Genomic Tests as Predictors of Breast Cancer Patients’ Prognosis


Authors: Z. Bielčiková;  L. Petruželka
Authors‘ workplace: Onkologická klinika 1. LF UK a VFN v Praze
Published in: Klin Onkol 2016; 29(1): 13-19
Category: Review
doi: 10.14735/amko201613

Overview

Hormonal dependent breast cancer is a heterogeneous disease from a molecular and clinical perspective. The relapse risk of early breast cancer patients treated with adjuvant hormonal therapy varies. Validated predictive markers concerning adjuvant cytotoxic treatment are still lacking in ER+/ HER2–  breast cancer, which has a good prognosis in general. This can lead to the inefficient chemotherapy indication. Molecular classification of breast cancer reports evidence about the heterogeneity of hormonal dependent breast cancer and its stratification to different groups with different characteristics. Multigene assays work on the molecular level, and their aim is to provide patients’ risk stratification and therapy efficacy prediction. The position of multigene assays in clinical practice is not stabile yet. Non‑ uniform level of evidence connected to patients’ prognosis interpretations and difficult comparison of tests are the key problems, which prevent their wide clinical use. The article is a summary of some of the most important multigene assays in breast cancer and their current position in oncology practice.

Key words:
breast cancer –  adjuvant therapy –  molecular classification –  multigene assays – risk of recurrence – prognosis

The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.

The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers.

Submitted:
5. 4. 2015

Accepted:
21. 5. 2015


Sources

1. Perou CM, Sørlie T, Eisen MB et al. Molecular portraits of human breast tumours. Nature 2000; 406(6797): 747– 752.

2. Petruželka L. Současné možnosti a nové perspektivy systémové léčby karcinomu prsu. Klin Farmakol Farm 2007; 21(3– 4): 103– 113.

3. Ryka A, Hovorková E, Sobande F et al. Naděje a úskalí molekulární klasifikace karcinomu prsu. Cesk Patol 2015; 51(1): 26– 32.

4. Dowsett M, Nielsen TO, A‘Hern R et al. Assessment of Ki67 in breast cancer: recommendations from the International Ki67 in Breast Cancer working group. Natl Cancet Inst 2011; 103(22): 1656– 1664. doi: 10.1093/ jnci/ djr393.

5. Svoboda M, Grell P, Fabián P et al. Molekulární taxonomie a prediktivní systémy karcinomu prsu definované na základě profilů genové exprese. Klin Onkol 2006; 19 (Suppl 2): 373– 381.

6. Gnant M, Harbeck N, Thomssen C. St. Gallen 2011: sum­mary of the consensus discussion. Breast Care (Basel) 2011; 6(2): 136– 141.

7. Perou CM, Sorlie T, Eisen MB et al. Molecular portraits of human breast tumours. Nature 2000; 406(6797): 747– 752.

8. Sorlie T, Perou CM, Tibshirani R et al. Gene expres­sion patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001; 98(19): 10869– 10874.

9. Parker JS, Mullins M, Cheang MC et al. supervis­ed risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009; 27(8): 1160– 1167. doi: 10.1200/ JCO.2008.18.1370.

10. Early Breast Cancer Trialists‘ Collaborative Group (EBCTCG). Effects of chemotherapy and hormonal ther­apy for early breast cancer on recurrence and 15‑year survival: an overview of the randomized trials. Lancet 2005; 365(9472): 1687– 1717.

11. IMPAKT Brussels. Belgium on 8– 10 May 2014 by Dr Patrick Neven.

12. Sotiriou CH, Wirapati P, Loi S et al. Gene Expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 2006; 98(4): 262– 272.

13. Zhang Y, Schnabel CA, Schroeder BE et al. Breast cancer index identifies early‑stage estrogen receptor‑ positive breast cancer patients at risk for early‑  and late‑ distant recurrence. Clin Cancer Res 2013; 19(15): 4196– 4205. doi: 10.1158/ 1078‑ 0432.CCR‑ 13‑ 0804.

14. Naoi Y, Kishi K, Tanei T et al. Development of 95- gene classifier as a powerful predictor of recurrences in node‑ negative and ER‑ positive breast cancer patients. Breast Cancer Res Treat 2011; 128(3): 633– 641. doi: 10.1007/ s10549‑ 010‑ 1145‑ z.

15. Azim HA, Michiels S, Zagouri F et al. Utility of prognostic genomic tests in breast cancer practice: the IMPAKT 2012 Working Group Consensus Statement. Ann Oncol 2013; 24(3): 647– 654. doi: 10.1093/ annonc/ mds645.

16. 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.

17. 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.

18. 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. doi: 10.1200/ JCO.2009.24.4798.

19. Paik S, Shak S, Tang G. Risk classification of breast cancer patients by teh recurrence score assay: caomparison to guidelines based on patient age, tumor size, and tumor grade. Abstract presented at Annual San Antonio Breast Cancer Symposium; December 8– 11, 2004. San Antonio, TX: abstr. 104.

20. 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.

21. 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 randomized trial. Lancet Oncol 2010; 11(1): 55– 65.

22. Mamounas EP, Tang G, Paik S et al. Association between the 21- gene recurrence score (RS) and benefit from adjuvant paclitaxel (Pac) in node‑ positive (N+), ER‑ positive breast cancer patients (pts): results from NSABP B‑ 28. Cancer Res 2012, 72: S1– S10.

23. Gluz O, Kreipe HH, Christgen M et al. Prospective comparison of recurrence score and independent central pathology assessment of prognostic tools in early breast cancer (BC): focus on HER2, ER, PR, Ki‑ 67 results from the phase III WSG‑ Plan B trial. Poster presented at: American Society for Clinical Oncology Annual Meeting; June 2012; Chicago, IL: abstr. 552.

24. Penault-Llorca F, Filleron T, Asselain B et al. Prediction of recurrence with the Oncotype DX recurrence ccore in node-positive, HR-positive, breast cancer patients treated with adjuvant FEC-D or FEC Chemotherapy. American Society of Clinical Oncology Annual Meeting; May 2014; Chicago, IL.

25. Sparano JA, Gray RJ, Makower DF et al. Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med 2015; 373(21): 2005–2014. doi: 10.1056/NEJMoa1510764.

26. Cancer.gov [homepage on the Internet]. National Cancer Institute. Tamoxifen citrate, letrozole, anastrozole, or exemestane with or without chemotherapy in treating patients with invasive RxPONDER breast cancer. Available from: https://clinicaltrials.gov/ct2/show/NCT00433589.

30. Nielsen TO, Parker JS, Leung S et al. A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen‑treated estrogen receptor‑ positive breast cancer. Clin Cancer Res 2010; 16(21): 5222– 5232. doi: 10.1158/ 1078‑ 0432.CCR‑ 10‑ 1282.

31. 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. doi: 10.1200/ JCO.2012.46.1558.

32. 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. doi: 10.1093/ annonc/ mdt494.

33. Kronenwett R, Bohmann K, Prinzler J et al. Decentral gene expression analysis: analytical validation of the endopredict genomic multianalyte breast cancer prognosis test. BMC Cancer 2012; 12: 456.

34. Denkert C, Kronenwett R, Schlake W et al. Decentral gene expression analysis for ER+/ Her2–  breast cancer: results of a proficiency testing program for the EndoPredict assay. Virchows Arch 2012; 460(3): 251– 259. doi: 10.1007/ s00428‑ 012‑ 1204‑ 4.

35. 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. doi: 10.1158/ 1078‑ 0432.CCR‑ 11‑ 0926.

36. Martin M, Brase JC, Calvo L et al. Clinical validation of the EndoPredict test in node‑ positive, chemother­apy‑treated ER+/ HER2− breast cancer patients: results from the GEICAM 9906 trial. Breast Cancer Res 2014; 16(2): R38. doi: 10.1186/ bcr3642.

37. Fan C, Oh DS, Wessels L et al. Concordance among gene‑ expression‑based predictors for breast cancer. N Engl J Med 2006; 355(6): 560– 569.

38. Poulet B, Jamshidian F, Butler S et al. Risk classification of early stage breast cancer as assessed by MammaPrint and Oncotype DX genomic assays. SABCS 2012: abstr. #P6- 07- 03.

39. Shivers SC, Clark L, Esposito N et al. Direct comparison of risk classification between MammaPrint®, Oncotype DX® and MammoStrat® assays in patients with early stage breast cancer. Cancer Res December 2013; 73 (Suppl 24): abstr. P6- 06- 02.

40. Alvarado M, Prasad C et al. A pilot laboratory study comparing the 21- gene assay and PAM50- ROR.

41. Kern P, Rezai M, Singer CH et al. Genomic testing in international guidelines. EMJ Oncol 2013; 1: 68– 74.

42. NCCN Breast cancer guidelines. V.2.2015.

43. Harris L, Fritsche H, Mennel R et al. American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol 2007; 25(33): 5287–5312.

44. Coates AS, Winer EP, Goldhirsch A et al. Tailoring therapies – improving the management of early breast cancer: St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015. Ann Oncol 2015; 26(8): 1533–1546. doi: 10.1093/annonc/mdv221.

45. Senkus E, Kyriakides S, Ohno S et al. Primary breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann of Oncol 2015; 26 (Suppl 5): v8–v30. doi: 10.1093/annonc/mdv298.

Labels
Paediatric clinical oncology Surgery Clinical oncology
Login
Forgotten password

Don‘t have an account?  Create new account

Forgotten password

Enter the email address that you registered with. We will send you instructions on how to set a new password.

Login

Don‘t have an account?  Create new account