Plasma Epstein-Barr Virus (EBV) DNA Is a Biomarker for EBV-Positive Hodgkin's Lymphoma

Gandhi, Maher K.; Lambley, Eleanore; Burrows, Jacqueline M.; Dua, Ujjwal; Elliott, Suzanne; Shaw, Peter J.; Prince, H. Miles; Wolf, Max; Clarke, Kerrie; Underhill, Craig; Mills, Tony; Mollee, Peter; Gill, Devinder; Marlton, Paula; Seymour, John F.; Khanna, Rajiv

doi:10.1158/1078-0432.ccr-05-2008

Cited by 118 publications

(107 citation statements)

References 21 publications

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“…27 The association between EBV and Hodgkin's disease pathogenesis is well recognized 28 and EBV DNA can be detected in the plasma of patients with active disease. 29 However, in the present study, despite the fact that patients with Hodgkin's disease were transplanted with high tumor burden, none of them showed evidence of EBV infection in histological samples at the time of initial diagnosis and were all EBV PCR negative at the time of transplantation.…”

Section: Discussioncontrasting

confidence: 62%

EBV-associated post-transplant lymphoproliferative disorder after umbilical cord blood transplantation in adults with hematological diseases

Sanz

Arango

Senent

et al. 2013

Bone Marrow Transplant

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We analyzed the incidence, clinicopathological features, risk factors and prognosis of patients with EBV-associated post-transplant lymphoproliferative disorder (EBV-PTLD) in 288 adults undergoing umbilical cord blood transplantation (UCBT) at a single institution. Twelve patients developed proven EBV-PTLD at a median time of 73 days (range, 36-812). Three-year cumulative incidence (CI) of EBV-PTLD was 4.3% (95% CI: 1.9-6.7). All patients presented with extranodal involvement. Most frequently affected sites were the liver, spleen, central nervous system (CNS), Waldeyer's ring and BM in 7, 6, 4, 3 and 3 patients, respectively. One patient had polymorphic and 11 had monomorphic EBV-PTLD (7 diffuse large B-cell lymphomas not otherwise specified, 4 plasmablastic lymphomas). We confirmed donor origin and EBV infection in all histological samples. EBV-PTLD was the cause of death in 11 patients at a median time of 23 days (range, 1-84). The 3-year CI of EBV-PTLD was 12.9% (95% CI: 3.2-22.5) and 2.6% (95% CI: 0.5-4.7) for patients receiving reduced-intensity conditioning (RIC) and myeloablative conditioning, respectively (Po0.0001). In conclusion, adults with EBV-PTLD after UCBT showed frequent visceral and CNS involvement. The prognosis was poor despite routine viral monitoring and early intervention. An increased risk of EBV-PTLD was noted among recipients of RIC regimens.

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Section: Discussioncontrasting

confidence: 62%

EBV-associated post-transplant lymphoproliferative disorder after umbilical cord blood transplantation in adults with hematological diseases

Sanz

Arango

Senent

et al. 2013

Bone Marrow Transplant

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“…EBV association was confirmed via EBV‐encoded‐RNA in‐situ hybridization (EBER‐ISH), as described previously 22. Peripheral blood mononuclear cells (PBMCs) were isolated and cryopreserved in 90% fetal bovine serum (FBS) with 10% dimethylsulphoxide (DMSO).…”

Section: Methodsmentioning

confidence: 99%

The impact of HLA class I and EBV latency-II antigen-specific CD8+ T cells on the pathogenesis of EBV+ Hodgkin lymphoma

Jones

Wockner

Brennan

et al. 2015

Clinical and Experimental Immunology

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SummaryIn 40% of cases of classical Hodgkin lymphoma (cHL), Epstein–Barr virus (EBV) latency‐II antigens [EBV nuclear antigen 1 (EBNA1)/latent membrane protein (LMP)1/LMP2A] are present (EBV+cHL) in the malignant cells and antigen presentation is intact. Previous studies have shown consistently that HLA‐A*02 is protective in EBV+cHL, yet its role in disease pathogenesis is unknown. To explore the basis for this observation, gene expression was assessed in 33 cHL nodes. Interestingly, CD8 and LMP2A expression were correlated strongly and, for a given LMP2A level, CD8 was elevated markedly in HLA‐A*02– versus HLA‐A*02+ EBV+cHL patients, suggesting that LMP2A‐specific CD8+ T cell anti‐tumoral immunity may be relatively ineffective in HLA‐A*02– EBV+cHL. To ascertain the impact of HLA class I on EBV latency antigen‐specific immunodominance, we used a stepwise functional T cell approach. In newly diagnosed EBV+cHL, the magnitude of ex‐vivo LMP1/2A‐specific CD8+ T cell responses was elevated in HLA‐A*02+ patients. Furthermore, in a controlled in‐vitro assay, LMP2A‐specific CD8+ T cells from healthy HLA‐A*02 heterozygotes expanded to a greater extent with HLA‐A*02‐restricted compared to non‐HLA‐A*02‐restricted cell lines. In an extensive analysis of HLA class I‐restricted immunity, immunodominant EBNA3A/3B/3C‐specific CD8+ T cell responses were stimulated by numerous HLA class I molecules, whereas the subdominant LMP1/2A‐specific responses were confined largely to HLA‐A*02. Our results demonstrate that HLA‐A*02 mediates a modest, but none the less stronger, EBV‐specific CD8+ T cell response than non‐HLA‐A*02 alleles, an effect confined to EBV latency‐II antigens. Thus, the protective effect of HLA‐A*02 against EBV+cHL is not a surrogate association, but reflects the impact of HLA class I on EBV latency‐II antigen‐specific CD8+ T cell hierarchies.

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“…Aside from plasma EBV DNA [15], there is no predictive biomarker to bode the patient's response to the corresponding treatment with a reliable accuracy. This classification problem is intrinsically highly unbalanced, mainly due to the discrete sampling of the samples (number of patients), and also due to the fact that a high percentage of the patients are cured from this kind of malignancy.…”

Section: Resultsmentioning

confidence: 99%

On the prediction of Hodgkin lymphoma treatment response

et al. 2015

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-Martínez, jlfm@uniovi.es, 0034 985 103 199. AbstractPurpose: The cure rate in Hodgkin Lymphoma is high, but the response along the treatment is still unpredictable and is highly variable among patients. Detecting those patients that do not respond to the treatment at early stages could bring improvements in their treatment. This research tries to identify the main biological prognostic variables currently gathered at diagnosis, and designing a simple machine learning methodology to help physicians improving the treatment response assessment. Methods: We carried out a retrospective analysis of the response to treatment for a cohort of 263 Caucasians who were diagnosed with Hodgkin Lymphoma in Asturias (Spain). For that purpose, we used a list of 35 clinical and biological variables that are currently measured at diagnosis, before any treatment begins. To establish the list of most discriminatory prognostic variables for the treatment response we designed a machine learning approach based on two different feature selection methods (Fisher's ratio and Maximum Percentile Distance) and recursive feature elimination using a nearest-neighbor classifier (k-NN). The weights of the k-NN classifier are optimized using different terms of the confusion matrix (true and false positive rates) in order to minimize risk in the decisions. Results and conclusions: We found that the optimum strategy to predict treatment response in Hodgkin lymphoma consists in solving two

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Plasma Epstein-Barr Virus (EBV) DNA Is a Biomarker for EBV-Positive Hodgkin's Lymphoma

Cited by 118 publications

References 21 publications

EBV-associated post-transplant lymphoproliferative disorder after umbilical cord blood transplantation in adults with hematological diseases

EBV-associated post-transplant lymphoproliferative disorder after umbilical cord blood transplantation in adults with hematological diseases

The impact of HLA class I and EBV latency-II antigen-specific CD8+ T cells on the pathogenesis of EBV+ Hodgkin lymphoma

On the prediction of Hodgkin lymphoma treatment response

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