presentación de powerpoint - sociedad española de ... · s. ramón y cajal (1852-1934) textbook...
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“Clasificación de la OMS de las neoplasias linfoides”
LINFOMA DE HODGKIN XXXVI Reunión Anual de la SEAP-IAP
Juan F. García
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Hodgkin T: Med Chi Trans 1832; 17:69-114.
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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
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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
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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%
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Nodular lymphocyte
predominant HL
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L&H cells
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BCL6 EMA
CD20 CD20
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OCT2
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PD-1
Characteristic
background of
germinal center
T-helper cells
rosetting the
tumor LH cells
CD4+, CD57+,
PD1+, …
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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.
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NLPHL vs. TCRLBCL
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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
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CD30
> 90%
CD15
70-80%
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CD20
CD79a
PAX5
EBV
LMP1
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• 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
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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%
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Nodular Sclerosis HL
• Young females
• Mediastinum
• Usually EBV-
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NS HL
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H&RS + lacunar cells
CD30
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Mixed Cellularity HL
• Males>Females
• Localized or
disseminated disease
• More frequent EBV+
• More frequent in
immunodeficiency
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MC HL
Mummy cell
EBV LMP1
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Lymphocyte Rich
Classical HL
• Rare
• Usually stages I&II
disease
• Less aggressive
• EBV-/+
• Differential diagnosis
with NLPHL
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LRCHL
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LRCHL CD20
CD30
EBV
LMP1
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Lymphocyte depleted HL
• Males>Females
• Localized or
disseminated disease
• More frequent EBV+
• More frequent in
immunodeficiency
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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 !!!
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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
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• 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”
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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
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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
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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
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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
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• 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
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Two molecular
subgroups of cHL
associated with
differential strengths
of the transcription
factor activity of the
NOTCH1, MYC, and
IRF4 proto-oncogenes.
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HL is a tumor characterized by the microenvironment
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Chemical cross-
talk between H/RS
cells and the
microenvironment
Steidl, et al. J Clin Oncol
2012;29:1812
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Steidl, et al. J Clin Oncol
2012;29:1812
Pathway activation in
HRS cells through
signaling from the
Microenvironment
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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.
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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
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Results _ Genes and pathways associated with treatment response.
Sánchez-Espiridión et al. Clin Cancer Res. 2009 Feb 15;15(4):1367-75.
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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
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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
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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
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CD68
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• 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.
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CD68 (PGM1)
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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
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“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
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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