Oral Presentation Joint 2016 COSA and ANZBCTG Annual Scientific Meeting

The biology underlying mammographic density and preclinical mouse models to test new therapies (#122)

Cecilia W Huo 1 , Grace Chew 1 2 , Mark Waltham 1 3 , Wendy Ingman 4 5 , Kristy Brown 6 , Paul Timpson 7 , Christine Khoo 8 , Stephen Fox 8 9 10 , Prue Hill 11 , Shou Chen 11 , John Price 3 12 , Chau H Nguyen 12 , Elizabeth D Williams 13 14 , Michael Henderson 1 15 , Erik W Thompson 1 13 16 , Kara Britt 10 17 18
  1. University of Melbourne Department of Surgery, St. Vincent’s Hospital, Melbourne, VIC, Australia
  2. Austin Health and Northern Health, Melbourne, VIC, Australia
  3. Department. of Biochemistry and Molecular Biology, School of Biomedical Sciences, Monash University, Clayton, VIC, Australia
  4. Discipline of Surgery, Faculty of Health Sciences, School of Medicine, The Queen Elizabeth Hospital, University of Adelaide, Adelaide, vic, Australia
  5. Robinson Research Institute, University of Adelaide, North Adelaide, Australia
  6. Hudson Institute of Medical Research, Clayton, VIC, Australia
  7. Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
  8. Department of Pathology, Peter MacCallum Cancer Centre, Melbourne, Australia
  9. Department of Pathology, University of Melbourne, Parkville, VIC, Australia
  10. Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
  11. Department of Pathology, St Vincent’s Hospital, Melbourne, VIC, Australia
  12. Centre for Chronic Disease Prevention and Management, College of Health and Biomedicine, Victoria University, St Albans, VIC, Australia
  13. Institute of Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology and Translational Research Institute, Queensland
  14. Australian Prostate Cancer Centre – Queensland, Brisbane
  15. Division of Surgery, Peter MacCallum Cancer Centre, Melbourne
  16. St Vincent’s Institute of Medical Research, Melbourne
  17. Cancer Genetics, Peter MacCallum Cancer Centre, Melbourne
  18. Department of Anatomy and Developmental Biology, Monash University, Melbourne

High mammographic density (HMD) confers a significantly increased risk of breast cancer and is associated with breast cancers of more advanced stages. To determine the pathobiology underlying density we have studied HMD and low mammographic (LMD) tissue from non-cancer bearing women. We developed a mouse biochamber model that allows us to grow HMD and LMD tissue in mice and test density modulating therapies. We have also now extended this model to assess the ability of the HMD tissue to drive early stage cancer growth.

Breast tissue was collected from high-risk women undergoing prophylactic mastectomy. Tissue slices resected from the mastectomy specimens were X-rayed, then HMD and LMD regions were dissected. Formalin fixed paraffin sections were collected and fresh tissue was used in murine biochambers either alone or in combination with mCherry/luciferase tagged DCIS.com cells for 6 weeks.

HMD tissue has increased proportions of stroma and epithelium, increased aromatase activity but no changes in hormone receptor or Ki-67 marker status. The HMD region showed increased collagen deposition and organization as well as increased immune cell deposition in the stroma and epithelium. HMD and LMD tissue grew in the murine biochambers and was able to maintain the histology and radiographic density of the input material. Tamoxifen treatment decreased the radiographic and stromal cell density in line with its density reducing effect in the clinic.  When grown together with DCIS.com cells, HMD breast tissue led to increased primary tumour take, increased biochamber weight and an increased

number of high-grade invasive BCs compared to LMD. This correlated with an increased metastatic burden in the mice co-implanted with HMD tissue. LMD tissue showed some protective effects. These data are consistent with emerging studies showing increased progression on breast cancers arising in HMD regions.

Cumulatively our work provides some model systems in which to identify and assess molecular processes important in MD and MD-associated breast cancer risk, and suggests that HMD status should be a consideration in decision making for management of patients with DCIS lesions.