BioscienceInnovation for Health and Security

Metabolic Analysis ofTumor Progression

Norma Pawley

Los Alamos National Laboratory

BioscienceInnovation for Health and Security

LA-UR: 07-3608

Cancer Cells: Analysis Tools:James P. Freyer Steven BrumbySusan Carpenter Jason D. Gans

Metabolism: Mass Spectroscopy:Pat J. Unkefer Munehiro TeshimaStable Isotope Chemistry & Biochemistry:

Clifford J. Unkefer

Exponential

Plateau

Necrotic

SEM Image of Tumor Spheroid

0600Distance from Surface

(µm)

Fraction 3Fraction 4Necrosis

Fraction 2Fraction 1

nutrients wastes

~250,000 cells/spheroid

In vitro Tumor Model: Understanding the Components

E

P P

E

“Normal” (Immortalized) Tumorigenic

Normal RatFibroblasts

Rat1-T1Tumorigenic

Rat1Immortalized

c-myc

transfection

h-ras

transfectionM

ass

Val

ues,

Lar

ge S

pher

oids

Mass Values, Small Spheroids

-25

100

225

350

475

600

-25 100 225 350 475 600

Cell Type (modeline):Small Spheroids (142 μm)

Large Spheroids (1318 μm)

Small Spheroid Only 208

Large Spheroid Only 230

Common to Both 153

Common, Significant Change in Intensity

64

Unique Mass Values

Understanding the Components: Methods – Analysis

E

P P

E

“Normal” TumorigenicPositive Mode

Negative Mode

3 replicateinjections

3 replicateinjections

LT

FT

LT

FT

LT

FT

LT

FT

LT

FT

LT

FT

5 xFor each data collection:

240 spectra (not including blanks, internal standards, QC, etc.)

-- hundreds of compounds per spectrum.

100,000 – 1,000,000 compounds per data collection exceeds reasonable manual analysis

In-house software for automated, high-throughput analysis of accurate mass data

1) Filter and Identify Peaks

2) Match Peaks across Samples(retention time alignment)

3) Fill in Missing Peak Data

4) Extract Peak Statistics (intensity, reproducibility, etc.)

5) Identify Data Trends and Patterns

Assess Glycolytic Phenotype:

Plateau Exponential

RAT1 (Normal) 2.2 ± 0.9 (3 reps)

1.1 ± 0.4 (2 reps)

RAT1T1 (Tumorigenic)

0.4 ± ---* (1 observation)

0.7 ± ---* (1 observation)

Understanding the Components: Initial Results – Sanity Check

– Energy charge consistent between normal and tumorigenic cell lines

– Energy charge is lower in exponential cells than in plateau

Plateau Exponential

RAT1 (Normal) 0.82 ± 0.05

(4 reps) 0.59 ± 0.04

(2 reps)

RAT1T1 (Tumorigenic)

0.77 ± 0.10 (4 reps)

0.60 ± 0.07 (3 reps)

[AMP] [ADP] [ATP]

[ADP] [ATP] 21

Assess Energy Charge:

Glucose/Glucose 6-phosphate ratios show shift of glycolytic phenotype (Warburg effect) for tumorigenic cells.

From: Gatenby and Gillies,Nature Reviews Cancer (2004),Vol 4, p. 891-899

Hundreds of compounds per spectrum – in process of assigning.

In the meantime, we can look for known compounds and assess our results with respect to current body of knowledge.

LactatePyruvateAlanine

GlutamineGlutamateGlucose

Glucose 6-phosphate

LactatePyruvateAlanine

GlutamineGlutamateGlucose

Glucose 6-phosphate

Plateau

Understanding the Spheroid Tumor ModelInitial Results – presence (blue) vs. absence (white)

Exponential

RAT1(Normal)

RAT1T1(Tumorigenic)

Spheroid82 μm

112 μm

Conclusions

– We can observe differences in metabolic phenotype between normal and tumorigenic cells.

– ‘Classic’ differences between metabolic phenotype of normal and tumorigenic cells (use of glucose and glutamine, glycolytic phenotype) are consistent with literature.

– Exponential growth states look similar between normal and tumorigenic cells, but final states (plateau) differ significantly.

– Effects of microenvironment have greater impact on energetic fingerprint than does cell type.