Breast Cancer Research and Treatment

, Volume 173, Issue 3, pp 667–677 | Cite as

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

  • Yujing J. HengEmail author
  • Jun Wang
  • Thomas U. Ahearn
  • Susan B. Brown
  • Xuehong Zhang
  • Christine B. Ambrosone
  • Victor Piana de Andrade
  • Adam M. Brufsky
  • Fergus J. Couch
  • Tari A. King
  • Francesmary Modugno
  • Celine M. Vachon
  • Natalie C. DuPre
  • Montserrat Garcia-Closas
  • Melissa A. Troester
  • David J. Hunter
  • A. Heather Eliassen
  • Rulla M. Tamimi
  • Susan E. Hankinson
  • Andrew H. Beck



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.


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).


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.


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.


Breast cancer Obesity Gene expression The cancer genome atlas Nurses’ health study Polish breast cancer study 



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.

Author 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.


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.

Compliance with ethical standards

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.

Supplementary material

10549_2018_5034_MOESM1_ESM.doc (44 kb)
Supplementary material 1 (DOC 44 KB) Detailed description of methodologies.
10549_2018_5034_MOESM2_ESM.doc (167 kb)
Supplementary material 2 (DOC 167 KB)
10549_2018_5034_MOESM3_ESM.pdf (665 kb)
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 (143 kb)
Supplementary material 4 (PDF 143 KB) Questionnaire provided to The Cancer Genome Atlas (TCGA) participants to collect lifestyle variables.
10549_2018_5034_MOESM5_ESM.xlsx (49.3 mb)
Supplementary material 5 (XLSX 50498 KB) Detailed differential gene expression analyses using limma.


  1. 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. CrossRefPubMedGoogle Scholar
  2. 2.
    Eliassen AH, Colditz GA, Rosner B et al (2006) Adult weight change and risk of postmenopausal breast cancer. JAMA 296:193–201. CrossRefPubMedGoogle Scholar
  3. 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. PubMedGoogle Scholar
  4. 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. CrossRefPubMedGoogle Scholar
  5. 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. CrossRefPubMedGoogle Scholar
  6. 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. CrossRefPubMedGoogle Scholar
  7. 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. CrossRefPubMedGoogle Scholar
  8. 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. CrossRefPubMedGoogle Scholar
  9. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  10. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  11. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Yager JD, Davidson NE (2006) Estrogen carcinogenesis in breast cancer. N Engl J Med 354:270–282. CrossRefPubMedGoogle Scholar
  13. 13.
    Yue W, Yager JD, Wang JP et al (2013) Estrogen receptor-dependent and independent mechanisms of breast cancer carcinogenesis. Steroids 78:161–170. CrossRefPubMedGoogle Scholar
  14. 14.
    Kahn BB, Flier JS (2000) Obesity and insulin resistance. J Clin Invest 106:473–481. CrossRefPubMedPubMedCentralGoogle Scholar
  15. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  16. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Lumeng CN, Saltiel AR (2011) Inflammatory links between obesity and metabolic disease. J Clin Invest 121:2111–2117. CrossRefPubMedPubMedCentralGoogle Scholar
  18. 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. PubMedGoogle Scholar
  19. 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. CrossRefPubMedGoogle Scholar
  20. 20.
    Sinicrope FA, Dannenberg AJ (2011) Obesity and breast cancer prognosis: weight of the evidence. J Clin Oncol 29:4–7. CrossRefPubMedGoogle Scholar
  21. 21.
    Dietze EC, Chavez TA, Seewaldt VL (2018) Obesity and triple-negative breast cancer disparities, controversies, and biology. Am J Pathol 188:280–290. CrossRefPubMedPubMedCentralGoogle Scholar
  22. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  23. 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 2:1–20CrossRefGoogle Scholar
  24. 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. CrossRefPubMedGoogle Scholar
  25. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Ogden CL, Carroll MD, Fryar CD, Flegal KM (2015) Prevalence of obesity among adults and youth: United States, 2011–2014. NCHS Data Brief 1–8Google Scholar
  27. 27.
    The Cancer Genome Atlas (2012) Comprehensive molecular portraits of human breast tumours. Nature 490:61–70. CrossRefGoogle Scholar
  28. 28.
    Wang J, Heng YJ, Eliassen AH et al (2017) Alcohol consumption and breast tumor gene expression. Breast Cancer Res 19:108. CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Heng YJ, Lester SC, Tse GM et al (2017) The molecular basis of breast cancer pathological phenotypes. J Pathol 241:375–391. CrossRefPubMedGoogle Scholar
  30. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  31. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  32. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Troy LM, Hunter DJ, Manson JE et al (1995) The validity of recalled weight among younger women. Int J Obes Relat Metab Disord 19:570–572PubMedGoogle Scholar
  34. 34.
    Wolf AM, Hunter DJ, Colditz GA et al (1994) Reproducibility and validity of a self-administered physical activity questionnaire. Int J Epidemiol 23:991–999CrossRefPubMedGoogle Scholar
  35. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  36. 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. CrossRefPubMedGoogle Scholar
  37. 37.
    Glue Grant Human Transcriptome Array Affymetrix.
  38. 38.
    Affymetrix (2007) Quality assessment of exon and gene arraysGoogle Scholar
  39. 39.
    Kauffmann A, Gentleman R, Huber W (2009) arrayQualityMetrics—a bioconductor package for quality assessment of microarray data. Bioinformatics 25:415–416. CrossRefPubMedGoogle Scholar
  40. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  41. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Liberzon A, Birger C, Thorvaldsdóttir H et al (2015) The molecular signatures database hallmark gene set collection. Cell Syst 1:417–425. CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Wu D, Smyth GK (2012) Camera: a competitive gene set test accounting for inter-gene correlation. Nucleic Acids Res 40:e133. CrossRefPubMedPubMedCentralGoogle Scholar
  44. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  45. 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. CrossRefPubMedGoogle Scholar
  46. 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 34:231–242PubMedGoogle Scholar
  47. 47.
    Chiang GG, Abraham RT (2007) Targeting the mTOR signaling network in cancer. Trends Mol Med 13:433–442. CrossRefPubMedGoogle Scholar
  48. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  49. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  50. 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. Google Scholar
  51. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Fantuzzi G (2005) Adipose tissue, adipokines, and inflammation. J Allergy Clin Immunol 115:911–920. CrossRefPubMedGoogle Scholar
  53. 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. CrossRefPubMedGoogle Scholar
  54. 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. CrossRefPubMedPubMedCentralGoogle Scholar
  55. 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. PubMedGoogle Scholar
  56. 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. CrossRefGoogle Scholar
  57. 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. CrossRefGoogle Scholar
  58. 58.
    Simpson ER, Brown KA (2013) Obesity and breast cancer: role of inflammation and aromatase. J Mol Endocrinol 51:T51–T59. CrossRefPubMedGoogle Scholar
  59. 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. CrossRefPubMedGoogle Scholar
  60. 60.
    Santen RJ, Yue W, Wang JP (2015) Estrogen metabolites and breast cancer. Steroids 61–66.
  61. 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. CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Yujing J. Heng
    • 1
    • 2
    Email author
  • Jun Wang
    • 3
    • 4
  • Thomas U. Ahearn
    • 5
  • Susan B. Brown
    • 3
  • Xuehong Zhang
    • 6
  • Christine B. Ambrosone
    • 7
  • Victor Piana de Andrade
    • 8
  • Adam M. Brufsky
    • 9
  • Fergus J. Couch
    • 10
  • Tari A. King
    • 11
  • Francesmary Modugno
    • 12
  • Celine M. Vachon
    • 13
  • Natalie C. DuPre
    • 6
  • Montserrat Garcia-Closas
    • 5
  • Melissa A. Troester
    • 14
  • David J. Hunter
    • 6
    • 15
    • 16
  • A. Heather Eliassen
    • 6
    • 15
  • Rulla M. Tamimi
    • 6
    • 15
  • Susan E. Hankinson
    • 3
    • 6
    • 15
  • Andrew H. Beck
    • 1
    • 2
  1. 1.Department of Pathology, Beth Israel Deaconess Medical CenterHarvard Medical SchoolBostonUSA
  2. 2.Cancer Research InstituteBeth Israel Deaconess Cancer CenterBostonUSA
  3. 3.Department of Biostatistics and Epidemiology, School of Public Health and Health SciencesUniversity of Massachusetts AmherstAmherstUSA
  4. 4.Department of Preventive MedicineUniversity of Southern CaliforniaLos AngelesUSA
  5. 5.Division of Cancer Epidemiology and GeneticsNational Cancer InstituteBethesdaUSA
  6. 6.Channing Division of Network Medicine, Department of Medicine, Harvard Medical SchoolBrigham and Women’s HospitalBostonUSA
  7. 7.Department of Cancer Prevention and ControlRoswell Park Cancer InstituteBuffaloUSA
  8. 8.Departamento de PatologiaAC Camargo Cancer CenterSão PauloBrazil
  9. 9.Department of MedicineUniversity of Pittsburgh Medical CenterPittsburghUSA
  10. 10.Department of Laboratory Medicine and PathologyMayo ClinicRochesterUSA
  11. 11.Dana-Farber Cancer Institute and Brigham and Women’s Cancer CenterBostonUSA
  12. 12.Department of Obstetrics, Gynecology and Reproductive SciencesUniversity of Pittsburgh School of MedicinePittsburghUSA
  13. 13.Department of Health Sciences ResearchMayo ClinicRochesterUSA
  14. 14.Department of EpidemiologyUniversity of North CarolinaChapel HillUSA
  15. 15.Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonUSA
  16. 16.Nuffield Department of Population HealthUniversity of OxfordOxfordUK

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