Evidence map›Paper›PMID 42458528›Full record

ReviewInfectious agents and cancer2026

Mechanistic interactions between Plasmodium falciparum and Epstein-Barr virus in endemic Burkitt Lymphoma pathogenesis: a narrative review (2010-2026).

Natalia A Msami

Abstract readReview
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In one paragraph

Review in Infectious agents and cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Natalia A MsamiSchool of Public Health, University of California, Berkeley, CA, USA. talia_msami@berkeley.edu.ORCID https://orcid.org/0009-0008-7303-8102

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endemic Burkitt Lymphoma, characterized by an MYC translocation during B-cell activation, is an aggressive, fast-proliferating cancer that predominantly accounts for more than half of all childhood cancers in sub-Saharan Africa. Although a well-established epidemiologic association exists between Epstein-Barr virus infection and Plasmodium falciparum malaria, disentangling their mechanistic interactions in the pathogenesis of endemic Burkitt Lymphoma remains difficult. To address this challenge, a comprehensive narrative review of studies published between 2010 and 2026, was conducted. Evidence from mouse models, in vitro and ex vivo studies was synthesized to identify potential key effector cells, cytokine groups, and molecular pathways likely involved in fostering an immune environment that supports lymphomagenesis. The synthesized evidence informed the development of a speculative multi-hit model of endemic Burkitt Lymphoma, in which chronic Plasmodium falciparum exposure reconfigures the immune landscape through sustained inflammation, altered effector cell function, and impaired immune surveillance. Within this framework, these changes may subsequently facilitate Epstein-Barr virus persistence, intermittent B-cell reactivation, and cumulative genomic instability, ultimately increasing the likelihood of MYC translocations and the development of endemic Burkitt Lymphoma. The review also proposes incorporating emerging immune effector populations into this conceptual multi-hit model. Although several of the mechanistic relationships explored remain inferential, the framework identifies potential therapeutic and preventive immune targets that warrant further investigation in experimental and longitudinal human studies in high-burden regions.

Indexed as

Endemic Burkitt LymphomaEpstein-Barr virusMalariaPlasmodium falciparumViral-parasitic interactions

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.