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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.

The identification of clinically viable strategies for overcoming resistance to platinum chemotherapy in lung adenocarcinoma has previously been hampered by inappropriately tailored in vitro assays of drug response. Therefore, using a pulse model that closely mimics the in vivo pharmacokinetics of platinum therapy, we profiled cisplatin-induced signalling, DNA-damage and apoptotic responses across a panel of human lung adenocarcinoma cell lines. By coupling this data to real-time, single-cell imaging of cell cycle and apoptosis we provide a fine-grained stratification of response, where a P70S6K-mediated signalling axis promotes resistance on a TP53 wildtype or null background, but not a mutant TP53 background. This finding highlights the value of in vitro models that match the physiological pharmacokinetics of drug exposure. Furthermore, it also demonstrates the importance of a mechanistic understanding of the interplay between somatic mutations and the signalling networks that govern drug response for the implementation of any consistently effective, patient-specific therapy., eLife digest Lung adenocarcinoma is the most common type of lung cancer, and it emerges because of a variety of harmful genetic changes, or mutations. Two lung cancer patients – or indeed, two different sets of cancerous cells within a patient – may therefore carry different damaging mutations. A group of drugs called platinum-based chemotherapies are currently the most effective way to treat lung adenocarcinoma. Yet, only 30% of patients actually respond to the therapy. Many studies conducted in laboratory settings have tried to understand why most cases are resistant to treatment, with limited success. Here, Hastings, Gonzalez-Rajal et al. propose that previous research has been inconclusive because studies done in the laboratory do not reflect how the treatment is actually administered. In patients, platinum-based drugs are cleared from the body within a few hours, but during experiments, the treatment is continually administered to cells growing in a dish. Hastings, Gonzalez-Rajal et al. therefore developed a laboratory method that mimics the way cells are exposed to platinum-based chemotherapy in the body. These experiments showed that the lung adenocarcinoma cells which resisted treatment also carried high levels of a protein known as P70S6K. Pairing platinum-based chemotherapy with a drug that blocks the activity of P70S6K killed these resistant cells. This combination also treated human lung adenocarcinoma tumours growing under the skin of mice. However, it was ineffective on cancerous cells that carry a mutation in a protein called p53, which is often defective in cancers. Overall, this work demonstrates the need to refine how drugs are tested in the laboratory to better reflect real-life conditions. It also underlines the importance of personalizing drug combinations to the genetic background of each tumour, a concept that will be vital to consider in future clinical trials.

Germline loss-of-function variation in TNFAIP3, encoding A20, has been implicated in a wide variety of autoinflammatory and autoimmune conditions, with acquired somatic missense mutations linked to cancer progression. Furthermore, human sequence data reveals that the A20 locus contains ~ 400 non-synonymous coding variants, which are largely uncharacterised. The growing number of A20 coding variants with unknown function, but potential clinical impact, poses a challenge to traditional mouse-based approaches. Here we report the development of a novel functional genomics approach that utilizes a new A20-deficient zebrafish (Danio rerio) model to investigate the impact of TNFAIP3 genetic variants in vivo. A20-deficient zebrafish are hyper-responsive to microbial immune activation and exhibit spontaneous early lethality. Ectopic addition of human A20 rescued A20-null zebrafish from lethality, while missense mutations at two conserved A20 residues, S381A and C243Y, reversed this protective effect. Ser381 represents a phosphorylation site important for enhancing A20 activity that is abrogated by its mutation to alanine, or by a causal C243Y mutation that triggers human autoimmune disease. These data reveal an evolutionarily conserved role for TNFAIP3 in limiting inflammation in the vertebrate linage and show how this function is controlled by phosphorylation. They also demonstrate how a zebrafish functional genomics pipeline can be utilized to investigate the in vivo significance of medically relevant human TNFAIP3 gene variants.

Identification of clinically viable strategies for overcoming resistance to platinum chemotherapy in lung adenocarcinoma has been hampered by inappropriately tailoredin vitroassays of drug response. Therefore, using a pulse model that closely recapitulates thein vivopharmacokinetics of platinum therapy, we profiled cisplatin-induced signalling, DNA damage and apoptotic responses across a panel of lung adenocarcinoma cell lines. By coupling this data with real-time, single cell imaging of cell cycle and apoptosis, we show thatTP53mutation status influenced the mode of cisplatin induced cell cycle arrest, but could not predict cisplatin sensitivity. In contrast, P70S6K-mediated signalling promoted resistance by increasing p53/p63 and p21 expression, reducing double-stranded DNA breaks and apoptosis. Targeting P70S6K sensitised bothTP53wildtype and null lines to cisplatin, but notTP53mutant lines. In summary, usingin vitroassays that mimicin vivopharmacokinetics identified P70S6K as a robust mediator of cisplatin resistance and highlighted the importance of considering somatic mutation status when designing patient-specific combination therapies.

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. Electronic supplementary material The online version of this article (10.1186/s13058-019-1127-y) contains supplementary material, which is available to authorized users.

High-risk neuroblastoma is an aggressive childhood cancer that is characterized by high rates of chemoresistance and frequent metastatic relapse. A number of studies have characterized the genetic and epigenetic landscape of neuroblastoma, but due to a generally low mutational burden and paucity of actionable mutations, there are few options for applying a comprehensive personalized medicine approach through the use of targeted therapies. Therefore, the use of multi-agent chemotherapy remains the current standard of care for neuroblastoma, which also conceptually limits the opportunities for developing an effective and widely applicable personalized medicine approach for this disease. However, in this review we outline potential approaches for tailoring the use of chemotherapy agents to the specific molecular characteristics of individual tumours by performing patient-specific simulations of drug-induced apoptotic signalling. By incorporating multiple layers of information about tumour-specific aberrations, including expression as well as mutation data, these models have the potential to rationalize the selection of chemotherapeutics contained within multi-agent treatment regimens and ensure the optimum response is achieved for each individual patient.

The assembly of protein complexes is a central mechanism underlying the regulation of many cell signaling pathways. A major focus of biomedical research is deciphering how these dynamic protein complexes act to integrate signals from multiple sources in order to direct a specific biological response, and how this becomes deregulated in many disease settings. Despite the importance of this key biochemical mechanism, there is a lack of experimental techniques that can facilitate the specific and sensitive deconvolution of these multi-molecular signaling complexes. Here this shortcoming is addressed through the combination of a protein complementation assay with a conformation-specific nanobody, which we have termed Bimolecular Complementation Affinity Purification (BiCAP). This novel technique facilitates the specific isolation and downstream proteomic characterization of any pair of interacting proteins, to the exclusion of un-complexed individual proteins and complexes formed with competing binding partners. The BiCAP technique is adaptable to a wide array of downstream experimental assays, and the high degree of specificity afforded by this technique allows more nuanced investigations into the mechanics of protein complex assembly than is currently possible using standard affinity purification techniques.

The dynamic assembly of multiprotein complexes is a central mechanism of many cell signaling pathways. This process is key to maintaining the spatiotemporal specificity required for an accurate, yet adaptive, response to rapidly changing cellular conditions. We describe a technique for the specific isolation and downstream proteomic characterization of any two interacting proteins, to the exclusion of their individual moieties and competing binding partners. We termed the approach bimolecular complementation affinity purification (BiCAP) because it combines the use of conformation-specific nanobodies with a protein-fragment complementation assay with affinity purification. Using BiCAP, we characterized the specific interactome of the epidermal growth factor receptor (EGFR) family member ERBB2 when in the form of a homodimer or when in the form of a heterodimer with either EGFR or ERBB3. We identified dimer-specific interaction patterns for key adaptor proteins and identified a number of previously unknown interacting partners. Functional analysis for one of these newly identified partners revealed a noncanonical mechanism of extracellular signal-regulated kinase (ERK) activation that is specific to the ERBB2:ERBB3 heterodimer and acts through the adaptor protein FAM59A in breast cancer cells.