Accumulation of Cd11c+CD163+ Adipose Tissue Macrophages Through Upregulation of Intracellular 11Β-HSD1 in Human Obesity

Accumulation of CD11c+CD163+ Adipose Tissue Macrophages through Upregulation of Intracellular 11 β-HSD1 in Human Obesity

This information is current as Shotaro Nakajima, Vivien Koh, Ley-Fang Kua, Jimmy So, of September 24, 2021. Lomanto Davide, Kee Siang Lim, Sven Hans Petersen, Wei-Peng Yong, Asim Shabbir and Koji Kono J Immunol 2016; 197:3735-3745; Prepublished online 3 October 2016;

doi: 10.4049/jimmunol.1600895 Downloaded from http://www.jimmunol.org/content/197/9/3735

Supplementary http://www.jimmunol.org/content/suppl/2016/10/01/jimmunol.160089 Material 5.DCSupplemental http://www.jimmunol.org/ References This article cites 62 articles, 14 of which you can access for free at: http://www.jimmunol.org/content/197/9/3735.full#ref-list-1

Why The JI? Submit online.

• Rapid Reviews! 30 days* from submission to initial decision by guest on September 24, 2021

• No Triage! Every submission reviewed by practicing scientists

• Fast Publication! 4 weeks from acceptance to publication

*average

Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts

The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology

Accumulation of CD11c+CD163+ Adipose Tissue Macrophages through Upregulation of Intracellular 11b-HSD1 in Human Obesity

Shotaro Nakajima,* Vivien Koh,† Ley-Fang Kua,† Jimmy So,‡ Lomanto Davide,‡ Kee Siang Lim,* Sven Hans Petersen,* Wei-Peng Yong,*,† Asim Shabbir,‡ and Koji Kono*,‡,x,{

Adipose tissue (AT) macrophages (ATMs) are key players for regulation of AT homeostasis and obesity-related metabolic disorders. However, the phenotypes of human ATMs and regulatory mechanisms of their polarization have not been clearly described. In this study, we investigated human ATMs in both abdominal visceral ATand s.c. ATand proposed an 11b-hydroxysteroid dehydrogenase type 1 (11b-HSD1)–glucocorticoid receptor regulatory axis that might dictate M1/M2 polarization in ATMs. The accumulation of Downloaded from CD11c+CD163+ ATMs in both visceral AT and s.c. AT of obese individuals was conﬁrmed at the cellular level and was found to be clearly correlated with body mass index and production of reactive oxygen species. Using our in vitro system where human peripheral blood monocytes (hPBMs) were cocultured with Simpson–Golabi–Behmel syndrome adipocytes, M1/M2 polarization was found to be dependent on 11b-HSD1, an intracellular glucocorticoid reactivating enzyme. Exposure of hPBMs to cortisol- induced expression of CD163 and RU-486, a glucocorticoid receptor antagonist, signiﬁcantly abrogated CD163 expression through coculture of mature adipocytes with hPBMs. Moreover, 11b-HSD1 was expressed in crown ATMs in obese AT. Importantly, http://www.jimmunol.org/ conditioned medium from coculture of adipocytes with hPBMs enhanced proliferation of human breast cancer MCF7 and MDA- MB-231 cells. In summary, the phenotypic switch of ATMs from M2 to mixed M1/M2 phenotype occurred through differentiation of adipocytes in obese individuals, and upregulation of intracellular 11b-HSD1 might play a role in the process. The Journal of Immunology, 2016, 197: 3735–3745.

verweight and obese individuals pose global health is- have been postulated as important elements in inﬂammation (4, 5). sues and are associated with increased risks of metabolic Understanding the regulatory mechanisms of ATM polarization

O diseases, including type 2 diabetes, cardiovascular dis- can be important in preventing the development of obesity-related by guest on September 24, 2021 ease, and certain cancers (1–3). Obesity and related metabolic metabolic disorders. However, human ATM phenotypes and their disorders are associated with a state of chronic, low-grade in- polarization mechanisms remain unclear. flammation in adipose tissue (AT), and AT macrophages (ATMs) There are at least two different phenotypes of ATMs: classically activated proinflammatory ATMs (M1 ATMs) and alternatively activated anti-inflammatory ATMs (M2 ATMs). In nonobese ani- *Center for Translational Medicine, Cancer Science Institute of Singapore, National Uni- versity of Singapore, Singapore 117599; †Department of Hematology–Oncology, National mals, resident M2 ATMs are predominantly observed and con- University of Singapore, Singapore 119228; ‡Department of Surgery, National University tribute to maintenance of AT homeostasis. Alternatively, during of Singapore, Singapore 119228; xDepartment of Organ Regulatory Surgery, Fukushima Medical University, Fukushima 960-1295, Japan; and {Department of Advanced Cancer obesity, secretions of chemotactic molecules, such as MCP-1 from Immunotherapy, Fukushima Medical University, Fukushima 960-1295, Japan hypertrophic adipocytes, result in the recruitment of circulating ORCID: 0000-0001-9330-5783 (K.S.L.). monocytes into AT and their differentiation into an M1 phenotype Received for publication May 24, 2016. Accepted for publication September 1, 2016. (6, 7). Indeed, this phenotypic switch from M2 to M1 in AT is a This work was supported by the National Medical Research Council of Singapore crucial determinant of insulin resistance in obese mice. In mice (the Clinician Scientist Award and the Singapore Translational Research Investigator fed a high-fat diet, a marked increase in the accumulation of F4/ Award) (to K.K.). 80+CD11c+ ATM–expressing inflammatory genes, as well as the The microarray data presented in this article have been submitted to the Gene Ex- depletion of these F4/80+CD11c+ cells, would normalize obesity- pression Omnibus (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE86492) under accession number GSE86492. induced insulin resistance (8, 9). In contrast, other groups reported Address correspondence and reprint requests to Prof. Koji Kono, Department of Organ that this phenotypic switch in human ATMs in obese individuals is Regulatory Surgery and Department of Advanced Cancer Immunotherapy, Fukushima fundamentally different from the mouse model. Zeyda et al. (10) Medical University, Fukushima 960-1295, Japan. E-mail address: [email protected] and Bourlier et al. (11) reported that human ATMs were of the M2 The online version of this article contains supplemental material. phenotype–producing proinflammatory mediators. Another study Abbreviations used in this article: AT, adipose tissue; ATM, AT macrophage; BMI, by Wentworth et al. (12) suggested that the percentage of CD11c+ body mass index; CLS, crown-like structure; CM, conditioned medium; ER, endo- + plasmic reticulum; FFA, free fatty acid; GR, glucocorticoid receptor; HbA1c, hemo- CD206 ATMs with mixed M1/M2 phenotype increased in obese globin A1c; hPBM, human peripheral blood monocyte; 11-bHSD, 11b-hydroxysteroid subjects and was correlated with markers of increased insulin dehydrogenase; 11b-HSD1, 11b-hydroxysteroid dehydrogenase type 1; 11b-HSD2, 11b-hydroxysteroid dehydrogenase type 2; qPCR, quantitative real-time PCR; ROS, resistance, such as crown-like structures (CLS), and also with the reactive oxygen species; SAT, s.c. AT; SGBS, Simpson–Golabi–Behmel syndrome; homeostasis model assessment of insulin resistance. Importantly, SVF, stromal vascular fraction; TAM, tumor-associated macrophage; VAT, visceral Becker and colleagues (13) demonstrated that metabolic activation AT; VEGF, vascular endothelial growth factor. pathways triggered by glucose, insulin, and palmitate also contribute Copyright Ó 2016 by The American Association of Immunologists, Inc. 0022-1767/16/$30.00 to ATM-specific polarization in humans and mice. Therefore, the www.jimmunol.org/cgi/doi/10.4049/jimmunol.1600895 3736 INCREASING CD11c+CD163+ ATMs IN HUMAN OBESITY regulation of ATM polarization is complex, and little is known of the human CD68 Ab (Dako, Glostrup, Denmark); human 11b-HSD1 Ab link between human ATM phenotype and metabolic disorders in (Abcam, Cambridge, U.K.); and b-actin Ab (Cell Signaling Technology, obese individuals. Further investigations on the phenotype of human Danvers, MA). ATMs and their functions are needed to develop efficient therapies Collection of AT for obesity and related metabolic diseases. This study was approved by the Domain-Specific Ethics Board of the Several markers of human M1 and M2 ATMs have been National University Hospital of Singapore (DSRB no. 2015/00031). We reported. Cell surface markers of M1 ATMs include CD11c, CD40, recruited 7 nonobese subjects (BMI , 30 kg/m2) and 22 obese subjects CD86, HLA-DR, and TLR4 (7, 14, 15). CD11c is predominantly (BMI $ 30 kg/m2) from the National University Hospital of Singapore expressed by crown ATMs in the proinflammatory state (12). (Table I). Abdominal VAT (omental AT) and SAT were collected during herniorrhaphy for nonobese subjects and during bariatric surgery for obese Several groups also reported CD11c as a human M1 marker subjects after obtaining informed consent. None of the subjects had any (16–18). Thus, it is considered to be a suitable marker of human clinical symptoms of systemic inflammation. M1 ATMs. Additionally, there are several known cell surface Isolation of stromal vascular fraction from AT markers of M2 ATMs such as CD163, CD204 (macrophage scavenger receptors), and CD206 (mannose receptor) (7, 14, 15). AT was minced with sterile scissors and digested in HBSS (Life Tech- Komahara et al. (15) reported that CD163 but not CD204 or nologies, Carlsbad, CA) containing 300 U/ml collagenase and 100 U/ml hyaluronidase supplemented with 10% BSA and 20 mM HEPES at 37˚C CD206 was upregulated by treatment with IL-10, which induces for 60 min. The digested sample was sieved through a 70-mm filter (BD M2 polarization in human monocyte-derived macrophages. In- Biosciences) and centrifuged at 600 3 g for 10 min to extract stromal terestingly, CD163 is one of the ATM markers associated with the vascular fraction (SVF) pallets, which contain preadipocytes, endothelial homeostasis model assessment of insulin resistance (19). Based on cells, and immune cells, including macrophages. The SVF pellet was in- Downloaded from published evidence, CD163 can be a useful marker to represent cubated with RBC lysis solution (Qiagen, Hilden, Germany) for 8 min and centrifuged at 300 3 g for 10 min. Finally, the pellet was washed with PBS human M2 ATMs. and resuspended in staining buffer containing 3% FBS and 0.05% sodium 11b-Hydroxysteroid dehydrogenases (11b-HSDs) are enzymes azide for flow cytometry analysis. that catalyze the interconversion of intracellular glucocorticoid. Flow cytometry analysis 11b-HSDs consist of two isotypes, 11b-HSD type 1 (11b-HSD1)

and 11b-HSD type 2 (11b-HSD2). 11b-HSD1 is highly expressed SVF cells or hPBMs were stained with Abs specific for PE-conjugated http://www.jimmunol.org/ in the liver, AT, ovary, and CNS, whereas 11b-HSD2 is found human CD11c, allophycocyanin-conjugated human CD14, and FITC- conjugated human CD163 in the presence of FcR blocking reagent (Mil- expressed in the kidney, colon, sweat glands, and placenta (20). tenyi Biotec, Bergisch Gladbach, Germany). For detection of intracellular 11b-HSD1 catalyzes the conversion of inactive cortisone to the reactive oxygen species (ROS) production, cells were incubated with active cortisol, whereas 11b-HSD2 catalyzes the reverse reaction 1 mM 5-(and-6)-chloromethyl-29,79-dichlorodihydrofluorescein diacetate, (21). It has been reported that both the mRNA level and activity of acetyl ester with or without 0.5 mg/ml PMA for 20 min at 37˚C shielded 11b-HSD1 correlate with body mass index (BMI) in both human from light. The reaction was stopped by the addition of ice-cold PBS, and cells were stained with allophycocyanin-conjugated human CD14 Ab. The visceral AT (VAT) and s.c. AT (SAT) (22–24). 11b-HSD1 is level of ROS production was determined as mean dichlorofluorescein expressed not only in adipocytes but also in stromal/vascular fluorescent intensity of PMA-treated CD14+ cells minus mean dichloro- compartments of human SAT (25, 26), suggesting that ATMs fluorescein fluorescence intensity of nontreated CD14+ cells. Cells were by guest on September 24, 2021 + might also express 11b-HSD1. Indeed, a positive correlation was gated on CD14 cells for macrophage phenotyping using an LSR II flow cytometer (BD Biosciences). The analyses of FACS data were performed observed between the expression of macrophage marker CD68 using FlowJo software (Tree Star, Ashland, OR). and 11b-HSD1 in human SAT (27). Moreover, glucocorticoid is known as a major inducer of CD163 expression in monocytes Immunofluorescence and H&E staining (28, 29). Taken together, it is likely that the 11b-HSD12 Paraffin-embedded 5-mm AT sections fixed in 10% formaldehyde were glucocorticoid receptor (GR) axis may regulate M2 polarization, deparaffinized and rehydrated. For immunofluorescence staining, the sec- especially CD163 expression, in monocytes/macrophages in AT tions were then incubated with epitope retrieval solution (Dako) for 20 min in obese individuals. at 100˚C. After washing with TBST, the sections were treated with + + blocking solution for 30 min and stained with anti-human CD68 Ab, anti- In the present study, we defined CD11c CD163 ATMs having a human caveolin Ab, and/or anti-human 11b-HSD1 Ab at 4˚C overnight. mixed M1/M2 phenotype of human ATMs and evaluated their The sections were washed and incubated for 1 h with Alexa Fluor 488– prevalence in both VAT and SATof obese individuals. Additionally, conjugated anti-mouse, Alexa Fluor 555–conjugated anti-rabbit, and Alexa we successfully established an in vitro coculture system to examine Fluor 647–conjugated anti-rabbit secondary Abs. Nuclei were stained with DAPI for 10 min. Finally, slides were mounted using ProLong Gold 1) the effects of adipocyte differentiation on polarization of human antifade reagent (Invitrogen), and images were obtained using the Nikon peripheral blood monocytes (hPBMs), and 2) the signaling mole- A1R confocal microscope (Nikon, Tokyo, Japan). CLS were defined as cule important for hPBM polarization. Finally, we also investigated three or more CD68+ cells surrounding an adipocyte, and 20 randomly the effects of mixed M1/M2 monocytes/macrophages on obesity- chosen low-power (310) fields were counted by one observer. For H&E associated tumor progression using breast cancer cell lines. staining, deparaffinized and rehydrated AT sections were stained with H&E and then mounted using Eukitt quick-hardening mounting medium (Sigma-Aldrich). Adipocyte areas were measured as 200 cells per AT using Materials and Methods ImageJ software. Materials Cell lines

Reagents used in this study included biotin, collagenase, dexamethasone, D- The human Simpson–Golabi–Behmel syndrome (SGBS) preadipocyte cell pantothenic acid hemicalcium salt (pantothenate), human insulin, human line was provided by Dr. Martin Wabitsch (University of Ulm, Ulm, transferrin, hyaluronidase, hydrocortisone (cortisol), palmitic acid, PMA, Germany). The human T cell acute lymphoblastic leukemia MOLT-4 cell RU-486, sodium azide, 1-methyl-3-isobutyl-xantine, 3,39,5-triiodo-L-thy- line was provided by Dr. Takaomi Sanda (National University of Singa- ronine sodium salt (triiodothyronine), and DAPI (Sigma-Aldrich, St. Louis, pore, Singapore). The human acute monocytic leukemia THP-1 cells were MO); rosiglitazone (Cayman Chemical, Ann Arbor, MI); allophycocyanin- obtained from the Japanese Collection of Research Bioresources Cell Bank conjugated human CD14 Ab, FITC-conjugated human CD163 Ab, PE- (Osaka, Japan), the human Hodgkin’s disease–derived HDLM-2 cells were conjugated human CD11c Ab, and human caveolin Ab (BD Biosciences; from the German Collection of Microorganisms and Cell Culture San Jose, CA); 5-(and-6)-chloromethyl-29,79-dichlorodihydroﬂuorescein (Braunschweig, Germany), and the human breast cancer MCF7 and MDA- diacetate, acetyl ester, Alexa Fluor 488–conjugated anti-mouse Ab, and MB-231 cell lines were from the American Type Culture Collection Alexa Fluor 647–conjugated anti-rabbit Ab (Invitrogen, Carlsbad, CA); (Manassas, VA). SGBS cells were maintained in DMEM/F-12 (1:1) (Life The Journal of Immunology 3737

Technologies) supplemented with 10% non–heat-inactivated FBS, 33 mM 50 mM DTT and bromophenol blue and boiled for 5 min. The protein biotin, and 17 mM pantothenate. MOLT-4, THP-1, HDLM-2, MCF7, and concentration was measured by using a BCA protein assay kit (Thermo MDA-MB-231 cell lines were maintained in RPMI 1640 (Biological In- Fisher Scientific, Waltham, MA), and proteins were loaded onto preparative dustries, Kibbutz Beit Haemek, Israel) supplemented with 5–10% FBS. gels (Invitrogen) and transferred to polyvinylidene difluoride membranes. The membranes were incubated with 5% milk blocking solution for 1 h at Adipogenic differentiation of SGBS cells room temperature, followed by incubation with anti–11b-HSD1 or anti–b- SGBS cells were washed twice with PBS and then cultured in serum-free actin Abs overnight at 4˚C. Each membrane was then washed three times DMEM/F-12 differentiation medium containing 33 mM biotin, 17 mM with TBST and incubated with HRP-conjugated anti-rabbit Ab for 1 h at pantothenate, 0.01 mg/ml human transferrin, 20 nM human insulin, 0.1 room temperature. Immunoreactive proteins were visualized using ECL mM cortisol, 0.2 nM triiodothyronine, 25 nM dexamethasone, 250 mM1- Prime and/or ECL Select (GE Healthcare). methyl-3-isobutyl-xantine, and 2 mM rosiglitazone. After 4 d, the medium Small interfering RNA transient transfection was changed to fresh serum-free medium supplemented with biotin, pantothenate, human transferrin, human insulin, cortisol, and triiodothyronine, Using RNAiMAX transfection reagent (Invitrogen), SGBS cells were and cells were further incubated for several days. The medium was transiently transfected with 11b-HSD1 small interfering RNA (siRNA) refreshed every 4 d. To quantify lipid accumulation, cells were fixed with (Mission siRNA, Sigma-Aldrich) or control siRNA (Mission siRNA uni- 10% formaldehyde and stained with Oil Red O (Sigma-Aldrich). versal negative control, Sigma-Aldrich). After 72 h, the transfected cells were seeded into each well of a six-well plate and differentiated for 7 d. Coculture of hPBMs with SGBS cells The expression level of 11b-HSD1 was confirmed by Western blot analysis. hPBMs were cocultured directly or indirectly with SGBS cells at various Cell proliferation assay stages of differentiation for 4 d. Direct cocultures were performed by directly adding hPBMs to six-well culture plates containing SGBS cells. A cell proliferation assay was performed using Cell Proliferation ELISA,

Indirect cocultures were performed by adding hPBMs into 0.4-mm pore size BrdU (Roche, Basel, Switzerland), according to the manufacturer’s in- Downloaded from cell culture inserts (Merck Millipore, Jaffrey, NH) and placing them into structions. MCF7 cells and MDA-MB-231 cells were seeded at 122 3 103 six-well culture plates containing SGBS cells. cells per well in 96-well dishes 24 h before conditioned medium (CM) treatment. CM from hPBMs, 14-d differentiated SGBS adipocytes, or Isolation of monocytes from PBMCs coculture of 14-d differentiated SGBS adipocytes with hPBMs were col- The use of buffy coats from healthy donors was approved by the Domain- lected, diluted with 10% FBS culture medium, and filtered to remove Specific Review Board of the National University Hospital of Singapore floating and apoptotic cells. Finally, MCF7 and MDA-MB-231 cells were treated with CM for up to 4 d and subjected to a proliferation assay.

(DSRB no. 2015/00031). PBMCs were isolated from buffy coats using http://www.jimmunol.org/ Ficoll-Paque (GE Healthcare, Little Chalfont, U.K.). Human monocytes Statistical analysis (hPBMs) were isolated using MACS magnetic cell separation systems (Miltenyi Biotec). All data are expressed as means 6 SEM. A Spearman correlation test was used to analyze the association in each experiment. A Mann–Whitney U Isolation of total RNA test, unpaired t test, Student t test, or one-way ANOVA was performed to determine statistical significance, and differences were considered to be Total RNA was isolated from human AT, human peripheral blood , monocytes, and cell lines using TRIzol (Invitrogen) or an RNeasy Mini kit significant at p 0.05. (Qiagen) according to the manufacturers’ instructions. RNA was quan- tified using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Results Scientific, Wilmington, DE), and the quality was verified by agarose gel + + Accumulation of CD11c CD163 ATMs in both abdominal by guest on September 24, 2021 electrophoresis. VAT and SAT in human obesity PCRs To study the phenotypic switch of human ATMs in obese indi- cDNA was synthesized using a HiSenScript RH(2) cDNA synthesis kit viduals, SVF cells were isolated from AT and stained with Abs (iNtRON Biotechnology, Gyeonggi, South Korea). Semiquantitative PCR against CD14 (a monocyte/macrophage marker), CD11c (a marker was performed on a Veriti 96-well thermal cycler (Applied Biosystems, of M1-like ATM), and CD163 (a marker of M2-like ATM) for Carlsbad, CA) using FastStart Taq DNA polymerase and dNTPack (Roche, 2 + Basel, Switzerland). Quantitative real-time PCR (qPCR) was performed on three-color FACS analysis. In nonobese AT, CD11c CD163 an ABI 7500 Fast real-time PCR system (Applied Biosystems) using ATMs (AT-resident M2 ATMs) were predominant in both ab- SYBR Fast qPCR Master mix (Kapa Biosystems, Wilmington, MA). The dominal VAT and SAT (Fig. 1A). However, in obese AT, the quantitative PCR data were normalized relative to housekeeping genes, percentages of CD11c+CD1632 ATMs (monocyte-like ATMs) and namely GAPDH for monocytes, specificity protein 1 for SGBS cells, and CD11c+CD163+ ATMs (mixed M1/M2 ATMs) were higher in peptidylprolyl isomerase A for AT. Sequences of primers can be provided upon request. comparison with nonobese AT (Fig. 1A). A high positive correlation was clearly observed between CD11c+CD163+ ATMs and Microarray hybridization and data analysis BMI in both VAT and SAT (Fig. 1B), and CD11c+CD1632 ATMs Total RNA was isolated as described above. Microarray gene expression were also moderately associated with BMI (Fig. 1C). Alterna- analysis was performed using Illumina HT-12 v4 Expression BeadChips tively, the percentage of CD11c2CD163+ ATMs was inversely (Illumina, San Diego, CA) according to the manufacturer’s instructions. correlated with BMI in both ATs (Fig. 1D). The percentages of Briefly, samples were first amplified, purified, and biotinylated and then + + + 2 2 + hybridized onto HT-12 arrays for 16 h at 56˚C. After that, the arrays were CD11c CD163 and CD11c CD163 ATMs but not CD11c CD163 washed and subsequently scanned using the Illumina BeadArray Reader. ATMs of total SVF cells were also correlated with BMI in VAT and Raw data were exported and analyzed using the GenomeStudio v2011.11 SAT (Supplemental Fig. 1A), suggesting that CD11c+CD163+ and + 2 software (Illumina). Differences between the log2 signal intensities of CD11c CD163 ATMs were overall increased in VAT and SAT in hPBMs cocultured with 14-d differentiated SGBS adipocytes and obese subjects. The increased percentage of CD11c+CD163+ ATMs hPBMs cocultured with SGBS preadipocytes were calculated to obtain fold-change values indicating regulation in gene expression. The might be driven by obesity and not by diabetes statuses, because the microarray data are available in the Gene Expression Omnibus database percentage was positively associated with BMI but not the levels of (accession no. GSE86492; http://www.ncbi.nlm.nih.gov/geo/query/acc. fasting glucose and hemoglobin A1c (HbA1c) in obese subjects cgi?acc=GSE86492). (Supplemental Fig. 1B). Among the diabetes statuses studied, only + + Western blot analysis insulin level was correlated with the percentage of CD11c CD163 ATMs (Supplemental Fig. 1B). Interestingly, the percentage of SGBS cells and hPBMs were lysed in RIPA buffer (25 mM Tris-HCl, + + 150 mM NaCl, 1% Triton X-100, 1% sodium deoxycholate, 0.1% SDS) CD11c CD163 ATMs was significantly higher in obese SAT with a protease inhibitor mixture and a phosphatase inhibitor mixture than in obese VAT (Fig. 1E), and a similar trend was observed in 2 2 (Sigma-Aldrich). The cell lysate was mixed with sample buffer containing CD11c+CD163 ATMs (Fig. 1F). The percentage of CD11c CD163+ 3738 INCREASING CD11c+CD163+ ATMs IN HUMAN OBESITY

Table I. Clinical characteristics and metabolism parameters of nonobese and obese subjects

Nonobese (BMI , 30 kg/m2) Obese (BMI $ 30 kg/m2) n (Male/female) 7 (7/0) 22 (7/15) Age (y) 50.6 6 7.4 (21266) 43.0 6 2.4 (21261) Race (Chinese/Indian/Malay/others) 4/1/0/2 5/5/11/1 BMI (kg/m2) 23.9 6 0.8 (22.5228.3) 44.9 6 1.9 (32.5262.8)**** Hypertension 2/7 9/22 Type 2 diabetes 0/7 9/22 Fasting glucose (mmol/l) ND 7.1 6 0.6 (4.6213.7) Fasting insulin (mU/l) ND 24.0 6 3.4 (6.3275.1) Fasting triglyceride (mmol/l) ND 1.5 6 0.1 (0.823.4) HDL cholesterol (mmol/l) ND 1.2 6 0.1 (0.721.8) HbA1c (%) ND 6.6 6 0.3 (5.129.5) Data are means 6 SEM. ****p , 0.0001 for lean versus obese. HDL, high-density lipoprotein.

ATMs was lower in obese SAT than in obese VAT (Fig. 1G). Activated monocytes/macrophages produce ROS that can affect

Importantly, note in our comparison analyses between non- their microenvironment (30, 31). Therefore, we investigated ROS Downloaded from obese and obese subjects that there were no female nonobese production in ATMs of obese individuals. Production of ROS in subjects, whereas .65% of the obese subjects were females. ATMs was found to be positively associated with BMI (Fig. 1H). Despite this, no signiﬁcant differences were found between The percentages of CD11c+CD163+ ATMs and CD11c+CD1632 males and females in all of the parameters studied (data not ATMs were also positively associated with ROS production in shown), indicating that gender is not a decisive factor affecting ATMs in both ATs (Fig. 1I, 1J). In contrast, inverse correlation

our research ﬁndings. was observed between ROS production in ATMs and the percentage http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 1. Increase in the percentage of CD11c+CD163+ ATMs in VAT and SAT of obese individuals. (A) Flow cytometry analysis of ATMs in VAT and SAT in nonobese and obese subjects. (B–D) Correlations between the percentage of CD11c+CD163+ (B), CD11c+CD1632 (C), or CD11c2CD163+ (D) ATMs and BMI in VAT and SAT. (E–G) Comparison of the percentage of CD11c+CD163+ (E), CD11c+CD1632 (F), or CD11c2CD163+ (G) ATMs between VAT and SAT in nonobese (VAT, n =5;SAT,n = 6) and obese (VAT, n = 20; SAT, n = 19) subjects. (H) Correlations between ROS production in ATMs and BMI. (I–K) Correlations between ROS production in ATMs and the percentage of CD11c+CD163+ (I), CD11c+CD1632 (J), or CD11c2CD163+ (K) ATMs. **p , 0.01. The Journal of Immunology 3739 of CD11c2CD163+ ATMs in both ATs (Fig. 1K). These data suggest than in nonobese SAT (Fig. 2D). However, the level remained that ATMs, especially CD11c+CD163+ ATMs and CD11c+CD1632 unchanged in VAT from nonobese and obese subjects (Fig. 2D). ATMs, produce ROS in obese individuals. Alternatively, the mRNA level of leptin was elevated more in obese AT than in nonobese AT, as expected, and the increase in Induction of adipocyte hypertrophy and dysfunction in VAT and leptin was not significant in SAT (Fig. 2D). ATMs aggregate SAT in obese individuals around necrotic adipocytes known as CLS, which is one of the We next examined the morphological and structural differences features of obesity (32). As shown in Fig. 2E, the number of between VAT and SAT in obese individuals. Hypertrophic adi- CLS increased in obese VAT and SAT and was correlated with pocytes were found in both VAT and SAT in an obese subject BMI. However, there was no significant difference between VAT (BMI, 50.9 kg/m2) when compared with a nonobese subject and SAT within the group (Fig. 2E). Increased adipocyte size (BMI, 22.5 kg/m2) (Fig. 2A). Indeed, hypertrophic adipocytes and the number of CLS were also driven by obesity but not by were observed in obese VAT and SAT, especially in the higher diabetes statuses because only BMI, but not fasting glucose, BMI group (BMI $ 45) (Fig. 2B). The size of each adipocyte fasting insulin, or HbA1c, was positively associated with these was larger in obese AT than in nonobese AT and was associated observations in VAT and SAT in obese subjects (Supplemental with BMI, but there was no significant difference between VAT Fig. 1C). and SAT in each group (Fig. 2C). We also measured the mRNA Our data suggest that although adipocyte hypertrophy and levels of adipokines, including adiponectin and leptin. As ex- dysfunction occur in obesity, there are not many significant dif- pected, the mRNA level of adiponectin was lower in obese SAT ferences between VAT and SAT. Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 2. Adipocyte hypertrophy and dysfunction in VAT and SAT in obese individuals. (A) H&E staining of VAT and SAT in a nonobese (BMI, 22.5 kg/m2) and an obese (BMI, 50.9 kg/m2) subject. Scale bars, 100 mm; original magniﬁcation 320. (B and C) Relative frequency (B) and box plots (C)of adipocyte size (area per adipocyte) in VAT and SAT in nonobese (n = 5), obese (30 # BMI , 45) (n = 9), and very obese (BMI $ 45) (n = 7) subjects. The lines inside the box plot represent the median size, and plus signs indicate the average size. (D) qPCR analysis of adipocyte function markers adiponectin and leptin in VAT and SAT in nonobese (n = 5) and obese (n = 13) subjects. (E) Immunoﬂuorescence staining of CD68 (green), caveolin (red), and DAPI (blue) in VAT and SAT in a nonobese (BMI, 22.5 kg/m2) and an obese (BMI, 50.9 kg/m2) subject. Arrows indicate CLS. Scale bars, 100 mm (left). The numbers of CLS in VAT and SAT in nonobese (n = 5), obese (30 # BMI , 45) (n = 9), and very obese (BMI $ 45) (n = 7) subjects (right) are shown. *p , 0.05, **p , 0.01. AU, arbitrary unit; Non-Ob, nonobese; Ob, obese. 3740 INCREASING CD11c+CD163+ ATMs IN HUMAN OBESITY

Induction of M1 and M2 markers and ROS production in for 4 d, and the surface expressions of CD11c and CD163 in hPBMs hPBMs when cocultured with human SGBS adipocytes were assessed using FACS. Most hPBMs expressed CD11c but not To next examine whether adipocyte hypertrophy and dysfunction in CD163 at the basal level (Fig. 3C, left). Four days of coculturing with obese individuals affects polarization of monocytes/macrophages, we SGBSadipocytesresultedinanupregulated expression of CD163 in + + established an in vitro coculture system using hPBMs and human hPBMs, and most of the cells exhibited a CD11c CD163 phenotype SGBS preadipocytes (33). Accumulation of lipid droplets and the (Fig. 3C, left). Importantly, the expression level of CD163 was gene expression levels of adipose function and differentiation signiﬁcantly higher in hPBMs cocultured with 14-d differentiated markers were elevated in SGBS cells after adipogenic differentiation adipocytes (mature adipocytes) than those with 7 d differentiation for 7 d, with .90% of the cells having differentiated to mature ad- (Fig. 3C, right), suggesting that adipogenic differentiation affects ipocytes after 14 d (Fig. 3A, 3B). To examine the effect of adipogenic polarization of hPBMs. Moreover, a similar outcome was observed differentiation on the polarization of hPBMs, hPBMs were cocul- in the indirect coculture system (Fig. 3D), indicating that released tured with or without SGBS cells at various stages of differentiation factors from adipocytes, but not cell–cell contact between adipo- (undifferentiated preadipocytes, 7- or 14-d differentiated adipocytes) cytes and hPBMs, are crucial for the polarization of hPBMs. Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 3. Induced expression of M1 and M2 markers in hPBMs when cocultured with SGBS adipocytes. (A) Oil Red O staining of undifferentiated or differentiated SGBS cells. (B) qPCR analysis of adipocyte differentiation and function markers in SGBS cells during adipogenic differentiation. Data are representative of three independent experiments. (C and D) Flow cytometry analysis of hPBMs cocultured directly (C) or indirectly (D) in the presence or absence of SGBS cells at various stages of differentiation (preadipocytes, 7-d differentiated adipocytes, and 14-d differentiated adipocytes) for4d(n = 3). The ﬂow plots were gated on CD14+ cells. Co-Adipo 7d, coculture with 7-d differentiated SGBS adipocytes; Co-Adipo 14d, coculture with 14-d differentiated SGBS adipocytes; Co-Preadipo, coculture with SGBS preadipocytes. (E) Heat map showing changes in gene expression of M1 and M2 markers in hPBMs cocultured for 24 and 48 h. hPBMs were derived from three healthy donors (donors 1, 2, and 3) and cocultured with SGBS cells (preadipocytes) or SGBS cells differentiated for 14 d (adipocytes). Expression represents fold differences between values of hPBMs cocultured with SGBS adipocytes and hPBMs cocultured with SGBS preadipocytes. Red indicates high expression (upregulation); blue indicates low expression (downregulation). (F) qPCR analysis of selected representative M1 (CD11c, CD40, and CD64) and M2 (CD163, CD206, IL-1ra, and TGF-b) markers in hPBMs cocultured with SGBS preadipocytes or 14-d differentiated SGBS adipocytes for 24 and 48 h (n =4).(G) ROS production in hPBMs directly cocultured with or without SGBS preadipocytes, 7-d differentiated SGBS adipocytes, or 14-d differentiated SGBS adipocytes (n = 3). (H) qPCR of HO-1 in hPBMs cocultured with SGBS preadipocytes or 14-d differentiated SGBS adipocytes for 24 and 48 h (n =4).*p , 0.05. The Journal of Immunology 3741 Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021

FIGURE 4. Induced CD163 expression in hPBMs through activation of 11b-HSD12GR axis. (A) Venn diagram of the top 100 up- and downregulated genes in hPBMs cocultured with 14-d differentiated SGBS adipocytes versus hPBMs cocultured with SGBS preadipocytes for 24 and 48 h. (B) Heat map showing fold changes in expression of 11b-HSD1 (HSD11B1) and 11b-HSD2 (HSD11B2) in hPBMs cocultured with 14-d differentiated SGBS adipocytes compared with hPBMs cocultured with SGBS preadipocytes (top). qPCR analysis of 11b-HSD1 in hPBMs cocultured with SGBS preadipocytes or 14-d differentiated SGBS adipocytes for 24 and 48 h (bottom) (n = 4). Co-Adipo 14d, coculture with 14-d differentiated SGBS adipocytes; Co-Preadipo, coculture with SGBS preadipocytes. (C) Western blot analysis of 11b-HSD1 in hPBMs cocultured with SGBS preadipocytes or 14-d differentiated SGBS adipocytes for 36 h. Data are representative of three independent experiments. (D and E) Flow cytometry (D) and qPCR (E) analyses of CD11c and CD163 in hPBMs by treatment with cortisol for 24 and 72 h (n = 3). The flow plots were gated on CD14+ cells. (F) Flow cytometry analysis of CD11c and CD163 in hPBMs cocultured with or without SGBS preadipocytes or 14-d differentiated SGBS adipocytes in the absence or presence of RU-486 (RU) for 4 d (n =3). The flow plots were gated on CD14+ cells. Co-Adipo 7d, coculture with 7-d differentiated SGBS adipocytes; Co-Adipo 14d, coculture with 14-d differentiated SGBS adipocytes; Co-Preadipo, coculture with SGBS preadipocytes. (G) Representative immunofluorescence staining of CD68 (green), 11b-HSD1 (red), and DAPI (blue) in obese VAT and SAT. Colocalizations of 11b-HSD1 and CD68 are represented in yellow in the merged image. Scale (Figure legend continues) 3742 INCREASING CD11c+CD163+ ATMs IN HUMAN OBESITY

Microarray analysis revealed that most of the M1 and M2 genes were upregulated at both 24 and 48 h, three genes were up- markers were upregulated in hPBMs cocultured with 14-d differ- regulated at 24 h and downregulated at 48 h, and 26 genes were entiated SGBS adipocytes (Fig. 3E). Similarly, qPCR of the se- downregulated at both 24 and 48 h (Fig. 4A). Among these genes, lected genes confirmed upregulation of the M1 and M2 markers HSD11B1 (11b-HSD1) was found to be highly ranked with sig- (Fig. 3F). The mRNA expressions of monocyte to macrophage nificant upregulation. Hence, we decided to focus on 11b-HSD1 for differentiation–associated 2 (Supplemental Table I) and mature further experiments. macrophage marker CD64 (Fig. 3E, 3F) were upregulated in Fig. 4B shows that the expression of 11b-HSD1 but not 11b- hPBMs cocultured with SGBS adipocytes, suggesting that the HSD2 was upregulated in hPBMs cocultured with SGBS adipo- differentiation of hPBMs might have occurred during the cocul- cytes from both microarray and qPCR analyses. Gene expression ture with SGBS adipocytes. Our results also indicated that ROS results were similarly associated with elevation of the 11b-HSD1 production was significantly increased in hPBMs cocultured with protein (Fig. 4C). 11b-HSD1 converts intracellular cortisone to SGBS adipocytes (Fig. 3G), and that the expression of an oxidative cortisol, which activates GR and downstream signaling (38). Our stress inducible gene, HO-1, was significantly elevated in hPBMs in vitro model confirmed that exposure of hPBMs with cortisol after coculturing with SGBS adipocytes for 48 h (Fig. 3H). markedly induced its surface expression of CD163 in a dose- and Cytokines and chemokines are known to be important factors for time-dependent manner (Fig. 4D) and at the transcriptional level the regulation of M1/M2 polarization in monocytes/macrophages (Fig. 4E). To test whether activation of GR is involved in the (34, 35). We next examined the gene expression levels of cyto- upregulation of CD163 in hPBMs, hPBMs were cocultured with kines, chemokines, and signaling molecules regulating these ex- SGBS preadipocytes or SGBS adipocytes in the absence or pressions, including NF-kB,MAPK,aswellasSTATsignaling, presence of GR antagonist RU-486 and then analyzed by FACS. Downloaded from in SGBS cells during adipogenic differentiation. Expression CD163 expression in hPBMs when cocultured with SGBS adi- of genes representing adipocyte function and differentiation pocytes was abrogated by the treatment with RU-486 in a dose- markers, including LEP (leptin), ADIPOQ (adiponectin), APOE dependent manner (Fig. 4F), indicating that the activation of GR (apolipoprotein E), FABP4 (adipocyte protein 2), LPL (lipo- regulates adipogenic differentiation-induced expression of CD163 protein lipase), LIPE (lipase E), RBP4 (retinol-binding protein in hPBMs, which might be regulated by the upregulation of in-

4), PPARG (peroxisome proliferator–activated receptor g), and tracellular 11b-HSD1. We further examined the expression of http://www.jimmunol.org/ CEBPA (C/EBPa), markedly increased during adipogenic 11b-HSD1 in ATMs in human obese AT. Immunofluorescence differentiation (Supplemental Fig. 2A). However, the expression staining of AT revealed that 11b-HSD1 was expressed in crown of inflammatory cytokines and chemokines, such as IL6 (IL-6), ATMs in obese VAT and SAT (Fig. 4G), and the expression is IL8 (IL-8), and CCL2 (MCP-1), were significantly downregu- higher in crown ATMs compared with noncrown ATMs (Fig. 4H). lated in adipocytes compared with preadipocytes (Supplemental As the number of CLS is very limited in nonobese AT (Fig. 2E), Fig. 2A). The expressions of Th2 cytokines, including IL-4 and the expression level of 11b-HSD1 in ATMs might be upregulated IL-13, which trigger alternative M2 polarization of macrophages in obese individuals. (35), were also not induced in SGBS adipocytes (Supplemental It has been known that 11b-HSD1 is also expressed in adipo- Fig. 2B), suggesting that these representative cytokines and che- cytes (25, 26, 39). Indeed, adipogenic differentiation markedly by guest on September 24, 2021 mokines might not be involved in the regulation of differentiation upregulated the gene and protein expressions of 11b-HSD1 in and polarization of hPBMs in our system. SGBS cells (Fig. 4I). Therefore, we tested whether cortisol pro- Our microarray data showed that the expression of M2 markers duced in SGBS adipocytes is involved in the induction of CD163 was more significantly increased in hPBMs cocultured with SGBS expression in hPBMs. We first measured the concentration of adipocytes than those of M1 markers. Previous reports suggested cortisol in CM of SGBS adipocytes. However, we did not detect that endoplasmic reticulum (ER) stress is a key regulator of al- any cortisol in CM of SGBS adipocytes even after 14 d of differ- ternative activation triggering human M2 macrophage differenti- entiation (S. Nakajima, V. Koh, L.F. Kua, and K. Kono, unpublished ation (36, 37). Indeed, our data showed that the expressions of ER data). We next examined the effect of 11b-HSD1 expression in stress markers were upregulated in hPBMs cocultured with SGBS SGBS cells on the polarization of hPBMs. SGBS cells were tran- adipocytes when compared with hPBMs cocultured with SGBS siently transfected with 11b-HSD1 siRNA or control siRNA and preadipocytes (Supplemental Fig. 3A). Based on previous reports allowed to differentiate to the adipogenic state for 7 d (Fig. 4J). and our data, ER stress might be involved in the induction of M2 After differentiation, SGBS cells were cocultured with hPBMs, polarization of hPBMs induced by coculturing with adipocytes. and the surface expressions of CD11c and CD163 in hPBMs were Our results collectively suggest that adipocyte differentiation assessed. Coculturing with wild-type SGBS adipocytes markedly induces polarization of hPBMs to a mixed M1/M2 phenotype. induced CD163 expression in hPBMs, and the expression per- sisted in the coculture with 11b-HSD1 knockdown SGBS adipo- Upregulation of CD163 expression in hPBMs cocultured with cytes (Fig. 4J), implying that 11b-HSD1–mediated production of SGBS adipocytes through upregulation of intracellular cortisol in SGBS adipocytes does not affect the polarization of b 11 -HSD1 and activation of GR hPBMs. The top 100 most up- and downregulated genes in hPBMs cocultured Taken together, induction of 11b-HSD1 within ATMs might with SGBS adipocytes were retrieved from our microarray data increase the concentration of intracellular cortisol, which induces (Supplemental Table I). Comparative analysis revealed that three CD163 expression in obese individuals.

bars, 100 mm. (H) Representative immunoﬂuorescence staining of serial sections in obese VAT with 11b-HSD1 (red) and DAPI (blue) (left), and CD68 (green), caveolin (red), and DAPI (blue) (right). Scale bars, 100 mm. (I) qPCR and Western blot (IB) analyses of 11b-HSD1 in SGBS cells during adipogenic differentiation (n = 3). Western blotting data are representative of three independent experiments. (J) Knockdown of 11b-HSD1 expression in SGBS cells during adipogenic differentiation for 7 d. Data are representative of three independent experiments (top). Flow cytometry analysis of hPBMs cocultured with or without wild-type SGBS cells, control siRNA-transfected SGBS cells, or 11b-HSD1 siRNA-transfected SGBS cells at 7-d adipogenic differentiation (n = 3) (bottom). *p , 0.05, **p , 0.01, ****p , 0.0001. The Journal of Immunology 3743 Downloaded from http://www.jimmunol.org/

FIGURE 5. Increased breast cancer cell proliferation using CM from coculture of adipocytes with hPBMs. (A) Cell proliferation assay of MCF7 and

MDA-MB-231 cell lines treated with CM from control (gray), hPBMs (blue), SGBS adipocytes (green), or cocultured SGBS adipocytes with hPBMs (red) by guest on September 24, 2021 for 4 d. Data are representative of three independent experiments. (B) qPCR analysis of VEGF-A in MDA-MB-231 cell line treated with each CM for 48 h. Data are representative of three independent experiments. (C) Schematic representation of our experimental conclusions. *p , 0.05, **p , 0.01.

Enhancement of adipocyte-induced breast cancer cell The expression of 11b-HSD1 is induced in human monocytes proliferation by mixed M1/M2 phenotype hPBMs upon differentiation and M2 polarization (42, 43). Our present Obesity might be associated with breast cancer progression (40, data showed that the expression of 11b-HSD1 was induced in 41). We therefore examined whether mixed M1/M2 phenotype hPBMs cocultured with adipocytes, which was involved in the monocytes/macrophages are related to breast cancer progression. expression of the M2 marker CD163 (Fig. 4). According to a Exposure of MCF7 and MDA-MB-231 cells to CM from SGBS published dataset in the National Center for Biotechnology In- adipocytes promoted their proliferation. CM from coculture of formation GEO database (dataset record GDS2429), 11b-HSD1 adipocytes with hPBMs further enhanced the proliferation but not 11b-HSD2 was upregulated in both LPS plus IFN-g– (Fig. 5A), suggesting that mixed M1/M2 phenotype monocytes/ induced human M1-activated macrophages and IL-4–induced macrophages might contribute to obesity-associated tumor human M2-activated macrophages. Moreover, in a murine mac- growth. Moreover, CM from coculture of adipocytes with hPBMs rophage J774.1 cell line, the mRNA expression and enzymatic also enhanced the mRNA expression of vascular endothelial activity of 11b-HSD1 were augmented by LPS stimulation, and growth factor (VEGF)-A in MDA-MB-231 cells (Fig. 5B). These pharmacological inhibition of 11b-HSD1 markedly suppressed data suggest that obesity-induced mixed M1/M2 ATMs might be LPS-induced production of inflammatory cytokines such as IL-1b, involved in obesity-associated tumor growth and angiogenesis TNF-a, and MCP-1 (44), suggesting that 11b-HSD1 regulates not through enhancement of cancer cell proliferation and production only M2 polarization but also M1 polarization. Immunofluores- of VEGF in cancer cells. cence staining of obese AT showed that 11b-HSD1 was highly expressed in crown ATMs compared with noncrown ATMs Discussion (Fig. 4H). A previous report suggested that crown ATMs had a In this study, we report that CD11c+CD163+ ATMs of a mixed M1/ mixed M1/M2 phenotype that expressed CD11c and another M2 M2 phenotype accumulated in obese individuals, and both the marker, CD206 (12). Therefore, 11b-HSD1 might be a general upregulation of intracellular 11b-HSD1 and activation of GR in marker of adipocyte-induced polarization of ATMs. ATMs are important for regulation of the polarization of ATMs. Whereas cortisol levels in blood are mainly controlled by the Additionally, CD11c+CD163+ ATMs might contribute to obesity- hypothalamic–pituitary–adrenal axis, intracellular cortisol levels associated cancer through promotion of cancer cell growth and within each tissue are regulated by 11b-HSD1 (45). AT has been angiogenesis (Fig. 5C). known as a glucocorticoid target tissue, which expresses 11b-HSD1 3744 INCREASING CD11c+CD163+ ATMs IN HUMAN OBESITY and GRs. 11b-HSD1 is known to be expressed in adipocytes, of human ATMs described in this study showed similarities with where it contributes to adipogenic differentiation by converting those reported in human tumor-associated macrophages (TAMs) cortisone to cortisol (46, 47). Cortisol release from AT by 11b- (59–61). Besides enhancing angiogenesis, invasion, and metastasis HSD1 induction in humans has been previously reported (48), of tumor through production of VEGF, IL-8, and epidermal suggesting that released cortisol from adipocytes might affect the growth factor, TAMs also produce IL-10, TGF-b, programmed differentiation and function of other cells, including macrophages, death receptor ligand 1, arginase-1, and PGE2, which induce Treg in AT. However, at least in our in vitro system, cortisol from ad- infiltration to tumor tissues and suppress the activity of cytotoxic ipocytes was not involved in the polarization of hPBMs because T cells and NK cells at the site of the tumor (34, 62). Our data the induction of CD163 expression in hPBMs was not abrogated showed that hPBMs cocultured with mature adipocytes expressed when hPBMs were cocultured with 11b-HSD1 knockdown SGBS several M2 markers that are also expressed in TAMs. Therefore, adipocytes (Fig. 4J). Crown ATMs also expressed 11b-HSD1 in ATMs in obese tissues might be involved in tumor progression. obese subjects (Fig. 4G, 4H), implying that intracellular cortisol In conclusion, our study indicates that a mixed M1/M2 regulated by 11b-HSD1 has critical roles for polarization and/or phenotype of CD11c+CD163+ ATMs accumulated in obese function of ATMs in human obesity. individuals, and that both the upregulation of intracellular 11b- We proposed from our results that ER stress might be involved in HSD1 and activation of GR in ATMs are important for regu- alternative M2 activation of hPBMs when the cells were cocultured lating polarization of ATMs. Prevention of polarization and with SGBS adipocytes. An earlier report suggested that induction accumulation of CD11c+CD163+ ATMs can act as novel ther- of ER stress led to the expression of several M2 markers, including apeutic strategies against obesity-related diseases, and the 11b-

CD36, CD163, and CD206, through activation of c-Jun N-terminal HSD12GR regulatory axis might be a potential target in such Downloaded from kinase in human peripheral monocytes/macrophages (36). Simi- therapies. larly, our microarray analysis also showed that M2 markers such as CD36, CD163, and MRC1 (CD206) (Fig. 3E) and ER stress Acknowledgments markers such as HSPA5 (78-kDa glucose-regulated protein), We are grateful to Dr. Martin Wabitsch and Dr. Takaomi Sanda for providing HYOU1 (oxygen-regulated protein 150 kDa), and DDIT3 (C/EBP- us with experimental materials. We thank Dr. Akihiro Yamamura, Dr. Juni-

homologous protein) were all upregulated in hPBMs cocultured chi Matsuo, Dr. Masaharu Hazawa, Dr. Shojiro Kitajima, Khin Thida Soe, http://www.jimmunol.org/ with SGBS adipocytes (Supplemental Fig. 3A). The release of free Tay Yuh Ling Amy, and Kar Mun Mah for helpful discussions and technical fatty acids (FFAs) (49) and palmitic acid, a representative FFA assistance. having potential to trigger ER stress in human monocytes (50), from hypertrophic adipocytes also suggested that a possible Disclosures mechanism underlying induction of ER stress and M2 polarization The authors have no financial conflicts of interest. in hPBMs might involve FFAs. We therefore examined whether treatment with palmitic acid affects surface expression of CD11c References and CD163 in hPBMs. However, exposure of hPBMs to palmitic 1. Flegal, K. M., B. I. Graubard, D. F. Williamson, and M. H. Gail. 2007. Cause- by guest on September 24, 2021 acid did not affect the expression of both CD11c and CD163 specific excess deaths associated with underweight, overweight, and obesity. (Supplemental Fig. 3B), indicating that FFAs might not play a role JAMA 298: 2028–2037. in the mechanism. 2. Renehan, A. G., M. Tyson, M. Egger, R. F. Heller, and M. Zwahlen. 2008. Body- mass index and incidence of cancer: a systematic review and meta-analysis of It is currently unknown what factors from adipocytes may induce prospective observational studies. Lancet 371: 569–578. differentiation and polarization of hPBMs. Our data suggest that the 3. Bhaskaran, K., I. Douglas, H. Forbes, I. dos-Santos-Silva, D. A. Leon, and L. Smeeth. 2014. Body-mass index and risk of 22 specific cancers: a population- representative pro- and anti-inflammatory cytokines and chemo- based cohort study of 5·24 million UK adults. Lancet 384: 755–765. kines such as IL-4, IL-6, IL-8, IL-13, and MCP-1 might not be 4. Weisberg, S. P., D. McCann, M. Desai, M. Rosenbaum, R. L. Leibel, and involved in the induction of M1/M2 polarization of hPBMs in our A. W. Ferrante, Jr. 2003. Obesity is associated with macrophage accumulation in adipose tissue. J. Clin. Invest. 112: 1796–1808. system (Supplemental Fig. 2). Another candidate is leptin. Our 5. Xu, H., G. T. Barnes, Q. Yang, G. Tan, D. Yang, C. J. Chou, J. Sole, A. Nichols, present data showed that the expression of leptin in AT was ele- J. S. Ross, L. A. Tartaglia, and H. Chen. 2003. Chronic inflammation in fat plays vated in obese individuals (Fig. 2D) and that adipogenic differ- a crucial role in the development of obesity-related insulin resistance. J. Clin. Invest. 112: 1821–1830. entiation induced leptin expression in SGBS cells (Fig. 3B). 6. Cancello, R., and K. Cle´ment. 2006. Is obesity an inflammatory illness? Role of Wabitsch et al. (51) also observed a significant increase of leptin low-grade inflammation and macrophage infiltration in human white adipose tissue. BJOG 113: 1141–1147. release into the CM after adipogenic differentiation of SGBS cells. 7. Dalmas, E., K. Cle´ment, and M. Guerre-Millo. 2011. Defining macrophage Gambero and colleagues (52) reported that human monocytes phenotype and function in adipose tissue. Trends Immunol. 32: 307–314. exposed to leptin expressed surface markers of M2 phenotype 8. Lumeng, C. N., J. L. Bodzin, and A. R. Saltiel. 2007. Obesity induces a phenotypic switch in adipose tissue macrophage polarization. J. Clin. Invest. 117: rather than M1 phenotype. We are currently conducting experi- 175–184. ments to elucidate the link between leptin and induction of 11b- 9. Patsouris, D., P. P. Li, D. Thapar, J. Chapman, J. M. Olefsky, and J. G. Neels. HSD1 in ATMs during obesity. 2008. Ablation of CD11c-positive cells normalizes insulin sensitivity in obese insulin resistant animals. Cell Metab. 8: 301–309. BMI is associated with an increased frequency of many cancers 10. Zeyda, M., D. Farmer, J. Todoric, O. Aszmann, M. Speiser, G. Gyo¨ri, (2, 3). Particularly, obesity is a significant risk factor for breast G. J. Zlabinger, and T. M. Stulnig. 2007. Human adipose tissue macrophages are of an anti-inflammatory phenotype but capable of excessive pro-inflammatory cancer in postmenopausal women (40, 41). Even in premeno- mediator production. Int. J. Obes. 31: 1420–1428. pausal women, the prevalence of estrogen receptor-negative tumor 11. Bourlier, V., A. Zakaroff-Girard, A. Miranville, S. De Barros, M. Maumus, is increased with obesity (53, 54), and some reports have focused C. Sengenes, J. Galitzky, M. Lafontan, F. Karpe, K. N. Frayn, and A. Bouloumie´. 2008. Remodeling phenotype of human subcutaneous adipose tissue macro- on the role of ATMs in obesity-related cancer (55, 56). Indeed, phages. Circulation 117: 806–815. Wagner et al. (57) showed that accumulation of macrophages in 12. Wentworth, J. M., G. Naselli, W. A. Brown, L. Doyle, B. Phipson, G. K. Smyth, M. Wabitsch, P. E. O’Brien, and L. C. Harrison. 2010. Pro-inflammatory CD11c+ inflammatory tumor-associated AT stimulated tumor growth and + CD206 adipose tissue macrophages are associated with insulin resistance in angiogenesis. Moreover, Arendt et al. (58) further demonstrated human obesity. Diabetes 59: 1648–1656. that obesity leads to the recruitment of inflammatory macrophages 13. Kratz, M., B. R. Coats, K. B. Hisert, D. Hagman, V. Mutskov, E. Peris, K. Q. Schoenfelt, J. N. Kuzma, I. Larson, P. S. Billing, et al. 2014. Metabolic in AT, and that these macrophages secreted CXCL12, which acted dysfunction drives a mechanistically distinct proinflammatory phenotype in on blood vessels to enhance angiogenesis. Gene expression profiles adipose tissue macrophages. Cell Metab. 20: 614–625. The Journal of Immunology 3745

14. Hill, A. A., W. Reid Bolus, and A. H. Hasty. 2014. A decade of progress in 39. Arai, N., H. Masuzaki, T. Tanaka, T. Ishii, S. Yasue, N. Kobayashi, T. Tomita, adipose tissue macrophage biology. Immunol. Rev. 262: 134–152. M. Noguchi, T. Kusakabe, J. Fujikura, et al. 2007. Ceramide and adenosine 59- 15. Komohara, Y., Y. Fujiwara, K. Ohnishi, D. Shiraishi, and M. Takeya. 2016. monophosphate-activated protein kinase are two novel regulators of 11b-hydroxysteroid Contribution of macrophage polarization to metabolic diseases. J. Atheroscler. dehydrogenase type 1 expression and activity in cultured preadipocytes. Thromb. 23: 10–17. Endocrinology 148: 5268–5277. 16. Deiuliis, J., Z. Shah, N. Shah, B. Needleman, D. Mikami, V. Narula, K. Perry, 40. Calle, E. E., C. Rodriguez, K. Walker-Thurmond, and M. J. Thun. 2003. J. Hazey, T. Kampfrath, M. Kollengode, et al. 2011. Visceral adipose inflam- Overweight, obesity, and mortality from cancer in a prospectively studied cohort mation in obesity is associated with critical alterations in tregulatory cell num- of U.S. adults. N. Engl. J. Med. 348: 1625–1638. bers. PLoS One 6: e16376. 41. Carmichael, A. R. 2006. Obesity as a risk factor for development and poor 17. Michaud, A., M. Pelletier, S. Noe¨l, C. Bouchard, and A. Tchernof. 2013. prognosis of breast cancer. BJOG 113: 1160–1166. Markers of macrophage infiltration and measures of lipolysis in human ab- 42. Thieringer, R., C. B. Le Grand, L. Carbin, T. Q. Cai, B. Wong, S. D. Wright, and dominal adipose tissues. Obesity (Silver Spring) 21: 2342–2349. A. Hermanowski-Vosatka. 2001. 11b-Hydroxysteroid dehydrogenase type 1 is 18.Boon,M.R.,L.E.Bakker,M.C.Haks,E.Quinten,G.Schaart,L.VanBeek, induced in human monocytes upon differentiation to macrophages. J. Immunol. Y. Wang, L. Van Schinkel, V. Van Harmelen, A. E. Meinders, et al. 2015. 167: 30–35. Short-term high-fat diet increases macrophage markers in skeletal muscle 43. Chinetti-Gbaguidi, G., M. A. Bouhlel, C. Copin, C. Duhem, B. Derudas, B. Neve, accompanied by impaired insulin signalling in healthy male subjects. Clin. B. Noel, J. Eeckhoute, P. Lefebvre, J. R. Seckl, and B. Staels. 2012. Peroxisome Sci. 128: 143–151. proliferator-activated receptor-g activation induces 11b-hydroxysteroid dehydro- 19. Fjeldborg, K., S. B. Pedersen, H. J. Møller, T. Christiansen, M. Bennetzen, and genase type 1 activity in human alternative macrophages. Arterioscler. Thromb. B. Richelsen. 2014. Human adipose tissue macrophages are enhanced but changed Vasc. Biol. 32: 677–685. to an anti-inflammatory profile in obesity. J. Immunol. Res. 2014: 309548. 44. Ishii, T., H. Masuzaki, T. Tanaka, N. Arai, S. Yasue, N. Kobayashi, T. Tomita, 20. Morton, N. M., and J. R. Seckl. 2008. 11b-Hydroxysteroid dehydrogenase type 1 M. Noguchi, J. Fujikura, K. Ebihara, et al. 2007. Augmentation of 11b- and obesity. Front. Horm. Res. 36: 146–164. hydroxysteroid dehydrogenase type 1 in LPS-activated J774.1 macrophages— 21. Seckl, J. R., and B. R. Walker. 2001. Minireview: 11b-hydroxysteroid dehy- role of 11b-HSD1 in pro-inflammatory properties in macrophages. FEBS Lett. drogenase type 1—a tissue-specific amplifier of glucocorticoid action. Endo- 581: 349–354. crinology 142: 1371–1376. 45. Stulnig, T. M., and W. Waldhaüsl. 2004. 11b-Hydroxysteroid dehydrogenase Downloaded from 22.Rask,E.,B.R.Walker,S.So¨derberg, D. E. Livingstone, M. Eliasson, O. Johnson, type 1 in obesity and type 2 diabetes. Diabetologia 47: 1–11. R. Andrew, and T. Olsson. 2002. Tissue-specific changes in peripheral cortisol 46. Bujalska, I. J., S. Kumar, M. Hewison, and P. M. Stewart. 1999. Differentiation metabolism in obese women: increased adipose 11b-hydroxysteroid dehydroge- of adipose stromal cells: the roles of glucocorticoids and 11b-hydroxysteroid nase type 1 activity. J. Clin. Endocrinol. Metab. 87: 3330–3336. dehydrogenase. Endocrinology 140: 3188–3196. 23.Lindsay,R.S.,D.J.Wake,S.Nair,J.Bunt,D.E.Livingstone,P.A.Permana, 47. Hauner, H., P. Schmid, and E. F. Pfeiffer. 1987. Glucocorticoids and insulin P. A. Tataranni, and B. R. Walker. 2003. Subcutaneous adipose 11 promote the differentiation of human adipocyte precursor cells into fat cells. J. b-hydroxysteroid dehydrogenase type 1 activity and messenger ribonucleic Clin. Endocrinol. Metab. 64: 832–835. acid levels are associated with adiposity and insulinemia in Pima Indians and 48. Stimson, R. H., J. Andersson, R. Andrew, D. N. Redhead, F. Karpe,

Caucasians. J. Clin. Endocrinol. Metab. 88: 2738–2744. P. C. Hayes, T. Olsson, and B. R. Walker. 2009. Cortisol release from adipose http://www.jimmunol.org/ 24. Michailidou, Z., M. D. Jensen, D. A. Dumesic, K. E. Chapman, J. R. Seckl, tissue by 11b-hydroxysteroid dehydrogenase type 1 in humans. Diabetes 58: B. R. Walker, and N. M. Morton. 2007. Omental 11b-hydroxysteroid dehydro- 46–53. genase 1 correlates with fat cell size independently of obesity. Obesity (Silver 49. Baglioni, S., G. Cantini, G. Poli, M. Francalanci, R. Squecco, A. Di Franco, Spring) 15: 1155–1163. E. Borgogni, S. Frontera, G. Nesi, F. Liotta, et al. 2012. Functional differences in 25. Napolitano, A., M. W. Voice, C. R. Edwards, J. R. Seckl, and K. E. Chapman. visceral and subcutaneous fat pads originate from differences in the adipose stem 1998. 11b-Hydroxysteroid dehydrogenase 1 in adipocytes: expression is cell. PLoS One 7: e36569. differentiation-dependent and hormonally regulated. J. Steroid Biochem. Mol. 50. Snodgrass, R. G., M. Boß, E. Zezina, A. Weigert, N. Dehne, I. Fleming, Biol. 64: 251–260. B. Brune,€ and D. Namgaladze. 2016. Hypoxia potentiates palmitate-induced pro- 26.Ricketts,M.L.,J.M.Verhaeg,I.Bujalska,A.J.Howie,W.E.Rainey,and inﬂammatory activation of primary human macrophages. J. Biol. Chem. 291: P. M. Stewart. 1998. Immunohistochemical localization of type 1 11b- 413–424. hydroxysteroid dehydrogenase in human tissues. J. Clin. Endocrinol. Metab. 51. Wabitsch, M., R. E. Brenner, I. Melzner, M. Braun, P. Mo¨ller, E. Heinze,

83: 1325–1335. by guest on September 24, 2021 K. M. Debatin, and H. Hauner. 2001. Characterization of a human preadipocyte 27. Makkonen, J., J. Westerbacka, M. Kolak, J. Sutinen, A. Corne´r, A. Hamsten, cell strain with high capacity for adipose differentiation. Int. J. Obes. Relat. R. M. Fisher, and H. Yki-Ja¨rvinen. 2007. Increased expression of the macro- Metab. Disord. phage markers and of 11b-HSD-1 in subcutaneous adipose tissue, but not in 25: 8–15. 52. Acedo, S. C., S. Gambero, F. G. Cunha, I. Lorand-Metze, and A. Gambero. 2013. cultured monocyte-derived macrophages, is associated with liver fat in human obesity. Int. J. Obes. 31: 1617–1625. Participation of leptin in the determination of the macrophage phenotype: an In Vitro Cell. Dev. Biol. 28. Ho¨gger, P., J. Dreier, A. Droste, F. Buck, and C. Sorg. 1998. Identification of the additional role in adipocyte and macrophage crosstalk. integral membrane protein RM3/1 on human monocytes as a glucocorticoid- Anim. 49: 473–478. inducible member of the scavenger receptor cysteine-rich family (CD163). J. 53. Dolle, J. M., J. R. Daling, E. White, L. A. Brinton, D. R. Doody, P. L. Porter, Immunol. 161: 1883–1890. and K. E. Malone. 2009. Risk factors for triple-negative breast cancer in 29. Schaer, D. J., F. S. Boretti, G. Schoedon, and A. Schaffner. 2002. Induction of the women under the age of 45 years. Cancer Epidemiol. Biomarkers Prev. 18: CD163-dependent haemoglobin uptake by macrophages as a novel anti- 1157–1166. inflammatory action of glucocorticoids. Br. J. Haematol. 119: 239–243. 54. Trivers, K. F., M. J. Lund, P. L. Porter, J. M. Liff, E. W. Flagg, R. J. Coates, and 30. Forman, H. J., and M. Torres. 2001. Redox signaling in macrophages. Mol. J. W. Eley. 2009. The epidemiology of triple-negative breast cancer, including Aspects Med. 22: 189–216. race. Cancer Causes Control 20: 1071–1082. 31. Forman, H. J., and M. Torres. 2002. Reactive oxygen species and cell signaling: 55. Khandekar, M. J., P. Cohen, and B. M. Spiegelman. 2011. Molecular respiratory burst in macrophage signaling. Am. J. Respir. Crit. Care Med. 166: mechanisms of cancer development in obesity. Nat. Rev. Cancer 11: 886– S4–S8. 895. 32. Cinti, S., G. Mitchell, G. Barbatelli, I. Murano, E. Ceresi, E. Faloia, S. Wang, 56. Wagner, M., E. S. Samdal Steinskog, and H. Wiig. 2015. Adipose tissue mac- M. Fortier, A. S. Greenberg, and M. S. Obin. 2005. Adipocyte death defines rophages: the inflammatory link between obesity and cancer? Expert Opin. Ther. macrophage localization and function in adipose tissue of obese mice and hu- Targets 19: 527–538. mans. J. Lipid Res. 46: 2347–2355. 57. Wagner, M., R. Bjerkvig, H. Wiig, J. M. Melero-Martin, R. Z. Lin, 33. Fischer-Posovszky, P., F. S. Newell, M. Wabitsch, and H. E. Tornqvist. 2008. M. Klagsbrun, and A. C. Dudley. 2012. Inflamed tumor-associated adipose tissue Human SGBS cells—a unique tool for studies of human fat cell biology. Obes. is a depot for macrophages that stimulate tumor growth and angiogenesis. An- Facts 1: 184–189. giogenesis 15: 481–495. 34. Mantovani, A., S. Sozzani, M. Locati, P. Allavena, and A. Sica. 2002. Macro- 58. Arendt, L. M., J. McCready, P. J. Keller, D. D. Baker, S. P. Naber, phage polarization: tumor-associated macrophages as a paradigm for polarized V. Seewaldt, and C. Kuperwasser. 2013. Obesity promotes breast cancer by M2 mononuclear phagocytes. Trends Immunol. 23: 549–555. CCL2-mediated macrophage recruitment and angiogenesis. Cancer Res. 73: 35. Mantovani, A., A. Sica, S. Sozzani, P. Allavena, A. Vecchi, and M. Locati. 2004. 6080–6093. The chemokine system in diverse forms of macrophage activation and polari- 59. Solinas, G., S. Schiarea, M. Liguori, M. Fabbri, S. Pesce, L. Zammataro, zation. Trends Immunol. 25: 677–686. F. Pasqualini, M. Nebuloni, C. Chiabrando, A. Mantovani, and P. Allavena. 2010. 36. Oh, J., A. E. Riek, S. Weng, M. Petty, D. Kim, M. Colonna, M. Cella, and Tumor-conditioned macrophages secrete migration-stimulating factor: a new C. Bernal-Mizrachi. 2012. Endoplasmic reticulum stress controls M2 macro- marker for M2-polarization, influencing tumor cell motility. J. Immunol. 185: phage differentiation and foam cell formation. J. Biol. Chem. 287: 11629–11641. 642–652. 37. Riek, A. E., J. Oh, J. E. Sprague, A. Timpson, L. de las Fuentes, L. Bernal- 60. Mantovani, A., and A. Sica. 2010. Macrophages, innate immunity and cancer: Mizrachi, K. B. Schechtman, and C. Bernal-Mizrachi. 2012. Vitamin D sup- balance, tolerance, and diversity. Curr. Opin. Immunol. 22: 231–237. pression of endoplasmic reticulum stress promotes an antiatherogenic monocyte/ 61. Mayi, T. H., M. Daoudi, B. Derudas, B. Gross, G. Bories, K. Wouters, J. Brozek, macrophage phenotype in type 2 diabetic patients. J. Biol. Chem. 287: 38482–38494. R. Caiazzo, V. Raverdi, M. Pigeyre, et al. 2012. Human adipose tissue macro- 38. Tomlinson, J. W., E. A. Walker, I. J. Bujalska, N. Draper, G. G. Lavery, phages display activation of cancer-related pathways. J. Biol. Chem. 287: M. S. Cooper, M. Hewison, and P. M. Stewart. 2004. 11b-Hydroxysteroid de- 21904–21913. hydrogenase type 1: a tissue-specific regulator of glucocorticoid response. 62. Qian, B. Z., and J. W. Pollard. 2010. Macrophage diversity enhances tumor Endocr. Rev. 25: 831–866. progression and metastasis. Cell 141: 39–51.

Suppl. Table I: Top 100 ranked up‐ and down‐regulated differentially expressed genes at 24h and 48h

GENE SYMBOL GENE NAME FOLD‐CHANGE

Up‐regulated at 24h HEY2 Hairy/enhancer‐of‐split related with YRPW motif 2 6.87 TM4SF5 Transmembrane 4L six family member 5 5.77 GJD3 Gap junction protein delta 3 5.29 HSD11B1 Hydroxysteroid (11‐beta) dehydrogenase 1, transcript variant 2 4.73 FGFR2 Fibroblast growth factor receptor 2, transcript variant 2 4.54 SERHL2 Serine hydrolase‐like 2 4.48 CDH13 Cadherin 13 H‐cadherin (heart) 4.33 ID4 Inhibitor of DNA binding 4 dominant negative helix‐loop‐helix protein 4.29 BRDT Bromodomain testis‐specific, transcript variant 2 3.92 SSX8 Synovial sarcoma X breakpoint 8 3.85 PDLIM4 PDZ and LIM domain 4 3.83 NPAS1 Neuronal PAS domain protein 1 3.83 SNORD126 Small nucleolar RNA C/D box 126, small nucleolar RNA 3.67 AWAT2 Acyl‐CoA wax alcohol acyltransferase 2 3.60 ARHGEF15 Rho guanine nucleotide exchange factor (GEF) 15 3.58 MTBP Mdm2 transformed 3T3 cell double minute 2 p53 binding protein (mouse) binding protein 3.51 PSG8 Pregnancy specific beta‐1‐glycoprotein 8 3.45 VANGL1 Vang‐like 1 (van gogh Drosophila) 3.44 TAS2R31 Taste receptor type 2 member 31 3.42 FAM231A Family with sequence similarity 231 member A 3.31 PBK PDZ binding kinase 3.30 MMD2 Monocyte to macrophage differentiation‐associated 2 3.26 UNC5A Unc‐5 homolog A (C. elegans) 3.25 PDGF1 Platelet‐derived growth factor alpha polypeptide 3.21 ZP2 Zona pellucida glycoprotein 2 (sperm receptor) 3.17 FUT1 Fucosyltransferase 1 (galactoside 2‐alpha‐L‐fucosyltransferase H blood group) 3.16 GUSBP7 Glucuronidase beta pseudogene 7 3.10 BTNL9 Butyrophilin‐like 9 3.04 WNK4 WNK lysine deficient protein kinase 4 3.03 HHAT Hedgehog acyltransferase 2.99 RPS3AP14 Ribosomal protein S3a pseudogene 14 2.99 HOXB8 Homeobox B8 2.98 RAP1GAP RAP1 GTPase activating protein 2.97 ARHGEF4 Rho guanine nucleotide exchange factor (GEF) 4, transcript variant 1 2.96 GJB5 Gap junction protein beta 5 2.95 ANTXRL Anthrax toxin receptor‐like, non‐coding RNA 2.93 OR8B2 Olfactory receptor family 8 subfamily B member 2 2.90 KRT222 Keratin 222 2.90 CABP5 Calcium binding protein 5 2.89 PDILT Protein disulfide isomerase‐like testis expressed 2.89 TP73 Tumor protein p73 2.87 KRTHA5 Keratin hair acidic 5 2.86 NME1 Non‐metastatic cells 1 protein (NM23A) expressed in, transcript variant 1 2.86 DAPL1 Death associated protein‐like 1 2.85 OR13C8 Olfactory receptor family 13 subfamily C member 8 2.83 XKRY2 XK Kell blood group complex subunit‐related Y‐linked 2 2.82 TM7SF4 Transmembrane 7 superfamily member 4 2.79 SKIDA1 SKI/DACH domain containing 1 2.78 FRMPD1 FERM and PDZ domain containing 1 2.77 CYP24A1 Cytochrome P450 family 24 subfamily A polypeptide 1 nuclear gene encoding mitochondrial protein 2.76 ATP1A2 ATPase Na+/K+ transporting alpha 2 (+) polypeptide 2.74 SETP20 SET pseudogene 20 2.72 CLEC18B C‐type lectin domain family 18 member B 2.72 PRLHR Prolactin releasing hormone receptor 2.69 POLN Polymerase (DNA directed) nu 2.69 MAGEA2B Melanoma antigen family A 2B 2.67 FOXA1 Forkhead box A1 2.67 KRTAP1‐3 Keratin associated protein 1‐3 2.67 PKD1L3 Polycystic kidney disease 1‐like 3 2.63 SLC28A3 Solute carrier family 28 (sodium‐coupled nucleoside transporter) member 3 2.63 IL17REL Interleukin 17 receptor E‐like 2.62 SLC5A7 Solute carrier family 5 (choline transporter) member 7 2.61 EPO Erythropoietin 2.61 SERPINA7P1 Serpin peptidase inhibitor clade A (alpha‐1 antiproteinase, antitrypsin) member 7 pseudogene 1 2.60 MAT1A Methionine adenosyltransferase I alpha 2.60 SFTPA1B Surfactant protein A1B 2.60 TACSTD2 Tumor‐associated calcium signal transducer 2 2.59 RPRD1B Regulation of nuclear pre‐mRNA domain containing 1B 2.58 HOXD12 Homeobox D12 2.58 HYPB Huntingtin interacting protein B, transcript variant 2 2.58 TTBK1 Tau tubulin kinase 1 2.58 AMTN Amelotin 2.57 MAGEB4 Melanoma antigen family B4 2.56 GDF6 Growth differentiation factor 6 2.56 GSX2 GS homeobox 2 2.55 GADL1 Glutamate decarboxylase‐like 1 2.54 CNTF Ciliary neurotrophic factor 2.53 OTOS Otospiralin 2.52 SCGB2A1 Secretoglobin family 2A member 1 2.52 CENPVP3 Centromere protein V pseudogene 3 2.50 MIR942 MicroRNA 942 2.47 CPA1 Carboxypeptidase A1 (pancreatic) 2.45 ELSPBP1 Epididymal sperm binding protein 1 2.44 OR5AY1 Olfactory receptor family 5 subfamily AY member 1 2.42 PRSS16 Protease serine 16 (thymus) 2.42 OR6Q1 Olfactory receptor family 6 subfamily Q member 1 2.41 TFAP2C Transcription factor AP‐2 gamma (activating enhancer binding protein 2 gamma) 2.40 METTL1 Methyltransferase like 1, transcript variant 2 2.40 SLC10A4 Solute carrier family 10 (sodium/bile acid cotransporter family) member 4 2.40 VIL1 Villin 1 2.39 ZNF366 Zinc finger protein 366 2.39 GOLSYN Golgi‐localized protein, transcript variant 7 2.39 C9 Complement component 9 2.38 ELFN2 Extracellular leucine‐rich repeat and fibronectin type III domain containing 2 2.37 CDCA3 Cell division cycle associated 3 2.36 HMGB4 High‐mobility group box 4, transcript variant 1 2.36 KLF14 Kruppel‐like factor 14 2.36 HIST1H2AJ Histone cluster 1 H2aj 2.36 QPRT Quinolinate phosphoribosyltransferase 2.35 SLURP1 Secreted LY6/PLAUR domain containing 1 2.35

Down‐regulated at 24h SLC16A10 Solute carrier family 16 member 10 (aromatic amino acid transporter) ‐4.98 GJB2 Gap junction protein beta 2 ‐4.96 IL24 Interleukin 24, transcript variant 1 ‐4.74 OSM Oncostatin M ‐4.71 DLL1 Delta‐like 1 (Drosophila) ‐4.19 LRRC31 Leucine rich repeat containing 31 ‐4.13 SDS Serine dehydratase ‐3.73 VNN2 Vanin 2, transcript variant 1 ‐3.64 CXCL5 Chemokine (C‐X‐C motif) ligand 5 ‐3.63 OLIG1 Oligodendrocyte transcription factor 1 ‐3.60 THBS1 Thrombospondin 1 ‐3.56 CXCL2 Chemokine (C‐X‐C motif) ligand 2 ‐3.43 CXCL1 Chemokine (C‐X‐C motif) ligand 1 (melanoma growth stimulating activity alpha) ‐3.38 TNFAIP6 Tumor necrosis factor alpha‐induced protein 6 ‐3.14 OLIG2 Oligodendrocyte lineage transcription factor 2 ‐3.11 NEU4 Sialidase 4 ‐3.10 PPAP2B Phosphatidic acid phosphatase type 2B, transcript variant 2 ‐3.09 MET Met proto‐oncogene (hepatocyte growth factor receptor), transcript variant 2 ‐2.98 PTGES Prostaglandin E synthase ‐2.97 E2F2 E2F transcription factor 2 ‐2.96 PROK2 Prokineticin 2 ‐2.94 MERTK C‐mer proto‐oncogene tyrosine kinase ‐2.93 ARL4C ADP‐ribosylation factor‐like 4C ‐2.83 SERPINB2 Serpin peptidase inhibitor clade B (ovalbumin) member 2 ‐2.83 ADA Adenosine deaminase ‐2.81 CCL7 Chemokine (C‐C motif) ligand 7 ‐2.81 DHRS3 Dehydrogenase/reductase (SDR family) member 3 ‐2.79 GAGE12H G antigen 12H ‐2.75 GAGE12C G antigen 12C ‐2.75 HPSE Heparanase ‐2.72 DNER Delta/notch‐like EGF repeat containing ‐2.71 PAPLN Papilin proteoglycan‐like sulfated glycoprotein ‐2.71 GPR160 G protein‐coupled receptor 160 ‐2.69 PRDM8 PR domain containing 8, transcript variant 1 ‐2.67 VMO1 Vitelline membrane outer layer 1 homolog (chicken) ‐2.67 ADAM8 ADAM metallopeptidase domain 8 ‐2.62 SLC22A18AS Solute carrier family 22 (organic cation transporter) member 18 antisense ‐2.62 PPIEL Peptidylprolyl isomerase E‐like pseudogene ‐2.58 CD93 CD93 molecule ‐2.57 SMPDL3A Sphingomyelin phosphodiesterase acid‐like 3A ‐2.55 HIF1A Hypoxia‐inducible factor 1 alpha subunit, transcript variant 2 ‐2.55 WIPI1 WD repeat domain phosphoinositide interacting 1 ‐2.53 GAGE2B G antigen 2B ‐2.50 KIR2DL4 Killer cell immunoglobulin‐like receptor two domains long cytoplasmic tail 4, transcript variant 1 ‐2.50 PID1 Phosphotyrosine interaction domain containing 1 ‐2.49 PPBP Pro‐platelet basic protein (chemokine (C‐X‐C motif) ligand 7) ‐2.45 MS4A4A Membrane‐spanning 4‐domains subfamily A member 4, transcript variant 2 ‐2.41 CHST7 Carbohydrate (N‐acetylglucosamine 6‐O) sulfotransferase 7 ‐2.41 RNASE1 Ribonuclease RNase A family 1 (pancreatic), transcript variant 3 ‐2.38 KIR2DL3 Killer cell immunoglobulin‐like receptor two domains long cytoplasmic tail 3, transcript variant 1 ‐2.37 IL19 Interleukin 19, transcript variant 2 ‐2.34 LGMN Legumain, transcript variant 2 ‐2.31 PFKFB3 6‐phosphofructo‐2‐kinase/fructose‐2,6‐biphosphatase 3 ‐2.29 KIFC3 Kinesin family member C3 ‐2.24 CHST15 Carbohydrate (N‐acetylgalactosamine 4‐sulfate 6‐O) sulfotransferase 15 ‐2.23 GAGE2E G antigen 2E ‐2.23 MS4A14 Membrane‐spanning 4‐domains subfamily A member 14, transcript variant 2 ‐2.23 VNN3 Vanin 3, transcript variant 2 ‐2.22 GATSL3 GATS protein‐like 3 ‐2.19 GAGE6 G antigen 6 ‐2.18 BASP1 Brain abundant membrane attached signal protein 1 ‐2.17 EMR3 Egf‐like module containing mucin‐like hormone receptor‐like 3 ‐2.17 CABLES1 Cdk5 and Abl enzyme substrate 1, transcript variant 1 ‐2.15 PDPN Podoplanin, transcript variant 4 ‐2.12 OLFML2B Olfactomedin‐like 2B ‐2.11 HTRA1 HtrA serine peptidase 1 ‐2.11 CTSLP4 Cathepsin L pseudogene 4 ‐2.10 BTG1 B‐cell translocation gene 1 anti‐proliferative ‐2.10 PLD1 Phospholipase D1 phosphatidylcholine‐specific ‐2.10 THBD Thrombomodulin ‐2.09 INDO Indoleamine‐pyrrole 2,3 dioxygenase ‐2.07 ABTB1 Ankyrin repeat and BTB (POZ) domain containing 1, transcript variant 3 ‐2.07 MAP3K7 MAP3K7 C‐terminal like, transcript variant 1 ‐2.06 CTSLP6 Cathepsin L pseudogene 6 ‐2.05 TMEM71 Transmembrane protein 71 ‐2.05 GAGE12B G antigen 12B ‐2.03 DDIT4 DNA‐damage‐inducible transcript 4 ‐2.00 FLT4 Fms‐related tyrosine kinase 4, transcript variant 2 ‐1.99 APBB3 Amyloid beta (A4) precursor protein‐binding family B member 3, transcript variant 3 ‐1.98 RASGRP3 RAS guanyl releasing protein 3 (calcium and DAG‐regulated) ‐1.98 MAP3K8 Mitogen‐activated protein kinase kinase kinase 8 ‐1.97 PMP22 Peripheral myelin protein 22, transcript variant 2 ‐1.96 TFPI Tissue factor pathway inhibitor (lipoprotein‐associated coagulation inhibitor), transcript variant 1 ‐1.96 NAMPT Nicotinamide phosphoribosyltransferase ‐1.96 MXD1 MAX dimerization protein 1 ‐1.95 MS4A7 Membrane‐spanning 4‐domains subfamily A member 7, transcript variant 2 ‐1.95 LIPN Lipase family member N ‐1.94 HIST1H2AC Histone cluster 1 H2ac ‐1.94 IDO1 Indoleamine 2,3‐dioxygenase 1 ‐1.93 IRAK2 Interleukin‐1 receptor‐associated kinase 2 ‐1.93 SPACA6P Sperm acrosome associated 6 pseudogene ‐1.92 RNASE4 Ribonuclease RNase A family 4, transcript variant 3 ‐1.91 HEY1 Hairy/enhancer‐of‐split related with YRPW motif 1, transcript variant 2 ‐1.90 MMP19 Matrix metallopeptidase 19, transcript variant 2 ‐1.90 ADORA2A Adenosine A2a receptor ‐1.89 CCL20 Chemokine (C‐C motif) ligand 20 ‐1.89 EBI2 Epstein‐Barr virus induced gene 2 (lymphocyte‐specific G protein‐coupled receptor) ‐1.89 DNAH17 Dynein axonemal heavy polypeptide 17 ‐1.89 SERINC2 Serine incorporator 2 ‐1.89 IL1A Interleukin 1 alpha ‐1.85

Up‐regulated at 48h EDN3 Endothelin 3, transcript variant 3 8.93 CCDC141 Coiled‐coil domain containing 141 8.36 LHX8 LIM homeobox 8 7.40 XKRY2 XK Kell blood group complex subunit‐related Y‐linked 2 7.32 SHROOM3 Shroom family member 3 7.29 RAG2 Recombination activating gene 2 7.15 NTF5 Neurotrophin 5 7.05 SLC37A2 Solute carrier family 37 (glycerol‐3‐phosphate transporter) member 2 6.83 TIMM50 Translocase of inner mitochondrial membrane 50 homolog (S. cerevisiae) 6.76 MIRLET7A2 MicroRNA let‐7a‐2 6.74 SSMEM1 Serine‐rich single‐pass membrane protein 1 6.67 GDF3 Growth differentiation factor 3 6.63 CLDN1 Claudin 1 6.45 OR10R2 Olfactory receptor family 10 subfamily R member 2 6.22 FIGLA Folliculogenesis specific basic helix‐loop‐helix 6.19 ART5 ADP‐ribosyltransferase 5 6.09 SRRM4 Serine/arginine repetitive matrix 4 6.08 LRRN4CL LRRN4 C‐terminal like 5.73 MACC1 Metastasis associated in colon cancer 1 5.70 S100A3 S100 calcium binding protein A3 5.64 MEP1B Meprin A beta 5.63 KRT38 Keratin 38 5.48 FAM186B Family with sequence similarity 186 member B 5.46 KIAA1543 KIAA1543 5.45 SALL1 Sal‐like 1 (Drosophila), transcript variant 1 5.45 KIF4A Kinesin family member 4A 5.36 CALML6 Calmodulin‐like 6 5.34 LIMS3 LIM and senescent cell antigen‐like domains 3 5.25 KRT2 Keratin 2 5.23 SERPIND1 Serpin peptidase inhibitor clade D (heparin cofactor) member 1 5.16 TPSD1 Tryptase delta 1 5.13 PDLIM2 PDZ and LIM domain 2 (mystique), transcript variant 1 5.12 DEFA3 Defensin alpha 3 neutrophil‐specific 5.07 GPR44 G protein‐coupled receptor 44 5.06 ZNF521 Zinc finger protein 521 5.03 NRN1L Neuritin 1‐like 4.95 IFITM5 Interferon induced transmembrane protein 5 4.93 KRTAP10‐7 Keratin associated protein 10‐7 4.90 RERG RAS‐like estrogen‐regulated growth inhibitor 4.89 METTL21C Methyltransferase like 21C 4.89 TMEM166 Transmembrane protein 166 4.85 ZDHHC15 Zinc finger DHHC‐type containing 15 4.83 GRIA4 Glutamate receptor ionotrophic AMPA 4, transcript variant 3 4.81 OR4E2 Olfactory receptor family 4 subfamily E member 2 4.81 ETV1 Ets variant 1 4.79 OR1L1 Olfactory receptor family 1 subfamily L member 1 4.64 GAL3ST1 Galactose‐3‐O‐sulfotransferase 1 4.60 MIR412 MicroRNA 412 4.58 OR52R1 Olfactory receptor family 52 subfamily R member 1 4.56 BAAT Bile acid Coenzyme A amino acid N‐acyltransferase (glycine N‐choloyltransferase) 4.51 RAB39 RAB39 member RAS oncogene family 4.51 PDE3A Phosphodiesterase 3A cGMP‐inhibited 4.42 NPM2 Nucleophosmin/nucleoplasmin 2 4.41 EPHB4 EPH receptor B4 4.32 DPH1 DPH1 homolog (S. cerevisiae) 4.31 TTTY17B Testis‐specific transcript Y‐linked 17B (non‐protein coding), non‐coding RNA 4.29 GRP Gastrin‐releasing peptide, transcript variant 3 4.25 ERBB4 V‐erb‐a erythroblastic leukemia viral oncogene homolog 4 (avian) 4.21 MBD3L4 Methyl‐CpG binding domain protein 3‐like 4 4.19 PTPRB Protein tyrosine phosphatase receptor type B 4.16 SPACA5 Sperm acrosome associated 5 4.13 PIWIL3 Piwi‐like 3 (Drosophila) 4.11 PCDHGB8P Protocadherin gamma subfamily B8 pseudogene, non‐coding RNA 4.11 NAT2 N‐acetyltransferase 2 (arylamine N‐acetyltransferase) 4.09 PDZD2 PDZ domain containing 2 4.07 LENG9 Leukocyte receptor cluster (LRC) member 9 4.06 LHX9 LIM homeobox 9, transcript variant 2 4.05 STON1 Stonin 1 4.04 PRR23B Proline rich 23B 4.03 OR5T2 Olfactory receptor family 5 subfamily T member 2 4.03 ASB9 Ankyrin repeat and SOCS box‐containing 9, transcript variant 2 4.02 PSPN Persephin 4.02 NRG2 Neuregulin 2, transcript variant 4 3.99 ZP1 Zona pellucida glycoprotein 1 (sperm receptor) 3.97 FAM153C Family with sequence similarity 153 member C 3.96 PMCH Pro‐melanin‐concentrating hormone 3.94 OR1G1 Olfactory receptor family 1 subfamily G member 1 3.93 TMEM76 Transmembrane protein 76 3.92 MIR181A2 MicroRNA 181a‐2 3.92 HSD11B1 Hydroxysteroid (11‐beta) dehydrogenase 1, transcript variant 2 3.89 ZAR1 Zygote arrest 1 3.88 SLC2A2 Solute carrier family 2 (facilitated glucose transporter) member 2 3.88 MIR602 MicroRNA 602 3.88 TRHDE Thyrotropin‐releasing hormone degrading enzyme 3.86 DAB1 Disabled homolog 1 (Drosophila) 3.86 CASR Calcium‐sensing receptor 3.84 SEMA3G Semaphorin 3G 3.84 OR10Z1 Olfactory receptor family 10 subfamily Z member 1 3.83 MSTP9 Macrophage stimulating pseudogene 9, non‐coding RNA 3.81 PTPN13 Protein tyrosine phosphatase non‐receptor type 13, transcript variant 3 3.80 MIR588 MicroRNA 588 3.80 OR6S1 Olfactory receptor family 6 subfamily S member 1 3.79 VWA5B1 Von Willebrand factor A domain containing 5B1 3.79 SLC5A5 Solute carrier family 5 (sodium iodide symporter) member 5 3.78 OXNAD1 Oxidoreductase NAD‐binding domain containing 1 3.77 CYP11B1 Cytochrome P450 family 11 subfamily B polypeptide 1, transcript variant 1 3.77 MESP1 Mesoderm posterior 1 homolog (mouse) 3.74 CECR2 Cat eye syndrome chromosome region candidate 2 3.73 UGT2B15 UDP glucuronosyltransferase 2 family polypeptide B15 3.73 WNK4 WNK lysine deficient protein kinase 4 3.72

Down‐regulated at 48h HS6ST3 Heparan sulfate 6‐O‐sulfotransferase 3 ‐7.48 SDS Serine dehydratase ‐4.63 DRC1 Dynein regulatory complex subunit 1 ‐4.54 EMR3 Egf‐like module containing mucin‐like hormone receptor‐like 3 ‐4.47 DLL1 Delta‐like 1 (Drosophila) ‐4.31 VNN2 Vanin 2, transcript variant 1 ‐4.18 MST1R Macrophage stimulating 1 receptor (c‐met‐related tyrosine kinase) ‐4.16 GJB2 Gap junction protein beta 2 ‐4.14 FUT1 Fucosyltransferase 1 (galactoside 2‐alpha‐L‐fucosyltransferase H blood group) ‐4.09 REEP2 Receptor accessory protein 2 ‐3.99 CXCL5 Chemokine (C‐X‐C motif) ligand 5 ‐3.94 EXD3 Exonuclease 3'‐5' domain containing 3 ‐3.91 TMEM171 Transmembrane protein 171 ‐3.73 VMO1 Vitelline membrane outer layer 1 homolog (chicken) ‐3.63 IL24 Interleukin 24, transcript variant 1 ‐3.63 MIR521‐2 MicroRNA 521‐2 ‐3.50 CTXN3 Cortexin 3 ‐3.39 TYRP1 Tyrosinase‐related protein 1 ‐3.36 DDIT4 DNA‐damage‐inducible transcript 4 ‐3.34 PAPLN Papilin proteoglycan‐like sulfated glycoprotein ‐3.30 THBS1 Thrombospondin 1 ‐3.28 NUPR1 Nuclear protein transcriptional regulator 1, transcript variant 1 ‐3.26 HIST1H2BA Histone cluster 1 H2ba ‐3.25 FRG2B FSHD region gene 2 family member B ‐3.16 P8 P8 protein (candidate of metastasis 1) ‐3.12 BTNL9 Butyrophilin‐like 9 ‐3.05 SLC2A5 Solute carrier family 2 (facilitated glucose/fructose transporter) member 5 ‐3.05 NEU4 Sialidase 4 ‐3.02 DHRS3 Dehydrogenase/reductase (SDR family) member 3 ‐2.97 PALLD Palladin cytoskeletal associated protein, transcript variant 2 ‐2.96 CXCR4 Chemokine (C‐X‐C motif) receptor 4, transcript variant 1 ‐2.90 PLK2 Polo‐like kinase 2 (Drosophila) ‐2.88 PRR25 Proline rich 25 ‐2.84 TGM2 Transglutaminase 2 (C polypeptide protein‐glutamine‐gamma‐glutamyltransferase), transcript variant 2 ‐2.84 VN1R103P Vomeronasal 1 receptor 103 pseudogene ‐2.82 SHISA9 Shisa family member 9 ‐2.82 ZMYND15 Zinc finger MYND‐type containing 15, transcript variant 2 ‐2.79 SNORD121B Small nucleolar RNA C/D box 121B, non‐coding RNA ‐2.77 LRRN4 Leucine rich repeat neuronal 4 ‐2.76 KCND2 Potassium voltage‐gated channel Shal‐related subfamily member 2 ‐2.76 CABLES1 Cdk5 and Abl enzyme substrate 1, transcript variant 1 ‐2.74 PROK2 Prokineticin 2 ‐2.74 ZNF843 Zinc finger protein 843 ‐2.73 ZEB1 Zinc finger E‐box binding homeobox 1 ‐2.73 SLC7A13 Solute carrier family 7 member 13 ‐2.71 RBP1 Retinol binding protein 1 cellular ‐2.71 SPACA6P Sperm acrosome associated 6 pseudogene ‐2.63 CD300A CD300a molecule ‐2.61 CNTF Ciliary neurotrophic factor ‐2.60 TNFRSF8 Tumor necrosis factor receptor superfamily member 8, transcript variant 1 ‐2.58 TMEM163 Transmembrane protein 163 ‐2.56 OSM Oncostatin M ‐2.55 CCL7 Chemokine (C‐C motif) ligand 7 ‐2.54 SULF2 Sulfatase 2, transcript variant 1 ‐2.54 FAIM3 Fas apoptotic inhibitory molecule 3 ‐2.53 CASC8 Cancer susceptibility candidate 8 (non‐protein coding) ‐2.53 RNASE2 Ribonuclease RNase A family 2 (liver eosinophil‐derived neurotoxin) ‐2.52 PTGES Prostaglandin E synthase ‐2.50 FXYD6 FXYD domain containing ion transport regulator 6 ‐2.46 TMEM71 Transmembrane protein 71 ‐2.46 RAI14 Retinoic acid induced 14 ‐2.45 FAM179A Family with sequence similarity 179 member A ‐2.45 TRAF3IP2 TRAF3 interacting protein 2, transcript variant 1 ‐2.40 HSD17B14 Hydroxysteroid (17‐beta) dehydrogenase 14 ‐2.40 PPIEL Peptidylprolyl isomerase E‐like pseudogene ‐2.39 MS4A14 Membrane‐spanning 4‐domains subfamily A member 14, transcript variant 2 ‐2.39 CADM1 Cell adhesion molecule 1, transcript variant 1 ‐2.38 SLC16A10 Solute carrier family 16 member 10 (aromatic amino acid transporter) ‐2.37 OR5M11 Olfactory receptor family 5 subfamily M member 11 ‐2.37 RGS2 Regulator of G‐protein signalling 2 ‐2.36 DYSF Dysferlin limb girdle muscular dystrophy 2B ‐2.35 TMEM119 Transmembrane protein 119 ‐2.33 SLC10A1 Solute carrier family 10 (sodium/bile acid cotransporter family) member 1 ‐2.33 C4BPA Complement component 4 binding protein alpha ‐2.32 YPEL4 Yippee‐like 4 (Drosophila) ‐2.31 SLAMF9 SLAM family member 9 ‐2.31 PAX5 Paired box 5 ‐2.31 CYBASC3 Cytochrome b ascorbate dependent 3 ‐2.29 MLXIPL MLX interacting protein‐like, transcript variant 2 ‐2.29 CYP4B1 Cytochrome P450 family 4 subfamily B polypeptide 1 ‐2.26 SLC2A1 Solute carrier family 2 (facilitated glucose transporter) member 1 ‐2.26 SEMA4C Semaphorin 4C ‐2.23 MYBPHL Myosin binding protein H‐like ‐2.23 TREM1 Triggering receptor expressed on myeloid cells 1 ‐2.23 GAGE12C G antigen 12C ‐2.22 OMP Olfactory marker protein ‐2.21 JSRP1 Junctional sarcoplasmic reticulum protein 1 ‐2.21 ITGB7 Integrin beta 7 ‐2.19 FAM3D Family with sequence similarity 3 member D ‐2.19 PPBP Pro‐platelet basic protein (chemokine (C‐X‐C motif) ligand 7) ‐2.19 ADCY4 Adenylate cyclase 4 ‐2.18 OR1I1 Olfactory receptor family 1 subfamily I member 1 ‐2.17 PRICKLE3 Prickle homolog 3 (Drosophila) ‐2.16 TTLL4 Tubulin tyrosine ligase‐like family member 4 ‐2.14 GAGE12H G antigen 12H ‐2.14 NKG7 Natural killer cell group 7 sequence ‐2.13 MEP1A Meprin A alpha (PABA peptide hydrolase) ‐2.12 IL8 Interleukin 8 ‐2.12 HSP90B3P Heat shock protein 90kDa beta (Grp94) member 3 (pseudogene) ‐2.12 SLC22A16 Solute carrier family 22 (organic cation/carnitine transporter) member 16 ‐2.11