A first-in-class pan-lysyl oxidase inhibitor impairs stromal remodeling and enhances gemcitabine response and survival in pancreatic cancer.

The lysyl oxidase family represents a promising target in stromal targeting of solid tumors due to the importance of this family in crosslinking and stabilizing fibrillar collagens and its known role in tumor desmoplasia. Using small-molecule drug-design approaches, we generated and validated PXS-5505, a first-in-class highly selective and potent pan-lysyl oxidase inhibitor. We demonstrate in vitro and in vivo that pan-lysyl oxidase inhibition decreases chemotherapy-induced pancreatic tumor desmoplasia and stiffness, reduces cancer cell invasion and metastasis, improves tumor perfusion and enhances the efficacy of chemotherapy in the autochthonous genetically engineered KPC model, while also demonstrating antifibrotic effects in human patient-derived xenograft models of pancreatic cancer. PXS-5505 is orally bioavailable, safe and effective at inhibiting lysyl oxidase activity in tissues. Our findings present the rationale for progression of a pan-lysyl oxidase inhibitor aimed at eliciting a reduction in stromal matrix to potentiate chemotherapy in pancreatic ductal adenocarcinoma.

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.

Temporal profiling of the breast tumour microenvironment reveals collagen XII as a driver of metastasis.

The tumour stroma, and in particular the extracellular matrix (ECM), is a salient feature of solid tumours that plays a crucial role in shaping their progression. Many desmoplastic tumours including breast cancer involve the significant accumulation of type I collagen. However, recently it has become clear that the precise distribution and organisation of matrix molecules such as collagen I is equally as important in the tumour as their abundance. Cancer-associated fibroblasts (CAFs) coexist within breast cancer tissues and play both pro- and anti-tumourigenic roles through remodelling the ECM. Here, using temporal proteomic profiling of decellularized tumours, we interrogate the evolving matrisome during breast cancer progression. We identify 4 key matrisomal clusters, and pinpoint collagen type XII as a critical component that regulates collagen type I organisation. Through combining our proteomics with single-cell transcriptomics, and genetic manipulation models, we show how CAF-secreted collagen XII alters collagen I organisation to create a pro-invasive microenvironment supporting metastatic dissemination. Finally, we show in patient cohorts that collagen XII may represent an indicator of breast cancer patients at high risk of metastatic relapse.

Prostate cancer cell proliferation is influenced by LDL-cholesterol availability and cholesteryl ester turnover.

BACKGROUND: Prostate cancer growth is driven by androgen receptor signaling, and advanced disease is initially treatable by depleting circulating androgens. However, prostate cancer cells inevitably adapt, resulting in disease relapse with incurable castrate-resistant prostate cancer. Androgen deprivation therapy has many side effects, including hypercholesterolemia, and more aggressive and castrate-resistant prostate cancers typically feature cellular accumulation of cholesterol stored in the form of cholesteryl esters. As cholesterol is a key substrate for de novo steroidogenesis in prostate cells, this study hypothesized that castrate-resistant/advanced prostate cancer cell growth is influenced by the availability of extracellular, low-density lipoprotein (LDL)-derived, cholesterol, which is coupled to intracellular cholesteryl ester homeostasis. METHODS: C4-2B and PC3 prostate cancer cells were cultured in media supplemented with fetal calf serum (FCS), charcoal-stripped FCS (CS-FCS), lipoprotein-deficient FCS (LPDS), or charcoal-stripped LPDS (CS-LPDS) and analyzed by a variety of biochemical techniques. Cell viability and proliferation were measured by MTT assay and Incucyte, respectively. RESULTS: Reducing lipoprotein availability led to a reduction in cholesteryl ester levels and cell growth in C4-2B and PC3 cells, with concomitant reductions in PI3K/mTOR and p38MAPK signaling. This reduced growth in LPDS-containing media was fully recovered by supplementation of exogenous low-density lipoprotein (LDL), but LDL only partially rescued growth of cells cultured with CS-LPDS. This growth pattern was not associated with changes in androgen receptor signaling but rather increased p38MAPK and MEK1/ERK/MSK1 activation. The ability of LDL supplementation to rescue cell growth required cholesterol esterification as well as cholesteryl ester hydrolysis activity. Further, growth of cells cultured in low androgen levels (CS-FCS) was suppressed when cholesteryl ester hydrolysis was inhibited. CONCLUSIONS: Overall, these studies demonstrate that androgen-independent prostate cancer cell growth can be influenced by extracellular lipid levels and LDL-cholesterol availability and that uptake of extracellular cholesterol, through endocytosis of LDL-derived cholesterol and subsequent delivery and storage in the lipid droplet as cholesteryl esters, is required to support prostate cancer cell growth. This provides new insights into the relationship between extracellular cholesterol, intracellular cholesterol metabolism, and prostate cancer cell growth and the potential mechanisms linking hypercholesterolemia and more aggressive prostate cancer.

Relationship between Circulating Lipids and Cytokines in Metastatic Castration-Resistant Prostate Cancer.

Circulating lipids or cytokines are associated with prognosis in metastatic castration-resistant prostate cancer (mCRPC). This study aimed to understand the interactions between lipid metabolism and immune response in mCRPC by investigating the relationship between the plasma lipidome and cytokines. Plasma samples from two independent cohorts of men with mCRPC (n = 146, 139) having life-prolonging treatments were subjected to lipidomic and cytokine profiling (290, 763 lipids; 40 cytokines). Higher baseline levels of sphingolipids, including ceramides, were consistently associated with shorter overall survival in both cohorts, whereas the associations of cytokines with overall survival were inconsistent. Increasing levels of IL6, IL8, CXCL16, MPIF1, and YKL40 correlated with increasing levels of ceramide in both cohorts. Men with a poor prognostic 3-lipid signature at baseline had a shorter time to radiographic progression (poorer treatment response) if their lipid profile at progression was similar to that at baseline, or their cytokine profile at progression differed to that at baseline. In conclusion, baseline levels of circulating lipids were more consistent as prognostic biomarkers than cytokines. The correlation between circulating ceramides and cytokines suggests the regulation of immune responses by ceramides. The association of treatment response with the change in lipid profiles warrants further research into metabolic interventions.

Personalized Medicine for Neuroblastoma: Moving from Static Genotypes to Dynamic Simulations of Drug Response.

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.

A non-genetic, cell cycle-dependent mechanism of platinum resistance in lung adenocarcinoma.

We previously used a pulse-based in vitro assay to unveil targetable signalling pathways associated with innate cisplatin resistance in lung adenocarcinoma (Hastings et al., 2020). Here, we advanced this model system and identified a non-genetic mechanism of resistance that drives recovery and regrowth in a subset of cells. Using RNAseq and a suite of biosensors to track single-cell fates both in vitro and in vivo, we identified that early S phase cells have a greater ability to maintain proliferative capacity, which correlated with reduced DNA damage over multiple generations. In contrast, cells in G1, late S or those treated with PARP/RAD51 inhibitors, maintained higher levels of DNA damage and underwent prolonged S/G2 phase arrest and senescence. Combined with our previous work, these data indicate that there is a non-genetic mechanism of resistance in human lung adenocarcinoma that is dependent on the cell cycle stage at the time of cisplatin exposure.

Analysis of pulsed cisplatin signalling dynamics identifies effectors of resistance in lung adenocarcinoma.

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.

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.

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.

The extracellular matrix as a key regulator of intracellular signalling networks.

The extracellular matrix (ECM) is a salient feature of all solid tissues within the body. This complex, acellular entity is composed of hundreds of individual molecules whose assembly, architecture and biomechanical properties are critical to controlling the behaviour and phenotype of the different cell types residing within tissues. Cells are the basic unit of life and the core building block of tissues and organs. At their simplest, they follow a set of rules, governed by their genetic code and effected through the complex protein signalling networks that these genes encode. These signalling networks assimilate and process the information received by the cell to control cellular decisions that govern cell fate. The ECM is the biggest provider of external stimuli to cells and as such is responsible for influencing intracellular signalling dynamics. In this review, we discuss the inclusion of ECM as a central regulatory signalling sub-network in computational models of cellular decision making, with a focus on its role in diseases such as cancer. LINKED ARTICLES: This article is part of a themed section on Translating the Matrix. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v176.1/issuetoc.

Inhibition of activin signaling in lung adenocarcinoma increases the therapeutic index of platinum chemotherapy.

Resistance to platinum chemotherapy is a long-standing problem in the management of lung adenocarcinoma. Using a whole-genome synthetic lethal RNA interference screen, we identified activin signaling as a critical mediator of innate platinum resistance. The transforming growth factor-ß (TGFß) superfamily ligands activin A and growth differentiation factor 11 (GDF11) mediated resistance via their cognate receptors through TGFß-activated kinase 1 (TAK1), rather than through the SMAD family of transcription factors. Inhibition of activin receptor signaling or blockade of activin A and GDF11 by the endogenous protein follistatin overcame this resistance. Consistent with the role of activin signaling in acute renal injury, both therapeutic interventions attenuated acute cisplatin-induced nephrotoxicity, its major dose-limiting side effect. This cancer-specific enhancement of platinum-induced cell death has the potential to dramatically improve the safety and efficacy of chemotherapy in lung cancer patients.

Dissecting Multi-protein Signaling Complexes by Bimolecular Complementation Affinity Purification (BiCAP).

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 Under-Appreciated Promiscuity of the Epidermal Growth Factor Receptor Family.

Each member of the epidermal growth factor receptor (EGFR) family plays a key role in normal development, homeostasis, and a variety of pathophysiological conditions, most notably in cancer. According to the prevailing dogma, these four receptor tyrosine kinases (RTKs; EGFR, ERBB2, ERBB3, and ERBB4) function exclusively through the formation of homodimers and heterodimers within the EGFR family. These combinatorial receptor interactions are known to generate increased interactome diversity and therefore influence signaling output, subcellular localization and function of the heterodimer. This molecular plasticity is also thought to play a role in the development of resistance toward targeted cancer therapies aimed at these known oncogenes. Interestingly, many studies now challenge this dogma and suggest that the potential for EGFR family receptors to interact with more distantly related RTKs is much greater than currently appreciated. Here we discuss how the promiscuity of these oncogenic receptors may lead to the formation of many unexpected receptor pairings and the significant implications for the efficiency of many targeted cancer therapies.

Bimolecular complementation affinity purification (BiCAP) reveals dimer-specific protein interactions for ERBB2 dimers.

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.

Signaling pathway models as biomarkers: Patient-specific simulations of JNK activity predict the survival of neuroblastoma patients.

Signaling pathways control cell fate decisions that ultimately determine the behavior of cancer cells. Therefore, the dynamics of pathway activity may contain prognostically relevant information different from that contained in the static nature of other types of biomarkers. To investigate this hypothesis, we characterized the network that regulated stress signaling by the c-Jun N-terminal kinase (JNK) pathway in neuroblastoma cells. We generated an experimentally calibrated and validated computational model of this network and used the model to extract prognostic information from neuroblastoma patient-specific simulations of JNK activation. Switch-like JNK activation mediates cell death by apoptosis. An inability to initiate switch-like JNK activation in the simulations was significantly associated with poor overall survival for patients with neuroblastoma with or without MYCN amplification, indicating that patient-specific simulations of JNK activation could stratify patients. Furthermore, our analysis demonstrated that extracting information about a signaling pathway to develop a prognostically useful model requires understanding of not only components and disease-associated changes in the abundance or activity of the components but also how those changes affect pathway dynamics.