1. Current state of breast cancer classification Marcella Mottolese UOC Anatomia Patologica

2. screening programs and adjuvant therapy changed the management of breast cancer impact in outcome with a decrease in mortality in most of the western world despite increasing breast cancer incidence

3. ? OPEN QUESTIONS ? How to predict the response to currently available cytotoxic chemotherapy ? How to identify tumor targets for directed therapies? How to identify patients with node negative disease at very low risk of relapse for whom the risk/benefit ratio might be in favour of chemotherapy?

4. Response to the adjuvant chemotherapy, mainly in early stage of the disease, are affected by a complex interplay of factors

5. Prognostic factors in breast cancer

6. Biomarkers Categories 1. Those that predict relapse or progression independent of future treatment effects designate as PROGNOSTIC FACTORS 2. Those that predict response or resistance to a specific therapy designate as PREDICTIVE FACTORS

7. Routinely used clinico-pathological parameters Age tumor Size lymph nodes lympho-vascular invasion ER, PR; HER2; Ki67 Tumor grade Clinico-pathological (tumor burden) Biological (intrinsic chacteristics)

8. Are these routinely used parameters sufficient for individualized therapy NO, because Brest Cancer is HETEROGENEOUS ClinicallyBiologically

9. This clinical heterogeneity is driven by the genetic variability of patients and tumors A continuum of abnormal gene expression predicts: the tumorigenic phenotype the sensitivity of tumors to treatment

10. Clinical tools

11. St Gallen 2009 : news and progress INTEGRATING MOLECULAR AND OTHER PATHOLOGICAL FEATURES Genetic predisposition Whole-genome studies Stem cells microRNAs Networks in cellular system Circulating tumor cells Angiogenesis Pharmacogenetics Resistance to treatment by crosstalk Multigene assays

12. St. Gallen 2009 Endocrine Responsive (ER ≥ 1%) Endocrine Non-Responsive (ER = <1%) HER2-Endocrine Therapy (± CT using suggested criteria) CT HER2+Endocrine Therapy + Trastuzumab + CT Trastuzumab + CT

13. St Gallen 2011 Focus on the identification of “tumor subtypes” to plan therapy more accurately Morphological evaluation of special histological types Immunohistochemical characterization as molecular classification surrogate Tumor Subtypes defined starting from molecular classification

14. Biology-driven trials Andre F et al 2011 JCO

15. How can molecular tools help standard pathology? Standardization, reproducibility & qualification Molecular sub-grouping Prognosis/Stratification Predictive markers Functional pathway read-outs

16. Molecular sub-grouping

17. ….very distinct gene expression patterns irrespective of stage (size, nodal, status) !

18. Sotiriou C, Pusztai L. N Engl J Med 2009;360:790-800

19. ‘Subtype’ Surrogate IHC markers Type of therapyNotes Luminal A ER and/or PgR + /HER2 -, Ki-67 <14% Endocrine therapy alone Few require CT (e.g. high nodal status). Luminal B (HER2 -) ER and/or PgR +/HER2-, Ki-67>14% CT + endocrine therapy Inclusion and type of CT may depend on perceived risk and patient preference. Luminal B (HER2 +) ER and/or PgR +/HER2 + CT + anti-HER2 + endocrine therapy No data are available to support the omission of CT in this group. HER2 + (non luminal) CT + anti-HER2 Triple negative (ductal)CT Consider DNA disrupting agents. ‘Special histological types’ A. Endocrine responsive B. Endocrine non responsive Endocrine therapy CT Medullary and adenoid cystic carcinomas may not require any adjuvant CT. St Gallen 2011

20. Ki67 (IHC) British Journal of Cancer (2007)

21. Ki-67 prognostic cut-off point for all breast cancer subtypes (multivariate analysis) The best cut-off point with the lowest p-value and highest HR was found at the Ki-67 index of 20%

22. Clinically, the majority of claudin-low tumors : are triple negative invasive ductal carcinomas with a high frequency of metaplastic and medullary differentiation. have a response rate to standard preoperative chemotherapy intermediate between that of basal-like and luminal tumors. resembles the mammary epithelial stem cell. Claudin-low breast cancer are characterized by: low to absent expression of luminal differentiation markers, high enrichment for epithelial-to-mesenchymal transition markers, immune response genes and cancer stem cell like features.

23. Prognosis/stratification

24. Breast cancer should be considered according to Hormonal Receptor, HER2, Ki-67 Distinct Clinical outcome

25. Disease free survival according to molecular subtype in 1015 breast cancer patients treated at IRE between 2000-2006 P-value (log-rank test) <0,0001

26. S Borgquist J Clin Pathol 2008;61:197-203 Estrogen receptors α and β show different associations to clinicopathological parameters and their co-expression might predict a better response to endocrine treatment in breast cancer

27. 934 prospective breast cancer patients

28. To replace or to complement the traditional biological parameters?  This may be highly misleading, because the molecular classes are heterogeneous and encompass different tumor types with different risk profiles and different responsiveness to the therapy

29. Not all the tumors with the basal-like profile are high risk tumors. This molecular class also includes: low-grade metaplastic carcinomas adenoid-cystic carcinomas, medullary carcinomas low grade apocrine carcinomas Heterogeneity may be evident in breast cancer with basal-like profile since: which have a very favorable prognosis

30. Predictive markers

31. ER and HER2 Breast Cancer HER-2 neuER Negative predictive value Positive predictive value HIGH 95% 30-50 % (<5% change to respond to anti- estrogens or trastuzumab)

32. a b 30μ ab 10 μ c d b

33. What about gene Expression signatures ?

34. The Role of Single Gene Analyses and Multigene Assays in Addressing the Controversy on Chemotherapy or Not when Stage/Biology are Discordant High Risk Relative Endocrine “Resistance ” Relative Chemo “Sensitivity” 21 Gene recurrence Score (RS) 70 Gene

35. Three Strategies for the Development of a Gene-Expression Prognostic Signature 1. “top-down” approach: 1. “top-down” approach: gene- expression data from patients with known clinical outcomes are compared to identify genes that are associated with prognosis without any a priori biologic assumption. 2. “bottom-up” approach: 2. “bottom-up” approach: gene- expression patterns associated with a specific biologic phenotype or a deregulated molecular pathway are first identified and then correlated with the clinical outcome. 3. candidate-gene approach: 3. candidate-gene approach: selected genes of interest on the basis of existing biologic knowledge are combined into a multivariate predictive model.

37. Summary of multi-parametric tests for breast cancer

38. Ongoing RCT’s of prediction of chemotherapy by multi-parameter assays

39. 21 gene Recurrence Score Assay: Strongly Predictive in NSABP B-20 (ER+No)

40. Mammaprint TM adds prognostic information in pT 1 tumors N=965 patients wit T 1a,b,c tumors; adjuvant systemic treatment in 41%; median 7 years Distant Metastasis-Free Survival PT 1ab PT 1c

41. T 1A, B N o M o: ONCOTYPE DX and MAMMAPRINT TM prolifiles

42. 1 st generation signatures add prognostic information to current “best”clinical tools

43. Breast Cancer Gene Expression Signatures and Cell proliferation 70 gene signature van’t Veer et al,200270 Cell cycle, angiogenesis, invasion and metastasis 76 gene signature Wang et al, 200576 Cell cycle, proliferation, DNA repair, immune response and apoptosis OncotypeDX RS Paik et al, 200416 Proliferation, ER and HER2 invasion Genomic grade index Sotiriou et al, 200697 Cell cycle and proliferation

44. 44

45. Learning about adverse biological features of T 1a, b N o M o breast cancers

46. 46

47. 47 Stromal Subtypes are Associated with Outcome Stromal Gene Expression Identifies Distinct Tumor Subclasses Epithelia Stroma Stromal Clusters Reflect Different Microenvironments

48. 48 The tumor microenviroment plays a key role in tumor progression Better understanding of intra-tumor diversity and epithelial- stromal cell interactions will lead to more efficacious cancer treatment

49. Functional Pathway

50. PI3K pathway gene signatures Best way to develop these signatures

51. PIK3CA mutations produce characteristic change in gene expression The mutant and the associated gene signature were associated with a good prognosis in TAM- treated ER+/HER2-BC Loi et al, PNAS 2010 A PIK3CA-GS developed from PIK3CA mutant ER+breast cancers

52. Unfavourable Biologic Profile (UBP≥3 ABF) versus Favourable Biologic Profile (FBP<3 ABF) 121 breast cancer patients CMF treated Novelli F, Mottolese M SABCS 2009 P-AKTPI3KKi-67HER2

53. A gene signatures may be useful as a functional read-out of pathway activity TAKE MESSAGES Gene signatures will probably be most useful in combination with genotype, ER, HER2, Ki-67 All predictive gene signatures need clinical validation in appropriate clinical trials