Epstein–Barr Virus Load in the Saliva of Patients with Oropharyngeal Cancer—Could It Have Prognostic Significance?

The discovery of EBV over 60 years ago was a breakthrough in understanding the development of many cancers, including head and neck cancers, but many processes remain to be explained. Scientists, looking for new biomarkers, have recently been paying a lot of attention to salivary EBV DNA load. Oral EBV DNA load may indicate not only EBV lytic replication activity but also potentially correlate with EBV-related disease progression. Numerous studies indicate that saliva may be an alternative clinical material for both early diagnosis and prognosis of head and neck cancer (HNC). Therefore, we assessed salivary EBV DNA in oropharyngeal cancer patients (OPSCC). We observed that the EBV DNA level was higher in the group of EBV-positive OPSCC than in EBV-negative subjects and was also higher in more advanced clinical stages. In addition, the salivary EBV DNA load was positively correlated with the concentration of anti-EBV antibodies, MMP3, MMP9, and NF-κB. The ROC analysis confirmed the diagnostic accuracy of salivary EBV DNA load. Our preliminary results indicate the usefulness of determining EBV DNA load in saliva as a non-invasive prognostic biomarker in EBV-positive oropharyngeal cancer, but confirmation in larger cohort studies is required.

Authors

Institutions

Publication Details

Journal
Viruses
Published
2025-11-20
DOI
https://doi.org/10.3390/v17111523
Primary Topic
Viral-associated cancers and disorders
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Epstein–Barr Virus Load in the Saliva of Patients with Oropharyngeal Cancer—Could It Have Prognostic Significance?

Magdalena Góralczyk, M Jarosz, Małgorzata Polz‐Dacewicz, Bartłomiej Drop et al.
Viruses
Viral-associated cancers and disorders
article

Epstein–Barr Virus Load in the Saliva of Patients with Oropharyngeal Cancer—Could It Have Prognostic Significance?

Magdalena Góralczyk, M Jarosz, Małgorzata Polz‐Dacewicz, Bartłomiej Drop, Karol Paradowski
article en

Abstract

The discovery of EBV over 60 years ago was a breakthrough in understanding the development of many cancers, including head and neck cancers, but many processes remain to be explained. Scientists, looking for new biomarkers, have recently been paying a lot of attention to salivary EBV DNA load. Oral EBV DNA load may indicate not only EBV lytic replication activity but also potentially correlate with EBV-related disease progression. Numerous studies indicate that saliva may be an alternative clinical material for both early diagnosis and prognosis of head and neck cancer (HNC). Therefore, we assessed salivary EBV DNA in oropharyngeal cancer patients (OPSCC). We observed that the EBV DNA level was higher in the group of EBV-positive OPSCC than in EBV-negative subjects and was also higher in more advanced clinical stages. In addition, the salivary EBV DNA load was positively correlated with the concentration of anti-EBV antibodies, MMP3, MMP9, and NF-κB. The ROC analysis confirmed the diagnostic accuracy of salivary EBV DNA load. Our preliminary results indicate the usefulness of determining EBV DNA load in saliva as a non-invasive prognostic biomarker in EBV-positive oropharyngeal cancer, but confirmation in larger cohort studies is required.

VirusesVol. 17(11)
Medical University of Lublin (PL), University of Life Sciences in Lublin (PL), University of Economics and Innovation (PL)
Uniwersytet Medyczny w Lublinie
Openalex Percentile: Top 52%
Viral-associated cancers and disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.