Epstein-Barr virus (EBV) and EBV-associated lymphomas

From MicrobeWiki, the student-edited microbiology resource

By Yangyang Liu (Kenyon '23)

Introduction

Figure 1. This electron microscopy visualization depicts three ubiquitous γ-herpes virus EBV. The visual credit for this image belongs to NIAID [1].

Epstein-Barr virus (EBV), formally called Human gammaherpesvirus 4, are a group within the Lymphocryptovirus genus of the Herpesviridae family. EBVise double-stranded DNA viruses that use RNA polymerase for mRNA synthesis based on their negative-strand as the template. EBV Infection occurs through oral transfer of saliva as well as genital secretions and more than 90% of normal adults would gain adaptive immunity after their primary EBV infection. The remaining EBV virus would remain in an asymptomatic latent state for a lifetime within resting B-cells, and a healthy adult with a working immune system would be able to contain the infection with the help of their cytotoxic T cells (CTLs), lymphocyte CD8+ and CD4+, and natural killer (NK) cells [1]. Only a small subset encountering life-threatening diseases due to them unable in maintaining the virus within the latent state. In an uncontrolled situation, EBV-driven lymphoproliferative disorders and lymphomas could develop with the patients. EBV-associated cancers are a common example among the ~15% of all human cancers involving a virus infection [2].

Some of the most well-known illnesses that are caused by EBV are mononucleosis, Burkitt’s lymphoma, Hodgkin’s lymphoma, non-Hodgkin lymphoma, post-transplant lymphoproliferative disease (PTLD), nasopharyngeal carcinoma, and numerous other types of cancer [3]. So far, there is limited success in antivirals development to combat EBV infection. With EBV’s putative role in carcinogenesis, it is important to learn about the mechanisms by which the virus alters host cell characteristics and thus evades the immune system of the hosts. This page investigates how different latency patterns of EBV infection could lead to numerous types of lymphoma, the EBV-associated NK-cell lymphoproliferative diseases (LPD), as well as possible treatment for the specific LPD Chronic active EBV infection (CAEBV).

Identifying Latency Patterns of EBV Infection

Figure 2. A diagram of an EBV dsDNA episome including the main viral latent proteins EBNAs and LMPs. EBNA1 is expressed under the alternative promoters Wp, Cp and Qp in a latency type-specific manner. The orange block indicates the location of the origin of replication, oriP. The green arrow denotes the transcription direction during latency III. The red arrow indicates the direction of transcription for EBNA1, which is activated during latency I and II. [2].

During primary in vivo infection, EBV preferentially infects B-lymphocytes by binding to the CD21 receptor on the cell surface, it will also bind to HLA class II molecules as a co-receptor. In most of the patients, the EBV episome would remain in the latent cycle in resting memory B cells after the primary infection while developing strategies to alter the pattern of the host’s cytotoxic T-lymphocyte (CTL) gene expression. Although there are nearly 100 viral proteins in a regular EBV genome, after infection, the infected resting memory B cells will limit the gene expression to nine viral latent proteins to evade immune recognition. The nine viral latent proteins are composed of six nuclear antigens EBNAs-1, -2, -3a, -3b, -3c, and -LP as well as three latent membrane proteins LMP-1, -2a, -2b. 2 small non-coding RNAs, EBER-1, EBER-2, and BamHI-A rightward transcripts (BART) are also expressed. The expression of nuclear antigens maintains the viral genome, they are also responsible for controlling the expression patterns of the three latent membrane proteins. Different expression combinations of EBNAs and LMPs can lead to different EBV latency programs and the associated lymphomas [4]. Type I latency is only seen in Burkitt’s lymphoma (BL) and selectively express EBNA-1. Type II latency expresses EBNA-1 along with LMP-1 and LMP-2, the common lymphoma for type II latency to be found are Hodgkin’s lymphoma (HL) and peripheral T-cell lymphoma (PTCL). The third and last EBV latency program type III, is commonly found in PTLD and AIDS-related lymphoma. All nine EBV latent proteins are expressed in type III latency [4].


MiRNAs for Viral Latency Identification

The EBV latency type classification is still ongoing work, as the traditional classification system stated above is only based on a few molecular markers of EBV latency which introduces limitations to typing of EBV latency types. As different latent infections are associated with different tumors, inaccurate latency identification is an academic and clinical issue. MicroRNAs (MiRNAs) species have been found in EBV-infected cells, and a total of 44 EBV miRNA have been reported to be involved in EBV viral latency and tumorigenesis. miRNAs are small non-coding RNAs that broadly regulate gene expression[5].Viral miRNAs are usually hard-to-detect and are 19-23 nt in length [6]. They are crucial in maintaining persistent EBV viral infections by promoting tumorigenesis in hosts and down-regulating viral early gene expression. Furthermore, the viral miRNAs are also able to regulate host gene expression at the post-transcriptional level to assist the virus in evading host immune responses. EBV was first found in 2004 to be encoding viral miRNAs, and the to-date 44 mature EBV miRNAs are produced and expressed as two independent transcripts from BHRF1 and BARTs intron prior to splicing [6]. Those abundant markers are a hopeful option to be turned into biomarkers for EBV latency types identification in the future.

Figure 3. qRT-PCR quantitative analysis of all EBV viral miRNA species' comprehensive expression pattern per latency type. Latency I, II, and III miRNA transcriptome's respective portions are marked below (miR-BHRF1, miR-BAR clusters I/II, miR-BAR2, and B95-8 deletion region). [3].

In a recent study, highly sensitive and specific quantitative real-time RT-PCR (qRT-PCR) had been combined with microarray assay for the analysis of patterns of EBV miRNA transcriptomes that are associated with EBV patency types in tumor cells. BHRF1 has been shown to drive chemoresistance and lymphomagenesis by inhibiting multiple cellular pro-apoptotic proteins, thus learning about its expression pattern can help to identify potentially therapeutic targets within BHRF1 [7]. The general BHRF1 miRNA expression is dependent on the viral latency type as well as the cell’s historical origin. In Figure 3, it can be seen that a nearly 100-fold difference is present between all tested cell lines. Within each latency type and cell lines, BHRF-1 miRNA can still have more than a 50-fold difference despite the fact that those miRNAs were transcribed together as a single transcript. The difference in expression level indicates that the BHRF1 family is latency III dependent as it is almost non-expressing within latency type II and low in expression in latency I [6]. The BamHI A rightward transcripts (BART) family, on the other hand, was expressed differently with the three latency types (with the exception of Namalwa cells). As the main cell source were tumors, this suggests that the BART family plays different roles in tumors with the different types of latency. The BART family also showed overall highest amount of expression within the latency type II cell line C666-1, indicating that they may contribute more to the NPC tumorigenesis (which is the origin of tumor cell line C666-1)[6]. Such findings have been shown in previous studies where BARTs are consistently and highly expressed in NPC [8]. Furthermore, the lack of expression within Namalwa BL cell line could indicate the occasional lost of EBV episomes within lymphoma cells after long-term culture. Overall, it can be seen that Figure 3 shows evidence indicating the functional role of EBV-encoded miRNA species in showing the expression trends of the EBV viral transcripts within the three latent types. These differentially expressed viral miRNAs are hopeful future molecular biomarkers of latent infection types identification. The BHRF1 family and BART family mentioned in particular could contributes greatly to epithelial tumors and to some lymphocyte tumors latency type differentiation and identification.



Spontaneous Latenty Type Transition Identification Using miRNAs

Figure 4. Heatmap clustering analysis of three latency types based on normalized qPCR data. Traditional biomarkers (EBNA1 promoters, Cp, Wp, Qp, and LMP1) indicates Latency group I for Daudi cells (upper left graph ). Clustering analysis based on all EBV miRNA species (lower left) and traditional and miRNA combined analysis indicates a transition from latency I to III of Daudi cells. [4].
Figure 5. Genotypic evaluation of the latency type I-III transition in Daudi cells. In contrast to latency I Akata(+) cells, Daudi cells had different levels of EBNA1 Wp activity and LMP1 expression (left). In addition, the average expression level pattern of the BHRF1 family in comparison to that of the BART family in the Daudi cell was in contrast to their patterns in Akata(+) cells (right).[5].


EBV is capable of switching latency types spontaneously in lymphoma cells in vitro. It has been difficult to detect and identify subtle latency transitions due to the lack of specificity and sensitivity of the traditional latency biomarkers. Researchers have tried using traditional biomarkers or miRNA alone, as well as the combination of both to increase the accuracy in detecting latency type switching among tumor cells. As stated in Figure 4, traditional markers alone indicated latency group I for the Burkitt's lymphoma cell line, Daudi [9]. On the other hand, EBV miRNA, as well as the traditional+miRNA combination, grouped the Daudi cells into latency group III. From the genotypic evaluation of the Daudi cells in comparison to the latent type I cell Akata (+), we are able to evaluate the accuracy of the clustering results from EBV miRNAs (Figure 5). Within Figure 5, it was clear that Daudi’s BHRF1 and BART family relative expression differs from the latent type I cell Akata (+). With the contrasting outcome of Daudi cells EBV viral transcript relative expression, it seems that there was a transition of the Daudi cells from type I to type III latency. It also seems that traditional viral latency biomarkers are an inadequate approach to distinguish the different EBV latency types, whereas the miRNA species that express differentially among latency types may fit the demands better.

EBV-associated rare NK/T-cell Lymphoproliferative Diseases

EBV is a B-lymphotropic virus, so it does not infect the T- and NK-cell lineages during its regular infection cycle in vivo [10]. However, ectopic T and/or NK cell infection does occur on very rare occasions, leading to EBV-associated T and NK-cell lymphoproliferative diseases (EBV+T/NK LPDs) that are characterized by the transformation and proliferation of EBV-infected T or NK cells [11]. The current ackowledged LPDs are classified into six categories, they are: chronic active EBV infection (CAEBV) of T- and NK-cell type, systemic EBV-positive T-cell lymphoma of childhood, aggressive NK-cell leukemia (ANKL), extranodal NK/T-cell lymphoma (ENKTL), nasal type, and primary EBV-positive nodal T/NK-cell lymphoma. Here we will focus on the study of CAEBV, since it is one of the LPDs that have a strong ethnic and geographical predilction towards Asians <ref=asian>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5597738/</ref>.

Chronic Active EBV Infection of T- and NK-cell Type (CAEBV)

Optimal Treatment for CAEBV

Conclusion

References



Authored for BIOL 238 Microbiology, taught by Joan Slonczewski, 2021, Kenyon College.