PTCL-NOS: Gene expression profiling Javeed Iqbal Department of - - PowerPoint PPT Presentation

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PTCL-NOS: Gene expression profiling Javeed Iqbal Department of - - PowerPoint PPT Presentation

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PTCL-NOS: Gene expression profiling Javeed Iqbal Department of Pathology and Microbiology James O. Armitage center for Leukemia and Lymphoma Research University of Nebraska Medical Center Omaha,NE T- cell Lymphomas: we are close to the

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PTCL-NOS: Gene expression profiling

T-cell Lymphomas: we are close to the finalization”

Javeed Iqbal Department of Pathology and Microbiology James O. Armitage center for Leukemia and Lymphoma Research University of Nebraska Medical Center Omaha,NE

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History of Lymphoma Classification

1956 1974 1982 1988 1998 2001

Rappaport Luke & Collins Kiel classification Kiel classification/u pdate Working Formulation

W.H.O Classification

REAL Classification NCI 2008 2016 Morphology/ Clinical + Immunohistochemistry

+ Cytogenetics, FISH + Molecular Biology

+ Gene Expression Profiles + Next Generation Sequencing

Classification project-1999

Nebraska

Transcriptomics Genomics

PTCL entities

~19 ~25 ~30

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University of Nebraska Medical Center

Molecular diagnosis Pathobiology and target characterization Rationalize/Justify the new clinical investigations

Gene Signatures in PTCL

  • The genomic characteristics of each tumor through

expression of a unique set of genes is known as “GENE SIGNATURE

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CLP DN1 DN4 DP CD8 CD4 CD8 γδ TFH TH1 T REG HSC CD4 Thymus Periphery Bone Marrow Cytotoxic T TBX21 BCL6 FOXP3 IFN-γ IL4 IL5 IL13 IL21 CXCL13 IL10 TGF-β STAT5 Helper T Cortex Medulla CD4+ CD8+ DN2 DN3 CD44+ CD25- CD44+ CD25+ CD44- CD25+ CD44- CD25- Pre-TCRβ Dependent TCRα Rearrangements TCRβ Rearrangements CD4-CD8- NOTCH IL7 γδ TH2 GATA3 MHC Class I MHC Class II CD24

Mature T cell development and activation

Complexity of T-cell immunobiology, numerous subsets and functional plasticity makes disease classification challenging

HSC: Hematopoietic stem cells CLP: common lymphoid progenitor

-selection phase repertoire selection phase

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W.H.O. classification of mature T/NK-cell neoplasms (2016 revised version)

Cutaneous Extra-nodal Nodal Leukemic

adapted from Swerdlow SH et al. Blood 2016 127:2375-2390)

Peripheral T-cell Lymphoma, Not Otherwise Specified PTCL-NOS Anaplastic large-cell lymphoma, ALK(+)ALCL Angioimmunoblastic T-cell lymphoma AITL Follicular PTCL Anaplastic large-cell lymphoma, ALK(-) ALCL

Nodal PTCL with TFH phenotype

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PTCL-NOS 30% AITL 22%

ALK-ALCL 7%

ENKTCL 12%

ALK+ ALCL 8%

ATLL 11% HSTL 2% EATL 5%

Others 3%

Overall frequency of PTCL subtypes

Park, S. & Ko, Y.H. Int J Hematol (2014) Scott V. Adams et.al J Clin Oncol. 2016; 34: 963–971 Vose et.al J Clin Oncol. 2008, 26:4124–4130

36% France

20% Asia 38% USA

Scott V. Adams et.al J Clin Oncol. 2016 Laurent et.al J Clin Oncol. 2017 Park et. al Int J Hem 2014

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Major PTCL subtypes have inferior clinical outcome

Proportion

Test: p<0.001

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Diagnosis Adult T-cell leuk/lymph (ATLL) Anaplastic large cell lymphoma, ALK- Anaplastic large cell lymphoma, ALK+

Angioimmunoblastic T-cell lymphoma Peripheral T-cell lymphoma, NOS

Generic NK-cell

  • Xu et.al PLOS One 2014

“No Survival Improvement for PTCL/AITL patients over the Past Two Decades: A Population-Based Study of 1207 Cases”

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University of Nebraska Medical Center

No major improvement in clinical outcome since last three decades in PTCL

OS of PTCL-NOS/AITL

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Dissecting out

High-through put technologies dissecting distinct molecular and prognostic subgroups

Gene expression profiling: (mRNA expression)

Genetic Evolution of molecular subgroups

Genomic DNA hybridization (DNA copy number variations) Patient-centered Research

Laboratory discoveries Delivery to patient care /communities

Next generation sequencing

Transcriptomics Genomics

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University of Nebraska Medical Center

Unsupervised hierarchical clustering of PTCL cases and normal T cells

Blood 2010;115:1026-1036

Major entities of PTCL form tight clusters with cases of PTCL-NOS and other rare entities interspersed.

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Blood 2010;115:1026-1036

Gene expression-based molecular predictors of the major subgroups of PTCL

  • More than half of the PTCL-NOS cases were not molecularly classified

International PTCL Project

AITL ATLL ALK+ALCL

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Dendrogram for clustering PTCL-NOS cases using centered correlation and complete linkage CT-PTCL Correlation Other PTCL-U Other PTCL-U

(A) Hierarchal clustering (C) GSEA analysis

IFN responsive genes CD8+ T-cell gene signature P<0.01 P<0.005

(E) Granzyme B expression by immunohistochemistry in CT-PTCL

H & E Granzyme B Proportion

Years Years (D) Survival of the CT-PTCL group

CT-PTCL PTCL-NOS

p=0.05 OS

Proportion CT-PTCL PTCL-NOS

p=0.06 EFS

Hours after stimulation

(B) Expression of the CT-PTCL signature in normal CD8+ T-cells stimulated with anti-CD3, anti-CD28 and IL12 for various time intervals (hours)

CD8+ T-cell 0 2 8 24 48

Identification of cytotoxic () PTCL group from PTCL- NOS

Blood 2010;115:1026-1036

International peripheral T-cell lymphoma Project

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HSTCL

NKCL / -PTCL NK- /  T-cell lines CT(α)-PTCL T-cell lines

Identification of -PTCL from PTCL-NOS

H &E

TCR-

Markers

Status

CD3

7/7 (+)

CD2

2/4 (+)

CD5

1/7 (+)

CD7

1/1 (+)

CD8

3/5 (+)

CD4

1/6 (+)

CD56

3/4 (+)

TIA1

4/4 (+)

Granzyme B

2/3 (+)

TCR-beta

5/5 (-)

EBER-1

3/5 (-)

OS of PTCL -PTCL have similar gene expression signature as NKCL but distinct from CT(α)- PTCL and HSTCL

  • Leukemia. 2011 Feb;25(2):348-58.
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Refinement of molecular diagnostic signatures

  • Unique molecular signatures were identified for major PTCL entities
  • Blood. 2014 May 8;123(19):2915-23.

Lymphoma and Leukemia Molecular Profiling Project (LLMPP) initiative

Blood 2014

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Gene signature/pathway enrichment summary in ALK(-)ALCL

  • ALK(-) ALCL is molecularly distinct from PTCL-NOS and ALK(+)ALCL

Re-classified from PTCL-NOS

ALK ALK

ALK(+) ALCL ALK(-) ALCL PTCL-NOS

  • Blood. 2014 May 8;123(19):2915-23.

Robust molecular signature for ALK(-)ALCL

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STAT3 and STAT5B mutations identified in NK or γδ-T cell derived lymphomas

  • Stat3 and Stat5B are often mutated at the SH2 domain in NK and γδ-T cell lymphomas
  • In vitro data analysis showed sensitivity of this mutations to JAK1/2 inhibition

Nat Commun. 2015 Jan 14;6:6025.

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Evaluation of pathological vs molecular diagnosis

  • Blood. 2014 May 8;123(19):2915-23.
  • f 152 PTCL-NOS cases, a subset of cases were classified

into unique PTCL entities

AITL PTCL-NOS

14% 20% n=152 n=117 Infrequent IDH2 mutation 1 of 17 33% IDH2 mutation

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₋ AITL ₋ ATLL ₋ ALK(-)ALCL ₋ ALK(+)ALCL ₋ NKCL ₋ -PTCL

n=251

n=121 32% PTCL-NOS

One-third of PTCL-NOS cases were not molecularly classified into WHO recognized PTCL entities

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Cluster1 Cluster 2 cluster3

GATA3 CCR4

TBX21 CXCR3 STAT1 EOMES 121 PTCL-NOS

(a)

Ig signature

TBX21 (mRNA)

Gata3 (mRNA)

(c) (b)

Unsupervised clustering of PTCL-NOS showed at least 3 major clusters

Years

proportion

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GATA3 Unclassifiable TBX21 37 0.9 20 1.41 49 2.08 n median OS (years) Time (years)

Proportion (OS)

p=0.01

(B)

PTCL-NOS can be further divided two major subgroups

(A)

Probability (LOOCV) TBX21 GATA3 Probability in TBX21 subgroup Probability in GATA3 subgroup

TBX21 Unclassifiable GATA3

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GEP identified distinct oncogenic pathways

(a)

GATA3 TBX21

-catenin oncogenic signature Proliferation MYC targets NF-B target gene signature Plasma cell gene signature INF- gene signature

IHC validation

PI3Kinase regulated Myc induced gene targets (up) Ribosomal transcripts (mTOR) Proliferation related

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p=0.2 p=0.05

Quartile

(D)

H&E CD3 TIA1

(B)

TIA1 H&E CD3

(C)

Proportion Time (years) Time (years)

Cytotoxic Pan-B plasma-cell Immunoglobulin

signature

Q1 Q2 Q3 Q4 Q4 Q1+Q2+Q3

OS in TBX21 subgroup OS in TBX21 subgroup

Q1 Q2 Q3 Q4

Tumor microenvironment significantly influences the prognosis in PTCL-TBX21 subgroup

  • Blood. 2014 May 8;123(19):2915-23.
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APC CD4

CD3 CD3 TCR /

JAK2 TYK2

IL-12R

JAK1 JAK2

IFNR

IL12

IFN

MHCII

STAT1 STAT4 TBX21 EOMES

Cellular immunity Inflammation

NOTCH3

DLL1/4

APC CD4

CD3 CD3 TCR/

JAK1 JAK3

IL-2R

JAK1 JAK3

IL4R

IL2

IL4

MHCII

STAT6 STAT5 GATA3 C-MAF

Humoral immunity Abs production

NOTCH 1/2

Jagged1/2

TH1/2 differentiation ProgramSchematic TH2 TH1

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University of Nebraska Medical Center

Schematic of the Gene Expression and Dosage Integration algorithm

Proc Natl Acad Sci U S A. 2008 Sep 9; 105(36): 13520–13525.

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  • Major Subgroups within PTCL-NOS characterized

by distinct genomic abnormalities

PTCL-TBX21

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CN Abnormalities Associating with Overall Survival

TP53 CDKN2A MYC

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Novel PTCL subgroups have distinct Chromosomal Abnormalities

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  • Unique Mutation Profiles in molecular subgroups
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University of Nebraska Medical Center

Distinct spectrum of DNMT3A mutations

PTCL-TBX21 AITL

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University of Nebraska Medical Center

The complexity of PTCL can finally be addressed with the integration of global genomic analyses, which demonstrated that molecularly defined subgroups of PTCL have diverse genetic features and arise by distinct genetic pathways.

Summary

  • Tet2
  • DNMT3A

AITL

RHOAG17V IDH2R172 ++ Chr5/21

GC reaction

14q (BCL11B) +Chr 3 gain

Epigenetic Changes Genomic copy number changes

PTCL-GATA3

PTCL-TBX21

CDKN2A-TP53 PTEN-PI3K AMPK-mTOR

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University of Nebraska Medical Center

Translate Gene Signatures into clinical settings applicable to FFPE

  • Immunohistochemistry based algorithm
  • Quantitative mRNA based assay
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Translation using Immunohistochemistry

Amador et. al, USCAP 2018 Unpublished

Validation Cohort

n=150 PTCL-NOS

PTCL-NOS subgroups

c c

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University of Nebraska Medical Center

Translating gene signatures for NanoString platform

Refinement of gene signature algorithm

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AITL_3__FFPE_R1

5 10 15 4 8 12

0.84

***

4 8 12 5 10 15

AITL_3__FF_R1

Correlation of gene signatures between Fresh frozen RNA and corresponding FFPE RNA on nCounter platform

ALCL.neg_2__FFPE_R2

2 6 10 14 5 10 15

0.89

***

5 10 15 2 6 10 14

ALCL.neg_2__FF_R2 ALCL.pos_5__FFPE_R2

5 10 15 5 10 15

0.88

***

5 10 15 5 10 15

ALCL.pos_5__FF_R2 TCL.GATA3_8__FFPE_R

5 10 15 5 10 15

0.93

***

5 10 15 5 10 15

PTCL.GATA3_8__FF_R2 TCL.TBX21_10__FFPE_R

5 10 15 5 10 15

0.90

***

5 10 15 5 10 15

PTCL.TBX21_10__FF_R TCL.TBX21_12__FFPE_R

4 8 12 2 6 10 14

0.84

***

2 6 10 14 4 8 12

PTCL.TBX21_12__FF_R

FFPE RNA FF RNA

100ng of RNA was run for all FF samples

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SLIDE 35

University of Nebraska Medical Center

AITL ALCL PTCL-GATA3 PTCL-TBX21

mRNA code set on nCounter NanoString platform

AITL ALCL PTCL-GATA3 PTCL-TBX21 mRNA diagnostic signature

Molecular diagnostic algorithm for FFPE PTCL entities

Digital algorithm Diagnostic signature score PTCL entities FFPE cases Average expression (n= 4 4 6 6 AITL ALCL PTCL-GATA3 PTCL-TBX21

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Genetically faithful model of PTCL-GATA3

H&E of different organs of a mouse implanted with a primary PTCL-NOS

CNA analysis in PTCL entities Developing PDX models of PTCL-NOS Generating Murine models

  • A. Loss of Pten/Trp53 (double(d)-

KO) in CD4+T-cells induces T- cell proliferation in mice

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TCRα TCRβ CD3δ CD3ε CD3ε CD3γ

CD3ζ

CD3ζ

CD28 CD28 CD4/CD8

MHC MHC

Ag

JAK/STAT

Cytokine Receptor Cytokine Receptor Cytokine

SOS GRB2 LAT SLP76

LCK ZAP-70 PI3K AKT mTOR

VAV NCK GADS ITK PLCγ1 IP3 PIP2 RAS DAG MALT1 Bcl10 CARMA1 PKCθ IKKβ IKKγ IKKα TAK1 MKK7 JNK2 NFκB IκB FOS JUN NFκB NFAT IκB Degraded RAF MEK1/2 ERK1/2

Calcium Channel Ca2+ Ca2+ CaM Calcineurin CaMKIV CREB NFAT NFAT

IP3R Intracellular Ca2+ Store MKK3/6 MKK4/7 p38 JNK MEKK1 NFκB Rac/cdc42

PIP3

PTCL-NOS GATA3: constitutively active PI3K and mTOR pathways PTCL-NOS TBX21: constitutively active NFκB and STAT3 pathways ALK-ALCL: enriched mTOR pathway signatures ALK-ALCL: constitutively active JAK/STAT3 pathway

NK/T-cell lymphoma: activation of NFκB and JAK/STAT3 pathways

HSTL: high frequency STAT3 mutation Molecularly defined AITL:

  • ncogenic pathways NFκB, TGFβ

and IL-6 signaling identified

Temsirolimus Everolimus Bortezomib Ruxolitinib STAT3

Integrating new genomic information for targeted therapy in PCTL

Blood reviews, 2016

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Acknowledgements

Alyssa Bouska Tayla Heavican Waseem Lone Jiayu Yu Catalina Amador Keenan Hartet Sneha R.

Chan Laboratory Wing C. Chan Timothy McKeithan Yuping Liu Pileri Laboratory Stefano Pileri Maria Antonella Laginestra National Cancer Centre Singapore Maarja-Liisa Nairismägi Soon Thye Lim Choon Kiat Ong Weill Cornell Medicine/ Cornell University Giorgio Inghirami Fu Laboratory Kai Fu Andy Bi

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Nebraska Medical Center

  • Catalina Amador
  • Timothy Greiner
  • Kai Fu
  • Julia Vose
  • James Armitage
  • Martin Bast
  • Lynette Smith

ACKNOWLEDGEMENT

  • International PTCL Project
  • LLMPP consortium members
  • City of Hope Medical Center

—John Chan —Dennis Weisenburger —Timothy Mckeithan

  • NCI-NIH

— Lou Staudt — George Wright — Elaine S. Jaffe

 Nebraska Medical Center Research support

Funding Support

 Clinical and Translation Research Program – UNMC  Eppley cancer Center Support  PTCL-SPORE  UH2/UH3  STTR