Mediator of DNA Damage Checkpoint 1 (MDC1) Is a Novel Estrogen Receptor Co-Regulator in Invasive 6 Lobular Carcinoma of the Breast 7 8 Evelyn K

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bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

1 Running Title: MDC1 co-regulates ER in ILC 2 3 Research article 4 5 Mediator of DNA damage checkpoint 1 (MDC1) is a novel estrogen receptor co-regulator in invasive 6 lobular carcinoma of the breast 7 8 Evelyn K. Bordeaux1+, Joseph L. Sottnik1+, Sanjana Mehrotra1, Sarah E. Ferrara2, Andrew E. Goodspeed2,3, James 9 C. Costello2,3, Matthew J. Sikora1 10 11 +EKB and JLS contributed equally to this project. 12 13 Affiliations 14 1Dept. of Pathology, University of Colorado Anschutz Medical Campus 15 2Biostatistics and Bioinformatics Shared Resource, University of Colorado Comprehensive Cancer Center 16 3Dept. of Pharmacology, University of Colorado Anschutz Medical Campus 17 18 Corresponding author 19 Matthew J. Sikora, PhD.; Mail Stop 8104, Research Complex 1 South, Room 5117, 12801 E. 17th Ave.; Aurora, 20 CO 80045. Tel: (303)724-4301; Fax: (303)724-3712; email: [email protected]. Twitter: 21 @mjsikora 22 23 Authors' contributions 24 MJS conceived of the project. MJS, EKB, and JLS designed and performed experiments. JLS developed models 25 for the project. EKB, JLS, SM, and AEG contributed to data analysis and interpretation. SEF, AEG, and JCC 26 developed and performed informatics analyses. MJS wrote the draft manuscript; all authors read and revised the 27 manuscript and have read and approved of this version of the manuscript. 28 29 Key words 30 Invasive lobular carcinoma, breast cancer, estrogen receptor, co-regulator, MDC1 31 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

32 ABSTRACT 33 34 Invasive lobular carcinoma (ILC) is the most common histological subtype of breast cancer, and nearly all ILC 35 tumors express estrogen receptor alpha (ER). However, clinical and laboratory data suggest ILC are strongly 36 estrogen-driven but not equally sensitive to anti-estrogen therapies. We hypothesized that ILC-specific ER 37 transcriptional co-regulators mediate ER functions in ILC and anti-estrogen resistance, and profiled ER-associated 38 proteins by mass spectrometry. Three ER+ ILC cell lines, MDA MB 134VI, SUM44PE, and BCK4, were 39 compared to published data from ER+ invasive ductal carcinoma (IDC) cell lines, and we examined whether 40 siRNA knockdown of identified proteins suppressed ER-driven proliferation in ILC cells. This approach found 41 mediator of DNA damage checkpoint 1 (MDC1), a key tumor suppressor in DNA damage response (DDR), as a 42 putative novel ER co-regulator in ILC. We confirmed ER:MDC1 interaction was specific to ILC cell lines versus 43 IDC cells, and found MDC1 knockdown suppressed ILC cell proliferation and suppressed tamoxifen resistance in 44 MDA MB 134VI. Using RNA-sequencing, we found that in ILC cells, MDC1 knockdown broadly dysregulates 45 the estrogen-driven ER transcriptome, with ER:MDC1 target genes enriched for hormone-response-elements in 46 their promoter regions. Importantly, our data are inconsistent with MDC1 regulating ER via MDC1 DDR and 47 tumor suppressor functions, but instead suggest a novel oncogenic role for MDC1 in mediating ER transcriptional 48 activity as a co-regulator. Supporting this, in breast tumor tissue microarrays MDC1 protein was frequently low or 49 absent in IDC or ER- ILC, but MDC1 loss is rare in ER+ ILC. ER:MDC1 interaction and MDC1 co-regulator 50 functions may underlie cell type-specific ER functions in ILC, and serve as important biomarkers and therapeutic 51 targets to overcome anti-estrogen resistance in ILC. 52 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

53 INTRODUCTION 54 55 Invasive lobular carcinoma (ILC) is the most common histological subtype of breast cancer relative to 56 invasive ductal carcinoma (IDC, no special type). ILC accounts for 10-15% of new breast cancer diagnoses 57 (~40,000 new cases annually) in the United States, making ILC among the top 10 most frequently diagnosed 58 cancers affecting women [1, 2]. Despite this prevalence and the unique clinical presentation of ILC [3, 4], only 59 recently have clinical and laboratory studies focused on ILC begun to characterize ILC as a unique disease among 60 breast cancers. 61 As ~95% of ILC express estrogen receptor alpha (i.e., are ER+) and >80% classify as the hormone- 62 dependent Luminal A molecular subtype [2], ILC is presumed to respond to anti-estrogens (tamoxifen or 63 aromatase inhibitors, AIs); however, prospective studies of ILC outcomes have yet to be reported. In retrospective 64 studies compared to IDC, patients with ILC have worse long-term outcomes, regardless of ER status. Reduced 65 disease-free and overall survival for patients with ILC >5-10y post-diagnosis have been confirmed in studies in 66 Europe (total n=18397, n=2033 ILC; [5–7]) and the US (NCI SEER; n≈800k; n≈85k ILC [8]). In SEER, ILC 67 patients had decreased disease-free survival (IDC:ILC HR=0.809, p<0.0001) and overall survival (HR=0.775, 68 p<0.0001) beyond 5 years post-diagnosis [8]. These data parallel the decades of recurrence risk faced by patients 69 with ER+ cancer [9], and indicate that despite being largely ER+/Luminal A, current therapies are not curative for 70 many patients with ILC. 71 Though nearly all patients with ILC are treated with anti-estrogens (since ~95% are ER+), the efficacy of 72 anti-estrogens for ILC is unclear. To address this, Metzger et al analyzed the BIG 1-98 trial (n=2923, n=324 ILC), 73 which compared adjuvant tamoxifen to the AI letrozole [10]. Letrozole-treated patients with ILC had similar 74 outcomes to IDC; however, tamoxifen-treated ILC patients had increased recurrence and poorer survival (8y 75 recurrence 34%, vs 25% in IDC; 8y overall survival 74%, vs 84% in IDC). Poor outcomes and tamoxifen 76 resistance were also reported for the ABCSG-8 trial [11]. Paralleling clinical data, we and others find ER+ ILC 77 models are tamoxifen-resistant, including de novo ER partial agonism by anti-estrogens, including both tamoxifen 78 and oral selective ER degraders [12–16]. Further, in cell line and in vivo ILC models, we found ER regulates 79 hundreds of unique target genes via distinct ER DNA binding [12], and that ER regulates novel signaling 80 pathways critical for endocrine response and resistance in ILC, such as cell-intrinsic Wnt signaling via WNT4 81 [12, 17–19]. Taken together, these data suggest ER has distinct function in ILC cells versus other breast cancer 82 cells. 83 Transcription factors including ER control gene expression by binding DNA to recruit transcriptional 84 machinery including co-regulator proteins [20]. Importantly, cell type-specific co-regulator functions can mediate 85 cell type-specific transcription factor activity and responsiveness to selective ER modulators (SERMs) [21, 22], 86 suggesting that co-regulator activity may mediate ILC-specific ER functions and SERM resistance. Consistent bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

87 with this, data from the Cancer Genome Atlas (TCGA) also suggest that ILC is a unique context for ER function. 88 In breast cancer cells, ER requires the pioneer factors FOXA1 and GATA3 to access DNA [23, 24], but mutations 89 in these factors are differentially enriched in ILC versus IDC (among Luminal A tumors). FOXA1 mutations are 90 enriched in ILC vs IDC (7% vs 2%), while GATA3 mutations are depleted in ILC vs IDC (5% vs 13%) [2]. The 91 role of these mutations is unclear, but these data support that ILC-specific functions of ER-interacting proteins 92 create a unique context for ER function in ILC cells. 93 Based on these observations, we hypothesized that unique ER co-regulators mediate distinct ER functions 94 in ILC, and profiled ER interacting proteins by the immunoprecipitation/mass spectrometry (IP/MS) method 95 RIME (Rapid IP and MS of Endogenous proteins [25]). RIME uses crosslinking with formaldehyde prior to IP to 96 preserve protein complexes, and was developed to identify ER co-regulators [26]. This approach led us to identify 97 MDC1 (mediator of DNA damage checkpoint 1) as a putative novel co-regulator of ER in ILC cells, where we 98 found MDC1 is required for ER-driven proliferation and gene regulation. These data led us to further investigate 99 the novel ER co-regulator functions of MDC1 in ILC cells. 100 101 RESULTS 102 103 RIME identifies ILC-specific ER-associated proteins and putative novel co-regulators 104 105 To identify ILC-specific ER co-regulator proteins, we profiled ER-associated proteins in ILC models 106 using RIME [25, 26]). We performed ER RIME with ER+ ILC cell lines MDA MB 134VI (MM134), SUM44PE 107 (44PE), and BCK4 in full serum treated with either vehicle (0.1% EtOH) or 1μM 4-hydroxytamoxifen (4OHT). 108 MS analyses identified 416, 231, and 333 ER-interacting proteins in MM134, 44PE, and BCK4 respectively 109 (Figure 1A; Supplemental File 1). Notably, few proteins specific to either vehicle or 4OHT conditions were 110 identified (Supplemental Figure 1). To identify putative ILC-specific ER-associated proteins, we compared 111 proteins identified in at least 2 ILC models (n=188) to ER RIME data from IDC cell lines MCF7 and ZR75- 112 1 (union, n=713 [26]). This identified ILC-specific ER-associated proteins (n=115), and ER-associated proteins 113 common to ILC and IDC cells (n=73) (Figure 1B; Supplemental File 1). We queried these proteins in the 114 STRING database [29] (Figure 1C-E), and among ILC-specific ER-associated proteins this identified a network 115 of epigenomic regulators and known co-regulators (e.g. DNMT1, KMT2D, BRD4, SAFB), and a DNA repair 116 network (e.g. FEN1, POLD2) (Figure 1C, E). Among ER-associated proteins common to ILC and IDC cells, this 117 identified a gene regulatory network of established ER co-regulators (e.g. EP300, GATA3, FOXA1, GREB1, 118 NCOA3) (Figure 1D, E). These data show ER associates with a core network of common co-regulator proteins in 119 ILC and IDC cells, but that ER also interacts with network of unique putative co-regulators in ILC cells. 120 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. A MM134 B ILC (n=416) ER-associated 26839 104 Proteins (n=188) 48 44PE 115 73 640 (n=231) 61 40 MCF7/ZR75-1 (IDC) Union 184 (n=713) BCK4 ILC-specific Shared (n=333) MAPRE1 ILC-specific DST E OFD1 PIBF1 WAPAL WAPL C CEP131 C2CD3 PIBF1 CSNK1E Mitosis, G2/M, PCM1 COL3A1 COL1A2 PDE4DIP Centrosome OFD1 MAPRE1 FLG2 PRKAR2A ILC-specific C2CD3 PDE4DIP SLTM CEP131 PREP AKAP9 SLTM LTA4H DST PCM1 MACF1 SNRNP70 CSNK1E CAMSAP3 FIP1L1 AKAP9 NUDCD2 HTATSF1 SNW1 EML2 SERPINA5 TTN PTGR1 SNRPB2 NHP2L1 PRKAR2A TRA2B mRNA splicing FKBP3 CPSF1 FKBP3 C4B C3 STMN1 DPYSL2 CPSF1 FNDC3A PPIH SNU13 MBNL1 FIP1L1 MAPK1 VANGL1 PPIH SNRNP70 C4A EML2 RHOA PPFIBP1 TRA2B SNRPB2 CPT1A FGFR1OP2 SNW1 FKBP1A YME1L1 EML4 FMR1 CTTNBP2NL PP2A binding, RBM12B STRN DNMT1 AFG3L2 STRN4 WD40 repeat HMGB2 HTATSF1 TFAP2B STOM 5 STRIP1 NCOA5 SAFB STRN3 ESR1 SUCLG1 AK2 PGAM5 RBX1 KMT2D TMEM160 BRD4 PMVK SMARCA2 SUMO2 TFAP2A ESR1 Gene regulation, RNF213 POLD2 BRD4 SEPT11 SEPT9 SAFB PNP NFYC SUMO2 Chromatin MDC1 UBR2 FEN1 SMARCA2 DNMT1 GLUD1 KMT2D remodeling NUDCD2 AK1 4 RHOA NFIC CPT1A Cell NELFE STMN1 STRN DPYSL2 morphogenesis MAPK1 VANGL1 EML4 BANF1 FEN1 STRN4 RBX1 FGFR1OP2 TMEM194A PGAM5 DNA synthesis/ STRN3 UBR2 repair STRIP1 SUN1 3 POLD2 PPFIBP1 RNF213 CTTNBP2NL NRM IP: IgG ER ER Rx: Veh Veh 4OHT 4 4 4 4 4 4 4 4 4 Cell Line: 3 4 3 4 3 4 1 B 1 B 1 B YLPM1 NAP1L4 D ADNP Shared SMARCE1 ADNP 2 CTBP1 NAP1L4 TRPS1 Shared SMARCC2 CTBP2 CTBP2 SMARCC2 CHD4 SMARCD2 NCOA3 TBL1XR1 TCEA1 CTBP1 EP300 AES NRIP1 XPO5 GATAD2B GATA3 SMARCE1 OTUB1 1 SMARCA4 Gene regulation, SMARCA4 TLE3 GATAD2B PSMD9 PSMD9 Chromatin CHD4 NCOR2 TLE3 TNKS1BP1 NRIP1 remodeling LUC7L FOXA1 TRIM24 SART3 SRRT CREBBP FOXA1 SMC1A TCEA1 GATA3 NCOR2 CPSF7 EP300 CREBBP NCBP1 TFAP2C TFAP2C 0 AES SMC1A GREB1 GRHL2 SMARCD2 PRPF31 ESR1 TBL1XR1 SNRPA PDS5A NCOA3 GREB1 DDX42 ESR1 SMU1 YLPM1 TRIM24 TRPS1 GRHL2 SF1 OTUB1 PDS5A RBM4 CTSD LUC7L RBM4 DNAJB1 CELF1 TNKS1BP1 HBB NCBP1 SF1 SART3 mRNA splicing NOSIP HSPE1 FBRS DDX42 CELF1 P4HB XPO5 SNRPA SRRT LONP1 COL1A1 PRPF31 DCAF7 CPSF7 CLPX IRF2BP1 SMU1 IRF2BP2 NOSIP CLPX GALK1 LONP1 ZNF703 DNAJB1 Protein folding STOML2 STOML2 HSPE1 IP: IgG ER ER Rx: Veh Veh 4OHT 4 4 4 4 4 4 4 4 4 Cell Line: 3 4 3 4 3 4 1 B 1 B 1 B bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Figure 1. RIME identifies unique ER-associated proteins in ILC cell lines. (A), ER co-IP/MS was performed using RIME as described in Materials and Methods using three ER-positive ILC cell lines. ER-associated proteins identified in at least 2 cell lines were used in subsequent analyses. (B), Proteins identified in (A) were compared to ER RIME in IDC models MCF7 and ZR751 from Mohammed, 2013. (C), ILC-specific ER-associated proteins (n=115; plus ER/ESR1, total n=116) were used for network analyses using the STRING database (v11.0; October 2019). Colored clusters were generated in STRING using MCL clustering. (D), STRING network analysis as in (C) for ER-associated proteins common to ILC and IDC (n=73, including ER). (E), Clusters from (C-D) with >5 members are highlighted; colored bars match circle colors in (C-D) network maps. Heatmaps show the mean spectral counts of technical duplicates for each protein, per cell line and treatment/IP condition. 134 = MDA MB 134VI; B4 = BCK4; 44 = SUM44PE. Functional notations for clusters listed at right are derived from gene ontology analyses using MSigDB/DAVID. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

121 Mediator of DNA damage checkpoint 1 (MDC1) is critical for ER function in ILC cells 122 123 We functionally profiled identified ER-associated proteins using an siRNA screen to determine how 124 target knockdown affected ER activity in MM134 (ILC) cells, and hypothesized that knocking down ER co- 125 regulators would suppress ER-mediated cell proliferation driven by E2 or tamoxifen [12]. We selected 133 126 proteins from RIME for screening, supplemented with co-regulators over-expressed in ER+ ILC versus ER+ IDC 127 (n=25; n=10 other differentially expressed co-regulators were added ad hoc). We also included transcription 128 factors with binding motifs flanking an ER binding site for the ILC-specific ER target gene WNT4 as factors with 129 putative functions to regulate ER activity in ILC [17](n=31) (total n=199, Supplemental File 2). MM134 cells 130 were hormone-deprived prior to siRNA transfection; 24hrs post-transfection, cells were treated with vehicle 131 (0.01% EtOH), 100pM estradiol (E2), or 100nM 4OHT. Additionally, because androgen receptor (AR) can drive 132 growth independently of ER in MM134 (Supplemental Figure 2A), we treated cells with synthetic androgen Cl- 133 4AS-1 (100nM) for counter-screening to identify ER-specific co-regulators. Six days post-treatment, cell 134 proliferation was assessed by dsDNA quantification, and we identified siRNAs that suppressed E2- and/or 4OHT- 135 driven growth, but did not reduce growth in vehicle- and/or androgen-treated conditions (complete dataset in 136 Supplemental File 3). Of note, siRNA targeting the ILC-specific ER-centered ‘gene regulation’ network (yellow 137 in Figure 1C/E, e.g. KMT2D, BRD4) did not pass the latter criteria and suppressed cell number in vehicle 138 conditions, suggesting a role for these proteins in ILC cell viability (Supplemental Figure 2B). Using these 139 filters, we identified 82 targets for which knockdown suppressed ER-driven proliferation (i.e. via E2 or 4OHT) 140 (Figure 2A, Supplemental File 3). siRNAs targeting ER itself (siESR1) and pioneer factor FOXA1 (siFOXA1) 141 were among the top hits, acting as positive controls for the siRNA screen; few siRNAs showed differential 142 suppression of E2- versus 4OHT-induced growth (Supplemental Figure 2C). Interestingly, siRNA targeting 143 MDC1 (siMDC1) was equivalent to siESR1 in suppressing both E2- and 4OHT-induced growth, and not affecting 144 AR-driven growth, suggesting MDC1 is associated with ER function (Figure 2B). Based on this, we further 145 examined MDC1 as a novel ER co-regulator in ILC cells. 146 We confirmed that MDC1 (mediator of DNA damage checkpoint 1) interacts with ER by co-IP, using a 147 different ER antibody (D8H8) than used for RIME (sc-543); ER:MDC1 interaction was observed in ILC cell lines 148 MM134 and 44PE but not in IDC cell line MCF7 (Figure 2C). ER:MDC1 interaction was also confirmed via the 149 reciprocal IP of MDC1, and we found that the ER:MDC1 interaction is not DNA-dependent as co-IP was not 150 ablated by treatment with benzonase or ethidium bromide (Figure 2D). Notably, ER:MDC1 interaction was also 151 observed in ER RIME from Martin et al using 44PE and an anti-estrogen resistant 44PE variant with mutant ER 152 (Y537S), as MDC1 was among the top 10 proteins identified by peptide count in both models (Figure 2E) [30]. 153 We further examined ER:MDC1 interaction in a panel of ER+ cell lines, and first confirmed that MDC1 is 154 expressed across ILC cell lines (MM134, MM330, 44PE, CAMA1) and IDC cell lines (MCF7, T47D, HCC1428), bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. %Growth vs. Ctrl MM134 Proliferation IP: A B C Input IgG ER 0 100 * 250kD 8 * MM134 siRNA Group E2 4OHT (ILC) NT control - - ESR1 ns IB: 44PE MDC1 RIME ns ZEB1 WNT4 ns MDC1 (ILC) CDCA5 RIME MCF7 FOXA1 RIME 4 TCEAL3 RIME * (IDC) TAGLN OE * ns ns SNW1 RIME Control +Benzonase +EtBr HOXA5 WNT4 D CDKN1C OE CAV1 OE RELB WNT4 IP: S100A9 RIME HEXIM1 RIME 0 BANF1 RIME siNT siESR1 siMDC1 ER 50kD DNTTIP1 RIME THRAP3 RIME Input: Ctrl +Bz +EtBr STRN3 RIME Veh 4OHT SUN1 RIME E2 Cl-4AS-1 ER CPSF1 RIME AHR WNT4 TRIM24 RIME F ILC IDC RACK1 RIME MM134 MM330 44PE CAMA1 MCF7 HCC1428 T47D CEBPA WNT4 S100A8 RIME 250kD 250kD IGFBP2 RIME MDC1 MDC1 STAT5A WNT4 GATAD2A RIME Total Total CDK13 RIME NFIC RIME siRNA: – – – PPP1CB RIME – UNK RIME OCIAD1 RIME RACGAP1 RIME FXR2 RIME PDS5A RIME UBE2I RIME G MM134 ER:MDC1 ER:FOXA1 TNRC18 RIME NFYC RIME Control (siNT) Fulv. Control MBNL1 RIME LATS2 OE TRIM25 RIME KLF12 WNT4 POLD2 RIME ATRX RIME NCOA5 RIME CELF1 RIME FOXO1 OE NCOA1 RIME SRRT RIME 10.9±11.4 3.4±2.6 13.6±8.1 PDCL RIME RAB35 RIME ARID5A OE siESR1 siMDC1 Fulv. CCND3 OE HMG20A RIME SORBS3 OE SLTM RIME PPARG WNT4 EDF1 RIME NFKB2 WNT4 FOXJ2 WNT4 NKX6-1 WNT4 RNF213 RIME NRIP2 OE 4.8±4.0 5.8±5.4 3.8±3.6 IRX5 RIME DNAJC7 RIME RECQL RIME H 44PE CAMA1 MM330 HCC1428 MCF7 T47D PYCARD RIME GLO1 RIME PRKACA RIME DNAJC17 RIME TAL1 WNT4 FOXA2 WNT4 CKAP2 RIME PSMD10 RIME STC2 RIME 12.5±9.2 22.2±9.4 20.4±12.6 3.9±5.8 2.9±3.6 4.2±3.6 NDUFC2 RIME MZF1 WNT4 BCL11B OE GSN RIME PIBF1 RIME C11orf58 RIME 44PE 44PE/ERmut 6.4±6.2 14.6±12.7 5.4±4.6 6.0±6.5 6.4±6.2 3.2±3.6 E 40

10 3.6±5.1 12.5±6.0 11.1±8.3 8.1±8.0 3.4±4.3 3.3±3.3 0 ILC cell lines IDC cell lines ESR1 MDC1 GREB1 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Figure 2. MDC1 is a novel ER-associated protein in ILC cells and is required for ER-driven proliferation. (A-B), MM134 cells were hormone-deprived prior to siRNA transfection, then treated with vehicle (0.01% EtOH), 100pM E2, 100nM 4OHT, or 100nM Cl-4AS-1 (synthetic androgen). After 6d, proliferation was measured by dsDNA quantification. (A), Growth vs mock siRNA control for E2 and 4OHT treatments. ‘Group’ represents context for gene inclusion in siRNA panel: RIME= identified by RIME; WNT4= transcription factor motif at ER binding site in WNT4 gene; OE= over-expressed in ER+ ILC vs ER+ IDC. (B), Data from screen in (A). *, p<0.05; n.s. = not significant; ANOVA w/ Dunnett’s multiple correction. (C), Nuclei (input) from cells in full serum were extracted prior to co-IP; ER co-IP enriched MDC1 vs IgG in ILC cell lines but not MCF7 (IDC). (D), Nuclear extracts were treated with benzonase (+Bz) or ethidium bromide (+EtBr) prior to co-IP to disrupt DNA structure and prevent DNA-dependent co-IP. MDC1 co-IP enriched ER vs IgG, reciprocal co-IP to (C). (E), Peptide counts from Martin et al 2017, points represent biological triplicate RIME samples. (F), Breast cancer cells were transfected with siNT or siMDC1 48hrs prior to lysate harvest for immunoblot. -, mock transfection (reagent only). Single v double bands at ~250kD are related to polyacrylamide gel strength. Ponceau stain for total protein shown as loading control. (G), Proximity ligation assay (PLA) in MM134 for ER:MDC1 (left) or ER:FOXA1 (right, as control). (H), PLA for ER:MDC1 as in (G). Values in G-H represent mean foci/cell +/- SD; complete quantification for (G-H) and statistical comparisons are shown in Supplemental Figure 3. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

155 and that MDC1 levels are suppressed by siRNA (Figure 2F; doublet v single band at 250kD is due to gel 156 strength, data not shown). Proximity ligation assay (PLA) confirmed ER:MDC1 interaction in MM134, consistent 157 with RIME and co-IP data; PLA signal was ablated by siMDC1 or siESR1 which confirms assay/antibody 158 specificity (Figure 2G). In the cell line panel, ER:MDC1 PLA signal was detected in all ILC models and 159 suppressed by target knockdown, consistent with ER:MDC1 proximity/interaction. In IDC models, lower PLA 160 signal was observed but was not suppressed by siRNA, consistent with non-specific signal (Figure 2H; 161 quantification and statistics in Supplemental Figure 3). Taken together with RIME and co-IP data, this supports 162 that ER:MDC1 interaction is specific to or enriched in ILC cells. 163 Paralleling these interaction data, MDC1 knockdown suppressed proliferation in four ILC cell lines 164 (MM134, 44PE, CAMA1, MDA MB 330/MM330; Figure 3A-B). In IDC cell lines, MDC1 knockdown 165 suppressed proliferation in MCF7, but not in HCC1428 or T47D (Figure 3A). We confirmed that individual 166 constructs from the siMDC1 pool utilized suppress ILC cell proliferation (Figure 3B). Importantly, suppression 167 of proliferation by MDC1 knockdown is incongruous with canonical functions of MDC1 in DNA damage 168 response, where MDC1 knockdown or loss ablates cell cycle checkpoints and allows unchecked proliferation [31, 169 32]. However, consistent with the effects of cell proliferation, siMDC1 halted cell cycle progression in MM134 170 (ILC) cells causing a G2/M arrest (Figure 3C). This G2/M arrest upon MDC1 knockdown contrasts G1/S arrest 171 upon ER knockdown, suggesting MDC1 plays a discrete role in ER-mediated cell proliferation. siMDC1 did not 172 impact cell cycle distribution in MCF7 cells, suggesting that the decrease in proliferation in MCF7 after MDC1 173 knockdown is related to loss of DNA repair capacity (siMDC1 also did not impact cell cycle in HCC1428, not 174 shown). Taken together, our data suggest MDC1 is uniquely critical for ER function in ILC cells, i.e. in the 175 context of ER:MDC1 interaction. 176 177 MDC1 is required for regulation of the ER transcriptome in ILC cells 178 179 MDC1 canonically mediates DNA damage response but has also implicated as a transcriptional regulator 180 (see Discussion), consistent with a putative role as an ER co-regulator in ILC. We found MDC1 knockdown 181 ablated regulation of ER target genes in MM134 cells (Supplemental Figure 4A), blocking E2-driven induction 182 of WNT4, IGFBP4, PDZK1, and TFCP2L1, and repression of PDE4B. This effect of siMDC1 was not universal, 183 as TFF1 induction in MM134 was unaffected. No effect was observed on these ER target genes in IDC cell line 184 HCC1428. To define how the ER transcriptome requires MDC1, we performed RNA-sequencing (RNAseq) after 185 MDC1 knockdown in ILC models MM134 and MM330, and IDC model HCC1428 (schema in Figure 4A). ESR1 186 knockdown (siESR1) was included to define ER target genes, and FOXA1 knockdown (siFOXA1) was included 187 to compare the role of MDC1 vs FOXA1. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. A siNT siMDC1 siESR1 1.2 ns

1.0 ns *

0.8 * * * 0.6 * ** * * 0.4 *

ILC IDC B MM134 MM330 HCC1428 1.4 (ILC) (ILC) (IDC) *

1.2

1.0 * * * * 0.8 * * 0.6 *

0.4

siMDC1 siMDC1 siMDC1 C MM134 MCF7 *** **ns 100

G2/M

50 S G1

Figure 3. MDC1 is required for ER-mediated proliferation in ILC cells. (A-B), Cell proliferation was assessed by dsDNA quantification 6d after siRNA transfection. *, p<0.05, ns, not significant vs siNT; ANOVA with Dunnett’s multiple correction. Bars represent mean of 5-6 biological replicates +/- SD. (B), Individual siRNA constructs from the siMDC1 pool were transfected. (C), Cells were fixed for cell cycle analyses 72hr after siRNA transfection. *, p<0.05, ns, not significant vs siNT; ANOVA. Bars represent mean of 3-4 biological replicates +/- SEM. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

188 We found MDC1 is required for a large proportion of the ER-driven transcriptome (Figure 4B, 189 Supplemental File 4). In MM134 cells, among n=3599 ER target genes, 57.3% were dysregulated upon MDC1 190 knockdown, and a similar proportion were dysregulated by FOXA1 knockdown (56.1%). This included 191 genes dysregulated by either MDC1 or FOXA1 knockdown (n=1387, 38.5%), but 18.8% (n=675) and 17.6% 192 (n=633) of ER target genes specifically required MDC1 or FOXA1, respectively. As expected, FOXA1 193 knockdown also dysregulated a majority of ER target genes in MM330 and HCC1428 (54.0% and 59.9%, 194 respectively), while MDC1 played a smaller role in the ER transcriptome in these cells compared to MM134 195 (23.9% and 32.1% of ER target genes in MM330 and HCC1428, respectively). siMDC1 dysregulated a large 196 proportion of the ER transcriptome in both ILC and IDC cells, despite disparate effects on cell proliferation, but 197 only a subset of ER:MDC1 target genes overlapped across models (Figure 4C, Supplemental File 4). Based on 198 this, we examined ER-driven regulatory pathways differentially effected by MDC1 knockdown in each cell 199 line (Figure 4D, Supplemental File 5). When considering all MDC1-regulated genes, the MsigDB Hallmark 200 signatures [33] for estrogen response were enriched in all 3 models, along with mTORC1 signaling (a 201 downstream component of ER signaling). However, Hallmark and Reactome DNA repair pathways were enriched 202 specifically in HCC1428 (Figure 4D). Differential enrichment of DNA repair pathways in the ILC v IDC models 203 suggests the role of MDC1 in ER function in IDC is related to DNA damage response [34], but in ILC cells 204 MDC1 is potentially acting instead as an ER transcriptional co-regulator. 205 Similarly, we examined regulatory sequences in the promoters of ER:MDC1 target genes by querying 206 identified target genes (from groups in Figure 4C) against the cisTarget database [35]. Notably, ILC-specific 207 ER:MDC1 target genes were heavily enriched for estrogen-response-elements and half-elements (ESR1 sites and 208 ESRR sites, respectively) and other nuclear receptor motifs (ROR, NR sites) (Figure 4E, Supplemental File 6). 209 ER:MDC1 targets shared in all three cell lines were instead predominantly enriched for AP2 motifs 210 (TFAP2A/TFAP2C), while ER:MDC1 targets unique to the IDC cell line HCC1428 were enriched for E2F 211 motifs. Similar enrichments were not observed in individual cell lines (Supplemental Figure 4B) or in other 212 overlapping pairs. The enrichment for ER sites in ER:MDC1 targets in ILC cells supports a unique role of MDC1 213 as an ER co-regulator in ILC cells. 214 Since MDC1 and FOXA1 regulate some distinct components of the ER transcriptome in ILC cells, we 215 examined whether MDC1 versus FOXA1 target genes had distinct regulatory features in their promoter regions. 216 We identified ER target genes for which siRNAs caused complete suppression of ER regulation (i.e. reversed 217 expression to the estrogen-deprived baseline; Supplemental Figure 4C-D). From these, we identified ER target 218 genes specific to the ILC cell lines (n=406), defined whether these genes were regulated by MDC1 and/or 219 FOXA1, and then examined regulatory site enrichments against the cisTarget database as above (Figure 4F, 220 Supplemental File 7). Paralleling our above analyses, MDC1 target genes were heavily enriched for nuclear 221 receptor motifs, including ESR1 (ER) and estrogen-related receptors (ERR); non-MDC1 target genes were instead bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. A RNAseq Schema B MM134 (ILC) MM330 (ILC) HCC1428 (IDC) siRNA: siRNA: siRNA: MM134, MM330 (ILC) HCC1428 (IDC) E2: – + + + + – + + + + – + + + +

Hormone-deprivation (CSS) 3d 1.5 siRNA transfection (siNT, siESR1, siFOXA1, siMDC1) 24hr E2 (or Veh) treatment 24hr

Harvest -1.5

MM134 C (n=2062) HCC MM330 1412 1428 ER:MDC1- (n=480) (n=1350) regulated 122 446 82 216 60 762

n=3599 n=2006 n=4206 D ER:MDC1-regulated (MDC1 only + FOXA1 + MDC1) E Transcriptional Regulator (cisTarget): MM134 MM330 HCC ER:MDC1-regulated MSigDB Hallmarks 1428 ILC-specific Shared all HCC1428-only Estrogen Response Early 4.7e-40 3.1e-32 4.2e-18 (n=122) (n=82) (n=762) Estrogen Response Late 3.7e-26 6.2e-25 8.5e-17 CEBPZ mTORC1 Signaling 9.4e-8 6.0e-3 1.3e-3 MEIS1 TWIST1PLAGL1 RFX5 FOS SPI1 FOXI1 SIN3A PBX3 E2F4 RELA KLF4 MECOM DNA Repair 0.29 0.84 5.8e-3 ESRRAESR1 SMAD3 SP1NFYC NFYB Reactome Pathways ZNF148RORC E2F2 HNF4A HNF4A TFAP2C RFX5SP2 E2F3E2F7 IRF3 DNA Double Strand Break Repair 0.20 0.89 4.2e-21 ESRRG FIGLA IKZF1GLI1 SMAD6 TFDP1 E2F6 ESRRB FOXG1 E2F8ZNF362 E2F5NFYA TFDP2 Homology Directed Repair 0.62 0.89 6.4e-20 HNF1AHDAC2 TFAP2BTFAP2AKLF5 DLX2 DNA Repair 0.11 0.90 6.4e-20 RORB RARA LEF1SMAD5 MYBL1 FOXM1 ELF1 E2F1 G2/M DNA Damage Checkpoint 0.70 0.87 3.1e-16 NR1I3 E2F4

F Transcriptional Regulator (cisTarget): ILC-Specific ER target genes (n=406) MDC1 v Non-MDC1 Targets FOXA1 v Non-FOXA1 Targets E2F ESR1 E2F 4 4 ERR Family ESR1 NR5A1/2 KLF Family 2 Enriched specifically 2 Enriched specifically in Non-MDC1 targets RAR/RXR in Non-FOXA1 targets RHOXF1 NR (other) SP Family 0 KLF Family 0 SOX Family Enriched specifically Enriched specifically in MDC1 targets DPRX in FOXA1 targets Other -2 FOXO1 -2 -2 0 2 4 -2 0 2 4 Other MDC1 NES FOXA1 NES bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Figure 4. MDC1 mediates ER control of target genes associated with hormone response elements in ILC cells. (A), Schema for RNA-sequencing experiment; samples were generated in biological triplicate. (B), ER target genes in each cell line were identified by E2 regulation (siNT vs siNT+E2; q<0.0001) and reversal by siESR1 (siNT+E2 vs siESR1+E2, q<0.0001). For MM330, a less stringent ligand reg. cutoff was used (q<0.01) due to ligand-independent activity of ER in these cells. MDC1 and FOXA1 targets defined by the E2 effect reversed by siRNA, q<0.0001. (C), Overlap of ER:MDC1 target genes across cell lines. (D), ER:MDC1 target genes from (C) were subject to over-representation analyses (ORA) against MSigDB genesets (H, C2/CP, and C6 at top; C2/Reactome at bottom). (E), Genes from (C) were applied to transcriptional regulator analyses (i.e. transcription factors motifs within 20kb of transcription start sites). Word clouds represent frequency of high confidence factors identified with NES 3. Single instances of motifs are omitted from the clouds but are listed in Supplemental File 6. (F), ILC-specific ER target genes were defined as MDC1- and/or FOXA1-targets as in (B) and analyzed as in (E). bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

222 enriched for E2F-family motifs. Conversely, FOXA1 targets were enriched for E2F-family targets. These 223 observations support that MDC1 plays a unique role in genes controlled by hormone-response-elements, and 224 suggests MDC1 plays a distinct role from FOXA1 in ER-mediated gene regulation in ILC cells. 225 226 MDC1 protein is differentially expressed in ER+ ILC tumors 227 228 Studies of MDC1 protein in human tumors suggest MDC1 is over-expressed in some tumor types to 229 suppress apoptosis, but is more often decreased or lost in tumors relative to normal tissues, likely promoting 230 genomic instability (recently reviewed [36]). In breast cancer, limited analyses to date have suggested MDC1 231 protein is decreased or lost in 30-70% of tumors, and that MDC1 loss is associated with advanced stage and poor 232 outcomes [37–39], but associations with ER status and histology are unknown. To examine this further, we first 233 assessed MDC1 mRNA levels in the Cancer Genome Atlas (TCGA) and METABRIC cohorts via cBioPortal [40]. 234 In both TCGA and METABRIC, MDC1 expression was highest in ER-/HER2- IDC tumors compared to other 235 IDC and to ER+/HER2- ILC (Figure 5A). Considering ER status only, MDC1 expression was higher in ER- IDC 236 vs either ER+ IDC or ER+ ILC in both datasets (FDR q<0.05); PR status was not associated with differences in 237 MDC1 expression in ER+ tumors (not shown). We did not identify significant associations between MDC1 238 mRNA levels and outcome in either cohort (not shown). We next assessed MDC1 protein levels by IHC staining 239 using commercial breast cancer tissue microarrays (TMAs). We investigated two antibodies for IHC staining, and 240 found that Abcam ab11171 (Abcam) showed specific nuclear staining in MM134 FFPE cell pellets and normal 241 breast tissue, and siMDC1 decreased staining intensity in MM134 cell pellets (Supplemental Figure 5A). In 242 breast tumor tissues, MDC1 IHC showed a broad range of expression levels across IDC and ILC tumors (Figure 243 5B; Supplemental File 8). ANOVA analyses did not detect statistically significant differences between ILC/IDC 244 based on ER status. However, we noted that low/negative MDC1 by IHC was rare in ER+ ILC tumors (chi-test p 245 = 0.027), which had MDC1 levels more consistent with normal and non-malignant breast tissues (Figure 5C, 246 Supplemental Figure 5B). The extent of MDC1 protein loss by IHC was not mirrored in mRNA data, suggesting 247 that MDC1 may be post-transcriptionally regulated in breast tumors cells (consistent with MDC1 protein 248 regulation in DDR [27, 28, 41]). While MDC1 protein loss or downregulation may be a mechanism by which 249 tumor cells facilitate increased genomic instability, ER+ ILC may uniquely maintain MDC1 protein based on its 250 critical role in ER function. 251 252 DISCUSSION 253 254 ILC are nearly all ER+ and have tumor biomarkers consistent with the Luminal A molecular subtype, but 255 these tumors have a unique relationship with estrogen and anti-estrogens relative to other breast cancers. For bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. A 8 TCGA B MDC1 ER (SP1) 100 300

4 ILC

95 171 -4 n 93 402 36 140 25 141 1 7 METABRIC ILC 4

42.5 300 0 ILC -4 n 92 1006 122 280 4 118 5 15 Histo D D D D L L L L ER + + – – + + – – HER2 + – + – + – + – FDR q<.05 294 240 TCGA+META C 300 IDC

200 200 300 IDC 100 MDC1 MDC1 IHC H-score

0 0 20%ile 0 ER+ IDC ER- IDC ER+ ILC ER- ILC Normal* n=167 n=91 n=23 n=10 n=27 IDC Chi-Test(Quintile; all): p=0.027 Chi-Test(Quintile; ER+, IDC v ILC): p=0.025 Chi-Test(Quintile, ER-, IDC v ILC): p=0.57 Chi-Test(Quintile, ER+ ILC v ER- ILC): p=0.038 200µm bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Figure 5. Loss of MDC1 protein is uncommon in ER+ ILC tumors. (A), MDC1 mRNA levels in breast tumors from TCGA (Firehose legacy dataset) and METABRIC cohorts. Red line = median expression. (B), Representative IHC images with H-scores from breast cancer TMAs. (C), MDC1 H-scores from full TMA cohort. Normal tissues include healthy/unaffected mammary glands, hyperplasia, and fibroadenoma samples (see Supplemental File 8). Dashed red line = median H-score. Pink dash line = lower quintile for full cohort. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

256 example, hormone replacement therapy using estrogen alone is sufficient to increase the risk of ILC, whereas IDC 257 risk is restricted to combined estrogen plus progestin therapy [1]. Despite being exquisitely estrogen-dependent, 258 ILC may be resistant to anti-estrogens, as suggested by limited response to tamoxifen (clinically [10, 11] and in 259 lab models [12, 13, 42, 43]) and by the poor long-term outcomes for patients with ILC [5–8]. Based on these data, 260 we hypothesized that ER function is unique in ILC cells and examined novel and/or ILC-specific ER co-regulator 261 proteins as a driver of ER functions in ILC cells. Using the co-IP/MS method RIME, coupled with an siRNA 262 screen against ER-driven proliferation, we identified the DNA damage response protein MDC1 as an ER- 263 associated protein in ILC cells. MDC1 is required for ER-driven proliferation in ILC cells, with MDC1 264 knockdown causing cell cycle arrest, whereas in the context of DDR function MDC1 knockdown or loss 265 abrogates cell cycle checkpoints. Similarly, RNAseq analyses showed MDC1 is required for a major subset of the 266 ER-regulated transcriptome in ILC cells, and is associated with DNA repair signatures only in IDC cells, 267 suggesting that MDC1 has ER co-regulator functions independent of its canonical role in DDR. Further, by IHC 268 we observed that loss of MDC1 protein is uncommon specifically in ER+ ILC, consistent with a critical role for 269 MDC1 in supporting ER function in ILC cells. 270 Beyond the canonical roles of MDC1 in DDR, reports in the literature implicate MDC1 as having co- 271 regulator activity. In GAL4 fusion assays, MDC1 (a.k.a. NFBD1 or KIAA0170) residues 508-995 enhanced 272 reporter activity in COS cells [44]. Other studies link MDC1 to epigenomic remodeling proteins, including the 273 SWI/SNF complex [45] and p300 histone acetyltransferase [46, 47]. Interaction with epigenomic enzymes may 274 suggest MDC1 acts to scaffold proteins on ER to mediate gene regulation (MDC1 has no known enzymatic 275 activity), similar to the NCOA family of co-regulators [48]. However, the canonical roles of MDC1 in DDR could 276 also impact ER-driven gene regulation, since ER may regulate genes by causing DNA damage to induce DDR- 277 driven recruitment of chromatin remodelers [49]. In this context, MDC1 has been previously reported to interact 278 with ER and AR (in MCF7 and CWR22Rv1 prostate cancer cells, respectively), but in these settings MDC1 acted 279 as a tumor suppressor [36, 39, 50]. In breast and prostate cancer lines, MDC1 shRNA knockdown enhanced 280 proliferation, migration, and invasion, consistent with abrogation of DDR cell cycle checkpoints. MDC1 is also a 281 tumor suppressor in tumorigenesis models, such as in Mdc1-knockout mice which show increased tumorigenesis 282 due to increased genomic instability [51–54]. MDC1 also functions as a tumor suppressor in DDR in ER-negative 283 breast cancer, where MDC1 links ID4 to the BRCA1 DDR network [55]. However, our data contrast the tumor 284 suppressor roles of MDC1 in DDR, and instead suggest an oncogenic role in mediating ER function and ER- 285 mediated proliferation. Similarly, we found MDC1 siRNA did not block AR-driven (ER-independent) growth in 286 MM134, supporting a specific role in ER function in ILC cells. Taken together, MDC1 can contribute to nuclear 287 receptor function via DDR and as a tumor suppressor in some settings, but in ILC, MDC1 has unique and 288 potentially oncogenic functions as an ER co-regulator. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

289 Understanding how MDC1 has ER co-regulator activity specifically in ILC cells is an important future 290 direction, and may be facilitated by differential post-transcriptional modification of MDC1 in the context of ILC. 291 MDC1 has extensive post-translational modification (PTM) including SUMOylation [56], methylation [57], 292 phosphorylation [31], and ubiquitination [27, 28], and MDC1 cleavage can generate MDC1 unable to engage in 293 DDR [41]. Future studies will examine differential MDC1 PTM in ILC versus IDC contexts. Differential MDC1 294 PTM as a mechanism to facilitate ER interaction may parallel our recent findings that ER protein is differentially 295 regulated in ILC cells, showing reduced ligand-driven ubiquitination and degradation versus ER in IDC cells [16]. 296 Defining how MDC1 and ER interact together on chromatin is also critical to understanding the ILC-specific co- 297 regulator functions of MDC1. However, MDC1 chromatin binding in DDR [44, 58] creates technical issues for 298 ChIP studies. We find different MDC1 antibodies have varying ability to co-IP ER versus known DDR partners 299 (not shown), and the latter may confound the interpretation of ChIP data of ER:MDC1. Future studies will better 300 define the ER:MDC1 interaction, to both understand the ILC-specificity of the interaction and facilitate genomic 301 studies of ER:MDC1 function. 302 The putative oncogenic functions of MDC1 as an ER co-regulator in ILC raises questions as to whether 303 MDC1 maintains its tumor suppressor functions in DDR in ILC cells. In our RNAseq, ER:MDC1 target genes in 304 ILC cells were not enriched for DDR-related signatures or E2F promoter motifs (unlike our data from IDC cells), 305 which may suggest a disconnect between MDC1 and DDR in ILC cells. Similarly, TCGA data suggest DDR may 306 be dysfunctional in some ILC tumors. TCGA identified a ‘Proliferative’ ILC subtype with the poorest disease-free 307 and overall survival (2-fold increased recurrence)[2]. Proliferative ILC has an elevated DDR signature (by reverse 308 phase protein array, RPPA) vs other ILC subtypes or vs Luminal A IDC, defined by high DDR protein levels 309 [59], but the functional implications of this elevated DDR signature has not been explored. Clinically, ILC have 310 the poorest response to chemotherapy among breast cancer subtypes, and patients with ILC receive little if any 311 survival benefit from chemotherapy [60–63]. Further mechanistic studies are needed to understand chemo- 312 response and -resistance, DDR function, and the potential crosstalk between ER, MDC1, and DDR in ILC cells. 313 Similarly, our data on the critical role of MDC1 in tamoxifen-mediated ER function, and identification of 314 MDC1 as a partner of mutant ER in anti-estrogen resistant/ER mutant 44PE cells, suggest that MDC1 plays a 315 central role in ER-dependent anti-estrogen resistance. Defining the role of ER:MDC1 interaction in clinical anti- 316 estrogen response and patient outcomes may require functional assessment of MDC1 in tumors tissues; our data 317 suggest MDC1 mRNA and MDC1 protein are not strongly correlated, and protein levels by IHC alone likely 318 cannot confirm ER:MDC1 interaction or MDC1 co-regulator activity. Additional data on estrogen-mediated gene 319 regulation in ILC tumors can facilitate identifying ER:MDC1-regulated genes in vivo, such as gene expression 320 data from an ongoing trial of neoadjuvant anti-estrogen therapy for patients with ILC [NCT02206984]. 321 Increasing evidence from clinical, epidemiological, and laboratory studies suggest that ILC is a 322 biologically distinct subset of breast cancer, and further that ILC represents a unique context for ER activity. Our bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

323 understanding of ER and anti-estrogens in breast cancer is almost exclusively based on IDC biology (e.g. data 324 from MCF-7), but work from our lab and others supports that ILC should be considered an independent tissue 325 type, not unlike study of ER in the endometrium, bone, CNS, or other tissues. As seen in other tissues, distinct co- 326 regulator cohorts may mediate tissue type-specific ER functions in ILC, and we identified MDC1 as a unique ER 327 co-regulator in ILC cells that is critical in estrogen response and anti-estrogen resistance phenotypes. Further 328 defining MDC1 functions will provide mechanistic basis for the unique ER activity in ILC, thus potentially 329 underlying the distinct biology of ILC. MDC1 may be a therapeutic target for a patient population in critical need 330 of precision treatments. 331 332 333 MATERIALS AND METHODS 334 335 Cell culture and reagents 336 MDA MB 134VI (MM134; ATCC, Manassas, VA, USA) and SUM44PE (Asterand/BioIVT, Westbury, 337 NY, USA) were maintained as described [12]. MDA MB 330 (MM330; ATCC) and HCC1428 (ATCC) were 338 maintained in DMEM/F12 (Corning #10092CV) + 10% fetal bovine serum (FBS; Nucleus Biologics #FBS1824). 339 MCF7 and CAMA-1 lines were generous gifts from the Rae Lab at the University of Michigan, and were 340 maintained in DMEM/F12 + 10% FBS. T47D were a generous gift from the Sartorius Lab at the University of 341 Colorado, and were maintained in MEM (Corning #10010) + 5% FBS + 1x Non-essential amino acids + 1nM 342 sodium pyruvate + 1nM insulin. BCK4 were a generous gift from the Jacobsen Lab at the University of Colorado 343 and were maintained as described [64]. Hormone-deprivation was performed as described [65] with phenol red- 344 free reagents in IMEM (ThermoFisher #A10488) supplemented with 10% charcoal-stripped fetal bovine serum

345 (CSS; prepared as described [65] with the same FBS as above). All lines were incubated at 37°C in 5% CO2. All 346 cell lines were regularly confirmed to be mycoplasma negative and were authenticated by STR profiling at the 347 University of Colorado Anschutz Tissue Culture Core. Estradiol (E2), 4-hydroxytamoxifen (4OHT), and 348 testosterone (TS) were obtained from Sigma; ICI 182780 (fulvestrant; fulv) and synthetic androgen Cl-4AS-1 349 were obtained from Tocris Biosciences. Small molecules were dissolved in ethanol, and vehicle treatments are 350 using 0.1% EtOH. 351 352 siRNA Knockdown Protocol 353 siRNA constructs were reverse transfected using RNAiMAX (ThermoFisher) according to manufacturer 354 instructions. Constructs are siGENOME SMARTpool siRNAs (GE Healthcare Dharmacon, Lafayette, CO, USA) 355 containing 4x siRNA targeting constructs, or individual siRNA constructs: Non-targeting pool #2 (D-001206-14- 356 05), Human ESR1 pool (M-003401-04-0010), Human MDC1 pool (M-003506-04-0005), Human FOXA1 pool bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

357 (M-010319-01-0005), and Human MDC1 individual constructs (D-003506-02-0002, D-003506-03-0002, D- 358 003506-05-0002, D-003506-06-0002). 359 360 Rapid immunoprecipitation mass spectrometry of endogenous proteins (RIME) 361 RIME was performed with Active Motif (Carlsbad, CA), and samples were prepared according to the 362 commercial protocol (Supplemental File 9). Briefly, MM134, 44PE, or BCK4 cells were plated in standard 363 conditions containing FBS (above) in three 15cm plates; 1 plate each was used for Vehicle treatment (ER IP), 364 4OHT treatment (ER IP), or Vehicle treatment for IgG IP control. Cells were treated with Vehicle (0.1% EtOH) 365 or 4OHT (1μM) for 24hr prior to harvest. At the time of harvest, cells (MM134: ~9x107/plate; 44PE: 366 ~3x107/plate; BCK4: ~2.5x107/plate) were fixed in 11% formaldehyde solution for 8min at room temperature 367 with gentle rocking. Fixation was quenched with 1/20 volume of 2.5M glycine, and cells were collected by 368 scraping. After centrifugation, pellets were washed twice in 0.5% Igepal CA-630 + 1mM PMSF in PBS, then 369 pelleted and snap frozen. Nuclear isolation, immunoprecipitation, and mass spectrometry (in technical duplicates) 370 were performed by Active Motif. ER IP used antibody sc-543 (Santa Cruz Biotechnology; Santa Cruz, CA; 371 antibody is discontinued) and rabbit IgG. MS was performed in technical duplicate for each sample (single 372 biological replicate per condition). Quality control reports from the mass spectrometry analyses are provided in 373 Supplemental File 10. 374 Identified peptides were filtered based on having <20% of peptides for a given protein in IgG samples 375 relative to all samples, and the identified protein being present in <40% of studies in the CRAPome database [66]. 376 Common tubulin and ribosomal protein contaminants were also excluded. ER RIME data from IDC cells in 377 Mohammed et al [26] used the union of peptides identified across biological replicates. 378 379 siRNA screen 380 siRNA SMARTpools containing 4 siRNA constructs per pool were ordered as a pre-plated custom 381 libraries in 96-well format (Dharmacon / Horizon Discovery; Layfayette, CO; sequences listed in Supplemental 382 File 3). MM134 cells were hormone-deprived as described above prior to reverse transfection with 10nM siRNA 383 (as above). 24hr post-transfection, cells were treated with Vehicle (0.01% EtOH), 100pM E2, 100nM 4OHT, or 384 10nM Cl-4AS-1 (all in biological triplicate) and allowed to grow for 6 days prior to assessing proliferation by 385 dsDNA quantification (see below). Raw data from dsDNA quantification and associated statistical analyses and 386 target filtering are provided in Supplemental File 3. Data analyses were performed in Graphpad Prism v7.0. 387 388 Cell proliferation 389 Total double-stranded DNA was measured as a surrogate for total cell number. dsDNA was quantified by

390 hypotonic lysis of cells in ultra-pure H2O, followed by addition of Hoechst 33258 (ThermoFisher Scientific, bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

391 #62249) at 1μg/mL in Tris-NaCl buffer (10mM Tris, 2M NaCl; pH 7.4) at equivalent volume to lysate. 392 Fluorescence (360nm ex / 460nm em) was measured on a Bio-Tek Synergy 2 microplate reader. 393 394 Immunoblotting 395 Cells were seeded in 12- or 24-well plates for ~80% confluence according to cell size (MM134 and 396 SUM44PE: 800k/well or 400k/well; MM330: 640k/well or 320k/well; CAMA-1: 400k/well or 200k/well; MCF7 397 and T47D: 320k/well or 160k/well; HCC1428: 240k/well or 120k/well) and treated with 10nM siRNA, 100pM 398 E2, and other treatments as indicated. Cell lysates were harvested after treatments in RPPA buffer (50mM

399 HEOES pH 7.4, 150mM NaCl, 1.5mM MgCl2, 1mM EGTA, 10% Glycerol. 1% Triton X-100, dH2O) with 400 phosphatase inhibitors (ThermoFisher #78420). BioRad Mini-PROTEAN TGX precast gels were used for 401 electrophoresis and transferred to PVDF membranes. Membranes were blocked in either 5% milk or 5% BSA in 402 Tris-buffered saline with 0.5% Tween 20, depending on primary antibody used. Primary antibody probing was 403 performed according to manufacturer recommended concentrations, and species-matched secondary antibodies 404 were diluted in TBS + 0.05% Tween-20. Membranes were imaged on LiCor C-DiGit blot scanner. Primary 405 antibodies for immunoblots were: ER, Leica 6F11 (Leica Biosystems #PA009); MDC1, Sigma M2444. 406 407 408 Co-immunoprecipitation (Co-IP) 409 Cells were seeded in 10cm plates for ~80% confluency as described above. All centrifugation steps 410 below were at 4⁰C. Cultures were rinsed and then harvested by scraping in HBSS+1mM EDTA, then centrifuged 411 for 5’ at 1000xg. Pellets were rinsed in 1mL of PBS and centrifuged for 3’ at 1000xg. The cell pellet was re-

412 suspended in 3 packed cell volumes of Hypotonic Buffer A (10mM HEPES-KOH pH 7.6; 1.5mM MgCl2, 10mM 413 KCl, 1x protease inhibitors, and 1mM DTT). Cells were incubated on ice for 3’ prior to Dounce homogenization; 414 nuclei were then centrifuged for 15’ at 18000xg. The supernatant was reserved as the ‘cytoplasmic fraction’, and 415 nuclei were re-suspended in two packed nuclear volumes (PNV) of Hypertonic Buffer B (20mM HEPES-KOH

416 pH 7.6, 25% glycerol, 1.5mM MgCl2, 0.6M KCl, 0.2mM EDTA, 1x protease inhibitors, and 1mM DTT), 417 homogenized by pipetting, and incubated at 4⁰C for 45’ with rotation. Resulting lysate was centrifuged for 10’ at 418 18000xg to collect the supernatant. Supernatant was diluted with 3 PNVs of Hypertonic Diluent Buffer C (20mM

419 HEPES-KOH pH7.6, 1.5mM MgCl2, 0.2mM EDTA, 0.67% NP-40 (IGEPAL), 1x protease inhibitors, and 1mM 420 DTT), then insoluble proteins were removed by centrifuging for 5’ at 18000xg. The resulting supernatant 421 (nuclear extract, NE) was utilized for immunoprecipitation. 422 NE was combined with 10ug of antibody for immunoprecipitation. Jackson ImmunoResearch 423 Chromapure Rabbit or Mouse served as IgG controls. α-MDC1 (Sigma, M2444) or α-ER (Cell Signaling, clone 424 D8H8, Cat # 8644) were used for reciprocal co-IP. NE was incubated with antibody overnight at 4⁰C with bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

425 rotation. Protein A/G magnetic beads (Thermo Scientific / Pierce, Cat # 88803; 25ul/10ug antibody) were

426 prepared by washing in Buffer D (20mM HEPES-KOH, pH7.6, 1.5mM MgCL2, 150mM KCl, 0.2mM EDTA, and 427 0.67% NP-40 (IGEPAL)) and separation by magnetic stand. Beads were added to IP reactions and incubated for 428 4 hours at 4⁰C with rotation. Beads were washed 5 times with 1mL of Buffer D. Protein complexes were eluted 429 by re-suspending beads in 100ul of Buffer D supplemented with 6x Laemmli buffer and allowed to incubate for 430 10’ at room temperature. Beads were then removed via magnetic stand, and cleared lysates were denatured by 431 heating at 95⁰C for 10’, then assessed by immunoblot as above. 432 For benzonase and ethidium bromide (EtBr) co-IP experiments, Buffer B was supplemented with 3uL of 433 benzonase (Millipore Sigma; ≥250units/uL, Cat #E1014) or 100ug/mL of Ethidium bromide (Bio Rad, Cat 434 #1610433). 435 436 Proximity Ligation Assay (PLA) 437 Cells were seeded for optimum density according to cell size (MM134 and SUM44PE at 40k/well, 438 MM330 32k/well, CAMA-1 at 20k/well, MCF7 and T47D at 16k/well, HCC1428 at 24k/well) in 10-well 439 chamber coverslides (Greiner Bio-One #543079) and incubated for 48 hours with indicated drug or siRNA at 37C

440 at 5% CO2. Cells were washed 2x with room temperature 1x PBS and fixed in 4% paraformaldehyde (Electron 441 Microscopy Sciences #15710) for 15min with shaking at room temperature. Cells were washed 2x with room 442 temperature 1x PBS. Cells were permeabilized with 0.1% Triton X-100 (ThermoFisher #BP151-100) in 1x PBS 443 for 15min at room temperature with shaking and rinsed in 1x PBS. PLA was then performed according to Sigma 444 Aldrich Duolink PLA Fluorescence Protocol (DUO92008, DUO92002, DUO92004). Primary antibodies for 445 proteins of interest were diluted to 1:200 (ER 6F11) or 1:2500 (Bethyl MDC1 A300-051A). DNA was stained for 446 imaging using Duolink mounting medium with DAPI (Sigma #DUO82040). PLA foci were quantified using 447 JQuantPlus software [67]. 448 449 Cell cycle analyses 450 Cells were plated in 6-well plates and transfected with siRNA as above. 72 hours post-siRNA, cells were 451 harvested by trypsinization, then fixed in 500uL of ice cold 70% ethanol at 4⁰C for 30’. Cells were centrifuged at 452 for 3’ at 18000xg and washed twice in 1x PBS, then stained in 500uL of FACS buffer (1x PBS, Ca2+/Mg2+ free, 453 1mM EDTA, 25mM HEPES pH 7.0 and 1% BSA) supplemented with 10μg of RNase A (ThermoFisher) and 454 10μg of Propidium Iodide solution. Cells were incubated overnight at 4⁰C prior to analysis on a Gallios cytometer 455 (Beckman Coulter Life Sciences) using Kaluza 2.1 analysis software (Beckman Coulter). 456 Quantitative PCR 457 RNA extractions were performed using the RNeasy Mini kit (Qiagen). RNA was converted to cDNA

458 using Promega reagents: 1:1 Oligo (dT)15 primer (cat# C110A) + Random hexamers (cat# C118A); GoScript 5x bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

459 Reaction Buffer (cat# A500D); MgCl2 (cat# A351H), dNTP (cat# U1511); RNasin Plus (cat# N261B); GoScript 460 Reverse Transcriptase (cat# A501D). qPCR reactions were performed with PowerUp SYBR Green Master Mix 461 (Life Technologies, cat #100029284) on a QuantStudio 6 Flex Real-Time PCR system. Expression data were 462 normalized by ΔCt to RPLP0. Primers used are listed in Supplemental File 11. 463

464 RNA sequencing and analysis 465 MM134, MM330, and HCC1428 cells were hormone deprived according to protocol (see above), plated 466 for optimal confluency in 48-well plates, and transfected with 10nM siNT, siMDC1, siER, and siFOXA1 467 according to the method described above. 24hours after siRNA transfections, cells were treated with 100pM E2. 468 Cells were harvested 24 hours after addition of E2, washed 3X with cold PBS, and frozen at -80C. RNA was 469 extracted as above. Knockdown validation via qPCR was performed before sample submission. 470 Library preparation and sequencing was performed at the University of Colorado Comprehensive Cancer 471 Center Microarray and Genomics Core Facility. Libraries were generated with Illumina Stranded mRNA Prep, 472 and were sequenced on a NovaSEQ6000 with 2x150 paired-end reads, targeting 40x106 clusters / 80x106 reads 473 per sample (final mean = 39,019,637 clusters/sample). Sequencing data were analyzed with the University of 474 Colorado Comprehensive Cancer Biostatistics and Bioinformatics Shared Resource. Illumina adapters and the 475 first 12 base pairs of each read were trimmed using BBDuk [68] and reads <50bp post trimming were discarded. 476 Reads were aligned and quantified using STAR (2.6.0a) [69] against the Ensembl human transcriptome (hg38.p12 477 genome (release 96)). Reads were normalized to counts per million (CPM) using the edgeR R package [70]. 478 Differential expression was calculated using the limma R package and the voom() function [71]. Over- 479 representation analysis was performed with the clusterProfiler R package [72] and gene sets from the Molecular 480 Signatures Database [33]. Transcriptional regulators were inferred using the RcisTarget R package [73] and the 481 cisTarget database [35]. A normalized enrichment score (NES) of 3 was used as a cutoff. Heatmaps were 482 generated with MeV v4.9.0 [74]. Raw and processed data will be deposited in GEO upon manuscript submission. 483 484 Immunohistochemistry 485 Tissue microarrays were acquired from Pantomics (Fairfield, CA): BRC1021, BRC1507, BRC15010, 486 BRM961, BRM962. IHC was performed by the CU Anschutz Research Histology Shared Resource. Antigen 487 retrieval used citrate buffer pH9.0 with 30’ incubation, followed by staining for ER (SP1, 1:100) or MDC1 488 (Abcam ab11171, 1:500; Bethyl A300-051, 1:1000). Staining was assessed by a board-certified pathologist (SM) 489 and converted to an H-score. For a subset of tumors with duplicate cores, H-scores were averaged across the 490 duplicates. Detailed information and scoring is provided in Supplemental File 8. 491 492 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

493 SUPPLEMENTAL MATERIALS: 494 495 The following supplemental materials are available for download: 496 - Supplemental Figures 1-5 497 - Supplemental File 1 (xlsx): MS spectrum counts related to Figure 1A-B 498 - Supplemental File 2 (xlsx): siRNA panel selections 499 - Supplemental File 3 (zip): siRNA screening raw data and analyses 500 - Supplemental File 4 (xlsx): ER target gene lists and regulation designation related to Figure 4B 501 - Supplemental File 5 (xlsx): Pathway analyses of ER:MDC1 target genes related to Figure 4D 502 - Supplemental File 6 (xlsx): Transcriptional reg analyses of MDC1 targets related to Figure 4E 503 - Supplemental File 7 (xlsx): Transcriptional reg analyses of MDC1vFOXA1 targets related to Figure 4F 504 - Supplemental File 8 (xlsx): TMA scoring and information 505 - Supplemental File 9 (pdf): Active Motif RIME protocol 506 - Supplemental File 10 (pdf): Active Motif quality control reports for ER RIME 507 - Supplemental File 11 (xlsx): qPCR primers used in Supplemental Figure 4 508 509 510 ACKNOWLEDGEMENTS 511 512 The authors thank Dr. Mary Reyland and Angela Ohm for technical assistance in utilizing the JQuantPro 513 software. 514 515 516 COMPETING INTERESTS 517 518 The authors have nothing to disclose. 519 520 FUNDING 521 522 This work was supported by R00 CA193734 (MJS) and T32 GM007635 (EKB) from the National Institutes of 523 Health, by a grant from the Cancer League of Colorado, Inc (MJS), and by grants from the American Cancer 524 Society (Institutional Research Grant #16-184-56 to U. Colorado Comprehensive Cancer Center – pilot funding to 525 MJS; Research Scholar Grant RSG-20-042-01-DMC to MJS). This work utilized the U. Colorado Cancer Center 526 Genomics Shared Resource and Biostatistics and Bioinformatics Shared Resource supported by P30 CA046934. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

527 The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the 528 official views of the National Institutes of Health. 529 530 DATA AVAILABILITY 531 532 RIME data (including QC data and Scaffold files provided by Active Motif) and RNA sequencing data are 533 available upon request and will be deposited to public repositories on publication. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

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50 6 S100A9* S100A8 S100A7 JUP 4 25 TLE3 2

GREB1 P300 NRIP1 GREB1 0 0 0 25 50 75 0 2 4 6 8 10 Mean Spectral Counts, Veh Mean Spectral Counts, Veh B 44PE 44PE (zoom) 10 100 TLE3 (H0YKT5, F5H7D6) 8

50 4 ESR1

2 P300, GREB1

0 0 0 50 100 0 2 4 6 8 10 Mean Spectral Counts, Veh Mean Spectral Counts, Veh C BCK4 BCK4 (zoom) 80 10

8 60

6 TLE3 40

ESR1 4

20 P300, 2 GREB1

Mean Spectral Counts, 4OHT NRIP1

0 0 0 20 40 60 80 0 2 4 6 8 10 Mean Spectral Counts, Veh Mean Spectral Counts, Veh Supplemental Figure 1. Tamoxifen treatment does not substantially alter the cohort of protein associated with ER. Points represent mean of technical replicates for proteins identified in Vehicle- vs 4OHT-treated cells for (A) MM134, (B) 44PE, or (C) BCK4. Lines represent linear regression and 95% prediction bands. ER and known ER co-regulators are labeled. *, proteins were identified in a single technical replicate. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. A MCF-7 (IDC) MM134 (ILC) * 5 105 8 105 *

4 105 * 5 * 6 10 * * 3 105 * * 4 105 * 2 105

2 105 1 105

0 0 Ctrl E2 TS Cl Ctrl E2 TS Cl Control +Letrozole +Fulvestrant B MM134 Proliferation Veh E2 4OHT Cl-4AS-1 4 Known ER co-regs ESR1 local STRING cluster, ILC-specific * 2 ns * * ns * * * * * * * * * 1 * * * ns * * * * * * * * * * * * * * * * 0.5 * * * * * * * * * * * * * * 0.25 Mock ESR1 FOXA1 GREB1 GATA3 EP300 NRIP1 NCOA3 KMT2DBRD4 DNMT1 SAFBSMARCA2 siRNA Target Estrogen- LATS2 C 80 OCIAD1 selective 20 CPSF1 CDK13 TCEAL3 GATAD2A SLTM 60 AHR NFYC RELB CDCA5 DNTTIP1 CDKN1C 10 S100A9 40 NCOA1 NFIC CAV1 NCOA5 ZEB1 HOXA5 PSMD10 BANF1 20 PRKACA MDC1 FOXA1

FXR2 4OHT- 1 ESR1 SNW1 selective RECQL 1 10 20 1 E2 Rank 1 20 40 60 80 E2 Rank Supplemental Figure 2. Selectivity for ER-associated proteins per ER ligand and effects on proliferation. (A), Cells were hormone-deprived prior to treatment with 100pM E2, 100nM testosterone (TS) or Cl-4AS-1 (Cl; non-aromatizable synthetic androgen), +/- 1µM fulvestrant or letrozole (aromatase inhibitor). Bars = mean of 5 biological replicates +/-SD. *, p<0.05 vs Control (far left), ANOVA + Dunnett’s correction. (B), Examples of known co-regulators that were filtered out by suppression of Veh/-E2 growth and AR-driven growth. Bars = mean of biological triplicate +/-SD. *, p<0.05 vs matched Mock siRNA condition, ANOVA + Dunnett’s correction. ns, not significant. ESR1 and FOXA1 shown at left as key examples passing filter criteria. (C), siRNA targets that passed stringency filters (n=82, including ESR1; see Figure 2A) were ranked by their suppression of E2- versus 4OHT-induced growth. Dotted lines indicate 90% prediction bands based on linear regression (regression forced through 0,0). Dashed red box is shown as zoomed inset at right. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. A MM134 - ER:MDC1 MM134 - ER:FOXA1 40 Ctrl: 6.1±4.6 40 Ctrl: 13.6±8.1 Fulv: 3.4±2.6 * Fulv: 3.8±3.6 * 30 30

20 20

10 10

0 0 Ctrl Fulv Ctrl Fulv

MM134 siNT: 10.9±11.4 44PE siNT: 12.5±9.2 B siESR1: 4.8±4.0 * siESR1: 6.4±6.2 * 60 siMDC1: 5.8±5.4 * 60 siMDC1: 3.6±5.1 *

40 40

20 20

0 0 siNT siESR1 siMDC1 siNT siESR1 siMDC1 ILC CAMA1 siNT: 22.2±9.4 MM330 siNT: 20.4±12.6 siESR1: 14.6±12.7 * siESR1: 5.4±4.6 * 60 siMDC1: 12.5±6.0 * 60 siMDC1: 11.1±8.3 *

40 40

20 20

0 0 siNT siESR1 siMDC1 siNT siESR1 siMDC1

HCC1428 siNT: 3.9±5.8 MCF7 siNT: 2.9±3.6 * * 60 siESR1: 6.0±6.5 60 siESR1: 6.4±6.2 siMDC1: 8.1±8.0 * siMDC1: 3.4±4.3 ns

40 40

20 20

0 0 siNT siESR1 siMDC1 siNT siESR1 siMDC1 IDC siNT: 4.2±3.6 T47D ns 60 siESR1: 3.2±3.6 siMDC1: 3.3±3.3 ns Median ± I.Q. Range

40 Condition: Mean ± Std. Dev.

0 siNT siESR1 siMDC1 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Supplemental Figure 3. ER:MDC1 PLA foci counts are suppressed by ER or MDC1 knockdown in ILC cells. Foci were quantified using JQuantPro software, using DAPI signal as a mask for nuclei (only nuclear PLA signal was quantified). Foci parameters (e.g. signal intensity and size cutoffs) were developed using the samples in (A), then applied to samples in (B) with minor modifications per cell line. (A-B), MM134 were treated with 100nM fulvestrant or siRNA as indicated prior for 48h to PLA. Points represent foci count per individual nucleus. Red lines show median foci/nucleus +/- interquartile range. P-values represent siRNA vs siNT, non-parametric ANOVA with Dunn’s multiple testing correction. (A), Fulvestrant leads to ER protein degradation, acting as a control for PLA signal specificity. (B), ER:MDC1 PLA quantification as in (B). Blue values note a non-significant change or a statistically significant increase in PLA foci after siRNA, inconsistent with specific ER:MDC1 PLA signal. bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license.

MM134 (ILC) q, siNT vs HCC1428 (IDC) q, siNT vs A siMDC1 siMDC1 4 ESR1 0.006 0.90 MDC1 0.006 0.04 3 WNT4 0.03 0.54 IGFBP4 0.006 0.82 PDZK1 0.03 0.29 2 TFF1 0.26 0.97 PDE4B 0.005 0.75 1 TFCP2L1 0.002 0.54 0.25 E2: – + + + – + + + siRNA: mock mock siNT siMDC1 mock mock siNT siMDC1

B ER:MDC1-regulated MM134 (ILC) MM330 (ILC) HCC1428 (IDC)

ZNF135 ZNF766 CTCF ZNF160 SP8 ZBTB33 ZNF641 NKX11 ZNF48 SOX3 TFAP2C SOX2 ZNF8 MAZ CEBPD THAP1 FOS E2F8 RB1 ZNF229 ZNF559 GPD1 ZNF135 SOX4 HNF4G ZNF131 FOXO3 E2F5 ESRRA JUN E2F5 ZNF513 ZCCHC14 KLF15 SUPT20H BARHL2 NFYB PBX4 ZNF362 AFF4 ZNF836 RXRG ZNF595 SOX1 CEBPB ZDHHC5 TFDP2 GRHL1 ZBTB16 KLF4RELA FOXA3 PGAM2 NFAT5 RXRA FOXI1 E2F2 FOXO4 FOXJ1 ESRRA CBFB LEF1 SRY FOXF1 ESR1FOXA2 PAX7 FOXF2 ZNF324 ZNF562 ZNF2 EGR1 SP5 IRX4 SP2 ASCL1 NFIC ZNF124 REL ETS1 HIC1 E2F4 HNF4G KLF6 SREBF1 TCF7L2 KLF4 NMRAL1 PEG3 ETV7 SP9 ZNF773 FOXN2 FOXL1 SOX9 XRCC4 ZNF513FOXA1 FOXC1 E2F4PDX1 RFX5 FOXA2 ZIC1 TFDP1 HNF4ACEBPZ ZNF417 INSM1 RB1 SRF ZNF561 SP7 E2F1TCF7L2 ZKSCAN7 MYC CEBPZ FOXG1 FOXD1 HOXA7 NHLH1 E2F3ESRRB ZNF555NKX31 NFYA NR5A2 CEBPD PURA RELA MAX NR2F1 ZNF841 NR1H3 PBX3 FEZF2 AGGF1HNF4AAKR1A1 ZBTB7B TOB2 TFAP2A KLF12 TCF12 ZIC1 CEBPG SRF SETDB1 PLAGL1 GRHPR SMAD1 EOMES CHURC1 SP1 RREB1 KLF5 ZNF880 KLF1 BCL11A KLF15 E2F7 ABL1 E2F6 ZNF8 ZNF711 AGGF1 NFKB1 AR E2F6 EBF1 TFDP1 CHD2 ZNF117 NFE2 FOXP1SKOR2 ELK1 SREBF1 POLR2A ZNF180 ZNF184 ZNF184 SOX10 E2F3 E2F1 ZNF689 PBX1 ZNF879 TCEAL6 BARHL1 SMAD3 WRNIP1 SMAD6 HNF4A KLF10 ZNF296 KLF11 ZNF607 ZNF121 NFYC ZNF233 EGR3 TFAP4RARG NHLH1 MAZ ZNF595 ARNT2 FOXP2 TCEAL6 RBPJ TOPORS YBX1 TP53 FOXJ3 ZNF70 KLF11 IRF3 RXRA ZBTB41 FOXO1 TCF12 HSF5 ZNF74 SIN3A FOXJ2 SREBF1 NR3C1 ZNF17 ETS2 SP110 MECOM THAP1 ZNF324B ELK1 SALL4 FOXK1 MAXZNF3 ZNF773

C MM134 (ILC) MM330 (ILC) HCC1428 (IDC) D siRNA: siRNA: siRNA: HCC1428 E2: – + + + + – + + + + – + + + + (n=2776) 1273687 1445

380 436 406 MM134 1.5 (n=2918) 1160 MM330 (n=2382)

n = 406 -1.5 ILC-specific ER target genes

n = 193: MDC1-regulated n = 250: FOXA1-regulated (n = 136, inclusive: MDC1+FOXA1 reg.) n=2918 n=2382 n=2776 bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Supplemental Figure 4. MDC1 mediates ER control of target genes associated with hormone response elements in ILC cells. (A), Cells were hormone-deprived prior to siRNA transfection; 24hrs later cells were treated +/- 100pM E2 for an additional 24hrs. Samples were generated in biological triplicate, mean shown in heatmap. q-value represents ANOVA with Dunnett’s multiple testing correction. (B), Word clouds representing frequency of high confidence factors identified with NES 2.5 in all ER:MDC1 targets from the indicated cell line. (C), ER targets were defined by siRNA fully suppressing E2-induced expression (i.e. siRNA+E2 vs siNT, q>0.05; equivalent to -E2). (D), Overlapping ER target genes from (C) identifies high-confidence ILC-specific ER target genes. MDC1 and FOXA1 targets were defined by siRNA fully suppressing E2-induced expression as in (C). bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. A Abcam ab11171 Bethyl A300-051 siNT siMDC1 siNT siMDC1 MM134 Normalbreast Normalbreast

B Frequency distribution 30 ER- IDC ER+ IDC ER- ILC ER+ ILC 20 Normal/Non-malignant

0 0 50 100 150 200 250 300 MDC1 H-score

Supplemental Figure 5. MDC1 IHC analyses in control samples and breast tumors. (A), Antibodies validated by immunoblot with indications for use in IHC were tested using FFPE cell pellets from MM134 48hrs post-siRNA transfection, and using sections from normal breast tissues. Abcam 11171 was selected due to greater specificity and reduced stromal staining in tissue sections. (B), Histogram of MDC1 H-scores. Dashed lines are LOWESS spline fits, and support that MDC1 H-score distribution in ER+ ILC mirrors normal tissue samples, but not other breast tumors.