Transcript Gene Expression Based Categorization of Transplant

Gene Expression Based Categorization of
Transplant Pancreas Biopsies
Fu L. Luan M.D.
[email protected]
University of Michigan
No disclosure to declare
Background
• Pancreas transplantation is an effective treatment for patients
with type 1 diabetes mellitus;
• Successful pancreas transplant establishes long-term
normoglycemia with no risk of hypoglycemia;
• Potential benefit on improvement of diabetic related endorgan damage and cardiovascular risk factors;
• Potential benefit on extending patient survival;
Value of Pancreas Allograft on Patient
Survival
P. Salvalaggio et al. Diabetes Care 32(4): 600-602; 2009
Effects of Pancreas Allograft on CVD Risks
Blood Pressure
Total cholesterol
F. L. Luan, et al. Transplantation 84:541-544; 2007
Pancreas Transplants, by Transplant Type,
1998-2007
All Pancreas
SPK
PAK
PTA
Number of Transplants
1600
1200
800
400
0
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Unadjusted 1-Year, 3-Year, 5-Year, and 10Year Pancreas Graft Survival
SPK
Unadjusted Graft Survival (%)
100%
PTA
PAK
80%
60%
40%
20%
0%
1-Year
3-Year
5-Year
10-Year
The Challenges to Maintain a Functioning
Pancreas Allograft
• Complication related to graft and vascular
thrombosis accounts for about 20% of early graft
failure;
• Acute rejection as cause of graft failure within the
first year was reported at around 20%;
• Chronic rejection as cause of graft failure within the
first year was reported at around 19%;
• Pancreas allograft biopsy is the gold standard;
• Clinical indication remains subtle;
• Maryland classification, and lately Banff
classification provide guidance for clinicians;
• Response to the treatment varies;
Molecular Mechanisms Involved in
Allograft Rejection and/or Failure
• Large amount of information available on molecular
mechanisms involved in kidney allograft rejection
and/or failure;
• Microarray technology has allowed better correlation of
sets of gene expression with transplant renal outcome;
• Little is known about molecular mechanisms involved in
pancreas allograft rejection or failure;
Hypothesis
• Pancreas allograft displays similar molecular
mechanisms in acute and chronic rejection, and/or
allograft failure;
• Pancreas allograft exhibits unique molecular markers
inherent to it’s organ specificity;
• The pattern of molecular expression in pancreas
allograft may correlates with the allograft outcome;
Materials and Methods
• 26 pancreas transplant biopsy and 4 human
pancreas specimens (unaffected area of tumor
pancreatectomies);
• All specimens were processed with fixation in
formaldehyde and paraffin-embedding ;
• Maryland classification for histological diagnosis;
• Patient management was individualized;
Technical Consideration (I)
• The formaldehyde-fixed, paraffin-embedded tissue samples
were cut in 5 µm sections;
• De-paraffinization was performed and followed by
rehydration;
• The sections (5 slides for each sample) were scraped off the
slides and harvested in appropriated lysis buffer;
• The total RNA was extracted using the phenol chloroform
protocol and reverse-transcribed into cDNA;
Technical Consideration (II)
• TaqMan® Low Density arrays (TLDA) technique was employed
for parallel analysis of different mRNAs in samples;
• The cDNA expression value of each sample was compared
with other samples following the delta CT technique and the
expression of target genes was normalized to a calibrator;
• Real time RT-PCR expression values were analyzed with DChip
using 2D hierachical clustering for samples as well as for
genes;
?
Can we group
these patients
and/or genes
based on the
expression?
Unordered values,
coded from low
(green) to high (red)
1) Assess similarity
between all
combinations
S1
S2
S3
S1
2) Merge the two with
the highest similarity
3) Repeat 1) and 2) until
nothing left to merge
S2
S3
Consider the
expression
profiles for
the samples
and define a
similarity, e.g
correlation
S1
S2
S3
?
How
meaningful
are those
groupings?
If there is a clear
structure (long
branches) we
probably capture
some effect
Non-random
data should be
robust to
perturbations
1) Initiate a
perturbation
by randomly
removing one
sample
2) Re-cluster
3) Compare the
sample
composition
of the
resulting
clusters
Selection of Gene Markers for the Study
• Molecules involved in rejection processes, both acute and
chronic, were obtained from the various literatures in kidney
transplantation;
• Molecules specific to pancreas, down-regulated during
disease processes and up-regulated during regeneration
processes, were obtained by searching publically available
dataset at http://www.ncbi.nlm.nih.gov/geo and
http://www.betacell.org;
• Molecules considered “house keeping genes” were chosen;
Gene Official Symbol
Full name
C3
Complement Component 3
CCL19, CCL2 and CCL5, CCR5
Chemokine (C-C motif) ligands 19, 2 and 5, receptor 5
Chemokine (C-X3-C motif) ligands 1 and 10, Chemokine (C-X-C
motif) receptor 3, hemokine receptor (CD234)
FAS and FASLG, GNLY, GZMB and
TNF receptor and TNF superfamily, member 6, Granulysin,
PRF1
Granzyme B and Perforin
membrane-spanning 4-domains, subfamily A, member 1, CD20,
MS4A1, PTGS1 and 2
Prostaglandin-endoperoxide synthase 1 (prostaglandin G/H synthase
and cyclooxygenase) and 2
ADAM metallopeptidase domain 8 and 19, Matrix metallopeptidase
ADAM8 and 19, MMP-2, 7 and 9, TIMP1
2, 7 and 9, TIMP metallopeptidase inhibitor 1
CX3CL1 and CXCL10, CXCR3,DARC
IL6, and IL10
EDN1, Serpine1, TNF
HOXB7, KRT15, OPCML, TUSC4
INS, GCG, SST, AMY1A,CCKAR,
ELA2A
PDX1, MAF, MAFB, NEUROD1
POLR2A, PPIA, UBC, 18s rRNA and
GAPDH
Interleukin 6 (interferon, beta 2), and 10
Endothelin 1, Serpin peptidase inhibitor, clade E (nexin, plasminogen
activator inhibitor type 1), member 1, Tumor necrosis factor
Homeobox B7, Keratin 15, Opioid binding protein/cell adhesion
molecule-like, Tumor suppressor candidate 4
Insulin, Glucagon, Somatostatin, Amylase, alpha 1A,
Cholecystokinin A receptor, Elastase 2A
Pancreatic and duodenal homeobox 1(Ipf1), V-maf
musculoaponeurotic fibrosarcoma oncogene homolog and B,
Neurogenic differentiation 1
Polymerase (RNA) II (DNA directed) polypeptide A, Peptidylprolyl
isomerase A, Ubiquitin C, 18s ribosomal RNA, Glyceraldehyde-3phosphate dehydrogenase
Demographics of Study Population
Cluster A
N=7
Cluster B (I)
N=12
Cluster B (II)
N=7
37.7 + 6.2
37.3 + 6.3
34.9 + 4.5
Sex (male, %)
6 (85.7)
6 (50.0)
5 (71.4)
Race (AA, %)
2 (28.6)
1 (8.3)
1 (14.3)
Type of transplant
SPK (%)
PAK (%)
6 (85.7)
1 (14.3)
6 (50.0)
6 (50.0)
2 (28.6)
5 (71.4)
Induction
Thymo/OKT3 (%)
Basiliximab (%)
4 (57.1)
3 (42.9)
3 (25.0)
9 (75.0)
1 (14.3)
5 (71.4)
CNI
CsA (%)
Tac (%)
2 (28.6)
5 (71.4)
2 (16.7)
10 (75.0)
1 (14.3)
6 (85.7)
Age (years, S.D.)
Clinical Phenotypes and Clustering
Cluster A
N=7
Cluster B
N=19
I
n=12
II
n=7
Pancreas allograft failure (%)
1 (14.8)
8 (66.7)
5 (71.4)
Acute rejection (Maryland)
III or lower (%)
IV and V (%)
7 (100)
0 (0)
7 (58.3)
4 (33.3)
5 (71.4)
1 (14.3)
Chronic rejection (%)
0 (0)
1 (8.3)
2 (28.6)
Positive CD20 expression (%)
0 (0)
0 (0)
4 (57.1)
CD 20 Protein Expression in Pancreas
Transplant Biopsies
Biopsy with negative CD20 mRNA
Biopsy with positive CD20 mRNA
Expression of Some of Selected Molecular
Markers
Expression of Some of Selected Molecular
Markers
Summary
• The first study looking into molecular expression in transplant
pancreas specimen;
• Technique feasibility of obtaining RNA of good quality using
paraffin preserved pancreas biopsy specimen;
• Existence of variable up- and down-regulation of molecular
markers;
• Corresponding expression of protein in the biopsy specimens;
• Apparent correlation of expression pattern with observed
clinical outcome;
Future Direction and Potential Implication
• Need for a validation study involving large sample size;
• Need for definition of additional molecular markers;
• Need for more detailed correlation between expression
patterns and transplant outcome;
• Finally, prospective molecular study of pancreas allograft
using protocol biopsy;
• Potential guidance for target therapeutic intervention based
on variable molecular expression in the tissue;
Acknowledgement
Laboratory
• Matthias Kretzler, M.D.
• Fabian Trillsch, M.D.*
Pathology
• Henry Appelman, M.D.
• Joel Greenson, M.D.
• Anna Henger,*
• Felix Eichinger,
* Currently in Germany
Transplant
• Silas Norman, M.D.