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Molecular Pathology of Breast Cancer Ian Ellis Molecular Medical Sciences, University of Nottingham Departments of Histopathology, Nottingham City Hospital NHS Trust Time Prognosis Intrinsic Time Prognosis How long the tumour has been there Stage Intrinsic The nature of the tumour Biology Nottingham Prognostic Index Grade + LN Stage + (0.2 x Size) 1-3 1-3 cm Nottingham Prognostic Index 100 Age matched % Survival 80 GPG (2.1=3.4) 60 MPG (3.41-5.4) 40 20 PPG (>5.4) 0 0 635 1040 316 2 4 6 237 357 39 8 10 12 14 46 63 7 GPG MPG PPG 16 18 Years Histological Grade in Breast Carcinoma Consistency and Reproducibility Poor Cutler et al 1966 Stenkvist et al 1979 Delides et al 1980 Gilchrist et al 1985 Histological Grade in Breast Cancer Tubule formation Majority of tumour Moderate degree Little or none (>75%) (10-75%) (<10%) Nuclear pleomorphism Small, regular uniform cells Moderate increase in size and variability Marked variation Mitotic counts Dependent on microscope field area - 1 point - 2 points - 3 points - 1 point - 2 points - 3 points 1 - 3 points Histological Grade Microscope Leitz Nikon Ortholux Labophot X25 X40 Objective Field diameter Field area 0.44 mm 0.63 mm 0.274 mm2 0.152 mm2 0.312 mm2 1 point Count* 0.59 mm Leitz Diaplan X40 0-9 0-5 0-11 2 points 10-19 6-10 12-22 3 points >20 >11 >23 * Assessed as number of mitoses per 10 fields at the tumour periphery Nottingham Method for Histological Grade in Breast Carcinoma Consistency and Reproducibility Satisfactory Dalton et al 1984 Frierson et al 1985 Robbins et al 1995 Nottingham Method for Histological Grade in Breast Carcinoma Recommended by: RCPath NHSBSP EU AJCC UICC WHO Cox Multivariate Analysis Size Grade Tumour type LN Stage Vascular Invasion ??? 0.19 0.64 0.29 0.76 0.18 Z values > 1.96 significant at p=0.05 level Z 4.86 6.69 3.47 11.18 3.18 Cum. Survival N P I 1 .8 EPG GPG .6 MPG I MPG II .4 .2 PPG Chi-Square 899.005 DF P-Value 4 <.0001 0 0 48 96 144 192 240 288 Time Traditional Prognostic Factors • • • • • Histological grade Histological type Lymph node stage Tumour size Vascular invasion Cox Multivariate Analysis Size Grade LN Stage Tumour type Vascular Invasion ER C-erb-B2 DNA Index Proliferation Index ? 0.17 0.86 0.81 0.31 0.19 0.001 0.02 0.28 0.17 Z values > 1.96 significant at p=0.05 level ?Z 2.93 5.64 6.96 1.46 1.78 1.21 0.11 1.27 1.26 Cox Multivariate Analysis Size Grade LN Stage Tumour type Vascular Invasion ER C-erb-B2 DNA Index Proliferation Index ? 0.17 0.86 0.81 0.31 0.19 0.001 0.02 0.28 0.17 Z values > 1.96 significant at p=0.05 level ?Z 2.93 5.64 6.96 1.46 1.78 1.21 0.11 1.27 1.26 Prognostic Factors but eliminated by multivariate analysis Receptors & related ER PR Bcl-2 Liv-1 PS2 Cap D Histological Angiogenesis LVI Type Nucleolar Organisers Cell Antigens Lectins CEA Epithelial memb. Ag Growth Factors EGFR Cerb-B2/3&4 Proliferation Markers Mib1 Ki67 TK S-Phase Oncogenes C-myc Suppressor genes P53 Adhesion molecules E-Cadherin Catenins Integrins Cell Antigens Do we really need prognostic factors for breast carcinoma? There are at least three situations in which prognostic factors could be helpful • To identify patients whose prognosis is so good that adjuvant therapy after local surgery would not be cost beneficial • To identify patients whose prognosis is so poor that a more aggressive adjuvant approach would be warranted • To identify patients likely to be responsive or resistant to particular forms of therapy Clark GM. Breast Cancer Res Treat. 1994;30:117-26 Cum. Survival N P I 1 .8 EPG GPG .6 MPG I MPG II .4 .2 PPG Chi-Square 899.005 DF P-Value 4 <.0001 0 0 48 96 144 192 240 288 Time Do we really need prognostic factors for breast carcinoma? There are at least three situations in which prognostic factors could be helpful • To identify patients whose prognosis is so good that adjuvant therapy after local surgery would not be cost beneficial • To identify patients whose prognosis is so poor that a more aggressive adjuvant approach would be warranted • To identify patients likely to be responsive or resistant to particular forms of therapy Clark GM. Breast Cancer Res Treat. 1994;30:117-26 Prognostic Factor: Altered natural history Predictive Factor: Resistance or sensitivity to therapy ER Immunohistology Cut off points for treatment Score treatment Effect of Endocrine 0 2–3 4–6 7–8 No effect Small (20%) chance Even (50%) chance Good (75%) chance Leake et al. J Clin Path 2000; 53: 634-635 Herceptin ® humanised anti-HER2 monoclonal antibody EGFR / HER2 signalling Membrane p21ras P Raf P p38 MAPK pp90rsk Mek Nucleus E2/Tam ER ER P P AIB1 CBP Hormone-dependent growth MAPK c-jun c-fos Cell proliferation Prognostic Factors but eliminated by multivariate analysis Receptors & related ER PR Bcl-2 Liv-1 PS2 Cap D Histological Angiogenesis LVI Type Nucleolar Organisers Cell Antigens Lectins CEA Epithelial memb. Ag Growth Factors EGFR Cerb-B2/3&4 Proliferation Markers Mib1 Ki67 TK S-Phase Oncogenes C-myc Suppressor genes P53 Adhesion molecules E-Cadherin Catenins Integrins Cell Antigens Improved knowledge of cancer biology ? New therapy targets Time Prognosis How long the tumour has been there No Intrinsic The nature of the tumour Yes Cum. Survival N P I 1 .8 EPG GPG .6 MPG I .4 MPG II .2 Chi-Square 899.005 DF P-Value 4 <.0001 PPG 0 0 48 96 144 192 240 288 Time ER neg ER pos Sorlie, et al. PNAS 2001 Subtypes and Prognosis SURVIVAL DISEASE-FREE SURVIVAL Sorlie T et al, PNAS 2001 cDNA expression patterns • Gene expression patterns of breast cancer • Patterns in two tumour samples from the same individuals were always more similar to each other than either was to any other sample ? i) (Either) tumour is very homogenous, ? ii) (Or) Most of gene expression relates to a person’s DNA rather than the tumours • Patterns distinguish subclasses • Subclasses carry clinical implications Perou et al, Nature; 2000: 747-752 Sorlie et al PNAS 2001: 10868 - 74 cDNA expression patterns • Patterns distinguish subclasses • Subclasses carry clinical implications Perou et al, Nature; 2000: 747-752 Sorlie et al PNAS 2001: 10868 - 74 Breast Cancer is a Family of Diseases • Convergence of clinical and genomic data • Unclear how many distinct members of this family • At a minimum: – – – – HER-2 + Basal-like or triple negative ER + (luminal A) ER + (luminal B) “Basal-like” HER2-positive ER/PR-negative HER2-negative ER-positive Luminal B ER-positive Luminal A Luminal / ER positive/ basal negative group [group 1] Basal positive luminal /ER negative [group 5] Choice of Markers 1- involved in breast carcinogenesis Predisposing genes Normal breast Hormones & their receptors Cell proliferation Atypical cell proliferation Growth factors Genetic alterations Oncogenes Tumour suppressor genes Carcinoma insitu Cell adhesion molecules Invasive carcinoma 2- cDNA microarray studies 3- Have prognostic and predictive power 4- Related to tumor histogenesis and cellular lineage evolution 5- Related to special morphological types 24 well characterized tumor markers selected Luminal and basal differentiation [ck 7/8, 18, 19, 5/6, 14, actin and p63], Hormone receptors markers [ER, PgR and AR], EGFR family markers [EGFR, c-erbB-2, c-erbB-3 and c-erbB-4], Tumor suppressor gene products [p53, BRCA1 and Fhit], Adhesion molecule markers [E-cad and P-cad], Mucins muc 1, muc 2, Neuroendocrine differentiation chromogranin and synaptophysin Apocrine differentiation GCDFP-15. Results Six groups Have been identified 1 2 3 4 Cluster Tree [Dendrogram] 5 6 Groups 1 & 2 336 (31.2%) 180 (16.7%) Luminal epithelial markers, MUC1 and hormone receptor positive HER2 and p53 negative Differences in c-erbB-3, c-erbB-4 and BRCA1 expression Group 3 234 (21.7%) Luminal epithelial markers, MUC1 and HER2 positive Hormone receptor E Cadherin negative or weakly expressing Group 4 4 (0.4%) BRCA1, p53 EGFR and P-cadherin positive Hormone receptor negative Group 5 183 (17%) p53 protein, basal epithelial markers positive Luminal epithelial marker, hormone receptor expression, HER2 and BRCA1 low or negative. Group 6 139 (12.9%) Luminal epithelial markers, HER2, E Cadherin positive Hormone receptor, MUC1 negative or weakly expressing El-Rehim et al Int. J Cancer 2005;116: 340 -350 Groups 1 & 2 336 (31.2%) 180 (16.7%) Luminal epithelial markers, MUC1 and hormone receptor positive HER2 and p53 negative Differences in c-erbB-3, c-erbB-4 and BRCA1 expression Group 3 234 (21.7%) Luminal epithelial markers, MUC1 and HER2 positive Hormone receptor E Cadherin negative or weakly expressing Group 4 4 (0.4%) BRCA1, p53 EGFR and P-cadherin positive Hormone receptor negative Group 5 183 (17%) p53 protein, basal epithelial markers positive Luminal epithelial marker, hormone receptor expression, HER2 and BRCA1 low or negative. Group 6 139 (12.9%) Luminal epithelial markers, HER2, E Cadherin positive Hormone receptor, MUC1 negative or weakly expressing El-Rehim et al Int. J Cancer 2005;116: 340 -350 Relationship with histological grade 400 300 200 No of cases GRADE 100 3.00 2.00 0 1.00 p6 ou Gr p5 ou Gr p4 ou Gr p3 ou Gr P<0.001 p2 ou Gr p1 ou Gr GROUP Group distribution among different tumour types 700 GROUP No of cases 600 500 6.00 400 5.00 300 4.00 200 3.00 100 2.00 0 1.00 us eo an all lty sc cia Mi pe &s ST dN typ ial ixe M ec sp on m m co Un lar bu Lo d ixe m T NS y ar ul ed M lar bu Tu ive as Inv Histological tumour types Highly significant association with patient outcome 1.0 G4 n=4 G1 n=328 G2 n=180 .9 G6 n=138 G3 n=231 Probability .8 G5 n=177 .7 0 20 40 Survival in months Log Rank p<0.0001 60 80 100 120 140 160 Conclusions Distinct sub classes of breast cancer can be identified by expression of proteins of known relevance in breast cancer These sub classes are comparable to those identified by cDNA expression array technology Conclusions Molecular classification of breast cancer based on protein expression potentially offers further refinement of traditional methods of classification A modern clinically relevant breast cancer classification based on molecular genetic, phenotypic and morphological characteristics appears realistic Breast Cancer Classes Luminal classes Class 1 Class 2 Class 6 n=202 n=153 n=80 Discriminators Luminal cytokeratins ER and PgR HER3 and HER4 Muc1 HER2 class Class 3 n=77 Discriminators HER2 ER/PgR Basal classes Class 4 Class 5 n=82 n=69 Discriminators Basal cytokeratins ER, PgR, HER2 p53 Significant associations with pathology Luminal tumour classes Class 1 and 2: good prognostic factors including smaller tumour size, grade 1 tumours, node-negative and tubular mixed carcinomas Class 6: Poorer prognostic factors such as larger tumour size, higher stage and grade. Basal tumour classes Poor prognostic factors including grade 3 tumours, larger size, higher stage, ductal NST and medullary carcinomas. Class 4 patients (altered p53) younger than Class 5 patients (normal p53) Breast Cancer Specific Survival Luminal classes Basal classes p<0.001 HER2 class p<0.001 Highly significant association with patient outcome Nottingham Prognostic Index Class divisions are providing additional information to NPI Breast Cancer Phenotypic Classes Breast Cancer Luminal CKs+ ER+ HER2+ ER- Basal CKs+ ER- Luminal HER2 Class HER23 Basal HER3HER4- HER3+ HER4+ PgR+ PgR+ PgR- Class 2 Luminal N Class 1 Luminal A Class 6 Luminal B Mixed Class p53+ p53- Class 4 Basal – p53 altered Class 5 Basal – p53 normal Classes of Breast Cancer • Gene & protein expression patterns of breast cancers similar • Patterns distinguish subclasses • Subclasses carry clinical implications Complex epithelium Expression markers Simple epithelial CKs: Superficial cells Basal cells CK7, CK8, CK18 and CK19 Basal / high molecular weight CKs: CK5 and CK14 Cell type marker Luminal cells CK7, CK8, CK18, and CK19, MUC1 alpha-6 intergrin and EP CAM Myoepithelial cells basal CKs + SMA, SM myosin heavy chain, calponin, caldesmon, p63, CD10, maspin, 14-3-3sigma and S100 Basal cells CK5, CK14, CK17 ? Stem cells CK5 without CK8 / CK18 or SMA Luminal Subtypes • Luminal A/B – generally carry a good prognosis (1) • Luminal A better prognosis than B (1) • Is this in part due to better response to ET in luminal A cf B • Expect better response to ET in luminal subtypes • Poorer response (pCR) to Anthracycline &/or Taxane chemotherapy (2) • Recurrence score - Multi gene predictor of distant relapse in ER(+) LN(-)ve Txs treated with tamoxifen(3) (1) Sorlie et al PNAS 2003: 100: 8418 – 23, (2) Rouzier et al Human Cancer Biology 2005; 11: 5678-85 , (3) Paik et al NEJM 2004; 23: Abstr 512 Luminal Subtypes • Luminal A/B – generally carry a good prognosis (1) • Luminal A better prognosis than B (1) • Expect better response to ET in luminal subtypes (1) Sorlie et al PNAS 2003: 100: 8418 – 23, (2) Rouzier et al Human Cancer Biology 2005; 11: 5678-85 , Luminal Subtypes Questions • Do patients with luminal A tumours need chemotherapy ? • Do luminal B tumours respond to tamoxifen ? • Should patients with luminal B tumours receive an AI ? These seem familiar questions related to ER & PgR ! Will arrays provide a better answer ? A Multigene Assay to Predict Recurrence of Tamoxifen -Treated, Node - Negative Breast Cancer • NSABP B-14 trial - node-negative, tamoxifen-treated • 675 cases (668 assessable) paraffin-embedded tumor tissue • RT-PCR assay of 21 genes (16 cancer related & 5 ref genes • End point - distant recurrence • Prospectively defined algorithm to determine risk groups (low, intermediate, or high) S Paik et al N Engl J Med 2004;351:2817-26. 21 Genes Panel (Oncotype) Estrogen ER PGR BCL2 SCUBE2 HER2 GRB7 HER2 Proliferation Ki67 STK15 Survivin CCNB1 (cyclin B1) MYBL2 BAG1 GSTM1 CD68 Invasion MMP11 (stromolysin 3) CTSL2 (cathepsin L2) Reference ACTB (b-actin) GAPDH RPLPO GUS TFRC S Paik et al N Engl J Med 2004;351:2817-26. A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, NodeNegative Breast Cancer Distant recurrence at 10 years low Int high (51% cases) (22% cases) (27% cases) 6.8% 14.3% 30.5% (4.0 - 9.6) (8.3 - 20.3) (23.6 - 37.4) •Low-risk group v high-risk group (P<0.001). •Multivariate - independent of age and tumor size •Predictive of overall survival (P<0.001) •Can use as a continuous function to predict distant recurrence in individual patients. S Paik et al N Engl J Med 2004;351:2817-26. DCIS Allelic imbalance analysis suggests that low grade & high grade carcinomas follow different genetic pathways Roylance et al. J Pathol 2002; 196:32-36 ?Common Precursor Other candidates: E Cadherin Lobular Carcinoma LOH 16q Low Grade Carcinoma C-erbB-2 & p53 High Grade Carcinoma BRCA 1 17q BRCA 2 13q 1q 3p 11q 13q 17q Medullary Tub & Lob Tubular E Cadherin ?Common Precursor Lobular Carcinoma Lobular Ductal LOH 16q Low Grade Carcinoma C-erbB-2 & p53 High Grade Carcinoma E Cadherin Lobular Carcinoma 16q ?Common Precursor LOH 16q Low Grade Carcinoma C-erbB-2 & p53 High Grade Carcinoma 17q Class 1 E Cadherin Lobular Carcinoma 16q ?Common Precursor LOH 16q Low Grade Carcinoma Class 2 C-erbB-2 & p53 High Grade Carcinoma 17q Luminal Type A lesions •Luminal ck •ER rich •HER2 neg •16q del CCLs Low Grade DCIS LN LOW GRADE NEOPLASIA FAMILY TUBULAR TUBULOLOBULAR ILC Complex epithelium Expression markers Simple epithelial CKs: Superficial cells Basal cells CK7, CK8, CK18 and CK19 Basal / high molecular weight CKs: CK5 and CK14 Basal Breast Cancer • The concept of BP has been known for some time • First described using electron microscopy >30 years age • Its potential poor survival first reported by Dairkee et al in 1987 Recently, topical following: - Its recognition as the worst prognostic group in the high profile cDNA expression analysis - High frequency in BRCA1 gene mutation carriers However, previous studies: - Have not focused on routine identification of the BP - Were not of sufficient size to examine its clinical relevance - Dissimilar results in the different subgroups For example: All: Independent marker of poor prog in BC as a whole - van de Rijn et al: in LN neg but not in LN pos - Nielsen et al: in LN pos but not in the LN neg Most studies have defined BP by expression of basal CKs - Nielsen et al: CK5/6, ER, EGFR and HER-2 - Matos et al: CK5, P-cadherin and p63 - Lakhini et al: basal CKs, EGFR and osteonectin Basal Phenotype • Grade 3 • Duct/NST, Medullary like carcinoma, adenoid cystic carcinoma • High mitotic count, lack of tubule formation, comedo necrosis and salivary gland type adenoid cystic change • Larger size, LN disease, poorer NPI, DM and recurrence • High rate of liver, lung, and brain mets, less bone mets • Not with VI or with age Basal Phenotype Negative - ER, PgR and AR - LA CKs - FHIT protein - MUC1 - HER2 - BRCA1 Positive - P-cadherin - p53 - EGFR - E-cadherin P 53 ER CK 14 HER-2 Basal Breast Cancer 1) Group1: tumours with basal phenotype (CK5/6 and/or CK14) [18.6% of total] Was further subdivided into two subgroups; - A) dominant basal pattern (> 50% of cells +ve) [8.6%] - B) basal characteristics (10 - 50% of cells +ve) [10%]. 2) Group2: tumours with myoepithelial phenotype (SMA and/or p63) [13.7%] Basal Breast Cancer [LR 22.54, p<0.001] Basal Phenotype criteria Total 1872 cases after excluding uninformative • • • • 347 cases (18.6%) showed expression of CK5/6 and/or CK14 in >10% of tumour cells (defined as BP) Combined basal CKs +ve and ER -ve: 228 (12%) also HER-2 -ve: 170 (9%) Basal CKs +ve, ER -ve and EGFR +ve: 81 (4%) Routine practice: BP defined as expression of basal CKs Basal phenotype LN negative, grade 3 tumours [510 cases, 27% of total cases] Familial Breast Cancer • BRCA 1 Prediction • BRCA 1 – basal phenotype – Ck 5/6&14 +ve - 44% of all BRCA 1 carriers – Ck 5/6&14 +ve – < 2% sporadic cancers Lakhani Clin Cancer Res 2005 11 5175 Breast Cancer Subtypes, Race and Age N Basal HER2+ Luminal A Luminal B Unclass Premenopausal African-American 97 39% 9% 36% 9% 6% Postmenopausal African-American 99 14% 7% 59% 16% 4% Premenopausal non African-American 164 16% 6% 51% 18% 10% Postmenopausal non African-American 136 16% 6% 58% 16% 4% TOTAL 496 20% 7% 51% 16% 6% Adapted from Carey LA et al, ASCO 04 P=0.0001 Basal-like Breast Cancer and Chemotherapy (MDACC) Gene expression array subtyping and pathologic complete response to neoadjuvant chemotherapy with T-FAC (n=83) Molecular classification Luminal Normal breast HER2+ Basal subtype Residual Pathologic complete Disease response 93% [78-99] 7% [1-22] 100% [29-100] 0% [0-31] 55% [32-77] 45% [23 -68] 55% [32-76] 45% [24-68] Chi square: P<0.001 Rouzier R et al, SABCS 2004 Basal-like Breast Cancer and Neoadjuvant Chemotherapy Clinical Response to AC N=104 Basal-like HER2+ Luminal N Overall RR Clinical CR Clinical PR 28 22 55 86%* 68% 60% 32%* 18% 5% 54% 50% 55% Pathologic stage post-chemotherapy Basal-like HER2+ Luminal N 0 I II III 27 22 55 30% 27% 13% 22% 14% 13% 26% 41% 36% 22% 18% 38% *p < 0.05 Carey LA, SABCS 2004 Treatment Approaches of Interest for Triple Negative Disease • Angiognesis inhibitors • EGFR inhibitors • PARP inhibitors (particularly in setting of BRCA1 and 2 mutant tumors) • Platinum salts – Take advantage of inability of BLC to repair double strand DNA breaks – Similarities between sporadic basal-like cancers and BRCA1 associated tumors Time Prognosis How long the tumour has been there Intrinsic The nature of the tumour Cum. Survival Tumour Size 1 0-9mm 10-14mm 15-19mm 20-24mm .8 .6 .4 25mm or more .2 Chi-Square 272.403 DF P-Value 4 <.0001 0 0 0 48 4 96 8 144 12 192 Time 16 Time (years) Cum. Survival Lymph Node Stage 1 .8 Stage 1 - LN Neg .6 .4 Stage 2 - Up to 3 low axillary LN +, or internal mammary LN + alone .2 Chi-Square 553.146 0 0 48 0 Stage 3: 4 or more axillary LN +, apical LN +, or low axillary AND internal mammary + DF P-Value 2 <.0001 96 4 144 8 192 12 240 Time 16 20 Time (years) Lymph Node Involvement Sentinel node biopsy Vascular Invasion Prognostic significance Close correlation with loco-regional lymph node status – Rosen et al, 1983; Davis et al, 1985; Orbo et al, 1990; Pinder et al, 1994; Yiangou et al, 1999 Correlates with early recurrence in lymph node negative patients – Rosen et al, 1983; Bettelheim et al, 1984; Neville et al, 1992 Vascular Invasion Prognostic significance Predicts for long term survival, independent of nodal status Roses et al, 1982; Pinder et al, 1994 Predicts for local recurrence following breast conserving surgery Fourquet et al, 1989; Borger et al, 1994; Pinder et al, 1994; Sundquist et al, 2000 Predicts for local recurrence after mastectomy O’Rourke et al, 1994; Sundquist et al, 2000 Progress to systemic metastatic disease • • • • • • 173 women who developed metastatic disease after a previous breast cancer. 72% had nodal metastases 59% had definite vascular invasion 84% had either lymph node metastases or vascular invasion or both. Consistently present whatever the histological grade of the primary tumour. Absence of VI and nodal involvement indicated a low risk of subsequent metastatic disease. (Evans 2001) LVI contribution and nodal status contribution to hazard Cumulative Proportion Surviving (Kaplan-Meier) Complete Censored 1.0 LVI+ TWO P =0.511 P =0.920 LN- 0.9 Cumulative Proportion Surviving ONE LVI+ LN- 0.8 ONE 0.7 TWO 0.6 0.5 0.4 0.3 0.2 0.1 0 40 20 80 60 120 100 160 140 Time 200 180 240 220 280 260 300 LVInegLNneg LVIposLNneg one two three fourplus P =0.563 Prognostic Factor: Altered natural history Predictive Factor: Resistance or sensitivity to therapy Predictive assays Luminal / ER +ve ER PR HER 2 Overexpression HER2 protein Gene amplification Basal “Triple negative” Gene expression Basal phenotype CK’s, EGFR ER Immunohistology Cut off points for treatment Score treatment Effect of Endocrine 0 2–3 4–6 7–8 No effect Small (20%) chance Even (50%) chance Good (75%) chance Leake et al. J Clin Path 2000; 53: 634-635 Herceptin ® humanised anti-HER2 monoclonal antibody Her-2 status 0 Normal 1+ Normal 2+ 3+ Low amplification High amplification IHC Images courtesy of MJ Kornstein, MD, Medical College of Virginia Breast cancer is heterogeneous The goal is… Move away from “one size fits all” strategy ? individualize therapy … to tailor treatment ER/PR - important in breast cancer biology & treatment selection • ER/PR are key markers to classify subtypes of breast cancer with different treatment needs (St. Gallen 2005) Phenotype Incidence (%) Response to Tamoxifen (%) ER+/PR+ 58 77 ER+/PR– 23 27 ER–/PR+ 4 46 ER–/PR– 15 11 Allred et al. Mod Pathol 1998;11:155-168 Goldhirsch et al. Ann Oncol 2005;16:1569-1583 ER/PR status defines different treatment needs in breast cancer Endocrine non-responsive Negative Endocrine Response Uncertain Low Positive Endocrine Responsive Positive Chemotherapy alone No benefit from endocrine therapy Endocrine therapy benefit from adding chemotherapy Endocrine therapy alone Less benefit from chemotherapy ER/PR status defines different treatment needs in breast cancer Endocrine responsive* Basic Definition Additional Features Main Therapy Strong ER expression Some PR expression Endocrine Therapy Endocrine Therapy (upfront AI**?) with possible chemotherapy and Herceptin depending on risk level & menopausal status Chemotherapy Endocrine Response Uncertain* Low ER expression No detectable PR expression or HER2 overexpression Endocrine Non-Responsive No detectable ER or PR expression – •Exact boundary between “endocrine responsive” and “endocrine response uncertain” is undecided ** Aromatase Inhibitor •Adapted from AdjuvantOnline.com and Goldhirsch et al. Ann Oncol 2005;16:1569-1583 Oestrogen Receptor (ER): Run 65 IDC: 90 –95% Intensity: High IDC: 50 –75% Intensity: Medium Slide courtesy of Merdol Ibraham, UK NEQAS IDC: 0% Intensity: Negative NEQAS RUN 65 ‘ER’ Results UK NEQAS Sections Scores >12/20 116 (36%) Scores 10-12/20 77 (23%) Scores <10/20 132 (41%) 'In House' Sections Scores > 12/20 253(78%) Scores 10-12/20 53(17%) Scores <10/20 17( 5%) ANTIGEN RETRIEVAL: main factor responsible for weak staining (Rhodes et al Am J Clin Pathol 2001; 115: 44–58) Slide courtesy of Merdol Ibraham, UK NEQAS Effective Feedback = Better Performance ER pass rates 2003-2006 2003 Slide courtesy of Merdol Ibraham, UK NEQAS 2006 ER/PR immunohistochemical results are variable from lab to lab ER false-negative results (n=172 labs) strongly ER-positive cases moderately ER-positive cases weakly ER-positive cases 2000 5% 28% 44% 2002 7% 14% 29% von Wasielewski et al. Am J Clin Pathol 2002;118:675-682 • Main reason for false-negative results: inefficient heat-induced epitope retrieval • Further reasons for variability: diverse primary antibodies, dilutions, incubation temp/time, detection systems, methods of scoring, arbitrary definition of positivity (cutpoint), reporting of results ER/PR immunohistochemical results variable from lab to lab Variable PR immunostaining using different PR antibodies on a strongly PR-positive breast carcinoma. Press et al. Steroids 2002;67:799-813 No. Participants using a Specific PR Clone: Run 75 46% 15% 11% Allred Score clinically validated Her-2 status 0 Normal 1+ Normal 2+ 3+ Low amplification High amplification IHC Images courtesy of MJ Kornstein, MD, Medical College of Virginia Negative Low positive No endocrine treatment? Positive Add chemotherapy? too low sensitivity and/or too high cutpoint ‘False-negativity’ Negative Low positive Endocrine treatment? Positive No chemotherapy? too high sensitivity and/or too low cutpoint ‘False-positivity’ Clinical validation means demonstration of… • Assay sensitivity • Assay specificity • Stability of reagents, no lot-to-lot variability • Assay reproducibility • Assay robustness • Concordance between assay versus reference method* • Correlation with patients’ clinical outcome (therapeutic response and/or prognosis) Clinical usefulness * eg. Herceptin Clinical Trial Assay (HER2), Allred Procedure (ER, PR), ligand binding assay (ER, PR), FISH (HER2) Personalised treatment of breast cancer • Breast cancer is a heterogeneous disease. • Accurate and reproducible measurement of ER, PR and HER2 expression is critical for optimal care of breast cancer patients. • Validated standardised assays are required to correctly classify breast cancer and optimize treatment efficacy and safety. Predictive assays ER & PR Presence of target protein HER 2 Presence and overexpression TP Gene amplification EGFR ? Target protein ? Gene copy number ? Gene mutation Leake et al. J Clin Path 2000; 53: 634-635 Future Classification of Breast Cancer Emerging classification system with clinical relevance based on: morphology phenotype molecular genetics Routine provision of prognostic and predictive information Identification of key therapeutic targets Linked development of theranostics with drug development Future Classification of Breast Cancer Translation of research techniques / methods to routine clinical practice Robust validated & standardised routine methods Quality assurance integrated into service provision Pathology has a central role - analytical & coordination “From inability to let well alone; from too much zeal for the new and contempt for what is old: from putting knowledge before wisdom, science before art, and cleverness before common sense, from treating patients as cases, and from making the cure of the disease more grievous than the endurance of the same, Good Lord, deliver us” Robert Hutchison (BMJ 1953: I : 671)