A Model of Dormant-Emergent Metastatic Breast Cancer Progression Enabling Exploration of Biomarker Signatures.

Breast cancer mortality predominantly results from dormant micrometastases that emerge as fatal outgrowths years after initial diagnosis. In order to gain insights concerning factors associated with emergence of liver metastases, we recreated spontaneous dormancy in an all-human ex vivo hepatic microphysiological system (MPS). Seeding this MPS with small numbers (<0.05% by cell count) of the aggressive MDA-MB-231 breast cancer cell line, two populations formed: actively proliferating ("growing"; EdU+), and spontaneously quiescent ("dormant"; EdU-). Following treatment with a clinically standard chemotherapeutic, the proliferating cells were eliminated and only quiescent cells remained; this residual dormant population could then be induced to a proliferative state ("emergent"; EdU+) by physiologically-relevant inflammatory stimuli, lipopolysaccharide (LPS) and epidermal growth factor (EGF). Multiplexed proteomic analysis of the MPS effluent enabled elucidation of key factors and processes that correlated with the various tumor cell states, and candidate biomarkers for actively proliferating (either primary or secondary emergence) versus dormant metastatic cells in liver tissue. Dormancy was found to be associated with signaling reflective of cellular quiescence even more strongly than the original tumor-free liver tissue, whereas proliferative nodules presented inflammatory signatures. Given the minimal tumor burden, these markers likely represent changes in the tumor microenvironment rather than in the tumor cells. A computational decision tree algorithm applied to these signatures indicated the potential of this MPS for clinical discernment of each metastatic stage from blood protein analysis.

Integrated Assessment of Diclofenac Biotransformation, Pharmacokinetics, and Omics-Based Toxicity in a Three-Dimensional Human Liver-Immunocompetent Coculture System.

In vitro hepatocyte culture systems have inherent limitations in capturing known human drug toxicities that arise from complex immune responses. Therefore, we established and characterized a liver immunocompetent coculture model and evaluated diclofenac (DCF) metabolic profiles, in vitro-in vivo clearance correlations, toxicological responses, and acute phase responses using liquid chromatography-tandem mass spectrometry. DCF biotransformation was assessed after 48 hours of culture, and the major phase I and II metabolites were similar to the in vivo DCF metabolism profile in humans. Further characterization of secreted bile acids in the medium revealed that a glycine-conjugated bile acid was a sensitive marker of dose-dependent toxicity in this three-dimensional liver microphysiological system. Protein markers were significantly elevated in the culture medium at high micromolar doses of DCF, which were also observed previously for acute drug-induced toxicity in humans. In this immunocompetent model, lipopolysaccharide treatment evoked an inflammatory response that resulted in a marked increase in the overall number of acute phase proteins. Kupffer cell-mediated cytokine release recapitulated an in vivo proinflammatory response exemplified by a cohort of 11 cytokines that were differentially regulated after lipopolysaccharide induction, including interleukin (IL)-1ß, IL-1Ra, IL-6, IL-8, IP-10, tumor necrosis factor-α, RANTES (regulated on activation normal T cell expressed and secreted), granulocyte colony-stimulating factor, macrophage colony-stimulating factor, macrophage inflammatory protein-1ß, and IL-5. In summary, our findings indicate that three-dimensional liver microphysiological systems may serve as preclinical investigational platforms from the perspective of the discovery of a set of clinically relevant biomarkers including potential reactive metabolites, endogenous bile acids, excreted proteins, and cytokines to predict early drug-induced liver toxicity in humans.

Analysis of ER resident proteins in Saccharomyces cerevisiae: implementation of H/KDEL retrieval sequences.

An elaborate quality control system regulates endoplasmic reticulum (ER) homeostasis by ensuring the fidelity of protein synthesis and maturation. In budding yeast, genomic analyses and high-throughput proteomic studies have identified ER resident proteins that restore homeostasis following local perturbations. Yet, how these folding factors modulate stress has been largely unexplored. In this study, we designed a series of polymerase chain reaction (PCR)-based modules including codon-optimized epitopes and fluorescent protein (FP) variants complete with C-terminal H/KDEL retrieval motifs. These conserved sequences are inherent to most soluble ER resident proteins. To monitor multiple proteins simultaneously, H/KDEL cassettes are available with six different selection markers, providing optimal flexibility for live-cell imaging and multicolor labeling in vivo. A single pair of PCR primers can be used for the amplification of these 26 modules, enabling numerous combinations of tags and selection markers. The versatility of pCY H/KDEL cassettes was demonstrated by labeling BiP/Kar2p, Pdi1p and Scj1p with all novel tags, thus providing a direct comparison among FP variants. Furthermore, to advance in vitro studies of yeast ER proteins, Strep-tag II was engineered with a C-terminal retrieval sequence. Here, an efficient purification strategy was established for BiP under physiological conditions.

BiP clustering facilitates protein folding in the endoplasmic reticulum.

The chaperone BiP participates in several regulatory processes within the endoplasmic reticulum (ER): translocation, protein folding, and ER-associated degradation. To facilitate protein folding, a cooperative mechanism known as entropic pulling has been proposed to demonstrate the molecular-level understanding of how multiple BiP molecules bind to nascent and unfolded proteins. Recently, experimental evidence revealed the spatial heterogeneity of BiP within the nuclear and peripheral ER of S. cerevisiae (commonly referred to as 'clusters'). Here, we developed a model to evaluate the potential advantages of accounting for multiple BiP molecules binding to peptides, while proposing that BiP's spatial heterogeneity may enhance protein folding and maturation. Scenarios were simulated to gauge the effectiveness of binding multiple chaperone molecules to peptides. Using two metrics: folding efficiency and chaperone cost, we determined that the single binding site model achieves a higher efficiency than models characterized by multiple binding sites, in the absence of cooperativity. Due to entropic pulling, however, multiple chaperones perform in concert to facilitate the resolubilization and ultimate yield of folded proteins. As a result of cooperativity, multiple binding site models used fewer BiP molecules and maintained a higher folding efficiency than the single binding site model. These insilico investigations reveal that clusters of BiP molecules bound to unfolded proteins may enhance folding efficiency through cooperative action via entropic pulling.

Cassette series designed for live-cell imaging of proteins and high-resolution techniques in yeast.

During the past decade, it has become clear that protein function and regulation are highly dependent upon intracellular localization. Although fluorescent protein variants are ubiquitously used to monitor protein dynamics, localization and abundance; fluorescent light microscopy techniques often lack the resolution to explore protein heterogeneity and cellular ultrastructure. Several approaches have been developed to identify, characterize and monitor the spatial localization of proteins and complexes at the suborganelle level, yet many of these techniques have not been applied to yeast. Thus, we have constructed a series of cassettes containing codon-optimized epitope tags, fluorescent protein variants that cover the full spectrum of visible light, a TetCys motif used for fluorescein arsenical hairpin (FlAsH)-based localization, and the first evaluation in yeast of a photoswitchable variant, mEos2, to monitor discrete subpopulations of proteins via confocal microscopy. This series of modules, complete with six different selection markers, provides the optimal flexibility during live-cell imaging and multicolour labelling in vivo. Furthermore, high-resolution imaging techniques include the yeast-enhanced TetCys motif, which is compatible with diaminobenzidine photo-oxidation used for protein localization by electron microscopy, and mEos2, which is ideal for super-resolution microscopy. We have examined the utility of our cassettes by analysing all probes fused to the C-terminus of Sec61, a polytopic membrane protein of the endoplasmic reticulum of moderate protein concentration, in order to directly compare fluorescent probes, their utility and technical applications. Our series of cassettes expand the repertoire of molecular tools available to advance targeted spatiotemporal investigations using multiple live-cell, super-resolution or electron microscopy imaging techniques.

Quantitative systems pharmacology modeling provides insight into inter-mouse variability of Anti-CTLA4 response.

Clinical responses of immuno-oncology therapies are highly variable among patients. Similar response variability has been observed in syngeneic mouse models. Understanding of the variability in the mouse models may shed light on patient variability. Using a murine anti-CTLA4 antibody as a case study, we developed a quantitative systems pharmacology model to capture the molecular interactions of the antibody and relevant cellular interactions that lead to tumor cell killing. Nonlinear mixed effect modeling was incorporated to capture the inter-animal variability of tumor growth profiles in response to anti-CTLA4 treatment. The results suggested that intratumoral CD8+ T cell kinetics and tumor proliferation rate were the main drivers of the variability. In addition, simulations indicated that nonresponsive mice to anti-CTLA4 treatment could be converted to responders by increasing the number of intratumoral CD8+ T cells. The model provides a mechanistic starting point for translation of CTLA4 inhibitors from syngeneic mice to the clinic.

Quantitative systems pharmacology model for Alzheimer's disease to predict the effect of aducanumab on brain amyloid.

Alzheimer's disease (AD) is an irreversible, progressive brain disorder that impairs memory and cognitive function. Dysregulation of the amyloid-ß (Aß) pathway and amyloid plaque accumulation in the brain are hallmarks of AD. Aducanumab is a human, immunoglobulin gamma 1 monoclonal antibody targeting aggregated forms of Aß. In phase Ib and phase III studies, aducanumab reduced Aß plaques in a dose dependent manner, as measured by standard uptake value ratio of amyloid positron emission tomography imaging. The goal of this work was to develop a quantitative systems pharmacology model describing the production, aggregation, clearance, and transport of Aß as well as the mechanism of action for the drug to understand the relationship between aducanumab dosing regimens and changes of different Aß species, particularly plaques in the brain. The model was used to better understand the pharmacodynamic effects observed in the clinical trials of aducanumab and assist in the clinical development of future Aß therapies.

Recombinant G protein-coupled receptor expression in Saccharomyces cerevisiae for protein characterization.

G protein-coupled receptors (GPCRs) are membrane proteins that mediate signaling across the cellular membrane and facilitate cellular responses to external stimuli. Due to the critical role that GPCRs play in signal transduction, therapeutics have been developed to influence GPCR function without an extensive understanding of the receptors themselves. Closing this knowledge gap is of paramount importance to improving therapeutic efficacy and specificity, where efforts to achieve this end have focused chiefly on improving our knowledge of the structure-function relationship. The purpose of this chapter is to review methods for the heterologous expression of GPCRs in Saccharomyces cerevisiae, including whole-cell assays that enable quantitation of expression, localization, and function in vivo. In addition, we describe methods for the micellular solubilization of the human adenosine A2a receptor and for reconstitution of the receptor in liposomes that have enabled its biophysical characterization.

Protein folding and secretion: mechanistic insights advancing recombinant protein production in S. cerevisiae.

The emergence of genomic approaches coupled to recombinant DNA technologies have identified the quality control systems that regulate proteostasis - biological pathways that modulate protein biogenesis, maturation, trafficking, and degradation. The elucidation of these pathways has become of growing importance in therapeutics as loss of proteostasis has been suggested to lead to a number of human diseases including Alzheimer's, Parkinson's Disease and Type II Diabetes. We anticipate that the most successful strategies for protein expression and therapeutics development may involve integration of protein engineering strategies with host manipulation, to exploit the cell's native stress response pathways and trafficking mechanisms. This review will highlight recent findings and mechanistic detail correlated to quality control in the early secretory pathway of Saccharomyces cerevisiae.

Approaches to in vitro tissue regeneration with application for human disease modeling and drug development.

Reliable in vitro human disease models that capture the complexity of in vivo tissue behaviors are crucial to gain mechanistic insights into human disease and enable the development of treatments that are effective across broad patient populations. The integration of stem cell technologies, tissue engineering, emerging biomaterials strategies and microfabrication processes, as well as computational and systems biology approaches, is enabling new tools to generate reliable in vitro systems to study the molecular basis of human disease and facilitate drug development. In this review, we discuss these recently developed tools and emphasize opportunities and challenges involved in combining these technologies toward regenerative science.

A microphysiological system model of therapy for liver micrometastases.

Metastasis accounts for almost 90% of cancer-associated mortality. The effectiveness of cancer therapeutics is limited by the protective microenvironment of the metastatic niche and consequently these disseminated tumors remain incurable. Metastatic disease progression continues to be poorly understood due to the lack of appropriate model systems. To address this gap in understanding, we propose an all-human microphysiological system that facilitates the investigation of cancer behavior in the liver metastatic niche. This existing LiverChip is a 3D-system modeling the hepatic niche; it incorporates a full complement of human parenchymal and non-parenchymal cells and effectively recapitulates micrometastases. Moreover, this system allows real-time monitoring of micrometastasis and assessment of human-specific signaling. It is being utilized to further our understanding of the efficacy of chemotherapeutics by examining the activity of established and novel agents on micrometastases under conditions replicating diurnal variations in hormones, nutrients and mild inflammatory states using programmable microdispensers. These inputs affect the cues that govern tumor cell responses. Three critical signaling groups are targeted: the glucose/insulin responses, the stress hormone cortisol and the gut microbiome in relation to inflammatory cues. Currently, the system sustains functioning hepatocytes for a minimum of 15 days; confirmed by monitoring hepatic function (urea, α-1-antitrypsin, fibrinogen, and cytochrome P450) and injury (AST and ALT). Breast cancer cell lines effectively integrate into the hepatic niche without detectable disruption to tissue, and preliminary evidence suggests growth attenuation amongst a subpopulation of breast cancer cells. xMAP technology combined with systems biology modeling are also employed to evaluate cellular crosstalk and illustrate communication networks in the early microenvironment of micrometastases. This model is anticipated to identify new therapeutic strategies for metastasis by elucidating the paracrine effects between the hepatic and metastatic cells, while concurrently evaluating agent efficacy for metastasis, metabolism and tolerability.

All-human microphysical model of metastasis therapy.

The vast majority of cancer mortalities result from distant metastases. The metastatic microenvironment provides unique protection to ectopic tumors as the primary tumors often respond to specific agents. Although significant interventional progress has been made on primary tumors, the lack of relevant accessible model in vitro systems in which to study metastases has plagued metastatic therapeutic development--particularly among micrometastases. A real-time, all-human model of metastatic seeding and cancer cells that recapitulate metastatic growth and can be probed in real time by a variety of measures and challenges would provide a critical window into the pathophysiology of metastasis and pharmacology of metastatic tumor resistance. To achieve this we are advancing our microscale bioreactor that incorporates human hepatocytes, human nonparenchymal liver cells, and human breast cancer cells to mimic the hepatic niche in three dimensions with functional tissue. This bioreactor is instrumented with oxygen sensors, micropumps capable of generating diurnally varying profiles of nutrients and hormones, while enabling real-time sampling. Since the liver is a major metastatic site for a wide variety of carcinomas and other tumors, this bioreactor uniquely allows us to more accurately recreate the human metastatic microenvironment and probe the paracrine effects between the liver parenchyma and metastatic cells. Further, as the liver is the principal site of xenobiotic metabolism, this reactor will help us investigate the chemotherapeutic response within a metabolically challenged liver microenvironment. This model is anticipated to yield markers of metastatic behavior and pharmacologic metabolism that will enable better clinical monitoring, and will guide the design of clinical studies to understand drug efficacy and safety in cancer therapeutics. This highly instrumented bioreactor format, hosting a growing tumor within a microenvironment and monitoring its responses, is readily transferable to other organs, giving this work impact beyond the liver.

Recombinant protein expression and purification: a comprehensive review of affinity tags and microbial applications.

Protein fusion tags are indispensible tools used to improve recombinant protein expression yields, enable protein purification, and accelerate the characterization of protein structure and function. Solubility-enhancing tags, genetically engineered epitopes, and recombinant endoproteases have resulted in a versatile array of combinatorial elements that facilitate protein detection and purification in microbial hosts. In this comprehensive review, we evaluate the most frequently used solubility-enhancing and affinity tags. Furthermore, we provide summaries of well-characterized purification strategies that have been used to increase product yields and have widespread application in many areas of biotechnology including drug discovery, therapeutics, and pharmacology. This review serves as an excellent literature reference for those working on protein fusion tags.

High-resolution three-dimensional reconstruction of a whole yeast cell using focused-ion beam scanning electron microscopy.

We developed an approach for focused gallium-ion beam scanning electron microscopy with energy filtered detection of backscattered electrons to create near isometric voxels for high-resolution whole cell visualization. Specifically, this method allowed us to create three-dimensional volumes of high-pressure frozen, freeze-substituted Saccharomyces cerevisiae yeast cells with pixel resolutions down to 3 nm/pixel in x, y, and z, supported by both empirical data and Monte Carlo simulations. As a result, we were able to segment and quantify data sets of numerous targeted subcellular structures/organelles at high-resolution, including the volume, volume percentage, and surface area of the endoplasmic reticulum, cell wall, vacuoles, and mitochondria from an entire cell. Sites of mitochondrial and endoplasmic reticulum interconnectivity were readily identified in rendered data sets. The ability to visualize, segment, and quantify entire eukaryotic cells at high-resolution (potentially sub-5 nanometers isotropic voxels) will provide new perspectives and insights of the inner workings of cells.

Decreased secretion and unfolded protein response upregulation.

Recombinant antibody fragments, for example, the classic monovalent single-chain antibody (scFv), are emerging as credible alternatives to monoclonal antibody (mAb) products. scFv fragments maintain a diverse range of potential applications in biotechnology and can be implemented as powerful therapeutic and diagnostic agents. As such, a variety of hosts have been used to produce antibody fragments resulting in varying degrees of success. Yeast, Saccharomyces cerevisiae, is an attractive host due to quality control mechanisms of the secretory pathway that ensure secreted proteins are properly folded. However, the expression of a recombinant protein in yeast is not trivial; neither are the quality control mechanisms the cell initiates to respond to overwhelming stress, such as an increased protein load, simplistic. The endoplasmic reticulum (ER) is a dynamic organelle, capable of sensing and adjusting its folding capacity in response to increased demand. When protein abundance or terminally misfolded proteins overwhelm the ER's capacity, the unfolded protein response (UPR) is activated. In the guidelines presented here, we discuss varying aspects of quality control, its modulation, and ways to design appropriate constructs for yeast recombinant protein expression. Furthermore, we have provided protocols and methods to monitor intracellular protein expression and trafficking as well as evaluation of the UPR, with essential controls. The latter part of this chapter will review considerations for the experimental design of microarray and quantitative polymerase chain reaction (q-PCR) techniques while suggesting appropriate means of data analysis.

Progress toward heterologous expression of active G-protein-coupled receptors in Saccharomyces cerevisiae: Linking cellular stress response with translocation and trafficking.

High-level expression of mammalian G-protein-coupled receptors (GPCRs) is a necessary step toward biophysical characterization and high-resolution structure determination. Even though many heterologous expression systems have been used to express mammalian GPCRs at high levels, many receptors are improperly trafficked or are inactive in these systems. En route to engineering a robust microbial host for GPCR expression, we have investigated the expression of 12 GPCRs in the yeast Saccharomyces cerevisiae, where all receptors are expressed at the mg/L scale. However, only the human adenosine A(2)a (hA(2)aR) receptor is active for ligand-binding and located primarily at the plasma membrane, whereas other tested GPCRs are mainly retained within the cell. Selective receptors associate with BiP, an ER-resident chaperone, and activated the unfolded protein response (UPR) pathway, which suggests that a pool of receptors may be folded incorrectly. Leader sequence cleavage of the expressed receptors was complete for the hA(2)aR, as expected, and partially cleaved for hA(2)bR, hCCR5R, and hD(2L)R. Ligand-binding assays conducted on the adenosine family (hA(1)R, hA(2)aR, hA(2)bR, and hA(3)R) of receptors show that hA(2)aR and hA(2)bR, the only adenosine receptors that demonstrate leader sequence processing, display activity. Taken together, these studies point to translocation as a critical limiting step in the production of active mammalian GPCRs in S. cerevisiae.