Personalized Medicine in Transplantation by Maarten Naesens - at Université Libre de Bruxelles - 2014-01-28

MAARTEN NAESENS, MD, PHD
MAARTEN NAESENS
DEPARTMENT OF NEPHROLOGY AND RENAL TRANSPLANTATION
DEPARTMENT OF N
UNIVERSITY HOSPITALS LEUVEN, BELGIUM, EU EPHROLOGY AND RENAL
TRANSPLANTATION
UNIVERSITY HOSPITALS LEUVEN, BELGIUM, EU
LABORATORY OF NEPHROLOGY
DEPARTMENT OF PEDIATRICS
DEPARTMENT OF MICROBIOLOGY AND IMMUNOLOGY
STANFORD UNIVERSITY, CALIFORNIA, USA
KU LEUVEN, BELGIUM, EU
BRUSSELS, JANUARY 28, 2013

TTS – 2ND TRANSPLANTOMICS AND BIOMARKERS MEETING
BARCELONA, MARCH 2011

Personalized Medicine and Organ
Transplantation
•  General: Personalized Medicine and Systems Medicine
•  Kidney Transplantation:
o 
o 
o 

Current Tools for Personalized Medicine
Novel Tools for Personalized Medicine
The BioMargin Project

•  Evidence-Based Medicine vs. Personalized Medicine

What is “Personalized Medicine?”
“Although personalized medicine has many definitions, most
share the core idea that any one patient’s health is best
managed by tailoring preventive measures and treatment
to personal preferences as well as to the patient’s particular
environmental and biologic … attributes.”
Feero, Guttmacher and Collins

Feero, Guttmacher and Collins New Engl J Med 2010

What is “Personalized Medicine?”
Traditional clinical diagnosis and management focuses on the
individual patient's clinical signs and symptoms, medical and family
history, and data from laboratory and imaging evaluation to diagnose and
treat illnesses. This is often a reactive approach to treatment, i.e.,
treatment/medication starts after the signs and symptoms appear.

Personalized medicine is a medical model that proposes the
customization of healthcare - with medical decisions, practices, and/or
products being tailored to the individual patient. In this model,
diagnostic testing* is essential for selecting appropriate therapies.
*Companion diagnostics; theranostics

From Wikipedia

Personalized Medicine

Which molecules are involved?

BIOMARKERS
Slideadapted from Atul Butte

Which molecules? Evolving paradigms

Feero et al New Engl J Med 2010

Which molecules? Evolving paradigms

Naesens and Sarwal, Nature Rev. Nephrol. 2010

Systems Medicine
Systems medicine is an interdisciplinary field of study that
looks at the dynamic systems of the human body as part of
an integrated whole, incorporating biochemical,
physiological, and environment interactions that sustain life.

From Wikipedia

The need for a holistic approach

Hokusai 1818

Systems Medicine
Etiome
(environment)

Metabolome

Proteome

Transcriptome

(Epi)Genome

Systems Medicine

Oksenberg et al Nat Rev Genet 2008

Omics: new research paradigms
Hypothesis-driven research

Hypothesis-generating / data-driven research
Holistic

Reductionistic

Holistic

Omics: new research paradigms
Hypothesis-driven research

Hypothesis-generating / data-driven research

Reductionistic

Holistic

Hypothesis/Theory

Samples

Falsification

Unbiased omics
strategies

New hypothesis 1

New hypothesis 2

Falsification

Falsification

Unbiased omics
strategies

Data-driven results
NH3

NH4

NH5

NH6

NH7

NH8
Data-driven hypothesis/theory

F

F

F

F

F

F

Personal “Omics” Profiling (POP)
Genome
Epigenome
Transcriptome
(mRNA, miRNA, isoforms, edits)
Proteome/peptidome
Cytokines
Metabolome
Autoantibody-ome

Microbiome
From: Michael Snyder; see also Chen R et al Cell 2012

Personal
Omics
Profile

Personal “Omics” Profiling (POP)
Genome (1TB)
Epigenome (2TB)
Transcriptome (0.7TB)
(mRNA, miRNA, isoforms, edits)
Proteome/peptidome (0.02 TB)
Cytokines
Metabolome (0.02 TB)
Autoantibody-ome

Microbiome (3TB)
From: Michael Snyder; see also Chen R et al Cell 2012

Personal
Omics
Profile
Total =
5.74TB/Sample
+
1 TB Genome

Kidney Transplantation Outcome

Time after last biopsy (years)

Time after last biopsy (years)

Why do kidney transplants fail?

B Last histological diagnosis within 2 years prior to graft loss
8.3%
8.3%
7.6%
6.2%

IF/TA 2-3 or glomerulosclerosis > 50% / prior specific disease
IF/TA 2-3 or glomerulosclerosis > 50% / never specific disease
IF/TA < 2 and glomerulosclerosis < 50% / prior specific disease
IF/TA < 2 and glomerulosclerosis < 50% / never specific disease

30.6%
23.6%
10.4%
2.08%
16.7%
11.8%
4.86%

No specific disease
T-cell mediated rejection (including borderline)
Mixed T-cell and antibody-mediated rejection
Antibody-mediated rejection
Transplant glomerulopathy^
De novo/recurrent glomerular disease
Polyomavirus nephropathy

All renal allograft recipients transplanted between 01/01/1991 – 31/01/2001 (N=1197)
N=144
All renal allograft biopsies performed between 01/01/1991 and 14/04/2011 (N=1365)
Naesens et al. submitted

The histology of indication biopsies

Prevalence (%)

60%

40%

IF/TA 2-3

Transplant
glomerulopathy

TCMR

Glom. dis.

20%
aABMR

0%

Normal
PVAN

0.5

1

2

4

6

8

Time after transplantation (years)

All renal allograft recipients transplanted between 01/01/1991 – 31/01/2001 (N=1197)
All renal allograft biopsies performed between 01/01/1991 and 14/04/2011 (N=1365)
Naesens et al. submitted

>10

Personalized medicine and transplantation
“If we are to improve on the results that we are achieving
today in adherent patients, then it will have to come from an
earlier intervention to prevent irreversible damage in an
individualized therapeutic approach – personalized medicine.”
Jeremy Chapman
Past-President of TTS

Chapman J. Curr Opin Nephrol Hypertens 2012

Current non-invasive diagnostics?
TCMR

eGFR

aABMR

proteinuria

cABMR

Glom. Dis.

haematuria

NSA/IFTA

DSA testing

RI index

ATN

PVAN

BKV PCR

None of these markers is a good biomarker for intragraft pathology:
low sensitivity, low specificity, low NPPV, low PPV

Graft dysfunction

Transplant biopsy

Nankivell and Kuypers Lancet 2011

Personalized medicine in transplantation?
Creatinine
Proteinuria
Diagnostic
threshold
Acute dysfunction
Subclinical acute rejection

Chronic
dysfunction

Time

I-BX

I-BX

BX for cause

Nankivell et al. NEJM 2003
Lerut et al. Transplantation 2007
Naesens et al. JASN 2009
Ters et al. AJT 2013

Creatinine
Proteinuria

Treatment
Diagnostic
threshold
Acute dysfunction

Chronic
dysfunction

Acute pathology

I-BX

I-BX

BX for cause

Time

Creatinine

Treatment

Proteinuria

Diagnostic
threshold
Acute dysfunction

Chronic
dysfunction

Acute pathology

I-BX

I-BX

BX for cause

I-BX

Chronic pathology
Chronic pathology
Time

Protocol BX
P-BX

P-BX

P-BX

P-BX


Integration histology – genomics
Traditional

Changing Banff consensus
on allograft pathology Dx

Improving patient care


Omics and Kidney Transplantation


One step closer to “Rejectostix”

In independent validation set:
ROC AUC=0.74 (0.61-0.86; P<0.001)
mRNA in urine
3 gene signature
CD3ε, IP-10 and 18s

Suthanthiran et al. NEJM 2013
Ingelfinger and Alexander NEJM 2013

What about the peripheral blood?
Recipient & and donor APCs
move to lymphoid organs
T cells stimulated in
secondary lymphoid organs

TISSUE SPECIFIC
ALLOIMMUNE INJURY
Alloreactive T cells to graft

Peripheral blood “5-gene test”

In independent validation set:
ROC AUC=0.74 (0.61-0.86; P<0.001)

mRNA in blood
5 gene signature
DUSP1, PBEF1,
PSEN1, MAPK9
and NKTR

Li, Naesens, Sarwal et al. AJT 2012

Peripheral blood “11-gene test”

mRNA in blood
11 gene signature

NPV = 99.6%
PPV = 2.3%

Pham et al. NEJM 2010

Biopsy reclassification: TCMR score

77/300 (26%)
biopsies
reclassified

Halloran et al. Am J Transplant 2013

mRNA in biopsy
Whole genome
expression
“TCMR score”

Cross-organ comparison of rejection?
The common rejection module (11 genes)

Khatri, Naesens, Sarwal et al. J Exp Med 2013

Validation of biomarker candidates

Prospec5ve*
studies*
Retrospec5ve*
longitudinal*
studies*
Clinical*assay*
development*
and*valida5on*
Exploratory*
studies*
Standardiza5on*
(FDA*MAQC*project)*

Partially based on Coyle and Johnston Nat Rev Clin Oncol 2010

Randomized**
Controlled*
Trials*


“Rejectostix”3
79% sensitivity
78% specificity

Randomized**
Controlled*
Trials*

Prospec5ve*
studies*

Peripheral blood
5-gene test2
91% sensitivity
94% specificity
TCMR score1
Sensitivity?
Specificity?

Allomap4
NPV 99.6%
PPV 2.3%

Retrospec5ve*
longitudinal*
studies*

Clinical*assay*
development*
and*valida5on*

Exploratory*
studies*

1Halloran

Standardiza5on*
(FDA*MAQC*project)*

et al. AJT 2013
Naesens, Sarwal AJT 2012
3Suthanthiran et al NEJM 2013
4Pham et al NEJM 2010
2Li,


Prospec5ve*
studies*
Retrospec5ve*
longitudinal*
studies*
Clinical*assay*
development*
and*valida5on*

1.
Exploratory*
studies*

OMICS

Standardiza5on*
(FDA*MAQC*project)*

Randomized**
Controlled*
Trials*

Systems Medicine in Kidney Transplantation


BioMargin partners
Analytical Centers (-omics data)

Clinical Centers

Acureomics

MHH Hannover

Urinary + plasma metabolomics

Mosaiques Diagnostic GmbH

UZ Leuven

VITO

AP-HP Paris

Urinary proteomics and peptidomics
Blood + biopsy miRNA

KU Leuven

Urinary mRNA
Blood + biopsy miRNA

UnivPDes
Cardinal Systems

Blood + biopsy mRNA

AP-HP Paris

CHU Limoges

Urinary lipidomics

CNRS

Inserm-Transfert

Biopsy lipidomics, peptidomics, proteomics

INSERM Limoges

Coordination
CEA

Urinary proteomics
+ peptidomics

INSERM Toulouse

Urinary proteomics
+ peptidomics
Urinary miRNA

Bio-informatics Center
www.biomargin.eu


STEP 4
STEP 3
Retrospec5ve*
longitudinal*
studies*

STEP 2

STEP 1

Clinical*assay*
development*
and*valida5on*

Exploratory*
studies*
Standardiza5on*
(FDA*MAQC*project)*

Prospec5ve*
studies*

Randomized**
Controlled*
Trials*

Study Outline
Step 1-3

Step 4

Biobank
Hannover
Biobank
Leuven

Biopsies

3XBIOS2

BECS

Biobank
Paris
Biobank
Limoges

3ÐBIOS2 = 3-step BIOmargin Study on BIObanked Samples
BECS = Biomargin European Cohort Study

Study Outline
Time post-TX
0m
Histology

Biopsy
RNA

Plasma
Serum

Blood
RNA

Urine

3m

6m

1y

2y

5y

Study Outline
Time post-TX
0m

3m

Time post-TX
Ind 6m Ind

1y

0m
2y

Histology

Histology

Biopsy
RNA

Biopsy
RNA

Plasma
Serum

Plasma
Serum

Blood
RNA

Blood
RNA

Urine

Urine

3m

Ind 6m Ind

1y
5y

3 x BIOS2

BECS

Number of samples
Number of molecules

Evidence based medicine
Evidence-Based Medicine (RCT) = commonality*
Treatment *
Homogenous
cohort

A

Treatment *
B

* the fact of being common to more than one
individual

Outcome
A

Comparison = evidence
Outcome
B

Biomarker discovery
Personal Medicine = individuality^
Donor
at
time
of
transplantation
DNA

Test set

mRNA

Heterogenous
cohort

Patient C

mRNA

Sequence

Expression

Outcome 1

Donor
at
time
of
transplantation
DNA

Recipient
at
time
of
transplantation

mRNA

Donor
RNA
seq
(biopsy)

DNA

mRNA

Expression

Sequence

Patient B

DNA

Expression

Sequence

Patient A

Recipient
at
time
of
transplantation

^ the qualities that distinguish one person or thing from another

Sequence

Expression

Outcome 1

DNA
mRNA
DNA
mRNA
Donor-‐recipient
specific
Sequence
Sequence
Expression
antigenic
capacity Expression
Integration:
Donor
RNA
seq
Recipient
ecipient
specific
donor-‐r RNA
seq
(biopsy)
(blood)
Recipient
antibodyome
antibody
responses
Donor
at
time
of
transplantation
Recipient
at
time
of
transplantation
by
protein
arrays

Outcome 2

DNA
mRNA
DNA
mRNA
Donor-‐recipient
specific
Sequence
Sequence
Expression
antigenic
capacity Expression
Integration:
Donor
RNA
seq
donor-‐recipient
specific Recipient
RNA
seq
Recipient
antibodyome
(biopsy)
(blood)
antibody
responses at
time
of
transplantation
Donor
at
time
of
transplantation
Recipient

by
protein
arrays
DNA
mRNA
DNA
mRNA
Donor-‐recipient
sSequence
pecific
Sequence
Expression
Expression
antigenic
capacity
Integration:
Donor
RNA
seq
Recipient
ecipient
specific
donor-‐r RNA
seq
(biopsy)
(blood)
Recipient
antibodyome
antibody
responses
by
protein
arrays

Patient D

Expression

Donor
at
time
of
transplantation
Donor
at
time
of
transplantation
DNA
mRNA
DNA
mRNA
Sequence
Expression

Sequence Donor
RNA
seqExpression

Outcome 2

Recipient
at
time
of
transplantation
Recipient
at
time
of
transplantation
DNA
mRNA
DNA
mRNA
Sequence
Expression

Validation set
Sequence

Outcome 2

Patient E
Donor
at
time
of
transplantation
Donor
at
time
of
transplantation
DNA
mRNA
DNA
mRNA
Sequence
Expression

Sequence

Group 1

Recipient
RNA
seq
(blood)
Donor
at
time
of
transplantation
Recipient
at
time
of
transplantation

Donor
RNA
seq
(biopsy)

Expression

Recipient
at
time
of
transplantation
Recipient
at
time
of
transplantation
DNA
mRNA
DNA
mRNA
Sequence
Expression

Group 2

Donor-‐recipient
specific
antigenic
capacity

Recipient
antibodyome
by
protein
arrays
Donor-‐recipient
specific
antigenic
capacity

Outcome 1

SequenceRecipient
RNA
seq
Expression
(biopsy)
(blood)
Donor
RNA
seq
Recipient
RNA
seq
Donor
at
time
of
transplantation
Recipient
at
time
of
transplantation
(biopsy)
(blood)
Donor
at
time
of
transplantation
Recipient
at
time
of
transplantation
DNA
mRNA
DNA
mRNA
Donor-‐recipient
specific mRNA
DNA
DNA
mRNA
Sequence
Sequence
Expression
antigenic
capacity Expression
Donor-‐recipient
specific
Integration:
Sequence
Expression
Donor
RNA
seq Sequence
Recipient
RNA
seq
antigenic
capacity Expressionrecipient
specific
donor-‐
Integration:
(biopsy)
(blood)
Donor
RNA
seq Recipient
antibodyome Recipient
ecipient
specific
antibody
r seq
donor-‐r RNA
esponses at
time
of
transplantation
Donor
at
time
of
transplantation(blood)
Recipient

(biopsy)
by
at
time
of
transplantation
protein
arrays
Recipient
antibodyome
antibody
responses at
time
of
transplantation
Donor

Recipient

by

DNA protein
arrays
mRNA
DNA
mRNA
Donor-‐recipient
specific mRNA
DNA
DNA
mRNA
Sequence
Sequence
Expression
antigenic
capacity Expression
Donor-‐recipient
specific Expression
Integration:
Sequence
Sequence
Expression
Donor
RNA

Recipient
RNA
seq
antigenic
capacityseq
donor-‐recipient
s
Donor
at
time
of
transplantation Integration:pecific at
time
of
transplantation
Recipient

Recipient
antibodyome
(biopsy)
(blood)
antibody
responses at
time
o RNA
seq
Donor
R ransplantation recipient
specific Recipient
f
transplantation
Donor
at
time
of
tNA
seq
Recipient

donor-‐
by

Recipient
antibodyome mRNA
(biopsy)
(blood)
antibody
responses
DNA protein
arrays
DNA
mRNA
DNA protein
arrays
mRNA
DNA
mRNA
by

Sequence
Expression
Sequence
Expression
Donor-‐recipient
sSequence
pecific
Sequence
Expression
Expression
antigenic
capacity
Donor-‐recipient
specific
Integration:
Donor
RNA
seq
Recipient
ecipient
specific
antigenic
capacity
donor-‐r RNA
seq
Integration:
Donor
RNA
seq Recipient
antibodyome Recipient
RNA
seq
(biopsy)
(blood)
antibody
responses
donor-‐recipient
specific
(biopsy)
(blood)
by
protein
arrays
Recipient
antibodyome
antibody
responses
by
protein
arrays
Donor-‐recipient
specific
Donor
RNA
seq Donor-‐recipient
specific Recipient
RNA
seq
antigenic
capacity
Integration:
Donor
RNA
seq
Recipient
RNA
seq
antigenic
capacity
(biopsy)
(blood)
Integration:
donor-‐recipient
specific
(biopsy)
(blood)
donor-‐recipient
specific
Recipient
antibodyome
antibody
responses
Recipient
antibodyome
antibody
responses
by
protein
arrays
by
protein
arrays

Heterogenous
cohort

Outcome 2

Recipient
antibodyome
by
protein
arrays

Integration:
Recipient
RNA
seq
donor-‐recipient
specific
(blood)
antibody
responses

Comparison =
Biomarker for outcome?

Integration:
donor-‐recipient
specific
antibody
responses

Comparison = validation of biomarker
- retrospectively
- prospectively

Evidence based biomarkers
‘Marker
enrichment’
clinical
trial
design

‘Planned
analysis’
clinical
trial
design

Coyle
and
Johnston
Nat
Rev
Clin
Oncol
2010

Personalized Medicine in Transplantation by Maarten Naesens - at Université Libre de Bruxelles - 2014-01-28

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