Benign Breast Disease – Focus on Atypia Lynn C. Hartmann, MD Women’s Cancer Program Mayo Clinic...
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Transcript of Benign Breast Disease – Focus on Atypia Lynn C. Hartmann, MD Women’s Cancer Program Mayo Clinic...
Benign Breast Benign Breast Disease –Disease –Focus on Focus on
AtypiaAtypia
Lynn C. Hartmann, MDLynn C. Hartmann, MD
Women’s Cancer ProgramWomen’s Cancer Program
Mayo Clinic Cancer CenterMayo Clinic Cancer Center
• 1967-2001: 13,647 women 1,173 cancers
• Iowa SEER Registry for comparison
• Mayo Benign Breast Disease Cohort
Breast Carcinogenesis Breast Carcinogenesis (presumed)(presumed)
Benign Breast Disease Breast Cancer
BBD: Risk PredictionBBD: Risk Prediction
Relative risks by histologyRelative risks by histology
Non-Non-proliferativeproliferative
ProliferativeProliferativeno atypiano atypia
Atypical Atypical hyperplasiahyperplasia
1.271.27 1.881.88 4.244.24
Cancer Prev Res 2011 Dec;4(12):1947-52.
On premalignant lesionsOn premalignant lesions
““If becoming a BC results from randomly If becoming a BC results from randomly acquiring multiple mutations enabling malignant acquiring multiple mutations enabling malignant behavior (growth, motility, invasion, etc), why is behavior (growth, motility, invasion, etc), why is there an apparent order to the development there an apparent order to the development and progression of premalignant lesions?”and progression of premalignant lesions?”
D. Craig AllredD. Craig Allred
Ca Prev Res, 2011Ca Prev Res, 2011
•
On premalignant lesionsOn premalignant lesions
• Incidence of premalignant lesions in non-Incidence of premalignant lesions in non-cancerous breasts declines significantly cancerous breasts declines significantly from PDWA to atypia to CISfrom PDWA to atypia to CIS
• Regions of gradual histologic continuity Regions of gradual histologic continuity between these existbetween these exist
• Premalignant lesions much more Premalignant lesions much more common in cancer-containing breasts common in cancer-containing breasts (coexistent atypia ~ 50%).(coexistent atypia ~ 50%).
On premalignant lesionsOn premalignant lesions
• Atypias coexisting with DCIS and Atypias coexisting with DCIS and invasive BC share genetic alterationsinvasive BC share genetic alterations
• ~ 50% of atypias contain monoclonal ~ 50% of atypias contain monoclonal populations of cellspopulations of cells
BBD: Risk PredictionBBD: Risk Prediction
Relative risks by histologyRelative risks by histology
Non-Non-proliferativeproliferative
ProliferativeProliferativeno atypiano atypia
Atypical Atypical hyperplasiahyperplasia
1.271.27 1.881.88 4.244.24
Atypia (ADH and ALH)Atypia (ADH and ALH)
• How well do current models work for How well do current models work for women with atypical hyperplasia?women with atypical hyperplasia?
• Does a positive family history further Does a positive family history further increase risk?increase risk?
• Can we better stratify risk within atypia?Can we better stratify risk within atypia?
• Can biomarkers stratify risk?Can biomarkers stratify risk?
Atypical HyperplasiaAtypical Hyperplasia
• ~ 50,000 US women diagnosed with AH ~ 50,000 US women diagnosed with AH each yeareach year
• ~ 54,000 US women diagnosed with ~ 54,000 US women diagnosed with DCIS each yearDCIS each year
Atypical Ductal Hyperplasia (ADH)Atypical Ductal Hyperplasia (ADH)
Within ducts, proliferation Within ducts, proliferation of monotonous cells in of monotonous cells in architecturally complex architecturally complex patterns including patterns including secondary lumens and secondary lumens and micropapillary formations.micropapillary formations.
Atypical Lobular Hyperplasia (ALH)Atypical Lobular Hyperplasia (ALH)
Expanded acini filled Expanded acini filled with monotonous with monotonous polygonal cells with polygonal cells with loss of acini lumens. loss of acini lumens.
Major Studies of Atypia and Associated Breast Cancer
Study Year Population Method of Diagnosis
Pathology Review
Median f/u (yrs)
# (%) with atypia
Breast Cancer Relative Risk
(95% CI)
Comments
Nashville 1 1985 10542 Tennessee patients with BBD 1950-1968
Surgical breast biopsy
Central review
17.5 377 (3.6%)268 women with FU (283 biopsies)
ALH 4.2 (2.6-6.9)
ADH 4.3 (2.7-6.9)
39 women with AH & FH with RR=8.9 (4.8-17)
Nurses Health Study 2
1992 Nurses Health Study part’s with cancer or BBD, 121 cases/488 controls
Surgical breast biopsy
Central review
9 3.7(2.1-6.8)
Risk higher in premenopausal than postmenopausal. FH does not increase risk.
Mayo3 2005 9087 women with biopsied BBD 1967-1991
Surgical breast biopsy
Central review
12.2 336 (3.7%) 4.4(3.4-5.6)
REF Iowa SEER
1Dupont WD, Page DL: Risk factors for breast cancer in women with proliferative breast disease. N Engl J Med 1985; 312:146-151. 2London SJ, Connolly JL, Schnitt SJ, Colditz GA: A prospective study of benign breast disease and the risk of breast cancer. JAMA 1992; 267:941-9443Hartmann LC, Sellers TA, Frost MH, et al.: Benign breast disease and the risk of breast cancer. N Engl J Med 2005; 353:229-237.
Gail modelGail model
• Best-known model; incorporates Best-known model; incorporates multiple factors in risk calculation multiple factors in risk calculation
• Gail model on NCI website is viewed ~ Gail model on NCI website is viewed ~ 500,000 times a year500,000 times a year
Atypia and Gail modelAtypia and Gail model
• 331 women with atypia in Mayo BBD 331 women with atypia in Mayo BBD cohortcohort
• Median follow-up 13.7 yearsMedian follow-up 13.7 years
• 58 invasive breast cancers; 8 in the first 58 invasive breast cancers; 8 in the first five yearsfive years
c-statistic 0.50 (0.44-0.55)
Pankratz et alJCO 11/08
Gail model features and association with Gail model features and association with breast cancer riskbreast cancer risk
CharacteristicsCharacteristics P-valueP-value
Age at biopsyAge at biopsy 0.9030.903
Age at menarcheAge at menarche 0.3980.398
Age at first live birthAge at first live birth 0.2690.269
First degree relatives with First degree relatives with breast cancerbreast cancer
0.2630.263
Number of biopsiesNumber of biopsies 0.4910.491
331 women with atypia—Mayo
Pankratz, Hartmann et al. JCO, 2008
If tissue is the basis of the model . . .
In displaying the phenotype of atypia, the tissue has already integrated various risk exposures.
Boughey J C et al. JCO 2010;28:3591-3596
©2010 by American Society of Clinical Oncology
Cumulative risk of BC after atypiaCumulative risk of BC after atypia
Cumulative breast cancer incidence Cumulative breast cancer incidence among women with atypical hyperplasiaamong women with atypical hyperplasia
Bre
as
t C
an
ce
r In
cid
en
ce
3+
38%
23%
12%
5%
Involution (Regression)Involution (Regression)
““In summary, recent work by the Mayo group In summary, recent work by the Mayo group emphasizes the emphasizes the potential for using visual potential for using visual assessmentsassessments of tissue architecture as of tissue architecture as integrated measures of riskintegrated measures of risk. .
JNCI, Nov 2010JNCI, Nov 2010
J Natl Cancer Inst (2010) 102 (22): 1685-1687.
JNCI editorial, Nov 2010JNCI editorial, Nov 2010
• Improving breast cancer risk prediction Improving breast cancer risk prediction is critically important given the is critically important given the limitations of currently available modelslimitations of currently available models and the and the desirability of tailoring screening desirability of tailoring screening and preventionand prevention to levels of risk.“ to levels of risk.“
No breast cancer
Breast cancer
Matched on age, era, histology
Can molecular analyses differentiate between cases and controls?
Biomarker StudiesBiomarker Studies
Association of cyclooxygenase-2 staining intensity in atypia Association of cyclooxygenase-2 staining intensity in atypia with risk of breast cancer *with risk of breast cancer *
COX-2 staining COX-2 staining intensityintensity
No. of women No. of women RR (95% CI)**RR (95% CI)**
All women All women 235235 3.31 (2.38 to 4.49)3.31 (2.38 to 4.49)
Staining categoryStaining category
0-1+0-1+ 130130 2.63 (1.56 to 4.15)2.63 (1.56 to 4.15)
2+2+ 7171 3.56 (1.94 to 5.97)3.56 (1.94 to 5.97)
3+3+ 3434 5.66 (2.59 to 10.75)5.66 (2.59 to 10.75)
*COX-2 = cyclooxygenase-2; RR = relative risk; CI = confidence interval
**Standarized incidence ratio and 95% confidence intervals, comparing observed number of breast cancers with those expected. All results account for age and calendar period.
Visscher DW et al, J Natl Cancer Inst 2008
Santisteban M et al. Breast Cancer Res Treat 2009
ER Expression in AtypiaER Expression in Atypia
• 246 women with AH who had open surgical 246 women with AH who had open surgical biopsy, 49 of whom developed BC biopsy, 49 of whom developed BC
• 87 with ADH87 with ADH• 141 with ALH141 with ALH• Median F/U = 14.4 yrsMedian F/U = 14.4 yrs• Used computerized digital image analysis to Used computerized digital image analysis to
quantitate ER expressionquantitate ER expression
Cancer Prev Res 2011 Mar;4(3):435-44.
Relationship between ER expression and atypia type.
Cancer Prev Res 2011 Mar;4(3):435-44.
Cancer Prev Res 2011 Mar;4(3):435-44.
ADH showing strong, homogeneous ER staining
ALH showing moderate ER staining heterogeneously
Relationship between ER expression and age in women with atypical hyperplasia.
Cancer Prev Res 2011 Mar;4(3):435-44.
ER Expression in AtypiaER Expression in Atypia
• ER expression did not vary by –ER expression did not vary by –
-- # of foci of atypia-- # of foci of atypia
-- Involution extent (controlling for age)-- Involution extent (controlling for age)
-- Extent of family history-- Extent of family history
Atypia: SummaryAtypia: Summary
• Atypia = High risk finding (RR ~ 4)Atypia = High risk finding (RR ~ 4)
• Features that do NOT further stratify Features that do NOT further stratify risk: risk: Family history Family history
Type of atypiaType of atypia
Atypia: SummaryAtypia: Summary
• Features that DO further stratify risk:Features that DO further stratify risk:
# of foci of atypia# of foci of atypia
extent of involutionextent of involution
younger ageyounger age
biomarkers, eg COX-2 and Ki67biomarkers, eg COX-2 and Ki67
require validationrequire validation
Missing ADH ALH ADH and ALH
Better risk prediction modelBetter risk prediction model
Clinical Risk Factors
Clinical Risk Factors
Benign HistologyBenign
Histology
BiomarkersBiomarkersMammographic
DensityMammographic
Density
Mayo BBD Mayo BBD Cohort Cohort
Breast CliniciansLynn Hartmann, MDAmy Degnim, MDKarthik Ghosh, MDJudy Boughey, MD
Basic ScienceDerek Radisky, PhD
Database Management Marlene Frost, PhD Teresa AllersJo Johnson Mary Campion Melanie Kasner
Biostatisticians Shane Pankratz, PhDRob Vierkant, MASLorelle Benetti, BARyan Frank, BA
Pathologists Dan Visscher, MDAziza Nassar, MDCarol Reynolds, MD
EpidemiologyCeline Vachon, PhD