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Background: The optimal management of oropharyngeal squamous cell carcinoma (OPSCC) includes both sur-gical and non-surgical, that is, (chemo)radiotherapy treatment options and their combinations. These approaches carry a risk of specific treatment-related side effects. HPV-positive OPSCC has been reported to be more sensitive to (chemo)radiotherapy-based treatment modalities. Objectives: This study aims to demonstrate how machine learning can aid in classifying OPSCC patients into risk groups (low-chance or high-chance) for overall survival. We examined the input variables using permutation feature importance. Furthermore, we provided explanations and interpretations using the Local Interpretable Model Agnostic Explanations (LIME) and SHapley Additive Explanation (SHAP) frameworks. Methods: The machine learning model for 3164 OPSCC patients was built using data obtained from the Surveillance, Epidemiology, and End Results (SEER) program database. A total of five variants of tree-based machine learning algorithms (voting ensemble, light GBM, XGBoost, Random Forest, and Extreme Random Trees) were used to divide the patients into risk groups. The developed model with the best predictive performance was temporally validated with a different cohort. Results: The voting ensemble machine learning algorithm showed an accuracy of 88.3%, Mathews' correlation coefficient of 0.72, and weighted area under curve of 0.93, when temporally validated. Human papillomavirus (HPV) status, age of the patients, T stage, marital status, N stage, and the treatment modality (surgery with postoperative radiotherapy) were found to have the most significant effects on the ability of the machine learning model to predict overall survival. Similarly, for the individual patients with SHAP framework, HPV status, gender, and treatment modality (surgery with postoperative radiotherapy) were the input features that improved the model's prediction. Conclusion: The proposed stratification of OPSCC patients into risk groups by machine learning techniques can provide accurate predictions and thus aid clinicians in administering early and personalized interventions. Clinicians could utilize the predicted risk with the explanations offered by the SHAP and LIME frameworks to understand previously undetected relationships between prognostic variables to make informed clinical decisions and effective interventions.

Background The clinical significance of tertiary lymphoid structures (TLSs) is not well-documented in early oral tongue squamous cell carcinoma (OTSCC). Methods A total of 310 cases of early (cT1-2N0) OTSCC were included in this multicenter study. Assessment of TLSs was conducted on hematoxylin and eosin-stained sections. TLSs were assessed both in the central part of the tumor and at the invasive front area. Results The presence of TLSs associated with improved survival of early OTSCC as presented by Kaplan–Meier survival analyses for disease-specific survival (P = 0.01) and overall survival (P = 0.006). In multivariable analyses, which included conventional prognostic factors, the absence of TLSs associated with worse disease-specific survival with a hazard ratio (HR) of 1.96 (95% CI 1.09–3.54; P = 0.025) and poor overall survival (HR 1.66, 95% CI 1.11–2.48; P = 0.014). Conclusion Histological evaluation of TLSs predicts survival in early OTSCC. TLSs showed superior prognostic power independent of routine WHO grading and TNM staging system.

Background: Machine learning models have been reported to assist in the proper management of cancer through accurate prognostication. Integrating such models as a web-based prognostic tool or calculator may help to improve cancer care and assist clinicians in making oral cancer management-related decisions. However, none of these models have been recommended in daily practices of oral cancer due to concerns related to machine learning methodologies and clinical implementation challenges. An instance of the concerns inherent to the science of machine learning is explainability. Objectives: This study measures the usability and explainability of a machine learning-based web prognostic tool that was designed for prediction of oral tongue cancer. We used the System Usability Scale (SUS) and System Causability Scale (SCS) to evaluate the explainability of the prognostic tool. In addition, we propose a framework for the evaluation of post hoc explainability of web-based prognostic tools. Methods: A SUS- and SCS-based questionnaire was administered amongst pathologists, radiologists, cancer and machine learning researchers and surgeons (n = 11) to evaluate the quality of explanations offered by the machine learning-based web prognostic tool to address the concern of explainability and usability of these models for cancer management. The examined web-based tool was developed by our group and is freely available online. Results: In terms of the usability of the web-based tool using the SUS, 81.9% (45.5% strongly agreed; 36.4% agreed) agreed that neither the support of a technical assistant nor a need to learn many things were required to use the web-based tool. Furthermore, 81.8% agreed that the evaluated web-based tool was not cumbersome to use (usability). The average score for the SCS (explainability) was 0.74. A total of 91.0% of the participants strongly agreed that the web-based tool can assist in clinical decision-making. These scores indicated that the examined web-based tool offers a significant level of usability and explanations about the outcome of interest. Conclusions: Integrating the trained and internally and externally validated model as a web-based tool or calculator is poised to offer an effective and easy approach towards the usage and acceptance of these models in the future daily practice. This approach has received significant attention in recent years. Thus, it is important that the usability and explainability of these models are measured to achieve such touted benefits. A usable and well-explained web-based tool further brings the use of these web-based tools closer to everyday clinical practices. Thus, the concept of more personalized and precision oncology can be achieved.

Background The evaluation of immune response can aid in prediction of cancer behaviour. Here, we assessed the prognostic significance of tumour-infiltrating lymphocytes (TILs) in oropharyngeal squamous cell carcinoma (OPSCC). Methods A total of 182 patients treated for OPSCC were included in this study. Assessment of TILs was conducted on tumour sections stained with standard haematoxylin and eosin (HE) staining. We used the scoring criteria proposed by the International Immuno-Oncology Biomarker Working Group. Results The multivariable analysis showed that TILs associated with disease-specific survival with a hazard ratio (HR) of 2.13 (95% CI 1.14–3.96; P = 0.017). Similarly, TILs associated significantly with overall survival with HR of 1.87 (95% CI 1.11–3.13; P = 0.018). In a sub-analysis of HPV-positive and HPV-negative cases separately, TILs showed a significant prognostic value in both groups (P Conclusion The evaluation of TILs as proposed by the International Immuno-Oncology Biomarker Working Group is a simple and promising method in prediction of survival of OPSCC. It is easily applicable and after further validation can be implemented in the routine pathological report as a basic immune parameter.

Objectives: Tumor mutation burden (TMB) is an emerging predictive cancer biomarker. Few studies have addressed the prognostic role of TMB in non-small cell lung carcinoma, with conflicting results. Moreover, the association of TMB with different histological subtypes of lung adenocarcinoma has hitherto not been systematically evaluated. Here we studied the prognostic value of TMB and its distribution in different histological subtypes of lung adenocarcinomas in a retrospective cohort using the most recent updated classification guidelines. Materials and methods: 176 surgically resected stage I-IV lung adenocarcinomas were histologically reclassified according to WHO 2015 guidelines. A modified classification subdividing the acinar subtype into classic acinar, complex glandular and cribriform subtypes was further applied and potentially prognostic histopathological characteristics such as tumor-infiltrating lymphocytes were evaluated. 148 patients with stage I-III tumors and complete follow-up data were included in the survival analyses. TMB was determined by a commercial next generation sequencing panel from 131 tumors, out of which 105 had survival data available. Results: Predominant micropapillary, solid and complex glandular as well as nonpredominant cribriform histological subtypes were associated with significantly shorter survival. High TMB concentrated in micropapillary, solid and acinar predominant subtypes. Interestingly, TMB >= 14 mutations/MB conferred a stage- and histology-independent survival benefit compared to TMB

Background: Archived formalin-fixed paraffin-embedded (FFPE) specimens from nonmalignant tissues derived from cancer patients are a vast and potentially valuable resource for high-quality genotyping analyses and could have a role in establishing inherited cancer risk. Methods: We systematically searched PubMed, Ovid MEDLINE, and Scopus databases for all articles that compared genotyping performance of DNA from nonmalignant FFPE tissue with blood DNA derived from cancer patients irrespective of tumor type. Two independent researchers screened the retrieved studies, removed duplicates, excluded irrelevant studies, and extracted genotyping data from the eligible studies. These studies included, but were not limited to, genotyping technique, reported call rate, and concordance. Results: Thirteen studies were reviewed, in which DNA from nonmalignant FFPE tissues derived from cancer patients was successfully purified and genotyped. All these studies used different approaches for genotyping of DNA from nonmalignant FFPE tissues to amplify single nucleotide polymorphisms (SNPs) and to estimate of loss of heterozygosity. The concordance between genotypes from nonmalignant FFPE tissues and blood derived from cancer patients was observed to be high, whereas the call rate of the tested SNPs was not reported in all included studies. Conclusion: This review illustrates that DNA from nonmalignant FFPE tissues derived from cancer patients can serve as an alternative and reliable source for assessment of germline DNA for various purposes, including assessment of cancer predisposition.

Although there are many histopathologic prognosticators, grading of early oral tongue squamous cell carcinoma (OTSCC) is still based on morphological cell differentiation which has low prognostic value. Here we summarize the emerging histopathological markers showing powerful prognostic value, but are not included in pathology reports. Using PubMed, Scopus, Ovid Medline, and Web of Science databases, a systematic literature search was preformed to identify early OTSCC studies that investigated the prognostic significance of hematoxylin-eosin-based histopathologic markers. Our meta-analysis showed that tumor budding was associated with overall survival (hazard ratio [HR] 2.32; 95% CI 1.40-3.84; p 0.01) and disease-specific survival (DSS) (1.89; 95% CI 1.13-3.15; p = 0.02). Worst pattern of invasion was associated with disease-free survival (DFS) (1.95; 95% CI 1.04-3.64; p = 0.04). Tumor-stroma ratio was also associated with DFS (1.75, 95% CI 1.24-2.48; p 0.01) and DSS (1.69; 95% CI 1.19-2.42; p 0.01). Tumor budding, worst pattern of invasion, and tumor-stroma ratio have a promising prognostic value in early OTSCC. The evaluation and reporting of these markers is cost-effective and can be incorporated in daily practice.

Contains fulltext : 251733.pdf (Publisher’s version ) (Open Access) INTRODUCTION: Patients with head and neck cancer (HNC) are usually confronted with functional changes due to the malignancy itself or its treatment. These factors typically affect important structures involved in speech, breathing, chewing, swallowing, and saliva production. Consequently, the intake of food will be limited, which further contributes to loss of body weight and muscle mass, anorexia, malnutrition, fatigue, and anemia. This multifactorial condition can ultimately lead to cancer cachexia syndrome. This study aims to examine the treatment of cachexia in HNC patients. METHODS: We systematically searched OvidMedline, PubMed, Scopus, and Web of Science for articles examining the treatment of cachexia in HNC. RESULTS: A total of nine studies were found, and these suggested interventions including nutritional, pharmacologic, therapeutic exercise, and multimodal approaches. The nutritional intervention includes essential components such as dietary counseling, oral nutritional supplements, and medical nutritional support. Individualized nutritional interventions include oral, enteral (feeding tubes i.e., percutaneous endoscopic gastrostomy [PEG], nasogastric tube [NGT]) and parenteral nutrition. The pharmacologic interventions aim at increasing the appetite and weight of cachectic patients. Therapeutic exercise and increased physical activity can help to enhance the synthesis of muscle protein, reducing inflammation and the catabolic effects of cachexia syndrome. CONCLUSION: Owing to the multifactorial nature of this syndrome, it is expected that the management approach should be multi-interventional. Early implementation of these interventions may help to improve survival and quality of health and life of cachectic HNC patients.

Objectives: The purpose of this study was to provide a scoping review on how to address and mitigate burnout in the profession of clinical oncology. Also, it examines how artificial intelligence (AI) can mitigate burnout in oncology. Methods: We searched Ovid Medline, PubMed, Scopus, and Web of Science, for articles that examine how to address burnout in oncology. Results: A total of 17 studies were found to examine how burnout in oncology can be mitigated. These interventions were either targeted at individuals (oncologists) or organizations where the oncologists work. The organizational interventions include educational (psychosocial and mindfulness-based course), art therapies and entertainment, team-based training, group meetings, motivational package and reward, effective leadership and policy change, and staff support. The individual interventions include equipping the oncologists with adequate training that include—communication skills, well-being and stress management, burnout education, financial independence, relaxation, self-efficacy, resilience, hobby adoption, and work-life balance for the oncologists. Similarly, AI is thought to be poised to offer the potential to mitigate burnout in oncology by enhancing the productivity and performance of the oncologists, reduce the workload and provide job satisfaction, and foster teamwork between the caregivers of patients with cancer. Discussion: Burnout is common among oncologists and can be elicited from different types of situations encountered in the process of caring for patients with cancer. Therefore, for these interventions to achieve the touted benefits, combinatorial strategies that combine other interventions may be viable for mitigating burnout in oncology. With the potential of AI to mitigate burnout, it is important for healthcare providers to facilitate its use in daily clinical practices. Conclusion: These combinatorial interventions can ensure job satisfaction, a supportive working environment, job retention for oncologists, and improved patient care. These interventions could be integrated systematically into routine cancer care for a positive impact on quality care, patient satisfaction, the overall success of the oncological ward, and the health organizations at large.

Background: The immune response has an important role in cancer progression. At the same time, anti-tumor effect of the immune response has been speculated to cause destruction of cancer cells. Rec...

The World Health Organization (WHO) grading system has a low prognostic value for early-stage oral tongue squamous cell carcinoma; greater prognostic power has been shown with tumor budding analysis. In this study, we combined tumor budding analysis with histopathologic grading according to WHO 2017. In our proposal, a revised grade I tumor is defined as a "well differentiated cohesive tumor"; revised grade II as a "moderately differentiated and/or slightly dissociated tumor"; and revised grade III as a "poorly differentiated and/or dissociated tumor." We evaluated the prognostic value of this proposed grading system in a multicenter cohort of 311 cases of early oral tongue squamous cell carcinoma. The proposed grading system showed significant prognostic value in multivariable analysis for disease-specific survival with a hazard ratio of 3.86 and a 95% confidence interval of 1.36-10.9 (P=0.001). For disease-free survival, the proposed grading system showed good predictive power in multivariable analysis (hazard ratio, 2.07; 95% confidence interval, 1.00-4.27; P=0.009). The conventional WHO grading system showed a low prognostic value for disease-specific survival and disease-free survival (P>0.05). In conclusion, the prognostic power of the WHO histopathologic grading improved significantly with incorporation of tumor budding. Our proposed grading system can be easily included in pathology reports.

Fascin 1 plays important pro-metastatic roles in head and neck carcinoma (HNSCC) migration, invasion, and metastasis. However, limited advancement in targeting metastasis remains a major obstacle in improving HNSCC patients’ survival. Therefore, we assessed the therapeutic potential of fascin 1 targeted inhibition and its potential prognostic value in HNSCC patients. Using in vitro and in vivo approaches, we investigated the effect of compound G2, a novel fascin 1 inhibitor, on HNSCC cells migration, invasion, and metastasis. High-throughput screening (HTS) was used to assess cytotoxic activity of compound G2 alone or combined with irradiation. We also evaluated the prognostic potential of fascin 1 in HNSCC patients. Interestingly, compound G2 reduced carcinoma cells migration and invasion in vitro and inhibited metastasis in vivo. Moreover, HTS revealed a modest cytotoxic activity of the compound G2 on HNSCC cell lines. Irradiation did not synergistically enhance the compound G2-mediated cytotoxic activity. Survival analyses showed that high fascin 1 immunoexpression, at the tumor invasive front, was associated with cancer-specific mortality in the advanced stages of HNSCC. Collectively, our findings suggest that fascin 1 represents a promising anti-metastatic therapeutic target and a useful prognostic marker in patients with HNSCC. Novel anti-metastatic agents could provide a valuable addition to cancer therapy. publishedVersion

Background: The clinical significance of tumor-stroma ratio (TSR) has been examined in many tumors. Here we systematically reviewed all studies that evaluated TSR in head and neck cancer. Methods: Four databases (Scopus, Medline, PubMed and Web of Science) were searched using the term tumo(u)r-stroma ratio. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) were followed. Results: TSR was studied in nine studies of different subsites (including cohorts of nasopharyngeal, oral, laryngeal and pharyngeal carcinomas). In all studies, TSR was evaluated using hematoxylin and eosin staining. Classifying tumors based on TSR seems to allow for identification of high-risk cases. In oral cancer, specifically, our meta-analysis showed that TSR is significantly associated with both cancer-related mortality (HR 2.10, 95%CI 1.56–2.84) and disease-free survival (HR 1.84, 95%CI 1.38–2.46). Conclusions: The assessment of TSR has a promising prognostic value and can be implemented with minimum efforts in routine head and neck pathology.

Stromal categorization has been used to classify many epithelial cancer types. We assessed the desmoplastic reaction and compared its significance with other stromal characteristics in early (cT1-2N0) oral tongue squamous cell carcinoma (OTSCC). In this multi-institutional study, we included 308 cases treated for early OTSCC at five Finnish university hospitals or at the A.C. Camargo Cancer Center in São Paulo, Brazil. The desmoplastic reaction was classified as immature, intermediate, or mature based on the amount of hyalinized keloid-like collagen and myxoid stroma. We compared the prognostic value of the desmoplastic reaction with a stromal grading system based on tumor-stroma ratio and stromal tumor-infiltrating lymphocytes. We found that a high amount of stroma with a weak infiltration of lymphocytes was associated statistically significantly with a worse disease-free survival with a hazard ratio (HR) of 2.68 (95% CI 1.26–5.69), worse overall survival (HR 2.95, 95% CI 1.69–5.15), and poor disease-specific survival (HR 2.66, 95% CI 1.11–6.33). Tumors having a high amount of stroma with a weak infiltration of lymphocytes were also significantly associated with a high rate of local recurrence (HR 4.13, 95% CI 1.67–10.24), but no significant association was found with lymph node metastasis (HR 1.27, 95% CI 0.37–4.35). Categorization of the stroma based on desmoplastic reaction (immature, intermediate, mature) showed a low prognostic value for early OTSCC in all survival analyses (P > 0.05). In conclusion, categorization of the stroma based on the amount of stroma and its infiltrating lymphocytes shows clinical relevance in early OTSCC superior to categorization based on the maturity of stroma.

Aims One of the objectives of current research is to customise the treatment of cancer patients. The achievement of this objective requires stratification of patients based on the most significant prognostic factors. The aims of this study were to evaluate the prognostic value of the tumour-stroma ratio (TSR), defined as the proportion of tumour cells relative to surrounding stroma, in patients with oral tongue squamous cell carcinoma (OTSCC), and to develop a prognostic nomogram based on the most significant clinicopathological features. Methods and results Clinicopathological data of 211 patients treated at 'Ospedali Riuniti' General Hospital (Ancona, Italy) for OTSCC were collected. One hundred and thirty-nine patients were restaged according to the 8th edition American Joint Committee on Cancer (AJCC) staging system. Evaluation of the TSR was performed on haematoxylin and eosin-stained slides, and correlation with survival outcomes was evaluated. In addition, with the aim of integrating the independent value of the TSR with the 8th edition AJCC staging system, a prognostic nomogram for OTSCC has been developed. OTSCC with a low TSR (i.e. a high proportion of stroma and a low proportion of tumour cells) was shown to have negative prognostic value in terms of disease-specific survival, with a hazard ratio (HR) of 1.883 and a 95% confidence interval (CI) of 1.033-3.432 (P = 0.039), and overall survival (HR = 1.747, 95% CI 0.967-3.154;P = 0.044), independently of other histological and clinical parameters. For the cohort of 139 patients restaged according to the 8th edition AJCC staging system, variables correlating with a poor prognosis were: the TSR, perineural invasion, and sex. The nomogram built on these parameters showed good predictive capacity, outperforming the 8th edition AJCC staging system in stratifying disease-specific survival in OTSCC patients. Conclusions Including the TSR in the predictive model could improve risk stratification of OTSCC patients and aid in making treatment decisions.

Background Tumour budding (B) and depth of invasion (D) have both been reported as promising prognostic markers in oral squamous cell carcinoma (OSCC). This meta-analysis assessed the prognostic value of the tumour budding and depth of invasion combination (BD model) in OSCC. Methods Databases including Ovid MEDLINE, PubMed, Scopus and Web of Science were searched for articles that studied the BD model as a prognosticator in OSCC. PICO search strategy was "In OSCC patients, does BD model have a prognostic power?" We used the reporting recommendations for tumour marker prognostic studies (REMARK) criteria to evaluate the quality of studies eligible for systematic review and meta-analysis. Results Nine studies were relevant as they analysed the BD model for prognostication of OSCC. These studies used either haematoxylin and eosin (HE) or pan-cytokeratin (PCK)-stained resected sections of OSCC. Our meta-analysis showed a significant association of BD model with OSCC disease-free survival (hazard ratio = 2.02; 95% confidence interval = 1.44-2.85). Conclusions The BD model is a simple and reliable prognostic indicator for OSCC. Evaluation of the BD model from HE- or PCK-stained sections could facilitate individualized treatment planning for OSCC patients.

Background: A role for incisional biopsy in preoperative prognostication is increasingly being advocated in oral tongue squamous cell carcinomas (OTSCC). Biopsies at two locations were compared and prognostic factors in biopsies and their corresponding resections were evaluated. Methods: A total of 138 OTSCC biopsy slides from Finland and Saudi-Arabia were compared for size (horizontal and vertical) and invasive front. The Finnish cases were assessed for tumor stroma ratio (TSR) and tumor-infiltrating lymphocytes (TILs) using light microscopy and digital image analysis assessment and compared. Furthermore, TSR, TILs, and previously analyzed budding and depth of invasion (BD) score in biopsies were compared with their evaluation in the corresponding resections. Results: Finnish biopsies were deeper than Saudi-Arabian biopsies (59% versus 42%) while Saudi-Arabian biopsies were wider (98% versus 76%). Invasion fronts were more readily assessable in Finnish biopsies (72% versus 40%). There was 86.8% agreement between TSR and 75% agreement between TIL evaluation using light microscopy and digital assessment. Significant agreement was obtained on comparing the TSR (P=0.04) and BD (P Conclusions: Biopsies of ≥5 mm depth from representative OTSCC areas are essential for prognostic information. Clinical pathologists are advised to assess BD score and TSR for prognostic features in such biopsies.

Background The prediction of overall survival in tongue cancer is important for planning of personalized care and patient counselling. Objectives This study compares the performance of a nomogram with a machine learning model to predict overall survival in tongue cancer. The nomogram and machine learning model were built using a large data set from the Surveillance, Epidemiology, and End Results (SEER) program database. The comparison is necessary to provide the clinicians with a comprehensive, practical, and most accurate assistive system to predict overall survival of this patient population. Methods The data set used included the records of 7596 tongue cancer patients. The considered machine learning algorithms were logistic regression, support vector machine, Bayes point machine, boosted decision tree, decision forest, and decision jungle. These algorithms were mainly evaluated in terms of the areas under the receiver-operating characteristic (ROC) curve (AUC) and accuracy values. The performance of the algorithm that produced the best result was compared with a nomogram to predict overall survival in tongue cancer patients. Results The boosted decision-tree algorithm outperformed other algorithms. When compared with a nomogram using external validation data, the boosted decision tree produced an accuracy of 88.7% while the nomogram showed an accuracy of 60.4%. In addition, it was found that age of patient, T stage, radiotherapy, and the surgical resection were the most prominent features with significant influence on the machine learning model’s performance to predict overall survival. Conclusion The machine learning model provides more personalized and reliable prognostic information of tongue cancer than the nomogram. However, the level of transparency offered by the nomogram in estimating patients’ outcomes seems more confident and strengthened the principle of shared decision making between the patient and clinician. Therefore, a combination of a nomogram – machine learning (NomoML) predictive model may help to improve care, provides information to patients, and facilitates the clinicians in making tongue cancer management-related decisions.

Background: Cell-in-cell structures (caused by cell cannibalistic activity) have been related to prognosis of many cancers. This is the first multi-institutional study to assess the prognostic impact of cell-in-cell structures in a large cohort of early oral tongue squamous cell carcinomas (OTSCC). Methods: A total of 308 cases from five Finnish University Hospitals and from the A.C. Camargo Cancer Center, São Paulo, Brazil, were included in this study. Cell-in-cell structures were evaluated on surgical postoperative sections that stained with hematoxylin and eosin staining. Results: We found that cell-in-cell structures associated with cancer-related mortality in univariable analysis with a hazard ratio (HR) of 2.99 (95%CI 1.52–5.88; P = 0.001). This association was confirmed in multivariable analysis (HR 2.22, 95%CI 1.12–4.44; P = 0.024). In addition, statistically significant associations were observed between the cell-in-cell structures and other adverse histopathologic characteristics including deep invasion (P

Tumour budding has emerged as a promising prognostic marker in many cancers. We systematically reviewed all studies that evaluated tumour budding in diagnostic biopsies. We conducted a systematic review of PubMed, MEDLINE, Scopus, Web of Science and Cochrane library for all articles that have assessed tumour budding in diagnostic (i.e. pretreatment or pre-operative) biopsies of any tumour type. Two independent researchers screened the retrieved studies, removed duplicates, excluded irrelevant studies and extracted data from the eligible studies. A total of 13 reports comprising 11 cohorts were found to have studied tumour budding in diagnostic biopsies. All these reports showed that evaluation of tumour budding in diagnostic biopsies was easily applicable. A strong association was observed between tumour budding score in diagnostic biopsies and corresponding surgical samples. Evaluation of tumour budding in diagnostic biopsies had a significant prognostic value for lymph node metastasis and patient survival. In all studies, tumour budding was a valuable marker of tumour aggressiveness and can be evaluated in technically satisfactory diagnostic biopsies. Thus, the assessment of tumour budding seems to identify the behaviour of cancer, and therefore to facilitate treatment planning.

Background The proper estimate of the risk of recurrences in early-stage oral tongue squamous cell carcinoma (OTSCC) is mandatory for individual treatment-decision making. However, this remains a challenge even for experienced multidisciplinary centers. Objectives We compared the performance of four machine learning (ML) algorithms for predicting the risk of locoregional recurrences in patients with OTSCC. These algorithms were Support Vector Machine (SVM), Naive Bayes (NB), Boosted Decision Tree (BDT), and Decision Forest (DF). Materials and methods The study cohort comprised 311 cases from the five University Hospitals in Finland and A.C. Camargo Cancer Center, Sao Paulo, Brazil. For comparison of the algorithms, we used the harmonic mean of precision and recall called F1 score, specificity, and accuracy values. These algorithms and their corresponding permutation feature importance (PFI) with the input parameters were externally tested on 59 new cases. Furthermore, we compared the performance of the algorithm that showed the highest prediction accuracy with the prognostic significance of depth of invasion (DOI). Results The results showed that the average specificity of all the algorithms was 71% . The SVM showed an accuracy of 68% and F1 score of 0.63, NB an accuracy of 70% and F1 score of 0.64, BDT an accuracy of 81% and F1 score of 0.78, and DF an accuracy of 78% and F1 score of 0.70. Additionally, these algorithms outperformed the DOI-based approach, which gave an accuracy of 63%. With PFI-analysis, there was no significant difference in the overall accuracies of three of the algorithms; PFI-BDT accuracy increased to 83.1%, PFI-DF increased to 80%, PFI-SVM decreased to 64.4%, while PFI-NB accuracy increased significantly to 81.4%. Conclusions Our findings show that the best classification accuracy was achieved with the boosted decision tree algorithm. Additionally, these algorithms outperformed the DOI-based approach. Furthermore, with few parameters identified in the PFI analysis, ML technique still showed the ability to predict locoregional recurrence. The application of boosted decision tree machine learning algorithm can stratify OTSCC patients and thus aid in their individual treatment planning.

AIMS Oral tongue squamous cell carcinoma (OTSCC) has a relatively poor outcome, and there is a need to identify better prognostic factors. Recently, tumour-stroma ratio (TSR) has been associated with prognosis in several cancers. The aim of this multi-institutional study was to evaluate the prognostic value of TSR from original haematoxylin and eosin (HE)-stained tumour-resection slides in a series of early-stage (cT1-2N0) OTSCC patients. METHODS AND RESULTS A TSR cutoff value of 50% was used to divide the patients into stroma-rich (≥50%) and stroma-poor (

It is of great clinical importance to identify simple prognostic markers from preoperative biopsies that could guide treatment planning. Here, we compared tumor budding (B), depth of invasion (D), and the combined scores (i.e., budding and depth of invasion (BD) histopathologic model) in preoperative biopsies and the corresponding postoperative specimens of oral tongue squamous cell carcinoma (OTSCC). Tumor budding and depth of invasion were evaluated in the pre- and postoperative samples from 100 patients treated for OTSCC. Sensitivity and specificity statistics were used. Our results showed statistically significant (P < 0.001) relationship between pre- and postoperative BD scores. There was an agreement between the pre- and postoperative BD model scores in 83 cases (83%) with 57.1% sensitivity (95% CI 39.4 to 73.7%) and 96.9% specificity (95% CI 89.3 to 99.6%). Our findings suggest that the BD model, analyzed from representative biopsies, could be used for the treatment planning of OTSCC.

Oral squamous cell carcinoma (OSCC) is a common malignancy of the head and neck region. OSCC has a relatively low survival rate and the incidence of the disease is increasing in some geographic areas. Staging and grading of OSCC are established prerequisites for management, as they influence risk stratification and are the first step toward personalized treatment. The current AJCC/UICC TNM staging (8th edition, 2017) of OSCC has included significant modifications through the incorporation of depth of invasion in the T stage and extracapsular spread/extranodal extension in the N stage. Further modifications for AJCC 8 have been suggested. On the other hand, the World Health Organization (WHO) classification (4th edition, 2017) still endorses a simple, differentiation-based histopathologic grading system of OSCC (despite its low prognostic value) and ignores factors such as tumor growth pattern and dissociation, stromal reactions (desmoplasia, local immune response), and tumor-stroma ratio. The various controversies and possible developments of the current staging and grading criteria of OSCC are briefly discussed in this update together with possible applications of artificial intelligence in the context of screening and risk stratification.

Little is known about the histopathological characteristics that may differentiate early oral tongue cancer (OTSCC) between young and older patients. From a total of 311 cases diagnosed with clinically early-stage OTSCC at 6 institutions, only 42 patients were young patients were aged ≤45 years. For comparison, 42 patients >60 years old were matched for center of management, clinical stage and gender. We compared epithelial and stromal histopathologic parameters between the two groups. Most of the parameters were similar between the two groups, although the young patients appeared to have marginally higher intensity of tumor budding, histologic risk score, infiltrative pattern of invasion and tumor-stroma ratio. However, none of the factors showed significant difference when comparing the two groups. The histological parameters reflect mechanisms of invasive growth and tissue response to invasive growth, but not the etiological difference in OTSCC between young and older patients. Further investigations are necessary to compare the genetic background of early OTSCC in the two groups.

Aims Previous studies have demonstrated that the tumour-stroma ratio (TSR) and tumour budding are of prognostic value for oral squamous cell carcinomas (OSCCs). The aim of this study was to evaluate the prognostic significance of those histological parameters, individually and in combination, for OSCC. Methods and results The TSR and tumour budding (the presence of five or more buds at the invasive front) were estimated in 254 patients with OSCC. The clinicopathological association was investigated with a chi-square test, and the prognostic significance (cancer-specific survival and disease-free survival) was verified with Kaplan-Meier analysis and the Cox proportional hazard model. The TSR (>= 50%, stroma-rich) was significantly and independently associated with both shortened cancer-specific survival and poor disease-free survival, whereas tumour budding was significantly associated with reduced cancer-specific survival. The TSR/tumour budding model was independently associated with a high risk of cancer mortality and recurrence (disease-free survival). In patients with early-stage tumours (clinical stage I and II, n = 103), the TSR, tumour budding and the TSR/tumour budding model were significantly associated with both cancer-related death and recurrence, whereas, in advanced-stage tumours (clinical stage III and IV, n = 144), only the TSR and the TSR/tumour budding model were significantly associated with cancer-specific survival. Conclusions The TSR, tumour budding and their combination provide significant information on OSCC outcome, suggesting that their incorporation in the routine evaluation of histopathological specimens might be useful in prognostication for OSCC patients.

Tumor-infiltrating lymphocytes (TILs) have shown a promising prognostic value in many epithelial cancers. We sought to assess the prognostic value of TILs in a multicenter cohort of early oral tongue squamous cell carcinoma (OTSCC). The percentage of TILs was assessed on the surgical resection slides stained with hematoxylin and eosin. The assessment of TILs was performed in the stromal compartment and in the intraepithelial compartment (at the invasive front and at the center of the tumor). We followed the method that was described recently by the International Immuno-Oncology Biomarker Working Group for the assessment of TILs. A total of 308 cases from the 5 Finnish university hospitals and from A.C. Camargo Cancer Center, São Paulo, Brazil, were included. We found a promising prognostic value for stromal TILs at the invasive front in the multivariable analysis with a hazard ratio of 2.61 (95% confidence interval [CI], 1.77‐3.83; P

IntroductionHNCs constitute a heterogenous group of neoplasms. A recent report based on GLOBOCAN database estimated diagnosis of more than half million new cases of HNC during 2018 45, and the incidence is expected to continue increasing according to estimate for 2030 46. HNC is associated with high mortality 45, and one of the main reasons for the low survival can be explained by late diagnosis. For example, human papilloma virus associated oropharyngeal squamous cell cancer has one of the most rapidly increasing incidences among all cancer types in high-income countries and supporting the development of effective early detection strategies is seen as an important approach to improve curative treatment (Lechner M, Breeze CE, O'Mahony JF, Masterson L. Early detection of HPV-associated oropharyngeal cancer. Lancet. 2019;393:2123.) (Timbang MR, Sim MW, Bewley AF, Farwell DG, Mantravadi A, Moore MG. HPV-related oropharyngeal cancer: a review on burden of the disease and opportunities for prevention and early detection. Hum Vaccin Immunother. 2019 May 3:1-9. doi: 10.1080/21645515.2019.1600985. [Epub ahead of print])The current methods to detect HNCs include visual inspection of the upper aerodigestive mucous membranes and pathological examination of tissue biopsy of a suspicious lesion. Serological and salivary biomarkers are under evaluation to aid in the early primary diagnosis or follow-up surveillance of this patient population but none of them has yet been proved useful in clinical practice (refs). Therefore, more reliable and noninvasive methods are warranted for early diagnosis of HNC.Exhaled breath analysisNon-invasive approaches to the early diagnosis of cancer is a crucial topic of research. Available methods include, for example, surface brushing and blood sampling. The main idea of these non-invasive approaches is to identify cancer biomarkers or signatures that would allow early detection of cancer before any clinical symptoms or signs develop. Such early diagnosis will lead to treatment planning at an early-stage and that, indeed, could improve the clinical outcome 1. However, daily diagnosis of many cancers (including those of head and neck) is still based on evaluation of changes in macroscopic appearance, radiological features and histopathological characteristics. The tools that are used in this traditional evaluation are not easily applicable in population screening as these diagnostic examinations either are invasive, expensive, and/or time-consuming, and involve exposure to radiation. On the other hand, analysis of exhaled breath would represent a non-invasive, fast and inexpensive screening tool that has shown promising results in many cancers 2-8. Easy access to sample supply is one of main advantages of breath analysis. The main gas phase constituents of exhaled breath are carbon dioxide, nitrogen, oxygen, water vapour and argon. In addition to these compounds, many volatile organic compounds (VOCs) are present at trace amounts, from part-per-million (ppm, 10-6) down to part-per-trillion (ppt, 10-12) levels. VOCs can be transferred to blood either in the lungs via gas exchange between alveoli and blood or they can be released in the lower or upper airways (including the oral and nasal cavity) 9. These volatile species can be analyzed in the gas phase using various mass spectrometry techniques, optical spectroscopy or sensors based on, for example, nanoparticles or semiconductive metal oxides. In addition to sampling the exhaled gas, breath samples can also be collected by condensing the breath on a cooled surface. The so-called exhaled breath condensate (EBC) is composed mostly of condensed water vapour but will also include small amounts of respiratory droplets containing nonvolatile molecules and water-soluble volatile compounds 10. The content of the EBC can be analyzed, for example, using enzyme immunoassay kits or chromatography – mass spectrometry techniques. The theory of exhaled breath analysis for cancer diagnosis is based on the concept that cancer initiation is associated with increase in oxidative stress that can cause alteration in the profile of DNA, proteins and other components 11. Such alterations can be detected in exhaled breath as increased or decreased concentrations of biomarkers connected with a specific disease that is associated with specific pathologic changes 12. 13. The history of research on breath analysis is strongly associated with Linus Pauling, the Nobel Prize winner in 1971, who explained that human breath is a complex gas containing more than 200 VOCs 14. To date, almost 900 different VOCs have been detected in exhaled breath 15. Methodological aspects in exhaled breath analysisCollection procedure: The collection procedure for a breath sample depends on whether the aim is to collect the gas phase portion of breath or the EBC. For gas phase samples, breath is either collected to sorbent materials or sample bags (offline analysis) or it can be analyzed immediately after the sample collection (online analysis). Storage in sorbent tubes or bags introduces risks related to sample stability during handling and storage 16. Exhalations can be divided into three phases. The initial brief phase contains gas from the oral cavity and trachea, this is often called “dead space phase”. The next phase is the mixed expiratory phase in which gas from the lungs and lower airways mixes with the dead space sample. The final phase is the end-tidal, which most closely reflects alveolar gas in the lungs. In most applications of breath analysis, the focus is on collecting the end-tidal phase and the first two phases are discarded. This can be done by real-time monitoring of the carbon dioxide content during sampling. Carbon dioxide originates fully from the alveolar gas-exchange and can be used as a marker for the end-tidal phase 16. However, in the case of HNC, the first two phases should not be discarded as they should contain the most relevant biomarkers for cancers in the upper aerodigestive tract.Condensation of exhaled breath occurs below the temperature of 4oC. Collecting devices for EBC use several different types of cooling maneuvers such as dry ice, wet ice with salt, and liquid nitrogen, and accordingly the condensate can be either liquid, solid or mix of both 17,18. EBC analysis is always performed offline. Importantly, it has been reported that the condensation temperature could affect different biomarkers’ concentration and therefore, reporting the condensation temperature is essential for process standardization and registration 18. There is a wide variety of exhaled breath collection devices such as EcoScreen Turbo 19, TURBO-DECCS 20, RTube TM 21, and devices for specific patient groups e.g. infants and children 22-24, and mechanically ventilated patients 25. Duration of sample collection: For gas phase sampling, the sampling time can be as short as the duration of a single exhalation (few seconds). When collecting the breath on a sorbent material, the concentrations of the analyte gases can be enriched by using longer sampling times (few minutes). In bag or online sampling, several samples can be acquired in succession to reduce the inter-individual variation of breath levels. Various physiological factors, such as breath holding, increased tidal volume and hyperventilation can have an influence on the retrieved breath concentrations but no universal breath gas sampling procedure currently exists. Some specific breath tests which are already in clinical use have been standardized, an example is the fractional nitric oxide (FeNO) test for measuring airway inflammation 26.Although the majority of published studies recommend EBC sample collection of 10 to 30 minutes, some studies reported short collection time of 3 minutes and others prolonged the time up to 60 minutes 27. The approximate volume of exhaled breath condensate after 10 to 15 minutes breathing is 1-3 ml 28. The length of sample collection time has a direct effect on the final volume 27. Increased tidal volume and/or minute ventilation, hyperventilation and mechanical ventilation are all associated with an increase in the volume of exhaled breath condensate 29-31.Sample storage: When using offline gas phase samples, the storage temperature and time depend on whether the sample is stored in a bag or a sorbent material. The optimal temperature for bag storage is 37 °C to avoid water condensation on bag surfaces. Storage losses depend heavily on the specific biomarkers and the used bag material. Bags manufactured from Tedlar have been shown to be stable for many compounds for up to 6 hours of storage 32. For samples that were collected onto a sorbent tube, a stable storage time of 1.5 months was achieved at – 80 °C. Out of the almost 600 compounds that were studied, a significant amount showed discernible levels of change in concentration after six months of storage 33.The optimum temperature for an EBC sample storage is below -70oC. However, some biomarkers require assessment of their stability at the storage temperature. Furthermore, division of the exhaled breath samples into aliquots is recommended as repetitive freezing and thawing may result in breakdown of certain compounds such as nucleic acids and prostaglandins 34.Potential contamination by saliva and oral bacterial activity: Salivary contamination can occur during collection of EBC and it is important confounding factor especially when analyzing volatile biomarkers. A clear example of salivary contamination is that exhaled breath nitrite levels are mostly attributable to oropharyngeal bacterial flora, as their levels decrease drastically rinsing the mouth with a chlorhexidine solution 35. Exclusion of saliva contamination can be done by testing salivary amylase in the EBC sample 36,37. Additionally, the ATS/ERS Task Force on EBC recommend using nasal clip to minimise the entry of nasal airway lining fluid into the sampled air and to ensure that all exhaled air will pass through the mouth 10. Oral bacteria and oral enzymatic activity also influence the exhaled breath gas levels. For example, exhaled ammonia is mainly produced by enzymatic hydrolysis of urea in the oral cavity 38.Potential breath biomarkers of HNC: In many neoplasms, exhaled breath has been a rich source of potential cancers biomarkers 11,39,40. These biomarkers can be divided into three categories. The first category includes the small volatile compounds. These can be measured in the gas phase and, in the case of water-soluble compounds also in the breath condensate (e.g. ammonia and formic acid). The second category includes biomolecules of low-molecular weight (e.g. isoprostanes, polypeptides and nucleic acids). The third category is miscellaneous including many compounds such as lipid mediators, chemokines and cytokines. The second and third category are mainly present in the breath condensate. DNA from exhaled breath condensate of healthy people has been used to identify mutations (e.g. TP53 gene mutations) that are associated with early neoplastic changes 41. A recent study has recognized several volatile organic compounds as breath gas biomarkers of thyroid cancer 39. Reported potential breath gas biomarkers for oral squamous cell carcinoma are aldehydes including undecane, dodecane, decanal, benzaldehyde, 3,7-dimethyl undecane, 4,5-dimethyl nonane, 1-octene, and hexadecane when analyzed by solid-phase microextraction with gas chromatography-mass spectrometry 42. By using linear discriminant analysis classification of these compounds, well-defined clusters for patients and controls were revealed 42. In addition, dimethyl disulfide, decamethylcyclopentasiloxane (D5) and p-xylene (PX) were reported as gas phase biomarkers that decrease after surgery 43. Ethanol, 2-propenenitrile and undecane were identified as exhaled gas biomarkers that could distinguish laryngeal and pharyngeal head and neck squamous cell carcinoma from benign tumors and from healthy subjects 44.Exhaled breath analysis as a diagnostic tool in head and neck cancerRecent research has analyzed exhaled breath to aid in early detection of HNC. An early attempt to analyze exhaled breath for diagnosis of HNC had been conducted by Hakim et al. (2011) 13 who used breath gas testing with nanoscale artificial nose. They were able to recognize patients with HNC from healthy people and from patients with lung cancer 13. The artificial nose based on nanoparticle sensors did not provide identification of the biomarkers responsible for the sensor response. A few years later, Gruber et al. 44 in their analysis of exhaled breath from patients with laryngeal and pharyngeal cancers found that ethanol, 2-propenenitrile and undecane can be used as potential biomarkers for these two cancers. Using artificially intelligent nanoarrays, Nakhleh et al. 47 have identified a set of many diseases including HNC from exhaled breath. In oral squamous cell carcinoma, a recent study has used exhaled breath analysis and found three compounds (benzaldehyde, 3,7-dimethylundecane, and butyl acetate) that have a relationship with pathological parameters of these cancers 42. Exhaled breath analysis as a predictive tool to monitor the treatment outcomeAssessment of treatment outcome is of great importance during the follow-up to ensure high survival rate and to early recognize any failure. Exhaled breath analysis has been recently introduced as an effective tool for monitoring response to treatment in lung cancer 48. In HNC, Hakim et al 13 suggested that breath analysis using artificial nose could be utilized as a test to follow-up after treatment of HNC especially for those cases at high-risk of developing a second primary tumor. Moreover, breath analysis from cured patients who underwent resection of HNC was similar to breath analysis of healthy control which indicates a successful surgery 49. Interestingly, Hartwig et al. 43 collected breath samples before and after surgical treatment of oral squamous cell carcinoma and compared the breath analysis for each case. They reported disappearance of cancer-associated volatile organic compounds in the breath after treatment 43. However, using breath analysis in monitoring the treatment of HNC is still a new field of research that requires more scientific efforts. Conclusion and FutureIn recent years, exhaled breath analysis has received increasing research interest in the early detection of many cancers. The currently available body of evidence refers to potential clinical use of exhaled breath in the early diagnosis of HNC easily and safely. Such evidence requires further validation in large cohorts and comparing different protocols that have been introduced. That will allow standardisation of the methods of breath sampling, including sample collection and storage. Translation of breath analysis from lab into clinic, after generalizability of the currently identified biomarkers, could be a step forward toward early detection of HNC through screening of high-risk populations. References1. Hashim D, Genden E, Posner M, Hashibe M, Boffetta P. Head and neck cancer prevention: from primary prevention to impact of clinicians on reducing burden. Ann Oncol. 2019;30(5):744-756.2. Oakley-Girvan I, Davis SW. Breath based volatile organic compounds in the detection of breast, lung, and colorectal cancers: A systematic review. Cancer Biomark. 2017;21(1):29-39.3. 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The eighth edition of the American Joint Committee on Cancer (AJCC8) staging manual has major changes in oral squamous cell carcinoma (OSCC). We searched PubMed, OvidMedline, Scopus, and Web of Science for studies that examined the performance of AJCC8 in OSCC. A total of 40 808 patients were included in the studies of our meta-analysis. A hazard ratio (HR) of 1.87 (95%CI 1.78-1.96) was seen for stage II, 2.65 (95%CI 2.51-2.80) for stage III, 3.46 (95%CI 3.31-3.61) for stage IVa, and 7.09 (95%CI 4.85-10.36) for stage IVb. A similar gradual increase in risk was noted for the N classification. For the T classification, however, there was a less clear variation in risk between T3 and T4. AJCC8 provides a good risk stratification for OSCC. Future research should examine the proposals introduced in the published studies to further improve the performance of AJCC8.

Invasion and metastasis are hallmarks of cancer. The concept of tumor budding at tumor-host interface has been documented in many carcinomas. A growing body of evidence indicates that tumor budding is a sign of invasion and early step for metastasis of many epithelial cancers including head and neck squamous cell carcinoma (HNSCC). In addition, recent research has underlined the importance of tumor budding as a promising prognosticator in HNSCC. This review summarizes the findings regarding tumor budding in HNSCC and focuses on the role of tumor budding in invasion and metastasis. Also, we highlight the prognostic significance of tumor budding in HNSCC and its potential for improving clinical decision making in terms of recommending optimal individualized treatment for this patient population.

Background Oral cancer can show heterogenous patterns of behavior. For proper and effective management of oral cancer, early diagnosis and accurate prediction of prognosis are important. To achieve this, artificial intelligence (AI) or its subfield, machine learning, has been touted for its potential to revolutionize cancer management through improved diagnostic precision and prediction of outcomes. Yet, to date, it has made only few contributions to actual medical practice or patient care. Objectives This study provides a systematic review of diagnostic and prognostic application of machine learning in oral squamous cell carcinoma (OSCC) and also highlights some of the limitations and concerns of clinicians towards the implementation of machine learning-based models for daily clinical practice. Data sources We searched OvidMedline, PubMed, Scopus, Web of Science, and Institute of Electrical and Electronics Engineers (IEEE) databases from inception until February 2020 for articles that used machine learning for diagnostic or prognostic purposes of OSCC. Eligibility criteria Only original studies that examined the application of machine learning models for prognostic and/or diagnostic purposes were considered. Data extraction Independent extraction of articles was done by two researchers (A.R. & O.Y) using predefine study selection criteria. We used the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) in the searching and screening processes. We also used Prediction model Risk of Bias Assessment Tool (PROBAST) for assessing the risk of bias (ROB) and quality of included studies. Results A total of 41 studies were published to have used machine learning to aid in the diagnosis/or prognosis of OSCC. The majority of these studies used the support vector machine (SVM) and artificial neural network (ANN) algorithms as machine learning techniques. Their specificity ranged from 0.57 to 1.00, sensitivity from 0.70 to 1.00, and accuracy from 63.4 % to 100.0 % in these studies. The main limitations and concerns can be grouped as either the challenges inherent to the science of machine learning or relating to the clinical implementations. Conclusion Machine learning models have been reported to show promising performances for diagnostic and prognostic analyses in studies of oral cancer. These models should be developed to further enhance explainability, interpretability, and externally validated for generalizability in order to be safely integrated into daily clinical practices. Also, regulatory frameworks for the adoption of these models in clinical practices are necessary.

The proliferation marker, securin, is involved in the progression of many carcinomas. However, its expression in oral tongue squamous cell carcinoma (OTSCC) has not been previously studied. We examined securin expression by immunohistochemistry in OTSCC. A total of 93 cases treated for OTSCC were included in this study. Expression of securin in OTSCC was studied by immunohistochemistry of tissue microarrays (52 cases) and routine tumor sections (41 cases). Securin overexpression is significantly associated with higher tumor grade (P = 0.03). Overexpression of securin was observed more frequently in advanced stages of OTSCC than in earlier stages but the difference was not statistically significant. These findings suggest that overexpression of securin in OTSCC may be important during progression of this cancer. No significant association was found between securin expression and the prognosis of OTSCC.

Estimation of risk of recurrence in early-stage oral tongue squamous cell carcinoma (OTSCC) remains a challenge in the field of head and neck oncology. We examined the use of artificial neural networks (ANNs) to predict recurrences in early-stage OTSCC. A Web-based tool available for public use was also developed. A feedforward neural network was trained for prediction of locoregional recurrences in early OTSCC. The trained network was used to evaluate several prognostic parameters (age, gender, T stage, WHO histologic grade, depth of invasion, tumor budding, worst pattern of invasion, perineural invasion, and lymphocytic host response). Our neural network model identified tumor budding and depth of invasion as the most important prognosticators to predict locoregional recurrence. The accuracy of the neural network was 92.7%, which was higher than that of the logistic regression model (86.5%). Our online tool provided 88.2% accuracy, 71.2% sensitivity, and 98.9% specificity. In conclusion, ANN seems to offer a unique decision-making support predicting recurrences and thus adding value for the management of early OTSCC. To the best of our knowledge, this is the first study that applied ANN for prediction of recurrence in early OTSCC and provided a Web-based tool. Electronic supplementary material The online version of this article (10.1007/s00428-019-02642-5) contains supplementary material, which is available to authorized users.

Background Colorectal carcinoma development progresses through a sequence of normal mucosa-polyp-carcinoma. Early detection of premalignancy is crucial for improved outcomes. We evaluated the diagnostic performance of plasma miRNA-221 and its feasibility in discriminating premalignant from malignant neoplasms and correlating it with immunohistochemical p53 expression. Methods A total of 109 plasma samples were collected (76 carcinoma, 14 premalignant, and 19 controls). MiRNA221 was quantified by qPCR for calculation of ∆Ct using RNU6B as endogenous control. p53 immunohistochemical staining was performed on corresponding tissue. Results Plasma miRNA-221 and p53 in tissues were significantly overexpressed in the malignant group when compared with the premalignant and control groups. Plasma miRNA-221 was increased in late-stage tumors with nodal or distant metastasis. ROC curve construction for distinguishing between malignant and premalignant tumors revealed a cutoff value of 2.97 with 74% sensitivity, 79% specificity, 73.7% positive predictive value and 78.6% negative predictive value (AUC = 0.824; p = 0.001). Plasma miRNA-221 significantly correlated with p53 in cancer samples (r = 0.507). Conclusions MiRNA-221 could have a diagnostic role in differentiating malignant from premalignant neoplasms and could also serve as a predictive marker indicating tumor progression.

Background Despite the importance of immune checkpoints in immunotherapy, the prognostic value of these molecules remains controversial in oral squamous cell carcinoma (OSCC). We performed a systematic review to investigate the prognostic significance of the immune checkpoints in OSCC. Materials A systematic search was conducted in Ovid Medline, Scopus and Cochrane libraries, and all studies that evaluated the prognostic significance of immune checkpoints in OSCC were systematically retrieved. Results Twelve immune checkpoints/modulators were studied for their prognostic values in OSCC patients between 1985 and 2017. Seven immune checkpoints (FKBP51, B7-H4, B7-H6, ALHD1, PD-L1, B7-H3 and IDO1) were reported to be associated with poor patients' survival in at least one study, and five (CTLA-4, TLT-2, VISTA, PD-L2 and PD-1) did not have a significant prognostic value. PD-L1 results were controversial as it was reported to be associated with both better and worse patients' survival. Conclusions Even though immune checkpoint markers had high expectation for OSCC prognostication, our systematic review revealed that the majority of them had been studied only once. The other molecules, which had been studied more than once, had controversial findings, except B7-H3.

One of the main changes in the 8th edition of the American Joint Committee on Cancer (AJCC) for staging of oral cancer is the inclusion of depth of invasion (DOI) in the T category. However, cancers in different oral subsites have variable behavior, with oral tongue squamous cell carcinoma (OTSCC) being the most aggressive one even at early stage. Thus, it is necessary to evaluate the performance of this new T category in homogenous cohort of early OTSCC. Therefore, we analyzed a large cohort of patients with a small (ae4 cm) OTSCC to demonstrate the differences in T stage between the AJCC 7th and 8th editions. A total of 311 early-stage cases (AJCC 7th) of OTSCC were analyzed. We used 5 mm and 10 mm DOI for upstaging from T1 to T2 and from T2 to T3 respectively, as in the AJCC 8th. We further reclassified the cases according to our own proposal suggesting 2 mm to upstage to T2 and 4 mm to upstage to T3. According to AJCC 7th, there were no significant differences in the survival analysis. When we applied the 8th edition, many cases were upstaged to T3 and thus associated with worse disease-specific survival (HR 2.37, 95% CI 1.12-4.99) and disease-free survival (HR 2.12, 95% CI 1.09-4.08). Based on our proposal, T3 cases were associated with even worse disease-specific survival (HR 4.19, 95% CI 2.27-7.74). The 8th edition provides better survival prediction for OTSCC than the 7th and can be further optimized by lowering the DOI cutoffs.

The prognostic significance of tumor-infiltrating lymphocytes (TILs) has been studied recently in many cancers. For the first time in a nonendemic region, we have evaluated the prognostic value of TILs in a whole population based nationwide cohort of nasopharyngeal carcinoma (NPC) in Finland. A total of 115 cases from Finnish hospitals were included. TILs were analyzed using hematoxylin and eosin stained slides according to the criteria of the International Immuno-Oncology Biomarker Working Group. TILs were evaluated separately in stromal and tumor compartments. The log-rank test and univariable and multivariable analyses were used to compare survival in patients with tumors with low and high TILs. A significant positive correlation was observed between the occurrence of intratumoral and stromal TILs (P

Background: Identifying informative prognostic biomarkers for oral tongue squamous cell carcinoma (OTSCC) is of great importance in order to better predict tumour behaviour and to guide treatment planning. Here, we summarise existing evidence regarding immunohistochemical prognostic biomarkers for OTSCC. Methods: A systematic search of the literature was performed using the databases of Scopus, Ovid Medline, Web of Science and Cochrane Library. All studies which had investigated the prognostic significance of immunohistochemical biomarkers in OTSCC during the period from 1985 to 2015 were retrieved. For the five most often evaluated biomarkers a random-effects meta-analysis on overall survival was performed, including those studies that provided the necessary statistical results. Results: A total of 174 studies conducted during the last three decades were found, and in these 184 biomarkers were evaluated for the prognostication of OTSCC. The five biomarkers most frequently assessed were p53, Ki-67, p16, VEGFs and cyclin D1. In the meta-analyses, the most promising results of the prognostic power for OTSCC were obtained for cyclin D1. For studies of VEGF A and C the results were equivocal, but the pooled analysis of VEGF A separately showed it to be a useful prognosticator for OTSCC. There was no sufficient evidence to support p53, Ki-67 and p16 as prognostic biomarkers for OTSCC. Limitations in the quality of the published studies (e.g., small cohorts, lack of compliance with REMARK guidelines) are widespread. Conclusions: Numerous biomarkers have been presented as useful prognosticators for OTSCC, but the quality of the conduct and reporting of original studies is overall unsatisfactory which does not allow reliable conclusions. The value of two biomarkers (VEGF-A and cyclin D1) should be validated in a multicentre study setting following REMARK guidelines.

Objective This study evaluated the association of four histopathological grading systems (WHO grading system, malignancy grading of the deep invasive margins (MG), histological risk (HR) model, and tumor budding and depth of invasion (BD) model) with clinicopathological parameters and outcome of 113 oral squamous cell carcinomas to identify their roles in prognosis. Methods Demographic and clinical features were obtained from patients' records. Sections from all paraffin-embedded blocks were evaluated according to the four grading systems. Demographic and clinical associations were analyzed using chi-square test, and correlations between the grading systems were established with the Spearman's rank correlation test. Survival curves were performed with Kaplan–Meier method, and multivariate analysis based on Cox proportional hazard model was calculated. Results Significant associations with survival were observed for WHO grading system and BD model in the univariate analysis, but only the BD model was significantly associated with disease outcome as an independent prognostic marker. Age, tumor size, and presence of regional metastasis were also independent markers of reduced survival. Conclusion A significant association between the BD model and outcome of OSCC patients was observed, indicating this new histopathological grading system as a possible prognostic tool.

Despite early diagnosis and treatment, almost 20 % of patients with early-stage (cT1-cT2N0) oral tongue squamous cell carcinoma (OTSCC) still die of their disease. The prognosis of OTSCC patients is influenced by several demographic, clinical, and histopathologic factors. The aim of this multicenter international study was to find which of the factors age, gender, stage, grade, lymphocytic host re- sponse, perineural invasion, worst pattern of invasion, or depth of invasion has the strongest prognostic power in early-stage OTSCC. Patient data of 479 patients with early-stage (cT1-2N0) OTSCC in Finland, Brazil, and the USA were retrieved and analyzed using Cox proportional hazards regression models. Our results indicate that depth of invasion (DOI) and worst pattern of invasion (WPOI) are the strongest pathological predictors for locoregional recurrence, with a hazard ratio (HR) for 4 mm DOI of 1.67 (95 % confidence interval (CI) 1.07-2.60) and HR for WPOI of 1.46 (95 %C I 0.95-2.25). In addition, mor- tality from early OTSCC was also predicted by DOI (HR 2.44, 95 % CI 1.34-4.47) and by WPOI (HR 2.34, 95 % CI 1.26-4.32). We suggest that clinically early-stage oral tongue carcinomas 4 mm or deeper, or with a growth pat- tern of small cell islands or satellites, should be considered as high-risk tumors which require multimodality treatment.

The prognostication of patient outcome is one of the greatest challenges in the management of early stage oral tongue squamous cell carcinoma (OTSCC). This study introduces a simple histopathological model for the prognostication of survival in patients with early OTSCC. A total of 311 cases (from Finland and Brazil) with clinically evaluated early stage OTSCC (cT1-T2cN0cM0) were included in this multicentre retrospective study. Tumour budding (B) and depth of invasion (D) were scored on haematoxylin-eosin-stained cancer slides. The cut-off point for tumour budding was set at 5 buds (low

Background: To determine the prevalence, types, and risk factors of oral potentially malignant disorders (OPMDs) among a group of Arab Jordanian dental patients, and to evaluate their awareness and attitudes toward early diagnosis and treatment. Materials and Methods: A total of 1,041 patients attending a University Hospital for dental care were examined for the presence of OPMDs. Histopathological examination was performed on all cases clinically diagnosed and patients were directly interviewed to evaluate their knowledge and attitudes toward early detection and treatment of oral cancer. Results: The prevalence of OPMDs overall was 2.8%. Lichen planus/lichenoid lesions were the most common lesions (1.8%) followed by leukoplakias (0.48%), chronic hyperplastic candidiosis (0.38%), and erythroplakia (0.096%). Smoking, alcohol, and age (>40 years) were the main identifiable risk factors. Patients with OPMDs displayed a general lack of awareness and negative attitudes towards early diagnosis and treatment. Conclusions: OPMDs among Arab dental patients are relatively uncommon and awareness about oral cancer among Jordanian dental patients is low. Interventions to improve public knowledge about oral cancer and attitudes toward early diagnosis and treatment are urgently indicated.

BACKGROUND: Mucoepidermoid carcinoma (MEC) is the most common salivary gland malignancy. Although several biomarkers have been evaluated, histological grade remains the most valuable prognostic marker. Toll-like receptor 9 (TLR9) is an immune receptor recognizing microbial DNA. Its expression associates with prognosis or cancer properties in several cancers. This study examined the role of TLR9 in MEC. METHODS: Sixty patients with salivary gland MEC were collected from two Finnish university hospitals, and tumor samples were stained for TLR9. Salivary gland high-grade MEC cell line (UT-MUC-1) was cultured to assess TLR9 and MMP-13 expression. The function of TLR9 was studied in vitro using traditional Matrigel invasion assay and novel human myoma organotypic model. RESULTS: Cancer-specific survival was related with tumor grade (P = 0.01), and there were no deaths in patients with low-grade MEC. TLR9 was expressed in 56 of 60 (93%) tumors. High TLR9 expression indicated better survival in the patient series (P = 0.002) and showed a trend for association with lower disease stage (P = 0.06) and higher differentiation grade (P = 0.068). In multivariate analysis, TLR9 expression was prognostically insignificant due to heavy correlation to disease stage and higher gradus. Treating UT-MUC-1 cells with TLR9 ligand CpG in vitro induced MMP-13 expression and invasion in Matrigel invasion assay, whereas decreased invasion was seen in myoma organotypic model. CONCLUSION: Functional TLR9 is present in salivary MEC, and high level of expression may indicate good prognosis. However, more studies are needed to evaluate biologicalconsequencesofTLR9interactionintumorcells. J Oral Pathol Med (2014) 43: 530–537

Oral tongue squamous cell carcinoma (OTSCC) is the most common carcinoma of the oral cavity, and according to a recent analysis of the Surveillance, Epidemiology, and End Results (SEER) database, patients with OTSCC are more likely to experience cause-specific mortality than patients with SCC of the other oral subsites (1). The traditional tumor (T), lymph node (N) and metastasis (M) staging system has been the cornerstone for clinical classification of OTSCC, although it has been widely criticized for its low prognostic value, especially in early-stage cases (2,3).

Human papillomavirus is detected in over 50% of oropharyngeal squamous cell carcinomas. Human papillomavirus–positive oropharyngeal squamous cell carcinomas differ from human papillomavirus–negative tumors, and both expression patterns are classified as distinct entities. The Bmi-1 oncogene is a well-known member of the mammalian polycomb-group family. HESC5:3 and HES77 are newly developed monoclonal antibodies produced against undifferentiated embryonic stem cells. Our aim was to explore their roles in both human papillomavirus–positive and –negative oropharyngeal squamous cell carcinomas. Our cohort comprised 202 consecutive oropharyngeal squamous cell carcinoma patients diagnosed and treated with curative intent. We used tissue microarray tumor blocks to study the immunohistochemical expression of Bmi-1, HESC5:3, and HES77. We compared the expressions of these stem cell markers with p16 immunoexpression and human papillomavirus status, as well as with other characteristics of the tumor, and with patients’ clinical data and follow-up data. Human papillomavirus– and p16-positive tumors expressed less Bmi-1 and more HESC5:3 than the negative tumors. HES77 expression was high in human papillomavirus–positive oropharyngeal squamous cell carcinoma, but it did not correlate with p16 positivity. In our multivariable model, Bmi-1 and HESC5:3 were still associated with human papillomavirus, but the association between human papillomavirus and HES77 remained absent. In conclusion, Bmi-1, HESC5:3, and HES77 may have a different role in human papillomavirus–positive and human papillomavirus–negative tumors. There was no correlation between Bmi-1, HESC5:3, and HES77 expression and survival.

Complex molecular pathways regulate cancer invasion. This study overviewed proteins and microRNAs (miRNAs) involved in oral tongue squamous cell carcinoma (OTSCC) invasion. The human highly aggressive OTSCC cell line HSC-3 was examined in a 3D organotypic human leiomyoma model. Non-invasive and invasive cells were laser-captured and protein expression was analyzed using mass spectrometry-based proteomics and miRNA expression by microarray. In functional studies the 3D invasion assay was replicated after silencing candidate miRNAs, miR-498 and miR-940, in invasive OTSCC cell lines (HSC-3 and SCC-15). Cell migration, proliferation and viability were also studied in the silenced cells. In HSC-3 cells, 67 proteins and 53 miRNAs showed significant fold-changes between non-invasive vs. invasive cells. Pathway enrichment analyses allocated "Focal adhesion" and "ECM-receptor interaction" as most important for invasion. Significantly, in HSC-3 cells, miR-498 silencing decreased the invasion area and miR-940 silencing reduced invasion area and depth. Viability, proliferation and migration weren't significantly affected. In SCC-15 cells, down-regulation of miR-498 significantly reduced invasion and migration. This study shows HSC-3 specific miRNA and protein expression in invasion, and suggests that miR-498 and miR-940 affect invasion in vitro, the process being more influenced by mir-940 silencing in aggressive HSC-3 cells than in the less invasive SCC-15.

Incidence rates for oral tongue squamous cell carcinoma (SCC) are steadily rising worldwide.All patients diagnosed with primary oral tongue SCC at the 5 university hospitals in Finland from 2005 to 2009 were studied. The mean follow-up time was 43 months (median, 54 months; range, 0-111 months).Three hundred sixty patients with primary oral tongue SCC were identified. Treatment with curative intent was provided for 328 patients (91%). The 5-year disease-specific survival (DSS) rates were as follows: stage I 87%; stage II 73%; stage III 69%; and stage IV 51%. The 5-year recurrence-free survival in general has improved from 47% in our previous published series (1995-1999) to 65% in the current series (p.001).The outcome of oral tongue SCC has significantly improved in Finland. However, the relatively high number of disease recurrences in patients with stage I and II disease, when compared with patients with stage III and IV disease, calls for an investigation of new treatment approaches. © 2017 Wiley Periodicals, Inc. Head Neck 39: 1306-1312, 2017.