Conventional Pathology Versus Gene Signatures for Assessing Luminal A and B Type Breast Cancers: Results of a Prospective Cohort Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Patients
2.2. Routine Pathology Assessment
2.3. Pathological Subtyping (PS)
2.4. Molecular Subtyping (MS)
2.5. Statistical Analysis
3. Results
3.1. Patients
3.2. Pathological Subtyping Versus Molecular Subtyping Using the 80-GS Only
3.3. Comparison of Luminal A and Luminal B tumors by Molecular or Pathological Subtyping
3.4. Comparison of Luminal A and Luminal B tumors by Molecular and Pathological Subtyping
4. Discussion
Supplementary Materials
Author Contributions
Acknowledgments
Conflicts of Interest
References
- Perou, C.M.; Sørlie, T.; Eisen, M.B.; van de Rijn, M.; Jeffrey, S.S.; Rees, C.A.; Pollack, J.R.; Ross, D.T.; Johnsen, H.; Akslen, L.A.; et al. Molecular portraits of human breast tumours. Nature 2000, 406, 747–752. [Google Scholar] [CrossRef] [PubMed]
- Sorlie, T.; Perou, C.M.; Tibshirani, R.; Aas, T.; Geisler, S.; Johnson, H.; Hastie, T.; Eisen, M.B.; van de Rijn, M.; Jeffrey, S.S.; et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl. Acad. Sci. USA 2001, 98, 10869–10874. [Google Scholar] [CrossRef] [PubMed]
- Glück, S.; de Snoo, F.; Peeters, J.; Stork-Sloots, L.; Somlo, G. Molecular subtyping of early-stage breast cancer identifies a group of patients who do not benefit from neo-adjuvant chemotherapy. Breast Cancer Res. Treat. 2013, 139, 759–767. [Google Scholar] [CrossRef] [PubMed]
- Whitworth, P.; Stork-Slooks, L.; de Snoo, F.A.; Richards, P.; Rotkis, M.; Beatty, J.; Mislowsky, A.; Pellicane, J.V.; Nguyen, B.; Lee, L.; et al. Chemosensitivity predicted by BluePrint 80-Gene functional subtype and MammaPrint in the Prospective Neoadjuvant Breast Registry Symphony Trial (NBRST). Ann. Surg. Oncol. 2014, 21, 3261–3267. [Google Scholar] [CrossRef] [PubMed]
- Tang, P.; Tse, G.M. Immunohistochemical surrogates for molecular classification of breast carcinoma: A 2015 update. Arch. Pathol. Lab. Med. 2016, 140, 806–814. [Google Scholar] [CrossRef] [PubMed]
- Van’t Veer, L.J.; Dai, H.; van de Vijver, M.J.; He, Y.D.; Hart, A.A.; Mao, M.; Peterse, H.L.; van der Kooy, K.; Marton, M.J.; Witteveen, A.T.; et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002, 415, 530–536. [Google Scholar] [CrossRef] [PubMed]
- Van de Vijver, M.J.; He, Y.D.; van’t Veer, L.J.; Dai, H.; Hart, A.A.; Voskuil, D.W.; Schreiber, G.J.; Peterse, J.L.; Roberts, C.; Marton, M.J.; et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 2002, 347, 1999–2009. [Google Scholar] [CrossRef] [PubMed]
- Cardoso, F.; van’t Veer, L.J.; Bogaerts, J.; Slaets, L.; Viale, G.; Delaloge, S.; Pierga, J.Y.; Brain, E.; Causeret, S.; DeLorenzi, M.; et al. 70-gene signature as an aid to treatment decisions in early-stage breast cancer. N. Engl. J. Med. 2016, 375, 717–729. [Google Scholar] [CrossRef] [PubMed]
- Paik, S.; Shak, S.; Tang, G.; Kim, C.; Baker, J.; Cronin, M.; Baehner, F.L.; Walker, M.G.; Watson, D.; Park, T.; et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N. Engl. J. Med. 2004, 351, 2817–2826. [Google Scholar] [CrossRef] [PubMed]
- Nielsen, T.O.; Parker, J.S.; Leung, S.; Voduc, D.; Ebbert, M.; Vickery, T.; Davies, S.R.; Snider, J.; Stijleman, I.J.; Reed, J.; 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, 5222–5232. [Google Scholar] [CrossRef] [PubMed]
- Parker, J.S.; Mullins, M.; Cheang, M.C.; Leung, S.; Voduc, D.; Vickery, T.; Davies, S.; Fauron, C.; He, X.; Hu, Z.; et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 2009, 27, 1160–1167. [Google Scholar] [CrossRef] [PubMed]
- Filipits, M.; Rudas, M.; Jakesz, R.; Dubsky, P.; Fitzal, F.; Singer, C.F.; Dietze, O.; Greil, R.; Jelen, A.; Sevelda, P.; 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, 6012–6020. [Google Scholar] [CrossRef] [PubMed]
- Krijgsman, O.; Roepman, P.; Zwart, W.; Carroll, J.S.; Tian, S.; de Snoo, F.A.; Bender, R.A.; Bernards, R.; Glas, A.M. A diagnostic gene profile for molecular subtyping of breast cancer associated with treatment response. Breast Cancer Res. Treat. 2012, 133, 37–47. [Google Scholar] [CrossRef] [PubMed]
- Yao, K.; Goldschmidt, R.; Turk, M.; Wesseling, J.; Stork-Sloots, L.; de Snoo, F.; Cristofanilli, M. Molecular subtyping improves diagnostic stratification of patients with primary breast cancer into prognostically defined risk groups. Breast Cancer Res. Treat. 2015, 154, 81–88. [Google Scholar] [CrossRef] [PubMed]
- Scholzen, T.; Gerdes, J. The Ki-67 protein: From the known and the unknown. J. Cell. Physiol. 2000, 182, 311–322. [Google Scholar] [CrossRef]
- Prat, A.; Cheang, M.C.; Martín, M.; Parker, J.S.; Carrasco, E.; Caballero, R.; Tyldesley, S.; Gelmon, K.; Bernard, P.S.; Nielsen, T.O.; et al. Prognostic significance of progesterone receptor-positive tumor cells within immunohistochemically defined luminal A breast cancer. J. Clin. Oncol. 2013, 31, 203–209. [Google Scholar] [CrossRef] [PubMed]
- Ekholm, M.; Grabau, D.; Bendahl, P.O.; Bergh, J.; Elmberger, G.; Olsson, H.; Russo, L.; Viale, G.; Fernö, M. Highly reproducible results of breast cancer biomarkers when analyzed in accordance with national guidelines—A Swedish survey with central re-assesment. Acta Oncol. 2015, 54, 1040–1048. [Google Scholar] [CrossRef] [PubMed]
- Focke, C.M.; van Diest, P.J.; Decker, T. St Gallen 2015 subtyping of luminal breast cancers: Impact of different Ki67-based proliferation assessment methods. Breast Cancer Res. Treat. 2016, 159, 257–263. [Google Scholar] [CrossRef] [PubMed]
- Cheang, M.C.; Chia, S.K.; Voduc, D.; Gao, D.; Leung, S.; Snider, J.; Watson, M.; Davies, S.; Bernard, P.S.; Parker, J.S.; et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J. Natl. Cancer Inst. 2009, 101, 736–750. [Google Scholar] [CrossRef] [PubMed]
- Dowsett, M.; Nielsen, T.; A’Hern, R.; Bartlett, J.; Coombes, R.C.; Cuzick, J.; Ellis, M.; Henry, N.L.; Hugh, J.C.; Lively, T.; et al. Assessment of Ki67 in breast cancer: Recommendations from the International Ki67 in Breast Cancer working group. J. Natl. Cancer Inst. 2011, 103, 1656–1664. [Google Scholar] [CrossRef] [PubMed]
- Bueno-de-Mesquita, J.M.; Nuyten, D.S.; Wesseling, J.; van Tinteren, H.; Linn, S.C.; van de Vijver, M.J. The impact of inter-observer variation in pathological assessment of node-negative breast cancer on clinical risk assessment and patient selection for adjuvant systemic treatment. Ann. Oncol. 2010, 21, 40–47. [Google Scholar] [CrossRef] [PubMed]
- Varga, Z.; Cassoly, E.; Li, Q.; Oehlschlegel, C.; Tapia, C.; Lehr, H.A.; Klingbiel, D.; Thürlimann, B.; Ruhstaller, T. Standardization for Ki-67 Assessment in Moderately Differentiated Breast Cancer. A Retrospective Analysis of the SAKK 28/12 Study. PLoS ONE 2015, 10, e0123435. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kuijer, A.; Straver, M.; Dekker, B.D.; van Bommel, A.C.M.; Elias, S.G.; Smorenburg, C.H.; Wesseling, J.; Linn, S.C.; Rutgers, E.J.Th; Siesling, S.; et al. Impact of 70-gene signature use on adjuvant chemotherapy decisions in patients with estrogen receptor-positive early stage breast cancer: Results of a prospective cohort study. J. Clin. Oncol. 2017, 35, 2814–2819. [Google Scholar] [CrossRef] [PubMed]
- Kwaliteitsinstituut voor de Gezondheidszorg CBO en Vereniging van Integrale Kankercentra. Pathologie, Richtlijn mammacarcinoom; Kwaliteitsinstituut voor de Gezondheidszorg CBO, VvIK: Utrecht, The Netherlands, 2012; pp. 92–94. [Google Scholar]
- Hammond, M.E.H.; Hayes, D.F.; Dowsett, M.; Allred, D.C.; Hagerty, K.L.; Badve, S.; Fitzgibbons, P.L.; Francis, G.; Goldstein, N.S.; Hayes, M.; et al. American society of clinical oncology/college of American pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J. Clin. Oncol. 2010, 28, 2784–2795. [Google Scholar] [CrossRef] [PubMed]
- Wolff, A.C.; Hammond, M.E.; Hicks, D.G.; Dowsett, M.; McShane, L.M.; Allison, K.H.; Allred, D.C.; Bartlett, J.M.; Bilous, M.; Fitzgibbons, P.; et al. Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. J. Clin. Oncol. 2013, 31, 3997–4013. [Google Scholar] [CrossRef] [PubMed]
- Rstudio, version 3.2.4; For Windows; RStudio: Boston, MA, USA, 2016.
- Nguyen, B.; Cusomano, P.G.; Deck, K.; Kerlin, D.; Garcia, A.A.; Barone, J.L.; Rivera, E.; Yao, K.; de Snoo, F.A.; van den Akker, J.; et al. Comparison of Molecular subtyping with BluePrint, MammaPrint, and TargetPrint to local clinical subtyping in breast cancer patients. Ann. Surg. Oncol. 2012, 19, 3257–3263. [Google Scholar] [CrossRef] [PubMed]
- Viale, G.; de Snoo, F.; Slaets, L.; Bogaerts, J.; van’t Veer, L.; Rutgers, E.J.; Piccart-Gebhart, M.J.; Stork-Sloots, L.; Glas, A.; Russo, L.; et al. Immunohistochemical versus molecular (BluePrint and MammaPrint) subtyping of breast carcinoma. Outcome results from the EORTC 10041/BIG 3-04 MINDACT trial. Breast Cancer Res. Treat. 2017, 167, 123–131. [Google Scholar] [CrossRef] [PubMed]
- Goldhirsch, A.; Winer, E.P.; Coates, A.S.; Gelber, R.D.; Piccart-Gebhart, M.; Thürlimann, B.; Senn, H.J. Personalizing the treatment of woman with early breast cancer: Highlights of the St. Gallen International Expert consensus on the Primary Therapy of Early Breast Cancer 2013. Ann. Oncol. 2013, 24, 2206–2223. [Google Scholar] [CrossRef] [PubMed]
- Goldhirsch, A.; Ingle, J.N.; Gelber, R.D.; Coates, A.S.; Thürlimann, B.; Senn, H.J. Thresholds for therapies: Highlights of the St. Gallen International Expert Consensus on the primary therapy of early breast cancer, 2009. Ann. Oncol. 2009, 20, 1319–1329. [Google Scholar] [CrossRef] [PubMed]
- Goldhirsch, A.; Wood, W.C.; Coates, A.S.; Gelber, R.D.; Thürlimann, B.; Senn, H.J. 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, 1736–1747. [Google Scholar] [CrossRef] [PubMed]
- Coates, A.S.; Winer, E.P.; Goldhirsch, A.; Gelber, R.D.; Gnant, M.; Piccart-Gebhart, M.; Thürlimann, B.; Senn, H.J. Tailoring therapies—Improving the management of early breast cancer: St. Gallen international Expert consensus on the Primary Therapy or Early Breast Cancer 2015. Ann. Oncol. 2015, 26, 1533–1546. [Google Scholar] [CrossRef] [PubMed]
- Urriticoechea, A.; Smith, I.E.; Dowsett, M. Proliferation marker Ki-67 in early stage breast cancer. J. Clin. Oncol. 2005, 23, 7212–7220. [Google Scholar] [CrossRef] [PubMed]
- Rakha, E.A.; Ellis, I.O. An overview of assessment of prognostic and predictive factors in breast cancer needle core biopsy specimens. J. Clin. Pathol. 2007, 60, 1300–1306. [Google Scholar] [CrossRef] [PubMed]
- Whitworth, P.; Beitsch, P.; Mislowsky, A.; Pellicane, J.V.; Nash, C.; Murray, M.; Lee, L.A.; Dul, C.L.; Rotkis, M.; Baron, P.; et al. Chemosensitivity and endocrine sensitivity in clinical luminal breast cancer patient in the Prospective Neoadjuvant Breast Registry Symphony Trial (NBRST) predicted by molecular subtyping. Ann. Surg. Oncol. 2017, 24, 669–675. [Google Scholar] [CrossRef] [PubMed]
- Beitsch, P.; Whitworth, P.; Baron, P.; Rotkis, M.C.; Mislowsky, A.M.; Richards, P.D.; Murray, M.K.; Pellicane, J.V.; Dul, C.L.; Nash, C.H.; et al. Pertuzumab/Trastuzumab/CT versus Trastuzumab/CT therapy for HER2+ breast cancer: Results from the Prospective Neoadjuvant Breast Registry Symphony Trial (NBRST). Ann. Surg. Oncol. 2017, 24, 2539–2546. [Google Scholar] [CrossRef] [PubMed]
Characteristics | Total n = 595 (%, valid) | Subset Ki67 n = 185 (%, valid) |
---|---|---|
Age, years, median | 58 | 57 |
(range) | (35–80) | (35–74) |
Pathological T-stage | ||
T1 | 480 (80.6) | 153 (82.7) |
T2 | 114 (19.2) | 31 (16.8) |
T3 | 1 (0.2) | 1 (0.5) |
Pathological N-stage | ||
N0(i+) | 496 (84.5) | 164 (89.6) |
N1mi | 54 (9.2) | 11 (6) |
N1(a-c) | 37 (6.3) | 8 (4.4) |
Nx | 8 | 2 |
Tumor grade | ||
1 | 86 (14.5) | 30 (16.3) |
2 | 438 (73.7) | 125 (67.9) |
3 | 70 (11.8) | 29 (15.8) |
Unknown | 1 | 1 |
ER status | ||
ER+ | 595 (100) | 185 (100) |
PR status | ||
PR+ | 518 (87.2) | 163 (88.6) |
PR- | 76 (12.8) | 21 (11.4) |
Unknown | 1 | 1 |
HER2 status | ||
HER2+ | 12 (2) | 2 (1.1) |
HER2− | 576 (98) | 182 (98.9) |
Unknown | 7 | 1 |
Ki67 Level | ||
<20%, low | 153 (83) | 153 (83) |
≥20%, high | 32 (17) | 32 (17) |
Not assessed | 410 | - |
70-GS | ||
Low risk | 349 (59) | 109 (59) |
High risk | 246 (41) | 76 (41) |
Molecular Subtypes | ||||
---|---|---|---|---|
Clinical Subtypes | 80-GS Luminal (%) | 80-GS HER2 (%) | 80-GS Basal (%) | Total |
ER+/PR+, HER2− | 567 (98) | 4 (1) | 5 (1) | 576 |
ER+/PR+, HER2+ | 9 (75) | 3 (25) | 0 (0) | 12 |
Total | 576 | 7 | 5 | 588 |
Molecular Subtypes | |||||
---|---|---|---|---|---|
Clinical Subtypes | Luminal A (%) | Luminal B (%) | HER2 (%) | Basal (%) | Total |
ER+, PR ≥ 20%, HER2−, BR I/II | 290 (65) | 154 (34) | 4 (1) | - | 448 |
ER+ & (PR < 20%, or HER2+ or BR III) | 52 (38) | 78 (57) | 3 (2) | 5 (3) | 138 |
Total | 342 | 232 | 7 | 5 | 586 |
Molecular Subtypes | |||||
---|---|---|---|---|---|
Clinical Subtypes | Luminal A (%) | Luminal B (%) | HER2 (%) | Basal (%) | Total |
ER+, PR ≥ 20%, HER2−, Ki67 < 20% | 96 (64) | 52 (34) | 3 (2) | 0 | 151 |
ER+ & (PR < 20%, or HER2+ or Ki67 ≥ 20%) | 11 (32) | 22 (65) | 0 | 1 (3) | 34 |
Total | 107 | 74 | 3 | 1 | 185 |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Van Steenhoven, J.E.C.; Kuijer, A.; Van Diest, P.J.; Van Gorp, J.M.; Straver, M.; Elias, S.G.; Wesseling, J.; Rutgers, E.; Timmer-Bonte, J.N.H.; Nieboer, P.; et al. Conventional Pathology Versus Gene Signatures for Assessing Luminal A and B Type Breast Cancers: Results of a Prospective Cohort Study. Genes 2018, 9, 261. https://doi.org/10.3390/genes9050261
Van Steenhoven JEC, Kuijer A, Van Diest PJ, Van Gorp JM, Straver M, Elias SG, Wesseling J, Rutgers E, Timmer-Bonte JNH, Nieboer P, et al. Conventional Pathology Versus Gene Signatures for Assessing Luminal A and B Type Breast Cancers: Results of a Prospective Cohort Study. Genes. 2018; 9(5):261. https://doi.org/10.3390/genes9050261
Chicago/Turabian StyleVan Steenhoven, Julia E.C., Anne Kuijer, Paul J. Van Diest, Joost M. Van Gorp, Marieke Straver, Sjoerd G. Elias, Jelle Wesseling, Emiel Rutgers, Johanna N.H. Timmer-Bonte, Peter Nieboer, and et al. 2018. "Conventional Pathology Versus Gene Signatures for Assessing Luminal A and B Type Breast Cancers: Results of a Prospective Cohort Study" Genes 9, no. 5: 261. https://doi.org/10.3390/genes9050261