Clinical Utility of Multigene Assays for Guiding Treatment Decisions in Early Breast Cancer Patients
Main Article Content
Abstract
The clinical management of invasive breast cancer has changed during the last decade with the use of molecular-based multigene assays (MGAs).They are increasingly used to gain additional prognostic and predictive information and guide adjuvant treatment decisions. Since 2004, several MGAs have become available but, four of them are the most widely used in clinical practice: the OncotypeDX® Breast Recurrence Score, the 70-gene signature MammaPrint®, the Prosigna® (PAM50) and the EndoPredict® (EP/EPclin Scores) assay. However, MGAs are not all the same and they do not provide interchangeable information. They differ in terms of the technological platform used for their development, the number and specific genes assessed, and the patient populations in which they were validated. Furthermore, although they are all validated for providing prognostic information, not all of them are supported with data from prospective randomised trials confirming the clinical value of their use in chemotherapy treatment decisions in certain groups of breast cancer patients; in this regard, so far there are published data only for OncotypeDX and MammaPrint, whilst PAM-50 (Prosigna) and EndoPredict assays are currently not supported by entirely prospective randomized trials evaluating their predictive value of chemotherapy benefit. As such, inclusion of these MGAs in major international treatment guidelines differs in indications for their use in clinical practice as prognosticators only or as predictors of chemotherapy benefit as well. Use of MGAs in clinical decision making can lead to de-escalation of chemotherapy recommendations and thus save a large number of patients from unnecessary side effects and decrease the cost of breast cancer treatment to National Health systems. This review provides an overview of the four most widely used MGAs in clinical practice, including basic information on their development and validation, as well as recent data on the information they can provide.
Keywords:
Breast cancer, Multigene assays, OncotypeDX, Mammaprint, Prosigna, Endopredict
Article Details
How to Cite
MARKOPOULOS, Christos.
Clinical Utility of Multigene Assays for Guiding Treatment Decisions in Early Breast Cancer Patients.
Medical Research Archives, [S.l.], v. 10, n. 10, oct. 2022.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/3176>. Date accessed: 22 dec. 2024.
doi: https://doi.org/10.18103/mra.v10i10.3176.
Section
Review Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
References
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29. Dubsky P, Brase JC, Jakesz R, et al. The EndoPredict score provides prognostic information on late distant metastases in ER+/HER2- breast cancer patients. Br J Cancer. 2013;109(12):2959-2964.
30. Dowsett M, Sestak I, Lopez-Knowles E, et al. Comparison of PAM50 risk of recurrence score with Oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol. 2013;31(22):2783-2790.
31. Denduluri N, Rugo HS, Davis SE, et al. Concordance between the 21-gene recurrence score (RS) and the 70-gene profile (MP) in breast cancer (BC) patients (pts). J Clin Oncol. 2011;29 Suppl 27: abstract 13.
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33. Varga Z, Sinn P, Fritzsche F, et al. Comparison of EndoPredict and Oncotype DX test results in hormone receptor positive invasive breast cancer. PloS one. 2013;8(3):e58483.
34. Varga Z, Sinn P, Seidman AD. Summary of head-to-head comparisons of patient risk classifications by the 21-gene Recurrence Score® (RS) assay and other genomic assays for early breast cancer. Int J Cancer. 2019;145:882-893.
35. Markopoulos C, Hyams DM, Gomez HL, et al. Multigene assays in early breast cancer: Insights from recent phase 3 studies. Eur J Surg Oncol. 2020;46 (4 Pt A):656-666.
36. Cardoso F, Kyriakides S, Ohno S, et al. Early breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Annals of Oncology. 2019;30: 1194–1220.
37. Burstein HJ, Curigliano G, Thürlimann GB, et al. Customizing local and systemic therapies for women with early breast cancer: the St. Gallen International Consensus Guidelines for treatment of early breast cancer 2021. Ann Oncol. 2021;32(10):1216-1235.
38. Andre F, Ismaila N, Allison KA, et al. Biomarkers for Adjuvant Endocrine and Chemotherapy in Early-Stage Breast Cancer: ASCO Guideline Update. Published at ascopubs.org/journal/jco on April 19, 2022:
DOI https://doi.org/10.1200/JCO.22.00069
39. assessed at http://www.nccn.org/professionals/physician_gls/pdf/breast.pdf
40. Blohmer JU, Rezai M, Kummel S, et al. Using the 21-gene assay to guide adjuvant chemotherapy decision-making in early-stage breast cancer: a cost-effectiveness evaluation in the German setting. J Med Econ. 2013;16(1):30-40.
41. Klang SH, Hammerman A, Liebermann N, Efrat N, Doberne J, Hornberger J. Economic implications of 21-gene breast cancer risk assay from the perspective of an Israeli-managed health-care organization. Value Health. 2010;13(4):381-387.
42. Chen E, Tong KB, Malin JL. Cost-effectiveness of 70-gene MammaPrint signature in node-negative breast cancer. Am J Manag Care. 2010;16(12):e333-342.
43. Retel VP, Joore MA, Drukker CA, et al. Prospective cost-effectiveness analysis of genomic profiling in breast cancer. Eur J Cancer. 2013;49(18):3773-3779.
44. Blank PR, Filipits M, Dubsky P, et al. Cost-effectiveness analysis of prognostic gene expression signature-based stratification of early breast cancer patients. Pharmacoeconomics. 2015;33(2):179-190.
45. Berdunov V, Millen S, Paramore A, et al. Cost-effectiveness analysis of the Oncotype DX Breast Recurrence Score test in node-positive early breast cancer. J Med Econ. 2022;25(1):591-604.
2. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004; 351(27):2817-2826.
3. Cronin M, Sangli C, Liu ML, 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. 2007;53(6):1084-1091.
4. Dowsett M, Cuzick J, Wale C, et al. Prediction of risk of distant recurrence using the 21-gene recurrence score in node-negative and node-positive postmenopausal patients with breast cancer treated with anastrozole or tamoxifen: a TransATAC study. J Clin Oncol. 2010;28(11):1829-1834.
5. Habel LA, Shak S, Jacobs MK, et al. A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res. 2006;8(3):R25.
6. Toi M, Iwata H, Yamanaka T, et al. Clinical significance of the 21-gene signature (Oncotype DX) in hormone receptor-positive early stage primary breast cancer in the Japanese population. Cancer. 2010;116(13):3112-3118.
7. Albain KS, Barlow WE, Shak 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. 2010;11(1):55-65.
8. Wolmark N, Mamounas EP, Baehner FL, et al. Prognostic Impact of the Combination of Recurrence Score and Quantitative Estrogen Receptor Expression (ESR1) on Predicting Late Distant Recurrence Risk in Estrogen Receptor-Positive Breast Cancer After 5 Years of Tamoxifen: Results From NRG Oncology/National Surgical Adjuvant Breast and Bowel Project B-28 and B-14. J Clin Oncol. 2016;34(20):2350-2358.
9. Sparano JA, Gray RJ, Makower DF, et al. Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. The TAILORx trial. N Engl J Med. 2018;379(2):111-121.
10. Gluz O, Nitz UA, Christgen M, et al. West German Study Group Phase III PlanB Trial: First prospective outcome data for the 21-gene Recurrence Score assay and concordance of prognostic markers by central and local pathology assessment. J Clin Oncol. 2016;34(20):2341-2349.
11. Stemmer SM, Steiner M, Rizel S, et al. Real-life analysis evaluating 1594 N0/Nmic breast cancer patients for whom treatment decisions incorporated the 21-gene recurrence score result: 5-year KM estimate for breast cancer specific survival with recurrence score results ≤30 is >98%. Paper presented at: San Antonio Breast Cancer Symposium (SABCS); 2015 Dec 8-12; San Antonio, TX.
12. Shak S, Petkov VI, Miller DP, et al. Breast cancer specific survival in 38,568 patients with node negative hormone receptor positive invasive breast cancer and Oncotype DX Recurrence Score results in the SEER database. Paper presented at: San Antonio Breast Cancer Symposium (SABCS); 2015 Dec 8-12; San Antonio, TX.
13. Paik S, Tang G, Shak S, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol. 2006;24(23):3726-3734.
14. Kalinsky K, Barlow WE, Gralow JR, et al. 21-Gene Assay to Inform Chemotherapy Benefit in Node-Positive Breast Cancer. The RxPONDER trial. N Engl J Med. 2021;385(25):2336-2347.
15. van 't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415(6871):530-536.
16. Buyse M, Loi S, van't Veer L, et al. Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J Natl Cancer Inst. 2006;98(17):1183-1192.
17. Bueno-de-Mesquita JM, Linn SC, Keijzer R, et al. Validation of 70-gene prognosis signature in node-negative breast cancer. Breast Cancer Res Treat. 2009;117(3):483-495.
18. Mook S, Schmidt MK, Viale G, et al. The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1-3 positive lymph nodes in an independent validation study. Breast Cancer Res Treat. 2009;116(2):295-302.
19. Drukker CA, Bueno-de-Mesquita JM, Retel VP, et al. A prospective evaluation of a breast cancer prognosis signature in the observational RASTER study. Int J Cancer. 2013;133(4):929-936.
20. Sapino A, Roepman P, Linn SC, et al. MammaPrint molecular diagnostics on formalin-fixed, paraffin-embedded tissue. J Mol Diagn. 2014;16(2):190-197.
21. Cardoso F, van't Veer LJ, Bogaerts J, et al. MINADCT investigators. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N Engl J Med. 2016;375(8):717-729.
22. Piccart M, van 't Veer LJ, Poncet C, et al. 70-gene signature as an aid for treatment decisions in early breast cancer: updated results of the phase 3 randomised MINDACT trial with an exploratory analysis by age. Lancet Oncol. 2021;22(4):476-488.
23. Prosigna [Package Insert]. Seattle, WA: NanoString Technologies Inc; 2013.
24. Filipits M, Rudas M, Jakesz R, et al. A new molecular predictor of distant recurrence in ER-positive, HER2-negative breast cancer adds independent information to conventional clinical risk factors. Clin Cancer Res. 2011;17(18):6012-6020.
25. Gnant M, Filipits M, Greil R, et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 Risk of Recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann Oncol. 2014;25(2):339-345.
26. Gnant M, Dowsett M, Filipits M, et al. Identifying clinically relevant prognostic subgroups in node-positive postmenopausal HR+ early breast cancer patients treated with endocrine therapy: A combined analysis of 2,485 patients from ABCSG-8 and ATAC using the PAM50 risk of recurrence (ROR) score and intrinsic subtype. J Clin Oncol. 2013;31: supplement abstract 506.
27. Liu S, Chapman JA, Burnell MJ, et al. Prognostic and predictive investigation of PAM50 intrinsic subtypes in the NCIC CTG MA.21 phase III chemotherapy trial. Breast Cancer Res Treat. 2015;149(2):439-448.
28. Sestak I, Dowsett M, Zabaglo L, et al. Factors predicting late recurrence for estrogen receptor-positive breast cancer. J Natl Cancer Inst. 2013;105(19):1504-1511.
29. Dubsky P, Brase JC, Jakesz R, et al. The EndoPredict score provides prognostic information on late distant metastases in ER+/HER2- breast cancer patients. Br J Cancer. 2013;109(12):2959-2964.
30. Dowsett M, Sestak I, Lopez-Knowles E, et al. Comparison of PAM50 risk of recurrence score with Oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol. 2013;31(22):2783-2790.
31. Denduluri N, Rugo HS, Davis SE, et al. Concordance between the 21-gene recurrence score (RS) and the 70-gene profile (MP) in breast cancer (BC) patients (pts). J Clin Oncol. 2011;29 Suppl 27: abstract 13.
32. Alvarado MD, Prasad C, Rothney M, et al. A prospective comparison of the 21-gene Recurrence Score and the PAM50-based Prosigna in estrogen receptor-positive early-stage breast cancer. Adv Ther. 2015;32(12):1237-1247.
33. Varga Z, Sinn P, Fritzsche F, et al. Comparison of EndoPredict and Oncotype DX test results in hormone receptor positive invasive breast cancer. PloS one. 2013;8(3):e58483.
34. Varga Z, Sinn P, Seidman AD. Summary of head-to-head comparisons of patient risk classifications by the 21-gene Recurrence Score® (RS) assay and other genomic assays for early breast cancer. Int J Cancer. 2019;145:882-893.
35. Markopoulos C, Hyams DM, Gomez HL, et al. Multigene assays in early breast cancer: Insights from recent phase 3 studies. Eur J Surg Oncol. 2020;46 (4 Pt A):656-666.
36. Cardoso F, Kyriakides S, Ohno S, et al. Early breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Annals of Oncology. 2019;30: 1194–1220.
37. Burstein HJ, Curigliano G, Thürlimann GB, et al. Customizing local and systemic therapies for women with early breast cancer: the St. Gallen International Consensus Guidelines for treatment of early breast cancer 2021. Ann Oncol. 2021;32(10):1216-1235.
38. Andre F, Ismaila N, Allison KA, et al. Biomarkers for Adjuvant Endocrine and Chemotherapy in Early-Stage Breast Cancer: ASCO Guideline Update. Published at ascopubs.org/journal/jco on April 19, 2022:
DOI https://doi.org/10.1200/JCO.22.00069
39. assessed at http://www.nccn.org/professionals/physician_gls/pdf/breast.pdf
40. Blohmer JU, Rezai M, Kummel S, et al. Using the 21-gene assay to guide adjuvant chemotherapy decision-making in early-stage breast cancer: a cost-effectiveness evaluation in the German setting. J Med Econ. 2013;16(1):30-40.
41. Klang SH, Hammerman A, Liebermann N, Efrat N, Doberne J, Hornberger J. Economic implications of 21-gene breast cancer risk assay from the perspective of an Israeli-managed health-care organization. Value Health. 2010;13(4):381-387.
42. Chen E, Tong KB, Malin JL. Cost-effectiveness of 70-gene MammaPrint signature in node-negative breast cancer. Am J Manag Care. 2010;16(12):e333-342.
43. Retel VP, Joore MA, Drukker CA, et al. Prospective cost-effectiveness analysis of genomic profiling in breast cancer. Eur J Cancer. 2013;49(18):3773-3779.
44. Blank PR, Filipits M, Dubsky P, et al. Cost-effectiveness analysis of prognostic gene expression signature-based stratification of early breast cancer patients. Pharmacoeconomics. 2015;33(2):179-190.
45. Berdunov V, Millen S, Paramore A, et al. Cost-effectiveness analysis of the Oncotype DX Breast Recurrence Score test in node-positive early breast cancer. J Med Econ. 2022;25(1):591-604.