The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Doxorubicin resistance in breast cancer cells is mediated by extracellular matrix proteins
Open accessAbstract
BACKGROUND: Cancer cell resistance to therapeutics can result from acquired or de novo-mediated factors. Here, we have utilised advanced breast cancer cell culture models to elucidate de novo doxorubicin resistance mechanisms. METHODS: The response of breast cancer cell lines (MCF-7 and MDA-MB-231) to doxorubicin was examined in an in vitro three-dimensional (3D) cell culture model. Cells were cultured with Matrigel™ enabling cellular arrangements into a 3D architecture in conjunction with cell-to-extracellular matrix (ECM) contact. RESULTS: Breast cancer cells cultured in a 3D ECM-based model demonstrated altered sensitivity to doxorubicin, when compared to those grown in corresponding two-dimensional (2D) monolayer culture conditions. Investigations into the factors triggering the observed doxorubicin resistance revealed that cell-to-ECM interactions played a pivotal role. This finding correlated with the up-regulation of pro-survival proteins in 3D ECM-containing cell culture conditions following exposure to doxorubicin. Inhibition of integrin signalling in combination with doxorubicin significantly reduced breast cancer cell viability. Furthermore, breast cancer cells grown in a 3D ECM-based model demonstrated a significantly reduced proliferation rate in comparison to cells cultured in 2D conditions. CONCLUSION: Collectively, these novel findings reveal resistance mechanisms which may contribute to reduced doxorubicin sensitivity.
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
Jemal, A., Bray, F., Center, M. M., Ferlay, J., Ward, E., & Forman, D. (2011) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.20107 · Cited by 54,679
Drug penetration in solid tumours
Minchinton, A. I., & Tannock, I. F. (2006) · Nature reviews. Cancer · doi:10.1038/nrc1893 · Cited by 2,805
Doxorubicin: an update on anticancer molecular action, toxicity and novel drug delivery systems
Tacar, O., Sriamornsak, P., & Dass, C. R. (2013) · Journal of Pharmacy and Pharmacology · doi:10.1111/j.2042-7158.2012.01567.x · Cited by 2,465
Multicellular tumor spheroids: An underestimated tool is catching up again
Hirschhaeuser, F., Menne, H., Dittfeld, C., West, J., Mueller-Klieser, W., & Kunz-Schughart, L. A. (2010) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2010.01.012 · Cited by 1,674
Opportunities and challenges for use of tumor spheroids as models to test drug delivery and efficacy
Mehta, G., Hsiao, A. Y., Ingram, M., Luker, G. D., & Takayama, S. (2012) · Journal of Controlled Release · doi:10.1016/j.jconrel.2012.04.045 · Cited by 1,172
High-throughput 3D spheroid culture and drug testing using a 384 hanging drop array
Tung, Y.-C., Hsiao, A. Y., Allen, S. G., Torisawa, Y.-S., Ho, M., & Takayama, S. (2011) · The Analyst · doi:10.1039/c0an00609b · Cited by 969
Environment-mediated drug resistance: A major contributor to minimal residual disease
Meads, M. B., Gatenby, R. A., & Dalton, W. S. (2009) · Nature Reviews Cancer · doi:10.1038/nrc2714 · Cited by 892
Mechanisms and insights into drug resistance in cancer
Zahreddine, H., & Borden, K. L. B. (2013) · Frontiers in Pharmacology · doi:10.3389/fphar.2013.00028 · Cited by 660
Molecular aspects of cancer cell resistance to chemotherapy
Rebucci, M., & Michiels, C. (2013) · Biochemical Pharmacology · doi:10.1016/j.bcp.2013.02.017 · Cited by 407
Inhibition of PI3K/mTOR Leads to Adaptive Resistance in Matrix-Attached Cancer Cells
Muranen, T., Selfors, L. M., Worster, D. T., Iwanicki, M. P., Song, L., Morales, F. C., Gao, S., Mills, G. B., & Brugge, J. S. (2012) · Cancer Cell · doi:10.1016/j.ccr.2011.12.024 · Cited by 384
Cited by
Emerging roles of ECM remodeling processes in cancer
Mohan, V., Das, A., & Sagi, I. (2020) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2019.09.004 · Cited by 334
Phan, N., Hong, J. J., Tofig, B., Mapua, M., Elashoff, D., Moatamed, N. A., Huang, J., Memarzadeh, S., Damoiseaux, R., & Soragni, A. (2019) · Communications Biology · doi:10.1038/s42003-019-0305-x · Cited by 269
Microfluidic Arrays of Breast Tumor Spheroids for Drug Screening and Personalized Cancer Therapies
Prince, E., Kheiri, S., Wang, Y., Xu, F., Cruickshank, J., Topolskaia, V., Tao, H., Young, E. W. K., McGuigan, A. P., Cescon, D. W., et al. (2022) · Advanced Healthcare Materials · doi:10.1002/adhm.202101085 · Cited by 121
Multiplexed drug testing of tumor slices using a microfluidic platform
Horowitz, L. F., Rodriguez, A. D., Dereli-Korkut, Z., Lin, R., Castro, K., Mikheev, A. M., Monnat, R. J., Folch, A., & Rostomily, R. C. (2020) · npj Precision Oncology · doi:10.1038/s41698-020-0117-y · Cited by 88
Berger Fridman, I., Ugolini, G. S., VanDelinder, V., Cohen, S., & Konry, T. (2021) · Biofabrication · doi:10.1088/1758-5090/abdb88 · Cited by 46
Metadata
- Authors
- Lovitt, C. J., Shelper, T. B., & Avery, V. M.
- Venue
- BMC Cancer
- Published
- 2018-01-06
- Volume
- 18
- Issue
- 1
- Pages
- 41-41
- ISSN
- 1471-2407 (ISSN-L)
- OpenAlex
- W2781664750
- Cited by
- 339
- References
- 34
- FWCI
- 12.55
- Type
- journal article
- Language
- en
- Open access
- gold
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Doxorubicin resistance in breast cancer cells is mediated by extracellular matrix proteins. https://app.cochat.ai/papers/10.1186/s12885-017-3953-6
- The paper
- Lovitt, C. J., Shelper, T. B., & Avery, V. M. (2018). Doxorubicin resistance in breast cancer cells is mediated by extracellular matrix proteins. BMC Cancer. https://doi.org/10.1186/s12885-017-3953-6
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.