Download molecular testing in lymphoma

Molecular Testing of Lymphomas
RCPath Symposium
Molecular Diagnosis on Tissues and Cells
Friday 25th November 2011
John Goodlad
Department of Pathology
Western General Hospital & University of Edinburgh
Edinburgh
[email protected]
Molecular Techniques in Haematological Malignancy
Spectrum of disease
•Lymphoma
•Leukaemia
Lymphoid
Myeloid
•Myelodysplasia
•Myeloproliferative disorders
Techniques available
•Polymerase Chain Reaction
Standard PCR
Reverse transcriptase PCR
Real time / Quantitative
PCR (Q-PCR)
•Fluorescence in situ hybridisation
Interphase
Spectral Karyotype
Imaging (SKI)
Fluorescence
immunophenotyping &
interphase cytogenetics
(FICTION)
•Comparative Genomic
Hybridisation
Conventional
Array based
•Gene expression profiling
•Massively parallel (next
generation) sequencing
•Proteomics
Areas of application
•Diagnosis / classification
•Therapy
Identification of
specific targets
Newly tailored drugs
•Assessing response to
treatment
Molecular Testing in Lymphoma
1. Establishing a diagnosis of lymphoma
•What is the significance of clonality?
2. Classification of lymphoma
3. Discovery and future developments
•Refining prognostic and diagnostic categories
•Developing new therapeutic regimens
1. Clonality testing in lymphoma
Dominant clonality often used as a marker of lymphoid malignancy
(Neoplastic versus benign lymphoproliferations)
Based on the premise that:
•Neoplastic lymphocytes are clonal
•Reactive (‘benign’) populations of lymphocytes are polyclonal
PCR is method of choice for clonality assays:
Strategies directed towards lymphocyte antigen receptor
•IG genes
•TCR genes
Important to be aware of the limitations and pitfalls
of this approach
Immunoglobulin gene rearrangements
CD34+
Progenitor B cell
DEATH
IGH gene rearrangement
No encounter with antigen
Pre-B cell
IGK+/-L gene rearrangement
Naïve B-cell
Immature B cell: IgM+/IgD-
Encounter with appropriate antigen
Mature B cell: IgM+/IgD+
SURVIVAL
Immunoglobulin heavy chain gene rearrangement: generation of diversity
5’
V1
V2
Vn
V3
D1
D2 D3
Dn
J1
J2
J3
Jn
Cm
Cd
C…
Cg
3
1. D-J joining
(incomplete DNA rearrangement)
5’
V1
V2
Vn
V3
D1 D2 J2
J3
Cm
Jn
Cd
Cg
C…
3’
2. V-DJ joining
(complete DNA rearrangement)
5’
V2
V1
D2 J2
J3
Cm
Jn
Cd
Cg
C…
3’
3. Transcription
V2
D2 J2
J3
Jn
Cm
Cd
Cg
C…
precursor IGH mRNA
4. RNA splicing
V2
5. Translation
D2 J2 Cm
mature IGH mRNA
Immunoglobulin heavy chain gene rearrangement:
generation of diversity
Gene segments
IGH
IGK
IGL
V segments
•Functional (family)
•Rearrangeable (family)
44 (7)
66 (7)
76
56
D segments
•Rearrangeable (family)
27 (7)
-
-
J segments
•Functional
•Rearrangeable
6
6
5
5
4
5
Potential functional rearrangements of IGH = 44 x 27 x 6 = 1188
Potentail functional rearrangements of IGK = 76 x 5 = 380
Potential functional rearrangements of IGL = 56 x 4 = 224
Number of possible different IG molecules = 1188 x 380 x 224 = 101,122,560
Van Dongen et al Leukemia 2003
In the presence of antigen T- and B-lymphocytes
combine to produce:
B
Plasma cells/specific antibody
T
B
B
B
B
An expanded
clone of memory
B-cells
A reactive lymphocyte proliferation is polyclonal;
Each expanded clone has different gene re-arrangement
A neoplastic lymphocyte proliferation is clonal
•Same gene rearrangement
•Same chromosomal abnormality
Polymerase Chain Reaction for IGH chain gene (and
TCR gene) re-arrangement can be used to
determine pattern of clonality within a lymphoid
infiltrate
•Implication is that clonality = maligancy
primers
Products:
Same size in monoclonal population
Different sizes in polyclonal population
Limitations and Pitfalls of Molecular Clonality Studies
1. Limited sensitivity
2. Clonality does not equate with malignancy
3. Ig & TCR re-arrangements are not markers of lineage
4. Pseudoclonality
5. Oligoclonality
6. False positive results
7. False negative results
How and when do we test for clonality
WHAT WE USE
BIOMED 2: antigen receptor PCR targets for clonality studies
IGHA (FR1*)
IGHB (FR2*)
•Number of
possible IG
molecules =
101,122,560
•Number of
possible TCRA/B
heterodimers =
2,979,236
•Number of
possible TCRG/D
heterodimers =
2880
IGHC (FR3*)
IGHD (D-J)
Primer design / Multiplex
PCR
•primers designed to
cover maximum number
of possible combinations
for each re-arrangement
IGHE (D-J
IGKA (V-J)
IGKB (Kde)
•Product size means
effective with FFPE
tissues (<300bp)
IGL (V-J)
•use in multiplex
reactions without cross
annealing to each other
TCRBA (V-J)
TCRBB (V-J)
TCRBC (D-J)
TCRGA (V-J)
TCRGB (V-J)
TCRD (V-J)
Majority of re-arrangements
covered by:
•83 upstream primers
•39 downstream primers
•14 tubes (reaction
mixtures)
* V-J re-arrangements
BIOMED 2 : Immunoglobulin gene re-arrangement:
Pre-GC (%)
MCL
SLL/CLL
GC & postGC (%)
FL
MALT
DLBCL
(n=4)
(n=9)
(n=30)
(n=29)
(n=24)
IGHA (FR1)
100
100
30
48
50
IGHB (FR2)
100
100
30
66
58
IGHC (FR3)
100
100
13
62
50
IGHD (D-J)
75
67
33
38
13
IGHE (D-J)
0
11
0
7
0
IGKA (V-J)
75
100
60
62
58
IGKB (Kde)
50
67
57
48
46
IGL (V-J)
75
44
23
28
8
ALL
100
100
94
97
96
•Different assays have different sensitivities
•Sensitivity of assay varies with lymphoma subtype (especially pre- or post GC)
•In 31 cases (20%) clonality demonstrated by only one assay
•Any one assay not suitable for all types of lymphoma
•Combination of assays should be performed to increase the sensitivity
Modified from Liu H et al. Br J Haematol 2007; 138:31-43
BIOMED 2 in action: routine strategy
e.g. Liu et al Leukaemia 2007
DNA sample
DNA size ladder PCR
%+ with >1
reaction
%+
58%
91%
IGHB + IGKA+IGKB
79%
99%
80%
100%
%+
%+ with >1
reaction
TCRGA + TCRGB
94%
30%
IGHA + IGHC + IGHD
TCRBA + TCRBB
98%
73%
IGL + IGHE
TCRBC + TCRD
100%
82%
DNA >300 bp
WHEN DO WE TEST?
1. Demonstration of clonality used as supportive evidence for neoplasia in
morphologically or immunophenotypically abnormal lymphoproliferations
that do not fully fulfill criteria for malignancy.
N.B. Clonality does not equate with malignancy
Dominant clones can be found in many conditions that are not
overtly malignant
Some clearly benign/reactive processes, e.g:
•Reactive and progressively transformed germinal centres
•Peripheral blood from patients infected with EBV or CMV
•Any lymphoid proliferation in context of immunosuppression
•Lichen planus
•Lichen sclerosus et atrophicus
•Drug hypersensitivity reactions
•B-cutaneous lymphoid hyperplasia
Lymphoid proliferations that may be associated with progression
to overt lymphoma in some, but by no means all cases, e.g:
•MGUS
•Monoclonal B-lymphocytosis
•“Cutaneous lymphoid dyscrasias”
•Pigmented purpuric dermatoses
•Atypical lobular panniculitis
•Pityriasis lichenoides
•“In situ lymphomas”:
•Follicular
•Mantle cell
Example 1: 55 year old male with peripheral blood lymphocytosis
Found to have infectious mononucleosis
Example 2: 65 year old female with breast carcinoma, axillary lymph node sample
“In situ follicular lymphoma”
2. Absence of clonality (polyclonal result) may help
confirm a diagnosis.
Other haematolymphoid malignancies that should not have
re-arranged IG or TCR genes, e.g:
•NK cell lymphomas
•Myeloid sarcoma
•Plasmacytoid dendritic cell neoplasms
Montypic but polyclonal lymphoid proliferations, e.g:
•HHV8-asscociated Castlemans disease
•HHV8(KSHV8)- and EBV- associated germinotropic
lymphoproliferative disorder
•Atypical marginal zone hyperplasia of MALT
Du et al Blood 2001, Du et al Blood 2002, Attygale et al Blood 2004
Example: 14 year old male with enlarged tonsils:
•Massively expanded marginal zones
•Lambda restricted population of cells on flow cytometry
•Polyclonal IG gene rearrangement (Fr1,2,3, IGK, IGL)
Atypical marginal zone hyperplasia
2. MOLECULAR TESTING AND LYMPHOMA CLASSIFICATION
LYMPHOMA CLASSIFICATION: HISTORICAL PERSPECTIVE
1666: Marcello Malpighi
Publishes the first recorded
description of any lymphoma
(Hodgkin's disease)
•“De viscerum structuru exercitatio
anatomica”
1832: Thomas Hodgkin
Often accredited with first description of
Hodgkin’s disease:
•"On Some Morbid Appearances of the
Absorbent Glands and Spleen". MedicoChirurgical Transactions, 17, 1832, 68–
114
An early indication of the limitations of early some
lymphoma diagnoses/classifications
Thomas Hodgkin’s diagnoses were based entirely on gross appearances
Original specimens of Thomas Hodgkin
still preserved in Guy’s museum
Histological examination in 1926
•3/7 cases diagnosed correctly
•Tuberculosis
•Other forms of lymphoma
Subsequent classification systems based purely on
light microscopic appearances
First real lymphoma classification in 1944, followed rapidly by many others*
Jackson & Parker
Lukes
1944
1963
Rye
Rappaport
Lukes & Collins
Kiel
1965
1966
1974
1978
Working Formulation
Updated Kiel
1985
1988
Hodgkin’s disease
Primarily LN
NHL
*all based entirely on light microscopic appearances
•Giemsa
•Haematoxylin & eosin
Limitations of morphology based classifications:
lymphomas with nodular/follicular growth pattern
Small cell lymphomas with nodular/follicular growth pattern circa 1980
•centroblastic-centrocytic (small) & centrocytic: Kiel
•follicular, predominantly small cleaved cell: W-F
Overall survival for this group of patients
•Median = 6.93 years
•5-year = approx 62%
•10-year = 35.3%
This group of lymphomas contains subsets of cases
with different chromosomal translocations
t(14;18)(q32;q21)
t(11;14)(q13;q32)
BCL2
Cyclin D1
Follicular lymphoma
Mantle cell lymphoma
Follicular lymphoma has much better outcome than mantle cell lymphoma
FL
Median Survival:
5-year OS:
8-10 years
>70%
Treatment dictated by classification:
Wait and watch or
symptomatic only
MCL
3-4 years
<40%
CHOP-like followed by
myeloablative regimens and
allogeneic stem cell transplant
in younger patients
Fundamentals of modern lymphoma classification
The International Lymphoma Study Group
•Pathologists/haematopathologists
•Clinicians
•US, Europe and rest of world
Nancy Harris - Boston
Elaine Jaffe - Bethesda
Harald Stein - Berlin
Peter Banks - San Antonio
John Chan - Hong Kong
Michael Cleary - Stanford
George Delsol - Toulouse
Chris De Wolf-Peters - Leuven
Brunangelo Falini - Perugia
Kevin Gatter - Oxford
Thomas Grogan - Tucson
Peter Isaacson - London
Daniel Knowles - Cornell
David Mason - Oxford
Konrad Muller-Hermelink - Wurzburg
Stefano Pileri - Bologna
Miguel Piris - Toledo
Elizabeth Ralfkiaer - Copenhagen
Roger Warnke - Stanford
1994:
A consensus list of lymphoid neoplasms that appear to be distinct clinical
entities
All available information used to define entities
• Morphology
• Immunophenotype
• Genetic features
• Clinical features
Reproducibility proven in consistency studies (Blood. 1997 Jun 1;89(11):3909-18)
Clinical utility verified (Blood. 1997 Jun 1;89(11):3909-18)
Understanding that modifications would be required as knowledge
increase
Internationally acceptable!
WHO 2008.
Classification of Tumours
of Haematopoietic and
Lymphoid Tissues
Treatment is dictated
largely by the diagnostic
category into which a
tumour is placed
In Edinburgh:
1.
Probes currently in routine use:
Breakapart
IGH
IGK
IGL
BCL2
BCL6
MALT1
MYC
CCND1
ALK1
Dual fusion
IGH/BCL2
IGH/MALT
AP12/MALT
MYC/IGH
CCND1/IGH
2.
3 m tissue sections
3.
Break-apart probes in first instance
4.
Negative controls run on each test to determine cut-off value
5.
Scoring on basis of number of abnormal versus normal signals
USE OF FISH +/- KARYOTYPING
1. Occasional as adjunct to clonality testing, often in atypical
follicular proliferations;
• IGH, IGL, IGK
• BCL2
• BCL6
2. Facilitate subclassification when pathological features
inconclusive
3. All large B-cell lymphomas
• Mandatory to make diagnosis of Burkitt lymphoma
 MYC
• Identify “double-hit” lymphoma
 MYC, BCL2, BCL6, IGH, IGK, IGL
Example: 14 year old female with lesion on scalp
•Small cell infiltrate in skin
•Relatively few ALK+ cells by IHC
ALK1
•ALK translocation confirmed with breakapart probe
Anaplastic large cell lymphoma, small cell
variant
3. DISCOVERY AND FUTURE DIRECTIONS
IMPACT OF NEW HIGH THROUGHPUT TECHNOLOGIES
‘Chipping away at the coal face.’
•Traditional methods allowed researchers to
survey only a relatively small numbers of
genes/abnormalities at any one time:
‘Industrial strength processing’
•Techniques now available that permit analysis of
thousands of genetic, epigentic and proteomic
changes in tumours in relatively short space of time
•Array based technologies
•Massively parallel sequencing
•Vast quantities of information can be obtained from a
large number of samples in a relatively short period of
time.
Example 1: Diffuse large B-cell lymphoma
Advances in classification and treatment
Gene expression profiling studies on DLBCL show that ‘cell of
origin’ is an important determinant of outcome
Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling.
Alizadeh AA, et al. Nature 2000; 403: 503-511
Two main prognostic groups
•Germinal centre B-like: good prognosis
•Activated B-like; bad prognosis
Gene expression profiling has identified a number of potential
therapeutic targets
e.g./
•GEP and other investigations show evidence of constitutive
activation of NFkB pathway in ABL-DLBCL but not GCBDLBCL
•Antiapoptotic effects of NFkB counteract action of
conventional doxorubicin-based cytotoxic chemotherapy in
DLBCL
•Inhibition of NFkB in ABL-DLBCL cell lines in vitro is toxic
•Inhibition of NFkB in vivo may sensitize tumour cells to
chemotherapy and improve outcome
•Trial of bortezomib in conjunction with doxorubicin based
chemotherapy in patients with relapsed/refractory DLBCL
Bortezomib and NFkB Activation
Inactive NFkB exists as protein complex in cytoplasm
During NFkB activation,
•IκB kinase (IKK) phosphorylates IκBα
•IκBα dissociates from NF-κB
•Freed NF-κB translocates to the nucleus and alters gene expression
Bortezomib blocks IκBα degradation
Prevents translocation of NF-κB to the nucleus
Bortezomib significantly improves survival in
relapsed/refractory ABL-DLBCL but not GCB-DLBCL
Figure 2 Overall survival in patients with DLBCL
Dunleavy, K. et al. Blood 2009;113:6069-6076
Copyright ©2009 American Society of Hematology. Copyright restrictions may apply.
Clinical trials already open to assess efficacy of Bortezomib
(Velcade) as front line treatment in ABC-DLBCL, eg
UK: ISRCTN 51837425
A Randomized Evaluation of Molecular Guided
Therapy for Diffuse Large B-Cell Lymphoma With
Bortezomib (REMoDL-B); ISRCTN 51837425.
GEP will be undertaken on samples of trial patients to
stratify into GC and ABC type DLBCL
Example 2:
Classic Hodgkin lymphoma; tumour cell genetics
impact on microenvironment to the benefit the tumour
Steidl et al Nature 2011.471.377
Common lymphoma associated translocations are rare in cHL
Whole transcriptome paired end sequencing (next-generation)
•Genome wide mapping of base pair sequences
Translocation breakpoints
Mutations
Gains and losses
Applied to two Hodgkin cell lines
•KM-H2 (89.2 million base pair readings)
•L428 (61.5 millon base pair readings)
Found three translocations:
•9q34.13 (BAT2LI) / 10q26.3 (MGMT)
•7p14.1-14.2 (ELMO1) / 15q26.1 (SLCO3A1)
•15q21.3 (BX648577) / 16p13.13 (CIITA)
CIITA–BX648577 gene fusion observed using paired-end
massively parallel whole transcriptome sequencing.
C Steidl et al. Nature 000, 1-5 (2011) doi:10.1038/nature09754
CIITA: a major MHC class II transactivator
Studied incidence of CIITA translocations
further by FISH; breakapart probe:
•15% classic Hodgkin lymphoma (8/55
cases)
•38% primary mediastinal large B-cell
lymphoma (29/77)
•27% mediastinal grey zone lymphoma
•3% diffuse large B-cell lymphoma (4/131)
•11% testicular DLBCL
•0% primary DLBCL of CNS
In cases of PMBCL presence of CTIIA
correlates with:
•Poorer disease specific survival (63.0% vs
85.0% at 10 years)
Steidl et al, Nature 2011
TRANSLOCATIONS INVOLVING CIITA
Fusion partners sought for CIITA using 3’ rapid amplification
of cDNA ends (RACE)
•Several different partners
•9p24 a frequent partner
Several genes at 9p24, including
•JAK2
•Programmed cell death ligand 1 (PD-L1) (CD273)
•Programmed cell death ligand 2 (PD-L2) (CD274)
Breakpoints typically in region of CD273 and CD274 genes
HRS cells also shown to have copy number gains of 9p24
•Green et al, Blood 2010; 116: 3268
CONSEQUENCES OF t(9;16)(q34.13; p13.13)
CIITA / CD273 or CIITA / CD274
Translocation interferes with MHCII expression but
upregulates PD-L expression
•Downregulation of MHCII
•Upregulation of CD273 or CD274
Decreased MHCII expression correlates with poor survival in variety of
lymphomas including cHL and DLBCL, eg
•Rimsza LM et al, Blood 2008
•Diepstra A et al, JCO 2007
•Roberts RA et al, Blood 2006
Upregulation of PD1 ligands correlates with inferior survival in several
cancers
•Blank C et al, Cancer Immunol Immuntherapy
Effects mediated via modulation of anti-tumour immune response
Anti-tumour host immune response
Cytotoxic T-cells are critical in recognition and elimination of altered self
antigens
•Virus infected cells
•Tumour cells
•MHC class I restricted - recognize antigen-MHC I complexes on
specific target cells
Activated by Th1 cells
•Recognize specific antigen-MHC II complexes
MHC II
MHC I
Th1
Tc
Downregulation of MHC II helps tumour cell evade
recognition by tumour specific T-cells
MHC II
MHC I
Th1
Tc
MHC I
MHC I
Programmed cell death 1 and its ligands
PD.1 expressed on a variety of cell types, including T-lymphocytes
Binding of PD.1 with one of its ligands (PD-L1 and PD-L2);
•Inhibits activated T-cells(Induction of a resting state)
•In some circumstances may facilitate apoptosis
Normally functions to induce self tolerance
•prevent development of autoimmune disease
t(9;16)(q34.13; p13.13): a Novel Translocation
Recurrent genetic event with fusion that impacts through both sides of the
translocation
First recurrent abnormality shown to favour tumour growth through effects on
microenvironment, rather than tumour cell division, differentiation and death
Provides opportunity for therapeutic manipulation
Blocking PD.1:PD-L interactions may restore anti-tumour T-cell immunity
•Specific PD.1 receptor blocking antibodies exist
• Already in clinical trials; lymphoma, carcinoma and melanoma
•Gordon L et al, Ann Oncol 2011;22 (suppl4): iv102 (prelim report in DLBCL)
CONCLUSIONS (i)
Molecular testing is already well established in lymphoma diagnosis
•Differentiating reactive and neoplastic populations
•Classification
Modern lymphoma classification systems define entities basis of
shared biological and clinical characteristics, allowing them to be
arranged into clinically relevant groupings
•Diagnostic category dictates treatment and likely prognosis
Molecular studies have changed our perception of cancer from that
of a genetic disease to complex signaling network
•Highlight biological and clinical heterogeneity within disease
categories
•Identification of new prognostic markers
•Identification of pathogenetic pathways of potential relevance
•Identification of potential therapeutic targets
CONCLUSIONS (ii)
These advances will allow
diagnostic categories to be refined
and incorporated into updated
lymphoma classifications
Ultimately may permit
•Molecular diagnosis
•Integration of diagnosis and
therapeutics
•Individually tailored treatment
1st EDINBURGH HAEMATOPATHOLOGY TUTORIAL:
“INTEGRATING TECHNOLOGICAL ADVANCES INTO DIAGNOSTIC PRACTICE”
JUNE 7-8, 2012
John Goodlad, MD, FRCPath
Western General Hospital
Edinburgh
Scotland
Ahmet Dogan, MD, PhD
Mayo Clinic
Rochester
Minnesota, USA
Andrew Wotherspoon, MBChB, FRCPath
Royal Marsden NHS Foundation Trust
London
UK
Daphne de Jong, MD, PhD
The Netherlands Cancer Institute
Amsterdam
The Netherlands
www.edinburgh-haematopathology.org.uk