results grade1 grade2 grade3 (1) can we identify metabolites or metabolic pathways that are...

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Results S co re sc a tte rp lo t (t1 v s. t2 ) S ta n d a rd d e via tio n o f t1 : 4 .9 92 S ta n d a rd d e via tio n o f t2 : 7 .0 89 -1 2.5 -10.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 10.0 t1 -2 0.0 -1 7.5 -1 5.0 -1 2.5 -1 0.0 -7.5 -5.0 -2.5 0.0 2.5 5.0 7.5 1 0.0 1 2.5 1 5.0 t2 grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF MS w/ BinBase: 470 detected compounds 161 known metabolites, 309 without identified structure. Partial Least Square (multivariate stats) grade3 grade2 grade1 breast adipos e

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Page 1: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Resu

lts S co re sca tte rp l o t (t1 vs. t2 )

S ta n d a rd d e via ti o n o f t1 : 4 .9 9 2

S ta n d a rd d e via ti o n o f t2 : 7 .0 8 9

+ /-3 .0 0 0 *S td .De v-1 2 .5 -1 0 .0 -7 .5 -5 .0 -2 .5 0 .0 2 .5 5 .0 7 .5 1 0 .0

t1

-2 0 .0

-1 7 .5

-1 5 .0

-1 2 .5

-1 0 .0

-7 .5

-5 .0

-2 .5

0 .0

2 .5

5 .0

7 .5

1 0 .0

1 2 .5

1 5 .0

t2

grade1grade2

grade3

(1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters?

Alex-CIS-GCTOF MS w/ BinBase: 470 detected compounds161 known metabolites, 309 without identified structure.

Partial Least Square (multivariate stats)

grade3

grade2

grade1

breast adipose

Page 2: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

0

10

20

30

40

50

60

E+P+H- E+P+H+ E+P-H- E+P-H+ E-P+H- E-P+H+ E-P-H- E-P-H+

grade 1 grade 2 grade 3

Resu

ltsGrade n1 23 tumors show differential up-regulation in Pentose Phosphate Pathway, nucleotides, amino acids, arachidonic acid

(but not free fatty acids, gln)

production of NADPH, ribose units production of DNA, RNA

Page 3: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Resu

ltsGrade n1 23 tumors show differential up-regulation in Pentose Phosphate Pathway, nucleotides, amino acids, arachidonic acid

(but not free fatty acids, gln)

Amino acids

Amino acids

lactate

Ca te g . B o x & Wh iske r P lo t: g l u ta m ic a ci d

n o rm a l 1 2 3

g ra d e

0

1 E 5

2 E 5

3 E 5

4 E 5

5 E 5

6 E 5

glu

tam

ic a

cid

n o rm a l 1 2 3

g ra d e

0

2 0 0 0

4 0 0 0

6 0 0 0

8 0 0 0

1 0 0 0 0

1 2 0 0 0

1 4 0 0 0

be

ta-a

lan

ine

glu -ala

M e a n M e a n ±S E M e a n ±1 .9 6 *S E

n o rm a l 1 2 3

g ra d e

2 0 0 0

4 0 0 0

6 0 0 0

8 0 0 0

1 0 0 0 0

1 2 0 0 0

1 4 0 0 0

1 6 0 0 0

1 8 0 0 0

2 0 0 0 0

2 2 0 0 0

2 4 0 0 0

2 6 0 0 0

2 8 0 0 0

3 0 0 0 0

3 2 0 0 0

3 4 0 0 0

ma

late

malate

Ca te g . B o x & Wh iske r P lo t: c i tri c a ci d

n o rm a l 1 2 3

g ra d e

1 5 0 0 0

2 0 0 0 0

2 5 0 0 0

3 0 0 0 0

3 5 0 0 0

4 0 0 0 0

4 5 0 0 0

5 0 0 0 0

5 5 0 0 0

citr

ic a

cid

citrate

n 1 2 3 grade n 1 2 3 grade

n 1 2 3 grade n 1 2 3 gradeCa te g . B o x & Wh iske r P lo t: a ra ch id o n i c a ci d

M e a n M e a n ±S E M e a n ±1 .9 6 *S E

n o rm a l 1 2 3

g ra d e

2 0 0 0

4 0 0 0

6 0 0 0

8 0 0 0

1 0 0 0 0

1 2 0 0 0

1 4 0 0 0

1 6 0 0 0

1 8 0 0 0

arac

hido

nic

acid

C20:4 2HOglutarate

n 1 2 3 graden 1 2 3 gradeIDH1?

Page 4: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Resu

lts

Can we validate biomarkers in a fully independent study?Cohort 2 (113 patients)

Page 5: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Resu

lts

Can we validate lipidomic biomarkers in a fully independent study?

Cohort 2 (113 patients)

Matej Orešič et al. (subm.)

Page 6: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Resu

lts

Can we validate lipidomic biomarkers in a fully independent study? Immunohistochemistry on tissue slides.

Orešič et al. (subm)

Page 7: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Can we get biochemical maps of differential regulation for hormone receptor status?

Met

hods

(1) Up to 20% of the identified metabolites lack enzyme annotations.

(2) Metabolic endpoint metabolites accumulate more than intermediates. ‘Comprehensive maps’ do not work.

Page 8: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Can we get biochemical maps of differential regulation for hormone receptor status?

Met

hods

(1) Up to 20% of the identified metabolites lack enzyme annotations.

(2) Metabolic endpoint metabolites accumulate more than intermediates. ‘Comprehensive maps’ do not work.

Page 9: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Chemical and biochemical mapping of metabolomic resultsM

etho

ds

Page 10: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Resu

ltsGrade 1 tumors vs normal

Red nodes: up-regulated in tumors at p<0.05, size ~ x-foldBlue nodes: down-regulated in tumors at p<0.05, size~x-foldRed edges: enzyme substrate/product in KEGGRpair DBGreen edges: chemical similarity > 0.7

Page 11: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

0

10

20

30

40

50

60

E+P+H- E+P+H+ E+P-H- E+P-H+ E-P+H- E-P+H+ E-P-H- E-P-H+

grade 1 grade 2 grade 3

Met

hods

% o

f pati

ents

Estrogen negativeEstrogen positive

triple neg.

ER+ PR+HER2-

ER- PR-HER2-

single neg.

Hormone receptor @ grade 3

Page 12: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Resu

lts

ER- PR- HER- (n=27) Vs ER+PR+ HER- (n=19) P<0.05

Breast Cancer: Grade 3Red : metabolite is enriched in triple negative Blue : metabolite is down regulated in triple negativeNode size= fold change. Largest fold change is 3.

Metabolic phenotype of triple negative tumorsPatients without Estrogen, Herceptin neu2, Progesteron receptor

Page 13: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

0

10

20

30

40

50

60

E+P+H- E+P+H+ E+P-H- E+P-H+ E-P+H- E-P+H+ E-P-H- E-P-H+

grade 1 grade 2 grade 3

Met

hods

% o

f pati

ents

Estrogen negativeEstrogen positive

triple neg.

ER- PR-HER2+

ER- PR-HER2- double neg.

Hormone receptor @ grade 3

Page 14: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

Resu

ltsEffect of HER2 status on metabolic phenotype

of triple negative tumors

ER- PR- HER- (n=27) Vs ER-PR- HER+ (n=11) P<0.05

Breast Cancer: Grade 3

Red : metabolite is enriched in triple negative Blue : metabolite is down regulated in triple negativeNode size= fold change. Largest fold change is 3.

Page 15: Results grade1 grade2 grade3 (1) Can we identify metabolites or metabolic pathways that are associated with breast cancer clinical parameters? Alex-CIS-GCTOF

0

10

20

30

40

50

60

E+P+H- E+P+H+ E+P-H- E+P-H+ E-P+H- E-P+H+ E-P-H- E-P-H+

grade 1 grade 2 grade 3

Met

hods

% o

f pati

ents

Estrogen negativeEstrogen positive

ER+ PR+HER2-

double pos.

ER+ PR+HER2+

triple pos.

Hormone receptor @ grade 2