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Biomedicines
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Novel Approaches towards Targeted Head and Neck Cancer Therapies
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Novel Approaches towards Targeted Head and Neck Cancer Therapies

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cancer Biology and Oncology".

Deadline for manuscript submissions: closed (31 January 2025) | Viewed by 7433

Special Issue Editor

Dr. Emilia Wiecheć

E-Mail Website
Guest Editor
Department of Biomedical and Clinical Sciences (BKV), Division of Cell Biology, Linköping University, Region Östergötland, 58185 Linköping, Sweden
Interests: head and neck cancer; cancer stem cells; biomarkers of treatment response; 3D tumor models; genetic and epigenetics of cancer cells; cancer metabolism EditInterests:

Special Issue Information

Dear Colleagues,

Head and neck cancer is often a highly malignant disease that is etiologically and genetically complex, and notoriously difficult to treat. Recent advances in our understanding of head and neck cancer biology have prompted us to compile this Special Issue. The research helping to uncover the unique properties of head and neck cancer has not only initiated the development of targeted therapies (therapies targeted at specific, upregulated signaling pathways and/or unique mutations frequently present in the particular cancer), such as EGFR-inhibitors and, to a certain extent, VEGF inhibitors, but has also helped to improve the efficacy of both classical chemotherapy protocols as well as radiotherapy. This Special Issue aims to gather manuscripts advancing our general knowledge of head and neck cancer biology, the development of novel therapies, as well as the communication on progress/improvement of classical therapies, including clinical trials.

Dr. Emilia Wiecheć
Guest Editor

Manuscript Submission Information

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Keywords

  • EGFR
  • VEGFR
  • RET
  • MET
  • PI3K
  • radiotherapy
  • chemotherapy
  • immunotherapy
  • HPV
  • preclinical HNSCC model
  • biomarkers of treatment response

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Published Papers (6 papers)

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Research

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22 pages, 7759 KiB  
Article
Machine Learning-Driven Identification of Exosome-Related Genes in Head and Neck Squamous Cell Carcinoma for Prognostic Evaluation and Drug Response Prediction
by Hua Cai, Liuqing Zhou, Yao Hu and Tao Zhou
Biomedicines 2025, 13(4), 780; https://doi.org/10.3390/biomedicines13040780 - 23 Mar 2025
Viewed by 448
Abstract
Background: This study integrated four Gene Expression Omnibus (GEO) datasets to identify disease-specific feature genes in head and neck squamous cell carcinoma (HNSCC) through differential expression analysis with batch effect correction. Methods: The GeneCards database was used to find genes related to [...] Read more.
Background: This study integrated four Gene Expression Omnibus (GEO) datasets to identify disease-specific feature genes in head and neck squamous cell carcinoma (HNSCC) through differential expression analysis with batch effect correction. Methods: The GeneCards database was used to find genes related to exosomes, and samples were categorized into groups with high and low expression levels based on these feature genes. Functional and pathway enrichment analyses (GO, KEGG, and GSEA) were used to investigate the possible biological mechanisms underlying feature genes. A predictive model was produced by using machine learning algorithms (LASSO regression, SVM, and random forest) to find disease-specific feature genes. Receiver operating characteristic (ROC) curve analysis was used to assess the model’s effectiveness. The diagnostic model showed excellent predictive accuracy through external data GSE83519 validation. Results: This analysis highlighted 22 genes with significant differential expression. A predictive model based on five important genes (AGRN, TSPAN6, MMP9, HBA1, and PFN2) was produced by using machine learning algorithms. MMP9 and TSPAN6 showed relatively high predictive performance. Using the ssGSEA algorithm, three key genes (MMP9, AGRN, and PFN2) were identified as strongly linked to immune regulation, immune response suppression, and critical signaling pathways involved in HNSCC progression. Matching HNSCC feature gene expression profiles with DSigDB compound signatures uncovered potential therapeutic targets. Molecular docking simulations identified ligands with high binding affinity and stability, notably C5 and Hoechst 33258, which were prioritized for further validation and potential drug development. Conclusions: This study employs a novel diagnostic model for HNSCC constructed using machine learning technology, which can provide support for the early diagnosis of HNSCC and thus contribute to improving patient treatment plans and clinical management strategies. Full article
(This article belongs to the Special Issue Novel Approaches towards Targeted Head and Neck Cancer Therapies)
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17 pages, 2243 KiB  
Article
Oxidative Stress Biomarkers in Laryngeal Squamous Cell Carcinoma and Their Clinical Implications: Preliminary Results
by Barbara Verro, Carmelo Saraniti, Diana Di Liberto, Giovanni Pratelli, Marianna Lauricella and Daniela Carlisi
Biomedicines 2025, 13(3), 667; https://doi.org/10.3390/biomedicines13030667 - 8 Mar 2025
Viewed by 623
Abstract
Background/Objectives: Laryngeal squamous cell carcinoma represents one of the most common head and neck cancers with a five-year survival rate that, despite diagnostic and therapeutic advances, has not shown any significant improvement in recent decades. Oxidative stress, generated by an imbalance between [...] Read more.
Background/Objectives: Laryngeal squamous cell carcinoma represents one of the most common head and neck cancers with a five-year survival rate that, despite diagnostic and therapeutic advances, has not shown any significant improvement in recent decades. Oxidative stress, generated by an imbalance between reactive oxygen species and cellular antioxidant systems, is considered a central mechanism in the carcinogenesis of laryngeal squamous cell carcinoma, causing DNA damage and genomic alterations. Methods: This prospective observational paired case–control study focused on the evaluation of antioxidant proteins, such as superoxide dismutase, catalase, heme-oxygenase 1, vimentin, metallothionein, and nuclear factor erythroid 2-related factor 2, in cancer tissues from fifteen patients with laryngeal squamous cell carcinoma, using adjacent healthy tissues as controls. Results: The results show a statistically significant overexpression of all proteins analyzed in cancer tissues compared to controls, with relevant correlations between specific biomarkers and clinical characteristics, age, sex, smoking habits, and degree of tumor differentiation. Conclusions: These preliminary studies, while limited by sample size and the complexity of molecular regulation, indicate that the overexpression of antioxidant enzymes in laryngeal squamous cell carcinoma tissues, along with their correlations with key clinical parameters, underscores a context-dependent role of oxidative stress in tumor progression. A deeper understanding of oxidative stress mechanisms could contribute to advance personalized management strategies for laryngeal squamous cell carcinoma, potentially improving treatment outcomes and patient prognosis. Full article
(This article belongs to the Special Issue Novel Approaches towards Targeted Head and Neck Cancer Therapies)
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24 pages, 27372 KiB  
Article
SAR1A Induces Cell Growth and Epithelial–Mesenchymal Transition Through the PI3K/AKT/mTOR Pathway in Head and Neck Squamous Cell Carcinoma: An In Vitro and In Vivo Study
by Shizhen Fang, Jie Wang, Tianyi Liu, Yang Jiang and Qingquan Hua
Biomedicines 2024, 12(11), 2477; https://doi.org/10.3390/biomedicines12112477 - 28 Oct 2024
Viewed by 1381
Abstract
Objectives: Head and neck squamous cell carcinoma (HNSCC) ranks sixth globally, with a 50% five-year survival rate. SAR1A exhibits high expression levels in various tumor types, yet its specific role in HNSCC remains to be clarified. Methods: In vitro assays, such as CCK8, [...] Read more.
Objectives: Head and neck squamous cell carcinoma (HNSCC) ranks sixth globally, with a 50% five-year survival rate. SAR1A exhibits high expression levels in various tumor types, yet its specific role in HNSCC remains to be clarified. Methods: In vitro assays, such as CCK8, EdU, colony formation, wound-healing, transwell, and Western blotting analyses, as well as in vivo assays, such as tumor xenografts and lung metastasis models, were conducted to evaluate the impacts of SAR1A on HNSCC proliferation, migration, and invasion. Transcriptome sequencing and KEGG enrichment pathway analysis revealed evident alterations in the PI3K/AKT/mTOR(PAM) pathways. LY294002 (a PI3K/AKT inhibitor) was used to investigate the role of the PAM pathway in proliferation, migration, and invasion in HNSCC. Results: Univariate and multivariate Cox regression were conducted to screen SAR1A as a gene prognostic biomarker in HNSCC, and it was validated in the Cancer Genome Atlas (TCGA) database. Functional assays demonstrated that the depletion of SAR1A leads to suppressed proliferation, migration, and invasion of HNSCC cells. This is accompanied by a decrease in the expression of epithelial–mesenchymal transition (EMT)-related markers in HNSCC cell lines. In addition, the diminished capacities of proliferation, migration, and invasion observed in SAR1A knockdown cells were reversed upon the overexpression of SAR1A. Furthermore, RNA-seq and KEGG enrichment analysis demonstrated a significant alteration in the PAM pathway following SAR1A knockdown. LY294002 effectively mitigated the increased proliferation, migration, and invasion induced by SAR1A overexpression. Conclusions: SAR1A facilitates HNSCC proliferation and EMT via the PI3K/AKT/mTOR pathway. Full article
(This article belongs to the Special Issue Novel Approaches towards Targeted Head and Neck Cancer Therapies)
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14 pages, 1466 KiB  
Article
The Impact of Clinical Prognosis of Viral Hepatitis in Head and Neck Cancer Patients Receiving Concurrent Chemoradiotherapy
by Yu-Ming Wang, Sheng-Dean Luo, Ching-Nung Wu, Shao-Chun Wu, Wei-Chih Chen, Yao-Hsu Yang and Tai-Jan Chiu
Biomedicines 2023, 11(11), 2946; https://doi.org/10.3390/biomedicines11112946 - 1 Nov 2023
Viewed by 1573
Abstract
This study evaluated the clinical characteristics of head and neck cancer (HNC) patients with hepatitis B (HBV) or hepatitis C (HCV) who underwent concurrent chemoradiotherapy (CCRT) and examined the prognostic impact of antiviral therapies. In a 19-year retrospective analysis of 8224 HNC patients [...] Read more.
This study evaluated the clinical characteristics of head and neck cancer (HNC) patients with hepatitis B (HBV) or hepatitis C (HCV) who underwent concurrent chemoradiotherapy (CCRT) and examined the prognostic impact of antiviral therapies. In a 19-year retrospective analysis of 8224 HNC patients treated with CCRT, 29.8% (2452) were diagnosed with HBV or HCV, of whom 714 received antiviral therapy. For non-metastatic HNC patients on CCRT, factors such as gender, Charlson Comorbidity Index (CCI), liver cirrhosis markers (Fibrosis-4, APRI), and initial tumor stage were significant determinants of their overall survival. However, the presence of HBV or HCV and the administration of antiviral treatments did not yield distinct survival outcomes. In summary, antiviral therapy for HBV or HCV did not affect the 5-year survival rates of non-metastatic HNC patients undergoing CCRT, while gender, tumor stage, CCI, and liver cirrhosis were notable prognostic indicators. Full article
(This article belongs to the Special Issue Novel Approaches towards Targeted Head and Neck Cancer Therapies)
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Review

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25 pages, 3082 KiB  
Review
Advancing Head and Neck Cancer Therapies: From Conventional Treatments to Emerging Strategies
by Aleksandra Mordzińska-Rak, Ilona Telejko, Grzegorz Adamczuk, Tomasz Trombik, Andrzej Stepulak and Ewa Błaszczak
Biomedicines 2025, 13(5), 1046; https://doi.org/10.3390/biomedicines13051046 - 25 Apr 2025
Viewed by 363
Abstract
Head and neck cancers (HNCs), particularly head and neck squamous cell carcinoma (HNSCC), are among the most aggressive and prevalent malignancies of the upper aerodigestive tract. As the incidence of HNCs continues to rise, this cancer type presents a significant public health challenge. [...] Read more.
Head and neck cancers (HNCs), particularly head and neck squamous cell carcinoma (HNSCC), are among the most aggressive and prevalent malignancies of the upper aerodigestive tract. As the incidence of HNCs continues to rise, this cancer type presents a significant public health challenge. Despite conventional treatment options, such as surgery, chemotherapy, and radiotherapy, the five-year survival rates remain relatively low due to resistance to these therapies, local recurrence, local lymph node metastasis, and in some advanced cases also distant metastasis. Consequently, patients with HNCs face a high mortality risk and have reduced quality of life due to the side effects of chemo- and radiotherapy. Furthermore, targeted therapies and immunotherapies have also shown limited effectiveness in many cases, with issues related to resistance and the accessibility of these treatments. Therefore, new strategies, such as those based on combination therapies and nanotechnology, are being explored to improve the treatment of HNC patients. The proteolysis-targeting chimeras (PROTACs) also emerged as a promising therapeutic approach, though research is still ongoing to bring this technology into clinical practice. Here, we aim to highlight the current knowledge of HNC therapies, with a focus on recent advancements, including nanomedicine and PROTAC-based strategies. The development and advancement of novel emerging therapies hold promise for the improvement of patients’ survival and quality of life. Full article
(This article belongs to the Special Issue Novel Approaches towards Targeted Head and Neck Cancer Therapies)
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22 pages, 2354 KiB  
Review
Advancements in Hyperspectral Imaging and Computer-Aided Diagnostic Methods for the Enhanced Detection and Diagnosis of Head and Neck Cancer
by I-Chen Wu, Yen-Chun Chen, Riya Karmakar, Arvind Mukundan, Gahiga Gabriel, Chih-Chiang Wang and Hsiang-Chen Wang
Biomedicines 2024, 12(10), 2315; https://doi.org/10.3390/biomedicines12102315 - 11 Oct 2024
Cited by 3 | Viewed by 2500
Abstract
Background/Objectives: Head and neck cancer (HNC), predominantly squamous cell carcinoma (SCC), presents a significant global health burden. Conventional diagnostic approaches often face challenges in terms of achieving early detection and accurate diagnosis. This review examines recent advancements in hyperspectral imaging (HSI), integrated with [...] Read more.
Background/Objectives: Head and neck cancer (HNC), predominantly squamous cell carcinoma (SCC), presents a significant global health burden. Conventional diagnostic approaches often face challenges in terms of achieving early detection and accurate diagnosis. This review examines recent advancements in hyperspectral imaging (HSI), integrated with computer-aided diagnostic (CAD) techniques, to enhance HNC detection and diagnosis. Methods: A systematic review of seven rigorously selected studies was performed. We focused on CAD algorithms, such as convolutional neural networks (CNNs), support vector machines (SVMs), and linear discriminant analysis (LDA). These are applicable to the hyperspectral imaging of HNC tissues. Results: The meta-analysis findings indicate that LDA surpasses other algorithms, achieving an accuracy of 92%, sensitivity of 91%, and specificity of 93%. CNNs exhibit moderate performance, with an accuracy of 82%, sensitivity of 77%, and specificity of 86%. SVMs demonstrate the lowest performance, with an accuracy of 76% and sensitivity of 48%, but maintain a high specificity level at 89%. Additionally, in vivo studies demonstrate superior performance when compared to ex vivo studies, reporting higher accuracy (81%), sensitivity (83%), and specificity (79%). Conclusion: Despite these promising findings, challenges persist, such as HSI’s sensitivity to external conditions, the need for high-resolution and high-speed imaging, and the lack of comprehensive spectral databases. Future research should emphasize dimensionality reduction techniques, the integration of multiple machine learning models, and the development of extensive spectral libraries to enhance HSI’s clinical utility in HNC diagnostics. This review underscores the transformative potential of HSI and CAD techniques in revolutionizing HNC diagnostics, facilitating more accurate and earlier detection, and improving patient outcomes. Full article
(This article belongs to the Special Issue Novel Approaches towards Targeted Head and Neck Cancer Therapies)
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