Davide Ambrosi (Torino)
Adhesion forces in T24 cell migration
The migration of tumor cells is a key aspect of extravasation,
when cancer cells exit the capillaries and enter organs. Notwithstanding
the relevance to understand the degradation dynamics, the elasticity
of the vessel wall and the cell adhesion play a major role. The
determination of the mechanical action exerted by a tumor cell
on the vessel wall is a specific example of the prediction of
the stress field exerted by a cell in a soft environment. In the
planar case, this subject has been addressed about ten years ago
by Dembo and Wang (1999). They showed how the traction exerted
by a cell on a deformable substrate can be indirectly obtained
on the basis of the displacement of the underlying layer. The
standard approach in this respect is to solve exactly the elasticity
problem by Green functions and then minimize the error by discrete
optimization, iteratively. One possible alternative strategy to
approach this inverse problem is to exploit the adjoint elasticity
equations for the substrate, obtained on the basis of the minimization
requirement of a suitable functional. In this case the linear
elasticity problem is solved in an approximate way, while being
intrinsically coupled with the minimization algorithm. In a joint
collaboration with the Grenoble University (Claude Verdier, Valentina
Peschetola, Alain Duperray) this methodology has been recently
applied to determine the force field generated by T24 tumor cells
on a polyacrylamide substrate. The shear stress obtained by numerical
integration provides quantitative insight of the traction field
generated by cells of this line and is a promising tool to investigate
the spatial pattern of forces generated in cell motion.
Robyn Araujo (George Mason University)
Combination Therapies: Insights from Mathematical Modeling
Realizing the promise of molecularly targeted inhibitors
for cancer therapy will require a new level of knowledge about
how a drug target is wired into the control circuitry of a complex
cellular network. This presentation will review general homeostatic
principles of cellular networks that enable the cell to be resilient
in the face of molecular perturbations, while at the same time
being sensitive to subtle input signals. Insights into such mechanisms
may facilitate the development of combination therapies that take
advantage of the cellular control circuitry, with the aim of achieving
higher efficacy at a lower drug dosage and with a reduced probability
of drug-resistance development.
Khalid Boushaba (Iowa State)
A mathematical model for cell signaling and endothelial
migration in a living zebra fish embryos
Angiogenesis in the zebrafish embryo begins after the first day
of development. During this time the intersegmental vessels in
the trunk develop from the dorsal aorta in the first wave of embryonic
angiogenesis. Previous work suggests a link between VEGF and Syndecan-2,
which may function as a co-receptor for VEGF. We are currently
developing equations that include terms expressing reaction, diffusion,
and cell movement biased by "convection" like terms
to model this interaction. These terms model the chemotactic influences
on cells, and hence the interaction of the cells with the extracellular
matrix that results in their directed movement towards the diffusible
growth factor. Using this approach as a framework, we expect to
develop mathematical models for angiogenesis for zebrafish that
are both predictive and descriptive of growth factor signaling
and extracellular matrix interactions during cell migration. Based
on the high degree of conservation of signaling pathways involved
in angiogenesis, we expect that modeling these processes in zebrafish
will be directly applicable to tumor angiogenesis.
Lloyd Demetrius (Harvard, Max Planck
Institute)
Cancer in Mice and Men: a comparison
Animal models, mostly mice and rats, have contributed
to the understanding of growth and control of tumors in humans
. I will invoke recent work in evolutionary theory to analyse
the extent to which extrapolations from mice models to human systems
are justified.
James Glazier (Indiana)
Simple Modeling of Avascular and Vascular Tumors Using
the GGH Model and CompuCell3D
While bioinformatics tools for the analysis of DNA sequences,
reaction kinetics models of biomolecular networks and molecular
dynamics simulations of biomolecules are all widely used, multi-cell
modeling of developmental processes (including tumor growth) at
the tissue scale is still relatively undeveloped. A key reason
for this neglect has been the lack of widely-accepted modeling
approaches and the computational difficulty of building such models.
Now, a growing community of modelers has settled on the GGH Model
(also known as the CPM) as a convenient methodology to create
multi-cell simulations of tissues. I will present sample simulations
of the front instabilities of a simple "toy" model of
growing avascular tumor spheroids and some slightly more sophisticated
models of tumor vascularization to illustrate the capabilities
and limitations of the GGH model as implemented in the open-source
modeling environment CompuCell3D (see www.compucell3d.org).
Richard Hill (Ontario Cancer Institute)
Cancer stem cells in tumours
A cancer stem (cancer-initiating) cell is defined as a cell within
a tumour that possesses the capacity to self-renew and to generate
the heterogeneous lineages of cancer cells that comprise the tumour.
This definition directly implies that an anti-cancer therapy can
cure a tumour only if all cancer stem cells are killed. A recent
milestone in cancer research was the introduction of flow sorting
techniques to isolate cell populations based on cell surface markers
that are differentially expressed in tumour cell subpopulations
that are enriched for cancer stem cells. Application of this technology
may allow discrimination of stem cells and non-stem cells on an
individual basis, although the interpretation of this data in
the context of the exact phenotype of a stem cell is currently
evolving. The question of whether cancer stem cells represent
a (small) subpopulation of tumour cells which may respond differently
to treatment (e.g. radiotherapy or chemotherapy) compared to the
bulk of non-stem tumour cells has direct implication for understanding
the response of tumours to treatment. Changes in tumour volume
after therapy, i.e. tumour response, are governed by the changes
in the mass of tumour cells, i.e. primarily by the non-stem cells.
In contrast, permanent tumour eradication is expected to be dependent
on the complete inactivation of the subpopulation of cancer stem
cells. This distinction is extremely important for optimization
of cancer research methodology. Today the vast majority of preclinical
studies in cancer research use volume dependent parameters such
as tumour regression or tumour growth delay as experimental endpoints.
An often unrecognised assumption in modelling such data is that
cancer stem cells have the same treatment response as non-stem
cells in the tumour. The validity of this assumption for different
tumour types is currently unknown.
David Hodgson (PMH)
Learning from the Fat Man: Modeling Radiation-related Second
Cancer Risk for Clinical Use
Numerous studies have demonstrated increased risks of second malignancy
among young cancer survivors, largely attributed to radiation
therapy (RT). However, due to the long latency required to observe
second solid cancers (SC) and the rapid evolution of RT techniques,
many estimates of radiation-related SC risks reflect the outcomes
of treatment no longer in use. Moreover, there is large variation
in the normal tissue exposure among individuals nominally receiving
the same form of RT. Consequently, published risks of SC are not
generalizable to contemporary HL patients, and conceal substantial
differences in risk among individual patients.
Ideally, patient-specific radiation exposure data could be used
to prospectively
estimate RT-related SC risk. This approach would have the potential
advantage of providing patient-specific SC risk estimates to newly
diagnosed patients undergoing treatment, and could aid the development
of more effective RT techniques by helping to quantify the reduction
in late toxicity expected from changes in RT practice.
This talk will review studies that have applied methods of modeling
cancer risk among atomic-bomb survivors to radiation-related second
cancer risk among patients receiving RT. Epidemiologic data are
emerging regarding dose-risk relationship following RT that suggest
that standard radiobiologic models may not apply to the SC risk
seen following RT. Advances in imaging and individual-level dosimetric
estimation will facilitate the creation of patient-specific estimates
of SC risk, however major challenges exist to create estimates
with confidence intervals sufficiently narrow to be clinically
interpretable, and to integrate predictive models into a contemporary
biologic theory of radiation carcinogenesis.
Yi Jiang (Los Alamos)
Multiscale modeling for tumor angiogenesis
Tumor angiogenesis, the formation of new blood vessels from existing
vasculature in response to chemical signals from a tumor, is a
crucial step in cancer invasion and metastasis. Though the detailed
processes involved in angiogenesis are well established, the biomechanical
and biochemical mechanisms behind the vessel formation are largely
unresolved. We have developed a cell-based, multiscale modeling
framework that has been successfully applied to study tumor induced
angiogenesis. Our multiscale model is the first to incorporate
intracellular signaling pathways, cellular dynamics, cell-cell,
cell-matrix, cell-environment interactions, as well as chemical
dynamics, for tumor-induced angiogenesis. It is also the first
to simulate emergent vessel branching, anastomosis, and the brush
border effect. I will show that the model has not only reproduced
realistic sprout morphogenesis, but also generated testable hypotheses
regarding mechanistic role of angiogenic factor (VEGF) and the
topography of extracellular matrix, on sprout branching and fusion.
Philip Jones (Cambridge Cancer Ctr.)
The self assembling stem cell niche: a new model of epidermal
homeostasis
Mammalian epidermis is an ideal system in which to study stem
cell behaviour as it is constantly being turned over, has a simple
architecture, and is predominantly composed of a single cell lineage,
the epidermal keratinocyte. Epidermis consists of layers of keratinocytes.
Cells are continually shed from the epidermal surface and replaced
by proliferation in the basal cell layer, raising the question
of how epidermal homeostasis is achieved.
It has been argued the epidermis is maintained by long-lived,
slowly-cycling stem cells, which in turn generate a short-lived
population of transit-amplifying (TA) cells that differentiate
after a limited number of cell divisions. We have recently reported
that this "classical" stem/TA cell model is inconsistent
with clonal fate data obtained through inducible genetic labelling
in the tail skin of adult mice, which reveals a different mechanism
of epidermal homeostasis. Murine epidermis is maintained by a
single population of committed progenitor cells which behave stochastically,
dividing to generate, on average, equal numbers of cycling or
post-mitotic cells. The discovery of a new paradigm of stem-cell
independent tissue maintenance in mouse raises the question as
to whether similar rules may govern the behaviour of human keratinocytes.
In the basal layer of human interfollicular epidermis, near-quiescent
stem cells are localised in a niche consisting of stem cell clusters,
separated by proliferating and differentiating keratinocytes.
Remarkably, this pattern is reconstituted in vitro. Combining
a range of existing observations with new experimental data, we
have elucidated the origin of patterning and quiescence in homeostatic
tissue, and explained the ability of stem cells to reconstitute
their niche in culture. Such behaviour points at a simple set
of organisational principles controlling stem and progenitor cell
fate, and provides a unified model of epidermal maintenance in
mouse and human. In particular, we show that epidermis is maintained
by a committed progenitor cell population whose stochastic behaviour
enables stem cells to remain largely quiescent unless called upon
for repair. These results raise questions as to the role of stem
cells in other adult tissues.
Rama Khokha (Ontario Cancer Institute)
Functional and Biological Variables in Metastasis
Metastasis is the multistep process by which cancer cells
target and colonize secondary organs. Cancer cells locally invade
by breaching extracellular matrix barriers, gaining access to
vasculature, and extravasating into the distant organs. This is
followed by their growth in the new environment, culminating in
metastatic colonization. Lung, liver, brain and bone are common
sites of metastasis for many human cancers. There is a considerable
debate concerning the identity of rate limiting steps in metastasis,
thus modeling individual steps, and gaining molecular understanding
of this process presents significant challenges. We will discuss
the recent technologies and genetic mouse models which are emerging
to meet these challenges.
Mike Milosevic (PMH)
Angiogenesis, Interstitial Fluid Dynamics and Hypoxia in
Tumors
It is now well established that the clinical behaviour of many
human cancers is determined by molecular interactions between
the malignant cells and the environment in which they exist. Abnormal
blood vessels that arise from aberrant angiogenesis are an important
cause of tumour hypoxia, which stimulates further angiogenesis
and leads to radioresistance, altered repair of DNA damage and
changes in the expression of genes important in tumour progression
and metastasis formation. In addition, the abnormal tumor vessels
contribute to high interstitial fluid pressure (IFP), an important
predictor of reduced survival in women receiving radiotherapy
for cervix cancer and a barrier to drug penetration. These and
other aspects of the abnormal microenvironment in tumors, while
conferring poor prognosis and impeding the effectiveness of currently
available treatments, also present unique opportunities for improving
cure rates. Combinations of radiotherapy or chemotherapy with
novel molecular treatments that target angiogenesis or hypoxia
are the focus of ongoing laboratory and clinical studies. Mathematical
models of how these treatments interact can generate new hypotheses
for laboratory and clinical testing, inform the design of future
studies with respect to important issues such as optimal dosing
and sequencing of the various treatments, and help to explain
unexpected preclinical or clinical findings.
Lance Munn (Harvard)
Multi-scale analyses of tumor physiology and blood vessel
dynamics
Recent cancer therapies have targeted tumor blood vessels with
inconsistent results. Some treatments show promise while others
fail, underscoring a frustrating lack of understanding of the
mechanisms that control blood vessel formation, destruction and
function . A major difficulty lies in the fact that the mechanisms
of vessel formation and remodeling operate at multiple scales,
each with its own set of controls, and each critical to the overall
function of the blood vessel network. Most importantly, “rare”
events occurring at the single cell level can dominate overall
vessel network function, and therefore, tumor growth. We are developing
analytical approaches--both experimental and computational-- that
span the size scale from single cells to bulk tumor in order to
incorporate the relevant parameters critical for understanding
tumor growth. Experimentally, intravital microscopy allows determination
of single-vessel hematocrit, blood velocity, permeability as well
as vessel and network morphology over time. Mathematical models
of blood flow, vessel growth & remodeling, and tumor growth
and invasion span the size scale from cells to tissue to elucidate
the cellular events that influence tissue-scale physiology. These
tools provide a framework for studying the effects of anti-tumor
therapies and improving their efficacy.
Leonard M. Sander (Michigan)
Micromechanics of collagen-gels and invasion by glioma
cells
Glioma is a highly invasive form of brain tumor. We have studied
the invasion process in a in vitro experiment where tumor spheroids
are seeded in collagen gels. We find that invasion involves strong
and complex interactions with the gel; the cells deform and align
the matrix. In order to better understand this process we study
a micromechanical model of collagen-I. We can reproduce the non-linear
elasticity of the gel, and we show that deformations are non-affine.
We discuss the relationship of the mechanics to the invasive process.
Shiladitya Sengupta (MIT)
Spatiotemporal targeting of tumor parenchyma and stroma
by hybrid nanoparticles
The talk shall focus on the design of a novel nanoscale
platform that enables the spatiotemporal targeting of tumor stroma
and parenchyma with an antiangiogenic agemt followed by a cytotoxic.
This enables the intratumoral exposure of the hypoxic tumor to
a chemotherapeutic agent resulting in disruption of the HIF1a-autocrine
loop and increased antitumor efficacy.
Jack Tuszynski (Cross Cancer Inst.)
MD and QMMM modeling successfully predict binding and effectiveness
of novel colchicine derivatives against multiple cancer cell lines
Colchicine is a highly toxic plant-derived alkaloid which inhibits
microtubule polymerization by binding to tubulin dimers. Currently,
the chemotherapeutic value of colchicine is limited by its toxicity
against normal cells. Theoretically, this could be remedied by
derivatizing colchicine to preferentially bind tubulin isotypes
which are more common in cancer cells than in normal body tissues,
and particularly in those cancer types which are resistant to
conventional therapies. In recent studies, it has been demonstrated
that class III ß-Tubulin over-expression is associated with
taxane-resistant subsets of non small cell lung cancer, advanced
ovarian cancer, breast cancer and cancer of unknown primary origin.
Our study investigates the uses of Quantum Mechanics Molecular
Mechanics (QMMM) and Molecular Dynamics (MD) modeling to construct
derivatives of colchicine which will bind class III ß-Tubulin
with increased affinity. Using QMMM and MD modeling techniques,
21 colchicine derivatives were designed to increase affinity for
class III ß-Tubulin by offering a better steric fit into
the binding pocket . Derivatives were designed and tested in silico
before being synthesized by organic chemists at Oncovista Inc.
of San Antonio, TX. The colchicine derivatives were then tested
in MTS cytotoxicity assays against up to seven different cancer
cell lines with differing characteristics and morphologies. Results
were obtained by graphing the MTS absorbance readings, and calculating
an EC50 Value (drug concentration at which 50% of the drug's effects
are seen) using sigmoidal dose-response analysis. Colchicine has
an EC50 Value in the range of 10-7 M, and several of our novel
derivatives (ie. CH-32, CH-34 and CH-35) were found to have EC50
Values in the range of 10-9 M, while other derivatives (ie. CH-6,
CH-7 and CH-21) were found to have EC50 values in the range of
10-5 M to 10-6 M. These results indicate that our derivatives
have up to 100X greater and lesser effectiveness than colchicine.
Interestingly, comparative derivative cytotoxicity was found to
correlate with theoretical QMMM and MD modeling predictions. Successful
derivatives warrant continued investigation, screening and development.
We propose that our modeling system may be used to design any
variety of drugs for specific targets such as vinca alkaloids,
taxanes and peloruside.
Zhihui Wang (Harvard-MIT, HST)
Multiscale Lung Cancer Modeling
Lung cancer accounts for one third of all cancer related deaths
worldwide. Computational models simulating cancer cell behavior
can provide valuable insights into the quantitative understanding
of the inherent complexity of neoplastic systems through an interdisciplinary
approach. We have been working on the development and analysis
of multiscale agent-based models to investigate the growth dynamics
of non-small cell lung cancer (NSCLC). Our proposed innovative
methods can be used to help identify biomarkers across different
biological levels, thereby generate novel hypotheses and help
guide further experiments.
Glenn F. Webb (Vanderbilt)
Models of Tumor Growth in vitro
Two models of in vitro tumor growth will be presented. (1) Transforming
growth factor TGF is known to have properties of both tumor suppressor
and tumor promoter. While it inhibits cell proliferation, it also
increases cell motility. A mathematical model quantifies the growth
of MCF10A/HER2 cell cultures in vitro under exposure to TGF. The
model supports the hypothesis that TGF increases the tendency
of cells and cell clusters to move randomly, while simultaneously
diminishing cell proliferation. (2) P-glycoprotein (P-gp) is a
protein over-expressed in cancer cells that causes multi-drug
resistance to cancer therapy. Recent experimental evidence demonstrates
that P-gp is transferred directly cell-to-cell in in vitro tumor
cell lines. A mathematical model quantifies the transfer process
of P-gp in in vitro cultures of MCF-7 human breast adenocarcinoma
cells. The model supports the hypothesis that P-gp is transferred
directly cell-to-cell and provides a framework for optimizing
chemotherapy regimens.
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