Anne Le, MD, HDR Associate Professor of Pathology and Oncology - PowerPoint Presentation

Slide1

Anne Le, MD, HDRAssociate Professor of Pathology and OncologyPI, Le Cancer Metabolism Research LaboratoryCo-director, Metabolomics Program

06.02.2017

Metabolomics Technologies and Applications

Slide2

Resources available on campus: The Metabolomics ProgramMetabolomics workflowMetabolic approaches based on specific research projects/questions

Topics

Slide3

12

Resources available at Johns Hopkins:

The Metabolomics Program

Slide4

High-throughput analysis of metabolites (intermediates and products of metabolism)Systematic

determination

of metabolite levels in the metabolome and their

changes

Metabolome

Refers

to the complete set of small-molecule metabolites

Total

metabolite

pool: polar compounds, nonpolar compounds (ex amino acids, nucleotides, antioxidants, organic acids,

etc

)

Metabolomics Technologies

Slide5

Separation Techniques: the retention time of the analyte serves as information regarding its identity. Gas Chromatography (GC)‏Capillary Electrophoresis (CE)‏

High Performance Liquid Chromatography (HPLC)‏: We are currently using this

Ultra Performance Liquid Chromatography (UPLC)

‏

Ion Chromatography (IC)

Fourier Transform (FT)

Detection

Techniques

Nuclear Magnetic Resonance Spectroscopy (NMR)

‏:

separation

step is not mandatory

in

NMR.

Mass Spectrometry (

MS)

Combination of Techniques (used to increase coverage of detected metabolites)

GC-MSHPLC-MSFTICR-MS (Fourier Transform Ion Cyclotron Resonance)

Metabolomics Technologies

Slide6

Metabolic extractionLC-MS/MSDetection

D

ata

analysis

Metabolomics Workflow

polar compounds

organic

compounds

13

C

6

Glucose

12

C

6

Glucose

Treated

Control

Sample collection (plasma):

0, 3, 6, 12, 24 hours

Slide7

Experimental DesignIf stable isotope-resolved metabolomics (SIRM) involveIn vitro: replace normal full medium with medium without Glucose or Glutamine and add with 0.2% D-Glucose-13C6 or 2mM 13C15N Glutamine

In vivo:

inject 13C labeled Glucose (100

ul

of 20% x3 injections 15 min apart) or Glutamine (100

uL

of 100

mM

x3 injections 15 min apart).

Always have non-labeled samples (at least n = 3) for identification purpose (technical control)

Metabolic

Extraction to have lyophilized metabolites

Re-suspend the dried metabolites in 50% acetonitrile in order to submit to mass spec

Run MS mode, which includes positive and negative modes if needed. This MS data will provide a putative range of retention time (RT) of a given metabolite of interest.

Create MSMS list containing relevant compounds for the project: p value < 0.05 and 2x fold change (depends on the project).

and acquire MSMS fragmentation of the compound of interest.

Harvest

the samples

This fragmentation data will be used to determine accurate RT based on the fragmentation matching

Use the found RT to quantify all the samples in MS data

Current Metabolomics in vitro and in vivo

Slide8

Glutamine from DatabaseGlutamine from OV8

Glutamine

84.0443

101.0708

41.9986

58.0298

74.0253

127.0490

-

20V

41.9986

58.0298

74.0253

127.0490

Slide9

Glutamine

OV8 CR Ct

OV8 Ct

Slide10

Targeted and Untargeted MetabolomicsRelative and absolute quantification

Slide11

Projects

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Thank you!ICTRDr. Thomas Hartung My lab members for their hard work and awesomeness! Dr. Andre Kleensang

Accelerated Translational

Incubator Pilot Program (ATIP)

Slide13

The Advisory Committee

Slide14

In order to identify a compound, we need to rely on mass to charge ratio (if just relying on m/z then the results are only putative identification)And retention time (time it takes to travel through the column to the detector)

In order to find the retention time, we rely on:

MS/MS fragmentation

of that compound

Or

the retention time from a purified compound (standard): Often applied for targeted metabolomics

Metabolite Identification

Slide15

Glutamine from DatabaseGlutamine from OV8

Glutamine

84.0443

101.0708

41.9986

58.0298

74.0253

127.0490

-

20V

41.9986

58.0298

74.0253

127.0490

Slide16

Glutamine

OV8 CR Ct

OV8 Ct

Slide17

NMR and MS-based stable isotope-resolved metabolomics (SIRM) with 13C-labelled

Slide18

Identify exogenous compounds with isotopic labelled (13C)

Molecule

MW

M/Z

Glc2Bz

283.277692

283.277692

Ac4Glc2Bz

451.424725

451.424725

Glc2Bz-6-p

361.241728

180.620864

Glc2Bz-1-p

361.241728

180.620864

Benzoic acid-

α-

13

C

Slide19

Glutaminolysis and TCA cycle pathway: Probability 113C

15N

Non-label

https://wikispaces.psu.edu/pages/viewpage.action?pageId=40045009

Glutamate

dehydrogenase

Glutaminase

M+4:

from OAA (M+4)

first cycle

M+6

M+7

Slide20

Glutaminolysis and TCA cycle pathway: Probability 213C

15N

Non-label

https://wikispaces.psu.edu/pages/viewpage.action?pageId=40045009

Glutamate

dehydrogenase

Glutaminase

CO

2

CO

2

Lactate

Alanine

Malic enzyme

M+2:

from CoA (M+2)

first cycle

M+6

M+7

Slide21

Glutaminolysis and TCA cycle pathway: Probability 313C

15N

Non-label

https://wikispaces.psu.edu/pages/viewpage.action?pageId=40045009

Glutamate

dehydrogenase

Glutaminase

CO

2

CO

2

Lactate

Alanine

Malic enzyme

M+6:

from OAA (M+4) and CoA (M+2)

M+4:

from OAA (M+4)

M+2:

from CoA (M+2)

first cycle

Slide22

Glutaminolysis and TCA cycle pathway: Probability 4 (RedCarb in hypoxia)13C

15N

Non-label

https://wikispaces.psu.edu/pages/viewpage.action?pageId=40045009

Glutamate

dehydrogenase

Glutaminase

M+5:

from

Isocitrate

(M+5)

RedCarb

(Reductive carboxylation)

CO

2

Slide23

Le et al. Cell Met 2012Identifying new metabolic pathwaysGlucose-independent Glutamine-driven TCA

Cycle in Cancer Cells

citrate

isocitrate

a-ketoglutarate

acetyl-CoA

glutamate

glutamine

succinate

fumarate

oxaloacetate

malate

pyruvate

ME

PC

RedCarb

alanine

GPT2

CO

2

CO

2

aspartate

GLS

Slide24

FludarabinePentostatin, Cladribine

(leukemia)Clofarabine

(acute lymphoblastic leukemia)

Mercaptopurine

(leukemia and autoimmune diseases)

Nelarabine

(T cell malignancies)

Cytarabrine

(

leukemias

and lymphomas)

Gemcitabine

(various carcinomas)

Azacitidine

Decitabine

5-Fluorouracil

(breast, colorectal, esophageal, stomach cancers)

Floxuridine

Capecitabine

5-Fluorouracil

(breast, colorectal, esophageal, stomach cancers

)

Thioguanine

(leukemia and autoimmune disease)

Methotrexate:

inhibition of folic acid metabolism

Metabolomics-based discovery of pancreatic cancer combination therapy

Current metabolic-based anti-cancer drug

Slide25

Targeting

glutamine metabolism for cancer therapy

Glutamine metabolism

Glutamine = the

most abundant amino acid in the

bloodstream, supplies:

nitrogen for

nucleobase

synthesis

carbon

for the

TCA cycle

lipid

synthesis, and nucleotide synthesis

Glutamine

Glutamine

Slide26

Arg317

Glu325

Crystal structure of GLS in complex with

BPTES

Reitzer, Wice et al. ; Wise, DeBerardinis et al. PNAS

Breast cancer

Days

p=0.02

0

40

80

120

160

0

1

2

3

Cell Number

with glutamine

without glutamine

Days

0

10

20

30

40

0

1

2

3

Cell number/ml

Pancreatic cancer

*0.0001

90% pancreatic cancer

have KRAS mutation which

regulates glutamine

metabolism to support pancreatic cancer cell growth

Mutations in BRAF, KRAS, and HRAS were found in

triple negative breast cancers.

These genetic alterations are known to regulate glutamine metabolism and render cancer cells addicted to

glutamine.

10 13 16 19

0

400

800

1200

1600

Control

BPTES

Tumor volume (mm

3

)

Days

Lymphoma

Elgogary

et al.,

PNAS

2016

Le

et al.,

PNAS 2012

Glutamine addiction of cancer cells

Slide27

Glutamine addiction of cancer cells and why?

Arg317

Glu325

Glutamine

Glutamate

GLS

citrate

isocitrate

a-ketoglutarate

TCA

cycle

Glutaminase

inhibitor

WT

IDH1

mutant IDH1

isocitrate

glutamine

glutamate

GLS

BPTES

Study by Seltzer et al, CR, 2011 reported a profound cell growth inhibition of mutant IDH1 glioblastoma by BPTES as this mutation requires a-KG to produce 2-HG

Slide28

Outcome of first

GLSi

clinical trial: room for improvement

28

35 patients were enrolled: 100 – 800mg three times/day and 600mg twice/day

Target inhibition was confirmed in tumors

Radiographic stable disease was observed in 7 out of 25 patients (28%)

(during 107 days):

Triple negative breast cancer

: 2 out of 9 patients

NSCLC

: 2 out of 4 patients

Mesothelioma

: 2 out of 4 patients

RCC

: 1 out of 3 patients

Side effects:

7 patients: increases ALT/AST (4 patients), creatinine

,

alkaline

phosphatase, and GGT increases,

lymphopenia

,

hypoglycemia

(1

patient

each

)

Slide29

A

B

Blank NP

BPTES-NP

PEST

GFP

2XHRE

pCMV

mCherry

Geminin

FLAG

Spacer

S/G

2

M Cycling Cells

Hypoxic Cells

C

BPTES-NP

0

4

8

12

Aspartate

Blank-NP

BPTES-NP

*

Blank-NP

0

1

2

3

Guanine

Intensity x10

8

D

***

0.0

0.4

0.8

1.2

1.6

Blank NP

BPTES-NP

Area

x10

6

(µm)

mCherry

: cycling cells

GFP: hypoxic cells

***

0

4

8

12

Uracil

Blank-NP

BPTES-NP

*

Intensity x10

8

0

2

4

6

Adenosine

Blank-NP

BPTES-NP

**

Intensity x10

8

Intensity x10

8

Glutaminase

inhibition

Selectively Targets

Cycling

Tumor Cells

Elgogary

et al.,

PNAS

2016

Slide30

BPTES-NP

13C

-Glc

13

C

-bGlc

13

C

6

-Glucose

Label

Blank-NP

13

C

-Lac

13

C

6

-Glucose label

A

C

D

B

0

20

40

60

80

Lactate/Glucose

Lactate To Glucose Ratio

Blank-NP

BPTES-NP

**

0

2

4

6

8

Glutamine

Intensity

x10

3

Blank-NP

BPTES-NP

*

0

4

8

12

16

Blank-NP

BPTES-NP

*

Intensity

x10

4

Glucose

13

C

5

15

N

2

-Glutamine label

13

C

-Gln

H-1 Chemical Shift (ppm)

H-1 Chemical Shift (ppm)

H-1 Chemical Shift (ppm)

*

0

5

15

25

35

Lactate

Blank-NP

BPTES-NP

Intensity

x10

3

Identifying Metabolic Pathways after Treatment in vivo

PDAC

Cells that Survive

BPTES

-NP Treatment are Reliant on

Glycolysis

Elgogary

et al.,

PNAS

2016

Slide31

A

0

2

6

10

14

Blank-NP

BPTES-NP

Glutamine m+7

0

200

400

600

Glycogen

NMR

Relative Intensity

Blank-NP

BPTES-NP

E

*

G

*

**

Glutamine m+7

0

0.1

0.2

0.3

0.4

Blank-NP

BPTES-NP

C

0

4

8

12

Glutamate

Blank-NP

BPTES-NP

*

B

Glucose 1 Phosphate m+6

0

4

8

12

Blank-NP

BPTES-NP

% Enrichment

(

m+6)

/(

m+0)

*100%)

% Enrichment

(

m+7)

/(

m+0)

*100%)

D

0

1

3

5

7

% Enrichment

(

m+6)

/(

m+0)

*100%)

Blank-NP

BPTES-NP

Glucose 6 Phosphate m+6

*

0

1

2

3

4

5

Blank-NP

BPTES-NP

% Enrichment

(

m+6)

/(

m+0)

*100%)

UDP Glucose m+6

F

*

Intensity

x10

3

Intensity

x10

7

Elgogary

et al.,

PNAS

2016

Identifying Metabolic Pathways after Treatment in vivo

PDAC

Cells that Survive

BPTES

-NP Treatment are Reliant on Glycogen

synthesis

Slide32

E

0

2

6

10

0

16

Blank-NP

Metformin

BPTES

-NP

Metformin+ BPTES-NP

Relative Tumor Volume

Days Post Initial Treatment

14

F

Blank-NP

Metformin+BPTES-NP

BPTES-NP

1 cm

Metformin

1 cm

1 cm

1 cm

0

2

6

10

14

Lactate

Intensity x10

6

Control

Metformin

A

B

**

0

4

8

12

16

Glucose 6 Phosphate

Intensity x10

4

Control

Metformin

**

D

Control

Metformin

0

2

6

10

14

18

UDP Glucose

Intensity x10

6

**

0

1

2

3

4

Glucose 1 Phosphate

Intensity x10

4

Control

Metformin

C

*

*

#

Figure 7

Identifying S

uitable

M

etabolic Inhibitor

for combination

therapy in vivo

Combined

BPTES

-NP and Metformin

Treatment

Enhanced Efficacy

Elgogary

et al.,

PNAS

2016

Slide33

Non labeling

Slide34

High

Medium

Low

B

Glucose

Glucose-6-phosphate

Fructose-6-phosphate

Fructose 1,6 bisphosphate

Glyceraldehyde 3 phosphate

1,3 Biphosphoglycerate

Glycerate-3-Phosphate

Glycerate-2-Phosphate

Phosphoenol Pyruvate

Pyruvate

Lactic

Acid

C

Control

tFL

Indolent FL

0

5000

15000

25000

2/3 Phosphoglycerate

P<0.005

Cont.

Indolent

tFL

0

1000

5000

9000

Pyruvate

P<0.05

Cont.

Indolent

tFL

0

5000

25000

45000

Glyceraldehyde 3 Phosphate

P<0.005

Cont.

Indolent

tFL

0

10000

20000

30000

Lactate

P<0.02

Cont.

Indolent

tFL

tFL

Indolent FL

Normal

Speen

A

Nguyen et al, unpublished data

1. Metabolic

Signature of

MYC

-transformed Lymphoma B cells

Slide35

35High level of N-acetyl-aspartyl-glutamate (NAAG) found in more aggressive cancer type

NAAG peptidase

Aspartate

Acetyl-CoA

NAA

+

+

Aspartate N-acetyltransferase

N-acetylaspartate L-glutamate ligase

Glutamate

NAAG

0

10

20

30

40

50

60

AST II & III

GBM

Overall Survival (Months)

AST vs. GBM Survival Time

0

5

10

15

20

25

30

35

40

AST II & III

GBM (AST

IV)

Concentation

(

uM

)

NAAG Concentrations

0

50

100

150

200

250

300

AST II & III

GBM

Concentation

(

uM

)

NAA Concentrations

Slide36

0

0.2

0.4

0.6

0.8

1

0

6

12

18

24

30

36

42

48

54

Survival Rate

Months

Survival Probability based on NAAG Levels

Low NAAG Group

High NAAG Group

High

NAAG

Levels in Tumors and Blood Observed in

GBM

Patients with Shorter Survival

(A)

Kaplan

Meier survival curve of patients with high and low

intratumoral

NAAG measured in raw intensity. Of the 55 patient samples, 27 of the samples with the highest NAAG levels (median survival = 12 months) and the lowest 28 NAAG levels (median survival = 14 months) were plotted. P=0.00833.

Slide37

Monitoring N-acetyl-aspartate (NAA) in Patients with Spontaneous Intracerebral Hemorrhage for Prognostication

Slide38

Slide39

High Performance Liquid Chromatography (HPLC)Uses pumps to pass a solvent containing sample mixture through a coated columnCompounds are separated and identified using retention times

(time it takes to travel through the column to the detector)UV detection is utilized because many organic compounds absorb UV light With

the advent of electrospray ionization, HPLC was coupled to MS. As compared to GC, HPLC has lower chromatographic resolution, but requires no

derivitization

for polar molecules, has no MW limitations, and separates molecules in the liquid phase.

Much

wider range of

analytes

can be measured with a higher sensitivity than GC methods

.

Normal Phase:

Polar silica column (

strongly

polar)

and a nonpolar solvent. Polar compounds in the mixture will interact longer with the polar silica while the nonpolar compounds such as hexane pass quickly through the column. Reverse Phase: Nonpolar silica column with a polar solvent. The nonpolar compounds will interact longer with the nonpolar silica while the polar compounds pass quickly through the column.The stationary phase is non-polar and the mobile phase are polar liquids such as methanol, acetonitrile, or water. The more non-polar substances have longer retention.

Slide40

High Performance Liquid Chromatography (HPLC)

Slide41

HPLC vs UPLCHPLC

UPLC

Compounds

with higher MW and

polarity

Larger sample

s

izes

Lower chromatographic resolution

Wide range

analytes

A more efficient variant of HPLC

the overall operating pressure is increased to obtain more rapid flow rates

Gives

faster results with better resolution, less solvent needed

Columns with smaller particles

Slide42

Capillary Electrophoresis (CE)Sample introduction: uses a sample vialCapillary

tube: all ions are pulled through the tube in the same direction by electroosmotic flow

Detector:

analyte

separation is detected using UV-VIS light absorption

Output

device:

data appears as peaks with different retention times

Slide43

Analyte is injected into a carrier fluid (eluent) in the eluent generator and is passed through a separation column with a stationary fixed material (adsorbent)As the eluent flows through the separation column, the components of the analyte will separate down the stationary column at different speeds

The detector analyzes the output at the end of the column and generates a measurable signal that shows as a peak on the chromatogram

A suppressor is used to reduce the background conductance of the eluent and enhances the conductance of sample ions

Ion

Chromatography

Thermo

Fisher

found:

IC-MS

method for low level quantification of anionic ionic liquids and anionic species, including

counterions

and impurities

.

• Using the LC-MS method, major ionic liquid

analytes

can be analyzed at sub-ppb levels with the confirmation of major cation impurities: sodium and potassium.”