Download Viruses and Hodgkin`s lymphoma

Annals of Oncology 13 (Supplement 1): 23–29, 2002
DOI: 10.1093/annonc/mdf603
Symposium article
Viruses and Hodgkin’s lymphoma
R. F. Jarrett*
LRF Virus Centre, Institute of Comparative Medicine, University of Glasgow, Glasgow, UK
Hodgkin’s lymphoma (HL) is unusual among human malignancies in that the epidemiology suggests an
infectious aetiology. The Epstein–Barr virus (EBV) is associated with a proportion of cases and this
association is believed to be causal. In these cases the Hodgkin and Reed–Sternberg (HRS) cells express
the EBV-encoded proteins LMP1 and LMP2, which can mimic CD40 and the B cell receptor, respectively, and therefore may play a critical role in facilitating the survival of HRS cells. EBV-associated and
non-EBV-associated HL cases have different epidemiological features and recent data suggest that
delayed exposure to EBV is a risk factor for the development of EBV-associated HL in young adults.
We suggest that HL can be divided into four entities on the basis of EBV status and age at presentation,
with three groups of EBV-associated cases and a single group of EBV-negative cases. The aetiology
of the latter cases is obscure although involvement of an infectious agent(s) is suspected.
Key words: epidemiology, Epstein–Barr virus, herpesvirus, Hodgkin’s lymphoma, infectious
mononucleosis, latent membrane protein.
Introduction
In a proportion of Hodgkin’s lymphoma (HL) cases, Epstein–
Barr virus (EBV) genomes are present in Hodgkin and Reed–
Sternberg (HRS) cells, and EBV gene products are expressed.
These cases are referred to as EBV-associated or EBVpositive. In 1997, a working group of the International Agency
for Research on Cancer (IARC) reviewed the available data
and concluded that there was sufficient evidence to regard the
association between EBV and HL as causal [1]. The data
supporting this are summarised in detail elsewhere [2–4]; this
article aims to review recent findings relevant to the biology of
EBV in HL and to discuss the relationship between HL and
infectious mononucleosis (IM). The aetiology of non-EBVassociated cases is less well understood, although involvement of infectious agents has frequently been suggested.
Studies examining the potential role of viruses in non-EBVassociated cases are discussed.
EBV and the biology of HL
EBV is an extremely efficient transforming agent and when
EBV infects B cells in vitro the six EBNA proteins (called
either EBNA1–6 or EBNA1, 2, 3a, 3b, 3c and LP) are expressed alongside three membrane proteins, LMP1 and LMP2A
and 2B (reviewed in [5, 6]). Two small non-polyadenylated
RNA transcripts, the EBERs, are also expressed at high level
*Correspondence to: Professor R. F. Jarrett, LRF Virus Centre, Institute
of Comparative Medicine, Faculty of Veterinary Medicine, University of
Glasgow, Glasgow G61 1QH, UK. Tel: +44-141-330-5775;
Fax: +44-141-330-5733; E-mail: [email protected]
© 2002 European Society for Medical Oncology
in cells latently infected by EBV [6]. In HRS cells in HL the
pattern of EBV gene expression is more restricted with
expression of the EBNA1, LMP1, 2A and 2B proteins and the
EBER RNAs, the so-called latency II pattern of transcription
[4, 6].
As discussed elsewhere in this journal, there is now compelling evidence that HRS cells, in most cases of HL, are derived
from germinal centre (GC) B cells. Human GC B cells have an
apoptosis-sensitive phenotype and survival of B cell clones in
the GC relies on signals delivered through B cell receptor
(BCR) and CD40 molecules. Survival of mature B cells in the
periphery is also dependent on a BCR maintenance signal,
without which B cells rapidly die [7]. A unifying feature of
HRS cells is that they do not express surface immunoglobulin;
therefore, in order to survive they must have evolved nonphysiological mechanisms of escaping apoptosis in GCs and
thereafter. Recent studies dissecting the functions of EBV
LMP1 and LMP2A provide insight into the mechanisms by
which EBV might contribute to this survival process.
LMP1 is the major transforming protein of EBV and is the
only latent protein that can transform rodent fibroblasts [5].
LMP1 is not expressed by B cells in the peripheral blood of
healthy individuals but is essential for transformation of B
cells by EBV [5, 8]. Expression of LMP1 appears to mimic a
constitutively active CD40 receptor [9]. Both CD40 and
LMP1 bind tumour necrosis factor (TNF) receptor-associated
factors (TRAFs), initiating a signalling cascade that leads to
activation of the transcription factors NF-κB, AP-1 and STAT
[5, 10–13]. LMP1 appears to provide a more potent and
sustained activation signal than CD40 and this may explain
why LMP1 has transforming effects [14]. By providing these
CD40-like signals, it is conceivable that LMP1 allows EBV-
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infected HRS cells (or precursors) to bypass a GC checkpoint
and escape apoptosis. Ongoing studies in transgenic mice
should help to resolve whether this does indeed happen
in vivo.
In contrast to LMP1, the LMP2A protein is expressed by
latently infected memory B cells in healthy individuals and is
not essential for transformation of B cells [6, 8]. There are two
variants of LMP2 (LMP2A and LMP2B) that have a common
C-terminus; LMP2A has an N-terminal cytoplasmic domain
that interacts with many other protein molecules, and most
functional studies have concentrated on this protein [5]. It is a
membrane-spanning protein that aggregates in lipid rafts and
interferes with BCR signalling [15, 16]. In primary B cells,
engagement of the BCR results in recruitment and activation
of Src family protein tyrosine kinases (PTKs), followed by
binding of the Syk PTK to the immunoreceptor tyrosine-based
activation motifs (ITAMs) contained in the BCR [17, 18]. The
N-terminal cytoplasmic domain of LMP2A is also able to
recruit Src family kinases, such as Lyn, and contains an ITAM
motif that binds Syk [19, 20]. By sequestration of these
molecules, LMP2A is able to block normal BCR signal transduction and this renders B cells largely unresponsive to stimulation through the BCR [21, 22]. This prevents a BCR-induced
switch to the EBV lytic cycle and thereby helps to maintain
viral latency. More importantly in the context of HL, studies
using transgenic mice have shown that LMP2A expression
provides a survival signal that can substitute for BCR signalling [23, 24]. LMP2A-expressing B cells lacking surface
immunoglobulin are able to exit the bone marrow and survive
in the periphery and therefore bypass normal developmental
checkpoints. The ITAM motif is also required for this
LMP2A-mediated survival signal and a substrate of Syk, the
SLP-65 or BLNK protein, appears to be a critical effector
molecule in both activation and suppression of BCR signalling
pathways [25, 26]. In addition, LMP2A has been shown to
augment signalling from LMP1 by extending its half-life [27].
Taken together, the above functional studies suggest a
mechanism by which EBV may facilitate survival of HRS
cells by mimicking CD40 and BCR signalling. This lends
weight to the argument that EBV plays a causal role in HL.
early childhood is associated with an increased risk of developing young-adult HL, and this is interpreted as suggesting
delayed exposure to a common infectious agent [30–33]. In
contrast, childhood HL is associated with less favourable
living conditions. Nodular sclerosis HL accounts for the vast
majority of cases in young adults, whereas mixed cellularity
disease is relatively more common in childhood and olderadult cases [30, 34, 35]. Consideration of the data available in
the 1950s and 60s led MacMahon [30] to propose that HL is
not a single disease entity but a grouping of several diseases
with different aetiologies; he suggested that these could be
separated on the basis of age at diagnosis and defined the three
age groups: 0–14 years, 15–34 years and 50 years and older.
He further suggested that young-adult HL was likely to have
an infectious aetiology. Subsequent data provide support for
this model [30, 31, 33, 36].
EBV and the epidemiology of HL
Correlates of EBV association
Descriptive epidemiology and multiple aetiology model
A plethora of studies investigating the relationship between
EBV and many features of the epidemiology and pathology of
HL has been published [2, 3]. These have provided much
useful data and several clear associations emerge. First, the
proportion of EBV-associated cases is greater for mixed cellularity than for nodular sclerosis HL, and this difference has
been statistically significant in almost every study [2, 3, 40].
Secondly, among EBV-associated cases there is a significant
male bias [41–43]. Thirdly, the proportion of EBV-associated
cases is higher in childhood, particularly under the age of
10 years, than in young adulthood [2, 3, 36, 38, 39, 41].
Fourthly, socio-economic status and material deprivation
HL has attracted much attention because of its unusual age
incidence curve and the geographical variation in age-specific
incidence patterns [3]. Classically, the age incidence curve is
described as bimodal; in developing countries the first peak is
seen in childhood and the second in the older adult age group,
whereas in developed countries the first peak is seen in young
adulthood. In practice, variations on these patterns are
observed and bimodality is not always present [28, 29].
Risk factors for disease development and the pathological
features of HL differ by age group. A high standard of living in
The polio model
In 1971, Correa and O’Conor [28] published data showing an
inverse correlation between the incidence of childhood and
young-adult HL. Countries with a high incidence of childhood
HL had a low incidence of young-adult disease and vice versa.
This led to comparisons with paralytic polio in the pre-vaccine
era—the so-called polio model [37]. This model predicts that
the same infectious agent causes childhood HL in developing
countries and young-adult HL in developed countries, with
living conditions determining the age of infection and age of
infection determining the risk of disease. Following the realisation that EBV is associated with a proportion of cases, we
investigated whether the pattern of EBV-positivity in HL
fitted this model. Data from our laboratory and others clearly
showed that most childhood HL cases in developing countries
were EBV-associated, whereas most young adult cases in
developed countries were not [2, 3, 38, 39]. Furthermore, an
extension and re-analysis of international cancer registry data
suggested that the inverse relationship between the incidence
of childhood and young-adult HL was not evident and perhaps
never existed [29]. Thus, recent molecular and epidemiological studies indicate that the polio model is not relevant to
the majority of HL cases.
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Figure 1. Age distribution of HL in Scotland and the North of England,
1994–1997, by EBV status. Solid line, EBV-associated cases; dashed
line, non-EBV-associated cases.
within countries are likely to influence EBV-positivity rates,
with greater deprivation (as measured by deprivation indices)
and lower socio-economic status being linked to more EBVassociated disease [44–46]. Finally, it is clear that racial/
ethnic differences influence these overall patterns [41, 47].
Most studies investigating the association between EBV
and HL have examined archival samples, often from referral
centres, and have reported the proportion of EBV-positive
cases in subgroups of HL cases. There have been few attempts
at population-based studies, and most have been relatively
small [43, 48, 49]. In collaboration with F. Alexander and
M. Taylor, we have recently completed a population-based
study of ∼600 consecutive adult HL cases—the Scotland and
Newcastle Epidemiological Study of Hodgkin’s Disease
(SNEHD). This study has allowed us to determine the age
distribution of HL by EBV status (Figure 1). As can be seen
in Figure 1, the EBV-positive and -negative cases have quite
distinct age distributions, with EBV-negative cases having a
unimodal age distribution and accounting for the young-adult
peak. The curve for EBV-positive cases is much flatter,
although on the basis of small peaks at each end of the age
range coupled with the risk factor data (some of which is
described below), we believe is bimodal with a first peak in
the 16–24 year age range and a second peak above the age of
50 years.
Association with IM—the polio model revisited
One of the first indications that HL was linked to EBV came
from cohort studies investigating the risk of developing HL
following IM [37]. Although IM is caused by delayed exposure to EBV, and EBV is now thought to be causally associated with HL, the nature of the association between IM and
HL remains controversial. Specifically, it is not clear whether
the increased risk associated with IM is specific for EBVassociated cases.
The association between IM and HL has been investigated
in cohort studies of IM patients, and also in case–control and
case studies of HL. Cohort studies performed in the 1970s
showed an excess risk of developing HL following IM of
around three-fold (reviewed in Gutensohn and Cole [37]).
These studies focused on the young-adult age group and most
diagnoses of HL were found to occur within 3 years of the
diagnosis of IM. Hjalgrim et al. [50] recently published a
study of cancer outcome among patients with a past history of
IM, which included 38 562 IM patients with 689 619 personyears of follow-up. The risk of developing HL was significantly increased [standardized incidence ratio 2.55; confidence interval (CI) 1.87–3.4] and remained elevated for up
to two decades after the occurrence of IM, but decreased with
time after diagnosis (P value for trend <0.001). The risk of HL
occurring in the young-adult age group (15–34 years) was
significantly higher (standardized incidence ratio 3.49) than
that in any other age group.
Case–control studies of HL have generally found that HL
cases are more likely to report prior IM than controls [31, 43,
51–54]. In some studies excess risk has been confined to, or
more marked among, young-adult cases [51, 55] and the risk
appears greater within 5 years of the diagnosis of IM [53].
To my knowledge, only two previous studies have examined
the association between prior IM and EBV-association in HL,
excluding case reports [42, 43, 56]. Sleckman et al. [42]
performed a retrospective case series analysis in which history
of IM was available for 83 cases of HL of known EBV status.
Cases were aged 15–55 years and 16 of the 83 patients had
EBV-associated disease. There was no association between
EBV-positive HL and prior IM and it was specifically noted
that 11 of 14 cases reporting previous IM had EBV-negative
HL. We performed a case–control study including 103 young
adult cases aged 16–24 years; as predicted for this age group
only a small proportion (19 of 103) had EBV-positive disease
[43]. Comparison of cases with matched controls showed that
excess risk associated with prior IM was specific for EBVassociated cases [odds ratio (OR) 9.16; CI 1.07–78.31]; no
excess risk was apparent among the EBV-negative cases (OR
1.60; CI 0.63–4.07). In this study all the EBV-associated HL
cases had either a prior history of IM or antibody titres to EBV
viral capsid antigens in excess of 640 [43].
More recently, we have examined the association with IM
in a larger case–control study of HL (SNEHD), including
adult subjects aged 16–74 years (F. Alexander, D. J. Lawrence, J. Freeland et al., unpublished data). This study appears
to resolve the apparent discrepancy in the previous two studies.
All HL patients, both EBV-positive and -negative, were more
likely to report prior IM than were controls. However, in all
comparisons case–control differences were greater for EBVassociated compared with non-EBV-associated HL cases.
When the analysis was restricted to young adults (16–34 years),
case–control differences remained significant for EBVpositive cases (P = 0.03) but not for EBV-negative cases
(P = 0.13). Young-adult EBV-positive cases also reported IM
in a first-degree relative more frequently than controls or
EBV-negative cases. When prior IM in the index case and/or a
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first-degree relative were analysed together, differences
between EBV-positive and EBV-negative young-adult cases
were statistically significant (P = 0.04). This suggests a specific association between prior IM and EBV-associated HL in
young adults. Time between IM and development of HL was
also shorter for EBV-positive compared with EBV-negative
cases, although this was not statistically significant (P = 0.07).
These data fit well with, and extend, the results of the study by
Hjalgrim et al. [50], in which risk following IM was greater for
young adults and at shorter time points after IM. Failure to
identify an association between EBV-positive IM and HL in
the study by Sleckman et al. [42] most probably relates to the
age range of the patients coupled with the relatively small
number of cases examined.
These data provide evidence that (i) IM is associated with an
increased risk of developing HL (both EBV-positive and
-negative) and (ii) this increased risk is greater for young-adult
EBV-positive cases compared with other groups of cases. Our
interpretation is that there is an increased risk of developing
HL following IM that reflects the shared lifestyles and characteristics of both groups of cases. However, superimposed on
this, prior IM appears to confer an additional risk of developing EBV-associated HL in young adulthood. In the latter cases
we believe that delayed exposure to EBV is causally related to
the development of HL. This, in turn, suggests that there is a
small group of cases for which the polio model is applicable.
Four disease model
We previously extended MacMahon’s three disease model
to incorporate EBV status of HL lesions [36]. On the basis of
the above data we have added a fourth entity, namely EBVassociated cases occurring following late exposure to EBV
(Figure 2). The current model therefore includes three EBVassociated groups of cases and a single non-EBV-associated
group, which has a unimodal age distribution and accounts for
the young adult age-incidence peak. The first two groups of
EBV-associated disease follow the two periods in life when
primary EBV infection is most likely to occur. It is not clear
whether there are quantitative or qualitative changes in the
virus–host relationship at short time periods after primary
infection, leading to an increased risk of EBV-associated HL.
However, we have shown that EBV-positive HL cases have
higher frequencies of EBV-infected cells in the peripheral
blood compared with EBV-negative cases (G. Khan, A. Lake,
J. Freeland et al., unpublished data). A greater number of
EBV-infected B cells may increase the probability of an EBVinfected cell encountering antigen and entering a GC reaction.
Non-EBV-associated cases
The majority of cases of HL in Western countries are nonEBV-associated, and these cases account for the young-adult
incidence peak (Figure 1). As mentioned above, epidemiological studies suggest that delayed exposure to a common
Figure 2. Four disease model of HL. This model divides HL into four
entities on the basis of age at diagnosis and EBV status of lesions. There
are three groups of EBV-associated cases (solid lines) and one non-EBV
associated entity (dashed line). The first EBV-associated entity has an
incidence peak below the age of 10 years and accounts for most
childhood cases in developing countries; the second occurs within the
young-adult age group (15–34 years) and is associated with delayed
exposure to EBV; the third has a peak incidence in the older adult age
group and accounts for over half the cases occurring over the age
55 years. The largest group is non-EBV-associated and accounts for the
young-adult incidence peak observed in developed countries. The overall
age distribution of HL in different geographical locales, and the
proportion of cases which are EBV associated, will reflect the relative
contributions of each of these entities.
infectious agent may play a role in these cases. Likely candidates are viruses that infect most people, and that infect individuals at older ages in developed countries in comparison
with developing countries. Members of the herpesvirus and
polyomavirus families fit these criteria; however, molecular
studies provide no evidence that known members of these
virus families are directly involved in the pathogenesis of HL.
Despite extensive surveys cytomegalovirus, human herpesvirus (HHV) -6, -7 and -8 have not been consistently detected
within lesions, although HHV-6 and -7 are frequently detected
at low-copy number, presumably in bystander cells [57–65].
Similarly, we have found no evidence of the polyomaviruses
LPV, JC, BK and SV40 viruses in DNA samples from HL
biopsies [61] (unpublished data).
At the Fifth International Symposium on Hodgkin’s disease, Benharroch et al. [66] reported the detection of measles
virus proteins in HRS cells using immunohistochemistry.
Measles virus transcripts were also detected in biopsies using
RT–PCR. The presence of measles virus proteins was not
restricted to non-EBV-associated cases but did appear to be
associated with improved survival. Follow-up studies are currently ongoing and will determine whether this is a consistent
finding in HL.
Overall, the data suggest that any virus directly involved in
the causation of EBV-negative HL is currently unknown.
Over the last decade our group has used cell culture and
molecular strategies to search for this agent, which so far
remains elusive. PCR assays aimed at detecting novel
members of the herpesvirus family have produced negative
27
results suggesting that a novel herpesvirus is not directly
involved (A. Gallagher, J. Perry, L. Shield et al., unpublished
data). Virus hunting in HL remains difficult, since it is not
possible to routinely purify large numbers of HRS cells, and
failure to identify a viral agent at the present time is most
probably due to technical limitations.
EBV and the hit-and-run hypothesis
An alternative possibility is that EBV is aetiologically
involved in all cases of HL but is using a hit-and-run mechanism in ‘EBV-negative’ cases. Young-adult cases may be more
able to mount an effective immune response and select against
HRS cells expressing viral proteins. Although it is very difficult to disprove this sequence of events, there is good
evidence that some patients with HL have never been infected
by EBV [67]. Therefore hit-and-run cannot explain all cases.
The association between prior IM and young-adult HL,
discussed above, also argues against this mechanism.
EBV genomes are normally present as stable episomes
within infected cells and do not integrate into host-cell DNA.
However, fragments of EBV genomes have been detected in
Burkitt’s lymphoma cases that were initially classified as
EBV-negative, sporadic cases [68]. We have searched for subgenomic fragments of the EBV genome in HL biopsies using
both Southern blot analysis and quantitative PCR, but have
not found any evidence to support this possibility (unpublished data). Staratschek-Jox et al. [69] combined fluorescence in situ hybridisation (FISH), using probes spanning the
entire EBV genome, and immunophenotyping to examine five
cases of HL that were EBV-negative by LMP1 immunohistochemistry. None of the EBV probes hybridised to HRS
cells in these cases, indicating that remnants of viral genomes
were not present.
Conclusions
The association between EBV and HL is now well established.
EBV is consistently detected in HRS cells in HL lesions;
EBV-encoded proteins are expressed and have a plausible role
in the pathogenic process; EBV-associated cases show distinct epidemiological features and prior IM confers an
increased risk of developing EBV-associated disease. These
findings provide support for the idea that the relationship
between EBV and HL is causal. The aetiology of non-EBVassociated cases is less well understood. These cases show a
unimodal age distribution with a peak incidence in young
adults. Involvement of infectious agents is suspected but no
single agent has, as yet, been identified, and there is no good
evidence to support a hit-and-run mechanism. Future molecular studies should shed light on the biology of this fascinating
group of cases.
Acknowledgements
I would like to thank Daniel Chui for reading the manuscript
and Freda Alexander for helpful advice and continued collaboration. Work in our laboratory is supported by specialist
programme grants from the Leukaemia Research Fund.
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