Comparison of saliva and blood derived cell free RNAs for detecting oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancer types around the world. Although OSCC can be diagnosed or monitored through tissue biopsy, this invasive procedure could cause considerable pain and discomfort to patients. As a preferable alternative, liquid biopsy offers less invasive diagnostics. In our study to enhance OSCC detection, we analyzed cell-free RNA (cfRNA) transcriptomes (mRNA, lncRNA) from blood (plasma) and saliva samples of individuals in three groups: OSCC group, oral benign tumor group, and a normal control group. Our transcriptomic profiling revealed that in the saliva group, CLEC2B was notably upregulated in the OSCC group compared to others, while DAZL, F9, and AC008735.2 were markedly downregulated. However, no OSCC-specific RNAs were identified in the blood (plasma) samples. Furthermore, OSCC group showed a higher neutrophil infiltration and lower B cells, CD4 + T cells (non-regulatory) and regulatory T cell (Tregs) infiltration in oral saliva environment when compared to the control groups. This study suggests that saliva might be a better liquid biopsy medium over blood (plasma) for cfRNA on detecting OSCC. CLEC2B, DAZL, F9, and AC008735.2 in saliva may serve as potential diagnostic liquid biomarkers for OSCC, warranting further investigation.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-02-07
DOI
https://doi.org/10.1038/s41598-025-88472-9
Citations
7
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
6.55
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparison of saliva and blood derived cell free RNAs for detecting oral squamous cell carcinoma

Manbin Xu, Hanwei Peng, Yuan Hu, Muyuan Liu
7 citations
Scientific Reports
Cancer-related molecular mechanisms research
6.55
article

Comparison of saliva and blood derived cell free RNAs for detecting oral squamous cell carcinoma

Manbin Xu, Hanwei Peng, Yuan Hu, Muyuan Liu
article en
7 citations

Abstract

Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancer types around the world. Although OSCC can be diagnosed or monitored through tissue biopsy, this invasive procedure could cause considerable pain and discomfort to patients. As a preferable alternative, liquid biopsy offers less invasive diagnostics. In our study to enhance OSCC detection, we analyzed cell-free RNA (cfRNA) transcriptomes (mRNA, lncRNA) from blood (plasma) and saliva samples of individuals in three groups: OSCC group, oral benign tumor group, and a normal control group. Our transcriptomic profiling revealed that in the saliva group, CLEC2B was notably upregulated in the OSCC group compared to others, while DAZL, F9, and AC008735.2 were markedly downregulated. However, no OSCC-specific RNAs were identified in the blood (plasma) samples. Furthermore, OSCC group showed a higher neutrophil infiltration and lower B cells, CD4 + T cells (non-regulatory) and regulatory T cell (Tregs) infiltration in oral saliva environment when compared to the control groups. This study suggests that saliva might be a better liquid biopsy medium over blood (plasma) for cfRNA on detecting OSCC. CLEC2B, DAZL, F9, and AC008735.2 in saliva may serve as potential diagnostic liquid biomarkers for OSCC, warranting further investigation.

Scientific ReportsVol. 15(1)
Shantou University (CN), Cancer Hospital of Shantou University Medical College (CN)
Zero hunger
Openalex Percentile: Top 3%
Cancer-related molecular mechanisms research
6.55
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.