Novel breast tissue feature strongly associated with risk of breast cancer.
OBJECTIVE
Accurate, individualized risk prediction for breast cancer is lacking. Tissue-based features may help to stratify women into different risk levels. Breast lobules are the anatomic sites of origin of breast cancer. As women age, these lobular structures should regress, which results in reduced breast cancer risk. However, this does not occur in all women.


METHODS
We have quantified the extent of lobule regression on a benign breast biopsy in 85 patients who developed breast cancer and 142 age-matched controls from the Mayo Benign Breast Disease Cohort, by determining number of acini per lobule and lobular area. We also calculated Gail model 5-year predicted risks for these women.


RESULTS
There is a step-wise increase in breast cancer risk with increasing numbers of acini per lobule (P = .0004). Adjusting for Gail model score, parity, histology, and family history did not attenuate this association. Lobular area was similarly associated with risk. The Gail model estimates were associated with risk of breast cancer (P = .03). We examined the individual accuracy of these measures using the concordance (c) statistic. The Gail model c statistic was 0.60 (95% CI, 0.50 to 0.70); the acinar count c statistic was 0.65 (95% CI, 0.54 to 0.75). Combining acinar count and lobular area, the c statistic was 0.68 (95% CI, 0.58 to 0.78). Adding the Gail model to these measures did not improve the c statistic.


CONCLUSIONS
Novel, tissue-based features that reflect the status of a woman's normal breast lobules are associated with breast cancer risk. These features may offer a novel strategy for risk prediction.
McKian
Kevin P
KP
Department of Oncology, Mayo Clinic Cancer Center, Mayo Graduate School of Medical Education, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.
Reynolds
Carol A
CA
Visscher
Daniel W
DW
Nassar
Aziza
A
Radisky
Derek C
DC
Vierkant
Robert A
RA
Degnim
Amy C
AC
Boughey
Judy C
JC
Ghosh
Karthik
K
Anderson
Stephanie S
SS
Minot
Douglas
D
Caudill
Jill L
JL
Vachon
Celine M
CM
Frost
Marlene H
MH
Pankratz
V Shane
VS
Hartmann
Lynn C
LC
D000328:Adult; D000367:Age Factors; D001706:Biopsy; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000235:genetics / Q000473:pathology*; D016022:Case-Control Studies; D049109:Cell Proliferation; D005260:Female; D020022:Genetic Predisposition to Disease; D006801:Humans; D006965:Hyperplasia; D016015:Logistic Models; D008875:Middle Aged; D010298:Parity; D010375:Pedigree; D011230:Precancerous Conditions / Q000235:genetics / Q000473:pathology*; D011237:Predictive Value of Tests; D011247:Pregnancy; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors