Memory of stochastic single-cell apoptotic signaling promotes chemoresistance in neuroblastoma.

Gene expression noise is known to promote stochastic drug resistance through the elevated expression of individual genes in rare cancer cells. However, we now demonstrate that chemoresistant neuroblastoma cells emerge at a much higher frequency when the influence of noise is integrated across multiple components of an apoptotic signaling network. Using a JNK activity biosensor with longitudinal high-content and in vivo intravital imaging, we identify a population of stochastic, JNK-impaired, chemoresistant cells that exist because of noise within this signaling network. Furthermore, we reveal that the memory of this initially random state is retained following chemotherapy treatment across a series of in vitro, in vivo, and patient models. Using matched PDX models established at diagnosis and relapse from individual patients, we show that HDAC inhibitor priming cannot erase the memory of this resistant state within relapsed neuroblastomas but improves response in the first-line setting by restoring drug-induced JNK activity within the chemoresistant population of treatment-naïve tumors.

Non-kinase targeting of oncogenic c-Jun N-terminal kinase (JNK) signaling: the future of clinically viable cancer treatments.

c-Jun N-terminal Kinases (JNKs) have been identified as key disease drivers in a number of pathophysiological settings and central oncogenic signaling nodes in various cancers. Their roles in driving primary tumor growth, positively regulating cancer stem cell populations, promoting invasion and facilitating metastatic outgrowth have led JNKs to be considered attractive targets for anti-cancer therapies. However, the homeostatic, apoptotic and tumor-suppressive activities of JNK proteins limit the use of direct JNK inhibitors in a clinical setting. In this review, we will provide an overview of the different JNK targeting strategies developed to date, which include various ATP-competitive, non-kinase and substrate-competitive inhibitors. We aim to summarize their distinct mechanisms of action, review some of the insights they have provided regarding JNK-targeting in cancer, and outline the limitations as well as challenges of all strategies that target JNKs directly. Furthermore, we will highlight alternate drug targets within JNK signaling complexes, including recently identified scaffold proteins, and discuss how these findings may open up novel therapeutic options for targeting discrete oncogenic JNK signaling complexes in specific cancer settings.

Histone Deacetylases and Histone Deacetylase Inhibitors in Neuroblastoma.

Histone deacetylases (HDACs) are enzymes that play a key role in regulating gene expression by remodeling chromatin structure. An imbalance of histone acetylation caused by deregulated HDAC expression and activity is known to promote tumor progression in a number of tumor types, including neuroblastoma, the most common solid tumor in children. Consequently, the inhibition of HDACs has emerged as a potential strategy to reverse these aberrant epigenetic changes, and several classes of HDAC inhibitors (HDACi) have been shown to inhibit tumor proliferation, or induce differentiation, apoptosis and cell cycle arrest in neuroblastoma. Further, the combined use of HDACi with other chemotherapy agents, or radiotherapy, has shown promising pre-clinical results and various HDACi have progressed to different stages in clinical trials. Despite this, the effects of HDACi are multifaceted and more work needs to be done to unravel their specific mechanisms of actions. In this review, we discuss the functional role of HDACs in neuroblastoma and the potential of HDACi to be optimized for development and use in the clinic for treatment of patients with neuroblastoma.

Applications of personalised signalling network models in precision oncology.

As our ability to provide in-depth, patient-specific characterisation of the molecular alterations within tumours rapidly improves, it is becoming apparent that new approaches will be required to leverage the power of this data and derive the full benefit for each individual patient. Systems biology approaches are beginning to emerge within this field as a potential method of incorporating large volumes of network level data and distilling a coherent, clinically-relevant prediction of drug response. However, the initial promise of this developing field is yet to be realised. Here we argue that in order to develop these precise models of individual drug response and tailor treatment accordingly, we will need to develop mathematical models capable of capturing both the dynamic nature of drug-response signalling networks and key patient-specific information such as mutation status or expression profiles. We also review the modelling approaches commonly utilised within this field, and outline recent examples of their use in furthering the application of systems biology for a precision medicine approach to cancer treatment.

Targeting promiscuous heterodimerization overcomes innate resistance to ERBB2 dimerization inhibitors in breast cancer.

BACKGROUND: The oncogenic receptor tyrosine kinase (RTK) ERBB2 is known to dimerize with other EGFR family members, particularly ERBB3, through which it potently activates PI3K signalling. Antibody-mediated inhibition of this ERBB2/ERBB3/PI3K axis has been a cornerstone of treatment for ERBB2-amplified breast cancer patients for two decades. However, the lack of response and the rapid onset of relapse in many patients now question the assumption that the ERBB2/ERBB3 heterodimer is the sole relevant effector target of these therapies. METHODS: Through a systematic protein-protein interaction screen, we have identified and validated alternative RTKs that interact with ERBB2. Using quantitative readouts of signalling pathway activation and cell proliferation, we have examined their influence upon the mechanism of trastuzumab- and pertuzumab-mediated inhibition of cell growth in ERBB2-amplified breast cancer cell lines and a patient-derived xenograft model. RESULTS: We now demonstrate that inactivation of ERBB3/PI3K by these therapeutic antibodies is insufficient to inhibit the growth of ERBB2-amplified breast cancer cells. Instead, we show extensive promiscuity between ERBB2 and an array of RTKs from outside of the EGFR family. Paradoxically, pertuzumab also acts as an artificial ligand to promote ERBB2 activation and ERK signalling, through allosteric activation by a subset of these non-canonical RTKs. However, this unexpected activation mechanism also increases the sensitivity of the receptor network to the ERBB2 kinase inhibitor lapatinib, which in combination with pertuzumab, displays a synergistic effect in single-agent resistant cell lines and PDX models. CONCLUSIONS: The interaction of ERBB2 with a number of non-canonical RTKs activates a compensatory signalling response following treatment with pertuzumab, although a counter-intuitive combination of ERBB2 antibody therapy and a kinase inhibitor can overcome this innate therapeutic resistance.