Adenoid cystic carcinoma (ACC) is a salivary gland malignancy characterized by slow but persistent growth, frequent local recurrence, and late metastatic progression. Patients with unresectable, recurrent, or metastatic disease have limited therapeutic options. Efforts to identify effective therapeutic targets have been hindered by the limited availability of well-characterized ACC models. In this study, we established 11 ACC cell lines and performed RNA sequencing of nine cell lines and their matched primary tumors to evaluate the preservation and evolution of molecular and lineage-associated characteristics during cell line establishment. Comparative transcriptomic analysis revealed reduced epithelial and luminal differentiation programs in the cell lines, accompanied by enrichment of myoepithelial, EMT-, and cancer stem cell-associated transcriptional programs. Digital deconvolution and single-sample gene set enrichment analysis supported enrichment of hybrid EMT/stem-like states during in vitro propagation, while comparison with publicly available primary-recurrent ACC data demonstrated partial preservation of recurrence-associated plasticity and invasion programs. Protein-level validation of representative epithelial, myoepithelial, EMT, and stemness markers supported the major transcriptomic changes. In addition, a cell line with a higher stemness signature showed reduced sensitivity to cisplatin. Together, these findings indicate that ACC cell line establishment is associated with transcriptional reprogramming and enrichment of plastic, EMT/stem-like states while retaining selected ACC lineage characteristics. These models provide experimentally tractable platforms for investigating ACC progression, therapeutic response, and mechanisms of treatment resistance.
Purpose Nasal vestibule squamous cell carcinoma (NV-SCC) lacks a universally accepted, site-specific staging system, limiting comparability across series and potentially influencing treatment selection. We evaluated variation in stage assignment and prognostic performance across four currently used classification systems in a single-centre cohort. Methods Patients with previously untreated NV-SCC managed between 2000 and 2024 were retrospectively reviewed. Tumours were restaged according to the UICC/AJCC sinonasal classification, the UICC/AJCC non-melanoma skin cancer classification, Wang’s classification, and the Rome classification. Overall survival (OS), disease-free survival (DFS), and local control (LC) were estimated using Kaplan-Meier analysis. Cox regression models explored associations between clinicopathological variables, treatment modality and outcomes. Results Seventy-eight patients were analysed. Restaging showed substantial discordance in stage assignment across systems. UICC-sinonasal staging assigned a considerable proportion of patients to locally advanced categories, whereas Wang’s classification concentrated most cases in cT2. The Rome classification appeared to provide a clinically coherent redistribution of early and advanced disease, although overlap between adjacent stages persisted. Bone infiltration showed the most consistent adverse association with OS, DFS, and LC across several staging-based models. Treatment-related associations were observed in selected models but should be considered exploratory because of the retrospective design and non-randomised treatment selection. Conclusion Applying different staging systems to NV-SCC showed considerable discordance in stage assignment and limited discrimination between adjacent categories. Vestibule-specific staging approaches, including the Rome classification, appeared anatomically coherent but require further validation. Bone infiltration was the most consistent adverse prognostic factor and should be considered in future refinements of staging systems.
Objective MRI-based 3D models provide patient-specific spatial information on the relationship between parotid gland tumors and the facial nerve. However, their potential role in clinical practice and the level of support for their implementation remain unclear. This study aimed to assess the level of consensus among surgeons on the current clinical workflows in parotid gland surgery and the future role of 3D models. Study design: We used a three-round Delphi study to explore consensus among surgeons performing more than five parotid surgeries annually. Round 1 consisted of semi-structured interviews about parotid surgery, innovations, and the use of 3D models. Inductive analysis was used to formulate statements and questions for round 2. In rounds 2 and 3, participants rated the questions and statements on a 7-point adjective scale. Results: A panel of 15 surgeons, including 9 otolaryngologists and 6 oral and maxillofacial surgeons from nine Dutch hospitals, completed all study rounds. Partial consensus was observed for 10% of statements in round 3. Trends toward greater importance of both MRI scanning and 3D model use were identified in cases involving malignancy, facial nerve dysfunction, deep lobe tumors, fixed tumors, non-palpable tumors, and indications for a mastoidectomy. Stronger trends toward importance were observed for using 3D models in preoperative planning and patient counseling than in their use during surgery. Conclusion: Although consensus was limited, this study identified indications for MRI use and highlighted the perceived value of 3D models in parotid gland tumor surgery.
Purpose: Taste alteration is a common post-treatment side effect of head and neck cancer (HNC) radiotherapy. Accurate normal tissue complication probability (NTCP) models can support treatment planning aimed at reducing side effects that impair quality-of-life. Deep learning (DL) offers opportunities to incorporate full 3D dose, CT, and organofinterest (OOI) data. Using a large prospective cohort, this study explores whether CNN and transformerbased DL models can outperform a conventional logistic regression model for predicting taste alteration 6 months after radiotherapy. Material/methods: Data from 972 patients was used, with the endpoint being moderatetosevere patientreported taste alteration at six months (EORTC QLQH&N35). DL models were trained using 3D dose distributions, planning CT, OOI segmentations and clinical features. A conventional NTCP model using oral cavity mean dose, parotid mean dose, and age served as reference. Attention maps were evaluated for the transformer-based DL model to quantify the model attention to specific regions of the head and neck area. In addition, two cropping approaches for the 3D data were compared. Results: The CNN and transformer DL models performed comparable to the reference NTCP model in the test set (Reference: AUC = 0.71; ResNet: AUC = 0.68; TransRP: AUC = 0.71), though calibration was best for the reference model. Shifting the crop improved DL performance and transformer attention focused on supraglottic and submandibular regions. Conclusion: This study showed that the prediction of taste alteration can be achieved using DL models, particularly transformer-based models which, in contrast to CNNs, can account for global features of comprehensive 3D information of dose distribution, CT-images and organs-of-interest segmentations.
Receipt of timely adjuvant radiation after primary surgery for head and neck cancer is a well-established quality benchmark. The social and structural drivers of suboptimal care, however, remain incompletely characterized. Very little work has been done on understanding the combined and interacting effects of social determinants on postoperative radiation therapy (PORT) receipt and timing. Upon examining PORT delivery among intermediate- and high-risk oropharyngeal squamous cell carcinoma patients, we identified that patients who are both uninsured and live far from a treatment center are at the highest risk for not receiving adjuvant radiation therapy. By identifying which specific patient subpopulations are most vulnerable to delayed or omitted treatment, this analysis provides actionable data to guide institutional interventions, optimize resource allocation, and support advocacy efforts aimed at closing equity gaps in head and neck cancer care.
