Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
9.0
4.8
Journals
Cancers
Special Issues
Clinical and Translational Research in Head and Neck Cancer—2nd Edition
cancers-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Cancers Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Clinical and Translational Research in Head and Neck Cancer—2nd Edition

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Clinical Research of Cancer".

Deadline for manuscript submissions: 15 December 2026 | Viewed by 1144

Editor

Dr. Young J. Kim

E-Mail Website
Guest Editor
Chair Oncology, Global Development Scientific Council, Regeneron Pharmaceuticals, New York, NY, USA
Interests: cancer immunology; tumor microenvironment; immune oncology

Special Issue Information

Dear Colleagues,

This Special Issue is the second edition of a previous Special Issue entitled “Clinical and Translational Research in Head and Neck Cancer”.

Head and neck cancer encompasses multiple histologic tumors that can represent the breadth of most human cancers, and these cancers’ unique occurrences in the face/scalp and the upper digestive tracts, including the sinonasal tracts, oral cavity, oropharynx, larynx, and cervical esophagus, provide unique challenges for scientists and clinicians. Although there are now new approved drugs for many of these tumor types, there are still important clinical concerns for weighing up oncologic cures and functional preservation. Hence, the incorporation of new modalities, such as immunotherapy and targeted biologics, will require basic, clinical, and translational research for optimal patient care that incorporates locoregional recurrence, overall survival, and quality of life maintenance. This Special Issue presents some of these recent advances in oncologic therapeutics in head and neck cancer patients to promote future translational and clinical studies.

Dr. Young J. Kim
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 communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly 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 2900 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

  • head and neck cancer
  • immunotherapy
  • translation
  • combinatorial clinical trials
  • oncologic therapeutics

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

22 pages, 1961 KB  
Article
Multimodal Fusion of Intraoperative FLIm and Preoperative PET/CT for Patient-Level Prediction of Lymph Node Metastasis in Head and Neck Cancer
by Lei Zhou, Nimu Yuan, Mohamed A. Hassan, Lisanne Kraft, Katjana Ehrlich, Brent W. Weyers, Vladimir Ivanovic, Osama A. A. Raslan, Dorina Gui, Marianne Abouyared, Arnaud F. Bewley, Andrew C. Birkeland, Donald Gregory Farwell, Laura Marcu and Jinyi Qi
Cancers 2026, 18(13), 2154; https://doi.org/10.3390/cancers18132154 (registering DOI) - 4 Jul 2026
Abstract
Background: Metastatic lymph node (MLN) detection remains a major clinical challenge in head and neck cancer, as nodal involvement is strongly associated with poor prognosis and directly affects treatment planning. Previous approaches typically rely on cropped lymph node (LN) regions or tumor contours [...] Read more.
Background: Metastatic lymph node (MLN) detection remains a major clinical challenge in head and neck cancer, as nodal involvement is strongly associated with poor prognosis and directly affects treatment planning. Previous approaches typically rely on cropped lymph node (LN) regions or tumor contours for MLN identification, requiring substantial expert annotation during preprocessing and relying solely on imaging information. As a result, small or low-contrast metastatic nodes may be missed, while benign lymph nodes may be incorrectly identified as metastatic due to overlapping imaging characteristics. To address these limitations, we propose a multimodal learning framework that integrates anatomical and metabolic features from head and neck PET/CT images with biochemical features derived from FLIm for patient-level MLN prediction, without requiring manual lymph node cropping or tumor contouring during inference. Methods: To enable robust imaging representation learning, a region-aware PET/CT network based on a merging-diverging architecture was first pretrained on the HECKTOR 2022 dataset and then fine-tuned on the institutional cohort. In parallel, FLIm point-wise measurements with clinical variables were encoded using a multilayer perceptron (MLP) and aggregated into subject-level representations. To effectively combine these modalities, two multimodal fusion strategies were evaluated at the decoder stage, including cube-based fusion and squeeze-and-excitation (SE)-based fusion. The proposed strategies were evaluated on a cohort of 53 patients. Results: Compared with the single-modality baselines, both multimodal fusion strategies achieved better patient-level MLN prediction. The PET/CT-only segmentation-driven model and FLIm-only model reached balanced accuracies of 0.815 and 0.665, with AUCs of 0.828 and 0.614, respectively. Cube-based fusion improved balanced accuracy and AUC to 0.827 and 0.850, respectively, while channel-wise SE-based fusion achieved the best overall performance, with a balanced accuracy of 0.839 and an AUC of 0.872. Conclusions: These results suggest that multimodal integration may improve patient-level MLN prediction compared with single-modality approaches. Given the limited sample size, these findings should be interpreted as hypothesis-generating and require validation in larger, independent patient cohorts. Full article
(This article belongs to the Special Issue Clinical and Translational Research in Head and Neck Cancer—2nd Edition)
►▼ Show Figures

Figure 1

13 pages, 554 KB  
Article
Post-Radiation PET Shows Higher Diagnostic Accuracy in HPV-Negative Head and Neck Cancers
by Kornél Dános, Angéla Horváth, Emese Kristóf, Imre Uri, Benedek Besenczi, Peter Prekopp, László Tamás, Gábor Polony and Tamás Györke
Cancers 2026, 18(8), 1237; https://doi.org/10.3390/cancers18081237 - 14 Apr 2026
Viewed by 755
Abstract
Background: Post-treatment evaluation of residual neck disease in head and neck squamous cell carcinoma (HNSCC) is challenging because of treatment-related changes and biological differences between HPV-positive and HPV-negative tumors. Methods: We performed a prospective single-center study of 58 node-positive HNSCC patients treated with [...] Read more.
Background: Post-treatment evaluation of residual neck disease in head and neck squamous cell carcinoma (HNSCC) is challenging because of treatment-related changes and biological differences between HPV-positive and HPV-negative tumors. Methods: We performed a prospective single-center study of 58 node-positive HNSCC patients treated with definitive chemoradiotherapy (CRT) followed by 18F-FDG PET/CT. PET-positive patients underwent neck dissection, while PET-negative patients were followed clinically for at least two years. Diagnostic performance was analyzed by p16 status. Results: PET/CT showed high overall accuracy (sensitivity 94%, specificity 83%, PPV 70%, NPV 97%). In p16-negative cases, sensitivity was 93%, specificity 80%, PPV 81%, and NPV 92%. In p16-positive cases, sensitivity and NPV reached 100%, but PPV was only 43%, indicating frequent false positives. Residual disease requiring neck dissection was associated with significantly worse survival (p = 0.008). Conclusions: PET/CT is reliable for post-treatment assessment, especially in p16-negative HNSCC. In p16-positive cases, careful interpretation and standardized PET/CT criteria are needed to reduce false positives and avoid unnecessary surgery. Full article
(This article belongs to the Special Issue Clinical and Translational Research in Head and Neck Cancer—2nd Edition)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop