Title: Evaluation of the Activities of Antitumor Drugs in Cancer Cell Lines by 1HNMRbased Metabolomics
1Evaluation of the Activities of Antitumor Drugs
in Cancer Cell Lines by 1H-NMR-based Metabolomics
- Mariacristina Valerio, Adriana Amaro, Luca
Casadei, Lorena Casciani, Cecilia Castro and
Roberta Di Clemente
2Outline
3Metabolomics for cancer research
Metabolomics/metabonomics approaches are being
used to profile cell lines, tumors and systemic
metabolism in cancer patients, and will provide
another functional genomics tool for cancer
research
4Metabolomics for cancer research
Applications of metabolomics in cancer research
5Metabolomics of cancer cells
6Metabolomics of cancer cells
To monitor in parallel hundreds or even thousands
of metabolites, high-throughput techniques are
required that enable screening for relative
changes rather than absolute concentrations of
compounds
71H-NMR-based DBS metabolomic approach
Overview of 1H-NMR Difference Based spectra
(DBS) metabolomics approach to evaluate the
activities of antitumor drugs
81H-NMR-based DBS metabolomic approach
91H-NMR-based DBS metabolomic approach
A living cell secretes enzymes and excretes
metabolites to the extracellular medium. These
enzymes and metabolites interact with and modify
the components of the medium, resulting in
metabolic profiles that are highly specific to
species and/or genetic backgrounds (Metabolic
footprinting)
- Metabolic Footprinting vs. Metabolic
Fingerprinting - the turnover of most intracellular metabolites
is extremely fast (quenching of cell metabolism
followed by an effective separation of intra- and
extracellular metabolites and subsequent
extraction of intracellular compounds- time
consuming-) - the concentration of intracellular metabolites
in cell extracts are fairly low compared with
concentrations in extracellular samples
101H-NMR-based DBS metabolomic approach
111H-NMR-based DBS metabolomic approach
- 1H NMR is an excellent starting tool for
metabolite determination - minimal sample preparation required
- rapid analysis time
- Unbiased detector (allows detection of all
low-weight metabolites which contain 1H)
Treated
Control
1H-NMR spectrum of the deproteinated culture
medium of control and treated samples
121H-NMR-based DBS metabolomic approach
Which metabolites can be observed by NMR?
131H-NMR-based DBS metabolomic approach
Which metabolites can be observed by NMR?
141H-NMR-based DBS metabolomic approach
Which metabolites can be observed by NMR?
151H-NMR-based DBS metabolomic approach
Which metabolites can be observed by NMR?
161H-NMR-based DBS metabolomic approach
171H-NMR-based DBS metabolomic approach
Control
tn
tf
tn
Treated
tf
A representative 500 MHz 1H-NMR spectrum of the
culture medium at time zero or before-treatment
for a drug intervention (T0) and at various time
points of the study (following the administration
of a drug)
181H-NMR-based DBS metabolomic approach
191H-NMR-based DBS metabolomic approach
- Each spectrum divided into contiguous
segments (bins) with widths ranging from 0.01 to
0.03 ppm
- Total area within each segment is integrated
n (individual sample)
A representative 500 MHz 1H-NMR spectrum
(interval between 1.6 and 4.2 ppm) of the culture
medium and the corresponding data-reduced
spectrum at time To and Tn
p (integral values)
201H-NMR-based DBS metabolomic approach
Difference Based Spectra (DBS) metabolomic
approach
211H-NMR-based DBS metabolomic approach
Difference Based Spectra (DBS) metabolomic
approach
221H-NMR-based DBS metabolomic approach
Difference Based Spectra (DBS) metabolomic
approach
input descriptors for multivariate analysis
231H-NMR-based DBS metabolomic approach
- Why DBS?
- the obtained values are representative of net
balances the positive ones being considered an
estimate of net fluxes of production, and the
negative an estimate of the utilization of
metabolites - The use of difference spectroscopy permit us to
monitor small absorption changes, as it allows us
to highlight fine structures among spectra from a
large and intense common signal. - we analyse the whole spectrum differences instead
of a balance made over a selection of relevant
metabolites, so that no assumptions are made
concerning the metabolites important in defining
the effect of the perturbation - reduce analysis time
INPUT DESCRIPTORS for multivariate analysis
241H-NMR-based DBS metabolomic approach
251H-NMR-based DBS metabolomic approach
Orthogonal-Projection to Latent Structure
(O-PLS-DA)
261H-NMR-based DBS metabolomic approach
271H-NMR-based DBS metabolomic approach
28Example 1H-NMR-based Metabolomics Analysis of
Silibinin Anticancer Action in Human
hepatocellular liver carcinoma cell line (HepG2)
29Metabolomic of Silibinin action in HepG2 cells
Experimental protocol
30Metabolomic of Silibinin action in HepG2 cells
Experimental protocol
- Extraction of metabolite from medium
- Bligh-Dyer modified in our laboratory
- NMR data collection
- recorded on a Bruker DRX 500 spectrometer
- On the hydro-alcoholic phase
31Metabolomic of Silibinin action in HepG2 cells
Multivariate analysis protocol (OPLS-DA)
- Classification
- Bridge between classification and metabolic
insight metabolites important in the response of
the system to the perturbation are identified - Metabolic insight.
32Metabolomic of Silibinin action in HepG2 cells
Net Balance
33branched amino acids (more utilized in control)
Ketoacids (more produced in treated)
34Metabolomic of Silibinin action in HepG2 cells
Glucose
(more utilized in control)
35Metabolomic of Silibinin action in HepG2 cells
OPLS-DA scores plot Summarizes changes in
NMR-visible metabolome throughout Silibinin
treatment
Scores plot of medium extracts from control and
treated HepG2 cell
36Metabolomic of Silibinin action in HepG2 cells
metabolic response of HepG2 cells to Silibinin
treatment
37Metabolomic of Silibinin action in HepG2 cells
NTP dNTP
Glc
G6P
R6P
Gly
DMG
C-unit
PRODUCED
Plp base Exchange
For
Serinogenesis
G3P
Ser
Glycolysis
UTILIZED
Phospholipid
Phe, Tyr,
Pyr
Lac
Ac,PUF
Ala
Cit
Pyr
OAA
AKG
Gln
Glu
Thr,Leu,
Transamination
Mal
Suc
OAA
Asp
Pro, His Arg
KETO ACID
Ile, Val
38Concluding Remarks
This kind of metabolomic approach is utilized in
our laboratory to determine the phenotype of
different tumor cell line and to evaluate the
activity of antitumor extracts and fractions of
extracts from plants . This approach was used
to evaluate the antitumor activity of a molecule
designed by an italian pharmaceutical industry,
now in preclinical phase.