A high density of T-cell lymphocytes and Tregs subset correlate to a worse survival in major salivary gland carcinomas

Salivary gland carcinomas (SGC) are rare and heterogeneous tumors with limited therapeutic options in advanced stages. Recent evidence suggests a potential role of the tumor immune microenvironment (TME) in disease progression. This study aimed to investigate the immune profile of SGCs by analyzing tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and PD-L1 expression, and to assess their correlation with histological grade and clinical outcome. A retrospective analysis was conducted on 103 SGC cases. Immunohistochemistry for CD3, CD4, CD8, CD20, CD56, PD-1, PD-L1, FOXP3, CD68, and CD163 was performed. Digital slide analysis was carried out in intratumoral and peritumoral regions using QuPath software. High intratumoral FOXP3 + Tregs were significantly associated with high-grade tumors and worse progression-free survival (PFS) (p = 0.009). A higher peritumoral CD3 + T cell density correlated with poor prognosis (p = 0.046). Concordance between pathologist assessments and QuPath quantification was moderate to high (Cohen's K = 0.71). In conclusion, intratumoral Tregs and peritumoural T lymphocytes may be used as negative prognostic biomarkers. Future multicentric studies and AI (Artificial Intelligence)-driven analyses could enhance immune characterization and guide immunotherapeutic strategies in SGC.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-03-03
DOI
https://doi.org/10.1038/s41598-026-39357-y
Primary Topic
Salivary Gland Tumors Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A high density of T-cell lymphocytes and Tregs subset correlate to a worse survival in major salivary gland carcinomas

Maria Raffaella Ambrosio, Guido Bartoletti, Francesco Vasuri, Luca Saragoni et al.
Scientific Reports
Salivary Gland Tumors Diagnosis and Treatment
article

A high density of T-cell lymphocytes and Tregs subset correlate to a worse survival in major salivary gland carcinomas

Maria Raffaella Ambrosio, Guido Bartoletti, Francesco Vasuri, Luca Saragoni, Elena Niccolai, Luca Muscatello, Debora Anconelli, Elena Cantone, A. Franchi, Luca Novelli, Luca Messerini, Amedeo Amedei
article en

Abstract

Salivary gland carcinomas (SGC) are rare and heterogeneous tumors with limited therapeutic options in advanced stages. Recent evidence suggests a potential role of the tumor immune microenvironment (TME) in disease progression. This study aimed to investigate the immune profile of SGCs by analyzing tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and PD-L1 expression, and to assess their correlation with histological grade and clinical outcome. A retrospective analysis was conducted on 103 SGC cases. Immunohistochemistry for CD3, CD4, CD8, CD20, CD56, PD-1, PD-L1, FOXP3, CD68, and CD163 was performed. Digital slide analysis was carried out in intratumoral and peritumoral regions using QuPath software. High intratumoral FOXP3 + Tregs were significantly associated with high-grade tumors and worse progression-free survival (PFS) (p = 0.009). A higher peritumoral CD3 + T cell density correlated with poor prognosis (p = 0.046). Concordance between pathologist assessments and QuPath quantification was moderate to high (Cohen's K = 0.71). In conclusion, intratumoral Tregs and peritumoural T lymphocytes may be used as negative prognostic biomarkers. Future multicentric studies and AI (Artificial Intelligence)-driven analyses could enhance immune characterization and guide immunotherapeutic strategies in SGC.

Scientific Reports
University of Pisa (IT), Prevention Institute (US), Ospedale "Santa Maria delle Croci" di Ravenna (IT), Azienda Usl Toscana Centro (IT), University of Florence (IT), University of Calabria (IT), University of Bologna (IT)
No poverty
Openalex Percentile: Top 36%
Salivary Gland Tumors Diagnosis and Treatment
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.