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Presentaci

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De la farmacogen tica a la farmacogen mica Javier Benitez Programa Gen tica del C ncer Humano Centro Nacional Investigaciones Oncol gicas Madrid Junio 06 – PowerPoint PPT presentation

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Title: Presentaci


1
De la farmacogenética a la farmacogenómica
Javier Benitez Programa Genética del Cáncer
Humano Centro Nacional Investigaciones
Oncológicas Madrid Junio 06
2
Antitumoral treatments
  • They are agressives, inspecifics and with a
    limited therapeutic margin.
  • Risk of toxicity , treatment failure or even
    death
  • - Wide interpatient variability in effects

3
Antitumoral treatments II
  • Children with ALL. 75 get total remision (cure)
  • 25 with treatment failure
    and/or severe toxicity
  • Sarcomas 50-75 long term survival (cure)
  • Cases with severe toxicity CNS and GUS
  • - Breat cancer Tamoxifen for ER and PR positive
    tumors (50)
  • Secondary effects in some patients
    Uterine cancer,
    tromboembolims

4
Genetic bases of farmacological response
  • - Genetic variability might explain many of these
    situations.
  • Their study could lead to individualised
    treatment and new drug developments.
  • Pharmacogenetics It studies candidate genes
  • Pharmacogenomics It describes a broader strategy
    to identify many genes that are relevant to the
    pharmacological effects of a given medication. It
    is based in a targeted (candidate pathways) or
    whole genome analysis.

5
Enzimatic activity of TPMT-6MP according to
genotype
Cheok et al, Nat Review 2006
6
Correlation between TPMT genotype and 6MP toxicity
Cheok et al, Nat Review 2006
7
Allelic frequencies in Spanish Population
(www.bioinfo.cnio.es)
40 SNPs from 14 genes No differences
with other populations More genes under study
100 patients with ALL
MTFR and MTX
TPMT and 6MP
G238C G460A A719C
(http//bioinfo.cnio.es/cgi-bin/cegen/frequencies.
cgi)
8
Strategy II. MTX pathway (folate analogue)
1
1- Entry 2- Degradation 3- target 4-
metabolyze 5-.. . They study 32 genes
from this pathway and identify some of them
associated to MTX resistence. They found
differences among ALL subtypes.
2
3
4
Kager et al. J Clin Invest 2005
9
Strategy III. Genome Wide Approach
Global gene expression profiling using DNA
microarrays can identify - genes with levels of
expression that are related to drug response. -
New drug targets It is a complementary strategy
to the identification of SNPs in genes that alter
protein function and drug response.
10
Expression Profiling of T-Cell Lymphomas
Differentiates Peripheral and Lymphoblastic
Lymphomas and Defines Survival Related Genes
Treatment response/ survival Genetic signature 6
genes
NFkB
165 genes differenciate both groups
Martinez Delgado et al.Clin. Cancer Res, 2004.
11
A cluster of CYP3As genes is associated with
evolution
Martinez Delgado et al. Leukemia 2005
12
Expression of CYP3A4 is associated to survival of
PTCLs

Normalized CYP3A4 expression
PTCLs
  • CYP3A4 is an important drug metabolizing enzyme,
    CYP3A4 expression in tumors could then be
    mediating the response to chemotherapy.
  • Detection of CYP3A4 expression could have
    clinical interest by identifying tumors more
    resistant to chemotherapy at the time of
    diagnosis. An alternative treatment?

Martinez Delgado et al. (in preparation)
13
Periferal T-cell lymphomas HSP90 as drug target
HSP90 is a chaperone HSP family inhibits
apoptotic pathways Overexpression of HSP90 - bad
prognosis
1
2
3
4
Genes correlated to proliferation not
specifically related to cell cycle regulation
HSP90
5
PROLIFERATION
6
  • Inhibitors of HSP90 (17AAG) under study
  • No effect in normal lymphocytes
  • Good response in peripheral T cell lines
  • Marta Cuadros et al. In
    preparation

7
8
9
10
14
Conclusions
  • Pharmacogenetics is starting to be introduced
    and applied in the clinical practice (6MP
    MTX.....)
  • The study of the response based on multiple
    genes (polygenic model) is now underway
  • Pharmacogenomics permits the identification of
    new therapeutic targets and groups of genes that
    modulate the pharmacological response.
  • It is still necessary to validate data. Problems
    with population variability, techniques,
    platforms etc....

15
Acknowledgements
Genotyping Lab
Human Genetics Lab Lara P. Fernandez Eva
Barroso Goria Ribas Beatriz Martinez Marta Cuadros
CeGen Madrid Genotyping Lab Emilio
Gonzalez Roger Milner Ana Gonzalez
Charo Jesus Mari
Endocrine Group Mercedes Robledo Fátima
Mercadillo Cristina Rodriguez
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