The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes
Open accessAbstract
Development and preclinical testing of new cancer therapies is limited by the scarcity of in vivo models that authentically reproduce tumor growth and metastatic progression. We report new models for breast tumor growth and metastasis in the form of transplantable tumors derived directly from individuals undergoing treatment for breast cancer. These tumor grafts illustrate the diversity of human breast cancer and maintain essential features of the original tumors, including metastasis to specific sites. Co-engraftment of primary human mesenchymal stem cells maintains phenotypic stability of the grafts and increases tumor growth by promoting angiogenesis. We also report that tumor engraftment is a prognostic indicator of disease outcome for women with newly diagnosed breast cancer; orthotopic breast tumor grafting is a step toward individualized models for tumor growth, metastasis and prognosis. This bank of tumor grafts also serves as a publicly available resource for new models in which to study the biology of breast cancer.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Kao, J., Salari, K., Bocanegra, M., Choi, Y.-L., Girard, L., Gandhi, J., Kwei, K. A., Hernandez-Boussard, T., Wang, P., Gazdar, A. F., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0006146 · Cited by 788
Klopp, A. H., Gupta, A., Spaeth, E., Andreeff, M., & Marini, F. (2011) · Stem Cells · doi:10.1002/stem.559 · Cited by 562
Cited by
Roles of the immune system in cancer: From tumor initiation to metastatic progression
Gonzalez, H., Hagerling, C., & Werb, Z. (2018) · Genes & Development · doi:10.1101/gad.314617.118 · Cited by 2,111
Steeg, P. S. (2016) · Nature Reviews Cancer · doi:10.1038/nrc.2016.25 · Cited by 1,363
Gao, H., Korn, J. M., Ferretti, S., Monahan, J. E., Wang, Y., Singh, M., Zhang, C., Schnell, C., Yang, G., Zhang, Y., et al. (2015) · Nature Medicine · doi:10.1038/nm.3954 · Cited by 1,393
Patient-derived tumour xenografts as models for oncology drug development
Tentler, J. J., Tan, A. C., Weekes, C. D., Jimeno, A., Leong, S., Pitts, T. M., Arcaroli, J. J., Messersmith, W. A., & Eckhardt, S. G. (2012) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2012.61 · Cited by 1,277
Single-cell analysis reveals a stem-cell program in human metastatic breast cancer cells
Lawson, D. A., Bhakta, N. R., Kessenbrock, K., Prummel, K. D., Yu, Y., Takai, K., Zhou, A., Eyob, H., Balakrishnan, S., Wang, C.-Y., et al. (2015) · Nature · doi:10.1038/nature15260 · Cited by 893
Metastatic Latency and Immune Evasion through Autocrine Inhibition of WNT
Malladi, S., Macalinao, D. G., Jin, X., He, L., Basnet, H., Zou, Y., de Stanchina, E., & Massagué, J. (2016) · Cell · doi:10.1016/j.cell.2016.02.025 · Cited by 791
MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices
McGinnis, C. S., Patterson, D. M., Winkler, J., Conrad, D. N., Hein, M. Y., Srivastava, V., Hu, J. L., Murrow, L. M., Weissman, J. S., Werb, Z., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0433-8 · Cited by 643
In Vitro Tumor Models: Advantages, Disadvantages, Variables, and Selecting the Right Platform
Katt, M. E., Placone, A. L., Wong, A. D., Xu, Z. S., & Searson, P. C. (2016) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2016.00012 · Cited by 754
Patient-derived xenografts undergo mouse-specific tumor evolution
Ben-David, U., Ha, G., Tseng, Y.-Y., Greenwald, N. F., Oh, C., Shih, J., McFarland, J. M., Wong, B., Boehm, J. S., Beroukhim, R., et al. (2017) · Nature Genetics · doi:10.1038/ng.3967 · Cited by 716
Palmer, A. C., & Sorger, P. K. (2017) · Cell · doi:10.1016/j.cell.2017.11.009 · Cited by 642
Animal models of human disease: challenges in enabling translation
McGonigle, P., & Ruggeri, B. (2014) · Biochemical Pharmacology · doi:10.1016/j.bcp.2013.08.006 · Cited by 610
Ibrahim, Y. H., García-García, C., Serra, V., He, L., Torres-Lockhart, K., Prat, A., Anton, P., Cozar, P., Guzmán, M., Grueso, J., et al. (2012) · Cancer Discovery · doi:10.1158/2159-8290.cd-11-0348 · Cited by 601
Tumor Microenvironment Complexity: Emerging Roles in Cancer Therapy
Swartz, M. A., Iida, N., Roberts, E. W., Sangaletti, S., Wong, M. H., Yull, F. E., Coussens, L. M., & DeClerck, Y. A. (2012) · Cancer Research · doi:10.1158/0008-5472.can-12-0122 · Cited by 542
Zhang, X., Claerhout, S., Prat, A., Dobrolecki, L. E., Petrovic, I., Lai, Q., Landis, M. D., Wiechmann, L., Schiff, R., Giuliano, M., et al. (2013) · Cancer Research · doi:10.1158/0008-5472.can-12-4081 · Cited by 481
Applications of patient-derived tumor xenograft models and tumor organoids
Yoshida, G. J. (2020) · Journal of Hematology & Oncology · doi:10.1186/s13045-019-0829-z · Cited by 471
Glucocorticoids promote breast cancer metastasis
Obradović, M. M. S., Hamelin, B., Manevski, N., Couto, J. P., Sethi, A., Coissieux, M.-M., Münst, S., Okamoto, R., Kohler, H., Schmidt, A., et al. (2019) · Nature · doi:10.1038/s41586-019-1019-4 · Cited by 462
Bruna, A., Rueda, O. M., Greenwood, W., Batra, A. S., Callari, M., Batra, R. N., Pogrebniak, K., Sandoval, J., Cassidy, J. W., Tufegdzic-Vidakovic, A., et al. (2016) · Cell · doi:10.1016/j.cell.2016.08.041 · Cited by 448
Self-citationCazet, A. S., Hui, M. N., Elsworth, B. L., Wu, S. Z., Roden, D., Chan, C.-L., Skhinas, J. N., Collot, R., Yang, J., Harvey, K., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05220-6 · Cited by 437
Guillen, K. P., Fujita, M., Butterfield, A. J., Scherer, S. D., Bailey, M. H., Chu, Z., DeRose, Y. S., Zhao, L., Cortes-Sanchez, E., Yang, C.-H., et al. (2022) · Nature Cancer · doi:10.1038/s43018-022-00337-6 · Cited by 416
Self-citationA framework for the development of effective anti-metastatic agents
Anderson, R. L., Balasas, T., Callaghan, J., Coombes, R. C., Evans, J., Hall, J. A., Kinrade, S., Jones, D., Jones, P. S., Jones, R., et al. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-018-0134-8 · Cited by 341
Shirure, V. S., Bi, Y., Curtis, M. B., Lezia, A., Goedegebuure, M. M., Goedegebuure, S. P., Aft, R., Fields, R. C., & George, S. C. (2018) · Lab on a Chip · doi:10.1039/c8lc00596f · Cited by 316
Translational value of mouse models in oncology drug development
Gould, S. E., Junttila, M. R., & de Sauvage, F. J. (2015) · Nature Medicine · doi:10.1038/nm.3853 · Cited by 293
Tumor organoids: applications in cancer modeling and potentials in precision medicine
Xu, H., Jiao, D., Liu, A., & Wu, K. (2022) · Journal of Hematology & Oncology · doi:10.1186/s13045-022-01278-4 · Cited by 286
Breast Tumor Heterogeneity: Source of Fitness, Hurdle for Therapy
Koren, S., & Bentires-Alj, M. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.10.031 · Cited by 284
Letai, A., Bhola, P., & Welm, A. L. (2022) · Cancer Cell · doi:10.1016/j.ccell.2021.12.004 · Cited by 281
Self-citationPatient-derived xenograft (PDX) models in basic and translational breast cancer research
Dobrolecki, L. E., Airhart, S. D., Alferez, D. G., Aparicio, S., Behbod, F., Bentires-Alj, M., Brisken, C., Bult, C. J., Cai, S., Clarke, R. B., et al. (2016) · Cancer and Metastasis Reviews · doi:10.1007/s10555-016-9653-x · Cited by 267
Self-citationThorel, L., Perréard, M., Florent, R., Divoux, J., Coffy, S., Vincent, A., Gaggioli, C., Guasch, G., Gidrol, X., Weiswald, L.-B., et al. (2024) · Experimental & Molecular Medicine · doi:10.1038/s12276-024-01272-5 · Cited by 236
Breast cancer models: Engineering the tumor microenvironment
Bahcecioglu, G., Basara, G., Ellis, B. W., Ren, X., & Zorlutuna, P. (2020) · Acta Biomaterialia · doi:10.1016/j.actbio.2020.02.006 · Cited by 213
Targeting the cancer-associated fibroblasts as a treatment in triple-negative breast cancer
Takai, K., Le, A., Weaver, V. M., & Werb, Z. (2016) · Oncotarget · doi:10.18632/oncotarget.12658 · Cited by 207
Kim, K.-T., Lee, H. W., Lee, H.-O., Song, H. J., Jeong, D. E., Shin, S., Kim, H., Shin, Y., Nam, D.-H., Jeong, B. C., et al. (2016) · Genome Biology · doi:10.1186/s13059-016-0945-9 · Cited by 198
PDXNET Consortium, Woo, X. Y., EurOPDX Consortium, Giordano, J., Srivastava, A., Zhao, Z.-M., Lloyd, M. W., de Bruijn, R., Suh, Y.-S., Patidar, R., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00750-6 · Cited by 190
Self-citationHarnessing the predictive power of preclinical models for oncology drug development
Honkala, A., Malhotra, S. V., Kummar, S., & Junttila, M. R. (2022) · Nature Reviews Drug Discovery · doi:10.1038/s41573-021-00301-6 · Cited by 121
Hippo pathway mediates resistance to cytotoxic drugs
Gujral, T. S., & Kirschner, M. W. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1703096114 · Cited by 91
Mieulet, V., Garnier, C., Kieffer, Y., Guilbert, T., Nemati, F., Marangoni, E., Renault, G., Chamming’s, F., Vincent-Salomon, A., & Mechta-Grigoriou, F. (2021) · Scientific Reports · doi:10.1038/s41598-021-83685-0 · Cited by 79
Garcia, P. L., Miller, A. L., & Yoon, K. J. (2020) · Cancers · doi:10.3390/cancers12051327 · Cited by 77
Shomali, M., Cheng, J., Sun, F., Koundinya, M., Guo, Z., Hebert, A. T., McManus, J., Levit, M. N., Hoffmann, D., Courjaud, A., et al. (2021) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-20-0390 · Cited by 69
Wang, E., Xiang, K., Zhang, Y., & Wang, X.-F. (2022) · Journal of the National Cancer Center · doi:10.1016/j.jncc.2022.10.001 · Cited by 56
Identification of synergistic drug combinations using breast cancer patient-derived xenografts
Turner, T. H., Alzubi, M. A., & Harrell, J. C. (2020) · Scientific Reports · doi:10.1038/s41598-020-58438-0 · Cited by 50
Sudhan, D. R., Guerrero-Zotano, A., Won, H., González Ericsson, P., Servetto, A., Huerta-Rosario, M., Ye, D., Lee, K.-M., Formisano, L., Guo, Y., et al. (2020) · Cancer Cell · doi:10.1016/j.ccell.2019.12.013 · Cited by 49
Pham, K., Delitto, D., Knowlton, A. E., Hartlage, E. R., Madhavan, R., Gonzalo, D. H., Thomas, R. M., Behrns, K. E., George, T. J., Hughes, S. J., et al. (2016) · The American Journal of Pathology · doi:10.1016/j.ajpath.2016.02.009 · Cited by 46
Colombo, P.-E., du Manoir, S., Orsetti, B., Bras-Gonçalves, R., Lambros, M. B., MacKay, A., Nguyen, T.-T., Boissière, F., Pourquier, D., Bibeau, F., et al. (2015) · Oncotarget · doi:10.18632/oncotarget.5069 · Cited by 34
Pipiya, V. V., Gilazieva, Z. E., Issa, S. S., Rizvanov, A. A., & Solovyeva, V. V. (2024) · Exploration of Targeted Anti-tumor Therapy · doi:10.37349/etat.2024.00237 · Cited by 23
Transplantable Mouse Tumor Models of Breast Cancer Metastasis
Chakrabarti, R., & Kang, Y. (2015) · Methods in Molecular Biology · doi:10.1007/978-1-4939-2297-0_18 · Cited by 20
Metadata
- Authors
- DeRose, Y. S., Wang, G., Lin, Y.-C., Bernard, P. S., Buys, S. S., Ebbert, M. T. W., Factor, R., Matsen, C., Milash, B. A., Nelson, E., Neumayer, L., Randall, R. L., Stijleman, I. J., Welm, B. E., & Welm, A. L.
- Venue
- Nature Medicine
- Published
- 2011-10-23
- Volume
- 17
- Issue
- 11
- Pages
- 1514-1520
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W2034428193
- Cited by
- 1,002
- References
- 2
- FWCI
- 18.89
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
