cancer metabolomics and its applications leo l. cheng massachusetts general hospital harvard medical...
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Cancer Metabolomicsand Its Applications
Leo L. Cheng
Massachusetts General Hospital
Harvard Medical School
1L. L. Cheng
Informatics for Cancer Diagnosis- Altered molecular biology
Ris
k
Pre
dic
tab
ilit
y
Clinical Relevance
Genomics
Proteomics
Metabolo-mics
Pathology
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HRMAS MRS - Tissue Samples (~10mg)
- High Resolution Magic Angle Spinning
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w/o HRMAS
w/ HRMAS
x400
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HRMAS MRS
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HRMAS MRS
P1 P2 P3 P35 P36
S1 p1,1 p2,1 p3,1 p35,1 p36,1
S2 p1,2 p2,2 p3,2 p35,2 p36,2
S3 p1,3 p2,3 p3,3 p35,3 p36,3
S198 p1,198 p2,198 p3,198 p35,198 p36,198
S199 p1,199 p2,199 p3,199 p35,199 p36,199
PC1 PC2 PC3 PC35 PC36
P1 c1,1 c2,1 c3,1 c35,1 c36,1
P2 c1,2 c2,2 c3.2 c35,2 c36,2
P3 c1,3 c2,3 c3,3 c35,3 c36,3
P35 c1,35 c2,35 c3,35 c35,35 c36,35
P36 c1,36 c2,36 c3,36 c35,36 c36,36
Principal Component Analysis
- Intensities of 36 most common and intensive peaks.
Example:PC3 for Sample 2= A-(c3,1*p1,2 +c3,2*p2,2 +c3,3*p3,2+ … +c3,36*p36,2)
Peak Intensity
PC Coefficient
- 199 samples from 82 prostatectomy cases.
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Prostate Tissue
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E. V. % Cum%Epithelium
(r, p)
Cancer
(r, p)
Stroma
(r, p)
PC2 5.93 16.48 43.540.381,
<0.0001-0.303,
<0.0001
PC13 0.67 1.87 85.660.146, 0.0401
-0.154, 0.0302
PC14 0.55 1.54 87.20-0.160, 0.0243
-0.217, 0.0021
- First 16 PCs vs. Vol% of Epithelium, Cancer, & Stroma
Linear Regressions Analysis - Concentration
-20/199 samples have cancer glands; -13/82 cases have paired cancer/histol-benign analyzed;-12/13T2 and 1/13T3 tumors.
Canonical (Discriminant) Analysis- Metabolomic (concentration) Profile
10
Histo-benign
CancerP < 0.0001
0 1 2 3 4 5 6 7 8 9
Canonical Score 1
0
1
2
3
4
5
6
Can
onic
al S
core
2
9L. L. Cheng Cancer Res. 2005;65:3030-3034
Predicting Cancer Stage
10L. L. Cheng Cancer Res. 2005;65:3030-3034
MetabolomicImaging
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MRSI
Carhuapoma JR etal. Stroke 2000, 31:726-73212L. L. Cheng
MRSI
Horn JJ etal. Radiology 2006, 238:192-19913L. L. Cheng
Metabolomic Imaging - Phantom
14T
7T
1
3 2
14L. L. ChengSci. Transl. Med, 2010;2:16ra8
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VEigen %Cum
%PCa vs.
HBHB Epi PCa Epi Stroma
PC1 9.2 25.5 25.5 p<0.050 p<0.001
PC3 3.4 9.4 49.7 p<0.001
PC6 1.9 5.3 69.0 p<0.017 p<0.002 p<0.003
PC10 1.0 2.8 83.3 p<0.026
- First 10 PCs vs. Vol% of Epithelium, Cancer, & Stroma
Linear Regressions Analysis – Relative Intensity
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Canonical (Discriminant) Analysis- Metabolomic (Relative Intensity) Profile
-12/13T2 and 1/13T3 tumors.
Sci. Transl. Med, 2010;2:16ra8
Principal Component Analysis (Std Peak pi, i=1,2, … 36): PCj for Sample 2 = Aj-(cj,1*p1,2+cj,2*p2,2+cj,3*p3,2+…+cj,36*p36,2)
= Aj-icj,i*pi,2 ; (i=1,2, … 36)
Metabolomic Profiles
Canonical Analysis (PCk, k=L,M … N):Canonical Score X for Sample 2 =
= BX-(eL,X*PCL+eM,X*PCM+…+eN,X*PCN) = BX-kek,X*PCk; (k=L,M … N) = BX-kek,X*(Ak-ick,i*pi,2) = BX-(kek,X*Ak)-ik ek,X*ck,i) pi,2
Overall Loading Factor
ek,X*ck,i
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Metabolomic Imaging - Whole Prostate ex vivo
Urethra
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• Five prostates from prostatectomies;Metabolomic Imaging
• 7T human scanner;
• Three planes of 2D localized MRS, 16x16;
• Voxel = 3x3x3 mm3;
• Seven tumor histology regions, five inside- four T2 and one T3;
• Seven planes analyzed;
• Thirteen metabolomic regions (>M+SD, >2)22L. L. Cheng
Sci. Transl. Med, 2010;2:16ra8
Metabolomic Imaging
T2
T3
R2 = 0.998P < 0.001
P < 0.004 (T2)P < 0.008 (all)
AUC = 0.969(T2 Only)AUC = 0.925(Including T3)
R2 = 0.975P < 0.013
T2
T3
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Predicting TumorRecurrence
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Chemical Recurrence
25L. L. Cheng Prostate, 2009, doi:10.1002/pros.21103
1 - Specificity
PC4, 6, 7, & 8 PC1-9
Chemical Recurrence
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AUC = 0.71 AUC = 0.78
Prostate, 2009, doi:10.1002/pros.21103
Lung CancerSerum Profiles
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Lung Cancer
Lung Cancer, 2009, doi:10.1016/j.lingcan.2009.05.01228L. L. Cheng
Lung Cancer, 2009, doi:10.1016/j.lingcan.2009.05.01229L. L. Cheng
Lung Cancer: Clinical Data
Lung Cancer: Canonical Analysis
Lung Cancer, 2009, doi:10.1016/j.lingcan.2009.05.01230L. L. Cheng
Lung Cancer: Nominal Logistic Regression Analysis
Serum Profile Based on Tissue (SPT)
AC:-1.10+0.27SPT-1.27SP
SCC:-1.73-1.86SPT+0.77SP
Ctrl:-2.90+2.12SPT+1.21SP
Nominal Logisticp < 0.0001
Lung Cancer, 2009, doi:10.1016/j.lingcan.2009.05.01231L. L. Cheng
L. L. Cheng 32
MGH/HMSMelissa A. BurnsJennifer L. TaylorWnelei He Elkan F. HalpernW. Scott McDougalChin-Lee Wu
MGH/HMSChin-Lee WuKate W. JordanEva M. RataiChristen B. Adkins Elita M. DeFeoBruce G. JenkinsW. Scott McDougal
U. Wis-MilwaukeeJinhua Sheng Leslie Ying
MGH/HMSChristen B. Adkins Yifen ZhangElkan F. HalpernW. Scott McDougalChin-Lee Wu
Charite U., BerlinAndreas MaxeinerMatthias Taupitz
MGH/HMSKate W. JordanChristen B. Adkins Eugene J. Mark
HSPH/MGH/HMSLi SuDavid C. Christiani
Cancer Res 2005 Sci Transl Med 2010 Lung Ca 2009Prostate 2009
Conclusions and Acknowledgements
Grant Supports: NCI/NIH, DOD, MGH Martinos Center, and Bertucci Prostate Cancer Research Fund