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  • Review Article
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Gene-expression-based prognostic assays for breast cancer

Nature Reviews Clinical Oncology volume 7, pages 340–347 (2010)Cite this article

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Abstract

Several gene-expression-based reference laboratory tests are now available for prognostication of patients diagnosed with breast cancer. For clinical oncologists, it is important to understand the clinical contexts for which these assays were developed in order to use them properly. This Review is aimed at providing a conceptual and technical overview of the steps involved in the development of gene-expression profiling-based prognostic assays. MammaPrint® and Oncotype DX®, two widely utilized assays, are compared with respect to differences in the clinical contexts for their development, technologies used, and clinical utilities with the aim of providing a guide to clinical oncologists for utilization of these assays.

Key Points

  • Clinical prognostic tests are most useful when developed and validated for a specific clinical context with a clear cut-off point for decision-making

  • There are two commercial reference laboratory tests based on gene-expression profiling (MammaPrint® and Oncotype DX®) that are either agency-approved or widely-accepted by the oncology community

  • These tests are not perfect and performances are similar

  • Their clinical utility should be determined based on specific clinical contexts

  • Oncotype DX® assay requires routinely processed formalin-fixed paraffin-embedded tumor tissue block, whereas the MammaPrint® assay requires snap-frozen tumor tissue or fresh tumor tissue procured in a special buffer

  • More studies are needed to examine the influence of intratumor heterogeneity or previous needle biopsy procedures on the performance of these assays

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Figure 1: Stages involved in developing a prognostic assay.
Figure 2: Influence of tumor heterogeneity on Oncotype DX® recurrence score.
Figure 3: Influence of tumor heterogeneity on individual genes in the Oncotype DX® assay.

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References

  1. Mook, S., van' t Veer, L. J., Rutgers, E. J., Piccart-Gebhart, M. J. & Cardoso, F. Individualization of therapy using Mammaprint: from development to the MINDACT Trial. Cancer Genomics Proteomics 4, 147–155 (2007).

    CAS  PubMed  Google Scholar 

  2. Ross, J. S., Hatzis, C., Symmans, W. F., Pusztai, L. & Hortobágyi, G. N. Commercialized multigene predictors of clinical outcome for breast cancer. Oncologist 13, 477–493 (2008).

    Article  PubMed  Google Scholar 

  3. Kim, C., Taniyama, Y. & Paik, S. Gene expression-based prognostic and predictive markers for breast cancer: a primer for practicing pathologists. Arch. Pathol. Lab. Med. 133, 855–859 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Paik, S. et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N. Engl. J. Med. 351, 2817–2826 (2004).

    Article  CAS  PubMed  Google Scholar 

  5. van 't Veer, L. J. et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 415, 530–536 (2002).

    Article  CAS  PubMed  Google Scholar 

  6. Loi, S. et al. Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade. J. Clin. Oncol. 25, 1239–1246 (2007).

    Article  CAS  PubMed  Google Scholar 

  7. Ma, X. J. et al. A five-gene molecular grade index and HOXB13:IL17BR are complementary prognostic factors in early stage breast cancer. Clin. Cancer Res. 14, 2601–2608 (2008).

    Article  CAS  PubMed  Google Scholar 

  8. Liedtke, C. et al. Genomic grade index is associated with response to chemotherapy in patients with breast cancer. J. Clin. Oncol. 27, 3185–3191 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Albain, K. S. et al. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial. Lancet Oncol. 11, 55–65 (2010).

    Article  CAS  PubMed  Google Scholar 

  10. van de Vijver, M. J. et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347, 1999–2009 (2002).

    Article  CAS  PubMed  Google Scholar 

  11. Wittner, B. S. et al. Analysis of the MammaPrint breast cancer assay in a predominantly postmenopausal cohort. Clin. Cancer Res. 14, 2988–2993 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Straver, M. E. et al. The 70-gene signature as a response predictor for neoadjuvant chemotherapy in breast cancer. Breast Cancer Res. Treat. 119, 551–558 (2010).

    Article  PubMed  Google Scholar 

  13. Paik, S., Kim, C. Y., Song, Y. K. & Kim, W. S. Technology insight: application of molecular techniques to formalin-fixed paraffin-embedded tissues from breast cancer. Nat. Clin. Pract. Oncol. 2, 246–254 (2005).

    Article  CAS  PubMed  Google Scholar 

  14. Geiss, G. K. et al. Direct multiplexed measurement of gene expression with color-coded probe pairs. Nat. Biotechnol. 26, 317–325 (2008).

    Article  CAS  PubMed  Google Scholar 

  15. Schena, M., Shalon, D., Davis, R. W. & Brown, P. O. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467–470 (1995).

    Article  CAS  PubMed  Google Scholar 

  16. Shi, L. et al. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat. Biotechnol. 24, 1151–1161 (2006).

    Article  CAS  PubMed  Google Scholar 

  17. Masuda, N., Ohnishi, T., Kawamoto, S., Monden, M. & Okubo, K. Analysis of chemical modification of RNA from formalin-fixed samples and optimization of molecular biology applications for such samples. Nucleic Acids Res. 27, 4436–4443 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Cronin, M. et al. Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay. Am. J. Pathol. 164, 35–42 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Perou, C. M. et al. Molecular portraits of human breast tumours. Nature 406, 747–752 (2000).

    Article  CAS  PubMed  Google Scholar 

  20. Sørlie, T. et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl Acad. Sci. USA 98, 10869–10874 (2001).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Parker, J. S. et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 27, 1160–1167 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Mook, S. et al. The 70-gene prognosis signature predicts early metastasis in breast cancer patients between 55 and 70 years of age. Ann. Oncol. 21, 717–722 (2010).

    Article  CAS  PubMed  Google Scholar 

  23. Straver, M. E. et al. The 70-gene signature as a response predictor for neoadjuvant chemotherapy in breast cancer. Breast Cancer Res. Treat. 119, 551–558 (2009).

    Article  PubMed  Google Scholar 

  24. Wittner, B. S. et al. Analysis of the MammaPrint breast cancer assay in a predominantly postmenopausal cohort. Clin. Cancer Res. 14, 2988–2993 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Glas, A. M. et al. Converting a breast cancer microarray signature into a high-throughput diagnostic test. BMC Genomics 7, 278 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Cardoso, F. et al. The MINDACT trial: the first prospective clinical validation of a genomic tool. Mol. Oncol. 1, 246–251 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Bogaerts, J. et al. Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial. Nat. Clin. Pract. Oncol. 3, 540–551 (2006).

    Article  CAS  PubMed  Google Scholar 

  28. Cardoso, F. et al. Clinical application of the 70-gene profile: the MINDACT trial. J. Clin. Oncol. 26, 729–735 (2008).

    Article  PubMed  Google Scholar 

  29. Paik, S. et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J. Clin. Oncol. 24, 3726–3734 (2006).

    Article  CAS  PubMed  Google Scholar 

  30. Sparano, J. A. TAILORx: trial assigning individualized options for treatment (Rx). Clin. Breast Cancer 7, 347–350 (2006).

    Article  PubMed  Google Scholar 

  31. Cronin, M. et al. Analytical validation of the Oncotype DX genomic diagnostic test for recurrence prognosis and therapeutic response prediction in node-negative, estrogen receptor-positive breast cancer. Clin. Chem. 53, 1084–1091 (2007).

    Article  CAS  PubMed  Google Scholar 

  32. Habel, L. A. et al. A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res. 8, R25 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Fan, C. et al. Concordance among gene-expression-based predictors for breast cancer. N. Engl. J. Med. 355, 560–569 (2006).

    Article  CAS  PubMed  Google Scholar 

  34. Schardt, J. A. et al. Genomic analysis of single cytokeratin-positive cells from bone marrow reveals early mutational events in breast cancer. Cancer Cell 8, 227–239 (2005).

    Article  CAS  PubMed  Google Scholar 

  35. Goldstein, L. J. et al. Prognostic utility of the 21-gene assay in hormone receptor-positive operable breast cancer compared with classical clinicopathologic features. J. Clin. Oncol. 26, 4063–4071 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Sotiriou, C. et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J. Natl Cancer Inst. 98, 262–272 (2006).

    Article  CAS  PubMed  Google Scholar 

  37. Toussaint, J. et al. Improvement of the clinical applicability of the Genomic Grade Index through a qRT-PCR test performed on frozen and formalin-fixed paraffin-embedded tissues. BMC Genomics 10, 424 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. Division of Pathology, National Surgical Adjuvant Breast and Bowel Project, Federal North Building, Suite 303, Pittsburgh, 15212, PA, USA

    Chungyeul Kim & Soonmyung Paik

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  1. Chungyeul Kim
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Correspondence to Soonmyung Paik.

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Competing interests

Dr. Soonmyung Paik declares he is a patent holder for the Oncotype DX® assay, produced by Genomic Health Inc. Dr. Paik is listed as one of the inventors for the Oncotype DX® assay but all rights have been assigned to the NSABP Foundation and Dr. Paik has no financial relationship with the company nor has he received any royalty based on the patent. C. Kim declares no competing interests.

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Kim, C., Paik, S. Gene-expression-based prognostic assays for breast cancer. Nat Rev Clin Oncol 7, 340–347 (2010). https://doi.org/10.1038/nrclinonc.2010.61

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