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Background: The incidence of squamous cell carcinoma of the oral tongue (SCCOT) among young adults is increasing in several regions of the world. Age-dependent differences in the biology of SCCOT have been suspected.

Methods: We used the Olink Explore 3072 high-throughput platform to comprehensively quantify plasma proteins in 24 young (≤ 40 years of age) and 50 old (> 50 years of age) individuals. Eight young and 20 old individuals were diagnosed with SCCOT, four young and nine old individuals with SCC at other oral subsites (SCCOO), and the remaining 12 young and 21 old individuals were healthy controls. Dimension reduction analysis, differential expression analysis, and functional enrichment analysis were performed to characterize young patient-specific biological signatures.

Results: Plasma levels of 2923 proteins were obtained. Principal component analysis indicated age-related expression patterns. Comparing young patients to young controls/old patients/old controls, differential abundance analysis showed that increases in protein levels of Peroxiredoxin 2 (PRDX2) and C-C motif chemokine ligand 26 (CCL26) and a decrease in Kallikrein related peptidase 4 (KLK4) were young patient-specific. Reactome pathway enrichment analysis identified “Cellular response to chemical stress,” “Detoxification of reactive oxygen species” and “Cellular responses to stimuli” as the top altered pathways in young patients with SCCOT.

Conclusions: Abnormal cellular stress and aberrant immune regulation could thus be linked to cancer development in young patients. The unique plasma proteomic signature observed in young patients with SCCOT suggests that they constitute a specific group with distinct underlying pathophysiological processes.

Squamous cell carcinoma of the oral tongue (SCCOT) represents an aggressive malignancy characterized by high metastatic potential and significant heterogeneity in its tumor microenvironment. The tumor-stroma ratio (TSR) has emerged as a prognostic biomarker, with higher stromal content frequently correlating with worse survival outcomes. Traditional approaches using the standard 50% TSR cutoff may not be optimal for SCCOT, and visual TSR estimation introduces variability during TSR region annotation. This study aimed to develop and validate a dedicated TSR estimation model for SCCOT by incorporating representative TSR regions from the invasive tumor front of whole slide images and to determine the optimal TSR threshold for prognostic stratification. Using hematoxylin and eosin-stained images from The Cancer Genome Atlas as a discovery cohort and whole slide images from Norrland's University Hospital Umea, Sweden (NUS) as a validation cohort, we developed a computational model to estimate TSR. The model demonstrated a high correlation with pathologist-based TSR estimation in both discovery (R = 0.848, p < 0.01) and validation (R = 0.783, p < 0.01) cohorts. The optimal 55% cutoff identified by the model improved prognostic accuracy over the traditional 50% threshold, with patients having high stroma within the tumor invasive front showing worse overall (log-rank p = 0.006) and disease-specific (log-rank p = 0.016) survival. Our computational TSR model for SCCOT demonstrates that automated TSR estimation enhances prognostic accuracy at an optimal cutoff of 55%, contributing to more precise risk stratification and potentially enabling personalized treatment strategies in SCCOT management.

Background: Bilateral salivary gland tumors, both benign and malignant and synchronous or metachronous are very rare.

Case presentation: Here three cases of synchronous bilateral salivary gland tumors are described and discussed. Recognizing the entity is important for diagnostics and treatment planning. The first patient was a 56-year-old female with a bilateral parotid tumor, a malignant tumor, salivary duct carcinoma on the right side and a benign tumor, pleomorphic adenoma on the left side. The second patient was a 50-year old female with a bilateral benign parotid tumor, a pleomorphic adenoma. The third patient was a 51-year old female with a bilateral malignant tumor, an acinic cell carcinoma. Details on the diagnostic work-up, histopathology and treatment are described and discussed.

Conclusions: In the case of a unilateral salivary gland tumor, especially of the major glands, the contralateral gland is always included in the clinical and radiological (MRI) head and neck evaluation prior to surgery, to detect or exclude possible bilateral occurrence.

Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a common disease in which inflammatory responses to exogenic stressors, such as viral infections, has been recognised. The role of viruses in CRSwNP pathogenesis is unclear.

Aims/objectives: We aimed to characterise Epstein-Barr virus (EBV), human papillomavirus (HPV), human cytomegalovirus (HCMV), and human adenovirus (HAdV) in nasal polyps and adjacent paired healthy turbinate mucosa.

Materials and methods: We used real-time PCR for EBV, HCMV, and HAdV DNA detection, combined PCR/microarrays for HPV detection and genotyping, in samples from 45 patients with CRSwNP. Additionally, we used EBER in situ hybridisation for EBV detection.

Results: EBV detection with EBER-ISH was significantly higher in polyps (36%) versus turbinate mucosa (12%). None of the viral comparisons with PCR between polyps and turbinate mucosa for EBV-, HCMV- or HAdV-DNA showed statistically significant differences. All samples were HPV negative.

Conclusions and significance: We report higher expression of EBV in nasal polyps (36%) than in adjacent healthy turbinate mucosa (12%), using a valid method; EBER-ISH in 45 patients with CRSwNP. EBV might be a possible stressor that can trigger polypoid inflammation.

Objectives: To evaluate the relationship between gingival phenotype, classified using a steel periodontal probe (TRAN method), and soft tissue dimensions measured clinically and histologically.

Materials and methods: Forty-five healthy volunteers were categorized into thin or thick phenotype groups based on gingival transparency at one maxillary central incisor. Clinical thickness measurements of the gingiva and mucosa were taken with an ultrasonic device, while histological assessments were conducted on tissue samples from the same region. The keratinized tissue width (KTW) was also recorded.

Results: Twenty-four participants were classified as thick phenotype and twenty-one as thin. Phenotype showed a significant moderate correlation with clinical gingival thickness (r = 0.682, p < 0.001), a weaker positive correlation with KTW (r = 0.290, p = 0.023). The optimal threshold for distinguishing thin and thick phenotypes was 1.065 mm, with the TRAN method showing good predictive accuracy (AUC = 0.912). Both clinical and histological measurements revealed a gradual thinning of soft tissues from the midpoint of the keratinized tissue to the MGJ and beyond. Ultrasonography demonstrated good repeatability for gingival thickness (ICC = 0.744) but underestimated mucosal thickness compared to histology (p < 0.001).

Conclusions: The TRAN method moderately correlates with clinical gingival thickness at the midpoint of KTW and with KTW. Soft tissue thickness decreases towards the MGJ. Clinical relevance: Probe concealment correlates with a gingival thickness of 1.065 mm at the midpoint of the KTW. Ultrasonography is reliable for gingival, but not mucosal, thickness assessment.

Objectives: This study aims to explore the histological dimensions of the gingiva and the alveolar mucosa and to evaluate their associations with gingival phenotypic parameters, including gingival thickness (GT), keratinized tissue width (KTW), and gingival transparency.

Methods: Histological and clinical assessments were performed on 45 healthy volunteers. Gingival and mucosal tissue samples were collected from the mucogingival junction region of one maxillary central incisor. Histomorphometric analysis included measurements of gingival and mucosal thickness, epithelial thickness, connective tissue thickness, epithelial papilla length and density, and keratinization. Clinical parameters included KTW and probe visibility upon insertion into the gingival sulcus. Correlations were statistically analyzed between clinical and histological parameters.

Results: Probe visibility showed no significant correlations with any assessed parameter. Histological gingival thickness strongly correlated with gingival connective tissue thickness, moderately with epithelial thickness and papilla length, and weakly with papilla density. Mucosal thickness was strongly associated with connective tissue thickness and moderately with keratinization, but not with other parameters. KTW exhibited weak correlations with epithelial thickness and papilla length.

Conclusions: Variability in gingival and mucosal thickness is primarily determined by connective tissue thickness, with a smaller contribution from the epithelium. Increased thickness is associated with longer, sparser epithelial papillae and with a tendency toward higher keratinization. KTW is significantly associated with epithelial thickness and papilla length, underscoring its relevance in gingival phenotype characterization.

Locoregional recurrences and distant metastases are major problems for patients with squamous cell carcinoma of the head and neck (SCCHN). Because SCCHN is a heterogeneous group of tumours with varying characteristics, the present study concentrated on the subgroup of squamous cell carcinoma of the oral tongue (SCCOT) to investigate the use of machine learning approaches to predict the risk of recurrence from routine clinical data available at diagnosis. The approach also identified the most important parameters that identify and classify recurrence risk. A total of 66 patients with SCCOT were included. Clinical data available at diagnosis were analysed using statistical analysis and machine learning approaches. Tumour recurrence was associated with T stage (P=0.001), radiological neck metastasis (P=0.010) and diabetes (P=0.003). A machine learning model based on the random forest algorithm and with attendant explainability was used. Whilst patients with diabetes were overrepresented in the SCCOT cohort, diabetics had lower recur‑ rence rates (P=0.015 after adjusting for age and other clinical features) and an improved 2‑year survival (P=0.025) compared with non‑diabetics. Clinical, radiological and histological data available at diagnosis were used to establish a prognostic model for patients with SCCOT. Using machine learning to predict recurrence produced a classification model with 71.2% accuracy. Notably, one of the findings of the feature importance rankings of the model was that diabetics exhibited less recur‑ rence and improved survival compared with non‑diabetics, even after accounting for the independent prognostic variables of tumour size and patient age at diagnosis. These data imply that the therapeutic manipulation of glucose levels used to treatdiabetes may be useful for patients with SCCOT regardless of their diabetic status. Further studies are warranted to investigatethe impact of diabetes in other SCCHN subtypes.

PURPOSE: The field cancerization concept indicates the presence of pre-cancerous changes in clinically normal tissue surrounding the tumor. In squamous cell carcinoma of the oral tongue (SCCOT) which is infrequently linked to human papillomavirus infection, we have previously reported that clinically normal tongue contralateral to tumor (NTCT) is molecularly abnormal. Here, combining our transcriptomic and genomic data, we aimed to investigate the contribution of molecular changes in NTCT to cancer development.

METHODS: Microarray gene expression data of 14 healthy controls, 23 NTCT and 29 SCCOT samples were investigated to characterize transcriptional profiles in NTCT. Whole exome sequencing and RNA-sequencing data of paired NTCT and tumor samples from 15 SCCOT patients were used to study correlation between copy number variation and differential gene expression.

RESULTS: Using supervised multivariate partial least squares discriminant analysis, a total of 61 mRNAs that distinguish NTCT from healthy tongue were selected. Functional enrichment analysis of the 22 upregulated genes showed increased "positive regulation of nitrogen compound metabolic process" in NTCT. All 12 genes involved in this process have roles in apoptosis (anti- and/or pro-apoptotic). Compared to healthy controls, Zinc Finger Protein 395 (ZNF395), a pro-apoptotic tumor suppressor located on chromosome 8p, was the only gene showing increased mRNA level in NTCT whereas decreased in SCCOT. Given the frequent loss of chromosome 8p in SCCOT, the impact of ZNF395 copy number variation on gene expression was further examined, revealing a positive correlation between copy number and mRNA level (correlation coefficient = 0.572, p < 0.001).

CONCLUSION: NTCT is susceptible to malignant transformation, where tissue homeostasis is maintained at least partly through regulation of apoptosis. Loss of the pro-apoptotic gene ZNF395 could thus initiate cancer development.

Background: Interpretable machine learning (ML) for early detection of cancer has the potential to improve risk assessment and early intervention.

Methods: Data from 261 proteins related to inflammation and/or tumor processes in 123 blood samples collected from healthy persons, but of whom a sub-group later developed squamous cell carcinoma of the oral tongue (SCCOT), were analyzed. Samples from people who developed SCCOT within less than 5 years were classified as tumor-to-be and all other samples as tumor-free. The optimal ML algorithm for feature selection was identified and feature importance computed by the SHapley Additive exPlanations (SHAP) method. Five popular ML algorithms (AdaBoost, Artificial neural networks [ANNs], Decision Tree [DT], eXtreme Gradient Boosting [XGBoost], and Support Vector Machine [SVM]) were applied to establish prediction models, and decisions of the optimal models were interpreted by SHAP.

Results: Using the 22 selected features, the SVM prediction model showed the best performance (sensitivity = 0.867, specificity = 0.859, balanced accuracy = 0.863, area under the receiver operating characteristic curve [ROC-AUC] = 0.924). SHAP analysis revealed that the 22 features rendered varying person-specific impacts on model decision and the top three contributors to prediction were Interleukin 10 (IL10), TNF Receptor Associated Factor 2 (TRAF2), and Kallikrein Related Peptidase 12 (KLK12).

Conclusion: Using multidimensional plasma protein analysis and interpretable ML, we outline a systematic approach for early detection of SCCOT before the appearance of clinical signs.

Oral cancer is a paradigm of Slaughter's concept of field cancerization, where tumors are thought to originate within an area of cells containing genetic alterations that predispose to cancer development. The field size is unclear but may represent a large area of tissue, and the origin of mutations is also unclear. Here, we analyzed whole exome and transcriptome features in contralateral tumor-distal tongue (i.e. distant from the tumor, not tumor-adjacent) and corresponding tumor tissues of 15 patients with squamous cell carcinoma of the oral tongue. The number of point mutations ranged from 41 to 237 in tumors and from one to 78 in tumor-distal samples. Tumor-distal samples showed mainly clock-like (associated with aging) or tobacco smoking mutational signatures. Tumors additionally showed mutations that associate with cytidine deaminase AID/APOBEC enzyme activities or a UV-like signature. Importantly, no point mutations were shared between a tumor and the matched tumor-distal sample in any patient. TP53 was the most frequently mutated gene in tumors (67%), whereas a TP53 mutation was detected in only one tumor-distal sample, and this mutation was not shared with the matched tumor. Arm-level copy number variation (CNV) was found in 12 tumors, with loss of chromosome (Chr) 8p or gain of 8q being the most frequent events. Two tumor-distal samples showed a gain of Chr8, which was associated with increased expression of Chr8-located genes in these samples, although gene ontology did not show a role for these genes in oncogenic processes. In situ hybridization revealed a mixed pattern of Chr8 gain and neutral copy number in both tumor cells and adjacent nontumor epithelium in one patient. We conclude that distant field cancerization exists but does not present as tumor-related mutational events. The data are compatible with etiologic field effects, rather than classical monoclonal field cancerization theory. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.