Annonce en lien avec l’Action/le Réseau : aucun
Laboratoire/Entreprise : Ecole P olytechnique CMAP / INRIA Xpop
Durée : 12 mois
Contact : Marc.Lavielle@inria.fr
Date limite de publication : 2018-09-30
Contexte :
In cancer, the most dreadful event is the formation of metastases that disseminate tumor cells throughout the organism. WAVE complexes are molecular machines composed of 5 subunits, most of which can be encoded by paralogous genes.
In several cancers, a high level of subunit expression has been associated with high grade and poor prognosis.
qRT-PCR has been used to systematically analyze the expression of all 11 genes encoding WAVE complex subunits in breast tumors from a retrospective cohort of patients with known clinical parameters and outcome. We could derive an optimal multivariate Cox model of metastasis-free survival (MFS) using expression levels of only two subunits, NCKAP1 and CYFIP2. Experimental results thus validated the prediction of the MFS statistical model and revealed an unexpected anti-
migratory function of the paralogous CYFIP2 subunit.
The very satisfactory results of this approach in breast cancer have incited us to apply it for cutaneous melanoma. Indeed, cutaneous melanoma is a cancer, where the primary tumor can easily be removed by surgery. However, this cancer is of poor prognosis because melanomas metastasize often and rapidly. The objective is therefore to
extend the method previously developed in breast cancer in order to
build a metastasis-free survival model for cutaneous melanoma.
Sujet :
Project in collaboration with
the
Pharmacy Service
of the Europea
n
Hospital
Georges Pompidou
(
AP
HP
)
and the
team of
Pharmaceutical Analytical Chemistry
, University P
aris Sud
.
Therapeutic
drug
monitoring
(TDM)
is based on the measurement of blood concentrations to adjust
the dosage of drugs. It is one approach to personalized medicine; it is still not widely used in oncology.
However, in vi
ew of their narrow therapeutic margins, the significant inter
–
individual
pharmacokinetic variability, and the relationships between concentration and described clinical
response, anticancer drugs are excellent candidates for the individualization of dosage
regimens to
optimize management and reduce the risks of toxicity.
The
aim
of this project is to develop a new fast, sensitive and reliable analytical tool for the
TDM
of
anti
–
cancer drugs. The
objective
is to combine the contribution of nanotechnologies and
co
mputa
tional
statistics
to the development of robust prediction models in order to offer patients the possibility of
real
–
time
TDM
of these molecules.
The postdoc will contribute to the development o
f classification models (prediction of the molecule in
solution) and regression models (prediction of the concentration of this molecule) in order to guarantee
the physico
–
chemical quality of the drugs prepared in hospital.
To build these models, experimen
tal Raman spectrum data will be acquired from samples containing
increasing and known amounts of molecules of interest covering their therapeutic concentrations.
Profil du candidat :
Post-doc
Formation et compétences requises :
PhD required
Adresse d’emploi :
center of applied mathematics at Ecole Polytechnique
CMAP (http://www.cmap.polytechnique.fr)
joint Inria-CMAP team Xpop
Document attaché : offre_postdoc.pdf