Evolving multidisciplinary treatment of squamous cell carcinoma of the head and neck in India✰

FAM83B promotes cell proliferation via regulating the expression of CDK4/CDK6/CCND1 complex in laryngeal squamous cell carcinoma

FAM83B, as one of the FAM83 family members, has been closely involved in cell transformation, and a growing number of scholars have been studied its role in tumours over the years. Whereas the effect and potential mechanism of FAM83B in laryngeal squamous cell carcinoma (LSCC) have not been investigated. In this research, we discovered that the expression quantity of FAM83B was remarkably higher in LSCC tissues (79.65 ± 35.98) than in matched adjacent tissues (59.34 ± 32.59) by tissue microarrays and immunohistochemistry. Furthermore, expression of FAM83B was knocked down in HEP-2 and TU177 cell lines via lentivirus, and in the course of intracorporal and extracorporeal experiments, FAM83B knockdown showed the inhibition of tumour growth, migration, and invasion ability. Moreover, cell cycle assay showed that FAM83B knockdown leads to an apparent accumulation of cells in the G1 phase, indicating that FAM83B knockdown can inhibit cell proliferation. Meanwhile, western blotting (WB) demonstrated that FAM83B knockdown led to a significant reduction in CDK4/CDK6/CCND1 protein expression, which may have decelerated cell cycle progression. Collectively, this study demonstrates that FAM83B serves as an oncogene in LSCC, promoting cell proliferation by controlling the protein expression of CDK4, CDK6, and CCND1, thus inducing a transference of the G1 stage to S stage in cell-cycle of LSCC cells. These results provide an academic foundation for elucidating the mechanism of LSCC occurrence and evolution and for developing treatment strategies for LSCC.

Social, Ethical and Treatment Related Problems Faced by Healthcare Workers in the Care of Head and Neck Cancer Patients: A Narrative Review from the Bioethics Consortium from India

Head and neck cancer (HNC) presents a variety of ethical difficulties for an oncologist involved in screening, diagnosis, treatment, and rehabilitation that are challenging to address, especially for those professionals/people who are not trained in medical ethics. The bioethics department has spent the last ten years compiling information and rating the seriousness of numerous niche ethical concerns and their effects on healthcare professionals practising in India. Based on these findings, the current analysis makes an effort to outline the different challenges faced by oncologists when screening, diagnosing, treating, and rehabilitating people affected with HNC, particularly in a traditional nation like India. According to the authors, this is the first overview to address these issues from an Indian viewpoint, and it represents a small effort to document a crucial but unaddressed component of cancer treatment. It is hoped that these endeavours would aid in educating upcoming healthcare professionals on how to effectively handle the difficulties.

Effects of immune inflammation in head and neck squamous cell carcinoma: Tumor microenvironment, drug resistance, and clinical outcomes

Background: Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor with a very high mortality rate, and a large number of studies have confirmed the correlation between inflammation and malignant tumors and the involvement of inflammation-related regulators in the progression of HNSCC. However, a prognostic model for HNSCC based on genes involved in inflammatory factors has not been established. Methods: First, we downloaded transcriptome data and clinical information from patients with head and neck squamous cell carcinoma from TCGA and GEO (GSE41613) for data analysis, model construction, and differential gene expression analysis, respectively. Genes associated with inflammatory factors were screened from published papers and intersected with differentially expressed genes to identify differentially expressed inflammatory factor-related genes. Subgroups were then typed according to differentially expressed inflammatory factor-related genes. Univariate, LASSO and multivariate Cox regression algorithms were subsequently applied to identify prognostic genes associated with inflammatory factors and to construct prognostic prediction models. The predictive performance of the model was evaluated by Kaplan-Meier survival analysis and receiver operating characteristic curve (ROC). Subsequently, we analyzed differences in immune composition between patients in the high and low risk groups by immune infiltration. The correlation between model genes and drug sensitivity (GSDC and CTRP) was also analyzed based on the GSCALite database. Finally, we examined the expression of prognostic genes in pathological tissues, verifying that these genes can be used to predict prognosis. Results: Using univariate, LASSO, and multivariate cox regression analyses, we developed a prognostic risk model for HNSCC based on 13 genes associated with inflammatory factors (ITGA5, OLR1, CCL5, CXCL8, IL1A, SLC7A2, SCN1B, RGS16, TNFRSF9, PDE4B, NPFFR2, OSM, ROS1). Overall survival (OS) of HNSCC patients in the low-risk group was significantly better than that in the high-risk group in both the training and validation sets. By clustering, we identified three molecular subtypes of HNSCC carcinoma (C1, C2, and C3), with C1 subtype having significantly better OS than C2 and C3 subtypes. ROC analysis suggests that our model has precise predictive power for patients with HNSCC. Enrichment analysis showed that the high-risk and low-risk groups showed strong immune function differences. CIBERSORT immune infiltration score showed that 25 related and differentially expressed inflammatory factor genes were all associated with immune function. As the risk score increases, specific immune function activation decreases in tumor tissue, which is associated with poor prognosis. We also screened for susceptibility between the high-risk and low-risk groups and showed that patients in the high-risk group were more sensitive to talazoparib-1259, camptothecin-1003, vincristine-1818, Azd5991-1720, Teniposide-1809, and Nutlin-3a (-) -1047.Finally, we examined the expression of OLR1, SCN1B, and PDE4B genes in HNSCC pathological tissues and validated that these genes could be used to predict the prognosis of HNSCC. Conclusion: In this experiment, we propose a prognostic model for HNSCC based on inflammation-related factors. It is a non-invasive genomic characterization prediction method that has shown satisfactory and effective performance in predicting patient survival outcomes and treatment response. More interdisciplinary areas combining medicine and electronics will be explored in the future.