Mixed IgG Fc immune complexes exhibit blended binding profiles and refine FcR affinity estimates.Z. C. Tan, A. Lux, M. Biburger, P. Varghese, S. Lees, F. Nimmerjahn, & A. S. Meyer. (2023). Cell Reports (Accepted).[Abstract]
Abstract: Immunoglobulin (Ig)G antibodies coordinate immune effector responses by selectively binding to target
antigens and then interacting with various effector cells via the Fcγ receptors. The Fc domain of IgG can
promote or inhibit distinct effector responses across several different immune cell types through variation
based on subclass and Fc domain glycosylation. Extensive characterization of these interactions has revealed
how the inclusion of certain Fc subclasses or glycans results in distinct immune responses. During an immune
response, however, IgG is produced with mixtures of Fc domain properties, so antigen-IgG immune complexes are
likely to almost always be comprised of a combination of Fc forms. Whether and how this mixed composition
influences immune effector responses has not been examined. Here, we measured Fcγ receptor binding to immune
complexes of mixed Fc domain composition. We found that the binding properties of the mixed-composition immune
complexes fell along a continuum between those of the corresponding pure cases. Binding quantitatively matched
a mechanistic binding model, except for several low-affinity interactions mostly involving IgG2. We found that
the affinities of these interactions are different than previously reported, and that the binding model could
be used to provide refined estimates of these affinities. Finally, we demonstrated that the binding model can
predict effector-cell elicited platelet depletion in humanized mice, with the model inferring the relevant effector
cell populations. Contrary to the previous view in which IgG2 poorly engages with effector populations, we observe
appreciable binding through avidity, but insufficient amounts to observe immune effector responses. Overall, this
work demonstrates a quantitative framework for reasoning about effector response regulation arising from IgG of
mixed Fc composition.
Design of cell-type-specific hyperstable IL-4 mimetics via modular de novo scaffolds.H. Yang, U. Y. Ulge, A. Quijano-Rubio, Z. J. Bernstein, J. David R. Maestas, J.-H. Chun, W. Wang, J.-X. Lin, K. M. Jude, S. Singh, B. T. Orcutt-Jahns, P. Li, J. Mou, L. Chung, Y.-H. Kuo, Y. H. Ali, A. S. Meyer, W. L. Grayson, N. M. Heller, K. C. Garcia, … J. B. Spangler. (2023). Nature Chemical Biology.[Abstract]
Abstract: The interleukin-4 (IL-4) cytokine plays a critical role in modulating immune homeostasis. Although there is great interest in harnessing this cytokine as a therapeutic in natural or engineered formats, the clinical potential of native IL-4 is limited by its instability and pleiotropic actions. Here, we design IL-4 cytokine mimetics (denoted Neo-4) based on a de novo engineered IL-2 mimetic scaffold and demonstrate that these cytokines can recapitulate physiological functions of IL-4 in cellular and animal models. In contrast with natural IL-4, Neo-4 is hyperstable and signals exclusively through the type I IL-4 receptor complex, providing previously inaccessible insights into differential IL-4 signaling through type I versus type II receptors. Because of their hyperstability, our computationally designed mimetics can directly incorporate into sophisticated biomaterials that require heat processing, such as three-dimensional-printed scaffolds. Neo-4 should be broadly useful for interrogating IL-4 biology, and the design workflow will inform targeted cytokine therapeutic development.
Analysis and modeling of cancer drug responses using cell cycle phase-specific rate
effects.S. M. Gross, F. Mohammadi, C. Sanchez-Aguila, P. J. Zhan, A. S. Meyer, & L. M. Heiser. (2023). Nature Communications (Accepted).[Abstract]
Abstract: A major challenge to improving outcomes for patients with cancer is the identification of
effective therapeutic strategies that can prevent tumor cell proliferation. Here we sought
to gain a deeper understanding of how anti-cancer agents modulate cell cycle progression in
HER2+ breast cancer, a disease subtype that accounts for 20% of all breast cancers. We
treated HER2+ breast cancer cells with a panel of drugs and tracked changes in cell number
and cell cycle phase, which revealed drug-specific cell cycle effects that varied across
time. This suggested that a computational model that could account for cell cycle phase
durations would provide a framework to explore drug-induced changes in cell cycle changes.
Toward that goal, we developed a linear chain trick (LCT) computational model, in which the
cell cycle is partitioned into subphases that faithfully captured drug-induced dynamic
responses. The model inferred phase-specific drug effects and independent modulation of cell
cycle phases, which we confirmed experimentally. We then used our LCT model to predict the
effect of unseen drug combinations that target cells in different cell cycle phases.
Experimental testing confirmed several model predictions and identified combination
treatment strategies that may improve therapeutic response in patients with HER2+ breast
cancer. Overall, this integrated experimental and modeling approach opens new avenues for
assessing drug responses, predicting effective drug combinations, and identifying optimal
drug sequencing strategies.
Abstract: Type I interferons (IFN) induce powerful antiviral and innate immune responses via the
transcription factor, IFN-stimulated gene factor (ISGF3). However, in some pathological contexts,
type I IFNs are responsible for exacerbating inflammation. Here, we show that a high dose of IFN-β
also activates an inflammatory gene expression program in contrast to IFN-λ3, a type III IFN, which
elicits only the common antiviral gene program. We show that the inflammatory gene program depends
on a second, potentiated phase in ISGF3 activation. Iterating between mathematical modeling and
experimental analysis, we show that the ISGF3 activation network may engage a positive feedback loop
with its subunits IRF9 and STAT2. This network motif mediates stimulus-specific ISGF3 dynamics that
are dependent on ligand, dose, and duration of exposure, and when engaged activates the inflammatory
gene expression program. Our results reveal a previously underappreciated dynamical control of the
JAK-STAT/IRF signaling network that may produce distinct biological responses and suggest that studies
of type I IFN dysregulation, and in turn therapeutic remedies, may focus on feedback regulators within it.
Abstract: Profiling immune responses across several dimensions, including time, patients, molecular features, and tissue
sites, can deepen our understanding of immunity as an integrated system. These studies require new analysis approaches
to realize their full potential. We highlight the recent application of tensor methods and discuss several future
opportunities.
Disulfide-HMGB1 Signals Through TLR4 and TLR9 to Induce Inflammatory Macrophages Capable of Innate-Adaptive Crosstalk in Human Liver Transplantation.A. Q. Terry, H. Kojima, R. A. Sosa, F. M. Kaldas, J. L. Chin, Y. Zheng, B. V. Naini, D. Noguchi, J. N.- Mejia, Y.-P. Jin, R. W. Busuttil, A. S. Meyer, D. W. Gjertson, J. W. Kupiec-Weglinski, & E. F. Reed. (2023). Submitted.
Multivalent, asymmetric IL-2-Fc fusions provide optimally enhanced regulatory T cell selectivity.B. Orcutt-Jahns, P. C. Emmel, E. M. Snyder, S. D. Taylor, & A. S. Meyer. (2022). Submitted.[Abstract]
Abstract: The common γ-chain receptor cytokines coordinate the proliferation and function of immune cell populations. One of these cytokines, interleukin (IL)-2, has potential as a therapy in autoimmune disease but is limited in effectiveness by its modest specificity toward regulatory T cells (Tregs). Engineering Treg-selective IL-2 has primarily focused on retaining binding to the high-affinity receptor, expressed more highly on Tregs, while reducing binding to the lower affinity receptor with broader expression. However, other parameters, such as the orientation and valency of Fc fusion, have signaling effects that have never been systematically explored. Here, we systematically profiled the signaling responses to a panel of wild type and mutein IL-2-Fc fusions across time, cell types, and concentrations. Exploring these responses, we found that dimeric muteins have unique specificity for Tregs through binding avidity. A mechanistic model of receptor interactions could capture these effects and directed the design of tetravalent IL-2-Fc fusions with greater Treg specificity than possible with current design strategies. Exploration of other surface targets on Tregs revealed that there are no other binding moieties that could be fused to IL-2 for greater selectivity. Instead, IL2Rα itself is a maximally unique surface target for Tregs, and so avidity is likely the only route to more selective Treg interaction. However, the binding model revealed that asymmetrical, multivalent IL-2 fusions can bias avidity effects toward IL2Rα for even further enhanced Treg selectivity. These findings present a comprehensive analysis of how ligand properties and their effects on surface receptor-ligand interactions translate to selective activation of immune cell populations, and consequently reveals two new routes toward therapeutic cytokines with superior Treg selectivity that can be exploited for designing selective therapies in many other contexts.
Cytokine-expression patterns reveal coordinated immunological programs associated with persistent MRSA bacteremia.J. L. Chin, Z. C. Tan, L. C. Chan, F. Ruffin, R. Parmar, R. Ahn, S. Taylor, A. S. Bayer, A. Hoffmann, J. Vance G Fowler, E. F. Reed, M. R. Yeaman, A. S. Meyer, & MRSA Systems Immunobiology Group. (2022). Submitted.[Abstract]
Abstract: Methicillin-resistant Staphylococcus aureus (MRSA) bacteremia is a common, life-threatening
infection that imposes up to 30% mortality even when appropriate therapy is used. Despite in
vitro efficacy, antibiotics often fail to resolve the infection in vivo, resulting in persistent
MRSA bacteremia. Recently, several genetic, epigenetic, and proteomic correlates of persistent
outcomes have been identified. However, the extent to which single variables or composite patterns
operate as independent predictors of outcome or reflect shared underlying mechanisms of persistence
is unknown. To explore this question, we employed a tensor-based integration of host transcriptional
and proteomic data across a well-characterized cohort of patients with persistent and resolving MRSA
bacteremia outcomes. Tensor-based data integration yielded high correlative accuracy with persistence
and revealed immunologic signatures shared across both the transcriptomic and proteomic datasets. We
find that elevated proliferation of mature granulocytes associates with resolving bacteremia outcomes.
In contrast, patients with persistent bacteremia heterogeneously exhibit correlates of granulocyte
dysfunction or immature granulocyte proliferation. Collectively, these results suggest that transcriptional
and proteomic correlates of persistent versus resolving bacteremia outcomes are complex and may not be
disclosed by conventional modeling. However, a tensor-based integration approach can help to reveal
consensus molecular mechanisms in an interpretable manner.
Abstract: Individual cells can assume a variety of molecular and phenotypic states and recent studies
indicate that cells can rapidly adapt in response to therapeutic stress. Such phenotypic plasticity
may confer resistance, but also presents opportunities to identify molecular programs that could be
targeted for therapeutic benefit. Approaches to quantify tumor-drug responses typically focus on
snapshot, population-level measurements. While informative, these methods lack lineage and temporal
information, which are particularly critical for understanding dynamic processes such as cell state
switching. As new technologies have become available to measure lineage relationships, modeling
approaches will be needed to identify the forms of cell-to-cell heterogeneity present in these data.
Here we apply a lineage tree-based adaptation of a hidden Markov model that employs single cell
lineages as input to learn the characteristic patterns of phenotypic heterogeneity and state
transitions. In benchmarking studies, we demonstrated that the model successfully classifies cells
within experimentally-tractable dataset sizes. As an application, we analyzed experimental
measurements in cancer and non-cancer cell populations under various treatments. We find evidence
of multiple phenotypically distinct states, with considerable heterogeneity and unique drug responses.
In total, this framework allows for the flexible modeling of single cell heterogeneity across lineages
to quantify, understand, and control cell state switching.
Abstract: Cancer drug response is heavily influenced by the extracellular matrix (ECM) environment.
Despite a clear appreciation that the ECM influences cancer drug response and progression, a
unified view of how, where, and when environment-mediated drug resistance contributes to
cancer progression has not coalesced. Here, we survey some specific ways in which the ECM
contributes to cancer resistance with a focus on how materials development can coincide with
systems biology approaches to better understand and perturb this contribution. We argue that
part of the reason that environment-mediated resistance remains a perplexing problem is our
lack of a wholistic view of the entire range of environments and their impacts on cell
behavior. We cover a series of recent experimental and computational tools that will aid
exploration of ECM reactions space, and how they might be synergistically integrated.
Abstract: Low dose human interleukin-2 (hIL-2) treatment is used clinically to treat autoimmune
disorders due to the cytokine’s preferential expansion of immunosuppressive
regulatory T cells (TRegs). However, high toxicity, short serum half-life, and off-target
immune cell activation limit the clinical potential of IL-2 treatment. Recent work showed
that complexes comprising hIL-2 and the anti-hIL-2 antibody F5111 overcome these limitations
by preferentially stimulating TRegs over immune effector cells. Although promising,
therapeutic translation of this approach is complicated by the need to optimize dosing
ratios and by the instability of the cytokine/antibody complex. We leveraged structural
insights to engineer a single-chain hIL-2/F5111 antibody fusion protein, termed F5111
immunocytokine (IC), that potently and selectively activates and expands TRegs. F5111 IC
conferred protection in mouse models of colitis and checkpoint inhibitor-induced diabetes
mellitus. These results provide a roadmap for IC design and establish a TReg-biased
immunotherapy that could be clinically translated for autoimmune disease treatment.
Abstract: Cell signaling is orchestrated in part through a network of protein kinases and
phosphatases. Dysregulation of kinase signaling is widespread in diseases such as cancer and
is readily targetable through inhibitors. Mass spectrometry-based analysis can provide a
global view of kinase regulation but mining these data is complicated by its stochastic
coverage of the proteome, measurement of substrates rather than kinases, and the scale of
the data. Here, we implement a Dual Data and Motif Clustering (DDMC) strategy that
simultaneously clusters peptides into similarly regulated groups based on their variation
and their sequence profile. We show that this can help to identify putative upstream kinases
and supply more robust clustering. We apply this clustering to clinical proteomic profiling
of lung cancer and identify conserved proteomic signatures of tumorigenicity, genetic
mutations, and immune infiltration. We propose that DDMC provides a general and flexible
clustering strategy for the analysis of phosphoproteomic data.
Abstract: To better understand the signaling complexity of AXL, a member of the TAM receptor
tyrosine kinase family, we created a physical and functional map of AXL signaling
interactions, phosphorylation events, and target-engagement of three AXL tyrosine kinase
inhibitors (TKI). We assessed AXL protein-complexes using BioID, effects of AXL TKI on
global phosphoproteins using mass spectrometry, and target engagement of AXL TKI using
activity-based protein profiling. BioID identifies AXL-interacting proteins that are mostly
involved in cell adhesion/migration. Global phosphoproteomics show that AXL inhibition
decreases phosphorylation of peptides involved in phosphatidylinositol-mediated signaling
and cell adhesion/migration. Comparison of three AXL inhibitors reveals that TKI RXDX-106
inhibits pAXL, pAKT and migration/invasion of these cells without reducing their viability,
while Bemcentinib exerts AXL-independent phenotypic effects on viability. Proteomic
characterization of these TKIs demonstrates that they inhibit diverse targets in addition to
AXL, with Bemcentinib having the most off-targets. AXL and EGFR TKI co-treatment did not
reverse resistance in cell line models of Erlotinib-resistance. However, a unique
vulnerability was identified in one resistant clone, wherein combination of Bemcentinib and
Erlotinib inhibited cell viability and signaling. We also show that AXL is overexpressed in
30-40% of non-small but rarely in small-cell lung cancer. Cell lines have a wide range of
AXL expression, with basal activation detected rarely.
Abstract: A critical property of many therapies is their selective binding to target populations.
Exceptional specificity can arise from high-affinity binding to surface targets expressed
exclusively on target cell types. In many cases, however, therapeutic targets are only
expressed at subtly different levels relative to off-target cells. More complex binding
strategies have been developed to overcome this limitation, including multi-specific and
multivalent molecules, creating a combinatorial explosion of design possibilities. Guiding
strategies for developing cell-specific binding are critical to employ these tools. Here, we
employ a uniquely general multivalent binding model to dissect multi-ligand and
multi-receptor interactions. This model allows us to analyze and explore a series of
mechanisms to engineer cell selectivity, including mixtures of molecules, affinity
adjustments, valency changes, multi-specific molecules, and ligand competition. Each of
these strategies can optimize selectivity in distinct cases, leading to enhanced selectivity
when employed together. The proposed model, therefore, provides a comprehensive toolkit for
the model-driven design of selectively binding therapies.
Abstract: Systems serology provides a broad view of humoral immunity by profiling both the
antigen-binding and Fc properties of antibodies. These studies contain structured
biophysical profiling across disease-relevant antigen targets, alongside additional
measurements made for single antigens or in an antigen-generic manner. Identifying patterns
in these measurements helps guide vaccine and therapeutic antibody development, improve our
understanding of diseases, and discover conserved regulatory mechanisms. Here, we report
that coupled matrix-tensor factorization (CMTF) can reduce these data into consistent
patterns by recognizing the intrinsic structure of these data. We use measurements from two
previous studies of HIV- and SARS-CoV-2-infected subjects as examples. CMTF outperforms
standard methods like principal components analysis in the extent of data reduction while
maintaining equivalent prediction of immune functional responses and disease status. Under
CMTF, model interpretation improves through effective data reduction, separation of the Fc
and antigen-binding effects, and recognition of consistent patterns across individual
measurements. Data reduction also helps make prediction models more replicable. Therefore,
we propose that CMTF is an effective general strategy for data exploration in systems
serology.
Abstract: The γ-chain receptor dimerizes with complexes of the cytokines interleukin-2 (IL-2),
IL-4, IL-7, IL-9, IL-15, and IL-21 and their corresponding “private” receptors. These
cytokines have existing uses and future potential as immune therapies because of their
ability to regulate the abundance and function of specific immune cell populations. Here, we
build a binding reaction model for the ligand-receptor interactions of common γ-chain
cytokines, which includes receptor trafficking dynamics, enabling quantitative predictions
of cell-type-specific response to natural and engineered cytokines. We then show that tensor
factorization is a powerful tool to visualize changes in the input-output behavior of the
family across time, cell types, ligands, and concentrations. These results present a more
accurate model of ligand response validated across a panel of immune cell types as well as a
general approach for generating interpretable guidelines for manipulation of
cell-type-specific targeting of engineered ligands.
Abstract: Multivalent cell surface receptor binding is a ubiquitous biological phenomenon with
functional and therapeutic significance. Predicting the amount of ligand binding for a cell
remains an important question in computational biology as it can provide great insight into
cell-to-cell communication and rational drug design toward specific targets. In this study,
we extend a mechanistic, two-step multivalent binding model. This model predicts the
behavior of a mixture of different multivalent ligand complexes binding to cells expressing
various types of receptors. It accounts for the combinatorially large number of interactions
between multiple ligands and receptors, optionally allowing a mixture of complexes with
different valencies and complexes that contain heterogeneous ligand units. We derive the
macroscopic predictions and demonstrate how this model enables large-scale predictions on
mixture binding and the binding space of a ligand. This model thus provides an elegant and
computationally efficient framework for analyzing multivalent binding.
Abstract: Cancer cell sensitivity or resistance is almost universally quantified through a direct or
surrogate measure of cell number. However, compound responses can occur through many
distinct phenotypic outcomes, including changes in cell growth, apoptosis, and non-apoptotic
cell death. These outcomes have divergent effects on the tumor microenvironment, immune
response, and resistance mechanisms. Here, we show that quantifying cell viability alone is
insufficient to distinguish between these compound responses. Using an alternative assay and
drug-response analysis amenable to high-throughput measurement, we find that compounds with
identical viability outcomes can have very different effects on cell growth and death.
Moreover, additive compound pairs with distinct growth/death effects can appear synergistic
when only assessed by viability. Overall, these results demonstrate an approach to
incorporating measurements of cell death when characterizing a pharmacologic response.
Abstract: The pharmacokinetic properties of antibodies are largely dictated by the pH-dependent
binding of the IgG fragment crystallizable (Fc) domain to the human neonatal Fc receptor
(hFcRn). Engineered Fc domains that confer a longer circulation half-life by virtue of more
favorable pH-dependent binding to hFcRn are of great therapeutic interest. Here we developed
a pH Toggle switch Fc variant containing the L309D/Q311H/N434S (DHS) substitutions, which
exhibits markedly improved pharmacokinetics relative to both native IgG1 and widely used
half-life extension variants, both in conventional hFcRn transgenic mice and in new knock-in
mouse strains. engineered specifically to recapitulate all the key processes relevant to
human antibody persistence in circulation, namely: (i) physiological expression of hFcRn,
(ii) the impact of hFcγRs on antibody clearance and (iii) the role of competing endogenous
IgG. DHS-IgG retains intact effector functions, which are important for the clearance of
target pathogenic cells and also has favorable developability.
Abstract: The recent wide-spread adoption of single cell profiling technologies has revealed that
individual cancers are not homogenous collections of deregulated cells, but instead are
comprised of multiple genetically and phenotypically distinct cell subpopulations that
exhibit a wide range of responses to extracellular signals and therapeutic insult. Such
observations point to the urgent need to understand cancer as a complex, adaptive system.
Cancer systems biology studies seek to develop the experimental and theoretical methods
required to understand how biological components work together to determine how cancer cells
function. Ultimately, such approaches will lead to improvements in how cancer is managed and
treated. In this review, we discuss recent advances in cancer systems biology approaches to
quantify, model, and elucidate mechanisms of heterogeneity.
Abstract: Conjugating certain types of lentiviral vectors with targeting ligands can redirect the
vectors to specifically transduce desired cell types. However, extensive genetic and/or
biochemical manipulations are required for conjugation, which hinders applications for
targeting lentiviral vectors for broader research fields. We developed envelope proteins
fused with biotin-binding molecules to conjugate the pseudotyped vectors with biotinylated
targeting molecules by simply mixing them. The envelope proteins fused with the monomeric,
but not tetrameric, biotin-binding molecules can pseudotype lentiviral vectors and be
conjugated with biotinylated targeting ligands. The conjugation is stable enough to redirect
lentiviral transduction in the presence of serum, indicating their potential in in vivo .
When a signaling molecule is conjugated with the vector, the conjugation facilitates
transduction and signaling in a receptor-specific manner. This simple method of ligand
conjugation and ease of obtaining various types of biotinylated ligands will make targeted
lentiviral transduction easily applicable to broad fields of research.
Abstract: Targeted cancer therapeutics have demonstrated more limited clinical efficacy than
anticipated, due to both intrinsic and acquired drug resistance. Underlying mechanisms have
been largely attributed to genetic changes, but a substantial proportion of resistance
observations remain unexplained by genomic properties. Emerging evidence shows that receptor
tyrosine kinase (RTK) reprogramming is a major alternative process causing targeted drug
resistance, separate from genetic alterations. Hence, the contributions of mechanisms
leading to this process need to be more rigorously assessed.
Abstract: Maternal Zika virus (ZIKV) infection during pregnancy is recognized as the cause of an
epidemic of microcephaly and other neurological anomalies in human fetuses. It remains
unclear how ZIKV accesses the highly vulnerable population of neural progenitors of the
fetal central nervous system (CNS), and which cell types of the CNS may be viral reservoirs.
In contrast, the related dengue virus (DENV) does not elicit teratogenicity. To model viral
interaction with cells of the fetal CNS in vitro, we investigated the tropism of ZIKV and
DENV for different induced pluripotent stem cell-derived human cells, with a particular
focus on microglia-like cells. We show that ZIKV infected isogenic neural progenitors,
astrocytes, and microglia-like cells (pMGLs), but was only cytotoxic to neural progenitors.
Infected glial cells propagated ZIKV and maintained ZIKV load over time, leading to viral
spread to susceptible cells. DENV triggered stronger immune responses and could be cleared
by neural and glial cells more efficiently. pMGLs, when cocultured with neural spheroids,
invaded the tissue and, when infected with ZIKV, initiated neural infection. Since microglia
derive from primitive macrophages originating in proximity to the maternal vasculature, they
may act as a viral reservoir for ZIKV and establish infection of the fetal brain. Infection
of immature neural stem cells by invading microglia may occur in the early stages of
pregnancy, before angiogenesis in the brain rudiments. Our data are also consistent with
ZIKV and DENV affecting the integrity of the blood–brain barrier, thus allowing infection
of the brain later in life.
Dissecting FcγR Regulation Through a Multivalent Binding Model.R. A. Robinett, N. Guan, A. Lux, M. Biburger, F. Nimmerjahn, & A. S. Meyer. (2018). Cell Systems.[Abstract]
Abstract: Many immune receptors transduce activation across the plasma membrane through their
clustering. With Fcγ receptors (FcγRs), this clustering is driven by binding to antibodies
of differing affinities that are in turn bound to multivalent antigen. As a consequence of
this activation mechanism, accounting for and rationally manipulating immunoglobulin (Ig)G
effector function is complicated by, among other factors, differing affinities between FcγR
species and changes in the valency of antigen binding. In this study, we show that a model
of multivalent receptor-ligand binding can effectively account for the contribution of
IgG-FcγR affinity and immune complex valency. This model in turn enables us to make
specific predictions about the effect of immune complexes of defined composition. In total,
these results enable both rational immune complex design for a desired IgG effector function
and the deconvolution of effector function by immune complexes.
Abstract: Metastases are a major cause of cancer mortality. AXL, a receptor tyrosine kinase (RTK)
aberrantly expressed in many tumors, is a potent oncogenic driver of metastatic cell
motility and has been identified as broadly relevant in cancer drug resistance. Despite its
frequent association with changes in cancer phenotypes, the precise mechanism leading to AXL
activation is incompletely understood. In addition to its ligand growth arrest specific-6
(Gas6), activation of AXL requires the lipid moiety phosphatidylserine (PS). PS is only
available to mediate AXL activation when it is externalized on cell membranes, an event that
occurs during certain physiologic processes such as apoptosis. Here it is reported that
exposure of cancer cells to PS-containing vesicles, including synthetic liposomes and
apoptotic bodies, contributes to enhanced migration of tumor cells via a PS-Gas6-AXL
signaling axis. These findings suggest that anti-cancer treatments that induce fractional
cell killing enhance the motility of surviving cells in AXL-expressing tumors, which may
explain the widespread role of AXL in limiting therapeutic efficacy. Implications: This
study demonstrates that motility behavior of AXL-expressing tumor cells can be elicited by
Gas6-bearing apoptotic bodies generated from tumor treatment with therapeutics that produce
killing of a portion of the tumor cells present but not all, hence generating potentially
problematic invasive and metastatic behavior of the surviving tumor cells.
Abstract: Traditional drug screening methods lack features of the tumor microenvironment that can
contribute to resistance. There remains a gap in whether extracellular signals, such as
stiffness, dimensionality, and cell-cell contacts act independently, or are integrated
within a cell, to affect drug sensitizations or resistance. This is critically important, as
adaptive resistance is mediated, at least in part, by the extracellular matrix (ECM) of the
tumor microenvironment. We developed an approach to screen drug responses in cells cultured
on 2D and in 3D biomaterial environments to explore how key features of ECM mediate drug
response. This approach uncovered that cells on 2D hydrogels and as spheroids encapsulated
in 3D hydrogels were less responsive to receptor tyrosine kinase (RTK)-targeting drugs
sorafenib and lapatinib, but not cytotoxic drugs, compared to single cells in hydrogels and
cells on plastic. Transcriptomic differences between these in vitro models and tumor
xenografts did not reveal mechanisms of ECM-mediated resistance. However, a systems biology
analysis of phospho-kinome data suggested that MEK phosphorylation was associated with
RTK-targeted drug resistance. Using sorafenib as a model drug, we found that
co-administration with a MEK inhibitor decreased ECM-mediated resistance in vitro and
reduced in vivo tumor burden compared to sorafenib alone. In sum, we provide a novel
strategy for identifying and overcoming ECM-mediated resistance mechanisms by performing
drug screening, phospho-kinome analysis, and systems biology across multiple biomaterial
environments.
Systems Approaches to Cancer Biology.T. C. Archer, E. J. Fertig, S. J. C. Gosline, M. Hafner, S. K. Hughes, B. A. Joughin, A. S. Meyer, S. R. Piccolo, & A. N. Shajahan-Haq. (2016). Cancer Research.[Abstract]
Abstract: Cancer systems biology aims to understand cancer as an integrated system of genes,
proteins, networks, and interactions rather than an entity of isolated molecular and
cellular components. The inaugural Systems Approaches to Cancer Biology Conference,
cosponsored by the Association of Early Career Cancer Systems Biologists and the National
Cancer Institute of the NIH, focused on the interdisciplinary field of cancer systems
biology and the challenging cancer questions that are best addressed through the combination
of experimental and computational analyses. Attendees found that elucidating the many
molecular features of cancer inevitably reveals new forms of complexity and concluded that
ensuring the reproducibility and impact of cancer systems biology studies will require
widespread method and data sharing and, ultimately, the translation of important findings to
the clinic.
Abstract: Resistance limits the effectiveness of receptor tyrosine kinase (RTK)-targeted therapies.
Combination therapies targeting resistance mechanisms can considerably improve response, but
will require an improved understanding of when particular combinations will be effective.
One common form of resistance is bypass signaling, wherein RTKs not targeted by an inhibitor
can direct reactivation of pathways essential for survival. Although this mechanism of
resistance is well appreciated, it is unclear which downstream signaling events are
responsible. Here, we apply a combined experimental- and statistical modeling-based approach
to identify a set of pathway reactivation essential for RTK-mediated bypass resistance.
Differences in the downstream pathway activation provided by particular RTKs lead to
qualitative differences in the capacity of each receptor to drive therapeutic resistance. We
identify and validate that the JNK pathway is activated during and strongly modulates bypass
resistance. These results identify effective therapeutic combinations that block
bypass-mediated resistance and provide a basic understanding of this network-level change in
kinase dependence that will inform the design of prognostic assays for identifying effective
therapeutic combinations in individual patients.
Abstract: Kinase inhibitor resistance often involves upregulation of poorly understood “bypass”
signaling pathways. Here, we show that extracellular proteomic adaptation is one path to
bypass signaling and drug resistance. Proteolytic shedding of surface receptors, which can
provide negative feedback on signaling activity, is blocked by kinase inhibitor treatment
and enhances bypass signaling. In particular, MEK inhibition broadly decreases shedding of
multiple receptor tyrosine kinases (RTK), including HER4, MET, and most prominently AXL, an
ADAM10 and ADAM17 substrate, thus increasing surface RTK levels and mitogenic signaling.
Progression-free survival of patients with melanoma treated with clinical BRAF/MEK
inhibitors inversely correlates with RTK shedding reduction following treatment, as measured
noninvasively in blood plasma. Disrupting protease inhibition by neutralizing TIMP1 improves
MAPK inhibitor efficacy, and combined MAPK/AXL inhibition synergistically reduces tumor
growth and metastasis in xenograft models. Altogether, extracellular proteomic rewiring
through reduced RTK shedding represents a surprising mechanism for bypass signaling in
cancer drug resistance.
Abstract: Axons navigate long distances through complex 3D environments to interconnect the nervous
system during development. Although the precise spatiotemporal effects of most axon guidance
cues remain poorly characterized, a prevailing model posits that attractive guidance cues
stimulate actin polymerization in neuronal growth cones whereas repulsive cues induce actin
disassembly. Contrary to this model, we find that the repulsive guidance cue Slit stimulates
the formation and elongation of actin-based filopodia from mouse dorsal root ganglion growth
cones. Surprisingly, filopodia form and elongate toward sources of Slit, a response that we
find is required for subsequent axonal repulsion away from Slit. Mechanistically, Slit
evokes changes in filopodium dynamics by increasing direct binding of its receptor, Robo, to
members of the actin-regulatory Ena/VASP family. Perturbing filopodium dynamics
pharmacologically or genetically disrupts Slit-mediated repulsion and produces severe axon
guidance defects in vivo. Thus, Slit locally stimulates directional filopodial extension, a
process that is required for subsequent axonal repulsion downstream of the Robo receptor.
Selectivity in Subunit Composition of Ena/VASP Tetramers.D. N. Riquelme, A. S. Meyer, M. Barzik, A. Keating, & F. Gertler. (2015). Bioscience Reports.[Abstract]
Abstract: The members of the actin regulatory family of Ena/VASP proteins form stable tetramers. The
vertebrate members of the Ena/VASP family, VASP, Mena, and EVL, have many overlapping
properties and expression patterns, but functional and regulatory differences between
paralogs have been observed. The formation of mixed oligomers may serve a regulatory role to
refine Ena/VASP activity. While it has been assumed that family members can form mixed
oligomers, this possibility has not been investigated systematically. Using cells expressing
controlled combinations of VASP, Mena, and EVL, we evaluated the composition of Ena/VASP
oligomers and found that VASP forms oligomers without apparent bias with itself, Mena, or
EVL. However, Mena and EVL showed only weak hetero-oligomerization, suggesting specificity
in the association of Ena/VASP family members. Co-expression of VASP increased the ability
of Mena and EVL to form mixed oligomers. Additionally, we found that the tetramerization
domain at the C-termini of Ena/VASP proteins conferred the observed selectivity. Finally, we
demonstrate that replacement of the TD with a synthetic tetramerizing coiled-coil sequence
supports homo-oligomerization and normal VASP subcellular localization.
Abstract: Dysregulation of ErbB-family signaling underlies numerous pathologies and has been
therapeutically targeted through inhibiting ErbB-receptors themselves or their cognate
ligands. For the latter, “decoy” antibodies have been developed to sequester ligands
including heparin-binding epidermal growth factor (HB-EGF); however, demonstrating
sufficient efficacy has been difficult. Here, we hypothesized that this strategy depends on
properties such as ligand-receptor binding affinity, which varies widely across the known
ErbB-family ligands. Guided by computational modeling, we found that high-affinity ligands
such as HB-EGF are more difficult to target with decoy antibodies compared to low-affinity
ligands such as amphiregulin (AREG). To address this issue, we developed an alternative
method for inhibiting HB-EGF activity by targeting its cleavage from the cell surface. In a
model of the invasive disease endometriosis, we identified A Disintegrin and
Metalloproteinase 12 (ADAM12) as a protease implicated in HB-EGF shedding. We designed a
specific inhibitor of ADAM12 based on its recombinant prodomain (PA12), which selectively
inhibits ADAM12 but not ADAM10 or ADAM17. In endometriotic cells, PA12 significantly reduced
HB-EGF shedding and resultant cellular migration. Overall, specific inhibition of ligand
shedding represents a possible alternative to decoy antibodies, especially for ligands such
as HB-EGF that exhibit high binding affinity and localized signaling.
Abstract: The AXL receptor is a TAM (Tyro3, AXL, MerTK) receptor tyrosine kinase (RTK) important in
physiological inflammatory processes such as blood clotting, viral infection, and innate
immune-mediated cell clearance. Overexpression of the receptor in a number of solid tumors
is increasingly appreciated as a key drug resistance and tumor dissemination mechanism.
Although the ligand-receptor (Gas6-AXL) complex structure is known, literature reports on
ligand-mediated signaling have provided conflicting conclusions regarding the influence of
other factors such as phosphatidylserine binding, and a detailed, mechanistic picture of AXL
activation has not emerged. Integrating quantitative experiments with mathematical modeling,
we show here that AXL operates to sense local spatial heterogeneity in ligand concentration,
a feature consistent with its physiological role in inflammatory cell responses. This effect
arises as a result of an intricate reaction-diffusion interaction. Our results demonstrate
that AXL functions distinctly from other RTK families, a vital insight for the envisioned
design of AXL-targeted therapeutic intervention.
The Receptor AXL Diversifies EGFR Signaling and Limits the Response to EGFR-Targeted
Inhibitors in Triple-Negative Breast Cancer Cells .A. S. Meyer, M. A. Miller, F. B. Gertler, & D. A. Lauffenburger. (2013). Science Signaling.[Abstract]
Abstract: The relationship between drug resistance, changes in signaling, and emergence of an
invasive phenotype is well appreciated, but the underlying mechanisms are not well
understood. Using machine learning analysis applied to the Cancer Cell Line Encyclopedia
database, we identified expression of AXL, the gene that encodes the
epithelial-to-mesenchymal transition (EMT)-associated receptor tyrosine kinase (RTK) AXL, as
exceptionally predictive of lack of response to ErbB family receptor-targeted inhibitors.
Activation of EGFR (epidermal growth factor receptor) transactivated AXL, and this
ligand-independent AXL activity diversified EGFR-induced signaling into additional
downstream pathways beyond those triggered by EGFR alone. AXL-mediated signaling
diversification was required for EGF (epidermal growth factor)-elicited motility responses
in AXL-positive TNBC (triple-negative breast cancer) cells. Using cross-linking
coimmunoprecipitation assays, we determined that AXL associated with EGFR, other ErbB
receptor family members, MET (hepatocyte growth factor receptor), and PDGFR
(platelet-derived growth factor receptor) but not IGF1R (insulin-like growth factor 1
receptor) or INSR (insulin receptor). From these AXL interaction data, we predicted
AXL-mediated signaling synergy for additional RTKs and validated these predictions in cells.
This alternative mechanism of receptor activation limits the use of ligand-blocking
therapies and indicates against therapy withdrawal after acquired resistance. Further,
subadditive interaction between EGFR- and AXL-targeted inhibitors across all AXL-positive
TNBC cell lines may indicate that increased abundance of EGFR is principally a means to
transactivation-mediated signaling.
ADAM-10 and -17 regulate endometriotic cell migration via concerted ligand and receptor
shedding feedback on kinase signaling. .M. A. Miller, A. S. Meyer, M. T. Beste, Z. Lasisi, S. Reddy, K. W. Jeng, C.-H. Chen, J. Han, K. Isaacson, L. G. Griffith, & D. A. Lauffenburger. (2013). Proc Natl Acad Sci U S A.[Abstract]
Abstract: A Disintegrin and Metalloproteinases (ADAMs) are the principal enzymes for shedding
receptor tyrosine kinase (RTK) ectodomains and ligands from the cell surface. Multiple
layers of activity regulation, feedback, and catalytic promiscuity impede our understanding
of context-dependent ADAM "sheddase" function and our ability to predictably target that
function in disease. This study uses combined measurement and computational modeling to
examine how various growth factor environments influence sheddase activity and cell
migration in the invasive disease of endometriosis. We find that ADAM-10 and -17 dynamically
integrate numerous signaling pathways to direct cell motility. Data-driven modeling reveals
that induced cell migration is a quantitative function of positive feedback through EGF
ligand release and negative feedback through RTK shedding. Although sheddase inhibition
prevents autocrine ligand shedding and resultant EGF receptor transactivation, it also leads
to an accumulation of phosphorylated receptors (HER2, HER4, and MET) on the cell surface,
which subsequently enhances Jnk/p38 signaling. Jnk/p38 inhibition reduces cell migration by
blocking sheddase activity while additionally preventing the compensatory signaling from
accumulated RTKs. In contrast, Mek inhibition reduces ADAM-10 and -17 activities but fails
to inhibit compensatory signaling from accumulated RTKs, which actually enhances cell
motility in some contexts. Thus, here we present a sheddase-based mechanism of rapidly
acquired resistance to Mek inhibition through reduced RTK shedding that can be overcome with
rationally directed combination inhibitor treatment. We investigate the clinical relevance
of these findings using targeted proteomics of peritoneal fluid from endometriosis patients
and find growth-factor-driven ADAM-10 activity and MET shedding are jointly dysregulated
with disease.
Abstract: Growth factor–induced migration is a critical step in the dissemination and metastasis of
solid tumors. Although differences in properties characterizing cell migration on
two-dimensional (2D) substrata versus within three-dimensional (3D) matrices have been noted
for particular growth factor stimuli, the 2D approach remains in more common use as an
efficient surrogate, especially for high-throughput experiments. We therefore were motivated
to investigate which migration properties measured in various 2D assays might be reflective
of 3D migratory behavioral responses. We used human triple-negative breast cancer lines
stimulated by a panel of receptor tyrosine kinase ligands relevant to mammary carcinoma
progression. Whereas 2D migration properties did not correlate well with 3D behavior across
multiple growth factors, we found that increased membrane protrusion elicited by growth
factor stimulation did relate robustly to enhanced 3D migration properties of the MDA-MB-231
and MDA-MB-157 lines. Interestingly, we observed this to be a more reliable relationship
than cognate receptor expression or activation levels across these and two additional
mammary tumor lines.
Abstract: In bioprocess development, the 96-well plate format has been widely used for
high-throughput screening of production cell line or culture conditions. However, suspension
cell cultures in conventional 96-well plates often fail to reach high cell density under
normal agitation presumably due to constraints in oxygen transfer. Although more vigorous
agitation can improve gas transfer in 96-well plate format, it often requires specialized
instruments. In this report, we employed Fluorinert, a biologically inert perfluorocarbon,
to improve oxygen transfer in 96-well plate and to enable the growth of a Chinese Hamster
Ovary cell line expressing a recombinant monoclonal antibody. When different amounts of
Fluorinert were added to the cell culture medium, a dose-dependent improvement in cell
growth was observed in both conventional and deep square 96-well plates. When sufficient
Fluorinert was present in the culture, the cell growth rate, the peak cell density, and
recombinant protein production levels achieved in deep square 96-wells were comparable to
cultures in ventilated shake flasks. Although Fluorinert is known to dissolve gases such as
oxygen and CO2, it does not dissolve nor extract medium components, such as glucose,
lactate, or amino acids. We conclude that mixing Fluorinert with culture media is a suitable
model for miniaturization of cell line development and process optimization. Proper cell
growth and cellular productivity can be obtained with a standard shaker without the need for
any additional aeration or vigorous agitation. \copyright 2011 American Institute of
Chemical Engineers Biotechnol. Prog., 2012
Abstract: Epithelial-mesenchymal transition (EMT), whether in developmental morphogenesis or
malignant transformation, prominently involves modified cell motility behavior. While major
advances have transpired in understanding the molecular pathways regulating the process of
EMT induction per se by certain environmental stimuli, an important outstanding question is
how the activities of signaling pathways governing motility yield the diverse movement
behaviors characteristic of pre-induction versus post-induction states across a broad
landscape of growth factor contexts. For the particular case of EMT induction in human
mammary cells by ectopic expression of the transcription factor Twist, we found the
migration responses to a panel of growth factors (EGF, HRG, IGF, HGF) dramatically disparate
between confluent pre-Twist epithelial cells and sparsely distributed post-Twist mesenchymal
cells - but that a computational model quantitatively integrating multiple key signaling
node activities could nonetheless account for this full range of behavior. Moreover,
motility in both conditions was successfully predicted a priori for an additional growth
factor treatment (PDGF). While this signaling network state model could comprehend motility
behavior globally, modulation of the network interactions underlying the altered pathway
activities was identified by ascertaining differences in quantitative topological influences
among the nodes between the two conditions.
Abstract: The concentration of biomarkers, such as DNA, prior to a subsequent detection step may
facilitate the early detection of cancer, which could significantly increase chances for
survival. In this study, the partitioning behavior of mammalian genomic DNA fragments in a
two-phase aqueous micellar system was investigated using both experiment and theory. The
micellar system was generated using the nonionic surfactant Triton X-114 and
phosphate-buffered saline (PBS). Partition coefficients were measured under a variety of
conditions and compared with our theoretical predictions. With this comparison, we
demonstrated that the partitioning behavior of DNA fragments in this system is primarily
driven by repulsive, steric, excluded-volume interactions that operate between the micelles
and the DNA fragments, but is limited by the entrainment of micelle-poor, DNA-rich domains
in the macroscopic micelle-rich phase. Furthermore, the volume ratio, that is, the volume of
the top, micelle-poor phase divided by that of the bottom, micelle-rich phase, was
manipulated to concentrate DNA fragments in the top phase. Specifically, by decreasing the
volume ratio from 1 to 1/10, we demonstrated proof-of-principle that the concentration of
DNA fragments in the top phase could be increased two- to nine-fold in a predictive manner.
Enhancing the Detection of Urinary Tract Infections Using Two-Phase Aqueous Micellar
Systems.S. A. Shiigi, A. S. Meyer, & D. T. Kamei. (2009). The UCLA USJ.[Abstract]
Abstract: Urinary tract infections (UTIs) are a leading cause of health expenditures, in part due to
the expensive and lengthy diagnostic method that involves culturing bacteria. A new
technique has been developed allowing for faster UTI diagnosis through an electrochemical
chip to measure unique ribosomal RNA (rRNA) found in bacteria associated with UTIs. Although
this technique has had success, concentrating the bacterial rRNA through the use of
two-phase aqueous micellar systems in the urine sample prior to utilizing the chip may
provide increased sensitivity. This approach is appealing because these systems are
relatively inexpensive, easily scalable, and simple to use. In this study, we examined the
partitioning behavior of bacterial RNA fragments, puri ed from Enteroccocus faecalis, in a
two-phase micellar system comprised of the nonionic surfactant Triton X-114 and
phosphate-buffered saline. Experimentally measured results were compared to theoretical
values to determine the governing factors involved in RNA partitioning. We demonstrated that
RNA fragments partition primarily due to steric, excluded-volume interactions that exist
between the RNA and micelles. However, the presence of entrained micelle-poor, RNA-rich
domains in the macroscopic micelle-rich, RNA-poor phase limits the extent of RNA
partitioning in this system. Additionally, by manipulating the volume ratio, or the volume
of the top, micelle-poor phase divided by that of the bottom, micelle-rich phase, we
demonstrated that RNA fragments can be concentrated up to four-fold in a predictive manner.
Concentrating the bacterial RNA with these two-phase micellar systems prior to detection
with the UTI chip may facilitate the earlier detection of UTIs.