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Current concepts in Breast Cancer- Beyond TNM

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1 Current concepts in Breast Cancer- Beyond TNM
Professor Ravi Kant FRCS (England), FRCS (Ireland), FRCS (Edinburgh), FRCS(Glasgow), MS, DNB, FAMS, FACS, FICS, Professor of Surgery

2 Applications of Genes Assay in CA Breast
To subclassify breast cancer To estimate prognosis To predict response to therapy

3 Applications of Genes Assay in CA Breast
To subclassify breast cancer To estimate prognosis To predict response to therapy

4 Gene Expression Patterns of Breast Carcinomas Distinguish Tumor Subclasses With Clinical Implications PNAS 2001;98;

5

6 Molecular classification & Prognosis:
Luminal A= Best prognosis Luminal B Luminal C Normal breast like Her 2+ Basal like= Worst= Triple Negative

7 Subtype ER +, Best overall survival, Best DFS Type Importance
Luminal A ER +, Best overall survival, Best DFS Luminal B ER,Her2+,Intermediate Her 2 +ve ER-, Intermediate Basal like ER-,PR-, Her2 - Worst

8 IHC profiles for the breast cancer subtypes
Basal-like: (ER−, PR−, HER2−, cytokeratin 5/6+, and/or HER1+). HER2+/ER− subtype (HER2+, ER−, PR−). luminal A (ER+and/or PR+, HER2−). luminal B (ER+and/or PR+, HER2+).

9 Tumor based Gene assay Mammaprint (Amsterdam) Oncotype Dx 76 gene
Test # of Genes Tissue Mammaprint (Amsterdam) 70 Fresh Oncotype Dx 21 Fixed 76 gene 76 Wound response Two gene ratio 2 Intrinsic subtype

10 Tumor based Gene assay Mammaprint 70
Test Aim Mammaprint 70 To predict risk of distant mets in N-, To identify who will benefit from Chemo Oncotype Dx 21 To identify N-, ER+ who will benefit by addition of Chemo to Tamoxifen 76 gene 76 To predict DFS & OS in N-, early stage Wound response To predict risk of mets & death Two gene ratio 2 Intrinsic subtype To predict clinical outcome

11 Tumor based Gene assay Oncotype Dx 21
Test Aim Mammaprint 70 To predict risk of distant mets in N-, To identify who will benefit from Chemo Oncotype Dx 21 To identify N-, ER+ who will benefit by addition of Chemo to Tamoxifen 76 gene 76 To predict DFS & OS in N-, early stage Wound response To predict risk of mets & death Two gene ratio 2 Intrinsic subtype To predict clinical outcome

12 MammaPrint • 70 gene classifier developed further by the company Agendia ( under the name MammaPrint. • MammaPrint was approved by the FDA in February 2007 for node negative women under 61 years of age and with a tumor < 5cm.

13 Tumor based Gene assay 76 gene 76
Test Aim Mammaprint 70 To predict risk of distant mets in N-, To identify who will benefit from Chemo Oncotype Dx 21 To identify N-, ER+ who will benefit by addition of Chemo to Tamoxifen 76 gene 76 To predict DFS & OS in N-, early stage Wound response To predict risk of mets & death Two gene ratio 2 Intrinsic subtype To predict clinical outcome

14 Tumor based Gene assay Wound response To predict risk of mets & death
Test Aim Mammaprint 70 To predict risk of distant mets in N-, To identify who will benefit from Chemo Oncotype Dx 21 To identify N-, ER+ who will benefit by addition of Chemo to Tamoxifen 76 gene 76 To predict DFS & OS in N-, early stage Wound response To predict risk of mets & death Two gene ratio 2 Intrinsic subtype To predict clinical outcome

15 Tumor based Gene assay Two gene ratio 2 Test Aim Mammaprint 70
To predict risk of distant mets in N-, To identify who will benefit from Chemo Oncotype Dx 21 To identify N-, ER+ who will benefit by addition of Chemo to Tamoxifen 76 gene 76 To predict DFS & OS in N-, early stage Wound response To predict risk of mets & death Two gene ratio 2 Intrinsic subtype To predict clinical outcome

16 Tumor based Gene assay Intrinsic subtype To predict clinical outcome
Test Aim Mammaprint 70 To predict risk of distant mets in N-, To identify who will benefit from Chemo Oncotype Dx 21 To identify N-, ER+ who will benefit by addition of Chemo to Tamoxifen 76 gene 76 To predict DFS & OS in N-, early stage Wound response To predict risk of mets & death Two gene ratio 2 Intrinsic subtype To predict clinical outcome

17 Applications of Genes Assay in CA Breast
To subclassify breast cancer To estimate prognosis/ prediction To predict response to therapy

18 Conventional classification
Convential Classification assumes that women with a tumor bigger than 2 cm have a high risk to develop distant metastasis.

19 Size is an insufficient indiactor of metastasis risk
Molecular studies shows that size alone is not an indicator of high or low metastasis risk. Small and large tumors can be either low or high risk as determined by Molecular studies Molecular classification

20 Molecular studies provides additional data to assess the risk of distant metastasis
classification

21 MammaPrint Discovers 34% Low Risk Patients in Adjuvant! High-Risk Group
87% MammaPrint Low Risk MammaPrint High Risk N = 209 n = 137 66% Looking at the 209 patients characterized as High Risk by Adjuvant On-line, MammaPrint identifies 72 patients, or 34% which would be re-characterized as Low Risk n = 72 34% Patients re-characterized as Low-Risk MammaPrint: 34% Buyse et al., Journal of the National Cancer Institute. 2006;98(17):

22 Gene Assay prediction > Adjuvant Online
Buyse M. Validation and clinical utility of 70 gene prognostic signatures for women with node negative breast cancer. J Natl Cancer Inst 2006;98:

23 Different proportion of low and high risk patients
MammaPrint profiles accurately 40% as low risk compared to only 15% with St. Gallen criteria.

24 MammaPrint identifies correctly

25 MammaPrint identifies correctly
40% of patients with low risk in comparison to the 15% that are identified with conventional methods, thus preventing many unnecessary chemotherapies. More precise in predicting the outcome of disease than St. Gallen when comparing survival rates.

26 Mets free / Survival

27 LN + or -

28

29 Gene Expression vs. Clinical

30 St Gallen vs NIH

31

32

33 TRANSBIG Validation: 302 Patients, Node-Neg, T1/2, Age < 61
Amsterdam Gene expression profiling Agilent platform 70-gene prognostic custom designed chip RNA Target n=400 Achieved n=307 High or Low Gene Signature Risk Tissue Samples UK (Guy’s, Oxford) 1984 – 1996 France (IGR, CRH) 1978 – 1998 Sweden (Karolinska) 1980 – 1990 Node negative, untreated <60 years > 5 years follow-up T1, T2 Tumor cell % > 50% Brussels Comparison of clinical v gene signature assessment of prognostic risk Endpoints Time to Distant Metastasis Overall Survival Distant Metastasis-Free Survival, Disease-Free Survival This is an overview of Agendia’s TRANSBIG multi-center validation study which is the second study that demonstrated the clinical utility of using MammaPrint to identify patients at risk of distant recurrence and which formed the basis for the FDA approval language (97% overall survival Low Risk vs. 65% High Risk, and 90% mets free Low Risk vs. 71% High Risk at 10 years). Hazard Ratios of 2.79 for overall survival, and 2.32 for time to distant mets. Audited clinical data Centrally reviewed path data (Milan) <<local>> pathological data Clinical Data Buyse et al., Journal of the National Cancer Institute. 2006;98(17): 33

34 Three step validation strategy
Independent validation study on archival material N300 Agendia 70-gene prognostic signature N=78 N=151 Prospective clinical trial specifically addressing the gene signature’s utility N6000 Level 1 The signature is robust The technology is reproducible Level 5 and 4 Level 2-3 Levels of evidence for biomarkers studies

35 MammaPrint® identifies early metastases risk with highest accuracy
29% 39% 50% 62% 75% 83% 96% 100% 4.52 7.54 4.68 3.24 3.5 9.14 2.13 2.33 2 3 4 5 7 10 15 none Censoring time (in years) 0.1 1 Adjusted hazard ratio for gene signature Cumulative proportion of events Time to distant metastasis HR: all endpoints strongest in first 5 years after diagnosis MammaPrint’s ability to assign risk of distant recurrence in the first 5 years following treatment is shown here with the hazard ratios being extremely high during this initial period, and thus extremely accurate at predicting an event. As most recurrences develop in the first 5 years post treatment, a profile with the highest hazard ratios in that period attests to its power as a prognostic tool. Buyse et al., Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer, Journal of the National Cancer Institute, Vol 98, No. 17, 2006

36 FDA Clearance of MammaPrint®
Study Purpose Details Comments 1 Nature Development 70-gene profile patients, LN0, <55yrs 6.4% adjuvant treatment Within 5 year metastasis risk by profile multivariate OR 18 2 NEJM Validation 70-gene profile patients 5.2% adjuvant treatment Metastasis-free at 10 yrs: low risk 87%,high risk: 44% 5 yrs: low risk 93%,high risk 56% 3 MammaPrint Development MammaPrint 2006 reproducibility of (1) and (2) on MammaPrint Highly reproducible MammaPrint as a diagnostic tool 4 TRANSBIG Independent European validation patients no adjuvant treatment Metastasis-free at 10 yrs: low risk 88%,high risk: 71% 5 yrs: low risk 96%,high risk 83% MammaPrint was developed and validated in several different studies that have been published in the following journals. The MammaPrint result generates a result that is either Low Risk or High Risk of distant recurrence at 10 years. The FDA cleared patient population is Stage I or II, ER+ or ER-, node-, and less than 61 years old. Agendia has submitted clearance to add patients 61 years and older. None of the patients in the studies had been treated with any form of adjuvant chemotherapy, giving a true natural biology of the patient’s tumor aggressiveness and your ability to use any form of hormonal or chemo therapy available. 36

37 TRANSBIG, the Translational Research Network of the Breast International Group (BIG), conducted an
independent validation study of both the Amsterdam and Rotterdam gene signatures in a series of 302 patients Although there was only a 3-gene overlap between the two signatures, both were validated on the same patient cohort

38 So time to learn basics again

39

40 MammaPrint interrogates critical genomic pathways
MammaPrint interrogates all of the critical genomic pathways associated with tumor progression and the metastatic cascade Catabolism and tumor hypoxia related metabolism Cell cycle and cytoskeleton related biogenesis Extracellular matrix adhesion and remodeling General signal transduction and intracellular transport Growth factor Immune response Cellular mobility or actin filament related We are all aware of Weingberg’s Criteria for Malignancy or Metastasis which is shown here. As you will see in the next slide, it is important to capture as many of these pathways as possible in the analysis of the tumor to provide the most accurate assessment of metastasis potential.

41 Applications of Genes Assay in CA Breast
To subclassify breast cancer To estimate prognosis/ prediction To predict response to therapy 41

42

43 71 Gene assay predictive value
Van de Vijver MJ,He YD, van’t Veer IJ, et al. A gene expression signature as predictor of survival in breast cancer. Amsterdam N Engl J Med 2002; 347:

44 Oncotype Dx-21 gene predictive value
Palk S, Tang G, Shak S et al. Gene expression and benefit of chemotherapy in women with node negative, ER + breast cancer. J Clin Oncol 2006;24: Can be done on fixed tissue.

45 21 gene analysis-Oncotype Dx
Independent of Tumor size Age Park S. NEMJ 2004;351: > Accurate than Adjuvant Online Goldstein RP. Abstract #63. San Antonio 2007

46 21 gene analysis can predict
breast cancer related mortality Habel LA. Breast Cancer Res 2006 NSABP- B14 trial

47 21 gene Predictive value

48 Newer prognostic Indicators
Wound response gene– risk of mets and death 2 gene recurrence score –adding chemotherapy to tamoxifen in ER+ ve, N- ve Chang HY . Gene signature of fibroblast serum predicts cancer progression:similAarities between tumors and wound. PloS Biol 2004; 2:

49 Wound response gene expression profile
Activation of fibroblasts Active wound healing predicts ▲ risk of metastases Death ( in Breast, Lung & Gastric cancer) Cong HY. PLoS Biol 2004;2:206-14

50 2 gene expression profile
60, ER+, Early stage (MaXJ.Cancer Cell 2004) Expression of Homeobox 13 IL-17B ▲ ratio= poor outcome ≡Tamoxifen alone will not do in such patients

51 Six models All are different
Great concordance in five out of six gene expression profile models 21 gene (Oncotype Dx) and 70 gene (Mammaprint) are popular 81% concordance between 21 & 70 gene. Perou, Fan C. NEMJ 2006

52 Breast Cancer: The Treatment Dilemma
Choices of 40 experts world-wide 61 y-old, fit, postmenopausal Node negative pT = 0.9 cm ductal cancer ER and PR negative HER2 negative Grade 2 Courtesy: Martine Piccart

53 Of 100 women with breast cancer
53

54 Only 25% will develop distant metastases
54

55 But we treat over 75% of all patients
with chemotherapy 55

56 Which means that 50% of all breast cancer patients get a toxic chemotherapy that they did not need!
56

57 Applications of Genes Assay in CA Breast
To subclassify breast cancer To estimate prognosis To predict response to therapy

58 To predict response to therapy
Selection of the therapy based on attributes of the Tumor Host

59 21 gene analysis can predict
Responsiveness to Chemo/ Hormone Gianni L. J Clin Oncol.2005 Palk S. J Clin Oncol 2006;24: NSABP- B14 trial

60 TAILORx = Trial Assigning Individualized Options for Treatment

61 TAILORx trial LN-, HER-, ER+ HRx HRx+ / - Chemo Chemo ►HRx Oncotype Dx

62 MINDACT study design 55% 10% 35% BOTH HIGH RISK DISCORDANT RISK
6000 patients, <70 YRS, 1-3 POS NODES ASSESS clinical RISK AND MammaPrint RISK (adjuvant!online & MammaPrint) 55% 10% 35% BOTH HIGH RISK DISCORDANT RISK BOTH LOW RISK RANDOMIZE decision-making Use clinical risk Use MammaPrint high low high low Chemotherapy No chemotherapy

63 MINDACT Microarray in Node Negative Disease may avoid Chemo
LN- 70 gene assay & adjuvant online Low risk HRx if Er+ Discordant Chemo or HRx High risk Chemo + HRx

64 Her2 positive MammaPrint low risk patients have an excellent survival
Knauer SABCC 2008

65 Benefit of adjuvant chemotherapy in MammaPrint high risk patients
88% Endocrine & Chemo (n= 265) benefit 69% Endocrine (n=184) HR 0.28 ( ; p=0<0.001) MammaPrint low risk (n=126) HR 1.99 ( ; p=non significant) Distant metastasis-free survival (years) Median Follow-up 5.2 years Knauer et al, 2008 unpublished

66 To predict response to therapy
Selection of the therapy based on attributes of the Tumor Host

67 To predict response to therapy based on attributes of the host
Drugs metabolized by CYP450 encoded enzymes CYP 2 CYP 3 CYP2D6 CYP2C19

68 To predict response to therapy based on attributes of the host
Drugs metabolized AmpliChip CYP450 by Roche

69 Prognostic Signature and Clinical Benefit
-the chemotherapy choice- MammaPrint prognosis signature Assigns patients to risk categories with high specificity and sensitivity (low risk vs high risk for recurrence) Low risk sufficiently low to forego chemotherapy High risk identifies patients with early relapse and shows chemo benefit (predictiveness) 69 69

70 Clinical applications of microarrays
Who to treat: Prognosis profiles as diagnostic tool -> improved selection for adjuvant therapy How to treat: Predictive profiles for drug response -> selection of patients who will benefit most WHO NEEDS THERAPY? WHICH THERAPY WILL WORK BEST? Prognostic factors Predictive factors

71 What does “low risk” mean?
MammaPrint® “Low Risk”: 90% metastasis-free without any adjuvant treatment over the following 10 years (NEJM 2002/JNCI 2006) Most of the “Low Risk” patients are ER+ With ER+ patients receiving hormonal therapy, a further 50% risk reduction can be achieved in the “Low Risk” group, thus MammaPrint “Low Risk” means >95% 10 year metastasis-free survival The cut-off point chosen in the development study was based on having only 10% of the patients having a recurrence in the Low Risk group (3 out of 34). Again this is with no hormonal therapy, so with the addition of hormonal therapy, and an assumed benefit of approximately 50%, the low-risk patients are more in the ~5% risk of distant recurrence at 10 years and you should feel confident this is an extremely Low Risk patient. MammaPrint does not have an intermediate group with as patients in the studies that were classified as High Risk, had a risk of distant recurrence of 30%-50% (~20 patients out of 40 had a recurrence in the development study).

72 Summary : Poor risk Basal like Luminal B HER2+/ER-
Poor 70 gene profile High 21 gene recurrence score Activated wound response

73 Summary : New Decision aid
21 gene (Oncotype Dx) & 70 gene (Mammaprint) is better than Adjuvant Online Personalised treatment Less toxicity, less cost

74 Contrast of Appearance vs. Expression Phenotyping
Microscope Low Grade High Grade Treatment Advice The Microscope is used to review an H&E for grading purposes however studies have shown significant discordance especially in the stage 2 grade. Today’s latest technologies for staging using molecular diagnostic tools include DNA Microarrays and RT-PCR. Microarray Low Risk High Risk

75 Triple Negative ER-, PR-, and HER2 – Basal like on gene profiling
Adverse prognosis → new Rx

76 Thanks


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