The use of automated Ki67 analysis to predict Oncotype DX risk-of-recurrence categories in early-stage breast cancer

PLoS ONE

Volumn 13, Issue 1, 2018, Pages

  Thakur, Satbir Singh ^a,b   Li, Haocheng ^a   Chan, Angela M Y ^b   Tudor, Roxana ^a   Bigras, Gilbert ^c   Morris, Don ^a,b   Enwere, Emeka K ^b   Yang, Hua ^a  

^a UNIVERSITY OF CALGARY   (Canada)

^b TOM BAKER CANCER CENTRE   (Canada)

^c UNIVERSITY OF ALBERTA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ESTROGEN RECEPTOR; KI 67 ANTIGEN; PROGESTERONE RECEPTOR; EPIDERMAL GROWTH FACTOR RECEPTOR 2; ERBB2 PROTEIN, HUMAN;

ADULT; AGED; ANTIGEN DETECTION; ARTICLE; BREAST CANCER; CANCER DIAGNOSIS; CANCER GRADING; CANCER RECURRENCE; CANCER STAGING; CLINICAL FEATURE; CONTROLLED STUDY; CORRELATIONAL STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; FEMALE; GENETIC SCREENING; HALO IMAGE ANALYSIS; HIGH RISK POPULATION; HUMAN; IMAGE ANALYSIS; LOW RISK POPULATION; MACHINE LEARNING; MAJOR CLINICAL STUDY; MITOSIS INDEX; PATHOLOGY; PREDICTION; RECURRENCE RISK; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; TUMOR GROWTH; VALIDATION STUDY; BREAST TUMOR; CELL PROLIFERATION; CHEMISTRY; COHORT ANALYSIS; IMAGE PROCESSING; IMMUNOHISTOCHEMISTRY; LABORATORY AUTOMATION; METABOLISM; MIDDLE AGED; PROCEDURES; PROGNOSIS; REPRODUCIBILITY; RETROSPECTIVE STUDY; RISK FACTOR; SELECTION BIAS; STATISTICS AND NUMERICAL DATA; TUMOR RECURRENCE; VERY ELDERLY;

ADULT; AGED; AGED, 80 AND OVER; AUTOMATION, LABORATORY; BREAST NEOPLASMS; CELL PROLIFERATION; COHORT STUDIES; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IMMUNOHISTOCHEMISTRY; KI-67 ANTIGEN; MACHINE LEARNING; MIDDLE AGED; NEOPLASM RECURRENCE, LOCAL; PROGNOSIS; RECEPTOR, ERBB-2; RECEPTORS, ESTROGEN; RECEPTORS, PROGESTERONE; REPRODUCIBILITY OF RESULTS; RETROSPECTIVE STUDIES; RISK FACTORS; SELECTION BIAS;

EID: 85040127042     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0188983     Document Type: Article

References (60)

1. GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11 [Internet]. Lyon, France: International Agency for Research on Cancer; [Internet]. 2013. Available from: http://globocan.iarc.fr.
2. Harris LN, Ismaila N, McShane LM, Andre F, Collyar DE, Gonzalez-Angulo AM, et al. Use of Biomark-ers to Guide Decisions on Adjuvant Systemic Therapy for Women With Early-Stage Invasive Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline. J Clin Oncol. 2016; 34 (10):1134–50. https://doi.org/10.1200/JCO.2015.65.2289 PMID: 26858339
3. Kwa M, Makris A, Esteva FJ. Clinical utility of gene-expression signatures in early stage breast cancer. Nat Rev Clin Oncol. 2017; 14(10):595–610. https://doi.org/10.1038/nrclinonc.2017.74 PMID: 28561071
4. Geyer FC, Rodrigues DN, Weigelt B, Reis-Filho JS. Molecular classification of estrogen receptor-positive/luminal breast cancers. Adv Anat Pathol. 2012; 19(1):39–53. https://doi.org/10.1097/PAP. 0b013e31823fafa0 PMID: 22156833
5. Sinn HP, Schneeweiss A, Keller M, Schlombs K, Laible M, Seitz J, et al. Comparison of immunohistochemistry with PCR for assessment of ER, PR, and Ki-67 and prediction of pathological complete response in breast cancer. BMC Cancer. 2017; 17(1):124. https://doi.org/10.1186/s12885-017-3111-1PMID: 28193205
6. Kurozumi S, Inoue K, Takei H, Matsumoto H, Kurosumi M, Horiguchi J, et al. ER, PgR, Ki67, p27(Kip1), and histological grade as predictors of pathological complete response in patients with HER2-positive breast cancer receiving neoadjuvant chemotherapy using taxanes followed by fluorouracil, epirubicin, and cyclophosphamide concomitant with trastuzumab. BMC Cancer. 2015; 15:622. https://doi.org/10.1186/s12885-015-1641-y PMID: 26345461
7. Nishimura R, Osako T, Okumura Y, Hayashi M, Arima N. Clinical significance of Ki-67 in neoadjuvant chemotherapy for primary breast cancer as a predictor for chemosensitivity and for prognosis. Breast Cancer. 2010; 17(4):269–75. https://doi.org/10.1007/s12282-009-0161-5 PMID: 19730975
8. Yoshioka T, Hosoda M, Yamamoto M, Taguchi K, Hatanaka KC, Takakuwa E, et al. Prognostic significance of pathologic complete response and Ki67 expression after neoadjuvant chemotherapy in breast cancer. Breast Cancer. 2015; 22(2):185–91. https://doi.org/10.1007/s12282-013-0474-2 PMID: 23645542
9. Denkert C, Budczies J, von Minckwitz G, Wienert S, Loibl S, Klauschen F. Strategies for developing Ki67 as a useful biomarker in breast cancer. Breast. 2015; 24 Suppl 2:S67–72.
10. Sanchez-Munoz A, Navarro-Perez V, Plata-Fernandez Y, Santonja A, Moreno I, Ribelles N, et al. Proliferation Determined by Ki-67 Defines Different Pathologic Response to Neoadjuvant Trastuzumab-Based Chemotherapy in HER2-Positive Breast Cancer. Clin Breast Cancer. 2015; 15(5):343–7. https://doi.org/10.1016/j.clbc.2015.01.005 PMID: 25752727
11. Fasching PA, Heusinger K, Haeberle L, Niklos M, Hein A, Bayer CM, et al. Ki67, chemotherapy response, and prognosis in breast cancer patients receiving neoadjuvant treatment. BMC Cancer. 2011; 11:486. https://doi.org/10.1186/1471-2407-11-486 PMID: 22081974
12. Kim KI, Lee KH, Kim TR, Chun YS, Lee TH, Park HK. Ki-67 as a predictor of response to neoadjuvant chemotherapy in breast cancer patients. J Breast Cancer. 2014; 17(1):40–6. https://doi.org/10.4048/jbc.2014.17.1.40 PMID: 24744796
13. Brown JR, DiGiovanna MP, Killelea B, Lannin DR, Rimm DL. Quantitative assessment Ki-67 score for prediction of response to neoadjuvant chemotherapy in breast cancer. Lab Invest. 2014; 94(1):98–106. https://doi.org/10.1038/labinvest.2013.128 PMID: 24189270
14. Sheri A, Dowsett M. Developments in Ki67 and other biomarkers for treatment decision making in breast cancer. Ann Oncol. 2012; 23 Suppl 10:x219–27.
15. Pathmanathan N, Balleine RL. Ki67 and proliferation in breast cancer. J Clin Pathol. 2013; 66(6):512–6. https://doi.org/10.1136/jclinpath-2012-201085 PMID: 23436927
16. Joensuu K, Leidenius M, Kero M, Andersson LC, Horwitz KB, Heikkila P. ER, PR, HER2, Ki-67 and CK5 in Early and Late Relapsing Breast Cancer-Reduced CK5 Expression in Metastases. Breast Cancer (Auckl). 2013; 7:23–34.
17. Vincent-Salomon A, Hajage D, Rouquette A, Cedenot A, Gruel N, Alran S, et al. High Ki67 expression is a risk marker of invasive relapse for classical lobular carcinoma in situ patients. Breast. 2012; 21 (3):380–3. https://doi.org/10.1016/j.breast.2012.03.005 PMID: 22531230
18. Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thurlimann B, Senn HJ, et al. Strategies for subtypes —dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol. 2011; 22(8):1736–47. https://doi.org/10.1093/annonc/mdr304 PMID: 21709140
19. Harbeck N, Thomssen C, Gnant M. St. Gallen 2013: brief preliminary summary of the consensus discussion. Breast Care (Basel). 2013; 8(2):102–9.
20. Dowsett M, Nielsen TO, A’Hern R, Bartlett J, Coombes RC, Cuzick J, et al. Assessment of Ki67 in breast cancer: recommendations from the International Ki67 in Breast Cancer working group. J Natl Cancer Inst. 2011; 103(22):1656–64. https://doi.org/10.1093/jnci/djr393 PMID: 21960707
21. Jang MH, Kim HJ, Chung YR, Lee Y, Park SY. A comparison of Ki-67 counting methods in luminal Breast Cancer: The Average Method vs. the Hot Spot Method. PLoS One. 2017; 12(2):e0172031. https://doi.org/10.1371/journal.pone.0172031 PMID: 28187177
22. Shui R, Yu B, Bi R, Yang F, Yang W. An interobserver reproducibility analysis of Ki67 visual assessment in breast cancer. PLoS One. 2015; 10(5):e0125131. https://doi.org/10.1371/journal.pone.0125131PMID: 25932921
23. Klauschen F, Wienert S, Schmitt WD, Loibl S, Gerber B, Blohmer JU, et al. Standardized Ki67 Diagnostics Using Automated Scoring—Clinical Validation in the GeparTrio Breast Cancer Study. Clin Cancer Res. 2015; 21(16):3651–7. https://doi.org/10.1158/1078-0432.CCR-14-1283 PMID: 25501130
24. Polley MY, Leung SC, McShane LM, Gao D, Hugh JC, Mastropasqua MG, et al. An international Ki67 reproducibility study. J Natl Cancer Inst. 2013; 105(24):1897–906. https://doi.org/10.1093/jnci/djt306PMID: 24203987
25. Varga Z, Diebold J, Dommann-Scherrer C, Frick H, Kaup D, Noske A, et al. How reliable is Ki-67 immunohistochemistry in grade 2 breast carcinomas? A QA study of the Swiss Working Group of Breast- and Gynecopathologists. PLoS One. 2012; 7(5):e37379. https://doi.org/10.1371/journal.pone.0037379PMID: 22662150
26. Anampa J, Makower D, Sparano JA. Progress in adjuvant chemotherapy for breast cancer: an overview. BMC Med. 2015; 13:195. https://doi.org/10.1186/s12916-015-0439-8 PMID: 26278220
27. Sueta A, Yamamoto Y, Hayashi M, Yamamoto S, Inao T, Ibusuki M, et al. Clinical significance of pre-therapeutic Ki67 as a predictive parameter for response to neoadjuvant chemotherapy in breast cancer: is it equally useful across tumor subtypes? Surgery. 2014; 155(5):927–35. https://doi.org/10.1016/j.surg.2014.01.009 PMID: 24582496
28. Darb-Esfahani S, Loibl S, Muller BM, Roller M, Denkert C, Komor M, et al. Identification of biology-based breast cancer types with distinct predictive and prognostic features: role of steroid hormone and HER2 receptor expression in patients treated with neoadjuvant anthracycline/taxane-based chemotherapy. Breast Cancer Res. 2009; 11(5):R69. https://doi.org/10.1186/bcr2363 PMID: 19758440
29. Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004; 351(27):2817–26. https://doi.org/10.1056/NEJMoa041588 PMID: 15591335
30. Braunstein LZ, Taghian AG. Molecular Phenotype, Multigene Assays, and the Locoregional Management of Breast Cancer. Semin Radiat Oncol. 2016; 26(1):9–16. https://doi.org/10.1016/j.semradonc.2015.08.002 PMID: 26617205
31. Gyorffy B, Hatzis C, Sanft T, Hofstatter E, Aktas B, Pusztai L. Multigene prognostic tests in breast cancer: past, present, future. Breast Cancer Res. 2015; 17:11. https://doi.org/10.1186/s13058-015-0514-2PMID: 25848861
32. Sinn P, Aulmann S, Wirtz R, Schott S, Marme F, Varga Z, et al. Multigene Assays for Classification, Prognosis, and Prediction in Breast Cancer: a Critical Review on the Background and Clinical Utility. Geburtshilfe Frauenheilkd. 2013; 73(9):932–40. https://doi.org/10.1055/s-0033-1350831 PMID: 24771945
33. Albain KS, Barlow WE, Shak S, Hortobagyi GN, Livingston RB, Yeh IT, 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. https://doi.org/10.1016/S1470-2045(09)70314-6 PMID: 20005174
34. Paik S, Tang G, Shak S, Kim C, Baker J, Kim W, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol. 2006; 24(23):3726–34. https://doi.org/10.1200/JCO.2005.04.7985 PMID: 16720680
35. Sparano JA, Gray RJ, Makower DF, Pritchard KI, Albain KS, Hayes DF, et al. Prospective Validation of a 21-Gene Expression Assay in Breast Cancer. N Engl J Med. 2015; 373(21):2005–14. https://doi.org/10.1056/NEJMoa1510764 PMID: 26412349
36. Klein ME, Dabbs DJ, Shuai Y, Brufsky AM, Jankowitz R, Puhalla SL, et al. Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis. Mod Pathol. 2013; 26(5):658–64. https://doi.org/10.1038/modpathol.2013.36 PMID: 23503643
37. Sahebjam S, Aloyz R, Pilavdzic D, Brisson ML, Ferrario C, Bouganim N, et al. Ki 67 is a major, but not the sole determinant of Oncotype Dx recurrence score. Br J Cancer. 2011; 105(9):1342–5. https://doi.org/10.1038/bjc.2011.402 PMID: 21970880
38. Cuzick J, Dowsett M, Pineda S, Wale C, Salter J, Quinn E, et al. Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohis-tochemical score and comparison with the Genomic Health recurrence score in early breast cancer. J Clin Oncol. 2011; 29(32):4273–8. https://doi.org/10.1200/JCO.2010.31.2835 PMID: 21990413
39. Harowicz MR, Robinson TJ, Dinan MA, Saha A, Marks JR, Marcom PK, et al. Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset. Breast Cancer Res Treat. 2017; 162(1):1–10. https://doi.org/10.1007/s10549-016-4093-4 PMID: 28064383
40. Turner BM, Skinner KA, Tang P, Jackson MC, Soukiazian N, Shayne M, et al. Use of modified Magee equations and histologic criteria to predict the Oncotype DX recurrence score. Mod Pathol. 2015; 28 (7):921–31. https://doi.org/10.1038/modpathol.2015.50 PMID: 25932962
41. Kim HS, Umbricht CB, Illei PB, Cimino-Mathews A, Cho S, Chowdhury N, et al. Optimizing the Use of Gene Expression Profiling in Early-Stage Breast Cancer. J Clin Oncol. 2016; 34(36):4390–7. https://doi.org/10.1200/JCO.2016.67.7195 PMID: 27998227
42. Khoury T, Yan L, Liu S, Bshara W. Oncotype DX RT-qPCR assay for ER and PR correlation with IHC: a study of 3 different clones. Appl Immunohistochem Mol Morphol. 2015; 23(3):178–87. https://doi.org/10.1097/PAI.0000000000000078 PMID: 24992175
43. Huang BF, Boutros PC. The parameter sensitivity of random forests. BMC Bioinformatics. 2016; 17 (1):331. https://doi.org/10.1186/s12859-016-1228-x PMID: 27586051
44. Chen X, Ishwaran H. Random forests for genomic data analysis. Genomics. 2012; 99(6):323–9. https://doi.org/10.1016/j.ygeno.2012.04.003 PMID: 22546560
45. Arima N, Nishimura R, Osako T, Nishiyama Y, Fujisue M, Okumura Y, et al. A Comparison of the Hot Spot and the Average Cancer Cell Counting Methods and the Optimal Cutoff Point of the Ki-67 Index for Luminal Type Breast Cancer. Oncology. 2016; 90(1):43–50. https://doi.org/10.1159/000441525 PMID: 26613521
46. Varga Z, Cassoly E, Li Q, Oehlschlegel C, Tapia C, Lehr HA, et al. Standardization for Ki-67 assessment in moderately differentiated breast cancer. A retrospective analysis of the SAKK 28/12 study. PLoS One. 2015; 10(4):e0123435. https://doi.org/10.1371/journal.pone.0123435 PMID: 25885288
47. Ohno S, Chow LW, Sato N, Masuda N, Sasano H, Takahashi F, et al. Randomized trial of preoperative docetaxel with or without capecitabine after 4 cycles of 5-fluorouracil- epirubicin-cyclophosphamide (FEC) in early-stage breast cancer: exploratory analyses identify Ki67 as a predictive biomarker for response to neoadjuvant chemotherapy. Breast Cancer Res Treat. 2013; 142(1):69–80. https://doi.org/10.1007/s10549-013-2691-y PMID: 24122389
48. Abubakar M, Howat WJ, Daley F, Zabaglo L, McDuffus LA, Blows F, et al. High-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium. J Pathol Clin Res. 2016; 2(3):138–53. https://doi.org/10.1002/cjp2.42 PMID: 27499923
49. Mohammed ZM, McMillan DC, Elsberger B, Going JJ, Orange C, Mallon E, et al. Comparison of visual and automated assessment of Ki-67 proliferative activity and their impact on outcome in primary operable invasive ductal breast cancer. Br J Cancer. 2012; 106(2):383–8. https://doi.org/10.1038/bjc.2011. 569 PMID: 22251968
50. Howat WJ, Blows FM, Provenzano E, Brook MN, Morris L, Gazinska P, et al. Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium. J Pathol Clin Res. 2015; 1(1):18–32. https://doi.org/10.1002/cjp2.3 PMID: 27499890
51. Abubakar M, Orr N, Daley F, Coulson P, Ali HR, Blows F, et al. Prognostic value of automated KI67 scoring in breast cancer: a centralised evaluation of 8088 patients from 10 study groups. Breast Cancer Res. 2016; 18(1):104. https://doi.org/10.1186/s13058-016-0765-6 PMID: 27756439
52. Honma N, Horii R, Iwase T, Saji S, Younes M, Ito Y, et al. Ki-67 evaluation at the hottest spot predicts clinical outcome of patients with hormone receptor-positive/HER2-negative breast cancer treated with adjuvant tamoxifen monotherapy. Breast Cancer. 2015; 22(1):71–8. https://doi.org/10.1007/s12282-013-0455-5 PMID: 23479208
53. Tashima R, Nishimura R, Osako T, Nishiyama Y, Okumura Y, Nakano M, et al. Evaluation of an Optimal Cut-Off Point for the Ki-67 Index as a Prognostic Factor in Primary Breast Cancer: A Retrospective Study. PLoS One. 2015; 10(7):e0119565. https://doi.org/10.1371/journal.pone.0119565 PMID: 26177501
54. Besusparis J, Plancoulaine B, Rasmusson A, Augulis R, Green AR, Ellis IO, et al. Impact of tissue sampling on accuracy of Ki67 immunohistochemistry evaluation in breast cancer. Diagn Pathol. 2016; 11 (1):82. https://doi.org/10.1186/s13000-016-0525-z PMID: 27576949
55. Inwald EC, Klinkhammer-Schalke M, Hofstadter F, Zeman F, Koller M, Gerstenhauer M, et al. Ki-67 is a prognostic parameter in breast cancer patients: results of a large population-based cohort of a cancer registry. Breast Cancer Res Treat. 2013; 139(2):539–52. https://doi.org/10.1007/s10549-013-2560-8PMID: 23674192
56. Cass JD, Varma S, Day AG, Sangrar W, Rajput AB, Raptis LH, et al. Automated Quantitative Analysis of p53, Cyclin D1, Ki67 and pERK Expression in Breast Carcinoma Does Not Differ from Expert Pathologist Scoring and Correlates with Clinico-Pathological Characteristics. Cancers (Basel). 2012; 4 (3):725–42.
57. Sun J, Chen C, Wei W, Zheng H, Yuan J, Tu YI, et al. Associations and indications of Ki67 expression with clinicopathological parameters and molecular subtypes in invasive breast cancer: A population-based study. Oncol Lett. 2015; 10(3):1741–8. https://doi.org/10.3892/ol.2015.3461 PMID: 26622743
58. Baxter E, Gondara L, Lohrisch C, Chia S, Gelmon K, Hayes M, et al. Using proliferative markers and Oncotype DX in therapeutic decision-making for breast cancer: the B.C. experience. Curr Oncol. 2015; 22(3):192–8. https://doi.org/10.3747/co.22.2284 PMID: 26089718
59. Flanagan MB, Dabbs DJ, Brufsky AM, Beriwal S, Bhargava R. Histopathologic variables predict Oncotype DX recurrence score. Mod Pathol. 2008; 21(10):1255–61. https://doi.org/10.1038/modpathol.2008.54 PMID: 18360352
60. Wienert S, Heim D, Kotani M, Lindequist B, Stenzinger A, Ishii M, et al. CognitionMaster: an object-based image analysis framework. Diagn Pathol. 2013; 8:34. https://doi.org/10.1186/1746-1596-8-34PMID: 23445542