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Molecular mechanisms linking high body mass index to breast cancer etiology in post-menopausal breast tumor and tumor-adjacent tissues

  • Epidemiology
  • Published:
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Abstract

Purpose

In post-menopausal women, high body mass index (BMI) is an established breast cancer risk factor and is associated with worse breast cancer prognosis. We assessed the associations between BMI and gene expression of both breast tumor and adjacent tissue in estrogen receptor-positive (ER+) and estrogen receptor-negative (ER−) diseases to help elucidate the mechanisms linking obesity with breast cancer biology in 519 post-menopausal women from the Nurses’ Health Study (NHS) and NHSII.

Methods

Differential gene expression was analyzed separately in ER+ and ER− disease both comparing overweight (BMI ≥ 25 to < 30) or obese (BMI ≥ 30) women to women with normal BMI (BMI < 25), and per 5 kg/m2 increase in BMI. Analyses controlled for age and year of diagnosis, physical activity, alcohol consumption, and hormone therapy use. Gene set enrichment analyses were performed and validated among a subset of post-menopausal cases in The Cancer Genome Atlas (for tumor) and Polish Breast Cancer Study (for tumor-adjacent).

Results

No gene was differentially expressed by BMI (FDR < 0.05). BMI was significantly associated with increased cellular proliferation pathways, particularly in ER+ tumors, and increased inflammation pathways in ER− tumor and ER− tumor-adjacent tissues (FDR < 0.05). High BMI was associated with upregulation of genes involved in epithelial-mesenchymal transition in ER+ tumor-adjacent tissues.

Conclusions

This study provides insights into molecular mechanisms of BMI influencing post-menopausal breast cancer biology. Tumor and tumor-adjacent tissues provide independent information about potential mechanisms.

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Data availability

All data generated during this study are included in this published article and its supplementary information files. The NHS/NHSII microarray data are publicly available at GSE115577. TCGA RNASeq data are available at https://cancergenome.nih.gov/. PBCS data are available from GSE49175 and GSE50939.

References

  1. Huang Z, Hankinson SE, Colditz GA et al (1997) Dual effects of weight and weight gain on breast cancer risk. JAMA 278:1407–1411. https://doi.org/10.1001/jama.1997.03550170037029

    Article  PubMed  CAS  Google Scholar 

  2. Eliassen AH, Colditz GA, Rosner B et al (2006) Adult weight change and risk of postmenopausal breast cancer. JAMA 296:193–201. https://doi.org/10.1001/jama.296.2.193

    Article  PubMed  CAS  Google Scholar 

  3. Barnard ME, Boeke CE, Tamimi RM (2015) Established breast cancer risk factors and risk of intrinsic tumor subtypes. Biochim Biophys Acta 1856:73–85. https://doi.org/10.1016/j.bbcan.2015.06.002

    Article  PubMed  CAS  Google Scholar 

  4. Yang XR, Chang-Claude J, Goode EL et al (2011) Associations of breast cancer risk factors with tumor subtypes: a pooled analysis from the breast cancer association consortium studies. J Natl Cancer Inst 103:250–263. https://doi.org/10.1093/jnci/djq526

    Article  PubMed  Google Scholar 

  5. Tamimi RM, Colditz GA, Hazra A et al (2012) Traditional breast cancer risk factors in relation to molecular subtypes of breast cancer. Breast Cancer Res Treat 131:159–167. https://doi.org/10.1007/s10549-011-1702-0

    Article  PubMed  CAS  Google Scholar 

  6. Suzuki R, Orsini N, Saji S et al (2009) Body weight and incidence of breast cancer defined by estrogen and progesterone receptor status—a meta-analysis. Int J Cancer 124:698–712. https://doi.org/10.1002/ijc.23943

    Article  PubMed  CAS  Google Scholar 

  7. Protani M, Coory M, Martin JH (2010) Effect of obesity on survival of women with breast cancer: systematic review and meta-analysis. Breast Cancer Res Treat 123:627–635. https://doi.org/10.1007/s10549-010-0990-0

    Article  PubMed  Google Scholar 

  8. Ewertz M, Jensen M-BB, Gunnarsdóttir K et al (2011) Effect of obesity on prognosis after early-stage breast cancer. J Clin Oncol 29:25–31. https://doi.org/10.1200/JCO.2010.29.7614

    Article  PubMed  Google Scholar 

  9. Jeon YW, Kang SH, Park MH et al (2015) Relationship between body mass index and the expression of hormone receptors or human epidermal growth factor receptor 2 with respect to breast cancer survival. BMC Cancer 15:865. https://doi.org/10.1186/s12885-015-1879-4

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Sparano JA, Wang M, Zhao F et al (2012) Obesity at diagnosis is associated with inferior outcomes in hormone receptor-positive operable breast cancer. Cancer 118:5937–5946. https://doi.org/10.1002/cncr.27527

    Article  PubMed  CAS  Google Scholar 

  11. Zhang X, Tworoger SS, Eliassen AH, Hankinson SE (2013) Postmenopausal plasma sex hormone levels and breast cancer risk over 20 years of follow-up. Breast Cancer Res Treat 137:883–892. https://doi.org/10.1007/s10549-012-2391-z

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Yager JD, Davidson NE (2006) Estrogen carcinogenesis in breast cancer. N Engl J Med 354:270–282. https://doi.org/10.1056/NEJMra050776

    Article  PubMed  CAS  Google Scholar 

  13. Yue W, Yager JD, Wang JP et al (2013) Estrogen receptor-dependent and independent mechanisms of breast cancer carcinogenesis. Steroids 78:161–170. https://doi.org/10.1016/j.steroids.2012.11.001

    Article  PubMed  CAS  Google Scholar 

  14. Kahn BB, Flier JS (2000) Obesity and insulin resistance. J Clin Invest 106:473–481. https://doi.org/10.1172/JCI10842

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Balaban S, Shearer RF, Lee LS et al (2017) Adipocyte lipolysis links obesity to breast cancer growth: adipocyte-derived fatty acids drive breast cancer cell proliferation and migration. Cancer Metab 5:1. https://doi.org/10.1186/s40170-016-0163-7

    Article  PubMed  PubMed Central  Google Scholar 

  16. Fuentes-Mattei E, Velazquez-Torres G, Phan L et al (2014) Effects of obesity on transcriptomic changes and cancer hallmarks in estrogen receptor-positive breast cancer. J Natl Cancer Inst 106:dju158. https://doi.org/10.1093/jnci/dju158

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Lumeng CN, Saltiel AR (2011) Inflammatory links between obesity and metabolic disease. J Clin Invest 121:2111–2117. https://doi.org/10.1172/JCI57132

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Lapeire L, Denys H, Cocquyt V, De Wever O (2015) When fat becomes an ally of the enemy: adipose tissue as collaborator in human breast cancer. Horm Mol Biol Clin Investig 23:21–38. https://doi.org/10.1515/hmbci-2015-0018

    Article  PubMed  CAS  Google Scholar 

  19. Denkert C, Loibl S, Noske A et al (2010) Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol 28:105–113. https://doi.org/10.1200/JCO.2009.23.7370

    Article  PubMed  CAS  Google Scholar 

  20. Sinicrope FA, Dannenberg AJ (2011) Obesity and breast cancer prognosis: weight of the evidence. J Clin Oncol 29:4–7. https://doi.org/10.1200/JCO.2010.32.1752

    Article  PubMed  Google Scholar 

  21. Dietze EC, Chavez TA, Seewaldt VL (2018) Obesity and triple-negative breast cancer disparities, controversies, and biology. Am J Pathol 188:280–290. https://doi.org/10.1016/j.ajpath

    Article  PubMed  PubMed Central  Google Scholar 

  22. Tao MH, Marian C, Nie J et al (2011) Body mass and DNA promoter methylation in breast tumors in the western New York exposures and breast cancer study. Am J Clin Nutr 94:831–838. https://doi.org/10.3945/ajcn.110.009365

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Mccullough LE, Chen J, White AJ et al (2015) Gene-specific promoter methylation status in hormone-receptor-positive breast cancer associates with postmenopausal body size and recreational physical activity. Int J Cancer Clin Res 2:1–20

    Article  Google Scholar 

  24. Creighton CJ, Sada YH, Zhang Y et al (2012) A gene transcription signature of obesity in breast cancer. Breast Cancer Res Treat 132:993–1000. https://doi.org/10.1007/s10549-011-1595-y

    Article  PubMed  CAS  Google Scholar 

  25. Toro AL, Costantino NS, Shriver CD et al (2016) Effect of obesity on molecular characteristics of invasive breast tumors: gene expression analysis in a large cohort of female patients. BMC Obes 3:22. https://doi.org/10.1186/s40608-016-0103-7

    Article  PubMed  PubMed Central  Google Scholar 

  26. Ogden CL, Carroll MD, Fryar CD, Flegal KM (2015) Prevalence of obesity among adults and youth: United States, 2011–2014. NCHS Data Brief 1–8

  27. The Cancer Genome Atlas (2012) Comprehensive molecular portraits of human breast tumours. Nature 490:61–70. https://doi.org/10.1038/nature11412

    Article  CAS  Google Scholar 

  28. Wang J, Heng YJ, Eliassen AH et al (2017) Alcohol consumption and breast tumor gene expression. Breast Cancer Res 19:108. https://doi.org/10.1186/s13058-017-0901-y

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Heng YJ, Lester SC, Tse GM et al (2017) The molecular basis of breast cancer pathological phenotypes. J Pathol 241:375–391. https://doi.org/10.1002/path.4847

    Article  PubMed  CAS  Google Scholar 

  30. Sun X, Gierach GL, Sandhu R et al (2013) Relationship of mammographic density and gene expression: analysis of normal breast tissue surrounding breast cancer. Clin Cancer Res 19:4972–4982. https://doi.org/10.1158/1078-0432.CCR-13-0029

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. García-Closas M, Brinton LA, Lissowska J et al (2006) Established breast cancer risk factors by clinically important tumour characteristics. Br J Cancer 95:123–129. https://doi.org/10.1038/sj.bjc.6603207

    Article  PubMed  PubMed Central  Google Scholar 

  32. Tamimi RM, Baer HJ, Marotti J et al (2008) Comparison of molecular phenotypes of ductal carcinoma in situ and invasive breast cancer. Breast Cancer Res 10:R67. https://doi.org/10.1186/bcr2128

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Troy LM, Hunter DJ, Manson JE et al (1995) The validity of recalled weight among younger women. Int J Obes Relat Metab Disord 19:570–572

    PubMed  CAS  Google Scholar 

  34. Wolf AM, Hunter DJ, Colditz GA et al (1994) Reproducibility and validity of a self-administered physical activity questionnaire. Int J Epidemiol 23:991–999

    Article  PubMed  CAS  Google Scholar 

  35. Chen WY, Rosner B, Hankinson SE et al (2011) Moderate alcohol consumption during adult life, drinking patterns, and breast cancer risk. JAMA 306:1884–1890. https://doi.org/10.1001/jama.2011.1590

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Xu W, Seok J, Mindrinos MN et al (2011) Human transcriptome array for high-throughput clinical studies. Proc Natl Acad Sci USA 108:3707–3712. https://doi.org/10.1073/pnas.1019753108

    Article  PubMed  PubMed Central  Google Scholar 

  37. Glue Grant Human Transcriptome Array Affymetrix. http://gluegrant1.stanford.edu/~DIC/GGHarray/

  38. Affymetrix (2007) Quality assessment of exon and gene arrays

  39. Kauffmann A, Gentleman R, Huber W (2009) arrayQualityMetrics—a bioconductor package for quality assessment of microarray data. Bioinformatics 25:415–416. https://doi.org/10.1093/bioinformatics/btn647

    Article  PubMed  CAS  Google Scholar 

  40. Leek JT, Johnson WE, Parker HS et al (2012) The SVA package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics 28:882–883. https://doi.org/10.1093/bioinformatics/bts034

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Ritchie ME, Phipson B, Wu D et al (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43:e47. https://doi.org/10.1093/nar/gkv007

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Liberzon A, Birger C, Thorvaldsdóttir H et al (2015) The molecular signatures database hallmark gene set collection. Cell Syst 1:417–425. https://doi.org/10.1016/j.cels.2015.12.004

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Wu D, Smyth GK (2012) Camera: a competitive gene set test accounting for inter-gene correlation. Nucleic Acids Res 40:e133. https://doi.org/10.1093/nar/gks461

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Rotunno M, Sun X, Figueroa J et al (2014) Parity-related molecular signatures and breast cancer subtypes by estrogen receptor status. Breast Cancer Res 16:R74. https://doi.org/10.1186/bcr3689

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Casbas-Hernandez P, Sun X, Roman-Perez E et al (2015) Tumor intrinsic subtype is reflected in cancer-adjacent tissue. Cancer Epidemiol Biomarkers Prev 24:406–414. https://doi.org/10.1158/1055-9965.EPI-14-0934

    Article  PubMed  CAS  Google Scholar 

  46. Luqmani YA, Al Azmi A, Al Bader M et al (2009) Modification of gene expression induced by siRNA targeting of estrogen receptor α in MCF7 human breast cancer cells. Int J Oncol 34:231–242

    PubMed  CAS  Google Scholar 

  47. Chiang GG, Abraham RT (2007) Targeting the mTOR signaling network in cancer. Trends Mol Med 13:433–442. https://doi.org/10.1016/j.molmed.2007.08.001

    Article  PubMed  CAS  Google Scholar 

  48. Newgard CB, An J, Bain JR et al (2009) A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. Cell Metab 9:311–326. https://doi.org/10.1016/j.cmet.2009.02.002

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Borgquist S, Wirfält E, Jirström K et al (2007) Diet and body constitution in relation to subgroups of breast cancer defined by tumour grade, proliferation and key cell cycle regulators. Breast Cancer Res 9:R11. https://doi.org/10.1186/bcr1644

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Yanai A, Miyagawa Y, Murase K et al (2013) Influence of body mass index on clinicopathological factors including estrogen receptor, progesterone receptor, and Ki67 expression levels in breast cancers. Int J Clin Oncol. https://doi.org/10.1007/s10147-013-0585-y

    Article  PubMed  Google Scholar 

  51. Asiedu MK, Ingle JN, Behrens MD et al (2011) TGFbeta/TNFalpha-mediated epithelial-mesenchymal transition generates breast cancer stem cells with a claudin-low phenotype. Cancer Res 71:4707–4719. https://doi.org/10.1158/0008-5472.CAN-10-4554

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Fantuzzi G (2005) Adipose tissue, adipokines, and inflammation. J Allergy Clin Immunol 115:911–920. https://doi.org/10.1016/j.jaci.2005.02.023

    Article  PubMed  CAS  Google Scholar 

  53. Lochhead P, Chan AT, Nishihara R et al (2015) Etiologic field effect: reappraisal of the field effect concept in cancer predisposition and progression. Mod Pathol 28:14–29. https://doi.org/10.1038/modpathol.2014.81

    Article  PubMed  Google Scholar 

  54. Roman-Perez E, Casbas-Hernandez P, Pirone JR et al (2012) Gene expression in extratumoral microenvironment predicts clinical outcome in breast cancer patients. Breast Cancer Res 14:R51. https://doi.org/10.1186/bcr3152

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Vaysse C, Lømo J, Garred Ø et al (2017) Inflammation of mammary adipose tissue occurs in overweight and obese patients exhibiting early-stage breast cancer. Breast Cancer 3:19. https://doi.org/10.1038/s41523-017-0015-9

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  56. Iyengar NM, Brown KA, Zhou XK et al (2017) Metabolic obesity, adipose inflammation and elevated breast aromatase in women with normal body mass index. Cancer Prev Res (Phila) 10:235–243. https://doi.org/10.1158/1940-6207.CAPR-16-0314

    Article  CAS  Google Scholar 

  57. Rose DP, Gracheck PJ, Vona-Davis L (2015) The interactions of obesity, inflammation and insulin resistance in breast cancer. Cancers (Basel) 7:2147–2168. https://doi.org/10.3390/cancers7040883

    Article  CAS  Google Scholar 

  58. Simpson ER, Brown KA (2013) Obesity and breast cancer: role of inflammation and aromatase. J Mol Endocrinol 51:T51–T59. https://doi.org/10.1530/JME-13-0217

    Article  PubMed  CAS  Google Scholar 

  59. O’Brien S, Anandjiwala J, Price T (1997) Differences in the estrogen content of breast adipose tissue in women by menopausal status and hormone use. Obstet Gynecol 90:244–248. https://doi.org/10.1016/S0029-7844(97)00212-3

    Article  PubMed  Google Scholar 

  60. Santen RJ, Yue W, Wang JP (2015) Estrogen metabolites and breast cancer. Steroids 61–66. https://doi.org/10.1016/j.steroids.2014.08.003

  61. Santa-Maria CA, Yan J, Xie XJ, Euhus DM (2015) Aggressive estrogen-receptor-positive breast cancer arising in patients with elevated body mass index. Int J Clin Oncol 20:317–323. https://doi.org/10.1007/s10147-014-0712-4

    Article  PubMed  CAS  Google Scholar 

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Acknowledgements

We thank the participants and staff of the NHS and the NHSII for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and interpretation of these data. We are also grateful to the participants of TCGA and PBCS.

Funding

Funding for this project was provided by the National Institutes of Health Grants U19 CA148065, UM1 CA186107, P01 CA87969, UM1 CA176726, and R01 CA166666; the National Institute of Health Epidemiology Education Training Grant (T32 CA09001 to NCD); the National Library of Medicine Career Development Award (K22LM011931 to AHB); Susan G. Komen (SAC110014 to SEH; CCR 14302670 to AHB); the Klarman Family Foundation (YJH and AHB); and the University of Pittsburgh School of Medicine Dean’s Faculty Advancement Award (FM). Funds from the National Institutes of Health Intramural Research Program supported the Polish Breast Cancer Study and work by MGC and TUA.

Author information

Author notes

  1. Susan E. Hankinson and Andrew H. Beck are the co-senior authors.

Authors and Affiliations

  1. Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Ave, Dana 517B, Boston, MA, 02215, USA

    Yujing J. Heng & Andrew H. Beck

  2. Cancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, USA

    Yujing J. Heng & Andrew H. Beck

  3. Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA

    Jun Wang, Susan B. Brown & Susan E. Hankinson

  4. Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA

    Jun Wang

  5. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA

    Thomas U. Ahearn & Montserrat Garcia-Closas

  6. Channing Division of Network Medicine, Department of Medicine, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA, USA

    Xuehong Zhang, Natalie C. DuPre, David J. Hunter, A. Heather Eliassen, Rulla M. Tamimi & Susan E. Hankinson

  7. Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY, USA

    Christine B. Ambrosone

  8. Departamento de Patologia, AC Camargo Cancer Center, São Paulo, Brazil

    Victor Piana de Andrade

  9. Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA, USA

    Adam M. Brufsky

  10. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA

    Fergus J. Couch

  11. Dana-Farber Cancer Institute and Brigham and Women’s Cancer Center, Boston, MA, USA

    Tari A. King

  12. Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

    Francesmary Modugno

  13. Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA

    Celine M. Vachon

  14. Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA

    Melissa A. Troester

  15. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    David J. Hunter, A. Heather Eliassen, Rulla M. Tamimi & Susan E. Hankinson

  16. Nuffield Department of Population Health, University of Oxford, Oxford, UK

    David J. Hunter

Authors
  1. Yujing J. Heng
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  2. Jun Wang
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Contributions

Conceived and designed the study: SEH, AHB, AHE, RMT, DJH. Nurses’ Health Studies microarray, data collection, and analyses: YJH, JW, XZ, NCD, AHE, RMT, SEH, AHB. The Cancer Genome Atlas data collection: SBB, CBA, VPA, AMB, FJC, TAK, FM, CMV. Polish Breast Cancer Study data collection and analyses: TUA, MGC, MAT. All authors contributed to the writing and reviewing of the manuscript.

Corresponding author

Correspondence to Yujing J. Heng.

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Competing interests

AHB is an equity stock holder and Board of Director Member of PathAI. All other authors declare no competing interests.

Ethics approval

The Committee on the Use of Human Subjects in Research at Brigham and Women’s Hospital, Boston, MA reviewed and approved this study.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOC 44 KB) Detailed description of methodologies.

Supplementary material 2 (DOC 167 KB)

10549_2018_5034_MOESM3_ESM.pdf

Supplementary material 3 (PDF 664 KB) Heatmaps displaying driver genes (p<0.10, limma analyses) that are contributing to the enrichment of the validated gene sets in A. estrogen receptor-positive tumors, B. estrogen receptor-negative tumors, C. estrogen receptor-positive tumor-adjacent tissues and D. estrogen receptor-negative tumor-adjacent tissues. Increasing color intensity of the cells indicates a smaller p value.

10549_2018_5034_MOESM4_ESM.pdf

Supplementary material 4 (PDF 143 KB) Questionnaire provided to The Cancer Genome Atlas (TCGA) participants to collect lifestyle variables.

Supplementary material 5 (XLSX 50498 KB) Detailed differential gene expression analyses using limma.

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Heng, Y.J., Wang, J., Ahearn, T.U. et al. Molecular mechanisms linking high body mass index to breast cancer etiology in post-menopausal breast tumor and tumor-adjacent tissues. Breast Cancer Res Treat 173, 667–677 (2019). https://doi.org/10.1007/s10549-018-5034-1

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