Epstein-Barr virus-associated malignancies
Tan, Geok Wee
DOI:
10.33612/diss.173425402
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Tan, G. W. (2021). Epstein-Barr virus-associated malignancies: Susceptibility factors and molecular detection in liquid biopsies. University of Groningen. https://doi.org/10.33612/diss.173425402
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CHAPTER
1
1. Epstein‐Barr virus
Epstein‐Barr virus (EBV) also known as human gammaherpesvirus 4, is a virus that infects more than 90% of the world’s population. It causes asymptomatic, persistent life‐long infection in most people while a small number of infected individuals develop infectious mononucleosis in adolescence or early adulthood.
EBV can infect both B cells and epithelial cells. It was thought to have definite tropism for B cells as epithelial cells lack expression of CD21, which functions as a receptor for EBV glycoprotein gp350/220. Studies eventually ascertained that the binding of gp350/220 and CD21 only aids the attachment of EBV to its target cells but is not necessary for EBV entry. The essential proteins for EBV fusion and entry into target cells are glycoproteins known as gH, gL and gB1. The gH/gL heterodimer either forms a complex with gp42 which binds
to human leukocyte antigen (HLA) class II molecules on B cells or directly binds to integrins and NMHC‐IIA followed by interaction with NRP1 and EphA2 on epithelial cells2. Lastly,
gB, a fusion protein, facilitates fusion and EBV into the host cells3.
Although the first contact in the human host is the epithelium of the oropharynx, EBV does not infect many epithelial cells and mostly passes through the epithelium to infect naïve B cells. The initial lytic infection invokes a cytotoxic T cell response, which EBV can escape by switching to a latent type of viral gene expression. Four different latency EBV infection patterns are recognized in B cells, and these are referred to as latency type 0, I, II and III. Initial infection of naïve B cells usually leads to latency type III infection, which is characterized by expression of all EBV nuclear antigens (EBNA‐1, ‐2, ‐3A, 3B, ‐3C, ‐LP) and latent membrane proteins (LMP‐1, ‐2A, ‐2B). This infection induces proliferation and entry of the B cells into the germinal center. Within the germinal center, the latency type changes to type II, which is characterized by expression of only EBNA‐1 and all three LMP proteins. The LMP proteins provide survival signals, allowing differentiation of the EBV infected B cell within the germinal center. Upon exit of the germinal center, EBV persists in memory B cells in a latency I stage, characterized by expression of only EBNA‐1 and/or a latency 0 stage with no expression of any of the EBV proteins at all. EBNA‐1 has an essential role in the replication and maintenance of the EBV genome. Reactivation of the lytic phase occurs infrequently in a small proportion of the EBV infected memory B cells. Additional infection of epithelial cells is likely to occur at this point where EBV from B cells can infect epithelial cells with higher efficiency4, resulting in productive replication and
shedding of EBV from differentiated epithelial cells in the oral cavity5. The host immune
system keeps the persistence and lytic activities of EBV at a low and benign level. When the virus‐host equilibrium is out of balance, extensive proliferation of EBV‐infected cells can lead to diseases.
2. EBV‐associated malignancies and diseases
Although EBV infection is usually asymptomatic, some of the infected individuals develop infectious mononucleosis (IM) caused by a strong T‐cell mediated immune response against lytic infection. IM usually causes fever, sore throat and enlarged lymph nodes in the neck. In general, these symptoms will recover within a month6. EBV infection increases
the risk of developing malignancies such as Hodgkin lymphoma (HL), diffuse large B‐cell lymphoma (DLBCL), Burkitt lymphoma (BL), nasopharyngeal carcinoma (NPC) and gastric carcinoma (GC). Individuals who are immunosuppressed following organ transplant are at risk to develop post‐transplant lymphoproliferative disorder (PTLD) due to uncontrolled growth of EBV‐infected B cells. These malignancies exhibit one of the three types of latency programs with variable expression of several EBV proteins. The percentage of cases associated with EBV varies in different geographic location for each of the cancers (Table 1). In this thesis, the main focus is on HL, monomorphic PTLD and NPC.
HL tumor cells, known as Hodgkin Reed‐Sternberg cells, arise from germinal center B cells. Four histological HL subtypes are recognized, with nodular sclerosis being the most common subtype. In the Caucasian population, about 30% of all HL cases are EBV positive and presence of EBV is most common in mixed cellularity HL (80‐90%). In nodular sclerosis HL, the presence of EBV is much lower, accounting for 15‐20% of the cases. HL is more common in Caucasian than in African and Asian, with estimated age‐standardized incidence rates per 100,000 of >2, 0.92 and 0.59 respectively7. HL patients are usually
treated with a combination of chemotherapy and radiotherapy. Treatment does not differ between EBV‐positive and EBV‐negative HL cases. In stage I and II disease the treatment generally leads to complete remission, while in stage III and IV the 5‐year disease free survival is about 70%. EBV‐positive adults aged between 50 to 74 years have inferior survival8.
PTLD develops in patients receiving immunosuppressive treatment following either solid organ transplantation or hematopoietic stem cell transplantation. Varying percentages of PTLDs are EBV‐positive9–11, with decreasing percentage of EBV‐positive cases over the
years10,12. EBV‐positive PTLDs accounted for more than 90% of the cases prior to 1995 and
this percentage decreased to 52% in the period of 2008‐201310,12. One of the risk factors
for PTLD is being sero‐negative for EBV prior to transplant. PTLDs are categorized into four subtypes, namely non‐destructive, polymorphic, monomorphic and classic Hodgkin lymphoma13. Treatment of PTLD includes reduction of immunosuppression or
Table 1. EBV‐associated malignancies. Associated
malignancies Target cell Latency type
Percentage of EBV positive
cases
Geographic location
Burkitt lymphoma B cell Latency I
> 95% Endemic (Sub‐ Saharan Africa) 15‐20% Sporadic (Western Europe, Northern America) 85% Southern America
Hodgkin lymphoma B cell Latency II
~30% Europe, Northern America > 60% Asia, Africa Diffuse large B‐cell
lymphoma B cell Latency II or III
5‐10% Asia
< 5% Western
Post‐transplant lymphoproliferative
disorders
B cell Latency III 60‐80% Worldwide
Plasmablastic
lymphoma B cell Latency I or II 50‐70 % Worldwide
Nasopharyngeal carcinoma Epithelial cell Latency II (or I/II) > 90% Endemic (South China, Southeast Asia) Gastric carcinoma Epithelial
cell Latency I ~10% Worldwide
Extranodal NK/T‐cell lymphoma
Natural
killer Latency I/II 90% Worldwide
NPC is the most common EBV‐associated epithelial malignancy with over 90% of cases being EBV positive. The incidence of NPC is high especially in endemic regions, i.e., Southern China and Southeast Asia. The estimated age‐standardized incidence rate in Asia is 2.1 per 100,000 per year, while it is 1.0 per 100,000 per year or less in other continents7.
Bidayuh, a minority population in Malaysia has one of the world’s highest incidence rate of 31 per 100,00014. NPC cases in endemic regions are predominantly non‐keratinizing
subtype and EBV‐positive. NPC has a higher incidence rate in males which is two‐ to three‐ fold higher than in females. The mainstay of treatment for NPC is radiotherapy or concurrent chemoradiotherapy in late stage disease. NPC is fairly sensitive to ionizing radiation, with 5‐year overall survival rate ranging from 78% to 100% for early stage and decreases remarkably to about 26% for late stage and recurrent cases15–17. Treatment of
metastatic NPC primarily involves palliative systemic chemotherapy and patients usually had median survival ranging from about seven to 34 months18.
3. EBV‐specific HLA associations
HLA genes encode for membrane proteins that present antigenic peptides to T cells and thereby are crucial factors for the regulation of the immune response. HLA proteins are divided into HLA class I molecules, which are expressed in almost all nucleated cells, and HLA class II molecules, for which expression is restricted to professional antigen presenting cells like dendritic cells, macrophages and B cells. HLA class I is responsible for the presentation of viral peptides to CD8+ T cells and can elicit cytotoxic responses. HLA class II presents antigens to CD4+ T cells which helps to orchestrate both humoral and cytotoxic immune responses.
There are nine classical HLA genes, including three class I (HLA‐A, ‐B, and –C) and six class II (HLA‐DRA, ‐DRB1,‐ DQA1, ‐DQB1, ‐DPA1 and ‐DPB1) molecules. HLA genes are highly polymorphic and allele frequencies vary between different ethnicities. Early studies demonstrated that certain alleles are risk alleles for HL patients19,20. Similarly, increased
frequencies of certain HLA alleles have also been demonstrated in NPC patients21. More
recently performed genome‐wide association studies have confirmed the strong susceptibility of variants in the HLA region for EBV‐positive HL22 and NPC23–25. Although no
genome‐wide association studies have been performed for PTLDs, several studies identified HLA associations with PTLD26–28.
The underlying mechanisms for the observed increased susceptibility to EBV‐associated diseases has been associated to efficiency of triggering EBV latency II‐specific cytotoxic immune responses. HLA‐A*01, HLA‐B*37 and HLA‐DRB1*10 are risk alleles for developing EBV‐positive HL, while HLA‐A*02:01 is a protective allele22,29. To date, HLA‐A*01‐restricted
EBV epitopes, as well as EBV‐specific CTL response have not been elucidated30,31. On the
other hand, a high affinity has been shown for the protective HLA‐A*02 allele that upon binding, resulted in an effective anti‐EBV immune response31. Interestingly, the HLA‐
A*02:07 allele has been shown to be a risk allele in both EBV‐positive HL and NPC. Although this risk allele differs at only one amino acid position from the protective HLA‐ A*02:01 allele, it is less efficient in inducing LMP2‐restricted CTL responses32. Individuals
carrying HLA‐B*46:01, along with HLA‐A*02:07 have an increased risk of developing NPC33.
However, studies on the susceptibility of the combination of HLA‐A*02:07 and HLA‐ B*46:01 showed contradictory results. One study reported that HLA‐A*02:07 is a risk allele even in the absence of HLA‐B*46:0134, while, another study demonstrated no effect
for individuals that have HLA‐A*02:07 alone without HLA‐B*46:0135. Both studies reported
that having HLA‐B*46:01 without HLA‐A*02:07 results in a mild protective effect and individuals with the HLA‐A*02:07‐HLA‐B*46:01 haplotype have an increased susceptibility to NPC35.
4. EBV‐based circulating biomarkers
Testing circulating biomarkers is especially valuable for detecting early stage cancers because of its non‐invasive nature. For EBV positive cancers, testing presence of EBV‐ derived biomarkers may result in high sensitivity as most infected cells have high EBV copy numbers. An overview of the sensitivity and specificity of commonly used EBV biomarkers to detect EBV‐associated cancers is shown in Table 2.
Table 2. Commonly studied circulating EBV biomarkers in EBV‐associated diseases. Biomarker Disease Sensitivity Specificity
VCA‐IgA NPC 79.8 % – 91.9 % 70.9 % – 89.5% EA‐IgA NPC 75 % – 92.6 % 90.8 % – 94.7 % EA‐IgG NPC 85.2% 82.3 % EBNA1‐IgA NPC 80.0 % – 90.7 % 80.0 % – 92.0 % EBV DNA NPC, HL, PTLD 58.7 % – 96.5 % 66.7 % – 100 % 4.1. EBV antibodies
EBV serology tests to determine the presence of antibodies against viral components showed that EBV‐associated cancer patients have higher EBV antibody titers as compared to controls36,37. The antibodies that are normally tested include those directed against viral
capsid antigen (VCA), EBV‐nuclear antigen (EBNA) and early antigen (EA). These proteins are expressed at different stages of the EBV life cycle. VCA and EA are expressed during lytic cycle, while EBNA1, which is essential for the persistence of the EBV genome in the host cell, is expressed during the latent stage. In NPC patients, the EBV antibody titers were positively correlated with tumor stage38. Probability of relapse was higher in patients
with increased IgG and IgA antibodies to EA in blood samples obtained one year after
4.2. EBV DNA
EBV DNA was detected in plasma of patients with EBV‐associated diseases such as HL, PTLD and NPC40–43. Presence of plasma EBV DNA in NPC patients had prognostic value,
with high plasma EBV DNA loads in pre‐treatment, during‐treatment and in post‐ treatment being associated with poor survival44. In HL, a decrease in circulating EBV DNA load was observed in patients who responded to treatment, while an increase of the EBV DNA load was shown in patients who did not respond to treatment42. In another HL study, presence of EBV DNA in pre‐treatment plasma was shown to be associated with inferior failure‐free survival in multivariate analysis40. In view of high EBV positivity in PTLD cases, EBV DNA is frequently used to monitor high‐risk post‐transplant patients. High EBV DNA load is often seen before presentation of clinical symptoms of PTLD45, hence preemptive treatment could be applied in these patients to halt the development of PTLD46,47. 4.3. EBV‐derived microRNAs
MicroRNA (miRNAs) are short non‐coding RNAs that alter gene expression at the post‐ transcriptional level by either inducing mRNA degradation or by repression of translation. Target recognition is dependent on sequence homology, which in general is high in the seed region of the miRNA, i.e., nucleotide 2‐7. The expression of miRNAs is dysregulated in many diseases including cancers. In accordance with this, tumor suppressors or oncogenic roles have been shown for many miRNAs.
EBV‐derived miRNAs were first described in 200448. These miRNAs were shown to target
both viral and human mRNAs and regulate expression in the same way as human miRNAs. In EBV‐associated malignancies, EBV‐derived miRNAs were detected in primary tumor tissue of NPC49, GC50, PTLD51and HL52 as well as in the circulation, e.g., blood plasma,
serum and in extracellular vesicles. Thus, EBV‐derived miRNAs might potentially be used as biomarkers for EBV‐associated cancers.
5. Tumor‐cell derived circulating biomarkers
5.1 Cell‐free DNA
Cell‐free (cf)DNA is a term that is used for DNA fragments released into the blood circulation from cells undergoing apoptosis, necrosis or via active secretion53. In healthy
individuals, cfDNA is considered to be derived from apoptotic cells, cleaved by endonucleases in between the nucleosomes that leads to fragments that are approximately 167 bp in size. On the other hand, DNA released from tumor cells originates from cell death that occurs as a result of necrosis, autophagy or mitotic catastrophe. These circulating tumor (ct)DNA differ in size and can range from 70 to 200 bp or even be up to 30 kb.
Cancer patients were shown to have higher levels of cfDNAs as compared to controls already in 197754. It was suggested that ctDNA constitutes a proportion of the total cfDNA
amount. More recent studies indeed confirmed presence of ctDNA in cancer patients based on detection of copy number losses and gains55,56 and somatic mutations57 in
plasma samples that were similar to those observed in tumor tissue. In recent years, next generation sequencing technology greatly increased knowledge on ctDNA and its value as a clinical biomarker. A few studies showed presence of genomic aberrations in cfDNA of HL patients and showed that these aberrations correspond to those found in paired primary tissue samples58,59.
As the majority of NPC cases are EBV positive, most studies are focused on circulating EBV DNA as a biomarker. The utilization of non‐EBV cfDNA as biomarker in NPC is less explored with exception of studies defining hypermethylation profile. Hypermethylation of tumor suppressor genes is frequently detected in cancers including NPC. The cfDNA methylation profile could be used as a potential biomarker in addition to EBV DNA for early detection of NPC. The sensitivity to detect early stage NPC was improved from 65% to 80% with the addition of EBV DNA to the methylation panel60. Similar to NPC, the presence and
potential clinical value of cfDNA in PTLD is largely unexplored.
5.2 Other biomarkers
Thymus and Activation Regulated Chemokine (TARC) is a chemokine that is produced in high amounts by the tumor cells of HL and can be detected at high levels in blood samples of the vast majority of HL patients. TARC levels remain high in HL patients that were unresponsive to treatment and were re‐elevated in patients with relapsed disease61,62.
High TARC levels at diagnosis have been correlated with negative prognosis63.
A study demonstrated that a model with three long non‐coding (lnc)RNAs MALAT1, AFAP1‐AS1 and AL359062 showed high sensitivity in discriminating NPC from controls. Higher levels of these lncRNAs were observed in EBV‐positive NPC as compared with EBV‐ negative NPC. The levels of these lncRNAs were elevated with tumor progression and reduced tremendously after treatment64.
6. Scope of the thesis
This thesis focuses on two EBV‐associated malignancies that both display a latency type II infection program, i.e., HL and NPC. In addition, PTLD which is commonly associated with EBV is included. The main aims of this thesis are to explore i) risk factors of HL and NPC, and ii) biomarkers in NPC, HL and PTLD.
Unlike most malignancies, HL and NPC both have an extremely abundant infiltration of immune cells in the tumor microenvironment. The presence and relevance of these cells in the tumor microenvironment has been reviewed in Chapter 2 of this thesis. Next to HL and NPC, GC, another common EBV‐associated malignancy, has been included in this chapter.
In Chapter 3 and Chapter 4, we studied the association between expression of HLA on the tumor cells in relation to the phenotype of known susceptibility HLA alleles in HL (Chapter 3) and NPC (Chapter 4) patients. The hypotheses of these studies were that risk allele carriers have selective pressure to retain HLA expression while protective allele carriers have pressure to lose expression of HLA to avoid recognition by cells of the immune system.
In Chapter 5, the value of new and existing circulating biomarkers for NPC have been compared systematically. Plasma biomarkers including EBV antibodies, EBV DNA and miRNAs were evaluated to compare their diagnostic and prognostic value.
In Chapter 6, we explored the feasibility of using nasal washings as a novel and non‐ invasive method to detect NPC biomarkers. Nasal washings were used to detect both EBV DNA and NPC‐associated miRNAs. We hypothesized that due to the proximity of the tumor site to the sampling site, tumor‐derived molecules (i.e., EBV DNA and miRNAs) might be detectable. This method might be particularly useful in countries with high NPC incidence but low socio‐economic status where accessibility to healthcare facilities is limited.
In Chapter 7 and Chapter 8, we explored the feasibility of using cfDNA as a disease biomarker in HL and PTLD patients. The aim was to detect copy number variations and EBV in retrospectively collected plasma samples with next‐generation sequencing.
In Chapter 9, we summarize our studies and present general conclusions based on our findings. In addition, we discuss our findings and present future perspectives.
References
1. Connolly, S. A., Jackson, J. O., Jardetzky, T. S. & Longnecker, R. Fusing structure and function: a structural view of the herpesvirus entry machinery. Nat. Rev. Microbiol. 9, 369–381 (2011).
2. Chesnokova, L. S., Nishimura, S. L. & Hutt‐Fletcher, L. M. Fusion of epithelial cells by Epstein‐Barr virus
proteins is triggered by binding of viral glycoproteins gHgL to integrins αvβ6 or αvβ8. Proc. Natl. Acad. Sci. 106, 20464–20469 (2009).
3. Zhu, Q. et al. Advances in pathogenesis and precision medicine for nasopharyngeal carcinoma.
MedComm mco2.32 (2021) doi:10.1002/mco2.32. 4. Shannon‐Lowe, C. D., Neuhierl, B., Baldwin, G., Rickinson, A. B. & Delecluse, H.‐J. Resting B cells as a transfer vehicle for Epstein‐Barr virus infection of epithelial cells. Proc. Natl. Acad. Sci. 103, 7065–7070 (2006). 5. Hutt‐Fletcher, L. M. The Long and Complicated Relationship between Epstein‐Barr Virus and Epithelial Cells. J. Virol. 91, e01677‐16‐ (2017). 6. Balfour, H. H., Dunmire, S. K. & Hogquist, K. A. Infectious mononucleosis. Clin. Transl. Immunol. 4, e33 (2015).
7. Ferlay, J. et al. Global Cancer Observatory: Cancer Today. Lyon, France: International Agency for
Research on Cancer. https://gco.iarc.fr/today (2018).
8. Diepstra, A. et al. Latent Epstein‐Barr virus infection of tumor cells in classical Hodgkin’s lymphoma predicts adverse outcome in older adult patients. J. Clin. Oncol. 27, 3815–3821 (2009). 9. Kinch, A. et al. A population‐based study of 135 lymphomas after solid organ transplantation: The role of Epstein‐Barr virus, hepatitis C and diffuse large B‐cell lymphoma subtype in clinical presentation and survival. Acta Oncol. (Madr). 53, 669–679 (2014). 10. Luskin, M. R. et al. The Impact of EBV Status on Characteristics and Outcomes of Posttransplantation Lymphoproliferative Disorder. Am. J. Transplant. 15, 2665–2673 (2015). 11. Leblond, V. et al. Posttransplant lymphoproliferative disorders not associated with Epstein‐Barr virus: a distinct entity? J. Clin. Oncol. 16, 2052–2059 (1998). 12. Nelson, B. P. et al. Epstein–Barr Virus‐Negative Post‐Transplant Lymphoproliferative Disorders. Am. J. Surg. Pathol. 24, 375–385 (2000). 13. Swerdlow, S. H., Webber, S., Chadburn, A. & Ferry, J. A. Post‐transplant lymphoproliferative disorders
(PTLD). in World Health Organization Calssification of Tumours of Haematopoietic and Lymphoid Tissues (eds. Swerdlow, S. et al.) 453–462 (International Agency for Research on Cancer, 2017). 14. Devi, B. C. R., Pisani, P., Tang, T. S. & Parkin, D. M. High incidence of nasopharyngeal carcinoma in
native people of Sarawak, Borneo Island. Cancer Epidemiol. Biomarkers Prev. 13, 482–6 (2004). 15. Cheah, S. K., Lau, F. N., Yusof, M. M. & Phua, V. C. E. Treatment Outcome with Brachytherapy for
Recurrent Nasopharyngeal Carcinoma. Asian Pacific J. Cancer Prev. 14, 6513–6518 (2013).
16. El‐Sherbieny, E., Rashwan, H., Lubis, S. H. & Choi, V. J. Prognostic factors in patients with
nasopharyngeal carcinoma treated in Hospital Kuala Lumpur. Asian Pacific J. Cancer Prev. 12, 1739–43 (2011). 17. Ee Phua, V. C. et al. Treatment Outcome for Nasopharyngeal Carcinoma in University Malaya Medical Centre from 2004‐2008. Asian Pacific J. Cancer Prev. 14, 4567–4570 (2013). 18. Chan, O. S. H. & Ngan, R. K. C. Individualized treatment in stage IVC nasopharyngeal carcinoma. Oral Oncol. 50, 791–797 (2014).
19. Perlin, E. & O’Donnell, M. Another Observation of Increased Frequency of HL‐A 5 and HL‐A 8 in
Hodgkin’s Disease. Am. J. Clin. Pathol. 64, 277.2‐278 (1975).
20. Hafez, M. M. et al. The value of HLA phenotypes in the prognosis of Hodgkin’s lymphoma. Int. J. Cancer
36, 19–22 (1985).
21. Chan, S. H., Day, N. E., Kunaratnam, N., Chia, K. B. & Simons, M. J. HLA and nasopharyngeal carcinoma
in chinese —A further study. Int. J. Cancer 32, 171–176 (1983).
22. Diepstra, A. et al. Association with HLA class I in Epstein‐Barr‐virus‐positive and with HLA class III in Epstein‐Barr‐virus‐negative Hodgkin’s lymphoma. Lancet 365, 2216–2224 (2005).
23. Tse, K.‐P. et al. Genome‐wide Association Study Reveals Multiple Nasopharyngeal Carcinoma‐
Associated Loci within the HLA Region at Chromosome 6p21.3. Am. J. Hum. Genet. 85, 194–203 (2009).
24. Tang, M. et al. The principal genetic determinants for nasopharyngeal carcinoma in China involve the
HLA class I antigen recognition groove. PLoS Genet. 8, e1003103 (2012).
NPC. Chinese Clin. Oncol. 5, 1–8 (2016). 26. Reshef, R. et al. Association of HLA Polymorphisms with Post‐transplant Lymphoproliferative Disorder in Solid‐Organ Transplant Recipients. Am. J. Transplant. 11, 817–825 (2011). 27. Vase, M. Ø. et al. HLA Associations and Risk of Posttransplant Lymphoproliferative Disorder in a Danish Population‐Based Cohort. Transplant. Direct 1, e25 (2015). 28. Kinch, A., Sundström, C., Tufveson, G. & Glimelius, I. Association between HLA‐A1 and ‐A2 types and Epstein–Barr virus status of post‐transplant lymphoproliferative disorder. Leuk. Lymphoma 57, 2351– 2358 (2016).
29. Niens, M. et al. HLA‐A*02 is associated with a reduced risk and HLA‐A*01 with an increased risk of developing EBV+ Hodgkin lymphoma. Blood 110, 3310–3315 (2007).
30. Rickinson, A. B. & Moss, D. J. Human cytotoxic T lymphocyte responses to Epstein‐Barr virus infection.
Annu. Rev. Immunol. 15, 405–431 (1997).
31. Brennan, R. M. & Burrows, S. R. A mechanism for the HLA‐A*01–associated risk for EBV+ Hodgkin
lymphoma and infectious mononucleosis. Blood 112, 2589–2590 (2008).
32. Lee, S. P., Tierney, R. J., Thomas, W. A., Brooks, J. M. & Rickinson, A. B. Conserved CTL epitopes within
EBV latent membrane protein 2: a potential target for CTL‐based tumor therapy. J Immunol 158, 3325– 3334 (1997).
33. Glimelius, I. et al. Predictors of histology, tissue eosinophilia and mast cell infiltration in Hodgkin’s Lymphoma ‐ a population‐based study. Eur. J. Haematol. 87, 208–216 (2011).
34. Yu, K. J. et al. Association of human leukocyte antigens with nasopharyngeal carcinoma in high‐risk
multiplex families in Taiwan. Hum. Immunol. 70, 910–914 (2009).
35. Tang, M. et al. Haplotype‐dependent HLA susceptibility to nasopharyngeal carcinoma in a Southern
Chinese population. Genes Immun. 11, 334–342 (2010).
36. Henle, G. & Henle, W. Epstein‐barr virus‐specific IgA serum antibodies as an outstanding feature of nasopharyngeal carcinoma. Int. J. Cancer 17, 1–7 (1976).
37. Evans, A. S. & Gutensohn, N. M. A population‐based case‐control study of EBV and other viral
antibodies among persons with Hodgkin’s disease and their siblings. Int. J. Cancer 34, 149–157 (1984).
38. Xia, C., Zhu, K. & Zheng, G. Expression of EBV antibody EA‐IgA, Rta‐IgG and VCA‐IgA and SA in serum
and the implication of combined assay in nasopharyngeal carcinoma diagnosis. Int. J. Clin. Exp. Pathol.
8, 16104–10 (2015).
39. De‐Vathaire, F. et al. Prognostic value of ebv markers in the clinical management of nasopharyngeal
carcinoma (NPC): A multicenter follow‐up study. Int. J. Cancer 42, 176–181 (1988).
40. Kanakry, J. A. et al. Plasma Epstein‐Barr virus DNA predicts outcome in advanced Hodgkin lymphoma :
correlative analysis from a large North American cooperative group trial. 121, 3547–3554 (2014).
41. Beck, R. et al. Detection of Epstein‐Barr virus DNA in plasma from patients with lymphoproliferative
disease after allogeneic bone marrow or peripheral blood stem cell transplantation. J. Clin. Microbiol.
37, 3430–1 (1999).
42. Lei, K. I. K., Chan, L. Y. S., Chan, W. Y., Johnson, P. J. & Dennis Lo, Y. M. Circulating cell‐free Epstein‐Barr virus DNA levels in patients with EBV‐associated lymphoid malignancies. Ann. N. Y. Acad. Sci. 945, 80– 83 (2001).
43. Lo, Y. M. et al. Quantitative analysis of cell‐free Epstein‐Barr virus DNA in plasma of patients with nasopharyngeal carcinoma. Cancer Res 59, 1188–1191 (1999).
44. He, S. S. et al. Dynamic changes in plasma Epstein–Barr virus DNA load during treatment have
prognostic value in nasopharyngeal carcinoma: a retrospective study. Cancer Med. 7, 1110–1117 (2018).
45. Colombini, E. et al. Viral load of EBV DNAemia is a predictor of EBV‐related post‐transplant
lymphoproliferative disorders in pediatric renal transplant recipients. Pediatr. Nephrol. 32, 1433–1442 (2017).
46. van Esser, J. W. J. et al. Prevention of Epstein‐Barr virus–lymphoproliferative disease by molecular
monitoring and preemptive rituximab in high‐risk patients after allogeneic stem cell transplantation. Blood 99, 4364–4369 (2002).
47. Worth, A. et al. Pre‐emptive rituximab based on viraemia and T cell reconstitution: a highly effective
strategy for the prevention of Epstein–Barr virus‐associated lymphoproliferative disease following stem cell transplantation. Br. J. Haematol. 155, 377–385 (2011).
48. Pfeffer, S. et al. Identification of virus‐encoded microRNAs. Science 304, 734–6 (2004).
Carcinoma. J. Virol. 83, 2357–2367 (2009).
50. Kim, D. N. et al. Expression of Viral MicroRNAs in Epstein‐Barr Virus‐Associated Gastric Carcinoma. J. Virol. 81, 1033–1036 (2007).
51. Fink, S. E. K. et al. A Comprehensive Analysis of the Cellular and EBV‐Specific MicroRNAome in Primary
CNS PTLD Identifies Different Patterns Among EBV‐Associated Tumors. Am. J. Transplant. 14, 2577– 2587 (2014).
52. Sakamoto, K. et al. Next‐generation sequencing of miRNAs in clinical samples of Epstein‐Barr virus‐
associated B‐cell lymphomas. Cancer Med. 6, 605–618 (2017).
53. Thakur, B. K. et al. Double‐stranded DNA in exosomes: a novel biomarker in cancer detection. Cell Res.
24, 766–769 (2014).
54. Leon, S. A., Shapiro, B., Sklaroff, D. M. & Yaros, M. J. Free DNA in the Serum of Cancer Patients and the
Effect of Therapy. Cancer Res. 37, 646–650 (1977).
55. Stroun, M. et al. Neoplastic Characteristics of the DNA Found in the Plasma of Cancer Patients.
Oncology 46, 318–322 (1989).
56. Vandenberghe, P. et al. Non‐invasive detection of genomic imbalances in Hodgkin/Reed‐Sternberg cells
in early and advanced stage Hodgkin’s lymphoma by sequencing of circulating cell‐free DNA: a technical proof‐of‐principle study. Lancet Haematol. 2, e55–e65 (2015).
57. Vasioukhin, V. et al. Point mutations of the N‐ras gene in the blood plasma DNA of patients with
myelodysplastic syndrome or acute myelogenous leukaemia. Br. J. Haematol. 86, 774–779 (1994).
58. Spina, V. et al. Circulating tumor DNA reveals genetics, clonal evolution and residual disease in classical
Hodgkin lymphoma. Blood 131, blood‐2017‐11‐812073 (2018).
59. Desch, A.‐K. et al. Genotyping circulating tumor DNA of pediatric Hodgkin lymphoma. Leukemia (2019)
doi:10.1038/s41375‐019‐0541‐6.
60. Yang, X. et al. Epigenetic markers for noninvasive early detection of nasopharyngeal carcinoma by
methylation‐sensitive high resolution melting. Int. J. Cancer 136, E127–E135 (2015).
61. Plattel, W. J. et al. Plasma thymus and activation‐regulated chemokine as an early response marker in
classical Hodgkin’s lymphoma. Haematologica 97, 410–415 (2012).
62. Plattel, W. J. et al. Interim thymus and activation regulated chemokine versus interim 18 F‐
fluorodeoxyglucose positron‐emission tomography in classical Hodgkin lymphoma response evaluation. Br. J. Haematol. 190, 40–44 (2020).
63. Weihrauch, M. R. et al. Elevated Serum Levels of CC Thymus and Activation‐Related Chemokine (TARC)
in Primary Hodgkin’s Disease: Potential for a Prognostic Factor. Cancer Res. 65, 5516–5519 (2005).
64. He, B. et al. Serum long non‐coding RNAs MALAT1, AFAP1‐AS1 and AL359062 as diagnostic and
prognostic biomarkers for nasopharyngeal carcinoma. Oncotarget 8, 41166–41177 (2017).
