Comprehensive Quantitative Analysis of Ovarian and Breast...
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Comprehensive Quantitative Analysis of Ovarian and Breast Cancer Tumor Peptidomes Zhe Xu 1 , Chaochao Wu 1 , Fang Xie 1 , Gordon W. Slysz 1 , Nikola Tolic 2 , Matthew E. Monroe1, Vladislav A. Petyuk 1 , Samuel H. Payne 1 , Grant M. Fujimoto 1 , Ronald J. Moore 1 , Thomas L. Fillmore 2 , Athena A. Schepmoes 1 , Douglas A. Levine 3 , Reid Townsend 4 , Sherri R. Davies 4 , Shunqiang Li 4 , Matthew Ellis 4 , Emily Boja 5 , Robert Rivers 5 , Henry Rodriguez 5 , Karin D. Rodland 1 , Tao Liu 1 , Richard D. Smith 1 1 Biological Sciences Division, 2 Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA; 3 Gynecology Service/Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY; 4 Department of Medicine, Washington University, St. Louis, MO; 5 Office of Cancer Clinical Proteomics Research, National Cancer Institute, National Institutes of Health, Bethesda, MD Introduction Overview Methods Results Acknowledgements Portions of this work were supported by the grant U24CA160019, from the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (CPTAC), National Institutes of Health grant P41GM103493, and Department of Defense Interagency Agreement MIPR2DO89M2058. The experimental work described herein was performed in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the DOE and located at Pacific Northwest National Laboratory, which is operated by Battelle Memorial Institute for the DOE under Contract DE-AC05-76RL0 1830. References 1. Hanahan D and Weinberg RA. Hallmarks of cancer: the next generation. Cell. 144, 646-674 (2011). 2. Lopezin-Otin C and Overall CM. Proteases degradomics: a new challenge for proteomics. Nature Rev Mol Cell Biol. 3, 509-519 (2002). 3. Villanueva et al. Differential exoprotease activities confer tumor-specific peptidome patterns. J Clin Invest. 116, 271–284 (2006). 4. Shen et al. Blood peptidome-degradome profile of breast cancer. PLoS One. 5, e13133 (2010). Conclusions Good coverage and reproducibility provided by the tumor peptidomics platform CONTACT: Zhe Xu, Ph.D. Biological Sciences Division Pacific Northwest National Laboratory E-mail: [email protected] •The reproducibility and coverage of a new tumor peptidomics pipeline have been demonstrated. •Clinical tumor samples and patient-derived tumor xenograft samples, with post- excision delay of up to 60 min, have been determined as suitable for peptidomics analysis. •Peptidomics profiles can be used to effectively separate different cancer types or subtypes, as well as individual patients. •The peptidome, studied using top-down approaches, provides a practical and useful adjunct to bottom-up approaches. www.omics.pnl.gov Career Opportunities: For potential openings in the Omics Separations and Mass Spectrometry Department at PNNL please contact: Dick Smith at [email protected] Josh Adkins at [email protected] • Top-down analysis of the peptidome can provide insights to which conventional bottom-up proteomics are blind. • Developed an effective and robust analytical platform for comprehensive analyses of the tissue peptidome, which is suitable for high throughput quantitative studies. • Peptidomic profiles reflect tumor-associated protease activity and are expected to provide unique and complementary results to those obtainable from conventional bottom-up proteomics approaches. • Aberrant degradation of proteins is associated with many pathological states including cancers. 1,2 • Mass spectrometric analyses of the tumor peptidome, the intracellular and intercellular products of protein degradation, have the potential to provide biological insights on proteolytic processing in cancer. 3 • Effective approaches for robust peptidomic identification and quantification are lacking, and suffer confounding factors and biases due to sample handling and processing. • We have previously shown the potential of peptidomics using top-down approaches. 4 • In this study we demonstrate the effectiveness and utility of a new peptidomics platform for comprehensive characterization of ovarian and breast tumor peptidomes. Protein extraction • Add extraction buffer (0.25% acetic acid with the protease inhibitors) • Homogenize/sonicate on ice bed • Centrifuge @ 14,000 × g, 4 °C for 30 min Ultrafiltration •Filter with 30 kDa MWCO filters @ 8,000 × g, 4 °C •Concentrated the sample in Speed-Vac •Final peptide/protein yield: 0.3% LC-MS/MS analysis • LC: 70 cm 75 m i.d. column; 3-m Jupiter C18; 240-min gradient; Waters UPLC •MS: Orbitrap Velos; 60K for MS and 15K for MS/MS (CID); top6 MS/MS Data analysis •MS/MS data: Sequest + MS-Align create one peptide database •LC-MS data: accurate mass and time (AMT) tag or Informed Quantitation (IQ) analysis Samples Workflow applied New Informed Quantitation (IQ) approach applied Mass and peptide MS intensity distribution of the peptidomes of the clinical ovarian tumor samples and Patient-derived xenograft breast tumors 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 0 2000 4000 6000 8000 10000 12000 14000 16000 Log10 (intensity) Monoisotopic Mass Distribution of intensity and mass PDX OvCa Comprehensive coverage provided by IQ approach Good reproducibility for tumor peptidome analyses 1142 (70.3%) WHIM6-0-a-3: 1416 WHIM6-0-a-1: 1368 WHIM6-0-a-3: 1408 Overlap of peptide identifications Correlation of peptide intensities Breast tumor Peptides Protein groups Ovarian tumor Post-excision delay of up to 60 min does not impact tumor peptidome characterization A-0 A-5 A-30 A-60 B-0 B-5 B-30 B-60 C-0 C-5 C-30 C-60 A-0 A-5 A-30 A-60 B-0 B-5 B-30 B-60 C-0 C-5 C-30 C-60 Volcano Plot for Kinetics-based Regression 0 up, 0 down out of 2547 Adjusted p-value log2 of 60 min / 0 min abundance ratio Time (0%) Both (0%) Percentages of peptides significantly affected by corresponding factors Pearson correlation of peptide intensities across all ovarian tumor datasets Peptidome profiles indicate tumor-specific proteolytic activities Breast cancer subtypes separated by peptidome profiles Pearson correlation of peptide intensities across all ovarian tumor datasets WHIM6-0-a-3 WHIM6-0-a-2 WHIM6-0-a-1 WHIM6-60-a WHIM6-60-b WHIM6-0-b WHIM16-2 WHIM16-1 WHIM2-2 WHIM2-1 PCA plot (64.7%) PC2 (23.2%) PC1 (41.5%) Proteolytic cleavage specificity for OvCa vs. BrCa Frequency 0 50 100 150 200 250 ACDEFGHIKLMNPQRSTVWY P1_Down P1_Up 0 500 1000 1500 2000 2500 ACDEFGHIKLMNPQRSTVWY P1_Down P1_Up Frequency OvCa tumor peptidome PDX tumor human- specific peptidome WHIM6- 0-a-1 WHIM6- 0-a-2 WHIM6- 0-a-3 WHIM6-0-a-1 WHIM6-0-a-2 WHIM6-0-a-3 WHIM6-0-b WHIM6-60-a WHIM6-60-b WHIM2-1 WHIM2-2 WHIM16-1 WHIM16-2 WHIM6-0-a-1 WHIM6-0-a-2 WHIM6-0-a-3 WHIM6-60-a WHIM6-0-b WHIM6-60-b WHIM2-1 WHIM2-2 WHIM16-1 WHIM16-2 WHIM6 WHIM16 WHIM2 0 1000 2000 3000 4000 5000 6000 7000 A-0 A-5 A-30 A-60 A-0 B-5 B-30 B-60 C-0 C-5 C-30 C-60 Total Identified peptide number Comparison between IQ and MS-Align+ IQ MS-Align+ Identified Peptide number 0 200 400 600 800 1000 1200 1400 1600 WHIM6-0-a-1 WHIM6-0-a-2 WHIM6-0-a-3 WHIM6-60-a WHIM6-0-b WHIM6-60-b WHIM2-1 WHIM2-2 WHIM16-1 WHIM16-2 OvCa tumor BrCa PDX tumor • Total protein groups (IDPicker3): 974 • Total protein groups (IDPicker3): 824 Patient A: 960 928(95.4%) Patient B: 956 Patient C: 950 Normalized Frequency 0 0.1 0.2 0.3 0.4 ACDEFGHIKLMNPQRSTVWY N-terminus with Met cleaved 0 0.1 0.2 0.3 0.4 A D F H K M P R T W N-terminus with Met 0 0.02 0.04 0.06 0.08 0.1 0.12 ACDEFGHIKLMNPQRSTVWY C-terminus Normalized Frequency 0 0.02 0.04 0.06 0.08 0.1 0.12 ACDEFGHIKLMNPQRSTVWY Other N-terminal peptides 0 0.05 0.1 0.15 ACDEFGHIKLMNPQRSTVWY C-terminus -1 0 0.02 0.04 0.06 0.08 0.1 ACDEFGHIKLMNPQRSTVWY C-terminus-2 Normalized Frequency 0 0.02 0.04 0.06 0.08 0.1 ACDEFGHIKLMNPQRSTVWY All peptidome peptides Normalized Frequency Analyses of N- and C- terminal cleavage specificities revealed involvement of N-terminal Met Excision (NME) processing Chymotrypsin and trypsin activities are the major contributor to both peptidomes, suggesting the involvement of proteasome-dependent pathway • Significantly improved sensitivity • Provides more accurate quantification • Better distinguishes overlapping features • Improves FDR and reduces “missing data” Solid lines : charge states chosen for MS/MS fragmentation Dashed lines: charge states present but not chosen for fragmentation A. B.
Transcript of Comprehensive Quantitative Analysis of Ovarian and Breast...
Comprehensive Quantitative Analysis of Ovarian and Breast Cancer Tumor Peptidomes Zhe Xu1, Chaochao Wu1, Fang Xie1, Gordon W. Slysz1, Nikola Tolic2, Matthew E. Monroe1, Vladislav A. Petyuk1, Samuel H. Payne1, Grant M. Fujimoto1, Ronald J. Moore1, Thomas L. Fillmore2, Athena A. Schepmoes1, Douglas A. Levine3, Reid Townsend4, Sherri R. Davies4, Shunqiang Li4, Matthew Ellis4, Emily Boja5, Robert Rivers5, Henry Rodriguez5, Karin D. Rodland1, Tao Liu1, Richard D. Smith1
1 Biological Sciences Division, 2 Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA; 3 Gynecology Service/Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY; 4
Department of Medicine, Washington University, St. Louis, MO; 5Office of Cancer Clinical Proteomics Research, National Cancer Institute, National Institutes of Health, Bethesda, MD
Introduction
Overview Methods Results
AcknowledgementsPortions of this work were supported by the grant U24CA160019, from the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (CPTAC), National Institutes of Health grant P41GM103493, and Department of Defense Interagency Agreement MIPR2DO89M2058. The experimental work described herein was performed in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the DOE and located at Pacific Northwest National Laboratory, which is operated by Battelle Memorial Institute for the DOE under Contract DE-AC05-76RL0 1830.
References 1. Hanahan D and Weinberg RA. Hallmarks of cancer: the next generation.
Cell. 144, 646-674 (2011).
2. Lopezin-Otin C and Overall CM. Proteases degradomics: a new challenge for proteomics. Nature Rev Mol Cell Biol. 3, 509-519 (2002).
3. Villanueva et al. Differential exoprotease activities confer tumor-specific peptidome patterns. J Clin Invest. 116, 271–284 (2006).
4. Shen et al. Blood peptidome-degradome profile of breast cancer. PLoS One. 5, e13133 (2010).
Conclusions
Good coverage and reproducibility provided by the tumor peptidomics platform
CONTACT: Zhe Xu, Ph.D. Biological Sciences Division
Pacific Northwest National Laboratory
E-mail: [email protected]
•The reproducibility and coverage of a new tumor peptidomics pipeline have been demonstrated.
•Clinical tumor samples and patient-derived tumor xenograft samples, with post-excision delay of up to 60 min, have been determined as suitable for peptidomics analysis.
•Peptidomics profiles can be used to effectively separate different cancer types or subtypes, as well as individual patients.
•The peptidome, studied using top-down approaches, provides a practical and useful adjunct to bottom-up approaches.
www.omics.pnl.gov
Career Opportunities: For potential openings
in the Omics Separations and Mass Spectrometry
Department at PNNL please contact:
Dick Smith at [email protected]
Josh Adkins at [email protected]
• Top-down analysis of the peptidome can provide insights to which conventional bottom-up proteomics are blind.
• Developed an effective and robust analytical platform for comprehensive analyses of the tissue peptidome, which is suitable for high throughput quantitative studies.
• Peptidomic profiles reflect tumor-associated protease activity and are expected to provide unique and complementary results to those obtainable from conventional bottom-up proteomics approaches.
• Aberrant degradation of proteins is associated with many pathological states including cancers.1,2
• Mass spectrometric analyses of the tumor peptidome, the intracellular and intercellular products of protein degradation, have the potential to provide biological insights on proteolytic processing in cancer.3
• Effective approaches for robust peptidomic identification and quantification are lacking, and suffer confounding factors and biases due to sample handling and processing.
• We have previously shown the potential of peptidomics using top-down approaches.4
• In this study we demonstrate the effectiveness and utility of a new peptidomics platform for comprehensive characterization of ovarian and breast tumor peptidomes.
Protein extraction
• Add extraction buffer (0.25% acetic acid with the protease inhibitors)
• Homogenize/sonicate on ice bed
• Centrifuge @ 14,000 × g, 4 °C for 30 min
Ultrafiltration
•Filter with 30 kDa MWCO filters @ 8,000 × g, 4 °C
•Concentrated the sample in Speed-Vac
•Final peptide/protein yield: 0.3%
LC-MS/MS analysis
•LC: 70 cm 75 m i.d. column; 3-m Jupiter C18; 240-min gradient; Waters UPLC
•MS: Orbitrap Velos; 60K for MS and 15K for MS/MS (CID); top6 MS/MS
Data analysis
•MS/MS data: Sequest + MS-Align create one peptide database
•LC-MS data: accurate mass and time (AMT) tag or Informed Quantitation (IQ) analysis
Samples
Workflow applied
New Informed Quantitation (IQ) approach applied
Mass and peptide MS
intensity distribution of the
peptidomes of the clinical
ovarian tumor samples and
Patient-derived xenograft
breast tumors
4
4.5
5
5.5
6
6.5
7
7.5
8
8.5
9
0 2000 4000 6000 8000 10000 12000 14000 16000
Lo
g1
0 (
inte
nsity)
Monoisotopic Mass
Distribution of intensity and mass
PDX
OvCa
Comprehensive coverage provided by IQ approach
Good reproducibility for tumor peptidome analyses
1142 (70.3%)
WHIM6-0-a-3:
1416
WHIM6-0-a-1:
1368
WHIM6-0-a-3:
1408
Overlap of peptide identifications Correlation of peptide intensities
Bre
ast tu
mo
r
Peptides
Protein
groups
Ova
ria
n tu
mo
r
Post-excision delay of up to 60 min does not impact tumor peptidome characterization
A-0
A-5
A-3
0
A-6
0
B-0
B-5
B-3
0
B-6
0
C-0
C-5
C-3
0
C-6
0
A-0
A-5
A-30
A-60
B-0
B-5
B-30
B-60
C-0
C-5
C-30
C-60
Volcano Plot for Kinetics-based Regression
0 up, 0 down out of 2547
Ad
juste
d p
-va
lue
log2 of 60 min / 0 min abundance ratio
Time (0%)
Both (0%)
Percentages of peptides significantly
affected by corresponding factors
Pearson correlation of peptide
intensities across all ovarian
tumor datasets
Peptidome profiles indicate tumor-specific proteolytic activities
Breast cancer subtypes separated by peptidome profiles
Pearson correlation of peptide
intensities across all ovarian
tumor datasets
WH
IM6-0
-a-3
WH
IM6-0
-a-2
WH
IM6-0
-a-1
WH
IM6-6
0-a
WH
IM6-6
0-b
WH
IM6-0
-b
WH
IM16
-2
WH
IM16
-1
WH
IM2-2
WH
IM2-1
PCA plot (64.7%)
PC
2 (
23
.2%
)
PC1 (41.5%)
Proteolytic cleavage specificity for OvCa vs. BrCa
Fre
qu
en
cy
0
50
100
150
200
250
A C D E F G H I K L M N P Q R S T V W Y
P1_Down
P1_Up
0
500
1000
1500
2000
2500
A C D E F G H I K L M N P Q R S T V W Y
P1_Down
P1_Up
Fre
qu
en
cy
OvCa tumor peptidome PDX tumor human-
specific peptidome WHIM6-
0-a-1
WHIM6-
0-a-2
WHIM6-
0-a-3
WH
IM6-0
-a-1
WH
IM6-0
-a-2
WH
IM6-0
-a-3
WH
IM6-0
-b
WH
IM6-6
0-a
WH
IM6-6
0-b
WH
IM2-1
WH
IM2-2
WH
IM16
-1
WH
IM16
-2
WHIM6-0-a-1
WHIM6-0-a-2
WHIM6-0-a-3
WHIM6-60-a
WHIM6-0-b
WHIM6-60-b
WHIM2-1
WHIM2-2
WHIM16-1
WHIM16-2
WHIM6
WHIM16
WHIM2
0
1000
2000
3000
4000
5000
6000
7000
A-0 A-5 A-30 A-60 A-0 B-5 B-30 B-60 C-0 C-5 C-30 C-60 Total
Ide
ntified
pe
ptid
e n
um
be
r
Comparison between IQ and MS-Align+
IQ MS-Align+
Ide
ntified P
ep
tid
e n
um
ber
0
200
400
600
800
1000
1200
1400
1600
WH
IM6
-0-a
-1
WH
IM6
-0-a
-2
WH
IM6
-0-a
-3
WH
IM6
-60
-a
WH
IM6
-0-b
WH
IM6
-60
-b
WH
IM2
-1
WH
IM2
-2
WH
IM1
6-1
WH
IM1
6-2
OvC
a t
um
or
BrC
a P
DX
tu
mo
r • Total protein groups (IDPicker3): 974
• Total protein groups (IDPicker3): 824
Patient A:
960
928(95.4%)
Patient B:
956
Patient C:
950
Norm
aliz
ed
Fre
qu
en
cy
0
0.1
0.2
0.3
0.4
A C D E F G H I K L M N P Q R S T V W Y
N-terminus with Met cleaved
0
0.1
0.2
0.3
0.4
A D F H K M P R T W
N-terminus with Met
0
0.02
0.04
0.06
0.08
0.1
0.12
A C D E F G H I K L M N P Q R S T V W Y
C-terminus
Norm
aliz
ed
Fre
qu
en
cy
0
0.02
0.04
0.06
0.08
0.1
0.12
A C D E F G H I K L M N P Q R S T V W Y
Other N-terminal peptides
0
0.05
0.1
0.15
A C D E F G H I K L M N P Q R S T V W Y
C-terminus -1
0
0.02
0.04
0.06
0.08
0.1
A C D E F G H I K L M N P Q R S T V W Y
C-terminus-2
Norm
aliz
ed
Fre
qu
en
cy
0
0.02
0.04
0.06
0.08
0.1
A C D E F G H I K L M N P Q R S T V W Y
All peptidome peptides
Norm
aliz
ed
Fre
qu
en
cy
Analyses of N- and C- terminal cleavage specificities revealed
involvement of N-terminal Met Excision (NME) processing
Chymotrypsin and trypsin activities are the major
contributor to both peptidomes, suggesting the
involvement of proteasome-dependent pathway
• Significantly improved sensitivity
• Provides more accurate
quantification
• Better distinguishes overlapping
features
• Improves FDR and reduces
“missing data”
Solid lines : charge states chosen for MS/MS fragmentation
Dashed lines: charge states present but not chosen for
fragmentation
A. B.
