Combined ALK and MDM2 inhibition increases antitumor activity and overcomes resistance in human ALK mutant neuroblastoma cell lines and xenograft models
Abstract
The efficacy of ALK inhibitors in patients with ALK-mutant neuroblastoma is limited, highlighting the need to improve their effectiveness in these patients. To this end we sought to develop a combination strategy to enhance the antitumor activity of ALK inhibitor monotherapy in human neuroblastoma cell lines and xenograft models expressing activated ALK. Herein, we report that combined inhibition of ALK and MDM2 induced a complementary set of anti-proliferative and pro-apoptotic proteins. Consequently, this combination treatment synergistically inhibited proliferation of TP53 wild-type neuroblastoma cells harboring ALK amplification or mutations in vitro, and resulted in complete and durable responses in neuroblastoma xenografts derived from these cells. We further demonstrate that concurrent inhibition of MDM2 and ALK was able to overcome ceritinib resistance conferred by MYCN upregulation in vitro and in vivo. Together, combined inhibition of ALK and MDM2 may provide an effective treatment for TP53 wild-type neuroblastoma with ALK aberrations.
Article and author information
Author details
Funding
Novartis
- Fang Li
The research was funded by Novartis, Inc., where all authors were employees at the time the study was conducted. The authors declare no other competing financial interests.
Ethics
Animal experimentation: All in vivo studies were reviewed and approved by the Novartis Institutes of Biomedical Research Institutional Animal Care and Use Committee (IACUC) in accordance with applicable local, state, and federal regulations.If needed, a letter from the IACUC Chair can be provided to confirm that all in vivo studies were reviewed and approved by the Novartis IACUC. Below is the contact of the Novartis IACUC Chair.CeCe Brotchie-Fine, MA, CPIAManager, Animal Welfare ComplianceIACUC Chair & Animal Welfare OfficerT +1 617 871 5064M+1 617 834 4784Email: Candice.brotchie-fine@novartis.comNovartis Institutes for BioMedical Research, Inc.700 Main Street, 460 ACambridge, MA 02139 USA
Copyright
© 2017, Wang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,565
- views
-
- 485
- downloads
-
- 37
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Cancer Biology
- Evolutionary Biology
In asexual populations that don’t undergo recombination, such as cancer, deleterious mutations are expected to accrue readily due to genome-wide linkage between mutations. Despite this mutational load of often thousands of deleterious mutations, many tumors thrive. How tumors survive the damaging consequences of this mutational load is not well understood. Here, we investigate the functional consequences of mutational load in 10,295 human tumors by quantifying their phenotypic response through changes in gene expression. Using a generalized linear mixed model (GLMM), we find that high mutational load tumors up-regulate proteostasis machinery related to the mitigation and prevention of protein misfolding. We replicate these expression responses in cancer cell lines and show that the viability in high mutational load cancer cells is strongly dependent on complexes that degrade and refold proteins. This indicates that the upregulation of proteostasis machinery is causally important for high mutational burden tumors and uncovers new therapeutic vulnerabilities.
-
- Cancer Biology
- Cell Biology
Understanding the cell cycle at the single-cell level is crucial for cellular biology and cancer research. While current methods using fluorescent markers have improved the study of adherent cells, non-adherent cells remain challenging. In this study, we addressed this gap by combining a specialized surface to enhance cell attachment, the FUCCI(CA)2 sensor, an automated image analysis pipeline, and a custom machine learning algorithm. This approach enabled precise measurement of cell cycle phase durations in non-adherent cells. This method was validated in acute myeloid leukemia cell lines NB4 and Kasumi-1, which have unique cell cycle characteristics, and we tested the impact of cell cycle-modulating drugs on NB4 cells. Our cell cycle analysis system, which is also compatible with adherent cells, is fully automated and freely available, providing detailed insights from hundreds of cells under various conditions. This report presents a valuable tool for advancing cancer research and drug development by enabling comprehensive, automated cell cycle analysis in both adherent and non-adherent cells.