1. The 70 gene Mammaprint ™ signature: a comparison with traditional clinico-pathological parameters. Patrizia Querzoli 1, Massimo Pedriali 1, Gardenia Munerato 1, Maria Lunardi 1, Giulia Querzoli 1, Paolo Carcoforo 2, Maria Isabel Carbonell Luna 3, Francesco Pellegrini 3, Pamela Pizzutilo 4, Monica Indelli 4, Enzo Durante 3, Italo Nenci 1 1: Section of Anatomic Pathology, Ferrara University; 2: Section of General Surgery, Ferrara University; 3: Breast Surgery, Ferrara University; 4:Clinical Oncology Unit, Az.Ospedaliero-Universitaria, S.Anna Hospital, Ferrara

2. BACKGROUND: Currently, the selection of patients for adjuvant treatment is based on patients and tumor characteristics such as age, menopausal status, tumor size, grade, nodal status and endocrine responsiveness. The pathologist is increasingly engaged in testing biomarkers that provide prognostic and predictive information to direct treatment in breast cancer patients. The 70 gene signature (MammaPrint™) is validated as an independent prognostic indicator for patients pN0 and pN+; moreover may be clinically more useful for prediction in endocrine responsive cancer to assign adjuvant-therapy 1,2,3,4. Gene Profiling Biopathological Characterization

3. METHODS: Our study involves 73 patients (aged 38-88) with invasive breast cancer and submitted to surgical procedure, tested on a biopsy punch of fresh tissue by Mammaprint™ (Agendia) within one hour from surgical excision (figure 1). Tumor biopsy was then placed in RNA later and shipped to Agendia, (NL), where RNA was isolated and hybridized on the 70 gene prognosis signature (figure 2) ; 18 women underwent mastectomy and 55 breast conserving surgery. Every case has already been characterized as follows: pTNM staging, tumoral histotype, histological grade, staging according to NPI (Nottingham Prognostic Index), quantitative evaluation of ER, PR, proliferation activity (Mib1) and HER2 by automatized immunohistochemical techniques (Benchmark XT Ventana) and evaluated by computerized densitometric image analysis (VIAS Ventana). The patients have been stratified for clinico-pathological and molecular class of risk with different tools: NPI, St Gallen guidelines and Adjuvantonline.

4. 3 mm AN PAT UNIFE Figure 1: Sample preparing procedure

5. Figure 3: Sample preparing procedure Figure 2

6. RESULTS: 52 cases were ductal, 7 lobular, 9 special, 5 mixed type. 6 were G1, 49 G2, 18 G3. 52 cancers were pT1, and 21 were pT2. 31 were pN0, 31 pN1 and 11 were pN2. In all cases NPI, ER, PR, Mib1 and HER2 were evaluated (e.g.1a ; ER+: 70; PR+ 56; High proliferation activity: 43; 0/1+/2+ Her2: 64). Applying St.Gallen criteria 6,8% of patients were low risk, 74% intermediate, and 19,2% high risk. Among the 73 patients 33 had a good prognosis-signature, whereas 40 had a poor prognosis-signature (e.g 1b; in e.g.1a and e.g.1b we report the biological and molecular profile of the same case ). At univariate analysis we detect a correlation between the age at diagnosis and the 70 gene prognostic profile (47,5% patients <60yrs/poor prognosis vs 24,2% patients <60 yrs/good prognosis, p=0,018), a direct correlation with histological grade (42,5% poor prognosis/G3 vs 3%poor prognosis/G3, p<0,0001) and with proliferation index (measured by Mib1) (80%high proliferation index/poor prognosis vs 33,3% high proliferation index/poor prognosis, p<0,0001). We also detect a direct correlation between Mammaprint™ evaluation of the risk and St. Gallen Criteria (p=0,038) [Table 1]. Changing categories by Mammaprint: 8 good prognosis NPI: High Risk Mammaprint; 14 intermediate NPI: Low Risk Mammaprint and 20 intermediate NPI: High Risk Mammaprint; 6 High Risk St.Gallen: Low Risk Mammaprint. According to Adjuvantonline 33,8% were low risk. Mammaprint identified a number of low risk cases higher than Adjuvantonline (45,2%). [Table 2 and Table 3]

7. E.g. 1a

8. E.g. 1b

9. Table1 Association between clinical-pathological characteristics and the 70 gene prognosis-signature (Mammaprint ™)

10. Comparison between different risk evaluations Table 2

11. Table 3: cases class risk distribution between different tools.

12. CONCLUSIONS: The gene signatures integrated in clinical practice could help oncologists to optimize clinical management decisions. Mammaprint could help to reduce such uncertainty, also because it seems to be predictive for chemotherapy benefit. Today’s pathologist plays a traditional but also emerging roles in risk assessment, diagnosis, staging and management of patients. REFERENCES: 1. van’t Veer LJ et al., Nature 2002 415(6871):530-536 2. van de Vijver MJ et al., N Engl J Med 2002 347(25):1999-2009 3. Knauer M et al., Abstract 31st Annual San Antonio Breast Cancer Symposium 2008 4. Knauer M et al., Abstract St Gallen Conference 2009