1. Laura J. Van ‘t Veer Helen Diller Family Comprehensive Cancer Center University of California, San Francisco Biology of disease Who is at risk for what type of breast cancer and how does type affect outcome BOP breast course Nov 2010

2. Kaplan-Meier Survival Curves Who gets what type of breast cancer? Which breast cancers return? Breast Cancer - Survival

3. Disease Biology Genetic make-up of individual Biology of screen-detected cancers and of interval cancers Biology informs need for systemic treatment - who is at risk for what type of disease - does type affect outcome - how can type of detection inform management

4. Who is at risk for what type of disease Opportunities for prevention Opportunities for management

5. rs numberGeneChromo- some MAFPer allele OR P (trend test) rs1045485CASP82q0.130.881.1 x 10 –7 rs2981582FGFR210q0.381.232.0 x 10 –76 rs1219648FGFR210q0.391.321.1 x 10 –10 rs109416795p120.241.192.9 x 10 –11 rs3803662TNRC916q0.251.2010 –36 0.271.285 x 10 –19 rs133870422q340.501.201.3 x 10 –13 rs132816158q240.401.085 x 10 –12 rs889312MAP3K15p0.281.137 x 10 –20 rs3817198LSP111p0.301.073 x 10 –9 Familial aggregation of breast cancer 5%(?) CHEK2 1100delC* Multiple low-penetrance alleles (polygenic model) 25% BRCA1/2 4.7% SNPs Breast cancer susceptibility loci

6. rs numberGeneChromo- some MAFPer allele OR P (trend test) rs1045485CASP82q0.130.881.1 x 10 –7 rs2981582FGFR210q0.381.232.0 x 10 –76 rs1219648FGFR210q0.391.321.1 x 10 –10 rs109416795p120.241.192.9 x 10 –11 rs3803662TNRC916q0.251.2010 –36 0.271.285 x 10 –19 rs133870422q350.501.201.3 x 10 –13 rs132816158q240.401.085 x 10 –12 rs889312MAP3K15p0.281.137 x 10 –20 rs3817198LSP111p0.301.073 x 10 –9 Recent breast cancer susceptibility loci - SNPs Easton et al; Cox et al; Stacey et al; Hunter et al

7. Association of 10 susceptibility loci with tumor subtypes Broeks et al, BCAC, submitted Triple negative ER+PR+Her2- ER+PR+Her2+ negative positive association (prevents) (increases)

8. N total = 1370 Breast cancer outcome: Example rs3803662 in TNRC9 Second Breast Cancer Risk Variant allele (homozygous carriers) in BOSOM breast cancer series Adjusted HR (95% CI) 2.7 (1.7-4.3) rs3803662 in TNRC9: increase of contralateral breast cancer risk Ongoing: Validation in BCAC series (studies with follow-up data) Same analyses for other breast cancer risk- related SNPs

9. Breast cancer outcome: MDM2 SNP309 *TP53 R72P MDM2 SNP309 (G = variant allele) GG GT TT TP53 R72P ‘wildtype’ TP53 R72P ‘variant allele’ SNP-SNP interaction effect on survival: MDM2 SNP309 and TP53 R72P variants combined: 7% worse survival (p<0.05) also if adjusted for known prognostic factors Schmidt et al Cancer Res 2007 N total =3739 in BCAC breast cancer series

10. Schmidt et al. JCO 2007 Breast cancer outcome: CHEK2 1100delC Contralateral breast cancer risk HR (95%CI) 2.1 (1.0-4.3) Recurrence-free survival HR (95%CI) 1.7 (1.2-2.4) Breast cancer-specific survival HR (95%CI) 1.4 (1.0-2.1) CHEK2 1100del C carrier: worse breast cancer outcome Treatment interaction? Interaction with SNPs? Tumor characteristics? Ongoing data collection and analyses in BOSOM and pooled BCAC series in BOSOM breast cancer series

11. Biology informs need of systemic treatment Opportunities to reduce over- and under- treatment Effect on morbidity

12. Kaplan-Meier Survival Curves Which breast cancers return? Breast Cancer - Survival

13. Of 100 women with breast cancer (stage 1/2)

14. …………~25% will develop a recurrence

15. ………..75% of all patients is treated with chemotherapy

16. So, overall 50% of patients receive toxic chemotherapy of which they do not benefit, but may suffer the toxic side-effects Can we do better?

17. Tumor samples of known clinical outcome No distant metastases group Unbiased full genome gene expression analysis 70 prognosis genes Tumor samples Distant metastases group Metastases: white=+ Prognosis reporter genes b Development of 70 gene MammaPrint Nature, 2002

18. Multi Gene Expression Profiles in Clinical Practice

19. Clinical Utility MammaPrint Prospective study implementing MammaPrint, 2003-2006 PIs Sabine Linn, Marc van de Vijver Sponsor: Dutch Health Insurance Council Bueno et al, Lancet Oncol, 2007, Knauer et al, SABCS 2008 #1084

20. Discordant cases MammaPrint signature versus Guidelines The Netherlands and Adjuvant-on-line ~30 % discordant cases led in ~20% to adapted treatment advise Bueno et al, Lancet Oncol, 2007, Knauer et al, SABCS 2008 #1084

21. Biology of screen detected cancers Method of detection may inform management

22. US general population screening data from SEER 1973-2005 Age-adjusted incidence breast cancer by Stage at diagnosis Distant In Situ Regional Localized -> Screening era

23. threshold set with 0% false negatives 70 Gene Prognosis Signature Supervised analysis on n=78 tumors, >96% adjuvantly untreated van´t Veer et al., Nature 415, p. 530-536, 2002 70 significant prognosis genes Tumor samples Nature, (2002) threshold 2 ultra-low

24. Biology of Screen-detected Cancers Age 49-60  Screen detected cancers show increase in ultra-low risk cancers P<0.001 Pre-screening n=143, sreen-detected n=73 12% 30% MammaPrint