Transcript Slide - Indiana CTSI

Hospital Engagement
Surgery
R. Graham Cooks, Cedric D’hue, Allison Dill, Demian Ifa,
Livia Eberlin, Christina Ferreira, Alan K. Jarmusch
Kevin Kerian, Valentina Pirro
Department of Chemistry
and Center for Analytical Instrumentation Development,
Bindley Biosciences Center, Discovery Park, Purdue University
Hospital Collaborators:
Nathalie Agar, Brigham & Women’s Hospital
Timothy Masterson, Michael Koch, Liang Cheng, IUPUI
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DESI Imaging
“Cat on a pillow”
7 mm
m/z 443
Resolution ~ 50 µm
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Tissue Analysis : Metabolite Profiling
b) Line Scans
a) One Pixel
c) Tissue Imaging
Image construction
log ( abundance ratio of m/z 788 : 448)
Signal ratios from MS
Abundance of Phosphatidylserine in
Human Liver Adenocarcinoma
3
Tumor margin
2.5
2
1.5
1
m/z 788
tumor
0.5
nontumor
0
-0.5
-1
-1.5
0
5
10
15
20
25
m/z 448
Lateral distance (mm)
Justin M. Wiseman, Satu M. Puolitaival, Zoltán Takáts, R. Graham Cooks, Richard M. Caprioli, Angew. Chem. 2005
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Brain Tumor Diagnosis by Mass Spectrometry
Endogenous lipid profiles
Differentiation of tumor
subtype, grade, and tumor
cell concentration
L.S. Eberlin, et al. Proc. Natl. Acad. Sci. 110, 1611 (2013)
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Human Brain Cancers
•
•
•
•
•
Over 125 types of brain tumors – complex to diagnose
Mean survival 12 – 15 months to some years
New cases (US): 22,910/year, deaths: 13,700/year
Neurosurgery is the primary treatment
Critical decisions made during neurosurgery
Need: Improved intraoperative diagnosis of tumors & margins One
Answer: Direct tissue analysis! – Molecular histology using Mass Spec
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Human Brain Gliomas – Subtypes
Same W.H.O grade
(III), different
subtypes
Gemistocytic
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L.S. Eberlin, I. Norton, et al Cancer Research, 2012, 72, 645
Human Brain Gliomas – Classification models
• A model creation dataset for 3
classifiers was constructed (type,
grade, %) using training set
Subtype
Grade
Overall Recognition
Capability
99.3 %
99.7 %
Cross
Validation
97.9 %
99.2 %
Concentration
99.0 %
97.5 %
 Independent Validation Set Class imaging Results (color coded)
Sample G26
Grade IV
astrocytoma
Sample G33
Grade IV
astrocytoma
(infiltrative)
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L.S. Eberlin, I. Norton, et al Cancer Research, 2012, 72, 645
Prostate Disease State Touch Spray MS
SCORE PLOT
ONE PIXEL
92
20
m/z 700 - 1000
Scores on PC4 (6.2%)
15
10
3 years of data;
dozens of patients
5
0
100
-5
17
93
7780
7274
63
84
10
59
95
81
91
32
94
39
71
89
11 12
98 13 99
96
41
47
97
49
36 15
48
70
881614
21
3118
30
37
76
53
58
83
6766
55
23
51 4538
19 42
57
50
86 85
62
60
33
54 6465
2035
46
3 2969 28 1
5 52
44
73
6
56
40 26
27 43
9
2
78
61
82
7
4
22 34
-10
75
25
24
8
-15
87
90
79
68
-25
-20
-15
-10
-5
0
Scores on PC3 (13.4%)
5
10
15
Kevin Kerian, Alan Jarmusch, Valentina Pirro -------Purdue
Timothy Masterson, Michael Koch, Liang Cheng--- IUPUI
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IUSM – DESI - Prostate
100
PI(36:4)PI(38:4)
788.4PS(36:1)
Cancer
PI(34:5)
H&E
885.5
Relative Abundance
786.4
812.4 835.3 861.6
816.5
810.3
723.4
747.4
0
100
788.4
Normal
788.5
885.5
812.4
834.4
723.5
747.6
786.5 810.4
861.5
0
720
740
760
780
800
820
840
860
880
Relative Abundance
m/z
100
0
788.5
861.5
0.25
0.30
0.35
0.40 0.45
Time (min)
0.50
0.55
861.5
0.60
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12
patients :
100
+
samples
Problem
Lack of Analytical
(Molecular)
Diagnosis Methods
Goal
Diagnosis:
Tumor or Normal
Tool
DESI-MS Imaging
Tool
MS Pathology: Prostate
TS-MS
Alan Jarmusch, Kevin Kerian, Valentina Pirro
6
SCORE PLOT
SCORE PLOT
(AVG) CV
prediction
rate = 95%
Scores on PC3 (6.1%)
DESI
20
5
4
10
92
9 6
7
2
3
76 61
5
0
-5
80
79131
74
71
7887
15 25 20
73 72
86
81 77
56
82
34 22 75
6360
69
58
94
85
57
59
92
99
67
84
97
16 14
53
49
27 26
68
52
5419 23
2428
43
6551
10
96
17 36 37
64
40
3511
66 88 50
44
90 21 46 48
98
62
55
31
38
4732
1812 100
4533
95 83
39
30 93
42
29
91
41
-10
89
70
-15
-25
-20
-15
-10
-5
0
Scores on PC2 (16.7%)
Touch
Spray
(AVG) CV
prediction
rate = 96%
15
Scores on PC4 (6.2%)
8
15
17
93
7780
7274
10
5
41
0
100
-5
10
15
30
53
83
86 8551
5 52
73
9
82
-10
-15
10
59
95
91 81 71
3294
8939
13
12
11
9698 97 99
36 15
48 4947
70
21
3118 88161437
5819 42 766766
4538
55
57 60 33 23
50 54
62
6465 20 46
3 2969 28 135 44
6
40 26 56 27 43
2 61
78
7
4
22 34
87
75
25
24
90
79
8
68
-25
5
63
84
-20
-15
-10
-5
0
Scores on PC3 (13.4%)
5
10
15
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Kevin Kerian,
Valentina Pirro
Problem
Lack of Analytical
(Molecular)
Diagnosis Methods
Goal
Diagnosis:
Tumor or Normal
Tool
DESI-MS Imaging
Tool
MS Pathology: Kidney
TS-MS
TS chronogram
RT: 0.00 - 0.69
100
95
0.10
85
75
0.64
0.28
90
80
6
secon
ds
0.07
0.48
0.12
0.57
0.56
70
0.25
65
NL:
1.58E7
TIC MS
TS_RCC_3
142014_Poi
nt1
Relative Abundance
TS
Case 1
Relative Abundance
*actual
photo
1 patient
0.44
60
55
50
45
40
35
TS spectrum (avg. 3 scans)
TS_RCC_3142014_Point1 #6-9 RT: 0.06-0.08 AV: 4 NL: 2.65E4
T: ITMS - p NSI Full ms [150.00-2000.00]
247.0
100
* many peaks – assumed to
be adducts
90
80
70
60
187.1
50
788.2
40
25
20
20
15
279.3
10
10
898.3 950.1
736.2 737.3
30
30
583.3
626.1
593.5 595.5 700.5
951.1
1060.2
1062.1
996.8
5
0
0.0
0
0.1
0.2
0.3
0.4
Time (min)
0.5
0.6
200
400
600
800
1000
1200
m/z
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MS Pathology: Kidney
Kevin Kerian,
Valentina Pirro
Alan Jarmusch
TS Case 1 – directly from surgically resected tissue
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DESI-MS Signatures in Bovine Early Embryonic Development
Positive ion mode (silver adducts)
Palmitic acid
Immature oocytes
80
Relative Abundance
Christina Ferreira,
PLoS One. 2013 20;8(9):e74981
100
60
Negative ion mode
(a)
Oleic acid
PIo (34:1)
281.25
PS (37:0)
40
PG (34:1)
PI (36:4)
804.58
255.23
747.52
20
PI (38:4)
821.57
885.55
857.52
0
200
300
400
500
600
700
800
900
1000
100
(b)
281.25
PG (36:2)
Eggs matured in vitro
Relative Abundance
80
773.53
885.55
255.23
60
747.52
PI (34:1)
PI (36:2)
40
861.55
835.53
821.57
20
0
200
Fertilization
300
400
500
600
700
800
900
1000
255.23
100
(c)
Blastocysts
developing
In vitro
Relative Abundance
80
283.26
60
PE (38:5) PI (36:1)
40
PEp (36:4), PEo (36:5)
863.57
885.55
20
764.55 821.56
722.51
0
200
300
400
500
600
700
800
900
1000
281.24
100
d)
Relative Abundance
80
Blastocysts
Developing In vivo
Cholesterol sulphate
60
465.30
PS (36:1)
40
PE (36:2) 788.54
861.55
885.55
835.53
20
742.53
722.51
303.23
0
200
300
400
500
600
700
800
900
1000
m/z
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Ambient Ionization for Early Detection of Parkinson’s Disease in Cerebrospinal fluid
 Method for MS/MS for monitoring 33 selected
metabolites in 0.47 min of analysis
PAPER SPRAY
Paper spray quantification using stable
isotope internal standards
Compound
Concentration
5 ppm in H2O
10 ppm in H2O
5 ppm in H2O
10 ppm in H2O
Methionine
Arginine
Reactive paper spray for more sensitivity
Derivatization of the primary
amine group on amino acids by
acetone forming a Schiff base
*in ng/mL or ppb; detection in water
solutions (no salts present); ** CSF
concentration in (in ppb) based on
literature reports.
Ryan Espy
Karen Cesafsky and Ryan Espy
Alanine
Arginine
LOD
(ng/m
L)*
2
2
Asparagine
13
5,000
Aspartic Acid
Glutamic
Acid
Glutamine
Glycine
Histidine
4
3,000
Lysine
Methionine
Phenylalanin
e
Proline
0.2
33,000
6
5
4
444,000
600
12,000
8,000/19,00
0
Compound
Iso/Leucine
0.4
CSF
(ng/mL) **
3,300
20,200
RSD
11%
17%
3%
3%
Compound
LOD
CSF
(ng/mL
(ng/mL)
)
4
28,000
0.3
6,000
0.2
3,000
4
4,000
Serine
4
42,000
Threonine
Tryptophan
Tyrosine
9
4
1
28,000
10,000
10,000
Valine
0.3
24,000
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 Reactive extraction spray. 18 amino acids can be monitored by MS/MS at CSF concentrations
Some amino acids present neutral loss of 46 after acetone reaction and can be detected by NL scanning
Relative Abundance
80
NL: 8.81E4
blank_acetone_extraction
129.15
100
115.01
60
143.16
40
AV: 15 T: + p ESI Full cnl
46.000 [80.070-300.000]
Ren et al., 2013. Analytical Methods, 5, 6686-6692.
229.21
157.37
178.87
193.08
201.06
183.07
117.25
153.17
20
221.02
213.04
236.14 242.86
245.87
0
172.21
100
iso/leucine
80
60
40
glycine
alanine
158.21
129.22
20
valine
NL: 5.43E5
ACSF 1X_acetone_extraction
phenyalanine
206.03
Asparagine
histidine
AV: 25 T: + p ESI Full cnl
46.000 [80.070-300.000]
tyrosine
222.84
184.05
196.09
116.13
0
120
140
160
180
m/z
200
220
240
Christina Ferreira and Yue Ren
ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH
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Parallels between embryo and cancer cell metabolism
 Energy metabolism: increased glycolysis.
 Amino acid metabolism: increased glutaminolysis.
 Increased fatty acid metabolism: beta-oxidation and de novo synthesis of fatty acids.
 Parallels in regulation pathways: pyruvate kinase isoform M2 (PKM2) active in cancer cells
and in embryos.
Smith and Sturmey, Biochem. Soc. Trans., 41:664-9 (2013).
DESI-MS
analysis
Embryos are individually placed onto glass slides
Immature_1to10_Niemann_TAG_070312
#61-73RT:1.28-1.49
AV:13 SB:7 0.03-0.14
NL:9.57E3
T:FTMS + p ESI Full ms [600.00-1200.00]
963.6562
100
Matured_1to10_Niemann_PL_070312
#103-138RT:3.14-4.20
AV:36 SB:140.07-0.46
NL:3.53E2
T:FTMS - p ESI Full ms [150.00-1000.00]
821.5663
100
90
90
80
80
Positive and negative
ion mode
free fatty acids,
cholesterol esters,
phospholipids,
C.R. Ferreira et al. J Mass Spectrom (2012)
tryacylglycerols and
C.R. Ferreira et al. Anal. Bioanal. Chem. (2012)
ubiquinone
Gonzalez-Serrano et al. PLoS One. 2013 Sep 20;8(9):e74981
885.5501
181.9372
70
Relative Abundance
70
Relative Abundance
Mouse or bovine
embryos are
washed to remove
culture media
688.1884
60
50
786.5291
742.5393
50
989.6719
40
804.5761
60
937.6406
625.3921
669.4184
30
861.5498
40
738.5221
700.5286
30
288.8971
713.4444
20
20
645.4909
757.4709
801.4969
10
266.9151
1015.6879
866.4817
909.6478
1041.7269
1085.7534
1134.5488
1173.8081
0
309.0485 394.0259
373.8744
10
906.5437
920.7562
479.0038
669.1102
506.2885 584.1326
991.5199
0
600
650
700
750
800
850
900
m/z
950
1000
1050
1100
1150
1200
200
300
400
500
600
m/z
700
800
900
1000
Bovine immature oocyte
DESI-MS
Ubiquinone as a hallmark in embryo
development and cancer stem cells
blastocyst produced in vivo
 ubiquinone ion (of m/z 1140.4,
Ag2NO3 adduct) is more abundant in
bovine blastocysts compared to
immature oocytes.
High resolution DESI-MS mass spectra of a bovine
oocyte (egg) and a blastocyst in the positive ion
mode. Abbreviations: TAG – triacylglycerols, Chol
ester – cholesterol ester.
 ubiquinone
adducts
appear
as
major
contributors
for
the
differentiation of mouse
cells genetically modified
to become cancer stem
cells (CSCs).
Valentina Pirro. Collaboration with Alice Chang (Purdue University)
Principal component analysis of DESIMS lipid profiles from control mammary
epithelial cells (green circles) and cells
genetically modified to express CSCs
properties.