metabolomics 2011 CCE project update LingYan Liu and Dan Raftery

metabolomics2011 CCE PROJECT UPDATE

LINGYAN LIU AND DAN RAFTERY

NMR ANALYSIS FROM ORIGINAL DATASET

Healthy Controls

CRC*Adenomatous

PolypsNon-adenomatous

Polyps

Samples (patients) 31 (31) 17 (14) 14 (14) 7(7)Age, mean (range) 53(20-85) 61(48-84) 58(47-73) 50(30-61)

CRC stageI - 2(2) - -II - 4(3) - -III - 5(4) - -IV - 5(4) - -

NA* - 1(1) - -EthnicityCaucation 21(21) 15(12) 10(10) 6(6)

African American 10(10) 1(1) 4(4) 1(1)Hispanic - 1(1) - -

*NA: stage information not available*CRC: colorectal cancer

Table 1. Summary of demographic and clinical parameters for recruited subjects.

CRC (n=23), adenomatous polyps (n=14), non-adenomatous polyps (n=7) and healthy controls (n=31).

-30 -20 -10 0 10 20 30 40-80

-60

-40

-20

0

20

40

Healthy Adenomatous polyps

Non_adenomatous polyps CRC

LV 1 (8.58%)

LV

2 (

5.2

3%

)

OSC-PLS SCORE PLOT FROM 1H NMR DATA.

Samples were divided into

training set

- samples obtained in the first batch

- to identify distinguishing metabolites and build a

statistical mode

validation set.

- samples obtained in the second batch

- used for validation of the model

SAMPLE GROUPING

Table 2. Quantitative comparison of 1HNMR marker metabolites in CRC and healthy serum.

a The percentage changes of CRC from healthy controls were calculated by 100x(CRC-healthy)/healthy.b p-values (CRC vs healthy) were calculated using unpaired t test with Welch’s correction on log2 transformed total sum normalized data.C area under ROC curve from cross-validation of individual marker model.

metabolites% change of CRC

from healthya p-valueb AUCROCc Sensitivity / Selectivity (%)

Marker 1 93.89 3.87E-02 0.74 75 / 76Marker 2 -21.56 3.25E-02 0.68 58 / 82Marker 3 41.79 3.17E-03 0.75 75 / 71Marker 4 -43.71 1.71E-02 0.73 75 / 76Marker 5 -17.18 2.44E-02 0.72 83 / 65Marker 6 60.37 5.68E-03 0.72 92 / 59

Six metabolites were found to differentiate CRC from Healthy Controls in the training set.

SIX MARKER METABOLITES

Figure 3. Box-and-whisker plot of six metabolites selected from training set.

Pathways involved include TCA and urea cycles, pyruvate and proprionate metabolism.

Cancer Healthy

-10

.5-9

.0-8

.0-7

.0

Formate

CRC HealthyCancer Healthy

-8.5

-8.0

-7.5

-7.0

Histidine


-5.5

-4.5

-3.5

Lactate

CRC Healthy

Marker 1 Marker 2 Marker 3

Cancer Healthy

-5.0

-4.6

-4.2

-3.8

Valine


-9-8

-7-6

-5

1,2-propanediol


-6.0

-5.0

-4.0

-3.0

Creatinine

CRC Healthy

Rel

ativ

e in

tegr

als

(log

2 sc

aled

)


SIX MARKER METABOLITES

AUC=0.99

B.ROC of prediction result on valid set

False positive rate

Tru

e po

sitiv

e ra

te

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

00.

210.

641.

06

AUC=1

Tru

e po

siti

ve

rate

False positive rate False positive rate

Tru

e po

sitiv

e ra

te

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

00.

210.

621.

04

cutoff value

Tru

e po

siti

ve

rate

False positive rate

A.

0 1

0.0

0.2

0.4

0.6

0.8

1.0

Healthy CRC

C.

Rel

ativ

e in

tegr

als

(log

2 sc

aled

)

Figure 4. Results of logistic regression analysis using the five metabolite markers. A) ROC curves obtained from the cross-validation of training set with CRC (n=12) and healthy controls (n=17) samples; the arrow indicates the cutoff selected for calculating sensitivity and specificity; B) ROC curve obtained from the prediction of validation sample set; and C) box- and-whisker plot for the prediction of validation set with CRC (n=5) and healthy controls (n=14).

L1-REGULARIZATION PATH SELECTED MARKER METABOLITES CONSTRUCTED MODEL FOR CRC DISCRIMINATION

A B

-8.5

-8.0

-7.5

-7.0

Histidine

Marker 2

Healthy APA B

-6-5

-4-3

CreatinineMarker 4

Healthy AP

A B-7

-6-5

-4

Glutamine

Healthy AP

Marker 7

A B

-11

.0-1

0.0

FormateMarker 1

Healthy APA B

-5.5

-5.0

-4.5

-4.0

Lactate

Healthy AP

Marker 3

Rel

ativ

e in

tegr

als

(log

2 sc

aled

)

Figure 7. Box-and-whisker plot for the five metabolites that show some difference between adenomatous polyps (n=14), and healthy controls (n=31). The differences were statistically significant for two of the 5 marker candidates (p <0.05 for both).

DIFFERENCE BETWEEN ADENOMATOUS POLYPS AND HEALTHY CONTROLS

SAMPLE INFORMATION FROM CCE

120 serum samples were received between Nov. 2009 and Sept.

2010.

In total 230 serum samples were received, including

- 35 Colon cancers (7 w/o any treatment; 28 w. treatment.)

- 14 Rectal cancers (8 w/o any treatment; 6 w. treatment.)

- 93 Healthy controls

- 86 Polyps

- 2 unknown (CCE-015-1 and CCE-015-2)

230 serum samples from CCE have been analyzed using 500 MHz 1H

NMR

All spectra were preprocessed, baseline corrected, aligned, and

uploaded to CCEhub.org.

26 metabolite features were identified and quantified by relative

integrals.

CCE NMR ANALYSIS

Experimental conditions and parameters such as GC column

combination, gas flow rate, gradient were evaluated and optimized.

230 serum samples have been analyzed using Leco GC x GC –TOFMS.

All spectra were processed. Net cdf. File and peak table of each

spectrum were uploaded to CCEhub.org. (With Ann Caitlin’s support.)

GCxGC -TOFMS Analysis

GC X GC – TOFMS ANALYSIS ON ORIGINAL DATA 24 metabolites were identified as putative markers from training set and quantified.

Appear in 90% samples; Similarity > 700(in scale of 1000)Metabolites can be found in hmdb

OPLS on training set which grouped as same as NMR data (12 CRC and 17 Healthy Controls)

-600000 -500000 -400000 -300000 -200000 -100000 0 100000 200000 300000 400000-250000

-200000

-150000

-100000

-50000

0

50000

100000

150000

200000

OPLS

Healthy Cancer Polyps_adenomatous Polyps_nonadenomatous

Cancer Healthy Polyps_A Polyps_NA

-2

-1

0

1

2

acetic acid

p=0.03


-1

0

1

2

Azelaic acid

P=0.005


-2

-1

0

1

2

3

L-Tryptophan

P=0.04Cancer Healthy Polyps_A Polyps_NA

-2

-1

0

1

2

3

Inositol phosphate


-1

0

1

2

3

Hexanedioic acid

P=0.01

P=0.02

GC-MS Analysis: 10 metabolites were found significantly differentiate in CRC from Healthy controls in training set.


Marker 4 Marker 6


-2

-1

0

1

Pyrrolidinone

P=0.003


-1

0

1

2

2-Hydroxyglutaric acid

P=0.003


-1

0

1

2

aminoisobutyric acid

P=0.02


-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

RIBITOL


-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

pyrophosphate

P=0.02P=0.002


Marker 9Marker 10

FINDINGS THUS FAR

NMR and GCxGC-MS data obtained on original 44 samples and over 230 CCE samples thus far.

NMR analysis indicates that several markers are holding up for distinguishing polyps from healthy controls as well as colon cancer.

These markers generally show a progression from health to polyps to cancer

Some indications that treatment can be followed May work best using ratio of metabolites over time

GC-MS data on original samples looks promising GC-MS data is expected to improve metabolite

profiles

SUPPLEMENTARY SLIDES

ROC of prediction result on validation set

False positive rate

Tru

e p

osi

tive

ra

te

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

00

.21

0.4

30

.64

0.8

51

.06

AUC=0.80 1 3 4

0.0

0.2

0.4

0.6

0.8

1.0

Prediction result by CRC-control model

Healthy Cancer Adenomatouspolyps

Non-adenomatouspolyps

PREDICTION ON VALIDATION SET

5 cancer , 12 healthy, 14 Adenomatous polyps, 7 non-adenomatous polyps.

Model built on 7 GC-MS detected markers.

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

ROC Curve

False Alarm Rate

Hit

Ra

te

0.10.2

0.3

0.4

0.50.60.7

0.9

AUC=0.84375

Cross-validation ROC

L1-REGULARIZATION PATH SELECTED MARKER METABOLITES CONSTRUCTED MODEL FOR CRC DISCRIMINATION

Cancer

-4.8

-4.4

-4.0

-3.6

Lactate

APCRCCancer

-5.0

-4.8

-4.6

-4.4

Valine

P-

P-value= 0.037 P-value= 0.0054

.A. B.

Rel

ativ

e in

tegr

als

(log

2 sc

aled

)

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

0.06

0.47

0.87

AUC=0.83

C.

Tru

e po

siti

ve r

ate

False positive rate APCRC

NMR Markr 3 NMR Marker 5

Figure 5. Box-and-whisker plot for two metabolites, A) Marker 3(p-value=0.037) and B) NMR Marker 5 (p-value=0.0054) which classify CRC and AP in the training set samples. C. ROC for the prediction of the validation set of samples using the model built from the two metabolites.

DIFFERENTIATING CRC FROM ADENOMATOUS POLYPS (AP).

-1012345678910

CRC samples healthy samples

difference (CRC spectrum-healthy spectrum)

chemical shift (ppm)

6.87.88.8

crea

tini

ne

form

ate

hist

idin

e

1,2-

prop

aned

iol

gluc

osela

ctat

e

vali

ne

Figure 2. Overlap of the mean 1H NMR spectra for CRC (red dashed) and healthy controls (blue) (bottom); difference of the mean spectra (top). The inset shows vertical expansion for the marker region.

1HNMR SPECTRA

Propane-1,2-diol

Valine

Lactate

Histidine

Lactaldehyde

Pyruvate

Formate

PROPANOATE METABOLISM

PYRUVATE METABOLISM

Alanine

Aspartate

Glutamate

Glutamine

UREA CYCLE

TCA CYCLE

Guanidinoacetate

Creatine

Creatinine

Figure 8. Pathway diagram showing altered metabolite for patients with CRC and those with AP. Upward arrow indicates significantly higher in CRC and downward arrow indicates significantly lower in CRC compared to healthy controls. The downward arrow with dashed line indicates significantly lower in AP compared to healthy controls.

Metabolic profiling was explored based on markers find from the data.

METABOLIC PROFILING

FORMIC ACID IN CANCER PATIENTS FOR DISEASE MONITORING

0 1 2 30

0.01

0.02

0.03

0.04

0.05

0.06

Successful treatment

CCE-009 (complete response)CCE-139 (Stage I after surgery)

Blood drawn time point

Form

ic a

cid

0 1 2 30

0.010.020.030.040.050.060.07

Stage IV patients after surgery

CCE-014 (stage IV after surgery, with 1 month Chemo)CCE-012 (stage IV after surgery)


Form

ic a

cid

0 1 2 30

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

Disease progression

CCE-026 CCE-013 (recurrence stable disease)CCE-028 CCE-020 (disease progression)CCE-053 (metastatic sites: lung, bone) CCE-187 (disease progression)


Form

ic a

cid

10

0.01

0.02

0.03

0.04

0.05

0.06

Valu

es

Column NumberHealthy Controls

FORMIC ACID IN CANCER PATIENTS FOR DISEASE MONITORING

Adenomatous Polyps (n=76) vs. Healthy Controls (n=93)

1 Healthy Control 2 AP0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

Val

ues

Formic acid p-value=0.048

Rela

tive Inte

gra

ls

Healthy Controls

Adenomatous Polyps

1 Healthy Control 2 AP

0.5

1

1.5

2

2.5

Val

ues

Acetoacetic acid, p-value=0.039

Healthy Controls

Adenomatous Polyps

1 Healthy Control 2 AP

10

20

30

40

50

60

Val

ues

Lactic acidp-value=0.018

Healthy Controls

Adenomatous Polyps

CCE NMR ANALYSIS ON POLYPS.

metabolomics 2011 CCE project update LingYan Liu and Dan Raftery

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