Supplementary Table 1. Primers used for qPCR and ChIP assays.

Gene Accession Forward Reverse Number ESRRG NM_001438 CGATGCCCAAGAGACTGTGTT AGACGCACCCCTTCTTTCAG

ESRRA NM_004451 GGCTGGAGCGAGAGGAGTATG GGAGGAGCGGTAGCGTGAG

PPARGC1A NM_013261 GCACCGAAATTCTCCCTTGTA TTTGCTTGGCCCTCTCAGAC

IDH3A NM_005530 ATTGATCGGAGGTCTCGGTGT CAGGAGGGCTGTGGGATT C

MAOB NM_000898 GGAGCCAGTGCATTATGAAGA GCCTGCAAAGTAAATCCTGTC

TFF1 NM_003225 GTCCCCTGGTGCTTCTATCCT AGCCGAGCTCTGGGACTAATC

CDH1 NM_004360 AAGAAGGAGGCGGAGAAGAG GGCTGTGGGGTCAGTATCAG (E-cadherin) qPCR EPCAM/TACSTD1 NM_002354 GCAGGGTCTAAAAGCTGGTG CCCTATGCATCTCACCCATC

SCEL NM_003843 CCCAAGGATGGATATCAGGA TCTACACCCAAGGGTTTTCG

EPPK1 NM_031308 TTCAGAGGCCAGAAACCAAC GGTTTCCTGCTTCTCGATCA

OCLN NM_002538 TCCAATGGCAAAGTGAATGA GCAGGTGCTCTTTTTGAAGG

MUC1 NM_001044392 TACCGATCGTAGCCCCTATG ACCTGAGTGGAGTGGAATGG

CRB3 NM_139161 AACCTGAGCTAGGTCAAAGACG GAGGGAGAAGACCACGATGA

CDH2 NM_001792 ATCCGACGAATGGATGAAAG CATAGTCCTGCTCACCACCA (N-cadherin)

VIM NM_003380 GAGAACTTTGCCGTTGAAGC CCAGAGGGAGTGAATCCAGA

KRT8 NM_002273 TCTGGGATGCAGAACATGAG CTCCTGTTCCCAGTGCTACC TFF1 ATGGGAGTCTCCTCCAACC CGGCCATCTCTCACTATGAA -5.5kb E-cadherin TGCCTGCCTTCTCAGCTACT TGGAGTACAGTGGCCCAATC ChIP ERRE1 E-cadherin TGACCTTGGGCAAGTTACTC CAAATGAGAAAACTGAGGCAT ATGAG

ERRE2 E-cadherin CTTTGGTGCTGGCTGGTT CAACTGAGGCGAAAGGCTTA

Supplementary Table 2. Summary of ERRγ mRNA level changes in breast carcinomas, classified by tumor grade or clinical outcome. The referred Oncomine datasets are ones where ERRγ levels were significantly different in one of the described classes. The numbers under classes refer to number of samples.

Class Dataset Tumor Grade ERRγ Levels in Class 3 p value Ref. 1 2 3 Bittner et al. Histological grade 18 74 126 Decreased 0.000769 Not Published Ivshina et al. Elston grade 68 166 55 Decreased 0.003 (1) Desmedt et al. Histological grade 7 3 Decreased 0.007 (2) Loi et al. Elston grade 14 20 24 Decreased 0.01 (3)

Dataset Outcome Class 1 Class 2 ERRγ Levels in Class 2 Fold change p value Ref. Metastatic event - 5 No Metastasis Metastasis Decreased -2.41 0.002 years 68 14 Loi et al. (4) No recurrence Recurrence Recurrence - 5 years Decreased -2.41 0.002 68 14 Alive Dead Dead - 5 years Decreased -1.06 0.009 232 48 Metastatic event - 3 No Metastasis Metastasis Decreased -1.06 0.008 Vandevijver et years 239 52 (5) al. Metastatic event - 5 No Metastasis Metastasis Decreased -1.06 0.015 years 207 78 Alive Dead Dead - 3 years Decreased -1.06 0.05 260 29 No recurrence Recurrence Recurrence - 3 years Decreased -1.30 0.011 217 68 Wang et al. (6) No recurrence Recurrence Recurrence - 1 year Decreased -1.56 0.028 269 16 Boersma Alive Dead Dead - 1 year Decreased -1.67 0.019 (7) et al. 36 5 Desmedt Alive Dead Dead - 5 years Decreased -5.10 0.028 (2) et al. 131 5 Pawitan Alive Dead Dead - 5 years Decreased -1.35 0.042 et al. 121 38 (8) No recurrence Recurrence Hess et al. Recurrence - 1 year Increased 1.22 0.018 (9) 85 5

1. Ivshina AV, George J, Senko O, et al. Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. Cancer Res 2006;66:10292-10301. 2. Desmedt C, Piette F, Loi S, et al. Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series. Clin Cancer Res 2007;13:3207-3214. 3. Loi S, Haibe-Kains B, Desmedt C, et al. Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen. BMC Genomics 2008;9:239. 4. Loi S, Haibe-Kains B, Desmedt C, et al. Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade. J Clin Oncol 2007;25:1239-1246. 5. van de Vijver MJ, He YD, van't Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002;347:1999-2009. 6. Wang Y, Klijn JG, Zhang Y, et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 2005;365:671-679. 7. Boersma BJ, Reimers M, Yi M, et al. A stromal gene signature associated with inflammatory breast cancer. Int J Cancer 2008;122:1324-1332. 8. Pawitan Y, Bjohle J, Amler L, et al. Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts. Breast Cancer Res 2005;7:R953-964. 9. Hess KR, Anderson K, Symmans WF, et al. Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer. J Clin Oncol 2006;24:4236-4244.

Supplementary Table 3. Relative mRNA expression levels of the transcription factors SNAI1, SNAI2, ZEB1, ZEB2 and TWIST1 in MDA-MB-231 cells expressing stably (via retroviral transduction and selection) or transiently (24 hours after infection with adenoviral vectors) PGC-1α or ERRγ. ND, not detectable.

MDA-MB-231 stable lines

MDA-control MDA-PGC-1α MDA-ERRγ

SNAI1 1.00 ± 0.07 1.58 ± 0.35 0.93 ± 0.17

SNAI2 1.00 ± 0.04 0.87 ± 0.06 1.00 ± 0.12

ZEB1 1.00 ± 0.08 0.95 ± 0.11 0.83 ± 0.12

ZEB2 1.00 ± 0.15 0.63 ± 0.11 0.62 ± 0.18

TWIST1 ND ND ND

MDA-MB-231 ± adeno-x

GFP PGC-1α ERRγ

SNAI1 1.00 ± 0.02 1.25 ± 0.10 0.58 ± 0.06

SNAI2 1.00 ± 0.06 1.17 ± 0.04 1.54 ± 0.14

ZEB1 1.00 ± 0.01 0.76 ± 0.05 0.81 ± 0.04

ZEB2 1.00 ± 0.09 0.73 ± 0.12 1.09 ± 0.17