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Biomolecules
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Biomolecules and Biomarkers in Head and Neck Medicine (Volume II)
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Biomolecules and Biomarkers in Head and Neck Medicine (Volume II)

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Molecular Biomarkers".

Deadline for manuscript submissions: closed (15 December 2023) | Viewed by 4070

Special Issue Editor

Dr. Antonio Celentano

E-Mail Website
Guest Editor
Melbourne Dental School, The University of Melbourne, Carlton, VIC 3053, Australia
Interests: early detection of cancer; mouth neoplasms; prognosis; biomarkers; cancer progression; leukoplakia; neoplastic cell transformation; oral diseases
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following a successful first run, we are pleased to announce the launch of a new edition of the Special Issue on Biomolecules and Biomarkers in Head and Neck Medicine.

In each of these fields, in the last few years, a range of new biomolecules and biomarkers associated with disease have been discovered and pursued, and a multitude of robust innovative diagnostic assays have been established. Biodiagnostics is, therefore, a rapidly evolving field; however, many questions and problems remain unresolved. The aim of this Special Issue is to highlight the biological functions, activities, and interactions of biomolecules within the head and neck region and to focus on the diagnostics of a plethora of head and neck pathologies using biomarkers in blood, saliva, and from tissue. These diseases include head and neck cancers, oral mucosal diseases, salivary gland diseases, infectious diseases, autoimmune and immune-mediated disorders, and orofacial pain, among others. We welcome your contribution to this Special Issue and look forward to working with you to advance knowledge and collaboration in the broad area of head and neck medicine. Your contribution is very welcome!

Dr. Antonio Celentano
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biomarkers
  • biomolecules
  • head and neck
  • pathology
  • medicine
  • diagnosis
  • prognosis

Related Special Issue

Published Papers (3 papers)

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Research

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10 pages, 1652 KiB  
Article
Applying Machine Learning for Enhanced MicroRNA Analysis: A Companion Risk Tool for Oral Squamous Cell Carcinoma in Standard Care Incisional Biopsy
by Neha Pruthi, Tami Yap, Caroline Moore, Nicola Cirillo and Michael J. McCullough
Biomolecules 2024, 14(4), 458; https://doi.org/10.3390/biom14040458 - 09 Apr 2024
Viewed by 441
Abstract
Machine learning analyses within the realm of oral cancer outcomes are relatively underexplored compared to other cancer types. This study aimed to assess the performance of machine learning algorithms in identifying oral cancer patients, utilizing microRNA expression data. In this study, we implemented [...] Read more.
Machine learning analyses within the realm of oral cancer outcomes are relatively underexplored compared to other cancer types. This study aimed to assess the performance of machine learning algorithms in identifying oral cancer patients, utilizing microRNA expression data. In this study, we implemented this approach using a panel of oral cancer-associated microRNAs sourced from standard incisional biopsy specimens to identify cases of oral squamous cell carcinomas (OSCC). For the model development process, we used a dataset comprising 30 OSCC and 30 histologically normal epithelium (HNE) cases. We initially trained a logistic regression prediction model using 70 percent of the dataset, while reserving the remaining 30 percent for testing. Subsequently, the model underwent hyperparameter tuning resulting in enhanced performance metrics. The hyperparameter-tuned model exhibited high accuracy (0.894) and ROC AUC (0.898) in predicting OSCC. Testing the model on cases of potentially malignant disorders (OPMDs) revealed that leukoplakia with mild dysplasia was predicted as having a high risk of progressing to OSCC, emphasizing machine learning’s advantage over histopathology in detecting early molecular changes. These findings underscore the necessity for further refinement, incorporating a broader set of variables to enhance the model’s predictive capabilities in assessing the risk of oral potentially malignant disorders. Full article
(This article belongs to the Special Issue Biomolecules and Biomarkers in Head and Neck Medicine (Volume II))
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24 pages, 6888 KiB  
Article
Assessment of Oxidative Stress-Induced Oral Epithelial Toxicity
by Ali I. Mohammed, Simran Sangha, Huynh Nguyen, Dong Ha Shin, Michelle Pan, Hayoung Park, Michael J. McCullough, Antonio Celentano and Nicola Cirillo
Biomolecules 2023, 13(8), 1239; https://doi.org/10.3390/biom13081239 - 11 Aug 2023
Cited by 1 | Viewed by 1468
Abstract
Reactive oxygen species (ROS) are highly reactive molecules generated in living organisms and an excessive production of ROS culminates in oxidative stress and cellular damage. Notably, oxidative stress plays a critical role in the pathogenesis of a number of oral mucosal diseases, including [...] Read more.
Reactive oxygen species (ROS) are highly reactive molecules generated in living organisms and an excessive production of ROS culminates in oxidative stress and cellular damage. Notably, oxidative stress plays a critical role in the pathogenesis of a number of oral mucosal diseases, including oral mucositis, which remains one of cancer treatments’ most common side effects. We have shown previously that oral keratinocytes are remarkably sensitive to oxidative stress, and this may hinder the development and reproducibility of epithelial cell-based models of oral disease. Here, we examined the oxidative stress signatures that parallel oral toxicity by reproducing the initial events taking place during cancer treatment-induced oral mucositis. We used three oral epithelial cell lines (an immortalized normal human oral keratinocyte cell line, OKF6, and malignant oral keratinocytes, H357 and H400), as well as a mouse model of mucositis. The cells were subjected to increasing oxidative stress by incubation with hydrogen peroxide (H2O2) at concentrations of 100 μM up to 1200 μM, for up to 24 h, and ROS production and real-time kinetics of oxidative stress were investigated using fluorescent dye-based probes. Cell viability was assessed using a trypan blue exclusion assay, a fluorescence-based live–dead assay, and a fluorometric cytotoxicity assay (FCA), while morphological changes were analyzed by means of a phase-contrast inverted microscope. Static and dynamic real-time detection of the redox changes in keratinocytes showed a time-dependent increase of ROS production during oxidative stress-induced epithelial injury. The survival rates of oral epithelial cells were significantly affected after exposure to oxidative stress in a dose- and cell line-dependent manner. Values of TC50 of 800 μM, 800 μM, and 400 μM were reported for H400 cells (54.21 ± 9.04, p < 0.01), H357 cells (53.48 ± 4.01, p < 0.01), and OKF6 cells (48.64 ± 3.09, p < 0.01), respectively. Oxidative stress markers (MPO and MDA) were also significantly increased in oral tissues in our dual mouse model of chemotherapy-induced mucositis. In summary, we characterized and validated an oxidative stress model in human oral keratinocytes and identified optimal experimental conditions for the study of oxidative stress-induced oral epithelial toxicity. Full article
(This article belongs to the Special Issue Biomolecules and Biomarkers in Head and Neck Medicine (Volume II))
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Other

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20 pages, 1303 KiB  
Systematic Review
In Vitro Cytotoxicity of Antiresorptive and Antiangiogenic Compounds on Oral Tissues Contributing to MRONJ: Systematic Review
by Robert H. Guirguis, Leonard P. Tan, Rebecca M. Hicks, Aniqa Hasan, Tina D. Duong, Xia Hu, Jordan Y. S. Hng, Mohammad H. Hadi, Henry C. Owuama, Tamara Matthyssen, Michael McCullough, Federica Canfora, Rita Paolini and Antonio Celentano
Biomolecules 2023, 13(6), 973; https://doi.org/10.3390/biom13060973 - 10 Jun 2023
Cited by 3 | Viewed by 1711
Abstract
Background: Invasive dental treatment in patients exposed to antiresorptive and antiangiogenic drugs can cause medication-related osteonecrosis of the jaw (MRONJ). Currently, the exact pathogenesis of this disease is unclear. Methods: In March 2022, Medline (Ovid), Embase (Ovid), Scopus, and Web of Science were [...] Read more.
Background: Invasive dental treatment in patients exposed to antiresorptive and antiangiogenic drugs can cause medication-related osteonecrosis of the jaw (MRONJ). Currently, the exact pathogenesis of this disease is unclear. Methods: In March 2022, Medline (Ovid), Embase (Ovid), Scopus, and Web of Science were screened to identify eligible in vitro studies investigating the effects of antiresorptive and antiangiogenic compounds on orally derived cells. Results: Fifty-nine articles met the inclusion criteria. Bisphosphonates were used in 57 studies, denosumab in two, and sunitinib and bevacizumab in one. Zoledronate was the most commonly used nitrogen-containing bisphosphonate. The only non-nitrogen-containing bisphosphonate studied was clodronate. The most frequently tested tissues were gingival fibroblasts, oral keratinocytes, and alveolar osteoblasts. These drugs caused a decrease in cell proliferation, viability, and migration. Conclusions: Antiresorptive and antiangiogenic drugs displayed cytotoxic effects in a dose and time-dependent manner. Additional research is required to further elucidate the pathways of MRONJ. Full article
(This article belongs to the Special Issue Biomolecules and Biomarkers in Head and Neck Medicine (Volume II))
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