Personalized Medicine Strategies for the future

Personalized Medicine
Strategies for the future
Loreto Gesualdo
UOC Nefrologia, Dialisi e Trapianto
Azienda Ospedaliero-Universitaria Policlinico
Università degli Studi di Bari
Eric C. Faulkner
Eric C. Faulkner
Eric C. Faulkner
PMC, march 2011
What Is Personalized Medicine?
“Personalized
Medicine” refers to the tailoring of
medical treatment to the individuals into
subpopulations that differ in their susceptibility to
a particular disease or their response to a
specific treatment. Preventative or therapeutic
interventions can then be concentrated on those
who will benefit, sparing expense and side
effects for those who will not.
PMC 2010
>2300
2010
> 6800 papers
The “Omics” Era
Transcriptomics
Genomics
Proteomics
Metabolomics
The new lexicon of “…omics”
Gene
DNA
Structural and
Comparative Genomics
Transcription
RNA
Translation
Protein
Environment
Functional Genomics
Transcriptomics
(Gene Expression)
Proteomics
PTMs
Biochemical Circuitry
Phenotypes
Monarch
Monarch butterfly
butterfly
Metabolomics
SYSTEMS BIOLOGY NETWORK IN PUGLIA REGION
DEB
Systems
Biology
Proteomics
DETO
CNR
CARSO
Transcriptomics
Genomics and
Metabolomics
BI
BA
O
NC
A
GENOMICA
RETE REGIONALE
DI OMICA E BIOLOGIA DEI SISTEMI
A
PROTEOMIC
A
MIC
O
L
O
AB
MET
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S
M
TE
L
BIO
O
GIA
D
I
S
I
E
“State-of-the-art” Core Facilities
Renal Center
How can we improve our understanding
and treatment of renal diseases?
Renal Disease
(Clinical Phase)
Renal Disease
(Pre-clinical Phase)
Tools Needed for Prediction and
Personalized Care
Decision
Support Tools:
Assess Risk
Refine Assessment
Monitor Progression
Predict/Diagnose
Predict Events
Initiating
Events
Earliest
Molecular
Detection
Earliest
Clinical
Detection
Typical
Current
Intervention
Cost
Disease Burden
Baseline Risk
1/reversibility
Inform Therapeutics
Time
Baseline Risk
Sources of New
Biomarkers:
Stable Genomics:
Single Nucleotide
Polymorphisms
(SNPs)
Haplotype Mapping
Gene Sequencing
Preclinical
Progression
Dynamic Genomics:
Gene Expression
Proteomics
Metabolomics
Molecular Imaging
Disease Initiation and Progression
Therapeutic Decision
Support
©2005 RALPH SNYDERMAN
Prospective Health Care
Participating Population
Low Risk
High Risk
Early
Chronic
1/reversibility
Late
Chronic
Cost
Disease Burden
Risk Assessment and Decision Support Tools
Time
Personalized Health Plan
Personal
Lifestyle Plan
Risk
Modification
Disease
Management
©2005 RALPH SNYDERMAN
The Empirical strategy for Drug Therapy
Patients
with
same
diagnosis treated with
the same medications
Toxicity (ADR)
Non-Responders
Adverse Drug Reactions (ADRs) are the fourth leading cause of
hospitalization, fifth leading cause of mortality in the USA
Relationship between Drug Dose and Response
High
Sensitive (toxicity)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Toxicity
Response
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Efficacy
Resistant (poor resp.)
Low
Low
Drug Dose
High
Many factors influence drug delivery & response
but inheritance can have a predominant effect
?
PharmacoPharmacogenetics
genetics
E. Vessell, 1980s
Microarray technology and
pharmacogenomics
Esempi di DNA analysis
ü AmpliChip CYP450 Test (Roche
Diagnostics)
ü Test per la TPMT (Tiopurina
metiltransferasi) [St. Jude
Children’s Research Hospital]
AmpliChip CYP450 Test
ü Permette l’analisi contemporanea di 33 polimorfismi,
duplicazioni e delezioni nei due geni del citocromo P450
(2D6 e 2C19) principalmente coinvolti nel metabolismo
ossidativo di diverse classi di farmaci (25%).
ü Alcune varianti alleliche di
tali geni nel 7-10% dei
bianchi e nell’1-2% degli
asiatici, mostrano infatti
alterata o assente attività
enzimatica.
CYP2C19: S-mephenytoin hydroxylase
CYP2D6: Debrisoquine hydroxylase
Varianti alleliche e fenotipi
ØIl gene CYP2D6 ha circa 70 varianti alleliche che
danno 4 fenotipi diversi predittivi della capacità di
risposta:
ØIl gene CYP2C19 ha 2 principali varianti alleliche
che danno attività enzimatica normale o assente
Dal genotipo alla predizione del fenotipo
CYP2D6
CYP2C19
Eric C. Faulkner
Eric C. Faulkner
Pharmacogenomics will
select the medications
each person, thereby
toxicity……..
make it increasingly possible to
and doses that are optimal for
improving efficacy and reducing
…… and will help us to define the mechanisms underlying
some
of
the
beneficial/detrimental
effects
of
immunosuppressive drugs.
Microarray technology and
pharmacogenomics
MYCOPHENOLIC ACID
INDUCES THE EXPRESSION
OF NEUTRAL
ENDOPEPTIDASE: A NOVEL
POTENTIAL ANTI-FIBROTIC
MECHANISM
Sezione di Nefrologia, Dialisi e Trapianto, DETO
“Policlinico”, Università degli Studi di Bari
Zaza et al., J Am Soc Nephrol. 2010 Dec;21(12):2157-68.
TREATMENT SCHEMA (training group)
Time 0
Time
0
(PBMC)
(PBMC)
Time 1 (3 months)
(PBMC)
Time 1 (3 months)
Time (PBMC)
2 (6 months)
(PBMC)
Continuing with CyA+AZA (50 mg/day) (n=15)
CyA+AZA (n=35)
(50 mg/day)
Switching to CyA+MPA (720 mg/day) (n=20)
Microarray (n=5)
Microarray (n=5)
Microarray (n=5)
• All patients at the baseline were treated with: CS, CyA, AZA
• All patients had ClCr more than 60 ml/min
• No patients had episodes of AR before enrollment
All patients suffering from cardiovascular diseases, infectious diseases, diabetes, chronic lung
diseases, neoplasm, or inflammatory diseases and patients receiving antibiotics or non-steroidal
anti-inflammatory agents were excluded.
MICROARRAY ANALYSIS
TIME 1 (CyA+MPA)
TIME 0 (CyA+AZA)
PT 1
PT 2
PT 1
PT 3
PT 3
PT 4
PT 5
PT 2
PT 4
3 MONTHS
PT 5
AZA
Myfortic
RNA from peripheral blood mononuclear cells (PBMC)
GeneChip® HG U133 A Array (more then 20.000 genes)
STATISTICAL ANALYSIS
PCA AND HIERARCHICAL CLUSTERING SHOW A CLEAR
DISCRIMINATION BETWEEN PATIENTS AT TIME 0 VERSUS TIME 1
PT 4
PT 1
PT 5
PT 2
PT 3
PT 1
PT 4
TIME 1 (MPA)
PT 5
PT 2
PT 3
TIME 0 (CyA+AZA)
TIME 1 (CyA+MPA)
TIME 0 (AZA)
TOP-RANKED GENES DIFFERENTIALLY REGULATED AFTER
3 MONTHS OF TREATMENT WITH MPA (selected by microarray analysis)
Probe set ID
Gene Symbol
Description
T0 (AZA)
T1(EC-MPA)
(Log2 mean±SD) (Log2 mean±SD)
Up-regulated genes
203434_s_at
215321_at
207286_at
205765_at
219990_at
220302_at
210666_at
211088_s_at
NEP
RPIB9
CEP135
CYP3A5
E2F8
MAK
IDS
PLK4
Neutral endopeptidase
Rap2-binding protein 9
Centrosomal protein 135kDa
Cytochrome P450, family 3, subfamily A, polypeptide 5
E2F transcription factor 8
Male germ cell-associated kinase
Iduronate 2-sulfatase
Polo-like kinase 4
3.94 ± 1.86
2.12 ± 0.41
2.21 ± 0.53
1.94 ± 0.52
2.32 ± 1.76
4.50 ± 1.55
6.13 ± 1.53
2.26 ± 1.58
7.08 ± 0.02
4.75 ± 1.00
4.87 ± 0.52
4.32 ± 1.43
4.55 ± 1.23
6.78 ± 0.59
8.01 ± 0.52
4.36 ± 1.02
Endothelin receptor type B
Neuroligin 4, Y-linked
Transmembrane protein 158
Zinc finger, BED-type containing 2
Phosphodiesterase 3A, cGMP-inhibited
LFNG O-fucosylpeptide 3-beta-N-acetylglucosaminyltransferase
Matrix-remodelling associated 5
Tryptase alpha/beta 1
Sparc/osteonectin
5.29 ± 1.06
3.96 ± 1.47
7.46 ± 1.08
5.72 ± 0.48
4.55 ± 1.56
6.16 ± 1.48
6.00 ± 0.75
5.44 ± 1.33
6.72 ± 0.23
3.09 ± 1.52
1.82 ± 1.05
5.51 ± 1.15
4.10 ± 1.43
2.67 ± 0.85
4.45 ± 0.64
4.55 ± 1.16
3.44 ± 0.36
5.18 ± 0.78
Down-regulated genes
206701_x_at
207703_at
213338_at
219836_at
206389_s_at
215270_at
209596_at
210084_x_at
202363_at
EDNRB
NLGN4Y
TMEM158
ZBED2
PDE3A
LFNG
MXRA5
TPSAB1
SPOCK1
• P.VALUE: Calculated using t-test
• FOLD CHANGE: ratio between log2 expression level at Time 1 versus Time 0
Immunohistochemistry showed higher NEP glomerular expression
in CyA+MPA compared to CyA+AZA and CyA only groups
A
B
p=0.4
E
p=0.03
p=0.02
C
D
% stained area
70
60
p=0.9
50
40
30
20
10
0
DD
P.value calculated by pairwise comparison t-test
CsA only
CsA+AZA CsA+EC-MPS
Immunohistochemistry showed higher NEP tubular expression in
CyA+MPA compared to CyA+AZA and CyA only groups
A
B
E
p=0.01
p=0.02
40
C
D
% stained area
p=0.04
30
p=0.6
20
10
0
DD
P.value calculated by pairwise comparison t-test
CsA only
CsA+AZA CsA+EC-MPS
Neutral endopeptidase (NEP)
Also known as Neprilysin, Membrane metallo-endopeptidase (MME), CD10, CALLA
• NEP is a glycoprotein that is particularly abundant in kidney,
where it is present on glomerular epithelial cells and brush border
of proximal tubules
McIntosh GG et al. Am J Pathol. 1999;154(1):771999;154(1):77-82
• NEP is a zinc-dependent metalloprotease enzyme that cleaves
peptides at the ammino-side of hydrofobic residues and inactivates
in vivo several peptide hormones (Angiotensin I, Angiotensin II,
Atrial natriuretic factor, Neurotensin, ecc.)
Ervin G et al. FASEB J. 1989; 3(2): 145145-51
TLR2 plays a role in the
activation of human
resident renal
stem/progenitor cells
Sezione di Nefrologia, Dialisi e Trapianto, DETO
“Policlinico”, Università degli Studi di Bari
Sallustio F et al., FASEB J. 2010 Feb;24(2):514-25.
Recent results obtained in humans suggest that
progenitors, localized at the urinary pole of the Bowman’s
capsule, can initiate the replacement and regeneration of
glomerular, as well as tubular, epithelial cells.
May the cells which constitute the reservoir
of the Bowman ’ s capsule modify their
expression while migrating down to the
injured tubules?
Gene expression profile
Six gene clusters have been identified on the basis of differential gene expression. Clusters A and E
discriminate MSCs from the renal cell lines; Clusters F and B discriminate ARPCs when compared to
the MSCs and RPTECs; Clusters C and D distinguish the stem/progenitor cells from RPTECs.
A
The secret for a Microarray study success?
RNA (from Tissue and/or cell sample)
FACILITY CORE
EACH STEP IS IMPORTANT
+
DATASET
….on the contrary
Genomics, Proteomics &
Systems Biology
Genomics
Proteomics
Systems Biology
1990
1995
2000
2005
2010
2015
2020
Systems biology:
the scientific challenge of the 21th century
The study of the mechanisms underlying complex biological processes
as integrated systems of many interacting components.
Systems biology involves (1) collection of large sets of experimental
data, (2) proposal of mathematical models that might account for at
least some significant aspects of this data set, (3) accurate computer
solution of the mathematical equations to obtain numerical predictions,
and (4) assessment of the quality of the model by comparing numerical
simulations with the experimental data
Reductionist Approach
Holistic Approach
Sauer U et al. Science 2007, 316: 550-1
Grazie per l’attenzione