Compensatory Pathways Induced by MEK Inhibition Are Effective Drug Targets for Combination Therapy against Castration-Resistant Prostate Cancer

Gioeli, Daniel; Wunderlich, Winfried; Sebolt–Leopold, Judith S.; Bekiranov, Stefan; Wulfkuhle, Julia; Petricoin, Emanuel F.; Conaway, Mark R.; Weber, Michael J.

doi:10.1158/1535-7163.mct-10-1033

Cited by 59 publications

(51 citation statements)

References 43 publications

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“…We did not observe persistent apoptosis following PD0325901 treatment in vivo, in contrast with effects in vitro (49). Due to the multiplicity of Ras effectors and complexity of negative feedback regulation, therapeutic strategies against more aggressive Ras-related tumors are likely to include combinations of compounds that target multiple points in the Ras signaling network (40,(50)(51)(52). These studies support the investigation of combinatorial effects of PD0325901 with additional Ras pathway inhibitors in NF1 tumors.…”

Section: Discussionsupporting

confidence: 66%

MEK inhibition exhibits efficacy in human and mouse neurofibromatosis tumors

et al. 2012

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Neurofibromatosis type 1 (NF1) patients develop benign neurofibromas and malignant peripheral nerve sheath tumors (MPNST). These incurable peripheral nerve tumors result from loss of NF1 tumor suppressor gene function, causing hyperactive Ras signaling. Activated Ras controls numerous downstream effectors, but specific pathways mediating the effects of hyperactive Ras in NF1 tumors are unknown. We performed crossspecies transcriptome analyses of mouse and human neurofibromas and MPNSTs and identified global negative feedback of genes that regulate Ras/Raf/MEK/ERK signaling in both species. Nonetheless, ERK activation was sustained in mouse and human neurofibromas and MPNST. We used a highly selective pharmacological inhibitor of MEK, PD0325901, to test whether sustained Ras/Raf/MEK/ERK signaling contributes to neurofibroma growth in a neurofibromatosis mouse model (Nf1 fl/fl ;Dhh-Cre) or in NF1 patient MPNST cell xenografts. PD0325901 treatment reduced aberrantly proliferating cells in neurofibroma and MPNST, prolonged survival of mice implanted with human MPNST cells, and shrank neurofibromas in more than 80% of mice tested. Our data demonstrate that deregulated Ras/ERK signaling is critical for the growth of NF1 peripheral nerve tumors and provide a strong rationale for testing MEK inhibitors in NF1 clinical trials.

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Section: Discussionsupporting

confidence: 66%

MEK inhibition exhibits efficacy in human and mouse neurofibromatosis tumors

et al. 2012

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“…The combination of the mTOR inhibitor rapamycin with the MEK inhibitor PD325901 resulted in synergistic growth inhibition in the androgen-responsive cell lines CWR22Rv1 (Gioeli et al 2011) and CASP 2.1 (Kinkade et al 2008) and the androgen-independent cell line CASP 1.1 (Kinkade et al 2008). While in vivo, the combination displayed potent antitumorigenic activity in a mouse model of CRPC (Gioeli et al 2011). In a phase Ib study in patients with advanced solid tumors, the combination of the MEK inhibitor GDC-0973 and the PI3K inhibitor GDC-0941 was shown to be well tolerated with a safety profile similar to that observed with either agent alone.…”

Section: Combination With Mek Inhibitorsmentioning

confidence: 99%

Targeting the PI3K/Akt/mTOR pathway in castration-resistant prostate cancer

Bitting

Armstrong

2013

Endocrine-Related Cancer

280

243

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The phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) pathway is a key signaling pathway that has been linked to both tumorigenesis and resistance to therapy in prostate cancer and other solid tumors. Given the significance of the PI3K/Akt/mTOR pathway in integrating cell survival signals and the high prevalence of activating PI3K/Akt/mTOR pathway alterations in prostate cancer, inhibitors of this pathway have great potential for clinical benefit. Here, we review the role of the PI3K/Akt/mTOR pathway in prostate cancer and discuss the potential use of pathway inhibitors as single agents or in combination in the evolving treatment landscape of castration-resistant prostate cancer.

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“…Network-modelling approaches are now being used to identify new drug targets, drug regimens and mechanisms of drug action (Kleiman et al, 2011;Lee et al, 2012;Schoeberl et al, 2009). 'Clean' molecularly targeted drugs lead to 'messy' system-wide adaptations (see above) (Chandarlapaty et al, 2011;Duncan et al, 2012;Gioeli et al, 2011), so we expect network models to be featured more prominently in the future for these purposes.…”

Section: Future Perspectivesmentioning

confidence: 99%

Models of signalling networks – what cell biologists can gain from them and give to them

Janes

Lauffenburger

2013

Journal of Cell Science

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SummaryComputational models of cell signalling are perceived by many biologists to be prohibitively complicated. Why do math when you can simply do another experiment? Here, we explain how conceptual models, which have been formulated mathematically, have provided insights that directly advance experimental cell biology. In the past several years, models have influenced the way we talk about signalling networks, how we monitor them, and what we conclude when we perturb them. These insights required wet-lab experiments but would not have arisen without explicit computational modelling and quantitative analysis. Today, the best modellers are crosstrained investigators in experimental biology who work closely with collaborators but also undertake experimental work in their own laboratories. Biologists would benefit by becoming conversant in core principles of modelling in order to identify when a computational model could be a useful complement to their experiments. Although the mathematical foundations of a model are useful to appreciate its strengths and weaknesses, they are not required to test or generate a worthwhile biological hypothesis computationally. Key words: Cell signalling, Computational biology, Systems biologyIntroduction A decade ago, we welcomed the first signalling-network models that were strongly grounded in wet-lab experiments (Hoffmann et al., 2002;Schoeberl et al., 2002). Excellent models now exist for many canonical signalling circuits in a variety of biological settings. However, such models should not be viewed as an end product but rather as a tool for addressing systems-level challenges in cell biology . Have models fulfilled this role and have they provided biological insights that experimentalists should bother to care about? Here, we answer 'Yes' to both questions and predict that signallingnetwork models will soon become indispensable for modern research in the field. Fortunately, the current wealth of dataintensive methods has primed today's cell biologists to embrace modelling, even though they may lack formal training in the underlying mathematics.In this Opinion, we propose that empirical cell biologists have much to gain from signalling-network models, and much to give by ensuring that these models stay in touch with reality. We begin with a brief primer on how computational models can be critically assessed from a biological standpoint. Then, we walk through a series of important insights about cell signalling that have stemmed from computational-systems modelling. We conclude with future perspectives on where signalling-network models are just beginning to have an impact and will continue to do so in the coming years.

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Compensatory Pathways Induced by MEK Inhibition Are Effective Drug Targets for Combination Therapy against Castration-Resistant Prostate Cancer

Cited by 59 publications

References 43 publications

MEK inhibition exhibits efficacy in human and mouse neurofibromatosis tumors

MEK inhibition exhibits efficacy in human and mouse neurofibromatosis tumors

Targeting the PI3K/Akt/mTOR pathway in castration-resistant prostate cancer

Models of signalling networks – what cell biologists can gain from them and give to them

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