Gamma-Fe2O3 nanoparticles increase therapeutic efficacy of combination with paclitaxel and anti-ABCG2 monoclonal antibody on multiple myeloma cancer stem cells in mouse model
- PMID: 24738341
- DOI: 10.1166/jbn.2014.1730
Gamma-Fe2O3 nanoparticles increase therapeutic efficacy of combination with paclitaxel and anti-ABCG2 monoclonal antibody on multiple myeloma cancer stem cells in mouse model
Abstract
Cancer stem cells (CSCs) are thought to be responsible for the relapse of multiple myeloma (MM). The objective of this study was to target therapy of MM cancer stem cells using gamma-Fe2O3@DMSA magnetic nanoparticle combination with paclitaxel and anti-ABCG2 monoclonal antibody, and to evaluate the combined therapeutic efficacy. CSCs were isolated from human MM cell line RPMI 8226 based on negative expression of CD138 and CD34. In vivo and in vitro studies demonstrated that the isolated CD138-CD34- cells displayed certain stem cell characteristics, including significant increase in expression of ABCG2 transporter, proliferation, mobility, drug resistance, clonogenic potential in soft agar media and tumorigenecity in mice. Treatment with nanoparticles, paclitaxel and anti-ABCG2 antibody remarkably inhibited the growth of CD138-CD34- cells in vitro and their derived tumors in xenografts. The inhibition was also correlated with elevated expression of caspase-9, caspase-8 and caspase-3, and down-regulation of NF-KB. Our data indicate that the nanoparticle combination with paclitaxel and anti-ABCG2 monoclonal antibody offers an effective approach to treatment of MM CSCs through an apoptotic pathway.
Similar articles
-
Anti-ABCG2 monoclonal antibody in combination with paclitaxel nanoparticles against cancer stem-like cell activity in multiple myeloma.Nanomedicine (Lond). 2014 Jan;9(1):45-60. doi: 10.2217/nnm.12.216. Epub 2013 Mar 27. Nanomedicine (Lond). 2014. PMID: 23534833
-
Inhibitory effect of epirubicin-loaded lipid microbubbles with conjugated anti-ABCG2 antibody combined with therapeutic ultrasound on multiple myeloma cancer stem cells.J Drug Target. 2016;24(1):34-46. doi: 10.3109/1061186X.2015.1052075. Epub 2015 Jul 23. J Drug Target. 2016. PMID: 26204324
-
Target therapy of multiple myeloma by PTX-NPs and ABCG2 antibody in a mouse xenograft model.Oncotarget. 2015 Sep 29;6(29):27714-24. doi: 10.18632/oncotarget.4663. Oncotarget. 2015. PMID: 26314844 Free PMC article.
-
Cancer stem cells in multiple myeloma.Cancer Lett. 2009 May 8;277(1):1-7. doi: 10.1016/j.canlet.2008.08.005. Epub 2008 Sep 21. Cancer Lett. 2009. PMID: 18809245 Free PMC article. Review.
-
Cancer stem cells: controversies in multiple myeloma.J Mol Med (Berl). 2009 Nov;87(11):1079-85. doi: 10.1007/s00109-009-0531-7. Epub 2009 Sep 17. J Mol Med (Berl). 2009. PMID: 19760278 Free PMC article. Review.
Cited by
-
PEGylated long-circulating liposomes deliver homoharringtonine to suppress multiple myeloma cancer stem cells.Exp Biol Med (Maywood). 2017 May;242(9):996-1004. doi: 10.1177/1535370216685008. Epub 2017 Jan 1. Exp Biol Med (Maywood). 2017. PMID: 28056549 Free PMC article.
-
Molecular-matched materials for anticancer drug delivery and imaging.Nanomedicine (Lond). 2015 Oct;10(19):3003-3013. doi: 10.2217/nnm.15.117. Epub 2015 Sep 30. Nanomedicine (Lond). 2015. PMID: 26420013 Free PMC article.
-
Recent Advances in Nanotherapeutics for Multiple Myeloma.Cancers (Basel). 2020 Oct 27;12(11):3144. doi: 10.3390/cancers12113144. Cancers (Basel). 2020. PMID: 33120945 Free PMC article. Review.
-
Recent advances in targeted drug delivery systems for multiple myeloma.J Control Release. 2024 Dec;376:215-230. doi: 10.1016/j.jconrel.2024.10.003. Epub 2024 Oct 12. J Control Release. 2024. PMID: 39384153 Review.
-
Targeting autophagy using metallic nanoparticles: a promising strategy for cancer treatment.Cell Mol Life Sci. 2019 Apr;76(7):1215-1242. doi: 10.1007/s00018-018-2973-y. Epub 2018 Nov 27. Cell Mol Life Sci. 2019. PMID: 30483817 Free PMC article. Review.
Publication types
MeSH terms
Substances
LinkOut - more resources
Other Literature Sources
Medical
Research Materials