRNA screening strategy. A, schematic of high-throughput screening (HTS). B, 4T1-Luc cells infected with control shRNAs (Luc + , GFP + ) were mixed with uninfected 4T1-Luc cells (Luc + , GFP − ) at the indicated ratios. A total of 0.5 × 10 6 cells were injected into the tail veins of BALB/c mice (3 mice/group). On day 21, animals were IVIS imaged in vivo and the lungs were removed at necroscopy. The IVIS imaging (left) and bright fi eld imag-ing of the lungs (middle) shows equivalent tumor burden in all animals. Right, GFP + lung metastases (arrowheads). C, table showing the screen hits. As described in Methods, the log ratio ( Z score) of tumor to preinoculation 4T1-Luc cells was calculated individually for mouse A, B, and C. Shown in red are Z scores >2, shown in bold are hits that were taken forward for in vivo validation.

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Fig. S3A). Ectopic St6galnac2 expression signifi cantly attenu-ated the metastatic potential of MDA-MB-231 cells in vivo as monitored by ex vivo IVIS imaging and histologic examination of lungs 5 weeks after intravenous injection ( Fig. 2D ), but had no impact on in vitro cell proliferation (Supplementary Fig. S3B).

Clinical Signifi cance of ST6GalNAc2 in Breast Cancer

Next, to address the clinical relevance of our in vivo models, ST6GALNAC2 expression was analyzed in the human breast cancer datasets present in the ROCK database ( 15 ). In 9 of 10 gene expression datasets examined, signifi cantly lower lev-els of ST6GALNAC2 expression were associated with estrogen receptor–negative (ER − ) breast tumors compared with estro-gen receptor–positive (ER + ) breast tumors ( Fig. 3A ). Similarly, ST6GALNAC2 expression was signifi cantly lower in ER − com-pared with ER + breast cancer cell lines ( Fig. 3A , fi nal). To assess whether ST6GALNAC2 expression affects survival outcome in ER − patients, a meta-analysis was performed across the 10 clini-cal datasets and in two additional datasets of ER − breast cancers

(ref. 16 ; total of 551 patients). Within these ER − cohorts, higher expression of ST6GALNAC2 signifi cantly correlated with improved survival outcome [overall rate ratios (RR), 0.67; 95% confi dence interval (CI), 0.48–0.93; P = 0.017; Fig. 3B ].

ST6GalNAc2 Silencing Promotes Galectin-3 Binding and Retention of Tumor Cells in the Lung

To interrogate the mechanisms linking variant sialylation to increased metastasis, we fi rst undertook matrix-assisted laser desorption/ionization–time-of-fl ight (MALDI-TOF) gly-comic analysis of the cell surface O -glycans isolated from cells transfected with siRNA oligonucleotides targeting St6galnac2 (si ST6 ) or NTC siRNA oligonucleotides (siNTC; Supplemen-tary Fig. S4A). Examination of the spectra ( Fig. 4A ) revealed that St6galnac2 silencing resulted in changes in the relative abundance of the O -glycans, compared with control siNTC-transfected cells, of which the main characteristics were as fol-lows: (i) an increase in unmodifi ed core 1 O -glycan (also known as T antigen; Galβ1-3GalNac; m / z 534) and (ii) a reduction in the α2-3,α2-6 disialyl core 1 O -glycan ( m / z 1,256). Interestingly,






Figure 2. Validation of St6GalNAc2 as a metastasis suppressor gene. A, 0.5 × 10 6 4T1-Luc cells infected with NTC shRNA (shNTC-A) or St6galnac2 shRNAs (sh ST6 -A, sh ST6 -B; see Supplementary Fig. S2A for qPCR analysis) were inoculated into the tail veins of BALB/c mice. On day 21, lungs removed at necroscopy were subjected to ex vivo IVIS imaging and weighed. Data shown are from 5 or 6 mice per group ±SEM. Student t test was used to generate P values. There was no statistical difference between the sh ST6 -A and sh ST6 -B groups ( P = 0.48, IVIS; P = 0.19, lung weight). Middle, ex vivo biolumines-cent images of excised lungs. Right, representative histologic sections illustrating the increase in lung tumor burden in the sh ST6 mice and the absence of detectable lung edema (see Supplementary Fig. S2B). Scale bar, 1 mm. Equivalent results were obtained in three independent experiments; for example, see Fig. 7C . B, 1.5 × 10 5 4T1-Luc cells were inoculated in female BALB/c mice. Primary tumor volume was measured until tumors reached the maximum allowable size (day 39), P = ns (not signifi cant) at all time points. Metastases were quantifi ed as percentage of tumor area in the lung from hematoxylin and eosin (H&E) sections. Data shown are from 7 animals in each group ±SEM. Two-way ANOVA used to generate P values. (continued on following page)

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no core 2 glycan structures were detected in either siNTC or si ST6 cells; tandem mass spectrometry (MS-MS) analysis (data not shown) revealed that the ions at m / z 983, 1,187, 1,344, and 1,793 corresponded to core 1 O -glycan structures extended with LacNAc residues. This lack of core 2 glycans is consistent with our gene expression profi ling, in which 4T1 cells showed negligible expression of the core 2 β1-6 N -acetylglucosaminyl-transferases (C2GnTs) that are required for the addition of GlcNAc in a β1-6 linkage to core 1 (data not shown).

Given the increase in unmodifi ed core 1 O -glycan (T anti-gen) following St6galnac2 silencing, we next investigated whether loss of St6galnac2 expression resulted in increased binding of galectin-3. Galectin-3 belongs to the family of soluble S-type lectins with β-galactoside binding specifi city ( 17 ) and has been reported to bind core 1 glycan present on tumor cell surface glycoproteins ( 18, 19 ). Little binding of recombinant galectin-3 (GST-GAL3) was observed in the siNTC-treated 4T1-Luc cells, but cell surface binding was strongly enhanced following St6galnac2 downregulation ( Fig. 4B ). As galectin-3 can promote tumor cell:endothelial cell interactions ( 18–22 ), the physiologic relevance of ST6Gal-NAc2-modulated O -glycosylation was then assessed in an in vivo lung retention assay that monitors tumor cell arrest in

the vasculature. si ST6 - and siNTC-transfected 4T1-Luc cells (Supplementary Fig. S4A) or sh ST6 and shNTC 4T1-Luc cells were labeled with CellTracker red or green dyes and inoculated in a 1:1 ratio into mice via the tail vein, and lungs were har-vested at 1 or 24 hours for examination by confocal microscopy. One hour after inoculation, there was no signifi cant difference in the number of cells present in the lungs, but at 24 hours, there was a signifi cant increase in the retention of si ST6 ( Fig. 5A ) or sh ST6 ( Fig. 5B ) cells compared with the siNTC and shNTC cells. Importantly, in a rescue experiment, this increased lung retention was abrogated by expression of human ST6GALNAC2 ( Fig. 5C and Supplementary Fig. S4B and S4C), directly eliminating off-target effects of the shRNAs.

Next, to address whether increased cell surface galectin-3 promotes the observed si ST6 -mediated tumor cell seeding in the lungs, 4T1-Luc cells were cotransfected with siRNA oligonucleotides targeting St6galnac2 and Lgals3 (galectin-3, si GAL3 ; Supplementary Fig. S4D). si GAL3 cotransfection effectively impaired the si ST6 -mediated increase in tumor cell retention in the lungs, but had no impact on retention of siNTC-transfected cells ( Fig. 5D ; Supplementary Fig. S4E).

To validate these observations, these assays were extended to three human breast cancer cell lines: MDA-MB-453 and






ZR75.1 cells that express high levels of ST6GALNAC2 , and MDA-MB-231 cells that have low-level expression (Sup-plementary Fig. S3A). si ST6 transfection of MDA-MB-453 and ZR75.1 cells resulted in an effi cient downregulation of ST6GalNAc2 mRNA and protein expression and signifi -cantly increased retention of both tumor cell lines in the lung ( Fig. 5E and Supplementary Fig. S5A–S5D). In contrast, si ST6 transfection of the low-expressing MDA-MB-231 cells had no impact on tumor cell retention ( Fig. 5F and Sup-plementary Fig. S5D), demonstrating that the phenotype observed with the si ST6 oligonucleotides is not due to an off-target effect. As observed for the 4T1-Luc cells, cotrans-fection of MDA-MB-453 cells with si GAL3 oligonucleotides effectively reversed the enhanced lung retention observed in si ST6 -transfected cells ( Fig. 5G and Supplementary Fig. S5E). Consistent with the hypothesis that reduced ST6GALNAC2 expression promotes galectin-3 binding, in the MDA-MB-231 cells, which have endogenously low-level ST6GALNAC2 expression, si GAL3 transfection alone or ectopic St6galnac2 expression signifi cantly attenuated the retention of cells ( Fig. 5H and I and Supplementary Fig. S5F and S5G). Importantly, treatment with a clinically relevant galectin-3 inhibitor, GCS-100 ( 23, 24 ), specifi cally inhibited the retention of control MDA-MB-231 cells in the lung but had no impact on the retention of MDA-MB-231 cells with stable ectopic St6galnac2 expression ( Fig. 5I and Supplementary Fig. S5G).

Inhibition of Galectin-3 Blocks the Increased Metastasis of Cells with Low-Level ST6GalNAc2 Expression

The data presented indicate a model in which tumor cells expressing low-level ST6GalNAc2 have an increased level of unmodifi ed core 1 O -glycan facilitating increased binding of galectin-3 to the cell surface ( Fig. 6A ), and increased reten-tion of tumor cells at sites of metastasis ( Fig. 5 ). It has been proposed that fi rm adhesion to the vasculature at metastatic sites is preceded by low-affi nity interactions, and that effi cient metastatic colonization is aided by the formation of tumor cell aggregates ( 25–27 ). Consequently, we next addressed the role of ST6GalNAc2 expression and galectin-3 binding under dynamic fl ow conditions. When a mixed suspension of shNTC- and sh ST6 -infected ZR75.1 cells (Supplementary Fig. S5A) were perfused across a monolayer of human umbili-cal vein endothelial cells (HUVEC), there was a signifi cant increase in the number of sh ST6 cells fi rmly adhered to the endothelium ( Fig. 6B , top, and Supplementary Movie S1). Importantly, this increased adhesion of sh ST6 ZR75.1 cells was completely abrogated in the presence of the galec-tin-3 inhibitor GCS-100 ( Fig. 6B , bottom and Supplementary Movie S2). Furthermore, in static adhesion assays, down-regulation of St6galnac2 expression in 4T1-Luc cells resulted in a signifi cant increase in adhesion to both HUVECs and

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Figure 2. (Continued) C, 0.5 × 10 6 shNTC-A or sh ST6 -A 4T1-Luc cells were inoculated into the spleen of BALB/c mice. On day 21, livers were weighed at necroscopy and subjected to ex vivo IVIS imaging. Data shown are from 5 or 6 mice per group ±SEM. Student t test was used to generate P values. Representative images of liver metastases are shown. Scale bar, 250 μm. D, 2 × 10 6 MDA-MB-231-Luc cells expressing ectopic St6galnac2 (231-ST6) or vector-alone infected (231-Vec) were inoculated into the tail veins of CB17 NOD.SCID mice. At 5 weeks, lungs were subjected to ex vivo IVIS imaging at necroscopy. Data shown are from 13 to 14 mice per group ±SEM. Student t test was used to generate P values. Representative histology images are shown. Scale bar, 1 mm. Equivalent results were obtained in two independent experiments.






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Figure 3. High levels of ST6GALNAC2 expression correlate with increased survival in patients with breast cancer. A, correlation of ST6GALNAC2 normalized expression level between ER + and ER − breast tumors and cell lines (fi nal) in the Breast Cancer Gene Expression Datasets (ROCK). Student t test was used to generate P values. B, forest plot showing meta-analysis of ST6GALNAC2 expression and survival outcome in the ER − tumors from the same datasets and in two additional datasets (GSE31519, GSE5327) of ER − breast cancers (total of 551 patients). See Methods for statistical analysis. ns, not signifi cant.

immortalized mouse endothelial cell (sEND) monolayers ( Fig. 6C ), and this adhesion was attenuated either by cotrans-fection with si GAL3 oligonucleotides or incubation with the galectin-3 inhibitor lactose (Galβ1-4Glc; refs. 18 , 20 , 21 ; Fig. 6D ). Galectin-3 has a single S-type lectin domain but is unique in the galectin family by being able to pentamerize once it has bound to a ligand ( 28 ), allowing it to mediate homotypic, as well as heterotypic, cell aggregation (refs. 20 , 22 , 29 ; Fig. 6A ). Analysis of confocal images collected in the lung retention assays ( Fig. 5 and Supplementary Figs. S4 and S5) revealed a signifi cant increase in the proportion of si ST6 - versus siNTC-transfected 4T1-Luc, MDA-MB-453, and ZR75.1 cells forming tumor cell aggregates in the lungs (Sup-plementary Fig. S6), and this increase in tumor emboli was fully attenuated by cotransfection with si GAL3 ( Fig. 6E and F ).

ST6GalNAc2 Expression Determines Responsiveness to Galectin-3 Inhibition

There have been numerous reports describing a role for galectin-3 in tumor progression and metastasis ( 17 , 30 , 31 ); however, there are confl icting data about the value of galec-tin-3 as a prognostic factor either in gene expression profi ling of human tumor samples or by monitoring protein levels in serum ( 32–35 ). In Fig. 3 , we show by meta-analysis of different datasets that higher expression of ST6GALNAC2 in ER − tumors

correlates with improved survival outcome. In contrast, galec-tin-3 ( LGALS3 ) expression in the same datasets demonstrated no signifi cant association with ER status in human breast cancers or cell lines ( Fig. 7A ) and, more importantly, no association with survival outcome within the ER − group ( Fig. 7B ). This is in keeping with our mechanistic studies that indicate it is the level of galectin-3 bound to the cell surface as determined by ST6GalNAc2 activity, rather than galectin-3 expression per se , which underpins the role of galectin-3 in promoting metastasis ( Fig. 6A ). To test this directly, mice inoculated with sh ST6 - or shNTC-infected 4T1-Luc cells were treated with or without the galectin-3 inhibitor GCS-100 ( Fig. 7C ). GCS-100 completely blocked the enhanced met-astatic colonization observed in cells with downregulated St6galnac2 expression, but importantly had no effect on the lung tumor burden of mice inoculated with shNTC cells. Together, these data suggest that low expression of ST6GAL-NAC2 identifi es patients with ER − breast cancer who could be stratifi ed for treatment with a galectin-3 inhibitor.

DISCUSSION

Because of the complexity of the metastatic process, the development of experimental approaches for identifying meta-static biomarkers and therapeutic targets is challenging. The






Figure 4. Downregulation of St6galnac2 expression alters the cell surface O -glycome and promotes galectin-3 binding. A, cell surface O -glycan populations obtained from 4T1-Luc cells were transfected with a NTC siRNA (siNTC) or St6galnac2 siRNA (si ST6 ) oligonucleotides. St6galnac2 mRNA levels 72 hours posttransfec-tion were monitored by qPCR (Supplementary Fig. S4A). Transfected cells were analyzed as their permethylated derivatives by MALDI-TOF mass spectrometry. All molecular ions are [M+Na] + . Structures that show residues outside a bracket have not been unequivocally defi ned. Letters “M” and “vm” correspond to major and very minor constituents, respectively, with the former being at least 10 times more abundant than the latter. Data are shown from one set of experiments. Similar trends were found in a repeat experiment. Blue dotted line indicates the peak at m / z 1,187. B, siRNA-transfected 4T1-Luc cells were incubated with 0.5 μg/mL of GST-tagged human recombinant galectin-3 (GST-GAL3) for 1 hour at 37°C. Cells were fi xed, stained with a fl uorescein isothiocyanate (FITC)-conjugated anti-GST and 4′,6-diamidino-2-phenylindole (DAPI). Scale bar, 50 μm. Right, quantifi cation of GST-GAL3 binding repre-sented as the percentage of cells with GST-GAL3 binding >2 SD from background (cells incubated without GST-GAL3).

100A

B

80

Inte

nsity

%

534.1

895.2

vm

M1,256.3

1,344.3

1,793.4

siNTC

1,187.3

983.3

60

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nsity

%

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0500 800 1,100

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Mass (m/z)

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1,344.81,187.6

1,256.8

895.5

vm

M534.3

983.6

0500 800 1,100 1,400 1,700 2,000

Galactose

GaINAc

GIcNAc

NeuAc

siNTC siST6

40 P = 0.001

30

20

GS

T-G

AL3

bin

ding

(%

)

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0siNTC siST6

GST-GAL3

GST-GAL3DAPI

goal of this study was to integrate RNAi technology and mas-sively parallel sequencing in a well-established mouse model to rapidly discover and validate genes involved in breast cancer metastasis. The study described here demonstrates the feasi-bility of this approach and the identifi cation of ST6GALNAC2 as a novel breast cancer metastasis suppressor gene.

Our results indicate that the sialyltransferase ST6GalNAc2 functions to suppress seeding of tumor cells at secondary sites, a late stage in the metastatic process. Although there are numerous reports describing an altered cell surface O -glycome in tumor cells ( 13, 14 , 36 ), there have been no published reports of a role for ST6GalNAc2 in the breast cancer metastatic proc-ess. At least 20 human sialyltransferases have been identifi ed in the human genome, of which six catalyze the transfer of sialic acid to GalNAc ( 37, 38 ). Of these, ST6GalNAc1, 2, and 4 are active on glycoproteins, whereas ST6GalNAc3, 5, and 6 function to transfer sialic acid residues onto gan-gliosides. To date, the focus on GalNAc sialyltransferases in

cancer has been on ST6GalNAc1 and ST6GalNAc5. Expres-sion of ST6GalNAc5 is normally restricted to brain tissue but has been reported to be a specifi c mediator of breast cancer infi ltration across the blood–brain barrier, promoting the for-mation of brain, but not lung, metastases ( 39 ). ST6GalNAc1, which shows increased expression in breast cancers ( 40 ), is the major enzyme responsible for the production of the sim-ple mucin-type sialyl-Tn antigen (Neu5Acα2-6GalNAc- O -Ser/Thr). Sialyl-Tn is rarely observed in normal tissues but is abun-dant in a range of cancer types ( 37 ), including breast cancer, where expression is associated with poor prognosis ( 14 , 41–44 ). Given the increased sialyltransferase activity associated with many cancers, it was of interest that ST6GALNAC2 was identi-fi ed in our screen as a metastasis suppressor gene. Although ST6GalNAc2 is able to sialylate the Tn antigen in vitro , in vivo it preferentially transfers sialic acid to the 6 position of the T antigen/core 1 antigen (Galβ1-3 GalNAc) and the sialyl-3T antigen (NeuAcα2-3Galβ1-3GalNAc), to create the sialyl-6T






antigen [Galβ1-3(NeuAcα2-6)GalNAc] and the disialyl-T anti-gen [NeuAcα2-3Galβ1-3(NeuAcβ2-6)GalNAc], respectively ( 12 ). As demonstrated here, cells in which ST6GalNAc2 expression is downregulated show an increase in the unmodifi ed core 1 antigen and a reduction in the disialyl core 1 antigen.

Unmodifi ed core 1 O -glycan on the cell surface is a known ligand for galectin-3 ( 18, 19 ) and we show here that tumor cells with downregulated ST6GalNAc2 expression show enhanced binding of galectin-3 ( Fig. 6A ). Galectin-3 has been reported to be involved in many of the biologic processes associated with tumor progression and metastasis ( 31 ). Of these, there are robust data showing that galectin-3 binding to the core 1 anti-gen on tumor cells promotes increased tumor cell homotypic aggregation and heterotypic adhesion to the endothelium ( 18–22 , 29 ) and that galectin-3 binding can protect against anoikis-mediated apoptosis ( 31 ). Our studies further support such involvement of galectin-3, but in addition have extended the mechanistic understanding of its role. We show that in mouse and human breast cancer cells with high ST6GalNAc2 expression, inhibition of galectin-3 has no effect on binding to the endothelium in vitro , aggregation in the vasculature, or tumor burden in vivo . Galectin-3 inhibition is effective only if tumor cells have low-level ST6GalNAc2 expression. These data demonstrate that it is the expression of ST6GalNAc2 and not

galectin-3 that determines enhanced retention of tumor cells at metastatic sites and that a role for galectin-3 is regulated by the profi le of O -linked glycans on the cell surface that facili-tate galectin-3 binding.

Clinical trials using galectin-3 inhibitors report a good safety profi le ( 22–24 , 45 ). However, our meta-analysis dem-onstrates that galectin-3 expression levels do not correlate with clinical outcome or identify patients who would benefi t from treatment with a galectin-3 inhibitor. In contrast, our data indicate that monitoring ST6GalNAc2 expression in ER − breast tumors may identify patients who would benefi t from treatment with a galectin-3 inhibitor. Certainly, further studies examining ST6GalNAc2 as a potential biomarker for predicting metastases in ER − breast cancers are warranted.

METHODS

shRNA Library and In Vivo Screen We used a miR-30–based shRNA library in the LMS (LTR-driven

miR30 SV40-GFP MSCV-based vector) backbone targeting the Cancer 1000 gene set ( 10 ). Forty-eight separate virus batches were produced from plasmid pools each containing 48 individual shRNAs using retroviral-mediated gene transfer with Phoenix packaging cells (G. Nolan, Stanford University, Stanford, CA). 4T1-Luc cells (SibTech)

Figure 5. A role for galectin-3 in promoting lung colonization in ST6GalNAc2 -silenced cells. A, siNTC- and si ST6 -transfected 4T1-Luc cells were labeled with CellTracker red or green dyes, respectively, mixed at a 1:1 ratio, and 0.5 × 10 6 cells were inoculated into the tail veins of BALB/c mice. At 1 and 24 hours after inoculation, the lungs were extracted and imaged by confocal microscopy, and lung retention was quantifi ed. Data shown are mean tumor cell coverage per fi eld of view (fov) from 4 mice in each group ±SEM. Student t test was used to generate P values. Equivalent results were obtained in three independent experiments, including dye swap experiments. Right, representative confocal images. Scale bar, 200 μm. B, shNTC-A and sh ST6 -A 4T1-Luc cells were labeled with CellTracker green or red dyes, respectively, and lung retention quantifi ed as described in A. C, shNTC-A and sh ST6 -A 4T1-Luc cells were transiently transfected with human ST6GALNAC2 (hST6) or vector alone (VEC), labeled with CellTracker dyes, and lung retention quantifi ed as described in A. D, 4T1-Luc cells were transfected with siNTC or si ST6 in the presence or absence of Lgals3 siRNA (si GAL3 ) oligo-nucleotides. Transfected cells were labeled with CellTracker dyes and lung retention quantifi ed as described in A. (continued on following page)

25

20

15

10

5

01 h 24 h 1 h 24 h

shNTC -A + VEC shNTC-A + hST6shST6 -A + VEC shST6 -A + hST6

1 h

24 h

1 h

24 h

siST6

siST6

siNTC

A C

DB siNTC

siNTC + siGAL3 siST6 + siGAL3

P = nsP = ns

P = ns

P = ns P = ns

P = ns

P = 0.003

P = 0.004

P = ns

P = 0.008

P = 0.019

P = ns

4T1-

Luc

cell

cove

rage

/fov

(AU

)

4T1-

Luc

cell

cove

rage

/fov

(AU

)

25

20

15

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5

0

4T1-

Luc

cell

cove

rage

/fov

(AU

)

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50

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4T1-

Luc

cell

cove

rage

/fov

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)

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0

50

40

30

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0

1 h 24 h

1 h 24 h 1 h 24 h 1 h 24 h

shNTC -A

shST6 -A






were infected at a multiplicity of infection of 0.2. Infected 4T1-Luc populations were FACSorted for GFP + cells before 0.5 × 10 6 cells were injected into the tail veins of three 6- to 8-week-old female BALB/c mice (Harlan; Fig. 1A ) and were sacrifi ced at day 21. gDNA was extracted from the preinoculation 4T1-Luc cells and lung tumors using Puregene (Gentra Systems). The shRNA sequences were ampli-fi ed using primers (Supplementary Table S1) complementary to the shRNA constant regions that also encompass the p5 and p7 sequences. To enable suffi cient representation of each shRNA, multiple PCR reac-tions from the plasmid DNA, 4T1-Luc cells, and from the lung tumor DNA were performed in parallel. Parallel PCR products were concen-trated and purifi ed using the QIAquick Gel Extraction Kit.

High-Throughput Sequencing and Data Analysis Amplifi ed shRNA sequences were subject to massively parallel

sequencing on an Illumina GA IIx , using a procedure similar to that previously described ( 46, 47 ). Briefl y, after cluster generation and sequencing-by-synthesis on the Illumina GA IIx , raw image data were analyzed using GA pipeline v1.5. Short reads were aligned to the shRNA library reference sequences using a custom software pack-age shALIGN ( 48 ), allowing up to two mismatches to the reference sequence. On average, 94% of the short reads aligned to the refer-ence library. Statistical analysis of screen results was performed in R 2.9.0 ( http://www.r-project.org/ ) using the shRNAseq package ( 48 ). shRNAs with no predicted target, or with greater than two predicted targets, were removed from the analysis. Total reads per shRNA were log 2 transformed and median normalized per pool. Normalized scores from technical replicates were averaged, and the log ratio of

siNTCsiST6

siNTC siNTC 231-VEC + VEH 231-VEC + GCS-100231-ST6 + GCS-100231-ST6 + VEHsiST6 siGAL3

E G

F H I

siNTCsiNTC + siGAL3

siST6siST6 + siGAL3

P = ns

P = ns

P = ns

P = ns

P = nsP = ns

P = ns

P = 0.007

P = ns

P = ns

P = 0.014

P = nsP = 0.044

P = 0.018

MD

A-M

B-4

53 c

ell c

over

age/

fov

(AU

)

MD

A-M

B-2

31 c

ell c

over

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(AU

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31 c

ell c

over

age/

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(AU

)

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A-M

B-2

31 c

ell c

over

age/

fov

(AU

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ell c

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(AU

) 35

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Parental

ST6GalNAc2

β-COP

Merge

siNTCMDA-MB-453

siST6

tumor to preinoculation 4T1-Luc cells was calculated individually for mouse A, B, and C. Hits were defi ned as shRNAs that had increased in representation by two SDs ( Z score >2) in two or more of the replicate tumor samples compared with the 4T1-Luc sample and had a Z score ≤−1 when comparing the 4T1-Luc sample to the plasmid sample.

Cell Culture All human cell lines were obtained from American Type Culture

Collection (ATCC) and short tandem repeat (STR) tested every 4 months using StemElite ID System (Promega). 4T1-Luc cells were cul-tured in RPMI-1640; ZR75.1, MDA-MB-453, MDA-MB-231 (ATCC), MDA-MB-231-Luc (SibTech Inc.), and sEND immortalized mouse skin endothelial cells were cultured in Dulbecco’s Modifi ed Eagle Medium (DMEM). Culture media were supplemented with 10% fetal calf serum (FCS ; Invitrogen), 50 U/mL penicillin, and 50 μg/mL strep-tomycin. HUVECs (Lonza) were cultured in EGM-2 Media BulletKit (Lonza) and used between passages two and fi ve. Cells were reverse transfected with 50 nmol/L SMARTpool siRNA oligonucleotides (Dharmacon; Supplementary Table S1) using Lipofectamine 2000 (4T1-Luc cells; Invitrogen) RNAiMAX (MDA-MB-453 and ZR75.1; Inv-itrogen) or Dharmafect4 (MDA-MB-231; Dharmacon), and cell assays were performed 48 to 72 hours later. For shRNA expression, individual targeting shRNAs, selected on the basis of RNAi Codex (ref. 47 ; Supple-mentary Table S1), were synthesized as 97 base pair oligonucleotides (Sigma Genosys), PCR-amplifi ed, cloned into the LMS vector, and veri-fi ed by sequencing. Infected 4T1-Luc cells (see shRNA library methods) were FACSorted for GFP + cells. Mission particles were purchased from Sigma. pGIPZ sh ST6 and shNTC plasmid DNA (V2LHS_6073 and

Figure 5. (Continued) E, siNTC and si ST6 -transfected MDA-MB-453 cells were stained for ST6GalNAc2 (green) and the Golgi protein β-COP (red). Nuclei were counterstained with 4′,6-diamidino-2-phenylindole (DAPI; blue). Scale bar, 20 μm. F, G, and H, 0.5 × 10 6 siNTC-, si ST6 -, or si GAL3 -transfected MDA-MB-453 or MDA-MB-231 cells labeled with CellTracker dyes were inoculated into the tail veins of CD1 mice nu/nu mice and lung retention assessed at 1 and 5 hours as described in A. I, 0.5 × 10 6 231-VEC or 231-ST6 cells labeled with CellTracker dyes were treated for 30 minutes with vehicle (VEH) or 250 μg/mL GCS-100 and inoculated into the tail veins of CD1 mice nu/nu mice that had been pretreated 1 day previously with 250 μg/mL GCS-100. Lung retention was assessed at 1 and 5 hours as described in A. A–I, qPCR analysis of ST6GALNAC2 and LGALS3 mRNA levels and representative confocal images are shown in Supplementary Fig. S4 (4T1-Luc cells) and Supplementary Fig. S5 (human cells). ns, not signifi cant; AU, arbitrary unit.






ZR75.1 shNTC

ZR75.1 shST6

Vehicle

Adh

eren

t cel

ls/fo

vA

dher

ent c

ells

/fov

30

A B

DC

E F

20

10ns

*

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0

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8004T1-Luc siNTC4T1-Luc siST6

600

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0–Lactose +Lactose –Lactose +Lactose

+ siGAL3– siGAL3

P = 0.006P = 0.001

P = 0.002

P = ns

P = 0.0006

P = ns

P = 0.03

P = ns

P = ns

P = ns

Flu

ores

cenc

e (c

ount

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Flu

ores

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ount

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4T1-

Luc

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aggr

egat

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ell a

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U)

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00siGAL3

siNTC siST6 siNTC siST6

siST6siST6 + siGAL3

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siNTCsiNTC + siGAL3

siST6siST6 + siGAL3

– siGAL3 siGAL3 siGAL3– – –

20

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0HUVEC sEND

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00 2 4 6 8 10

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nsns

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Time (min)

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Galectin-3 Core 1/T antigen Disialyl-T antigen

High ST6 tumor cells Low ST6 tumor cells

4T1-Luc siNTC4T1-Luc siST6

Endothelial cells

Figure 6. ST6GalNAc2 expression enhances tumor cells interaction with the vasculature. A, model of tumor:endothelial interactions modulated by ST6GalNAc2 expression levels. See text for details. B, sh ST6 and shNTC ZR75.1 cells (see Supplementary Fig. S5A for qPCR analysis) were labeled with CellTracker dyes, mixed at a 1:1 ratio, and co-perfused over activated HUVECs under fl ow conditions (see Methods) in the absence (left and Supplementary Movie S1) and presence (right and Supplementary Movie S2) of the galectin-3 inhibitor GCS-100. Data shown are the mean number of shNTC and sh ST6 cells that adhered to HUVECs at 1, 5, and 10 minutes. Equivalent results were obtained in three independent experiments. Two-way ANOVA with Bonferroni posttest was used to generate P values. *, P < 0.05; **, P < 0.01. C and D, 4 × 10 4 4T1-Luc cells transfected with siNTC or si ST6 in the presence or absence of si GAL3 were added to monolayers of HUVEC or sEND endothelial cells in 24-well plates in the presence or absence of 100 mmol/L lactose and incubated for 30 minutes at 37°C. Wells were washed and adherent cells quantifi ed. Data shown are mean values from triplicate samples ±SEM. Student t test was used to generate P values. Equivalent results were obtained in three or two independent experiments, respectively. E and F, aggregation of tumor cells transfected with siNTC or si ST6 , with or without si GAL3 cotransfection, in the lung was quantifi ed for the mice shown in Fig. 5D (4T1-Luc cells) and Fig. 5G (MDA-MB-453 cells) at 24 and 5 hours, respectively. Data shown are mean size of tumor cell aggregates/fov for the 4 mice in each group ±SEM. Student t test was used to generate P values. Representative confocal images are shown. Scale bar, 100 μm. ns, not signifi cant; AU, arbitrary unit.






Figure 7. ST6GalNAc2 expression determines responsiveness to galectin-3 inhibition. A, correlation of LGALS3 normalized expression level between ER + and ER − tumors and cell lines (fi nal) in the Breast Cancer Gene Expression Datasets (ROCK). Student t test was used to generate P values, P = ns for all datasets. B, forest plot showing meta-analysis of LGALS3 expression and survival outcome in the ER − tumors from the same datasets and in two additional datasets (GSE31519, GSE5327) of ER − breast cancers (total of 551 patients). See Methods for statistical analysis. C, shNTC and sh ST6 4T1-Luc cells were inoculated into the tail veins of BALB/c mice. Mice were injected intraperitoneally with PBS or GCS-100 three times a week. Lungs were IVIS imaged in vivo and weighed at necroscopy (day 18). Data shown are from 7 or 8 mice per group ±SEM. One-way ANOVA was used to generate P values. ns, not signifi cant.

6

A

B C

ER– P = ns across all datasetsER+

4

LGA

LS3

(Log

2 med

ian

cent

red

inte

nsity

)

LGA

LS3

(Log

10 m

ean

cent

red

inte

nsity

)

LGA

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(Log

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ian

cent

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inte

nsity

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LGA

LS3

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mal

ized

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xpre

ssio

n)

2

Study DesmedtGSE7390

LoiGSE6532

MillerGSE3494

PawitanGSE1456

SotiriouGSE2990

WangGSE2034

MinnGSE2603

van de VijverNKI295

ChinGSE8757

NeveE-TABM-157

PerreardGSE2607

0.5

0.0

–0.5

2.0

1.0

0.0

–1.0

–2.0

15

10

5

0

RR 95% CI

0.74

2.791.393.552.080.341.370.881.571.010.35

0.33

0.28–2.00

1.29–6.000.47–4.13

0.95–13.220.50–8.710.04–2.790.52–3.660.38–2.040.69–3.580.40–2.590.08–1.58

0.02–5.69

ER

– tu

mor

s (L

GA

LS3)

Study

GSE8757

GSE7390GSE6532GSE3494GSE1456GSE2607GSE2990

GSE2034GSE31519GSE2603

GSE5327

NKI295

Overall 1.19 0.88–1.60 P = 0.26

0.3

1 × 106

1 × 105

1 × 104

1 × 103

0.6

0.4

0.2

shNTC -A

shST6 -

A

shNTC -A

shST6 -

A

shNTC -A

shST6 -

A

shNTC -A

shST6 -

A

Lung

wei

ght (

mg)

Pho

tons

(p/

s/cm

2 /sr

)

0.0

Vehicle GCS-100 Vehicle GCS-100

ns

** ** ***ns

ns

ns

1.0 3.0 4.02.0

Favors better survival Favors poorer survivalRR

RHS4346) together with packaging plasmid psPAX2 and envelope plasmid pMD2 (Thermo Scientifi c Open Biosystems) were cotrans-fected into HEK293T cells using Lipofectamine 2000. Forty-eight hours after transfection, supernatant was collected, supplemented with 4 μg/mL polybrene, and used to infect the cells. Stable shRNA-infected cells were selected using puromycin (Sigma) at 2 μg/mL. To generate St6galnac2 -overexpressing MDA-MB-231-Luc cells, full-length mouse St6galnac2 (I.M.A.G.E. clone) was subcloned into the lentivi-ral vector pDEST/pHIV-H2BmRFP-rfa_verB using Gateway Cloning Technology. Briefl y, vector plasmid, packaging plasmid psPAX2, and envelope plasmid pMD2.G were cotransfected into HEK293T cells using Lipofectamine 2000. Virus particles were collected and used to infect MDA-MB-231-Luc cells. Red fl uorescent protein (RFP)-express-ing cells were selected by FACSorting. For transient expression, sh ST6 and shNTC 4T1-Luc cells were transfected with a human ST6GAL-NAC2 (hST6) cDNA expression clone (EX-C0746-Lv41; GeneCopoeia) or empty vector (VEC) using Lipofectamine 2000, and lung retention assays were performed 48 hours later.

In Vivo Studies For the experimental lung metastasis assay, 0.5 × 10 6 cells were

injected into the tail veins of female 6- to 8-week-old BALB/c (4T1-Luc cells) or CB17 NOD.SCID mice (Harlan; MDA-MB-231 cells). For GCS-100 treatment, mice were injected intraperitoneally with 250 μg of GCS-100 on day −1 and then three times a week starting on day 1. For the experimental liver metastasis assay, 0.5 × 10 6 4T1-Luc cells were inoculated into the spleen parenchyma of 6- to 8-week-old BALB/c mice. For orthotopic inoculation, BALB/c mice were injected

with 1.5 × 10 5 4T1-Luc cells, and tumor volumes were measured until they reached maximum allowable size.

For lung retention assays, cells were transfected with siRNA oligo-nucleotides, labeled 48 hours later with CellTracker Red CMTPX or Green CMFDA dyes (Molecular Probes), trypsinized, and mixed at a 1:1 ratio, and 0.5 × 10 6 cells injected into the tail veins of 6- to 8-week-old BALB/c mice (4T1-Luc cells) or CD1 nu/nu mice (human cell lines). Mice were sacrifi ced at 1, 5, or 24 hours, and lungs were examined on a Zeiss LSM 710 microscope using ×10 lens. Ten images were taken for each lung. Tumor cell colonization of the lung and tumor cell aggrega-tion within the lung was quantifi ed in ImageJ, by converting the red and green images into separate binary images and measuring tumor cell coverage and mean size of tumor cell aggregates per fi eld of view (fov). All animal work was carried out with UK Home Offi ce approval.

In Vitro Studies The following reagents were used for immunofl uorescent staining:

anti-human ST6GalNAc2 (Abcam; #68510), fl uorescein isothiocy-anate (FITC)–conjugated anti-glutathione S -transferase (anti-GST; Abcam; #6647), in-house–generated rat anti-β-COP monoclonal antibody, GST-tagged human recombinant galectin-3 (GST-GAL3; Novus Biologicals; #H00003958-P01), and Alexa Fluor–conjugated secondary antibodies (Invitrogen).

For static adhesion assays, monolayers of HUVEC and sEND cells were stimulated with 10 ng/mL TNF-α (R&D Systems) for 4 to 6 hours before use. A total of 4 × 10 4 siRNA-transfected 4T1-Luc cells were labeled with CellTracker Green CMFDA dye and incubated with monolayer cultures of HUVEC or sEND cells in the presence or






absence of 100 nmol/L lactose for 30 minutes at 37°C. The cells were washed with PBS, and the numbers of adherent cells were quantifi ed on a VICTOR X fl uorescent plate reader.

For dynamic adhesion to endothelial cells under fl ow, HUVEC monolayers were grown to confl uency on the base of each parallel plate fl ow chamber and stimulated with 10 ng/mL of TNF-α (R&D Systems) for 4 to 6 hours before use. Single-cell suspensions of shNTC or sh ST6 ZR75.1 cells were achieved using enzyme-free cell dissocia-tion buffer (Life Technologies) and labeled with 1 μmol/L CellTracker orange or green dyes. Cells were transferred into perfusion media (DMEM plus 10% FCS and 25 mmol/L HEPES), mixed in a 1:1 ratio and 2 × 10 6 cells/mL perfused over HUVECs for 10 minutes at 1.25 dynes/cm 2 . Three fi elds of view were selected for each fl ow experiment and recorded using ×10 inverted objective lens (Olympus IX-80 micro-scope). Images were acquired at three time points in three channels (phase contrast, GFP, and RFP). Dye swaps did not affect cell behavior. For the galectin-3 inhibitor assays, tumor cells and HUVECs were pre-treated with 300 μg/mL GSC-100 for 30 and 10 minutes, respectively, and GSC-100 was present during the fl ow assay.

O-glycomic Profi le Analysis A total of 2 × 10 7 siNTC- and si ST6 -transfected 4T1-Luc cells were

snap-frozen and treated as described previously ( 49, 50 ). Briefl y, all samples were subjected to homogenization in an extraction buffer (25 mmol/L Tris, 150 mmol/L NaCl, 5 mmol/L EDTA and 1% (3-[(3-chola-midopropyl)dimethyl-ammonio]-1-propane sulfonate, CHAPS at pH 7.4). After reduction, carboxymethylation, and tryptic digestion, O -gly-cans were released by reductive elimination. Released O -glycans were then permethylated and purifi ed by C 18 -Sep-Pak. All permethylated samples were dissolved in 10 μL of methanol, and 1 μL of the dissolved sample was premixed with 1 μL of matrix (20 mg/mL 2,5-dihydroxy-benzoic acid in 70% v/v aqueous methanol), spotted onto a target plate (2 × 0.5 μL) and dried under vacuum. Mass spectrometry (MS) data were acquired using a Voyager-DE STR MALDI-TOF (Applied Biosystems). MS-MS data were acquired using a 4800 MALDI-TOF/TOF (Applied Biosystems) mass spectrometer. The collision energy was set to 1 kV, and argon was used as collision gas. The 4700 Calibration Standard Kit, Calmix (Applied Biosystems), was used as the external calibrant for the MS mode of both instruments and [Glu1] fi brinopep-tide B human (Sigma) was used as an external calibrant for the MS-MS mode of the MALDI-TOF/TOF instrument. The MS and MS-MS data were processed using Data Explorer 4.9 Software (Applied Biosystems). The spectra were subjected to manual assignment and annotation with the aid of the glycobioinformatics tool GlycoWorkBench. Assignments for the selected peaks were based on 12 C isotopic composition together with the knowledge of the biosynthetic pathways. Structures were con-fi rmed by data obtained from MS-MS experiments.

Statistical Analysis Statistical analysis was performed using GraphPad Prism5 soft-

ware and R version 2.11.1. Two-tailed Student t tests were performed as indicated. Two-way ANOVA with Bonferroni posttest was used to generate P values for dynamic adhesion assays with and with-out galectin-3 inhibitor (GCS-100). Clinical relevance of variable ST6GALNAC2 expression was assessed using publicly available data. For meta-analysis, the highest quartile of gene expression was used to dichotomize the ER − samples from each study. For each study, we computed individual RR and 95% CI and then calculated an overall RR and 95% CI using the Mantel–Haenszel method. There was no evidence of interstudy heterogeneity as assessed using Cochran’s Q statistic. We assessed whether the overall RR was signifi cantly differ-ent from RR = 1 using a one degree-of-freedom score test.

Disclosure of Potential Confl icts of Interest No potential confl icts of interest were disclosed.

Authors’ Contributions Conception and design: N. Murugaesu, M. Iravani, A. Dell, A. Ashworth, C.M. Isacke Development of methodology: N. Murugaesu, M. Iravani, A. van Weverwijk, A. Ivetic, D.A. Johnson, A. Antonopoulos, S.M. Haslam, A. Dell, C.J. Lord, A. Ashworth Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): N. Murugaesu, M. Iravani, A. van Weverwijk, D.A. Johnson, A. Antonopoulos, A. Fearns, M. Jamal-Hanjani, K. Fenwick, S.M. Haslam, A. Dell, C.J. Lord Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): N. Murugaesu, M. Iravani, A. van Weverwijk, A. Ivetic, D.A. Johnson, A. Antonopoulos, D. Sims, C. Mitsopoulos, Q. Gao, N. Orr, M. Zvelebil, S.M. Haslam, A. Dell, H. Yarwood, C.J. Lord, C.M. Isacke Writing, review, and/or revision of the manuscript: N. Muru-gaesu, M. Iravani, A. Ivetic, A. Antonopoulos, S.M. Haslam, A. Dell, H. Yarwood, C.J. Lord, A. Ashworth, C.M. Isacke Study supervision: C.M. Isacke

Acknowledgments The authors thank S. Lowe (Cold Spring Harbor Laboratory) for

providing the Cancer 1000 shRNA library, D.J. Burgess for help with handling the library and setting up the screen, F. Wallberg for assist-ance with FACSorting, D. Bird and R. Hayward for assistance with mouse experiments, H. Patterson and D. Robertson for assistance with confocal microscopy, C. Bakal for assistance with the image analysis, M. Ashenden and J. Burchell for helpful advice and discus-sion, and F. Cotter for generously providing the GCS-100 inhibitor.

Grant Support This work was supported by Breakthrough Breast Cancer (to

C.M. Isacke) and Biotechnology and Biological Sciences Research Council (to A. Dell and S.M. Haslam; grant numbers BBF008309 and BBK016164). A. Ivetic is generously supported by the British Heart Foundation Centre of Research Excellence at King’s College London.

Received June 14, 2013; revised December 9, 2013; accepted December 23, 2013; published OnlineFirst February 11, 2014.

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2014;4:304-317. Published OnlineFirst February 11, 2014.Cancer Discovery Nirupa Murugaesu, Marjan Iravani, Antoinette van Weverwijk, et al. Sialyltransferase as a Breast Cancer Metastasis Suppressor

Functional Screen Identifies ST6GalNAc2In VivoAn

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