Proteomic strategies for identifying resistance mechanisms ...€¦ · Proteomic strategies for...

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Proteomic strategies for identifying resistance mechanisms and therapeutic targets in lymphoma Megan S. Lim MD PhD Professor, Director of Hematopathology Joint (HUP and CHOP) GENERAL SESSION 3 May 10, 2019 1

Transcript of Proteomic strategies for identifying resistance mechanisms ...€¦ · Proteomic strategies for...

Page 1: Proteomic strategies for identifying resistance mechanisms ...€¦ · Proteomic strategies for identifying resistance mechanisms and therapeutic targets in lymphoma Megan S. Lim

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

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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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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

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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

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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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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%)

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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

15

T cell B cell

NHL HL

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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

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A distinct cytokine-mediated protein network regulated by ALK

IL31Rb

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Protein-protein interaction networksusing ALK-dependent cytokine receptors

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● 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

25

gp1

30LI

FR

OSM

gp1

30O

SMR

OSM

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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

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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

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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

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Future DirectionsMechanisms and biomarkers of CAR-T therapy

resistance

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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

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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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