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Published in: Journal of Translational Medicine 1/2016

Open Access 01-12-2016 | Research

Testing chemotherapy efficacy in HER2 negative breast cancer using patient-derived spheroids

Authors: Kathrin Halfter, Oliver Hoffmann, Nina Ditsch, Mareike Ahne, Frank Arnold, Stefan Paepke, Dieter Grab, Ingo Bauerfeind, Barbara Mayer

Published in: Journal of Translational Medicine | Issue 1/2016

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Abstract

Background

Targeted anti-HER2 therapy has greatly improved the prognosis for many breast cancer patients. However, treatment for HER2 negative disease is currently still selected from a multitude of untargeted chemotherapeutic treatment options. A predictive test was developed using patient-derived spheroids to identify the most effective therapy for patients with HER2 negative breast cancer of all stages, for clinically relevant subgroups, as well as individual patients.

Methods

Tumor samples from 120 HER2 negative patients obtained through biopsy or surgical excision were tested in the breast cancer spheroid model using scaffold-free cell culture. Similarly, spheroids were also generated from established HER2 negative breast cancer cell lines T-47D, MCF7, HCC1143, and HCC1937 to compare treatment efficacy of heterogeneous cell populations from patient tumor tissue with homogeneous cell lines. Spheroids were treated in vitro with guideline-recommended compounds. Treatment mediated impact on cell survival was subsequently quantified using an ATP assay.

Results

Differences were observed in the metabolic activity of the untreated spheroids, whereby cell lines consistently achieved higher values compared to tissue spheroids (p < 0.001). A higher number of cells per spheroid correlated with a higher basal metabolic activity in tissue-derived spheroids (p < 0.01), while the opposite was observed for cell line spheroids (p < 0.01). Recurrent tumors showed a higher mean vitality (p < 0.01) compared to primary tumors. Except for taxanes, treatment efficacy for most tested compounds differed significantly between breast cancer tissue spheroids and breast cancer cell lines. Overall a high variability in treatment response in vitro was seen in the tissue spheroids regardless of the tested substances. A greater response to anthracycline/docetaxel was observed for hormone receptor negative samples (p < 0.01). A higher response to 5-FU (p < 0.01) and anthracycline (p < 0.05) was seen in high grade tumors. Smaller tumor size and negative lymph node status were both associated with a higher treatment efficacy to anthracycline treatment combined with 5-FU (cT1/2 vs cT3/4, p = 0.035, cN+ vs cN−, p < 0.05).

Conclusions

The tissue spheroid model reflects current guideline treatment recommendations for HER2 negative breast cancer, whereas tested cell lines did not. This model represents a unique diagnostic method to select the most effective therapy out of several equivalent treatment options.
Literature
1.
go back to reference Senkus E, Kyriakides S, Ohno S, Penault-Llorca F, Poortmans P, Rutgers E, Zackrisson S, Cardoso F, Committee EG. Primary breast cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2015;26(Suppl 5):v8–30.CrossRefPubMed Senkus E, Kyriakides S, Ohno S, Penault-Llorca F, Poortmans P, Rutgers E, Zackrisson S, Cardoso F, Committee EG. Primary breast cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2015;26(Suppl 5):v8–30.CrossRefPubMed
2.
go back to reference Drukker CA, van den Hout HC, Sonke GS, Brain E, Bonnefoi H, Cardoso F, Goldhirsch A, Harbeck N, Honkoop AH, Koornstra RH, et al. Risk estimations and treatment decisions in early stage breast cancer: agreement among oncologists and the impact of the 70-gene signature. Eur J Cancer. 2014;50(6):1045–54.CrossRefPubMed Drukker CA, van den Hout HC, Sonke GS, Brain E, Bonnefoi H, Cardoso F, Goldhirsch A, Harbeck N, Honkoop AH, Koornstra RH, et al. Risk estimations and treatment decisions in early stage breast cancer: agreement among oncologists and the impact of the 70-gene signature. Eur J Cancer. 2014;50(6):1045–54.CrossRefPubMed
3.
go back to reference Gonzalez-Angulo AM, Morales-Vasquez F, Hortobagyi GN. Overview of resistance to systemic therapy in patients with breast cancer. Adv Exp Med Biol. 2007;608:1–22.CrossRefPubMed Gonzalez-Angulo AM, Morales-Vasquez F, Hortobagyi GN. Overview of resistance to systemic therapy in patients with breast cancer. Adv Exp Med Biol. 2007;608:1–22.CrossRefPubMed
4.
go back to reference Henry NL, Hayes DF, Ramsey SD, Hortobagyi GN, Barlow WE, Gralow JR. Promoting quality and evidence-based care in early-stage breast cancer follow-up. J Natl Cancer Inst. 2014;106(4):dju034.CrossRefPubMedPubMedCentral Henry NL, Hayes DF, Ramsey SD, Hortobagyi GN, Barlow WE, Gralow JR. Promoting quality and evidence-based care in early-stage breast cancer follow-up. J Natl Cancer Inst. 2014;106(4):dju034.CrossRefPubMedPubMedCentral
5.
go back to reference Eccles SA, Aboagye EO, Ali S, Anderson AS, Armes J, Berditchevski F, Blaydes JP, Brennan K, Brown NJ, Bryant HE, et al. Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer. Breast Cancer Res. 2013;15(5):R92.CrossRefPubMedPubMedCentral Eccles SA, Aboagye EO, Ali S, Anderson AS, Armes J, Berditchevski F, Blaydes JP, Brennan K, Brown NJ, Bryant HE, et al. Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer. Breast Cancer Res. 2013;15(5):R92.CrossRefPubMedPubMedCentral
6.
go back to reference Stahel R, Bogaerts J, Ciardiello F, de Ruysscher D, Dubsky P, Ducreux M, Finn S, Laurent-Puig P, Peters S, Piccart M et al. Optimising translational oncology in clinical practice: Strategies to accelerate progress in drug development. Cancer Treat Rev. 2014. Stahel R, Bogaerts J, Ciardiello F, de Ruysscher D, Dubsky P, Ducreux M, Finn S, Laurent-Puig P, Peters S, Piccart M et al. Optimising translational oncology in clinical practice: Strategies to accelerate progress in drug development. Cancer Treat Rev. 2014.
7.
go back to reference Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thurlimann B, Senn HJ, Panel M. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International expert consensus on the primary therapy of early breast cancer 2013. Annals of oncology: official journal of the European Society for Medical Oncology/ESMO. 2013;24(9):2206–23.CrossRef Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thurlimann B, Senn HJ, Panel M. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International expert consensus on the primary therapy of early breast cancer 2013. Annals of oncology: official journal of the European Society for Medical Oncology/ESMO. 2013;24(9):2206–23.CrossRef
8.
go back to reference Weigel MT, Dowsett M. Current and emerging biomarkers in breast cancer: prognosis and prediction. Endocr Relat Cancer. 2010;17(4):R245–62.CrossRefPubMed Weigel MT, Dowsett M. Current and emerging biomarkers in breast cancer: prognosis and prediction. Endocr Relat Cancer. 2010;17(4):R245–62.CrossRefPubMed
9.
go back to reference Graham LJ, Shupe MP, Schneble EJ, Flynt FL, Clemenshaw MN, Kirkpatrick AD, Gallagher C, Nissan A, Henry L, Stojadinovic A, et al. Current approaches and challenges in monitoring treatment responses in breast cancer. J Cancer. 2014;5(1):58–68.CrossRefPubMedPubMedCentral Graham LJ, Shupe MP, Schneble EJ, Flynt FL, Clemenshaw MN, Kirkpatrick AD, Gallagher C, Nissan A, Henry L, Stojadinovic A, et al. Current approaches and challenges in monitoring treatment responses in breast cancer. J Cancer. 2014;5(1):58–68.CrossRefPubMedPubMedCentral
10.
go back to reference Petrelli F, Barni S. Surrogate endpoints in metastatic breast cancer treated with targeted therapies: an analysis of the first-line phase III trials. Med Oncol. 2014;31(1):776.CrossRefPubMed Petrelli F, Barni S. Surrogate endpoints in metastatic breast cancer treated with targeted therapies: an analysis of the first-line phase III trials. Med Oncol. 2014;31(1):776.CrossRefPubMed
11.
go back to reference Chung C, Christianson M. Predictive and prognostic biomarkers with therapeutic targets in breast, colorectal, and non-small cell lung cancers: a systemic review of current development, evidence, and recommendation. J Oncol Pharm Pract. 2014;20(1):11–28.CrossRefPubMed Chung C, Christianson M. Predictive and prognostic biomarkers with therapeutic targets in breast, colorectal, and non-small cell lung cancers: a systemic review of current development, evidence, and recommendation. J Oncol Pharm Pract. 2014;20(1):11–28.CrossRefPubMed
12.
go back to reference Rutherford T, Orr J Jr, Grendys E Jr, Edwards R, Krivak TC, Holloway R, Moore RG, Puls L, Tillmanns T, Schink JC, et al. A prospective study evaluating the clinical relevance of a chemoresponse assay for treatment of patients with persistent or recurrent ovarian cancer. Gynecol Oncol. 2013;131(2):362–7.CrossRefPubMed Rutherford T, Orr J Jr, Grendys E Jr, Edwards R, Krivak TC, Holloway R, Moore RG, Puls L, Tillmanns T, Schink JC, et al. A prospective study evaluating the clinical relevance of a chemoresponse assay for treatment of patients with persistent or recurrent ovarian cancer. Gynecol Oncol. 2013;131(2):362–7.CrossRefPubMed
13.
go back to reference Houssami N, Macaskill P, von Minckwitz G, Marinovich ML, Mamounas E. Meta-analysis of the association of breast cancer subtype and pathologic complete response to neoadjuvant chemotherapy. Eur J Cancer. 2012;48(18):3342–54.CrossRefPubMed Houssami N, Macaskill P, von Minckwitz G, Marinovich ML, Mamounas E. Meta-analysis of the association of breast cancer subtype and pathologic complete response to neoadjuvant chemotherapy. Eur J Cancer. 2012;48(18):3342–54.CrossRefPubMed
14.
go back to reference Tan MC, Al Mushawah F, Gao F, Aft RL, Gillanders WE, Eberlein TJ, Margenthaler JA. Predictors of complete pathological response after neoadjuvant systemic therapy for breast cancer. Am J Surg. 2009;198(4):520–5.CrossRefPubMedPubMedCentral Tan MC, Al Mushawah F, Gao F, Aft RL, Gillanders WE, Eberlein TJ, Margenthaler JA. Predictors of complete pathological response after neoadjuvant systemic therapy for breast cancer. Am J Surg. 2009;198(4):520–5.CrossRefPubMedPubMedCentral
15.
go back to reference Angelucci D, Tinari N, Grassadonia A, Cianchetti E, Ausili-Cefaro G, Iezzi L, Zilli M, Grossi S, Ursini LA, Scognamiglio MT, et al. Long-term outcome of neoadjuvant systemic therapy for locally advanced breast cancer in routine clinical practice. J Cancer Res Clin Oncol. 2013;139(2):269–80.CrossRefPubMedPubMedCentral Angelucci D, Tinari N, Grassadonia A, Cianchetti E, Ausili-Cefaro G, Iezzi L, Zilli M, Grossi S, Ursini LA, Scognamiglio MT, et al. Long-term outcome of neoadjuvant systemic therapy for locally advanced breast cancer in routine clinical practice. J Cancer Res Clin Oncol. 2013;139(2):269–80.CrossRefPubMedPubMedCentral
16.
go back to reference Prat A, Lluch A, Albanell J, Barry WT, Fan C, Chacon JI, Parker JS, Calvo L, Plazaola A, Arcusa A, et al. Predicting response and survival in chemotherapy-treated triple-negative breast cancer. Br J Cancer. 2014;111(8):1532–41.CrossRefPubMedPubMedCentral Prat A, Lluch A, Albanell J, Barry WT, Fan C, Chacon JI, Parker JS, Calvo L, Plazaola A, Arcusa A, et al. Predicting response and survival in chemotherapy-treated triple-negative breast cancer. Br J Cancer. 2014;111(8):1532–41.CrossRefPubMedPubMedCentral
17.
go back to reference Liu Y, Liu Q, Wang T, Bian L, Zhang S, Hu H, Li S, Hu Z, Wu S, Liu B, et al. Circulating tumor cells in HER2− positive metastatic breast cancer patients: a valuable prognostic and predictive biomarker. BMC Cancer. 2013;13:202.CrossRefPubMedPubMedCentral Liu Y, Liu Q, Wang T, Bian L, Zhang S, Hu H, Li S, Hu Z, Wu S, Liu B, et al. Circulating tumor cells in HER2− positive metastatic breast cancer patients: a valuable prognostic and predictive biomarker. BMC Cancer. 2013;13:202.CrossRefPubMedPubMedCentral
18.
go back to reference Schroth W, Goetz MP, Hamann U, Fasching PA, Schmidt M, Winter S, Fritz P, Simon W, Suman VJ, Ames MM, et al. Association between CYP2D6 polymorphisms and outcomes among women with early stage breast cancer treated with tamoxifen. JAMA: J Am Med Assoc. 2009;302(13):1429–36.CrossRef Schroth W, Goetz MP, Hamann U, Fasching PA, Schmidt M, Winter S, Fritz P, Simon W, Suman VJ, Ames MM, et al. Association between CYP2D6 polymorphisms and outcomes among women with early stage breast cancer treated with tamoxifen. JAMA: J Am Med Assoc. 2009;302(13):1429–36.CrossRef
19.
go back to reference Brown JR, Wimberly H, Lannin DR, Nixon C, Rimm DL, Bossuyt V. Multiplexed quantitative analysis of CD3, CD8, and CD20 predicts response to neoadjuvant chemotherapy in breast cancer. Clin Cancer Res. 2014;20(23):5995–6005.CrossRefPubMedPubMedCentral Brown JR, Wimberly H, Lannin DR, Nixon C, Rimm DL, Bossuyt V. Multiplexed quantitative analysis of CD3, CD8, and CD20 predicts response to neoadjuvant chemotherapy in breast cancer. Clin Cancer Res. 2014;20(23):5995–6005.CrossRefPubMedPubMedCentral
20.
go back to reference Connolly RM, Leal JP, Goetz MP, Zhang Z, Zhou XC, Jacobs LK, Mhlanga J, JH O, Carpenter J, Storniolo AM, et al. TBCRC 008: early change in 18F-FDG uptake on PET predicts response to preoperative systemic therapy in human epidermal growth factor receptor 2-negative primary operable breast cancer. J Nucl Med. 2015;56(1):31–7.CrossRefPubMedPubMedCentral Connolly RM, Leal JP, Goetz MP, Zhang Z, Zhou XC, Jacobs LK, Mhlanga J, JH O, Carpenter J, Storniolo AM, et al. TBCRC 008: early change in 18F-FDG uptake on PET predicts response to preoperative systemic therapy in human epidermal growth factor receptor 2-negative primary operable breast cancer. J Nucl Med. 2015;56(1):31–7.CrossRefPubMedPubMedCentral
21.
go back to reference 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.CrossRefPubMedPubMedCentral 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.CrossRefPubMedPubMedCentral
22.
go back to reference Gupta A, Mutebi M, Bardia A. Gene-expression-based predictors for breast cancer. Ann Surg Oncol. 2015. Gupta A, Mutebi M, Bardia A. Gene-expression-based predictors for breast cancer. Ann Surg Oncol. 2015.
23.
go back to reference von Minckwitz G, Untch M, Blohmer JU, Costa SD, Eidtmann H, Fasching PA, Gerber B, Eiermann W, Hilfrich J, Huober J, et al. Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. J Clin Oncol. 2012;30(15):1796–804.CrossRef von Minckwitz G, Untch M, Blohmer JU, Costa SD, Eidtmann H, Fasching PA, Gerber B, Eiermann W, Hilfrich J, Huober J, et al. Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. J Clin Oncol. 2012;30(15):1796–804.CrossRef
24.
go back to reference Harbeck N, Schmitt M, Meisner C, Friedel C, Untch M, Schmidt M, Sweep CG, Lisboa BW, Lux MP, Beck T, et al. Ten-year analysis of the prospective multicentre chemo-n0 trial validates American Society Of Clinical Oncology (ASCO)-recommended biomarkers uPA and PAI-1 for therapy decision making in node-negative breast cancer patients. Eur J Cancer. 2013;49(8):1825–35.CrossRefPubMed Harbeck N, Schmitt M, Meisner C, Friedel C, Untch M, Schmidt M, Sweep CG, Lisboa BW, Lux MP, Beck T, et al. Ten-year analysis of the prospective multicentre chemo-n0 trial validates American Society Of Clinical Oncology (ASCO)-recommended biomarkers uPA and PAI-1 for therapy decision making in node-negative breast cancer patients. Eur J Cancer. 2013;49(8):1825–35.CrossRefPubMed
25.
go back to reference Albain KS, Barlow WE, Shak S, Hortobagyi GN, Livingston RB, Yeh IT, Ravdin P, Bugarini R, Baehner FL, Davidson NE, 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.CrossRefPubMedPubMedCentral Albain KS, Barlow WE, Shak S, Hortobagyi GN, Livingston RB, Yeh IT, Ravdin P, Bugarini R, Baehner FL, Davidson NE, 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.CrossRefPubMedPubMedCentral
26.
go back to reference Voskoglou-Nomikos T, Pater JL, Seymour L. Clinical predictive value of the in vitro cell line, human xenograft, and mouse allograft preclinical cancer models. Clin Cancer Res. 2003;9(11):4227–39.PubMed Voskoglou-Nomikos T, Pater JL, Seymour L. Clinical predictive value of the in vitro cell line, human xenograft, and mouse allograft preclinical cancer models. Clin Cancer Res. 2003;9(11):4227–39.PubMed
28.
go back to reference Becher OJ, Holland EC. Genetically engineered models have advantages over xenografts for preclinical studies. Cancer Res. 2006;66(7):3355–8 (discussion 3358–3359).CrossRefPubMed Becher OJ, Holland EC. Genetically engineered models have advantages over xenografts for preclinical studies. Cancer Res. 2006;66(7):3355–8 (discussion 3358–3359).CrossRefPubMed
30.
go back to reference Bock BC, Stein U, Schmitt CA, Augustin HG. Mouse models of human cancer. Cancer Res. 2014;74(17):4671–5.CrossRefPubMed Bock BC, Stein U, Schmitt CA, Augustin HG. Mouse models of human cancer. Cancer Res. 2014;74(17):4671–5.CrossRefPubMed
31.
go back to reference Whittle JR, Lewis MT, Lindeman GJ, Visvader JE. Patient-derived xenograft models of breast cancer and their predictive power. Breast Cancer Res. 2015;17:17.CrossRefPubMedPubMedCentral Whittle JR, Lewis MT, Lindeman GJ, Visvader JE. Patient-derived xenograft models of breast cancer and their predictive power. Breast Cancer Res. 2015;17:17.CrossRefPubMedPubMedCentral
32.
33.
go back to reference Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, Clark L, Bayani N, Coppe JP, Tong F, et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell. 2006;10(6):515–27.CrossRefPubMedPubMedCentral Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, Clark L, Bayani N, Coppe JP, Tong F, et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell. 2006;10(6):515–27.CrossRefPubMedPubMedCentral
34.
go back to reference Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, Pietenpol JA. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Investig. 2011;121(7):2750–67.CrossRefPubMedPubMedCentral Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, Pietenpol JA. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Investig. 2011;121(7):2750–67.CrossRefPubMedPubMedCentral
35.
go back to reference Kenny PA, Lee GY, Myers CA, Neve RM, Semeiks JR, Spellman PT, Lorenz K, Lee EH, Barcellos-Hoff MH, Petersen OW, et al. The morphologies of breast cancer cell lines in three-dimensional assays correlate with their profiles of gene expression. Mol Oncol. 2007;1(1):84–96.CrossRefPubMedPubMedCentral Kenny PA, Lee GY, Myers CA, Neve RM, Semeiks JR, Spellman PT, Lorenz K, Lee EH, Barcellos-Hoff MH, Petersen OW, et al. The morphologies of breast cancer cell lines in three-dimensional assays correlate with their profiles of gene expression. Mol Oncol. 2007;1(1):84–96.CrossRefPubMedPubMedCentral
36.
go back to reference Cifani P, Kirik U, Waldemarson S, James P. Molecular portrait of breast-cancer-derived cell lines reveals poor similarity with tumors. J Proteome Res. 2015;14(7):2819–27.CrossRefPubMed Cifani P, Kirik U, Waldemarson S, James P. Molecular portrait of breast-cancer-derived cell lines reveals poor similarity with tumors. J Proteome Res. 2015;14(7):2819–27.CrossRefPubMed
38.
go back to reference Theodoraki MA, Rezende CO Jr., Chantarasriwong O, Corben AD, Theodorakis EA, Alpaugh ML. Spontaneously-forming spheroids as an in vitro cancer cell model for anticancer drug screening. Oncotarget. 2015. Theodoraki MA, Rezende CO Jr., Chantarasriwong O, Corben AD, Theodorakis EA, Alpaugh ML. Spontaneously-forming spheroids as an in vitro cancer cell model for anticancer drug screening. Oncotarget. 2015.
39.
go back to reference Hoffmann OI, Ilmberger C, Magosch S, Joka M, Jauch KW, Mayer B. Impact of the spheroid model complexity on drug response. J Biotechnol. 2015. Hoffmann OI, Ilmberger C, Magosch S, Joka M, Jauch KW, Mayer B. Impact of the spheroid model complexity on drug response. J Biotechnol. 2015.
40.
go back to reference Bartlett R, Everett W, Lim S, Natasha G, Loizidou M, Jell G, Tan A, Seifalian AM. Personalized in vitro cancer modeling—fantasy or reality? Transl Oncol. 2014;7(6):657–64.CrossRefPubMedPubMedCentral Bartlett R, Everett W, Lim S, Natasha G, Loizidou M, Jell G, Tan A, Seifalian AM. Personalized in vitro cancer modeling—fantasy or reality? Transl Oncol. 2014;7(6):657–64.CrossRefPubMedPubMedCentral
41.
go back to reference Sachs N, Clevers H. Organoid cultures for the analysis of cancer phenotypes. Curr Opin Genet Dev. 2014;24:68–73.CrossRefPubMed Sachs N, Clevers H. Organoid cultures for the analysis of cancer phenotypes. Curr Opin Genet Dev. 2014;24:68–73.CrossRefPubMed
42.
go back to reference Herrmann D, Conway JR, Vennin C, Magenau A, Hughes WG, Morton JP, Timpson P. Three-dimensional cancer models mimic cell-matrix interactions in the tumour microenvironment. Carcinogenesis. 2014. Herrmann D, Conway JR, Vennin C, Magenau A, Hughes WG, Morton JP, Timpson P. Three-dimensional cancer models mimic cell-matrix interactions in the tumour microenvironment. Carcinogenesis. 2014.
43.
go back to reference Vidi PA, Bissell MJ, Lelievre SA. Three-dimensional culture of human breast epithelial cells: the how and the why. Methods Mol Biol. 2013;945:193–219.CrossRefPubMedPubMedCentral Vidi PA, Bissell MJ, Lelievre SA. Three-dimensional culture of human breast epithelial cells: the how and the why. Methods Mol Biol. 2013;945:193–219.CrossRefPubMedPubMedCentral
44.
go back to reference Kunz-Schughart LA, Freyer JP, Hofstaedter F, Ebner R. The use of 3-D cultures for high-throughput screening: the multicellular spheroid model. J Biomol Screen. 2004;9(4):273–85.CrossRefPubMed Kunz-Schughart LA, Freyer JP, Hofstaedter F, Ebner R. The use of 3-D cultures for high-throughput screening: the multicellular spheroid model. J Biomol Screen. 2004;9(4):273–85.CrossRefPubMed
45.
go back to reference Evensen NA, Li J, Yang J, Yu X, Sampson NS, Zucker S, Cao J. Development of a high-throughput three-dimensional invasion assay for anti-cancer drug discovery. PLoS One. 2013;8(12):e82811.CrossRefPubMedPubMedCentral Evensen NA, Li J, Yang J, Yu X, Sampson NS, Zucker S, Cao J. Development of a high-throughput three-dimensional invasion assay for anti-cancer drug discovery. PLoS One. 2013;8(12):e82811.CrossRefPubMedPubMedCentral
46.
go back to reference Qvarnstrom OF, Simonsson M, Carlsson J, Tran TA. Effects of affinity on binding of HER2-targeting Affibody molecules: model experiments in breast cancer spheroids. Int J Oncol. 2011;39(2):353–9.PubMed Qvarnstrom OF, Simonsson M, Carlsson J, Tran TA. Effects of affinity on binding of HER2-targeting Affibody molecules: model experiments in breast cancer spheroids. Int J Oncol. 2011;39(2):353–9.PubMed
47.
go back to reference Kerr DJ, Wheldon TE, Kerr AM, Kaye SB. In vitro chemosensitivity testing using the multicellular tumor spheroid model. Cancer Drug Deliv. 1987;4(2):63–74.CrossRefPubMed Kerr DJ, Wheldon TE, Kerr AM, Kaye SB. In vitro chemosensitivity testing using the multicellular tumor spheroid model. Cancer Drug Deliv. 1987;4(2):63–74.CrossRefPubMed
48.
go back to reference Campbell JJ, Hume RD, Watson CJ. Engineering mammary gland in vitro models for cancer diagnostics and therapy. Mol Pharm. 2014;11(7):1971–81.CrossRefPubMed Campbell JJ, Hume RD, Watson CJ. Engineering mammary gland in vitro models for cancer diagnostics and therapy. Mol Pharm. 2014;11(7):1971–81.CrossRefPubMed
49.
go back to reference Khaitan D, Dwarakanath BS. Multicellular spheroids as an in vitro model in experimental oncology: applications in translational medicine. Expert Opin Drug Discov. 2006;1(7):663–75.CrossRefPubMed Khaitan D, Dwarakanath BS. Multicellular spheroids as an in vitro model in experimental oncology: applications in translational medicine. Expert Opin Drug Discov. 2006;1(7):663–75.CrossRefPubMed
50.
go back to reference Hirschhaeuser F, Menne H, Dittfeld C, West J, Mueller-Klieser W, Kunz-Schughart LA. Multicellular tumor spheroids: an underestimated tool is catching up again. J Biotechnol. 2010;148(1):3–15.CrossRefPubMed Hirschhaeuser F, Menne H, Dittfeld C, West J, Mueller-Klieser W, Kunz-Schughart LA. Multicellular tumor spheroids: an underestimated tool is catching up again. J Biotechnol. 2010;148(1):3–15.CrossRefPubMed
51.
go back to reference Halfter K, Ditsch N, Kolberg HC, Fischer H, Hauzenberger T, von Koch FE, Bauerfeind I, von Minckwitz G, Funke I, Crispin A, et al. Prospective cohort study using the breast cancer spheroid model as a predictor for response to neoadjuvant therapy—the SpheroNEO study. BMC Cancer. 2015;15:519.CrossRefPubMedPubMedCentral Halfter K, Ditsch N, Kolberg HC, Fischer H, Hauzenberger T, von Koch FE, Bauerfeind I, von Minckwitz G, Funke I, Crispin A, et al. Prospective cohort study using the breast cancer spheroid model as a predictor for response to neoadjuvant therapy—the SpheroNEO study. BMC Cancer. 2015;15:519.CrossRefPubMedPubMedCentral
52.
go back to reference Soule HD, Vazguez J, Long A, Albert S, Brennan M. A human cell line from a pleural effusion derived from a breast carcinoma. J Natl Cancer Inst. 1973;51(5):1409–16.PubMed Soule HD, Vazguez J, Long A, Albert S, Brennan M. A human cell line from a pleural effusion derived from a breast carcinoma. J Natl Cancer Inst. 1973;51(5):1409–16.PubMed
53.
go back to reference Keydar I, Chen L, Karby S, Weiss FR, Delarea J, Radu M, Chaitcik S, Brenner HJ. Establishment and characterization of a cell line of human breast carcinoma origin. Eur J Cancer. 1979;15(5):659–70.CrossRefPubMed Keydar I, Chen L, Karby S, Weiss FR, Delarea J, Radu M, Chaitcik S, Brenner HJ. Establishment and characterization of a cell line of human breast carcinoma origin. Eur J Cancer. 1979;15(5):659–70.CrossRefPubMed
54.
go back to reference Gazdar AF, Kurvari V, Virmani A, Gollahon L, Sakaguchi M, Westerfield M, Kodagoda D, Stasny V, Cunningham HT, Wistuba II, et al. Characterization of paired tumor and non-tumor cell lines established from patients with breast cancer. Int J Cancer. 1998;78(6):766–74.CrossRefPubMed Gazdar AF, Kurvari V, Virmani A, Gollahon L, Sakaguchi M, Westerfield M, Kodagoda D, Stasny V, Cunningham HT, Wistuba II, et al. Characterization of paired tumor and non-tumor cell lines established from patients with breast cancer. Int J Cancer. 1998;78(6):766–74.CrossRefPubMed
55.
go back to reference Tomlinson GE, Chen TT, Stastny VA, Virmani AK, Spillman MA, Tonk V, Blum JL, Schneider NR, Wistuba II, Shay JW, et al. Characterization of a breast cancer cell line derived from a germ-line BRCA1 mutation carrier. Cancer Res. 1998;58(15):3237–42.PubMed Tomlinson GE, Chen TT, Stastny VA, Virmani AK, Spillman MA, Tonk V, Blum JL, Schneider NR, Wistuba II, Shay JW, et al. Characterization of a breast cancer cell line derived from a germ-line BRCA1 mutation carrier. Cancer Res. 1998;58(15):3237–42.PubMed
56.
go back to reference Esposito A, Criscitiello C, Curigliano G. Highlights from the 14(th) St Gallen International Breast Cancer Conference 2015 in Vienna: Dealing with classification, prognostication, and prediction refinement to personalize the treatment of patients with early breast cancer. Ecancermedicalscience. 2015;9:518.PubMedPubMedCentral Esposito A, Criscitiello C, Curigliano G. Highlights from the 14(th) St Gallen International Breast Cancer Conference 2015 in Vienna: Dealing with classification, prognostication, and prediction refinement to personalize the treatment of patients with early breast cancer. Ecancermedicalscience. 2015;9:518.PubMedPubMedCentral
57.
go back to reference Gradishar WJ, Anderson BO, Blair SL, Burstein HJ, Cyr A, Elias AD, Farrar WB, Forero A, Giordano SH, Goldstein LJ, et al. Breast cancer version 3.2014. J Natl Compr Canc Netw. 2014;12(4):542–90.PubMed Gradishar WJ, Anderson BO, Blair SL, Burstein HJ, Cyr A, Elias AD, Farrar WB, Forero A, Giordano SH, Goldstein LJ, et al. Breast cancer version 3.2014. J Natl Compr Canc Netw. 2014;12(4):542–90.PubMed
58.
go back to reference von Minckwitz G, Rezai M, Loibl S, Fasching PA, Huober J, Tesch H, Bauerfeind I, Hilfrich J, Eidtmann H, Gerber B, et al. Capecitabine in addition to anthracycline- and taxane-based neoadjuvant treatment in patients with primary breast cancer: phase III GeparQuattro study. J Clin Oncol. 2010;28(12):2015–23.CrossRef von Minckwitz G, Rezai M, Loibl S, Fasching PA, Huober J, Tesch H, Bauerfeind I, Hilfrich J, Eidtmann H, Gerber B, et al. Capecitabine in addition to anthracycline- and taxane-based neoadjuvant treatment in patients with primary breast cancer: phase III GeparQuattro study. J Clin Oncol. 2010;28(12):2015–23.CrossRef
59.
go back to reference Kaufmann M, Klinga K, Runnebaum B, Kubli F. In vitro adriamycin sensitivity test and hormonal receptors in primary breast cancer. Eur J Cancer. 1980;16(12):1609–13.CrossRefPubMed Kaufmann M, Klinga K, Runnebaum B, Kubli F. In vitro adriamycin sensitivity test and hormonal receptors in primary breast cancer. Eur J Cancer. 1980;16(12):1609–13.CrossRefPubMed
60.
go back to reference Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, Bonnefoi H, Cameron D, Gianni L, Valagussa P et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet. 2014. Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, Bonnefoi H, Cameron D, Gianni L, Valagussa P et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet. 2014.
61.
go back to reference Lahsaee S, Corkery DP, Anthes LE, Holly A, Dellaire G. Estrogen receptor alpha (ESR1)-signaling regulates the expression of the taxane-response biomarker PRP4K. Exp Cell Res. 2016;340(1):125–31.CrossRefPubMed Lahsaee S, Corkery DP, Anthes LE, Holly A, Dellaire G. Estrogen receptor alpha (ESR1)-signaling regulates the expression of the taxane-response biomarker PRP4K. Exp Cell Res. 2016;340(1):125–31.CrossRefPubMed
62.
go back to reference Lovitt CJ, Shelper TB, Avery VM. Evaluation of chemotherapeutics in a three-dimensional breast cancer model. J Cancer Res Clin Oncol. 2015;141(5):951–9.CrossRefPubMed Lovitt CJ, Shelper TB, Avery VM. Evaluation of chemotherapeutics in a three-dimensional breast cancer model. J Cancer Res Clin Oncol. 2015;141(5):951–9.CrossRefPubMed
63.
go back to reference Sakamoto R, Rahman MM, Shimomura M, Itoh M, Nakatsura T. Time-lapse imaging assay using the BioStation CT: a sensitive drug-screening method for three-dimensional cell culture. Cancer Sci. 2015;106(6):757–65.CrossRefPubMedPubMedCentral Sakamoto R, Rahman MM, Shimomura M, Itoh M, Nakatsura T. Time-lapse imaging assay using the BioStation CT: a sensitive drug-screening method for three-dimensional cell culture. Cancer Sci. 2015;106(6):757–65.CrossRefPubMedPubMedCentral
64.
go back to reference Salgado R, Denkert C, Demaria S, Sirtaine N, Klauschen F, Pruneri G, Wienert S, Van den Eynden G, Baehner FL, Penault-Llorca F, et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann Oncol. 2015;26(2):259–71.CrossRefPubMed Salgado R, Denkert C, Demaria S, Sirtaine N, Klauschen F, Pruneri G, Wienert S, Van den Eynden G, Baehner FL, Penault-Llorca F, et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann Oncol. 2015;26(2):259–71.CrossRefPubMed
65.
go back to reference Denkert C, Loibl S, Muller BM, Eidtmann H, Schmitt WD, Eiermann W, Gerber B, Tesch H, Hilfrich J, Huober J, et al. Ki67 levels as predictive and prognostic parameters in pretherapeutic breast cancer core biopsies: a translational investigation in the neoadjuvant GeparTrio trial. Ann Oncol. 2013;24(11):2786–93.CrossRefPubMed Denkert C, Loibl S, Muller BM, Eidtmann H, Schmitt WD, Eiermann W, Gerber B, Tesch H, Hilfrich J, Huober J, et al. Ki67 levels as predictive and prognostic parameters in pretherapeutic breast cancer core biopsies: a translational investigation in the neoadjuvant GeparTrio trial. Ann Oncol. 2013;24(11):2786–93.CrossRefPubMed
66.
go back to reference Garcia-Martinez E, Gil GL, Benito AC, Gonzalez-Billalabeitia E, Conesa MA, Garcia Garcia T, Garcia Garcia E, Vicente V, Ayala de la Pena F. Tumor-infiltrating immune cell profiles and their change after neoadjuvant chemotherapy predict response and prognosis of breast cancer. Breast Cancer Res. 2014;16(6):488.CrossRefPubMedPubMedCentral Garcia-Martinez E, Gil GL, Benito AC, Gonzalez-Billalabeitia E, Conesa MA, Garcia Garcia T, Garcia Garcia E, Vicente V, Ayala de la Pena F. Tumor-infiltrating immune cell profiles and their change after neoadjuvant chemotherapy predict response and prognosis of breast cancer. Breast Cancer Res. 2014;16(6):488.CrossRefPubMedPubMedCentral
67.
go back to reference Denkert C, Loibl S, Noske A, Roller M, Muller BM, Komor M, Budczies J, Darb-Esfahani S, Kronenwett R, Hanusch C, et al. Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol. 2010;28(1):105–13.CrossRefPubMed Denkert C, Loibl S, Noske A, Roller M, Muller BM, Komor M, Budczies J, Darb-Esfahani S, Kronenwett R, Hanusch C, et al. Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol. 2010;28(1):105–13.CrossRefPubMed
68.
go back to reference Alvarado MD, Prasad C, Rothney M, Cherbavaz DB, Sing AP, Baehner FL, Svedman C, Markopoulos CJ. 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. Alvarado MD, Prasad C, Rothney M, Cherbavaz DB, Sing AP, Baehner FL, Svedman C, Markopoulos CJ. 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.
69.
go back to reference Llombart-Cussac A, Pivot X, Biganzoli L, Cortes-Funes H, Pritchard KI, Pierga JY, Smith I, Thomssen C, Srock S, Sampayo M, et al. A prognostic factor index for overall survival in patients receiving first-line chemotherapy for HER2-negative advanced breast cancer: an analysis of the ATHENA trial. Breast. 2014;23(5):656–62.CrossRefPubMed Llombart-Cussac A, Pivot X, Biganzoli L, Cortes-Funes H, Pritchard KI, Pierga JY, Smith I, Thomssen C, Srock S, Sampayo M, et al. A prognostic factor index for overall survival in patients receiving first-line chemotherapy for HER2-negative advanced breast cancer: an analysis of the ATHENA trial. Breast. 2014;23(5):656–62.CrossRefPubMed
70.
go back to reference Stover DG, Wagle N. Precision medicine in breast cancer: genes, genomes, and the future of genomically driven treatments. Curr Oncol Rep. 2015;17(4):15.CrossRefPubMed Stover DG, Wagle N. Precision medicine in breast cancer: genes, genomes, and the future of genomically driven treatments. Curr Oncol Rep. 2015;17(4):15.CrossRefPubMed
71.
go back to reference Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, Haibe-Kains B, Desmedt C, Ignatiadis M, Sengstag T, Schutz F, et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 2008;10(4):R65.CrossRefPubMedPubMedCentral Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, Haibe-Kains B, Desmedt C, Ignatiadis M, Sengstag T, Schutz F, et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 2008;10(4):R65.CrossRefPubMedPubMedCentral
72.
go back to reference Bae SY, Kim S, Lee JH, Lee HC, Lee SK, Kil WH, Kim SW, Lee JE, Nam SJ. Poor prognosis of single hormone receptor- positive breast cancer: similar outcome as triple-negative breast cancer. BMC Cancer. 2015;15:138.CrossRefPubMedPubMedCentral Bae SY, Kim S, Lee JH, Lee HC, Lee SK, Kil WH, Kim SW, Lee JE, Nam SJ. Poor prognosis of single hormone receptor- positive breast cancer: similar outcome as triple-negative breast cancer. BMC Cancer. 2015;15:138.CrossRefPubMedPubMedCentral
73.
go back to reference Early Breast Cancer Trialists’ Collaborative G. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet. 2005;365(9472):1687–717.CrossRef Early Breast Cancer Trialists’ Collaborative G. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet. 2005;365(9472):1687–717.CrossRef
Metadata
Title
Testing chemotherapy efficacy in HER2 negative breast cancer using patient-derived spheroids
Authors
Kathrin Halfter
Oliver Hoffmann
Nina Ditsch
Mareike Ahne
Frank Arnold
Stefan Paepke
Dieter Grab
Ingo Bauerfeind
Barbara Mayer
Publication date
01-12-2016
Publisher
BioMed Central
Published in
Journal of Translational Medicine / Issue 1/2016
Electronic ISSN: 1479-5876
DOI
https://doi.org/10.1186/s12967-016-0855-3

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