Establishment of oral squamous cell carcinoma cell line and magnetic bead-based isolation and characterization of its CD90/CD44 subpopulations

Gene-Expression Patterns of Tumor and Peritumor Tissues of Smoking and Non-Smoking HPV-Negative Patients with Head and Neck Squamous Cell Carcinoma

We studied the gene-expression patterns in specimens of tumor and peritumor tissue biopsies of 26 patients with head and neck carcinomas depending on smoking status. Histological and immunohistochemical examinations verified that all tumors belonged to the "classical" subgroup of head and neck carcinomas, and the HPV-negative tumor status was confirmed. The expression of 28 tumor-associated genes determined by RT-PCR was independent of patients' sex or age, TNM status, degree of differentiation, or tissue localization. Moreover, in peritumor tissue, none of the 28 genes were differentially expressed between the groups of smoking and nonsmoking patients. During oncotransformation in both studied groups, there were similar processes typical for HNSCC progression: the expression levels of paired keratins 4 and 13 were reduced, while the expression levels of keratin 17 and CD44 were significantly increased. However, further investigation revealed some distinctive features: the expression of the genes EGFR and TP63 increased significantly only in the nonsmoking group, and the expression of IL6, CDKN2A, EGF, and PITX1 genes changed only in the smoking group. In addition, correlation analysis identified several clusters within which genes displayed correlations in their expression levels. The largest group included 10 genes: TIMP1, TIMP2, WEE1, YAP, HIF1A, PI3KCA, UTP14A, APIP, PTEN, and SLC26A6. The genetic signatures associated with smoking habits that we have found may serve as a prerequisite for the development of diagnostic panels/tests predicting responses to different therapeutic strategies for HNSCC.

Differential Markers of Subpopulations of Epithelial Cells of the Larynx in Squamous Cell Carcinoma

In squamous cell carcinoma of the larynx, the population of epithelial cells in the tumor tissue is initially heterogeneous and, in addition to tumor cells invading the organ mucosa, includes normal epithelial cells of protein-mucous glands and cells of the stratified epithelium covering the mucous membrane. A search for differential markers to separate these subpopulations was carried out. The surface marker CD44 and cytokeratins 5 and 17 that are often used to verify carcinoma cells, are common markers for all epithelial cells of the larynx. In highly differentiated carcinoma, subpopulations of normal and tumor epithelial cells can be separated by the level of expression of cytokeratins 10 and 18 and nuclear markers Ki-67 and p63. However, in moderately differentiated carcinoma, tumor cells and normal cells of the basal layer of the stratified epithelium covering the mucous membrane of the larynx have similar phenotypes, which should be taken into account when conducting experimental studies.

Precision Medicine in Head and Neck Cancers: Genomic and Preclinical Approaches

Head and neck cancers (HNCs) represent the sixth most widespread malignancy worldwide. Surgery, radiotherapy, chemotherapeutic and immunotherapeutic drugs represent the main clinical approaches for HNC patients. Moreover, HNCs are characterised by an elevated mutational load; however, specific genetic mutations or biomarkers have not yet been found. In this scenario, personalised medicine is showing its efficacy. To study the reliability and the effects of personalised treatments, preclinical research can take advantage of next-generation sequencing and innovative technologies that have been developed to obtain genomic and multi-omic profiles to drive personalised treatments. The crosstalk between malignant and healthy components, as well as interactions with extracellular matrices, are important features which are responsible for treatment failure. Preclinical research has constantly implemented in vitro and in vivo models to mimic the natural tumour microenvironment. Among them, 3D systems have been developed to reproduce the tumour mass architecture, such as biomimetic scaffolds and organoids. In addition, in vivo models have been changed over the last decades to overcome problems such as animal management complexity and time-consuming experiments. In this review, we will explore the new approaches aimed to improve preclinical tools to study and apply precision medicine as a therapeutic option for patients affected by HNCs.

DeepFoci: Deep learning-based algorithm for fast automatic analysis of DNA double-strand break ionizing radiation-induced foci

DNA double-strand breaks (DSBs), marked by ionizing radiation-induced (repair) foci (IRIFs), are the most serious DNA lesions and are dangerous to human health. IRIF quantification based on confocal microscopy represents the most sensitive and gold-standard method in radiation biodosimetry and allows research on DSB induction and repair at the molecular and single-cell levels. In this study, we introduce DeepFoci - a deep learning-based fully automatic method for IRIF counting and morphometric analysis. DeepFoci is designed to work with 3D multichannel data (trained for 53BP1 and γH2AX) and uses U-Net for nucleus segmentation and IRIF detection, together with maximally stable extremal region-based IRIF segmentation. The proposed method was trained and tested on challenging datasets consisting of mixtures of nonirradiated and irradiated cells of different types and IRIF characteristics - permanent cell lines (NHDFs, U-87) and primary cell cultures prepared from tumors and adjacent normal tissues of head and neck cancer patients. The cells were dosed with 0.5-8 Gy γ-rays and fixed at multiple (0-24 h) postirradiation times. Under all circumstances, DeepFoci quantified the number of IRIFs with the highest accuracy among current advanced algorithms. Moreover, while the detection error of DeepFoci remained comparable to the variability between two experienced experts, the software maintained its sensitivity and fidelity across dramatically different IRIF counts per nucleus. In addition, information was extracted on IRIF 3D morphometric features and repair protein colocalization within IRIFs. This approach allowed multiparameter IRIF categorization of single- or multichannel data, thereby refining the analysis of DSB repair processes and classification of patient tumors, with the potential to identify specific cell subclones. The developed software improves IRIF quantification for various practical applications (radiotherapy monitoring, biodosimetry, etc.) and opens the door to advanced DSB focus analysis and, in turn, a better understanding of (radiation-induced) DNA damage and repair.

DDX5 Silencing Suppresses the Migration of Basal cell Carcinoma Cells by Downregulating JAK2/STAT3 Pathway

Basal cell carcinoma is driven by the aberrant activation of hedgehog signaling. DEAD (Asp-Glu-Ala-Asp) box protein 5 is frequently overexpressed in human cancer cells and associated with the tumor growth and invasion. The purpose of this study was to investigate the role of DEAD (Asp-Glu-Ala-Asp) box protein 5 in the growth, migration, and invasion of basal cell carcinoma. The role of DEAD (Asp-Glu-Ala-Asp) box protein 5 was detected by quantitative real-time polymerase chain reaction, Western blot, and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick-end labeling assay in basal cell carcinoma cells. The associations between JAK2/STAT3 pathway and DEAD (Asp-Glu-Ala-Asp) box protein 5 were analyzed in basal cell carcinoma cells. Results showed that DEAD (Asp-Glu-Ala-Asp) box protein 5 is overexpressed in basal cell carcinoma cells. DEAD (Asp-Glu-Ala-Asp) box protein 5 knockdown inhibited the migration and invasion of basal cell carcinoma cells. DEAD (Asp-Glu-Ala-Asp) box protein 5 knockdown increased the apoptosis of basal cell carcinoma cells induced by tunicamycin. Results found that DEAD (Asp-Glu-Ala-Asp) box protein 5 knockdown increased JAK2 and STAT3 expression in basal cell carcinoma cells. JAK2 inhibitor decreased STAT3 expression and abolished the inhibitory effects of DEAD (Asp-Glu-Ala-Asp) box protein 5 silencing on migration and invasion in basal cell carcinoma cells. In conclusion, these results indicate that DEAD (Asp-Glu-Ala-Asp) box protein 5 is a potential target for inhibiting basal cell carcinoma cells growth, migration, and invasion by downregulating JAK2/STAT3 pathway.

An Effective Primary Head and Neck Squamous Cell Carcinoma In Vitro Model

Head and neck squamous cell carcinoma is a highly malignant disease and research is needed to find new therapeutic approaches. Faithful experimental models are required for this purpose. Here, we describe the specific cell culture conditions enabling the efficient establishment of primary cell culture models. Whereas a classical 10% serum-containing medium resulted in the growth of fibroblast-like cells that outcompeted epithelial cells, we found that the use of specific culture conditions enabled the growth of epithelial tumor cells from HPV+ and HPV- head and neck cancer tissue applicable for research. EpCAM and high Thy-1 positivity on the cell surface were mutually exclusive and distinguished epithelial and fibroblast-like subpopulations in all primary cultures examined and thus can be used to monitor stromal contamination and epithelial cell content. Interestingly, cells of an individual patient developed tumor spheroids in suspension without the use of ultra-low attachment plates, whereas all other samples exclusively formed adherent cell layers. Spheroid cells were highly positive for ALDH1A1 and hence displayed a phenotype reminiscent of tumor stem cells. Altogether, we present a system to establish valuable primary cell culture models from head and neck cancer tissue at high efficiency that might be applicable in other tumor entities as well.