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    Breast Cancer: From FNA to DNA

    Ashraf Khan, MD, FRCPath

    University of MassachusettsMedical School

    Worcester, MA

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    Cancer Statistics, 2007

    CA Cancer J Clin2007;57;43-66

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    Breast Cancer:

    Evolution of Diagnostic Pathology

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    Breast: TDLU

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    ADH: a continuum

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    Tumor Growth & Progression

    Transformation

    Growthof Transformed Cells

    Local Invasion

    Distant Metastasis

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    Tumor Initiation & Progression

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    Tumor Heterogeneity

    CK 5/6

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    Tumor Progression &Heterogeneity

    Emergence of New subclones as aresult of random spontaneous

    mutations Different Phenotype

    Invasiveness

    ability to metastasize

    hormone responsiveness

    response to anti-neoplastic therapy

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    METASTATICCASCADE

    SPREAD OFTUMOR

    THROUGHBLOODVESSELS

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    StereotacticMammotomy/Biopsy

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    FNA

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    Breast: Stereotactic NeedleCore Biopsy Specimen

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    DNA

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    Prognosis in Breast Cancer

    Traditional prognostic factorsTNM staging information 5y w/Stage I: 87%, II: 75%, III: 46%, IV: 13%

    Histologic subtype tubular, mucinous, medullary, lobular, papillary vs. Ductal NOS better 30y survival (60% vs. 20%)

    Histologic grade (SBR) Nuclear grade, tubule formation, mitosis 10 y I. 85% II. 60% III. 15%

    Hormone receptor status ER/PR

    80% ER/PR+ cases respond to endocrine therapy 40% of ER or PR 10% of ER&PR

    HER2 response to Trastuzumab (Herceptin)

    Others LVI, Ki67, DNA ploidy

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    Breast Cancer: Grading

    Grade I

    Grade II Grade III

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    Breast Cancer: Estrogen receptor

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    Breast Cancer: HER-2/neu

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    Breast Cancer:HER-2 gene amplification

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    TUMORS HAVE PERSONALITIES

    Various sub-types ofbreast cancer havedifferent biologicalbehavior and aspecific statisticalprofile

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    Need for new biomarkers to help inmanagement of breast cancer

    Breast Cancer Rx Includes:

    Local/Regional therapy

    Surgery Radiation Rx

    Systemic therapy

    Hormonal treatment

    Chemotherapy

    Herceptin for HER-2 positive tumors

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    Aug. 2000

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    Molecular classification ofbreast cancer

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    CK 5/6

    Breast: Cytokeratin Immunostaining

    CK 5/6

    CK 8/18

    CK 8/18

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    Basal phenotype

    common morphological features:

    high histological grade, metaplastic features ,wide tumor necrosis pushing borders, marked lymphoid reaction,

    lack of tubule formation

    no specific hallmark morphological features to identify

    reliably on routine H&E sections Modern Pathology (2006) 19, 264271

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    Modern Pathology (2006) 19, 264271

    Breast: Basal-like Carcinoma

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    Features of basal-like carcinomaMalzahn 1998 Basal cytokeratin 5, 14 or 17 expression is associated with aggressive behavior

    Perou 2000 First characterized the gene expression pattern of the basal like carcinomas

    Tsuda 2000 Myoepithelial tumors (S-100 and cytokeratin 14 positives) have bad prognosis

    Sorlie 2001 Tumor gene expression has clinical implications. Basal breast carcinomas are hormonereceptors and Her2/neu negatives and often with TP53 mutation

    van de Rijn 2002 Cytokeratins 17 and 5 related with aggressive breast carcinomas

    Foulkes 2003 BRCA1 mutations are frequent in basal breast carcinomas

    Nielsen 2004 Basal carcinomas are negative for hormone receptors and Her2. Frequent cytokeratin 5,EGFR and CD117 expression

    Jones 2004 Cytogenetic subgroup of grade III, breast carcinomas with cytokeratin 14 expression havepoor clinical outcomes

    Abd El-Rehim 2004 Differences in luminal and basal cytokeratin expressions in breast carcinomas. Frequent

    EGFRexpression

    Tsuda 2005 KIT and EGFRare frequent in breast carcinomas with mesenchymal or myoepithelialdifferentiation

    Rakha 2006 Myoepithelial carcinomas may be a subtype of basal breast carcinomas

    Bertucci 2006 Medullary features are frequent in basal breast carcinomas

    Shaolei Lu 2007 -4 Integrin expression increased in basal like breast cancer

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    2001

    Gene expression patterns of breast carcinomas distinguishtumor subclasses with clinical implications

    Therese Srliea,b,c, Charles M. Peroua,d, Robert

    Tibshiranie, Turid Aasf, Stephanie Geislerg, HildeJohnsenb, Trevor Hastiee, Michael B. Eisenh, Matt van deRijni, Stefanie S. Jeffreyj, Thor Thorsenk, Hanne Quistl,John C. Matesec, Patrick O. Brownm, David Botsteinc, PerEystein Lnningg, and Anne-Lise Brresen-Daleb,n

    PNAS

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    Co yri ht 2001 by the National Academy of Sciences

    Srlie, Therese et al. (2001) Proc. Natl. Acad. Sci. USA 98, 10869-10874

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    Copyright 2001 by the National Academy of Sciences

    Srlie, Therese et al. (2001) Proc. Natl. Acad. Sci. USA 98, 10869-10874

    (85 samples) with the status of TP53 indicated by the color of the terminal dendrogram line

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    Copyright 2001 by the National Academy of Sciences

    Srlie, Therese et al. (2001) Proc. Natl. Acad. Sci. USA 98, 10869-10874

    (luminals B and C were considered one group)

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    Sorlie et al. Proc. Natl. Acad. Sci.2003

    OS and DDFS based on subtypes

    M l l b t i f b t

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    Molecular sub-typing of breastcancer

    Molecular studies have identified specific subsets ofinvasive ductal carcinoma with clinical implications:

    Basal-like carcinoma - CK 5/6 +

    HER-2 overexpressing sub group

    Normal breast-like

    Luminal cell like, ER+

    Luminal cell like ca are ER positive and have a betterprognosis compared to basal like ca which are ER

    negative

    Sorlie et al PNAS, 2001;98:10869-74

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    2002

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    N Engl J Med, Vol. 347, No. 25 2002

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    Marc J. van de Vijer et alN Engl J Med, Vol. 347, No. 25 2002

    295 patients, 180 poor-prognosis signature 115 had a good-prognosis

    signature,the mean overall 10-year survival rateswere 54.6+/-4.4 percent and 94.5+/-2.6percent,

    At 10 years, the probability of remainingfree of distant metastases was 50.6% wpoor prognosis sig. and 85.2% w goodprognosis signature.The hazard ratio for distant metastases inthe poor-prognosis group was 5compared with the good-prognosisgroup.

    The gene-expression profile was found tobe more powerful predictor of theoutcome than standard systems based onclinical and histologic criteria.

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    Marc J. van de Vijer et alN Engl J Med, Vol. 347, No. 25 2002

    M l l P fili f B

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    Molecular Profiling of BreastCancer

    MammaPrint

    Based on evaluation of a 70-gene set in T1

    and T2 breast cancers Classifies tumors in to Good and Bad

    prognosis groups

    FDA approved in Feb. 2007

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    Oncotype Dx

    Dec. 2004

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    Molecular sub-typing of breast cancer:Oncotype DX

    Multigene (21 [16 cancer genes and 5 house

    keeping genes]) assay to predict recurrenceof tamoxifen-treated node-negative breastcancer using National Surgical AdjuvantBreast and Bowel Project (NSABP) trial B-14

    database:

    Paik S et al. NEJM. 2004;351:2817-26

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    Molecular sub-typing of breast cancer: Oncotype DX

    Paik S et al. NEJM. 2004;351:2817-26

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    Oncotype DX Sample Report

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    Molecular Sub-typing of Breast Cancer

    Robustness, scalability, and integration of a wound-responsegene expression signature in predicting breast cancer survival

    Howard Y. Chang a, b c, Dimitry S. A. Nuyten c, d, e, Julie BSneddon b, Trevor Hastie f, Robert Tibshirani f, ThereseSrlie b, g, Hongyue Dai h i, Yudong D. He h i, Laura J. van'tVeer d i, Harry Bartelink e, Matt van de Rijn j, Patrick O.Brown b, k, l, and Marc J. van de Vijver d, laProgram in Epithelial Biology, Departments of bBiochemistry,fHealthResearch and Policy, and jPathology, and kHoward Hughes Medical

    Institute, Stanford University School of Medicine, Stanford, CA 94305;Departments of dDiagnostic Oncology and eRadiation Oncology, TheNetherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, TheNetherlands; hRosetta Inpharmatics, Seattle, WA 98109; and gNorwegianRadium Hospital, 0310 Oslo, Norway

    Chang, Howard Y. et al. (2005) Proc. Natl. Acad. Sci. USA 102, 3738-3743

    2005

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    Copyright 2005 by the National Academy of Sciences

    Chang, Howard Y. et al. (2005) Proc. Natl. Acad. Sci. USA 102, 3738-3743

    Performance of a "wound response" gene expression signature in predicting breast cancer progression

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    Copyright 2005 by the National Academy of Sciences

    Chang, Howard Y. et al. (2005) Proc. Natl. Acad. Sci. USA 102, 3738-3743

    Integration of diverse gene expression signatures for risk prediction

    Breast Cancer: Concordance among gene

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    g gexpression predictors

    Fan et al NEJM, 2006

    B east Cance compa ison of

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    Breast Cancer: comparison ofvarious gene expression models

    Fan et al NEJM, 2006

    Future Perspective on Breast

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    Future Perspective on BreastCancer Typing

    POOR

    PROGNOSIS

    GOOD

    PROGNOSIS

    Th k

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    Thank you