Physical Biology,
Journal Year:
2019,
Volume and Issue:
16(4), P. 041005 - 041005
Published: April 16, 2019
Abstract
Whether
the
nom
de
guerre
is
Mathematical
Oncology,
Computational
or
Systems
Biology,
Theoretical
Evolutionary
Bioinformatics,
simply
Basic
Science,
there
no
denying
that
mathematics
continues
to
play
an
increasingly
prominent
role
in
cancer
research.
Oncology—defined
here
as
use
of
research—complements
and
overlaps
with
a
number
other
fields
rely
on
core
methodology.
As
result,
Oncology
has
broad
scope,
ranging
from
theoretical
studies
clinical
trials
designed
mathematical
models.
This
Roadmap
differentiates
related
demonstrates
specific
areas
focus
within
this
unique
field
The
dominant
theme
personalization
medicine
through
mathematics,
modelling,
simulation.
achieved
patient-specific
data
to:
develop
individualized
screening
strategies
detect
earlier;
make
predictions
response
therapy;
design
adaptive,
treatment
plans
overcome
therapy
resistance;
establish
domain-specific
standards
share
model
models
simulations
reproducible.
cover
art
for
was
chosen
apt
metaphor
beautiful,
strange,
evolving
relationship
between
cancer.
Journal of The Royal Society Interface,
Journal Year:
2017,
Volume and Issue:
14(136), P. 20170490 - 20170490
Published: Nov. 1, 2017
Adult
gliomas
are
aggressive
brain
tumours
associated
with
low
patient
survival
rates
and
limited
life
expectancy.
The
most
important
hallmark
of
this
type
tumour
is
its
invasive
behaviour,
characterized
by
a
markedly
phenotypic
plasticity,
infiltrative
morphologies
the
ability
malignant
progression
from
low-
to
high-grade
types.
Indeed,
widespread
infiltration
healthy
tissue
glioma
cells
largely
responsible
for
poor
prognosis
difficulty
finding
curative
therapies.
Meanwhile,
mathematical
models
have
been
established
analyse
potential
mechanisms
invasion.
In
review,
we
start
brief
introduction
current
biological
knowledge
about
invasion,
then
critically
review
highlight
future
challenges
Bulletin of Mathematical Biology,
Journal Year:
2019,
Volume and Issue:
81(10), P. 3722 - 3731
Published: July 23, 2019
The
number
of
publications
on
mathematical
modeling
cancer
is
growing
at
an
exponential
rate,
according
to
PubMed
records,
provided
by
the
US
National
Library
Medicine
and
Institutes
Health.
Seminal
papers
have
initiated
promoted
helped
define
field
oncology
(Norton
Simon
in
J
Natl
Cancer
Inst
58:1735–1741,
1977;
Norton
Can
Res
48:7067–7071,
1988;
Hahnfeldt
et
al.
59:4770–4775,
1999;
Anderson
Comput
Math
Methods
Med
2:129–154,
2000.
https://doi.org/10.1080/10273660008833042
;
Michor
Nature
435:1267–1270,
2005.
https://doi.org/10.1038/nature03669
Cell
127:905–915,
2006.
https://doi.org/10.1016/j.cell.2006.09.042
Benzekry
PLoS
Biol
10:e1003800,
2014.
https://doi.org/10.1371/journal.pcbi.1003800
).
Following
introduction
undergraduate
graduate
programs
biology,
we
begun
see
curricula
developing
with
specific
exclusive
focus
oncology.
In
2018,
218
articles
were
published
various
journals,
including
not
only
traditional
journals
like
Bulletin
Mathematical
Biology
Journal
Theoretical
Biology,
but
also
renowned
science,
tremendous
impact
(Cell,
Research,
Clinical
Discovery,
Scientific
Reports,
PNAS,
Communications,
eLife,
etc).
This
shows
breadth
models
that
are
being
developed
for
multiple
purposes.
While
some
phenomenological
nature
following
a
bottom-up
approach,
other
more
top-down
data-driven.
Here,
discuss
emerging
trend
predict
novel,
optimal,
sometimes
even
patient-specific
treatments,
propose
convention
when
use
model
novel
treatments
and,
probably
importantly,
to.
Processes,
Journal Year:
2019,
Volume and Issue:
7(1), P. 37 - 37
Published: Jan. 13, 2019
Multiscale
systems
biology
and
pharmacology
are
powerful
methodologies
that
playing
increasingly
important
roles
in
understanding
the
fundamental
mechanisms
of
biological
phenomena
clinical
applications.
In
this
review,
we
summarize
state
art
applications
agent-based
models
(ABM)
hybrid
modeling
to
tumor
immune
microenvironment
cancer
response,
including
immunotherapy.
Heterogeneity
is
a
hallmark
cancer;
heterogeneity
at
molecular,
cellular,
tissue
scales
major
determinant
metastasis,
drug
resistance,
low
response
rate
molecular
targeted
therapies
immunotherapies.
Agent-based
an
effective
methodology
obtain
understand
quantitative
characteristics
these
processes
propose
solutions
aimed
overcoming
current
obstacles
treatment.
We
review
focusing
on
intra-tumor
heterogeneity,
particularly
interactions
between
cells
stromal
cells,
role
tumor-associated
vasculature
immune-related
mechanobiology,
discuss
digital
pathology
parameterizing
validating
spatial
computational
potential
therapeutics.
Science Advances,
Journal Year:
2020,
Volume and Issue:
6(50)
Published: Dec. 11, 2020
Early
cancer
detection
aims
to
find
tumors
before
they
progress
an
incurable
stage.
To
determine
the
potential
of
circulating
tumor
DNA
(ctDNA)
for
detection,
we
developed
a
mathematical
model
evolution
and
ctDNA
shedding
predict
size
at
which
become
detectable.
From
176
patients
with
stage
I
III
lung
cancer,
inferred
that,
on
average,
0.014%
cell's
is
shed
into
bloodstream
per
cell
death.
For
annual
screening,
predicts
median
sizes
2.0
2.3
cm
representing
~40%
decrease
from
current
3.5
cm.
informed
monthly
relapse
testing,
0.83
suggests
that
treatment
failure
can
be
detected
140
days
earlier
than
imaging-based
approaches.
This
mechanistic
framework
help
accelerate
clinical
trials
by
precomputing
most
promising
early
strategies.
Frontiers in Molecular Biosciences,
Journal Year:
2020,
Volume and Issue:
7
Published: April 30, 2020
Intratumoral
heterogeneity
is
a
major
ongoing
challenge
in
the
effective
therapeutic
targeting
of
cancer.
Accumulating
evidence
suggests
that
fraction
cells
within
tumor
termed
Cancer
Stem
Cells
(CSCs)
are
primarily
responsible
for
this
diversity
resulting
resistance
and
metastasis.
Adding
to
complexity,
recent
studies
have
shown
there
can
be
different
subpopulations
CSCs
with
varying
biochemical
biophysical
traits
varied
dissemination
drug-resistance
potential.
Moreover,
cancer
exhibit
high
level
plasticity
or
ability
dynamically
switch
between
CSC
non-CSC
statesoramong
subsets
CSCs.
The
molecular
mechanisms
underlying
such
has
been
under
extensive
investigation
trans-differentiation
process
Epithelial
Mesenchymal
transition
(EMT)
identified
as
contributing
factor.
Besides
genetic
epigenetic
factors,
also
shaped
by
non-cell-autonomous
effects
microenvironment.
In
review,
we
discuss
developments
understanding
progression
at
levels,and
latest
silico
approaches
being
taken
characterizing
cell
implications
improving
existing
approaches.
Nature Communications,
Journal Year:
2017,
Volume and Issue:
8(1)
Published: Jan. 31, 2017
Reconstructing
the
evolutionary
history
of
metastases
is
critical
for
understanding
their
basic
biological
principles
and
has
profound
clinical
implications.
Genome-wide
sequencing
data
enabled
modern
phylogenomic
methods
to
accurately
dissect
subclones
phylogenies
from
noisy
impure
bulk
tumour
samples
at
unprecedented
depth.
However,
existing
are
not
designed
infer
metastatic
seeding
patterns.
Here
we
develop
a
tool,
called
Treeomics,
reconstruct
phylogeny
map
anatomic
locations.
Treeomics
infers
comprehensive
patterns
pancreatic,
ovarian,
prostate
cancers.
Moreover,
correctly
disambiguates
true
artifacts;
7%
variants
were
misclassified
by
conventional
statistical
methods.
These
artifacts
can
skew
creating
illusory
heterogeneity
among
distinct
samples.
In
silico
benchmarking
on
simulated
across
wide
range
sample
purities
(15-95%)
depths
(25-800
×
)
demonstrates
accuracy
compared
with
