E-Learning By : Amira AL-Qattan E-Learning By : Amira AL-Qattan.
Amira webinar
-
Upload
fhccommunity -
Category
Business
-
view
321 -
download
3
description
Transcript of Amira webinar
Cancer Metabolism Reinvention of Hallmark of Cancer
Miroslava Cuperlovic-Culf, Ph.D.
Senior Research Officer, National Research Council of Canada
Adjunct Professor, Mount Allison University
from Moncton, NB, Canada
22. May, 2012
TissueCancer analysisDiagnosticPrognostic Organism
Treatment assessmentDiagnosticRisk assesment
Cell
Cancer analysisDrug discoveryDiagnostic
ALTERED METABOLISM:CAUSE or EFFECT OF CANCER
Genetic changes of oncogenes andOncosuppressors
Cancer metabolic phenotype
Tumour microenvironment(pH, hypoxia, nutrient deprivation, autophagy)
Bioenergetics
Biosynthesis
Oxidative state
Glucose
Glucose
PEP
Pyruvate
G6P
Lactate + H+
Lactate +H+
R5P
AcetylCoA
Citrate
aKG
Amino Acids Import
Citrate
Acetyl CoA
Fatty acids
Glutamate
H2CO3
H++ CO2
GLUT1
ATP
ADPGLY
COLY
SIS
Cholesterol
PPP
CANCER METABOLIC PHENOTYPE
FATT
Y AC
IDSY
NTH
ESIS
NUCLEOTIDESSYNTHESIS
AMINO ACIDSYNTHESIS
Fatty acids
MYCHIF1
AKTp53
STAT3
EGFR
SNPAlternative splicingTranscription factorsEpigenetics
miRNA;Translation kinetics
AbilityDesire
Strategy
Action
Protein activation/inhibitionProtein interactions
Cuperlovic-Culf, et al. Exp Opin Mol Diagn 2008; Cuperlovic-Culf, et al. DDT 2010; Cuperlovic-Culf, NMR Metabolomics in Cancer Research. Oxford Biosciences, 2013
LN229
BS149
LN319
LN18
A172
U343
LN405
U373
HS683
Cuperlovic-Culf, et al. Jour Biol Chem 2012
Glioblastoma multiforme the most common and most aggressive malignant primary brain tumor in humans: median survival 3months – 2 years (with treatment)
1 2 3 4
SAM method: Tusher, et al. PNAS, 2001
Microarray data from: Grzmil, et al. Cancer Res, 2001, GSE15824 Wiedemeyer, et al. Cancer Cell 2008, GSE9200
overexpression in group Increased metabolites
Group 1:overexpression (red) Increased metabolites
CONCLUSIONS• Metabolic profiling (qualitative and
quantitative) leads to information about tumour subtypes;
• Metabolic biomarkers for tumour subtypes can be related to gene expression characteristics;
FUTURE
CONCLUSIONS FUTURE• Testing of clinical samples for
biomarkers of subtypes discovery and validation;
• Development and testing of drug options for glioblastoma subtypes
THANK YOU/ MERCI
Mohamed TouaibiaPier Jr. Morin
David FergusonMarc Surette
Anissa Belkaid
Rodney OuelletteAdrian CulfNatalie Lefort
Nabil BelacelDan TulpanJason Hines
METABOLITE CANCER NORMALL-Valine
L-LeucineL-Isoleucine
73.01(1.36) 110.53(9.12)
L-Lysine 10.31(1.36) 20.55(2.21)L-Alanine 11.62(1.54) 16.35(1.1)
L-Aspartic acid 0.77(0.08) 2.65(0.71)Phenylalanine 6.06(0.96) 11.12(1.88)
Tyrosine 0.25(0.12) 0.50(0.14)Glutamine 5.53(0.83) 3.44(0.81)
Total Choline 13.93(5.32) 6.58(1.84)UDP-glucose 6.59(0.75) 1.63(1.63)
Lactic acid 58.29(13.84) 56.47(18.19)
METABOLITE IDC (ER+) AC (ER-)L-Valine
L-LeucineL-Isoleucine
78.05(1.76) 67.98(6.10)
Glycerol-3-phosphate 50.31(4.56) 38.27(2.12)
L-Alanine 12.06(0.59) 11.17(2.05)
L-Aspartic acid 0.79(0.07) 0.74(0.09)Phenylalanine 6.82(0.62) 5.23(0.51)
Tyrosine 0.26(0.08) 0.24(0.16)Choline 15.02(5.01) 12.84(5.66)
Lactic acid 49.2(3.19) 67.39(14.51)
Cuperlovic-Culf, et al. Chem Sci (2011)
BREAST CANCER