npj Systems Biology and Applications,
Год журнала:
2022,
Номер
8(1)
Опубликована: Сен. 8, 2022
The
promise
of
precision
medicine
has
been
limited
by
the
pervasive
resistance
to
many
targeted
therapies
for
cancer.
Inferring
timing
(i.e.,
pre-existing
or
acquired)
and
mechanism
drug-induced)
such
is
crucial
designing
effective
new
therapeutics.
This
paper
studies
cetuximab
in
head
neck
squamous
cell
carcinoma
(HNSCC)
using
tumor
volume
data
obtained
from
patient-derived
xenografts.
We
ask
if
mechanisms
can
be
determined
this
alone,
not,
what
would
needed
deduce
underlying
mode(s)
resistance.
To
answer
these
questions,
we
propose
a
family
mathematical
models,
with
each
member
assuming
different
present
method
fitting
models
individual
volumetric
data,
utilize
model
selection
parameter
sensitivity
analyses
ask:
which
member(s)
best
describes
HNSCC
response
cetuximab,
does
that
tell
us
about
driving
resistance?
find
along
time-course
single
dose
initial
fraction
and,
some
instances,
escalation
are
required
distinguish
among
thereby
infer
These
findings
inform
future
experimental
design
so
leverage
synergy
wet
laboratory
experimentation
modeling
study
novel
cancer
Frontiers in Oncology,
Год журнала:
2023,
Номер
13
Опубликована: Окт. 9, 2023
Introduction
Radiation
therapy
(RT)
is
one
of
the
most
common
anticancer
therapies.
Yet,
current
radiation
oncology
practice
does
not
adapt
RT
dose
for
individual
patients,
despite
wide
interpatient
variability
in
radiosensitivity
and
accompanying
treatment
response.
We
have
previously
shown
that
mechanistic
mathematical
modeling
tumor
volume
dynamics
can
simulate
volumetric
response
to
patients
estimation
personalized
optimal
reduction.
However,
understanding
implications
choice
underlying
model
critical
when
calculating
dose.
Methods
In
this
study,
we
evaluate
biological
effects
2
models
on
personalization:
(1)
cytotoxicity
cancer
cells
lead
direct
reduction
(DVR)
(2)
responses
microenvironment
carrying
capacity
(CCR)
subsequent
shrinkage.
Tumor
growth
was
simulated
as
logistic
with
pre-treatment
being
described
proliferation
saturation
index
(PSI).
The
effect
according
each
respective
a
standard
schedule
fractionated
Gy
weekday
fractions.
Parameter
sweeps
were
evaluated
intrinsic
rate
parameter
both
observe
qualitative
impact
parameter.
then
calculated
minimum
required
locoregional
control
(LRC)
across
all
combinations
full
range
radiosensitvity
values.
Results
Both
estimate
higher
will
require
lower
achieve
LRC.
two
make
opposite
estimates
PSI
LRC:
DVR
tumors
values
LRC,
while
CCR
Discussion
Ultimately,
these
results
show
importance
which
best
describes
particular
setting,
before
using
any
such
recommendations.
Mathematical Biosciences & Engineering,
Год журнала:
2024,
Номер
21(3), С. 4104 - 4116
Опубликована: Янв. 1, 2024
<abstract><p>In
this
paper,
Gompertz
type
models
are
proposed
to
understand
the
temporal
tumor
volume
behavior
of
prostate
cancer
when
a
periodical
treatment
is
provided.
Existence,
uniqueness,
and
stability
periodic
solutions
established.
The
used
fit
data
forecast
growth
based
on
treatments
using
capsaicin
docetaxel
anticancer
drugs.
Numerical
simulations
show
that
combination
most
efficient
cancer.</p></abstract>
iScience,
Год журнала:
2024,
Номер
27(9), С. 110699 - 110699
Опубликована: Авг. 10, 2024
Many
cancers
resist
therapeutic
intervention.
This
is
fundamentally
related
to
intratumor
heterogeneity:
multiple
cell
populations,
each
with
different
phenotypic
signatures,
coexist
within
a
tumor
and
its
metastases.
Like
species
in
an
ecosystem,
cancer
populations
are
intertwined
complex
network
of
ecological
interactions.
Most
mathematical
models
ecology,
however,
cannot
account
for
such
diversity
or
predict
consequences.
Here,
we
propose
that
the
generalized
Lotka-Volterra
model
(GLV),
standard
tool
describe
species-rich
communities,
provides
suitable
framework
ecology
heterogeneous
tumors.
We
develop
GLV
growth
discuss
how
emerging
properties
provide
new
understanding
disease.
potential
extensions
their
application
plasticity,
cancer-immune
interactions,
metastatic
growth.
Our
work
outlines
set
questions
road
map
further
research
ecology.
Dynamic Games and Applications,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 14, 2024
Abstract
We
present
a
game-theoretic
model
of
polymorphic
cancer
cell
population
where
the
treatment-induced
resistance
is
quantitative
evolving
trait.
When
stabilization
tumor
burden
possible,
we
expand
into
Stackelberg
evolutionary
game,
physician
leader
and
cells
are
followers.
The
chooses
treatment
dose
to
maximize
an
objective
function
that
proxy
patient’s
quality
life.
In
response,
evolve
level
maximizes
their
proliferation
survival.
Assuming
in
its
ecological
equilibrium,
compare
outcomes
three
different
strategies:
giving
maximum
tolerable
throughout,
corresponding
standard
care
for
most
metastatic
cancers,
ecologically
enlightened
therapy,
anticipates
short-run,
response
treatment,
but
not
evolution
evolutionarily
both
consequences
treatment.
Of
therapeutic
strategies,
therapy
leads
highest
values
function,
lowest
dose,
resistance.
Conversely,
our
model,
worst
Revista Iberoamericana de Automática e Informática Industrial RIAI,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 10, 2025
El
modelado
matemático
de
sistemas
biomédicos
puede
ayudar
a
los
profesionales
oncológicos
diseñar
ciclos
administración
fármacos
más
seguros
y
eficaces.
Para
lograr
este
objetivo,
en
el
proceso
toma
decisiones
se
utiliza
modelo
del
crecimiento
tumoral
impacto
la
quimioterapia.
Sin
embargo,
son
propensos
un
alto
grado
incertidumbre,
no
solo
por
errores
medición,
sino
también
dinámica
sistema
modelada
variabilidad
entre
pacientes.
abordar
problema,
han
aplicado
restricciones
probabilísticas
al
control
fármacos,
haciéndolo
robusto
frente
perturbaciones.
Este
trabajo
compara
una
versión
lineal
otra
linealizada
las
formulaciones
estocásticas
predictivo
basado
modelo.
Ambos
algoritmos
mejoran
eficacia
seguridad
tratamiento,
con
diferencias
cuanto
conservadurismo
coste
computacional.
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Фев. 24, 2025
The
analysis
of
unperturbed
tumor
growth
kinetics,
particularly
the
estimation
parameters
for
S-shaped
equations
used
to
describe
growth,
requires
an
appropriate
likelihood
function
that
accounts
increasing
error
in
solid
measurements
as
size
grows
over
time.
This
study
aims
propose
suitable
functions
parameter
models
growth.
Five
different
are
evaluated
and
compared
using
three
Bayesian
criteria
(the
Information
Criterion,
Deviance
Bayes
Factor)
along
with
hypothesis
tests
on
residuals.
These
applied
fit
data
from
Ehrlich,
fibrosarcoma
Sa-37,
F3II
tumors
Gompertz
equation,
though
they
generalizable
other
or
analogous
systems
(e.g.,
microorganisms,
viruses).
Results
indicate
volume-dependent
dispersion
outperform
standard
constant-variance
capturing
variability
measurements,
Thres
model,
which
provides
interpretable
Additionally,
models,
such
those
assuming
a
normal
distribution,
remain
valuable
complementary
benchmarks
analysis.
It
is
concluded
incorporating
preferred
accurate
clinically
meaningful
modeling,
whereas
constant-dispersion
serve
useful
complements
consistency
historical
comparability.
