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2012 EDUCATIONAL BOOK - American Society of Clinical Oncology

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consortium to facilitate the testing <strong>of</strong> agents against a<br />

backdrop <strong>of</strong> comprehensive tumor pr<strong>of</strong>iling, with the ability<br />

to use the adaptive design process to enrich enrollment on<br />

the basis <strong>of</strong> standard markers. The biomarker design <strong>of</strong> the<br />

trial allows the evaluation <strong>of</strong> three levels <strong>of</strong> biomarkers. The<br />

first are standard or investigational device exemption (IDE)<br />

approved, which are integral markers used in the adaptive<br />

randomization. These include hormone and HER2 receptors,<br />

the U.S. Food and Drug Administration (FDA)—approved<br />

70-gene pr<strong>of</strong>ile, other measures <strong>of</strong> HER2 overexpression<br />

(fluorescent in situ hybridization and expression array) and<br />

volume on magnetic resonance imaging. The second level<br />

comprises “qualifying” biomarkers. These are biomarkers<br />

that have promise in predicting response to a specific agent,<br />

but require validation in a CLIA-approved testing environment.<br />

This includes cell line predictors that predict response<br />

and can be read by expression array, or other specific<br />

phosphoprotein that is thought to be a key target <strong>of</strong> a<br />

particular agent. These markers, if they prove to be predictive<br />

<strong>of</strong> response, would potentially be used as integral<br />

markers in future trials <strong>of</strong> the agent and the data generated<br />

from their evaluation in the I-SPY 2 TRIAL can be used to<br />

support an IDE application. The last layer is the exploratory<br />

biomarkers. These include hypothesis-generating markers<br />

from new platforms such as RNAseq. The platforms being<br />

Authors’ Disclosures <strong>of</strong> Potential Conflicts <strong>of</strong> Interest<br />

Author<br />

Employment or<br />

Leadership<br />

Positions<br />

Consultant or<br />

Advisory Role<br />

used to characterize tumors in the trial include Agilent<br />

Technologies (Palo Alto, CA) and Affymetrix (Santa Clara,<br />

CA) expression arrays, reverse phase protein arrays,<br />

genome-wide association study (GWAS), and RNAseq.<br />

The goal <strong>of</strong> the trial is to graduate agents and biomarker<br />

pairs with a predicted likelihood <strong>of</strong> success in phase III<br />

trials. 7 Going forward, if an agent is shown to improve the<br />

chance <strong>of</strong> obtaining a pathologic complete response and this<br />

observation can be confirmed in a separate neoadjuvant<br />

trial, the FDA is willing to consider awarding accelerated<br />

approval on the basis <strong>of</strong> these data. 43 This provides a<br />

regulatory path forward for accelerating successful agents to<br />

the neoadjuvant or adjuvant settings, in which they are<br />

likely to provide the greatest benefit. Indeed, it is about time<br />

that we design our trials around the biomarkers that characterize<br />

risk and response to treatment. The I-SPY 2 TRIAL<br />

is one such effort directed at more rapidly and efficiently<br />

finding better options for patients with breast cancer. Furthermore,<br />

this platform provides the opportunity to validate<br />

several <strong>of</strong> the emerging markers described in the first<br />

portion <strong>of</strong> this article, and to help us move faster toward the<br />

time when we will be able to provide precision medicine<br />

approaches to reduce the suffering and death associated<br />

with a diagnosis <strong>of</strong> breast cancer.<br />

Stock<br />

Ownership Honoraria<br />

Laura Esserman Agendia<br />

Christopher Benz*<br />

Angela DeMichele*<br />

*No relevant relationships to disclose.<br />

1. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). Effects <strong>of</strong><br />

chemotherapy and hormonal therapy for early breast cancer on recurrence<br />

and 15-year survival: an overview <strong>of</strong> the randomised trials. Lancet. 2005;365:<br />

1687-1717.<br />

2. Slamon DJ. Proto-oncogenes and human cancers. N Engl J Med. 1987;<br />

317:955-957.<br />

3. Slamon DJ, Leyland-Jones B, Shak S, et al. Use <strong>of</strong> chemotherapy plus a<br />

monoclonal antibody against HER2 for metastatic breast cancer that overexpresses<br />

HER2. N Engl J Med. 2001;344:783-792.<br />

4. Romond EH, Perez EA, Bryant J, et al. Trastuzumab plus adjuvant<br />

chemotherapy for operable HER2-positive breast cancer. N Engl J Med<br />

2005;353:1673-1684.<br />

5. Fisher B. Breast-cancer management: alternatives to radical mastectomy.<br />

N Engl J Med. 1979;301:326-328.<br />

6. Esserman LJ, Shieh Y, Rutgers EJ, et al. Impact <strong>of</strong> mammographic<br />

screening on the detection <strong>of</strong> good and poor prognosis breast cancers. Breast<br />

Cancer Res Treat. 2011;130:725-734.<br />

7. Barker AD, Sigman CC, Kell<strong>of</strong>f GJ, et al. I-SPY 2: an adaptive breast<br />

cancer trial design in the setting <strong>of</strong> neoadjuvant chemotherapy. Clin Pharmacol<br />

Ther. 2009;86:97-100.<br />

8. van de Vijver MJ, He YD, van’t Veer LJ, et al. A gene-expression<br />

signature as a predictor <strong>of</strong> survival in breast cancer. New Engl J Med.<br />

2002;347:1999-2009.<br />

9. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence <strong>of</strong><br />

tamoxifen-treated, node-negative breast cancer. New Engl J Med. 2004;351:<br />

2817-2826.<br />

10. Paik S, Tang G, Shak S, et al. Gene expression and benefit <strong>of</strong><br />

chemotherapy in women with node-negative, estrogen receptor-positive<br />

breast cancer. J Clin Oncol. 2006;24:3726-3734.<br />

11. van’t Veer LJ, Bernards R. Enabling personalized cancer medicine<br />

through analysis <strong>of</strong> gene-expression patterns. Nature. 2008;452:564-570.<br />

190<br />

REFERENCES<br />

Research<br />

Funding<br />

ESSERMAN, BENZ, AND DEMICHELE<br />

Expert<br />

Testimony<br />

Other<br />

Remuneration<br />

12. Hatzis C, Pusztai L, Valero V, et al. A genomic predictor <strong>of</strong> response<br />

and survival following taxane-anthracycline chemotherapy for invasive<br />

breast cancer. JAMA. 2011;305:1873-1881.<br />

13. Esserman L, Shieh Y, Thompson I. Rethinking screening for breast<br />

cancer and prostate cancer. JAMA. 2009;302:1685-1692.<br />

14. Kok M, Linn SC, Van Laar RK, et al. Comparison <strong>of</strong> gene expression<br />

pr<strong>of</strong>iles predicting progression in breast cancer patients treated with tamoxifen.<br />

Breast Cancer Res Treat. 2009;113:275-283.<br />

15. Esserman LJ, Moore DH, Tsing PJ, et al. Biologic markers determine<br />

both the risk and the timing <strong>of</strong> recurrence in breast cancer. Breast Cancer Res<br />

Treat. 2011;129:607-616.<br />

16. Tutt A, Wang A, Rowland C, et al. Risk estimation <strong>of</strong> distant metastasis<br />

in node-negative, estrogen receptor-positive breast cancer patients using an<br />

RT-PCR based prognostic expression signature. BMC Cancer. 2008;8:339.<br />

17. Yau C, Wang Y, Zhang Y, et al. Young age, increased tumor proliferation<br />

and FOXM1 expression predict early metastatic relapse only for<br />

endocrine-dependent breast cancers. Breast Cancer Res Treat. 2011;126:803-<br />

810.<br />

18. Yau C, Esserman L, Moore DH, et al. A multigene predictor <strong>of</strong><br />

metastatic outcome in early stage hormone receptor-negative and triplenegative<br />

breast cancer. Breast Cancer Res. 2010;12:R85.<br />

19. Liu MC, Dixon JM, Xuan JJ, et al. Molecular signaling distinguishes<br />

early ER positive breast cancer recurrences despite adjuvant tamoxifen.<br />

Cancer Res. 2011;71 (suppl; abstr S1-8).<br />

20. Bianchini G, Pusztai L, Iwamoto T, et al. Molecular Tumor Characteristics<br />

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(suppl; abstr S1-7).<br />

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predicts clinical outcome in breast cancer patients treated with tamoxifen.<br />

Cancer Cell. 2004;6:445.<br />

22. Ma XJ, Wang Z, Ryan PD, et al. A two-gene expression ratio predicts

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