Head and neck cancer of unknown primary: unveiling primary tumor sites through machine learning on DNA methylation profiles.

BACKGROUND: The unknown tissue of origin in head and neck cancer of unknown primary (hnCUP) leads to invasive diagnostic procedures and unspecific and potentially inefficient treatment options for patients. The most common histologic subtype, squamous cell carcinoma, can stem from various tumor primary sites, including the oral cavity, oropharynx, larynx, head and neck skin, lungs, and esophagus. DNA methylation profiles are highly tissue-specific and have been successfully used to classify tissue origin. We therefore developed a support vector machine (SVM) classifier trained with publicly available DNA methylation profiles of commonly cervically metastasizing squamous cell carcinomas (n = 1103) in order to identify the primary tissue of origin of our own cohort of squamous cell hnCUP patient's samples (n = 28). Methylation analysis was performed with Infinium MethylationEPIC v1.0 BeadChip by Illumina. RESULTS: The SVM algorithm achieved the highest overall accuracy of tested classifiers, with 87%. Squamous cell hnCUP samples on DNA methylation level resembled squamous cell carcinomas commonly metastasizing into cervical lymph nodes. The most frequently predicted cancer localization was the oral cavity in 11 cases (39%), followed by the oropharynx and larynx (both 7, 25%), skin (2, 7%), and esophagus (1, 4%). These frequencies concord with the expected distribution of lymph node metastases in epidemiological studies. CONCLUSIONS: On DNA methylation level, hnCUP is comparable to primary tumor tissue cancer types that commonly metastasize to cervical lymph nodes. Our SVM-based classifier can accurately predict these cancers' tissues of origin and could significantly reduce the invasiveness of hnCUP diagnostics and enable a more precise therapy after clinical validation.

Integrated Molecular and Histological Insights for Targeted Therapies in Mesenchymal Sinonasal Tract Tumors.

PURPOSE OF REVIEW: This review aims to provide a comprehensive overview of mesenchymal sinonasal tract tumors (STTs), a distinct subset of STTs. Despite their rarity, mesenchymal STTs represent a unique clinical challenge, characterized by their rarity, often slow progression, and frequently subtle or overlooked symptoms. The complex anatomy of the sinonasal area, which includes critical structures such as the orbit, brain, and cranial nerves, further complicates surgical treatment options. This underscores an urgent need for more advanced and specialized therapeutic approaches. RECENT FINDINGS: Advancements in molecular diagnostics, particularly in next-generation sequencing, have significantly enhanced our understanding of STTs. Consequently, the World Health Organization has updated its tumor classification to better reflect the distinct histological and molecular profiles of these tumors, as well as to categorize mesenchymal STTs with greater accuracy. The growing understanding of the molecular characteristics of mesenchymal STTs opens new possibilities for targeted therapeutic interventions, marking a significant shift in treatment paradigms. This review article concentrates on mesenchymal STTs, specifically addressing sinonasal tract angiofibroma, sinonasal glomangiopericytoma, biphenotypic sinonasal sarcoma, and skull base chordoma. These entities are marked by unique histopathological and molecular features, which challenge conventional treatment approaches and simultaneously open avenues for novel targeted therapies. Our discussion is geared towards delineating the molecular underpinnings of mesenchymal STTs, with the objective of enhancing therapeutic strategies and addressing the existing shortcomings in the management of these intricate tumors.

[Digital transformation of a routine histopathology lab : Dos and don'ts!] / Digitalisierung der histopathologischen Routinediagnostik : Dos and Don'ts!

The implementation of digital histopathology in the laboratory marks a crucial milestone in the overall digital transformation of pathology. This shift offers a range of new possibilities, including access to extensive datasets for AI-assisted analyses, the flexibility of remote work and home office arrangements for specialists, and the expedited and simplified sharing of images and data for research, conferences, and tumor boards. However, the transition to a fully digital workflow involves significant technological and personnel-related efforts. It necessitates careful and adaptable change management to minimize disruptions, particularly in the personnel domain, and to prevent the loss of valuable potential from employees who may be resistant to change. This article consolidates our institute's experiences, highlighting technical and personnel-related challenges encountered during the transition to digital pathology. It also presents a comprehensive overview of potential difficulties at various interfaces when converting routine operations to a digital workflow.

Molecular subtyping of head and neck cancer - Clinical applicability and correlations with morphological characteristics.

AIM: We aimed to evaluate the applicability of a customized NanoString panel for molecular subtyping of recurrent or metastatic head and neck squamous cell carcinoma (R/M-HNSCC). Additionally, histological analyses were conducted, correlated with the molecular subtypes and tested for their prognostic value. MATERIAL AND METHODS: We conducted molecular subtyping of R/M-HNSCC according to the molecular subtypes defined by Keck et al. For molecular analyses a 231 gene customized NanoString panel (the most accurately subtype defining genes, based on previous analyses) was applied to tumor samples from R/M-HNSCC patients that were treated in the CeFCiD trial (AIO/IAG-KHT trial 1108). A total of 130 samples from 95 patients were available for sequencing, of which 80 samples from 67 patients passed quality controls and were included in histological analyses. H&E stained slides were evaluated regarding distinct morphological patterns (e.g. tumor budding, nuclear size, stroma content). RESULTS: Determination of molecular subtypes led to classification of tumor samples as basal (n = 46, 45 %), inflamed/mesenchymal (n = 31, 30 %) and classical (n = 26, 25 %). Expression levels of Amphiregulin (AREG) were significantly higher for the basal and classical subtypes compared to the mesenchymal subtype. While molecular subtypes did not have an impact on survival, high levels of tumor budding were associated with poor outcomes. No correlation was found between molecular subtypes and histological characteristics. CONCLUSIONS: Utilizing the 231-gene NanoString panel we were able to determine the molecular subtype of R/M-HNSCC samples by the use of FFPE material. The value to stratify for different treatment options remains to be explored in the future. The prognostic value of tumor budding was underscored in this clinically well annotated cohort.

The Role of SOX2 and SOX9 in Radioresistance and Tumor Recurrence.

Head and neck squamous cell carcinoma (HNSCC) exhibits considerable variability in patient outcome. It has been reported that SOX2 plays a role in proliferation, tumor growth, drug resistance, and metastasis in a variety of cancer types. Additionally, SOX9 has been implicated in immune tolerance and treatment failures. SOX2 and SOX9 induce treatment failure by a molecular mechanism that has not yet been elucidated. This study explores the inverse association of SOX2/SOX9 and their distinct expression in tumors, influencing the tumor microenvironment and radiotherapy responses. Through public RNA sequencing data, human biopsy samples, and knockdown cellular models, we explored the effects of inverted SOX2 and SOX9 expression. We found that patients expressing SOX2LowSOX9High showed decreased survival compared to SOX2HighSOX9Low. A survival analysis of patients stratified by radiotherapy and human papillomavirus brings additional clinical relevance. We identified a gene set signature comprising newly discovered candidate genes resulting from inverted SOX2/SOX9 expression. Moreover, the TGF-ß pathway emerges as a significant predicted contributor to the overexpression of these candidate genes. In vitro findings reveal that silencing SOX2 enhances tumor radioresistance, while SOX9 silencing enhances radiosensitivity. These discoveries lay the groundwork for further studies on the therapeutic potential of transcription factors in optimizing HNSCC treatment.

Carcinoid syndrome caused by a pulmonary carcinoid mimics intestinal manifestations of ulcerative colitis: A case report.

BACKGROUND: Pulmonary carcinoids are rare, low-grade malignant tumors characterized by neuroendocrine differentiation and relatively indolent clinical behavior. Most cases present as a slow-growing polypoidal mass in the major bronchi leading to hemoptysis and pulmonary infection due to blockage of the distal bronchi. Carcinoid syndrome is a paraneoplastic syndrome caused by the systemic release of vasoactive substances that presents in 5% of patients with neuroendocrine tumors. Due to such nonspecific presentation, most patients are misdiagnosed or diagnosed late and may receive several courses of antibiotics to treat recurrent pneumonia before the tumor is diagnosed. CASE SUMMARY: We report the case of a 48-year-old male who presented with cough, dyspnea, a history of recurrent pneumonitis, and therapy-refractory ulcerative colitis that completely subsided after the resection of a pulmonary carcinoid. CONCLUSION: We report and emphasize pulmonary carcinoid as a differential diagnosis in patients with nonresponding inflammatory bowel diseases and recurrent pneumonia.

Predicting HPV association using deep learning and regular H&E stains allows granular stratification of oropharyngeal cancer patients.

Human Papilloma Virus (HPV)-associated oropharyngeal squamous cell cancer (OPSCC) represents an OPSCC subgroup with an overall good prognosis with a rising incidence in Western countries. Multiple lines of evidence suggest that HPV-associated tumors are not a homogeneous tumor entity, underlining the need for accurate prognostic biomarkers. In this retrospective, multi-institutional study involving 906 patients from four centers and one database, we developed a deep learning algorithm (OPSCCnet), to analyze standard H&E stains for the calculation of a patient-level score associated with prognosis, comparing it to combined HPV-DNA and p16-status. When comparing OPSCCnet to HPV-status, the algorithm showed a good overall performance with a mean area under the receiver operator curve (AUROC) = 0.83 (95% CI = 0.77-0.9) for the test cohort (n = 639), which could be increased to AUROC = 0.88 by filtering cases using a fixed threshold on the variance of the probability of the HPV-positive class - a potential surrogate marker of HPV-heterogeneity. OPSCCnet could be used as a screening tool, outperforming gold standard HPV testing (OPSCCnet: five-year survival rate: 96% [95% CI = 90-100%]; HPV testing: five-year survival rate: 80% [95% CI = 71-90%]). This could be confirmed using a multivariate analysis of a three-tier threshold (OPSCCnet: high HR = 0.15 [95% CI = 0.05-0.44], intermediate HR = 0.58 [95% CI = 0.34-0.98] p = 0.043, Cox proportional hazards model, n = 211; HPV testing: HR = 0.29 [95% CI = 0.15-0.54] p < 0.001, Cox proportional hazards model, n = 211). Collectively, our findings indicate that by analyzing standard gigapixel hematoxylin and eosin (H&E) histological whole-slide images, OPSCCnet demonstrated superior performance over p16/HPV-DNA testing in various clinical scenarios, particularly in accurately stratifying these patients.

Independent Tissue-Based Biomarkers in Endometrioid Endometrial Cancer: Tumor Budding in Microsatellite Instability and WHO Grading in Copy-Number-Low Patients.

The molecular characterization of endometrial endometrioid adenocarcinomas has provided major advances in its prognostic stratification. However, risk assessment of microsatellite instability (MSI) and copy-number (CN)-low cases remains a challenge. Thus, we aimed to identify tissue-based morphologic biomarkers that might help in the prognostic stratification of these cases. Histomorphologic parameters (WHO grading, tumor budding (TB), tumor-stroma ratio (as a quantitative description of stromal desmoplasia), tumor-infiltrating lymphocytes (TIL), "microcystic, elongated, fragmented" (MELF) pattern) were analyzed in resection specimens of the TCGA-UCEC cohort (n = 228). For each quantitative parameter, a two-tiered system was developed utilizing systematically determined cutoffs. Associations with survival outcomes were calculated in univariate and multivariate analysis and validated in two independent cohorts. In MSI tumors, only TB remained an independent prognostic factor. TB (≥3 buds/high-power field) was associated with inferior outcomes and with lymph node metastases. The prognostic significance of TB was confirmed in two validation cohorts. For CN-low tumors, established grading defined by the WHO was independently prognostic with inferior outcomes for high-grade tumors. The evaluation of TB might help in identifying MSI-patients with unfavorable prognosis who, e.g., could benefit from lymphadenectomy. WHO-based grading facilitates independent prognostic stratification of CN-low endometrioid adenocarcinomas. Therefore, we propose the utilization of TB and WHO-based grading, two tissue-based and easy-to-assess biomarkers, in MSI/CN-low endometrial carcinomas for improved clinical management.

Novel Discovery of the Somatostatin Receptor (SSTR2) in Pleomorphic Adenomas via Immunohistochemical Analysis of Tumors of the Salivary Glands.

Reliable preoperative diagnosis between salivary gland tumor entities is difficult. In this monocentric retrospective study, we examined the somatostatin receptor 2 (SSTR2) status of salivary gland tumors after salivary gland tumor resection via immunohistochemistry (IHC), and stains were compared in analogy to the HER2 mamma scale. A total of 42.3% of all pleomorphic adenoma (PA) tumors (42 of 99, 95% confidence interval 32.5-52.8%) demonstrated ≥20% of cells displaying the SSTR2 as compared to just 1% of all other tumors (1/160, 95% CI 0.02-3.4%). The other tumor was a neuroendocrine carcinoma. PA had a higher intensity of SSTR2 staining, with 90.9% staining ≥ an intensity of 2 (moderate). Tumors with an intensity of SSTR2 expression equal to or greater than 2 had an 89.9% likelihood of being a PA (95% CI: 82.2-95.0%, AUC: 0.928). Only one Warthin tumor demonstrated a 'strong' SSTR2 staining intensity. No Warthin tumor showed a percentage of cells staining for SSTR2 above ≥20%. This result demonstrates consistent and strong expression of SSTR2 in PAs as compared to Warthin tumors, which may allow physicians to utilize radioligand-somatostatin analog PET CT/MR imaging to diagnose the PA. SSTR2 positivity, if shown to be clinically relevant, may allow peptide receptor radionuclide therapy in the future.

A distinct stimulatory cDC1 subpopulation amplifies CD8+ T cell responses in tumors for protective anti-cancer immunity.

Type 1 conventional dendritic cells (cDC1) can support T cell responses within tumors but whether this determines protective versus ineffective anti-cancer immunity is poorly understood. Here, we use imaging-based deep learning to identify intratumoral cDC1-CD8+ T cell clustering as a unique feature of protective anti-cancer immunity. These clusters form selectively in stromal tumor regions and constitute niches in which cDC1 activate TCF1+ stem-like CD8+ T cells. We identify a distinct population of immunostimulatory CCR7neg cDC1 that produce CXCL9 to promote cluster formation and cross-present tumor antigens within these niches, which is required for intratumoral CD8+ T cell differentiation and expansion and promotes cancer immune control. Similarly, in human cancers, CCR7neg cDC1 interact with CD8+ T cells in clusters and are associated with patient survival. Our findings reveal an intratumoral phase of the anti-cancer T cell response orchestrated by tumor-residing cDC1 that determines protective versus ineffective immunity and could be exploited for cancer therapy.

Assessment of the Tumor-Stroma Ratio and Tumor-Infiltrating Lymphocytes in Colorectal Cancer: Inter-Observer Agreement Evaluation.

BACKGROUND: To implement the new marker in clinical practice, reliability assessment, validation, and standardization of utilization must be applied. This study evaluated the reliability of tumor-infiltrating lymphocytes (TILs) and tumor-stroma ratio (TSR) assessment through conventional microscopy by comparing observers' estimations. METHODS: Intratumoral and tumor-front stromal TILs, and TSR, were assessed by three pathologists using 86 CRC HE slides. TSR and TILs were categorized using one and four different proposed cutoff systems, respectively, and agreement was assessed using the intraclass coefficient (ICC) and Cohen's kappa statistics. Pairwise evaluation of agreement was performed using the Fleiss kappa statistic and the concordance rate and it was visualized by Bland-Altman plots. To investigate the association between biomarkers and patient data, Pearson's correlation analysis was applied. RESULTS: For the evaluation of intratumoral stromal TILs, ICC of 0.505 (95% CI: 0.35-0.64) was obtained, kappa values were in the range of 0.21 to 0.38, and concordance rates in the range of 0.61 to 0.72. For the evaluation of tumor-front TILs, ICC was 0.52 (95% CI: 0.32-0.67), the overall kappa value ranged from 0.24 to 0.30, and the concordance rate ranged from 0.66 to 0.72. For estimating the TSR, the ICC was 0.48 (95% CI: 0.35-0.60), the kappa value was 0.49 and the concordance rate was 0.76. We observed a significant correlation between tumor grade and the median of TSR (0.29 (95% CI: 0.032-0.51), p-value = 0.03). CONCLUSIONS: The agreement between pathologists in estimating these markers corresponds to poor-to-moderate agreement; implementing immune scores in daily practice requires more concentration in inter-observer agreements.

Unraveling the Role of Epithelial-Mesenchymal Transition in Adenoid Cystic Carcinoma of the Salivary Glands: A Comprehensive Review.

Salivary adenoid cystic carcinoma (SACC) is considered a challenging malignancy; it is characterized by a slow-growing nature, yet a high risk of recurrence and distant metastasis, presenting significant hurdles in its treatment and management. At present, there are no approved targeted agents available for the management of SACC and systemic chemotherapy protocols that have demonstrated efficacy remain to be elucidated. Epithelial-mesenchymal transition (EMT) is a complex process that is closely associated with tumor progression and metastasis, enabling epithelial cells to acquire mesenchymal properties, including increased mobility and invasiveness. Several molecular signaling pathways have been implicated in the regulation of EMT in SACC, and understanding these mechanisms is crucial to identifying new therapeutic targets and developing more effective treatment approaches. This manuscript aims to provide a comprehensive overview of the latest research on the role of EMT in SACC, including the molecular pathways and biomarkers involved in EMT regulation. By highlighting the most recent findings, this review offers insights into potential new therapeutic strategies that could improve the management of SACC patients, especially those with recurrent or metastatic disease.

Establishment of a Machine Learning Model for the Risk Assessment of Perineural Invasion in Head and Neck Squamous Cell Carcinoma.

Perineural invasion is a prevalent pathological finding in head and neck squamous cell carcinoma and a risk factor for unfavorable survival. An adequate diagnosis of perineural invasion by pathologic examination is limited due to the availability of tumor samples from surgical resection, which can arise in cases of definitive nonsurgical treatment. To address this medical need, we established a random forest prediction model for the risk assessment of perineural invasion, including occult perineural invasion, and characterized distinct cellular and molecular features based on our new and extended classification. RNA sequencing data of head and neck squamous cell carcinoma from The Cancer Genome Atlas were used as a training cohort to identify differentially expressed genes that are associated with perineural invasion. A random forest classification model was established based on these differentially expressed genes and was validated by inspection of H&E-stained whole image slides. Differences in epigenetic regulation and the mutational landscape were detected by an integrative analysis of multiomics data and single-cell RNA-sequencing data were analyzed. We identified a 44-gene expression signature related to perineural invasion and enriched for genes mainly expressed in cancer cells according to single-cell RNA-sequencing data. A machine learning model was trained based on the expression pattern of the 44-gene set with the unique feature to predict occult perineural invasion. This extended classification model enabled a more accurate analysis of alterations in the mutational landscape and epigenetic regulation by DNA methylation as well as quantitative and qualitative differences in the cellular composition in the tumor microenvironment between head and neck squamous cell carcinoma with or without perineural invasion. In conclusion, the newly established model could not only complement histopathologic examination as an additional diagnostic tool but also guide the identification of new drug targets for therapeutic intervention in future clinical trials with head and neck squamous cell carcinoma patients at a higher risk for treatment failure due to perineural invasion.

Tumour budding-based grading as independent prognostic biomarker in HPV-positive and HPV-negative head and neck cancer.

BACKGROUND: The prognostic significance of tumour budding (TB) and minimal cell nest size (MCNS) was shown in human papillomavirus (HPV)-negative head and neck squamous cell carcinomas (HNSCC). However, the optimisation of cutpoints, the prognostic impact in HPV-positive HNSCC, and the comparison with other histopathological grading systems are insufficiently investigated. METHODS: TB and MCNS were analysed digitally in 1 and 10 high-power fields (HPF) of 331 HPV-positive and HPV-negative cases from TCGA. Optimising the cutpoints a new cellular dissociation grading (CDG) system was defined and compared to the WHO grading and the Brandwein-Gensler (BG) risk model. RESULTS: The two-tiered CDG system based solely on TB yielded optimal prognostic stratification with shortened overall survival for CDG-high cases. Optimal cut-offs were two buds (1 HPF) and six buds (10 HPF), respectively. Analysing MCNS did not add prognostic significance to quantifying TB. CDG was a significant prognostic marker in HPV-negative and HPV-positive tumours and prognostically superior to the WHO and BG systems. High CDG was associated with clinically occult lymph-node metastases. CONCLUSIONS: The most comprehensive study of TB in HNSCC so far confirmed its prognostic impact in HPV-negative tumours and for the first time in HPV-positive tumours. Further studies are warranted to evaluate its applicability for therapy guidance in HNSCC.

A Novel Subgroup of UCHL1-Related Cancers Is Associated with Genomic Instability and Sensitivity to DNA-Damaging Treatment.

PURPOSE: Identification of molecularly-defined cancer subgroups and targeting tumor-specific vulnerabilities have a strong potential to improve treatment response and patient outcomes but remain an unmet challenge of high clinical relevance, especially in head and neck squamous cell carcinoma (HNSC). EXPERIMENTAL DESIGN: We established a UCHL1-related gene set to identify and molecularly characterize a UCHL1-related subgroup within TCGA-HNSC by integrative analysis of multi-omics data. An extreme gradient boosting model was trained on TCGA-HNSC based on GSVA scores for gene sets of the MSigDB to robustly predict UCHL1-related cancers in other solid tumors and cancer cell lines derived thereof. Potential vulnerabilities of UCHL1-related cancer cells were elucidated by an in-silico drug screening approach. RESULTS: We established a 497-gene set, which stratified the TCGA-HNSC cohort into distinct subgroups with a UCHL1-related or other phenotype. UCHL1-related HNSC were characterized by higher frequencies of genomic alterations, which was also evident for UCHL1-related cancers of other solid tumors predicted by the classification model. These data indicated an impaired maintenance of genomic integrity and vulnerability for DNA-damaging treatment, which was supported by a favorable prognosis of UCHL1-related tumors after radiotherapy, and a higher sensitivity of UCHL1-related cancer cells to irradiation or DNA-damaging compounds (e.g., Oxaliplatin). CONCLUSION: Our study established UCHL1-related cancers as a novel subgroup across most solid tumor entities with a unique molecular phenotype and DNA-damaging treatment as a specific vulnerability, which requires further proof-of-concept in pre-clinical models and future clinical trials.

Comparison of PD-L1 expression in squamous cell cancer of unknown primary and oropharyngeal squamous cell carcinoma.

PURPOSE: The tumorigenesis of squamous cell cancer of unknown primary (SCCUP) in the head and neck area has not been decoded so far, while poor survival rates and limited therapeutic options pose a serious challenge. The aim of this project was to investigate immunological characteristics of SCCUPs and compare them to oropharyngeal squamous cell carcinoma (OPSCC). METHODS: PD-L1 expression (TC) was examined by immunohistochemistry in 50 lymph node metastases of SCCUP and 47 primaries of OPSCC. CD3 + and CD8 + lymphocytic infiltration was measured in 5 high power fields. Expression of p16 and HPV ISH were assessed. RESULTS: SCCUP demonstrated a significantly higher expression of PD-L1 than OPSCC. In p16-negative SCCUPs PD-L1 proved to be an independent prognostic factor to prioritize high-risk patients. CONCLUSIONS: Immunologic differences between SCCUP and OPSCC were detected. A higher PD-L1 expression in SCCUP could potentially facilitate further evaluation of checkpoint inhibitor therapy.

Tumour cell budding and spread through air spaces in squamous cell carcinoma of the lung - Determination and validation of optimal prognostic cut-offs.

PURPOSE: Prognostic stratification of patients with squamous cell carcinomas of the lung (SCC-L) is challenging. Therefore, we investigated several histomorphological parameters (tumour cell budding (TCB), spread through air spaces (STAS), tumour-stroma-ratio, immune cell infiltration) which could potentially serve as prognostic parameters in SCC-L. We aimed to systematically determine optimal cut-off-values and assess the prognostic capability of these patterns. We furthermore assessed interobserver variability (IOV) for prognostically significant patterns TCB and STAS. EXPERIMENTAL DESIGN: The Cancer Genome Atlas (TCGA) study cohort consisted of 335 patients with SCC-L. Histomorphological parameters analysed comprised TCB, minimal cell nest size (MCNS), STAS, stroma content and immune cell infiltration. The most significant cut-off-values were determined and univariate and multivariate survival outcomes were estimated. The identified cut-off-points were validated in an independent SCC-L cohort (n = 346 patients). Two experienced pathologists probed IOV in the validation cohort. RESULTS: In the TCGA study cohort, TCB, STAS and immune cell infiltration were identified as significant prognostic parameters. TCB-high tumours, a high number of STAS foci, extensive STAS for distance of STAS in alveoli and a low immune cell infiltration remained as independent prognostic factors in multivariate Cox proportional hazard analyses for overall survival (OS). The significance of TCB, number of STAS foci and distance of STAS in alveoli for OS could be validated in the validation cohort. IOV reached a Kappa ≥ 0.89 for prognostic parameters. CONCLUSIONS: We determined optimal cut-offs and identified TCB and STAS (number of STAS foci, distance of STAS in alveoli) as independent and uncorrelated prognostic factors for patients with SCC-L. The significance was validated in a large independent cohort. IOV was almost perfect for prognostic parameters. We propose the application of TCB- and STAS-based grading in SCC-L as prognostic morphological classifiers.

NOTCH1 Intracellular Domain and the Tumor Microenvironment as Prognostic Markers in HNSCC.

(1) Background: NOTCH1 is the second most common mutated gene in whole-exome sequencing of HNSCC. The aim of this project was to gain further insight into the relevance of NOTCH1 in HNSCC, potentially establishing NOTCH1 as a prognostic marker or therapeutic target; (2) Methods: NOTCH1 was silenced via RNA interference in six HNSCC cell lines and the impact was evaluated in migration and proliferation assays. Subsequently, the protein expression of NOTCH1 intracellular domain (NICD) and NOTCH1 mRNA expression were examined in 70 oropharyngeal squamous cell cancer tissue samples. Lastly, the NICD expression was compared with the local infiltration of lymphocytes, measured with the immunoscore; (3) Results: Knockdown of NOTCH1 decreased migration and proliferation. A high NICD expression was associated with lower OS. A high immunoscore resulted in significantly better OS. NICD expression was independent of the immunoscore and as a whole differentiated three distinct prognostic groups; (4) Conclusions: These data suggest that NOTCH1 is involved in migration and proliferation of HNSCC cell lines. In vivo, NICD expression was associated with overall survival and could, therefore, be used as a prognostic marker. NICD expression differs from NOTCH1 mRNA levels, potentially explaining the previously suggested bimodal role as an oncogene and tumor suppressor in HNSCC.