“Clasificación de la OMS de las neoplasias linfoides”

LINFOMA DE HODGKIN XXXVI Reunión Anual de la SEAP-IAP

Juan F. García

Hodgkin T: Med Chi Trans 1832; 17:69-114.

Hodgkin´s Lymphoma in 1930 S. Ramón y Cajal (1852-1934) Textbook of Pathology

Nobel Laureate for Medicine, 1906

By courtesy of Dr. C. Llorente. Hospital de Alcorcon, Madrid

Hodgkin’s Lymphoma

Two diseases

Nodular lymphocyte predominant Hodgkin’s Lymphoma

Classical Hodgkin’s Lymphoma

•Nodular sclerosis HL

•Lymphocyte-rich classical HL

•Mixed cellularity HL

•Lymphocyte depletion HL

NLPHL

• Cell origin: CG B-lymphocytes

Clinical features

• Rare (<10%). Child and young adults

• Localized stages

• Indolent clinical outcome

• Some cases can progress/transform to

diffuse large B-cell lymphoma (frequently with

TCRBCL-like morphology)

Pathology

• Nodular pattern

• Tumor cells: L&H, with similar phenotype to

normal GC B-lymphocytes (CD20+, CD79a+,

Bcl6+, OCT2+, PAX5+, Ig+, Bcl2-,...)

• EMA+, CD30-, CD15-

• Background: nodules of small B-lymphocytes

(IgD+) and CD57+, PD1+ T-lymphocytes.

• Not associated with EBV

Classic HL

• Cell origin: CG B-lymphocytes

Clinical features

• Any age (peaks of incidence on the 2nd and

5th decade)

• Any stages

• Highly aggressive tumor, characterized by fatal

outcome without treatment

• Exceedingly rare histological transformation

Pathology

• Different histological patterns

• Tumor cells: H&RS, without expression of

characteristic markers of B-cells

• PAX5+, CD30+, CD15+

• Background: polymorphous: T-lymphocytes,

eosinophils, macrophages, fibroblasts, plasma

cells, mast cells, dendritic cells,...

• EBV: 40-70%

Nodular lymphocyte

predominant HL

L&H cells

BCL6 EMA

CD20 CD20

OCT2

PD-1

Characteristic

background of

germinal center

T-helper cells

rosetting the

tumor LH cells

CD4+, CD57+,

PD1+, …

NLPHL differential diagnosis:

T-cell/histiocyte-rich large B-cell lymphoma

• TCRLBCL: tumor cell content is dramatically

outnumbered by reactive T cells or (less often)

histiocytes,

• TCRLBCL usually presents as:

– Advanced stage

– Multiple lymphadenopaty

– Severe systemic disease with B-symptoms and

frequent hepatosplenomegaly, and follows a more

aggressive course than NLPHL.

Fraga M, et al. Histopathology. 2002;41(3):216-29.

NLPHL vs. TCRLBCL

Classical Hodgkin Lymphoma

• Lymphoid malignancy in which tumor (H/RS)

cells usually represent a minor population

(<5%) within the affected tissue, whereas the

majority of the malignancy is composed of

benign B- and T-lymphocytes, eosinophils,

macrophages, fibroblasts, plasma cells, mast

cells, dendritic cells, ...

• Origin: GC B-lymphocytes

• Phenotype:

•CD20-/+, CD79a-, Bcl6-, Igs-, OCT2-/+

•PAX5+, MUM1+, Bcl2+ (30-40%)

•CD30+, CD15+ (70-80%), EBV(LMP1)+ (40-70%)

• Genetics:

•Rearranged and somatically mutated Ig genes

•Gains of 9p and 2p

CD30

CD30

> 90%

CD15

70-80%

CD20

CD79a

PAX5

EBV

LMP1

• Brink AA, et al. Mod Pathol

1998;11:376.

• van Spronsen DJ, et al.

Histopathology 2000;37:420.

• Rassidakis GZ, et al. Blood

2002;100:3935

• Garcia, et al. Blood

2003;101(2):681

p=0,0026

BCL2+

BCL2-

BCL2 expression in

classical HL is an adverse

prognostic marker

Subtype Neoplastic

cellularity

Reactive background Fibrosis

%

NS

• Variable number

of H&RS cells

• Lacunar cells

• T-lymphocytes,

numerous

eosinophils

• Abundant

• Broad collagen

bands that

surround

nodules

50-70%

MC

• Many H&RS cells

and variants

• Mummy cells

• Heterogeneous:

histiocytes,

eosinophils,

neutrophils, plasma

cells,…

• Absent or

interstitial

20-40%

LRCHL

• Low number of

classical H&RS

and mononuclear

variants

• Nodules of mature

B-lymphocytes

• Histiocytes

• Can exist

<5%

LD

• Abundant and

pleomorphic

• Poor

• Absent or

diffuse fibrosis <5%

Nodular Sclerosis HL

• Young females

• Mediastinum

• Usually EBV-

NS HL

H&RS + lacunar cells

CD30

Mixed Cellularity HL

• Males>Females

• Localized or

disseminated disease

• More frequent EBV+

• More frequent in

immunodeficiency

MC HL

Mummy cell

EBV LMP1

Lymphocyte Rich

Classical HL

• Rare

• Usually stages I&II

disease

• Less aggressive

• EBV-/+

• Differential diagnosis

with NLPHL

LRCHL

LRCHL CD20

CD30

EBV

LMP1

Lymphocyte depleted HL

• Males>Females

• Localized or

disseminated disease

• More frequent EBV+

• More frequent in

immunodeficiency

Classical HL, differential diagnosis

HRS cells (with characteristic morphological features

and phenotype) can be occasionally found in NHL:

• T-cell lymphomas (in particular AITCL)

• Small B-cell lymphomas: B-CLL, rare FCL and MZL

Neoplastic vs. reactive background !!!

Phenotype

CD20 CD79a OCT2 PAX5 MUM1 BCL2 BCL6 CD30 CD15 EBV

HL -/+ - -/+ + + -/+ - + +/- 30-70%

LMP1+

DLBCL + + + + -/+ +/- + -+ - 10-15%

LMP1-

Differential diagnosis: classical HL vs NLPHL

Phenotype

CD20 CD79a OCT2 PAX5 MUM1 EMA CD30 CD15 EBV (LMP)

Classical

HL -/+ - -/+ + + -/+ + +/- 30-40%

NLPHL + + + + -/+ + - - -

Differential diagnosis: classical HL vs DLBCL

• The term “Gray Zone Lymphoma” was firstly used in 1998 at the

“Workshop on Hodgkin's disease and related diseases” to

designate lymphomas at the border of cHL and other entities.

• Cases with morphological and immunophenotypic features

transitional between PMBCL and cHL (NS) have been reported.

• There are composite (cHL and PMBCL at the time of diagnosis)

or sequential/metachronous lymphomas (cHL following a

diagnosis of PMBCL or viceversa).

The updated 2008 WHO classification of Tumours of

the Hematopoietic and Lymphoid Tissues has

addressed this problem by creation of the new

provisional category:

“B-cell lymphoma unclassifiable, with features

intermediate between diffuse large B-cell lymphoma

and classical Hodgkin lymphoma”

Classical Hodgkin Lymphoma

• Origin: GC B-lymphocytes

• Defective transcription of Ig genes (crippling mutations,

deficit of transcription factors, epigenetic deregulation,…)

• Normal GC B-lymphocytes that do not express

functional Igs are rapidly eliminated by CD95/FAS-

mediated apoptosis

Survival mechanisms of the H/RS cells:

• NF-kappaB activation (CD30 signaling, LMP1 [EBV], JAK/STAT

signaling, IkBa mutations, REL (2p) amplifications, ...)

• Deregulation of cell cycle and apoptosis mechanisms: p53, Rb,

CDKis, Cyclins (B1, D2, D3, E), c-FLIP, Bcl-2, Bcl-xl, c-IAP2,

XIAP,…

• Immune evasion/regulation through aberrant production of

cytokines and chemokines HL characteristic microenviroment

5 well characterized HL-derived

cell lines

L540

L428

HDLM2

KMH2

L1236

Two independent cultures from

each cell line

Gene expression profile of

Hodgkin Lymphoma cell lines

B-cells (CD77+, centroblasts)

isolated from reactive tonsils

Gene expression profile of Hodgkin’s Lymphoma cell lines:

Inactivation of B-cell receptor signaling and B-cell differentiation program

BCL6 FOS

IRF4

B-CELL RECEPTOR

CD19

CD20

CD22

CD79A CD79B

CD10

MHC class II

CD40 CD40

BRDG1

HCLS1

TNFRSF17

(B-cell maturation factor)

LYN

SYK

PKC

VAV

BTK

Transcription factors

FOS

FOXO1A

MAFB

FOSL2

ATF3

Interleukins-growth factors and receptors

TNFSF8 (CD30L)

IL7

IL8RA

IL16

LTB

PDGFD

TNFRSF8 (CD30)

IL13RA1

IL1A

IL1RAPL1

IGF1

Signal transduction

PRKA

PRKCs

PI3KCD

PRKG

CAMK4

PI3KCG

Gene expression profile of Hodgkin’s Lymphoma cell lines

Cell cycle, checkpoints, apoptosis

TP53INP1

cyclin G2

GADD45B

ATM

POLD4

BTG1

CASP5

P73L (p63)

BCL2

GAS1

GADD45G

• Primary HRS cells differ extensively from the usually studied cHL cell lines,

• Lost of B-cell identity is not linked to the acquisition of a plasma cell-like

gene expression program,

• EBV infection of HRS cells has a minor transcriptional influence

Two molecular

subgroups of cHL

associated with

differential strengths

of the transcription

factor activity of the

NOTCH1, MYC, and

IRF4 proto-oncogenes.

HL is a tumor characterized by the microenvironment

Chemical cross-

talk between H/RS

cells and the

microenvironment

Steidl, et al. J Clin Oncol

2012;29:1812

Steidl, et al. J Clin Oncol

2012;29:1812

Pathway activation in

HRS cells through

signaling from the

Microenvironment

Hodgkin Lymphoma: role of T cells in the microenvironment

Alvaro T, et al. Outcome in Hodgkin's lymphoma can be predicted

from the presence of accompanying cytotoxic and regulatory T

cells. Clin Cancer Res 2005. 11(4):1467-73.

Comparison of survival time (OS, EFS, DFS) according to TIA-1+ cells and FoxP3+:

(a) tumor infiltrate with a low level of TIA-1+ cells and a high level of FoxP3+ cells,

(b) tumor infiltrate with a high level of TIA-1+ cells and a low level of FoxP3+ cells,

(c) tumor infiltrate with intermediate levels of TIA-1+ and FoxP3+ cells.

CLUSTER 1

Immune response

CLUSTER 2

Extracellular matrix

Adhesion

Cell-cell signalling

CLUSTER 3

Cell cycle

Apoptosis

Signal transduction

CLUSTER 4

Cell cycle

CD8B1

CD3D

SH2D1A

ITM2A

ALDH1A1

LYZ

STAT1

MAD2L1

CDC2

CHEK1

STK6

TOP2A

PCNA

RRM2

TYMS

CYCS

CASP14

PDCD10

STK17A

PRKACB

PPP1CA

RAB27A

CDH1

FZD4

CR1

CCL26

HLA-DRB3

PTGS1

HSPG2

TIMP4

Hierarchical clustering of genes

associated with treatment response Good response

Poor response

HL tumors

Results _ Genes and pathways associated with treatment response.

Sánchez-Espiridión et al. Clin Cancer Res. 2009 Feb 15;15(4):1367-75.

Univariate Logistic regression analysis of genes included in the assay

Gene Name p value Hazard Ratio (95% CI) Pathway

BCL2 0.000 1.191 (1.089- 1.303) Apoptosis

CCNA2 0.000 1.243 (1.137- 1.358) CellCycle

CDC2 0.000 1.123 (1.052- 1.199) CellCycle

HMMR 0.000 1.160 (1.082- 1.243) CellCycle

LYZ 0.000 0.800 (0.738- 0.866) Monocyte

STAT1 0.000 0.810 (0.748- 0.878) Monocyte

BCL2L1 0.001 0.836 (0.751- 0.931) Apoptosis

CCNE2 0.001 1.152 (1.057- 1.255) CellCycle

CENPF 0.005 1.148 ( 1.041- 1.265) CellCycle

CASP3 0.014 1.104 (1.020- 1.194) Apoptosis

IRF4 0.020 0.872 (0.777- 0.978) IRF4

262 out of 282 samples succesfully analyzed ( 92,90% )

Genes from functional pathways underlying cHL resistance used to derive the Molecular Risk Score algorithm

Panel of 11 genes and Molecular Risk Algorithm

Group variables used in a multivariate logistic regression model able to predict treatment response

Blood 2010;116(8)

Beatriz Sanchez-Espiridion, et al. A molecular risk score based on

four functional pathways for advanced classical Hodgkin lymphoma

MOLECULAR RISK SCORE

Logistic regression model including the best genes is able to predict treatment response and

used to derived a Molecular Risk Score for each patient

Identification of patients with

different clinical course :

Failure free survival (FFS)

Blood 2010;116(8)

Beatriz Sanchez-Espiridion, et al. A molecular risk score based on

four functional pathways for advanced classical Hodgkin lymphoma

FFS (Integrated Molecular Risk + StageIV)

Integrated Model ( Molecular Risk Score + Stage IV)

0 50 1000

20

40

60

80

100

1st quartile

2nd quartile

3rd quartile

4th quartile

P value < 0.0001

FFSc

Perc

en

t su

rviv

al

A. International Prognostic Score Multivariate Cox Regression Analysis and

Molecular Risk Algorithm ( N= 262)

p value Hazard Ratio ( 95 % CI)

Molecular Risk Score 0.000 31.190 ( 7.885- 123.375)

Hemoglobin (<10.5g/dl) 0.649 1.126 (0.675- 1.878)

Albumin (<4g/dl) 0.724 1.085 ( 0.691 - 1.704)

Leucocytosis (≥ 15.000/mm3) 0.241 1.338 (0.822 - 2.175)

Linfopenia( < 600/mm3) 0.232 0.649 (0.319 - 1.319)

Age ( ≥ 45 yr) 0.452 1.194 (0.752 - 1.895)

Stage IV 0.066 1.516 (0.972 - 2.363)

Gender (=Male) 0.328 0.800 (0.512 - 1.251)

B. International Prognostic Score Cox Regression Analysis and Molecular Risk

Algorithm ( N= 262) Backward stepwise selection

p value Hazard Ratio

Molecular Risk Score 0.000 24.080 ( 6.133 - 94.552)

Stage IV 0.047 1.548 (1.006 - 2.381)

Blood 2010;116(8)

Beatriz Sanchez-Espiridion, et al. A molecular risk score based on

four functional pathways for advanced classical Hodgkin lymphoma

CD68

• We analyzed four TAM markers (CD68, CD163 [as a marker for M2

macrophages], LYZ, and STAT1) using IHC and automated

quantification, in two independent series of advanced cHL (266

and 103 patients, respectively).

• Survival analyses did not show consistent correlation between

CD163, LYZ, and STAT1 and failure-free or disease-specific

survival.

• There was an association between CD68 and disease-specific

survival, but it was not consistent in both series.

CD68 (PGM1)

CD68 (KP1 clone)

Spain Houston

Cutoff point FFS DSS FFS DSS

Median 0.333 0.000* 0.400 0.661

Q4 (75%) 0.100 0.000* 0.563 0.517

5% 0.288 0.047* 0.898 0.866

25% 0.146 0.000* 0.501 0.768

CD163

Spain Houston

Cutoff point FFS DSS FFS DSS

Median 0.058 0.320 0.242 0.169

Q4 (75%) 0.037 0.218 0.437 0.350

5% 0.318 0.074 0.933 0.654

25% 0.064 0.211 0.124 0.076

CD68 ( PGM1 clone)

Spain Houston

Cutoff point FFS DSS FFS DSS

Median 0.850 0.068 0.156 0.529

Q4 (75%) 0.686 0.026* 0.300 0.779

5% 0.457 0.052 0.397 0.262

25% 0.884 0.131 0.423 0.639

STAT1

Spain Houston

Cutoff point FFS DSS FFS DSS

Median 0.280 0.840 0.622 0.065

Q4 (75%) 0.800 0.892 0.639 0.005*

5% 0.492 0.957 0.893 0.986

25% 0.178 0.520 0.938 0.078

LYZ

Spain Houston

Cutoff point FFS DSS FFS DSS

Median 0.437 0.028* 0.621 0.908

Q4 (75%) 0.565 0.071 0.178 0.573

5% 0.402 0.242 0.107 0.382

25% 0.397 0.020** 0.465 0.931

IHC TAM markers (CD68, CD163, LYZ, and STAT1) in

independent series of advanced cHL

“Polarization” patterns of immune response can be

related with treatment response in cHL

B

M2

T cytotoxic

Plasmacytoid

DC IL11

IL20

IL3

CCL26

T NK

Unfavorable outcome Favorable outcome

TH2

M1 TH1

Treg

54

MADRID

Hospital 12 de Octubre

Hospital Clínico de San Carlos

Hospital Gregorio Marañón

Hospital La Paz

Hospital Ramón y Cajal

Hospital de Móstoles

Hosp. Severo Ochoa, Leganés

Hospital de la Princesa

Fundación Jimenez Diaz

MD Anderson Cancer Center

GALICIA

Complejo Hosp. de Vigo

Hospital Clínico de Santiago

CASTILLA y LEÓN

Hospital Clínico de Salamanca

ANDALUCIA

Hosp. Virgen del Rocio

Hospital N.S. de Valme

CANARIAS

Hosp. Universitario de Canarias

CASTILLA–LA MANCHA

Hosp. Virgen de la Salud

MURCIA

Hospital Virgen de la Arrixaca

CENTRO NACIONAL

Centro Nacional de Investigaciones Oncológicas

BALEARES

Hospital Son Dureta

CATALUÑA

Hospital del Mar Hospital Vall d'Hebron

PAIS VASCO

Hospital de Cruces

CANTABRIA

Hosp. Marqués de Valdecilla

ASTURIAS

Hospital Central de Asturias

Hospital de Cabueñes

Hospital Virgen del Nalón

The Spanish Hodgkin’s Lymphoma Study Group