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Proteomic strategies for identifying resistance mechanisms and therapeutic targets
in lymphoma
Megan S. Lim MD PhDProfessor, Director of Hematopathology
Joint (HUP and CHOP)
GENERAL SESSION 3 May 10, 2019
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Disclosure
• No relevant items to disclose
• GENOMENON: Co-Founder and Advisor
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Patient
Genome Sequencing Proteome Profiling
Functional Screens
Gene Expression
Animal
ModelBiomarkers
Paradigm for Research
3
Metabolome Profiling
Pathobiologic events
Outline
• Discovery of novel targetable ALK-regulated cytokine network through integration of N-glycoproteomic and functional genomics
• Functional validation of novel target (IL31Rb) in ALCL
• Conclusions and broad applications for identifying novel CAR-T targets in de novo disease and resistance
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LC-MS/MS-based proteomics for definitive protein identification
Parent ion selected
MS scan
m/z, amu
Inte
nsit
y
Database
search
Protein ID
CIDMS/MS
m/z, amu
Inte
nsit
yDaughter ions
Peptides Liquid chromatography
Column SCX AND RP
MSSpray needle
Trypsin K/RLysine-C KGlutamic-C D/E
Proteinase K all
LC-MS/MS-based proteomics
Bioinformatics
• Unambiguously identify proteins
• Femtomolar sensitivity
• Unbiased
• Identify the precise site of apost-translational modification
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N-glycoproteomicsignatures of lymphoma
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7
N-Glycoproteins are excellent lymphoma biomarkers
• Glycosylation is a common post translational modification
• Glycoproteins are secreted or expressed in the cell surface
• Most CD markers recognize glycoproteins
• Good target for biomarker discovery
MembraneProteins
13,000 predicted TM proteins3100 membrane glycoproteins UniProt
417 CD molecules
S/TX
HypothesisGlycoproteins can be used as biomarkers for early
disease detection, diagnosis, monitoring and harnessed as a therapeutic target in lymphoma
Rational selection of candidates
Biomarkers Therapeutic targets
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Aims
• Compendia of glycoproteomic profiles for distinct lymphoma cell lines using LC-MS/MS
• Functional study of candidate glycoproteins
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WHO entities Lineage Origin N
T-ALL T Precursor T 1
ALCL, ALK + T Mature T 5
ALCL, ALK - T Mature T 2
MF T Mature T 1
Sézary syndrome T Mature T 1
Aggressive NK-cell leukemia NK Mature NK 3
MCL B Pre-GC 3
BL B GC 3
DLBCL B GC 1
PMBL B GC 2
FL B GC 6
Classical HL B GC 3
NLPHL B GC 1
Myeloma B Post-GC 4
Cysteine reduction/alkylation
Trypsin digestion
Validation and functional studies
Protein extraction
Solid-Phase Extraction of
Glycopeptides
LC-MS/MS
Data analysis
36 well-characterized human cell lines
14 subtypes of lymphoid neoplasia
Unbiased N-glycoproteomics of lymphoid neoplasia
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Glycoproteomic Profiling By Solid Phase Extraction of Glyoproteins (SPEG)
LC-MS/MS analysisPNGase F (N-glycosidase) : N-glycopeptides Alkaline b-elimination : O-glycopeptides
carbohydrate aldehyde
hydrazide resin
Modified from Nat Biotech 2003& Nat Protocol 2007 11
1
2
3
4Schwartz et al. (2005). Nature Biotech. v23(11):1391-1398.
- 1905 unique 11mers - N[115] in the center
Motif # Count Fold Inc.*
1 1080 8.88
2 59 25.87
3 703 10.37
4 24 19.89
Fold Inc. = Fold Increase over background sequence data
Consensus N-glycosylation motif analysis
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1
2
3
4Schwartz et al. (2005). Nature Biotech. v23(11):1391-1398.
- 1905 unique 11mers - N[115] in the center
Motif # Count Fold Inc.*
1 1080 8.88
2 59 25.87
3 703 10.37
4 24 19.89
Fold Inc. = Fold Increase over background sequence data
Consensus N-glycosylation motif analysis
NXT1080
NXS703
NXC24
YNXS59
(1.3%)(3.2%)
13
(57.8%)
(37.7%)
N-glycoproteins identified in 36 cell lines
439
715
528
426496
581663 681
508
641731 703
484
805
5296 63 53 61 77 102 94 71 88 101 93 77 93
0
200
400
600
800
1000 N-glycoproteinsCD markers
1155
Detection of virtually all CD proteins
currently used for diagnostic
evaluation of lymphoid neoplasia
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Classification of lineage and subtype
log2 (Raw Spectral Counts +1)
ALCL
BCL
FL
MCL
BL/FL
HL/PMBL
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T cell B cell
NHL HL
CD30(+) ALCL
T/NK cell lymphoma cell lines
NK cell lymphoma
ALK(+)ALK(-)
N-glycoproteomic profiles classify cell lines according to disease subtype
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ALK
ALK
Y Y YYJAK3 PI3K
AKTPDK
STAT3/5 PKCα
NPM
AUTOPHOSPHORYLATION
NPM
Apoptosis Proliferation ??
t(2;5)(p23;q35)
PLC
NPM-ALK+ ALCL as a biologic tumor model
for functional studies
Activation
Localization
Expression
CD30 ALK
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Leverage Integrative Large-Scale Data
Transcriptome and N-Glycoproteome
Cell nucleus
Ribosome
Protein
GT
C
Complementary
base pairmRNA
DNAU
A
Genomics(24,000)
Proteomics(1,000,000)
Transcriptomics(100,000)
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Solid-Phase
Extraction of N-
linked
glycopeptides
(SPEG)
LC-
MS/MS
ALK+ALCL
cell lines
DMSO
ALKi
Protein
extraction
RNA
extraction
DNA
extractionLentiviral
sgRNA
library
RNA-Seq
NGS
Functional
proteogenomics
Therapeutic
vulnerabilities
Investigation of ALK “regulome” by integrating N-glycoproteomics and functional genomics
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Integrated N-glycoproteomic and transcriptomic data
Cytokine/receptor signaling pathways are regulated by ALK activity in ALK+ALCL
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IL4R
A distinct cytokine-mediated protein network regulated by ALK
IL31Rb
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Protein-protein interaction networksusing ALK-dependent cytokine receptors
● IL2Ra (CD25)
● IL31Rb (Oncostatin M receptor)
T/NK-cell B-cell
DE
LS
UD
-HL-1
HH
Hu
t-7
8M
ac-1
Ma
c-2
A
Karp
as
299
SR
-78
6S
UP
-M2
JU
RK
AT
YT
NK
-92
NK
-92
MI
U-2
66
KM
S-1
2K
MS
-11
RP
MI 8
22
6F
L-5
18
DE
VK
arp
as
11
06
PN
CE
B-1
Gra
nta
519
Rec-1
FL-2
18
OC
I-Ly2
SU
D-H
L-4
BJA
-BR
am
os
OC
I-Ly1
Ra
jiF
L-1
8F
L-3
18
KM
H-2
Me
d-B
1L1236
L428
ALCL,ALK+
IL2RaIL31Rb
Potential novel biomarkers
Validation: A distinct cytokine signature is characteristic of ALK+ ALCL
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Oncostatin M Receptor (IL31Rb) in ALK+ ALCL
OSMR
gp1
30LI
FR
OSM
gp1
30O
SMR
OSM
200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300m/z05
101520253035404550556065707580859095
100
Rela
tive A
bundance
526.2
8
788.4
2
901.4
2
639.3
4
564.9
7
641.3
7648.8
0
613.3
8
413.3
4
527.3
6
902.4
1
301.1
7
586.4
1
509.2
2
360.3
1
414.2
5
1128.6
2
612.3
0
789.5
8
1014.7
0
556.1
0
657.5
7
1122.3
4
396.0
0386.1
4
468.1
1y3
y4
y5
y6 y7
y8y9b3
b4b5 b7
b8
y9+2
Position Sequence
176 NIQNN*VSCYLEGK
326 SVNILFN*LTHR
380 MMQYN*VSIK
491 ILFYNVVVENLDKPSSSELHSIPAPAN*STK
580 NVGPN*TTSTVISTDAFRPGVR
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IL31Rb
Co
u
nt
DEL Karpas 299 SR786 SU-DHL-1
SupM2 MAC2A Jurkat
8.75 2.16 2.46 4.76
13.7 1.02 1.02
L428
KM
H2
RA
JI
Ka
rpa
s 2
99
SU
-DH
L-1
HH
HU
T7
8
HT
108
0
YT
NK
-92M
I
BJA
B
DE
L
SR
786
MA
C2A
Ju
rka
t
Su
pM
2
MA
C1
HT
108
0GAPDH
IL31Rb
TonsilALK-,
IL31Rb-
ALK-,
IL31Rb+
ALK+,
IL31Rb+
IL31Rb + IL31Rb -
ALK + 21 0
ALK - 14 21
Χ2 = 20.16
p<0.001
ALCL, ALK+Cell lines 56 primary biopsies of ALCL
IL31Rb is expressed in ALK+ALCL
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IL31Rb and OSM expression is ALK-dependent and mediated via STAT3
ALK inhibitor
OSMR
p-ALK
ALK
β-actin
-3 h 22 h10 h6 h
+ - + - + - +-3 h 22 h10 h6 h
+ - + - + - + -3 h 22 h10 h6 h
+ - + - + - +
Karpas 299 SUD-HL-1 SR786
OSMR
p-STAT3
STAT3
β-actin
STAT3 inhibitor 0 50 100 200 -3 h 10 h6 h
+ - + - +
Karpas 299
OSM
p-ALK
ALK
β-actin
ALK inhibitor
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gp1
30LI
FR
OSM
gp1
30O
SMR
OSM
NPM-ALK regulates IL31Rb in a kinase dependent manner
Real time RT-PCR
*** P<0.001 by student T-test
n.s *** *** ****** ***
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LentiviralVector
Packaged Pooled Lentiviral sgRNA
LibraryBarcoded
Pooled Plasmid sgRNA Library
TransducedTarget Cells
Barcode Representation
Freq
uen
cy80-90% of Sequences Within 1 Order of Magnitude
Quantitative Identification of
Enriched or Depleted sgRNA Corresponding
to Gene Targets
BarcodedsgRNA
Amplification
Designs: sgRNAsgRNA expression: U6, U6-Tet, H1 or H1-TetMarkers: GFP, RFP, PuroR, Promoters: UbiC, EF1a, CMV
PCR & Cloning
Target CellTransduction
14, 250 sgRNAs
CRISPR-Cas9 sgRNA genome-wide vulnerabilityWeinstock D, Ngo S, Root, D
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Markov Chain Monte Carlo Simulation
IL6-STAT3 IL2-STAT5
Cytokine receptor pathways are exquisite vulnerability targets in ALK+ALCL
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Scra
mble
shR
NA
OS
MR
shR
NA
0
2 0
4 0
6 0
8 0
Pe
rce
nta
ge
of
tum
or
gro
wth
Scramble
shRNA
IL31Rb
shRNA
p <0.01
Pe
rcen
tage
of tu
mo
r gro
wth
IL31Rb knockdown abrogates tumor growth in ALK+ALCL xenotransplants
Scramble
shRNA
IL31Rb
shRNAIL31Rb
β-actin
WT
Scra
mb
le s
hR
NA
IL3
1R
bsh
RN
A
IL31Rb contributes to oncogenesis in ALK+ALCL
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• Largest compendium of N-glycoproteins in lymphoma
1,115 glycoproteins, including 198 CD markers
• N-glycoprotein signatures classify lymphoid neoplasia according to:
Lineage, Cell of origin, WHO subtypes
• Integrated N-glycoproteomics and transcriptomics are complementary
• A distinctive cytokine/receptor-JAK-STAT signaling network regulated by ALK
IL31Rb are pathogenetically-relevant vulnerable targets
Delphine Rolland
Conclusions and Implications
30Rolland D et al., Proc Natl Acad Sci, 2017
Model of OSM-OSMR signaling in ALCL and acquired resistance
Tumor microenvironment
NPM-ALK
OSMOSMR
gp130
gp130
STAT3
TT
Autocrine and paracrine promotion of
cell survival, proliferation
OSM
OSM
OSMOSMR
OSMR
gp130
Cell migration, invasion
Therapy resistance
31
OSMR is regulated by ALK in
EML4-ALK+ lung cancer and upregulated in
acquired resistance
0 1 2 3 4 5 6 7 8 9 1 0
0
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
1 0 0
C riz o t in ib ( M )
Pe
rce
nta
ge
of
co
ntr
ol
(DM
SO
)
H 3 1 2 2
H 3 1 2 2 c lo n e 2
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Sensitive
Resistant
SensitiveResistant
Sensitive
Resistant
Future DirectionsMechanisms and biomarkers of CAR-T therapy
resistance
33
5000-6000 proteins
35000 phosphopeptides
2500 phosphoproteins
LC-MS/MSIdentification and quantification of
phosphopeptides
ImmunoprecipitationThree pY specific antibodies
MOACTi-bead chromatography for phosphopeptide enrichment
(S/T/Y)
Peptide PreparationTrypsin-mediated cleavage
Cell CultureALCL cells treated +/- ALK inhibitor
N-GlycoproteomePhosphoproteome
U of Pennsylvania Delphine Rolland, Pharm D PhD
John Basappa PhD
Kaiyu Ma PhD
Ozlem Onder PhD
FundingNIH R01DE119249
NIH R01CA136905
NIH R01CA140806
NIH F31CA171373
COG Translational Award
COG Young Investigator Award
University of Michigan Cancer Center
University of Pennsylvania
Kojo SJ Elenitoba-Johnson MD
U of Michigan Scott McDonnell PhD
Venkatesha Basrur PhD
Kevin Conlon MS
Carla McNeal-Schwalm MD
Alexey Nesvizhskii PhD
Damian Fermin PhD
Noah Brown MD
Nathanael G Bailey, MD
Carlos Murga-Zamalloa MD
Steven Hwang BS
Mahmoud A ElAzzouny, PhD
Charles F Burant, MD., PhD
Lili Zhao, PhD
Gilbert S. Omenn MD
Seoul National University Yoon-Kyung Jeon MD PhD
Dana Farber CI /Broad David Weinstock MD
David Root PhD
Samuel Y. NG PhD
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