Download Quantification of Proteins in Normal vs Breast Cancer Cells

Quantification of Membrane and MembraneBound Proteins in Normal and Malignant
Breast Cancer Cells Isolated from the Same
Patient with Primary Breast Carcinoma
Liang, Zhao et. Al, 2006
Presented by:
Richard Pelikan
October 27, 2006
BioInf 2032
Motivation

How do you affect cells?
Motivation

How do you affect cells?
 Target
the cell membrane
Motivation

How do you affect cells?
 Target
the cell membrane
 What do you target?
Here goes
nothin’!
Objective

SILAC = Stable Isotope Labeling with
Amino acids in cell Culture

Determine if SILAC can effectively
determine changes in the protein
expression levels on cell membranes

Determine if these measurements are
related to disease
Outline
Introduction to Proteomics
 Experiments
 Results
 Discussion

Outline
Introduction to Proteomics
 Experiments
 Results
 Discussion

Introduction to Proteomics

Proteomics: The study of proteins
 How
do proteins interact?
 What effect can we have on proteins?
 How are proteins related to states of health?

More difficult than genomics
 Differences
between cells, organisms, etc.
Introduction to Proteomics

Which proteins can we monitor to measure
health?
 Biomarkers:
biological entities which shows
information

How do you find biomarkers?
 Develop
multiple protein assays
 Use high-throughput protein measurement
systems
Mass Spectrometry (MS)

Zap proteins with lasers, generating a
unique signature for the protein mixture
Mass Spectrometry (MS)

Zap proteins with lasers, generating a
unique signature for the protein mixture
1) Collect biofluids
Mass Spectrometry (MS)

Zap proteins with lasers, generating a
unique signature for the protein mixture
1) Collect biofluids
2) Zap with lasers
Mass Spectrometry (MS)
Zap proteins with lasers, generating a
unique signature for the protein mixture
1) Collect biofluids
2) Zap with lasers
3) Analyze data
100
90
80
70
60
Intensity

50
40
30
20
10
0
0
500
1000
1500
2000
2500
3000
mass/charge
3500
4000
4500
5000
Mass Spectrometry (MS)
Heavy molecules move slower
Amount

Mass / Charge
Mass Spectrometry (MS)
Heavy molecules move slower
7 Daltons
Amount

16 Daltons
(I’m tall for my
weight!)
Mass / Charge
Mass Spectrometry (MS)
Heavy molecules move slower
Amount

Mass / Charge
Mass Spectrometry (MS)
Heavy molecules move slower
Amount

Mass / Charge
Mass Spectrometry (MS)
Heavy molecules move slower
Amount

Mass / Charge
Mass Spectrometry (MS)
Heavy molecules move slower
Amount

Mass / Charge
Mass Spectrometry (MS)
Heavy molecules move slower
Amount

7
Mass / Charge
Mass Spectrometry (MS)
Heavy molecules move slower
Amount

7
Mass / Charge
Mass Spectrometry (MS)
Heavy molecules move slower
Amount

7
16
Mass / Charge
Mass Spectrometry (MS)

There is a tradeoff between the simplicity
of data production and quality of data

(In general) you don’t know which peak
corresponds to which protein

There are ways to control which proteins
you expect to see
Example of protein control
Introduction
Quantities of proteins can be measured
using MS technology
 It is necessary to have control over what
you see in the data to be able to identify
proteins
 Verification is still important!

Outline
Introduction to Proteomics
 Experiments
 Results
 Discussion

Experiments

Biofluid: Cells taken from a 74-year old
patient with breast cancer
 Some
cells are healthy, some are from the
tumor itself

Technology: MS instrumentation is
relatively standard
 Details
results
are only for performing replication of
Experiments – Protein Control
Normal cells
Tumor cells
+ Light tag solution
+ Heavy tag solution
Cells produce
tagged proteins
Mass spectra of the mixture
shows uneven proportions of
light and heavy proteins
m/z
Experiments – measuring ratios

A protein is broken down into peptides by
trypsin digestion

Each peptide generates a light-heavy pair

The ratio of each pair is averaged to
achieve the assumed ratio of the parent
protein
Figure 2 – Peptide Ratios
Experiments

Force cells to produce proteins with
differently weighted tags

Measure the differences in amounts of
proteins with light or heavy tags

Identify and study which proteins are
differentially expressed
Outline
Introduction to Proteomics
 Experiments
 Results
 Discussion

Results

997 proteins identified through the SILAC
technique
 830
of which are actually membrane proteins
 Only 35 were found to be “differentially
expressed”
 Many of these are reported in literature as
cancer biomarkers

Immunohistochemistry seems to reflect
the results seen in the MS data
Results - Immunohistochemistry
Normal

Cancer
Normal
Cancer
Staining seems to reflect regulation
observed in MS data (for this individual)
Outline
Introduction to Proteomics
 Experiments
 Results
 Discussion

Discussion

SILAC seems to be effective for
characterizing changes in the membrane
proteome

Didn’t detect one of the most prominent
membrane tumor markers
Discussion

Issues exist with this approach
 How
can it be high-throughput?
 To what degree is the differential expression
ratio significant to disease?
 Why the reliance on biopsy material?

Suggestions
 Do
a classification study
 Explain their independent tests better
Thank you!!

Forget proteomics, look forward to: